2016-2017
INTERAGENCY AUTISM COORDINATING COMMITTEE
strategic plan
for autism spectrum disorder
2016-2017
INTERAGENCY AUTISM COORDINATING COMMITTEE
strategic plan
for autism spectrum disorder
II
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
COVER DESIGN
Medical Arts Branch, Office of Research Services, National Institutes of Health
COPYRIGHT INFORMATION
All material appearing in this report is in the public domain and may be reproduced or copied.
A suggested citation follows.
SUGGESTED CITATION
Interagency Autism Coordinating Committee (IACC). 2016-2017 Interagency Autism Coordinating Committee Strategic Plan
For Autism Spectrum Disorder. October 2017. Retrieved from the U.S. Department of Health and Human Services Interagency
Autism Coordinating Committee website: https://iacc.hhs.gov/publications/strategic-plan/2017/.
III
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
TABLE OF CONTENTS
About the IACC................................................................................................................................................................................................... IV
Introduction ...........................................................................................................................................................................................................V
Overview of Progress on Strategic Plan Objectives ................................................................................................................................. IX
2016-2017 Strategic Plan Objectives ........................................................................................................................................................... XII
Question 1: How Can I Recognize the Signs of ASD, and Why is Early Detection So Important? ............................................. XIV
Question 2: What is the Biology Underlying ASD? ................................................................................................................................... 12
Question 3: What Causes ASD, and Can Disabling Aspects of ASD be Prevented or Preempted? ............................................28
Question 4: Which Treatments and Interventions Will Help? .............................................................................................................. 44
Question 5: What Kinds of Services and Supports are Needed to Maximize Quality of Life
for People on the Autism Spectrum? .................................................................................................................................................................... 62
Question 6: How Can We Meet the Needs of People with ASD as
They Progress into and through Adulthood? ...............................................................................................................................................72
Question 7: How Do We Continue to Build, Expand, and Enhance the Infrastructure System
to Meet the Needs of the ASD Community? ..........................................................................................................................................................86
Budget Recommendation .............................................................................................................................................................................. 100
Statement on Duplication of Effort ............................................................................................................................................................. 104
Conclusion ........................................................................................................................................................................................................ 106
Interagency Autism Coordinating Committee Member Roster ........................................................................................................... 163
Strategic Plan Working Group Members ...................................................................................................................................................167
Office of Autism Research Coordination Staff List ................................................................................................................................. 180
IV
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
ABOUT THE IACC
The Interagency Autism Coordinating Committee (IACC) is a Federal advisory committee charged with coordinating
Federal activities concerning autism spectrum disorder (ASD) and providing advice to the Secretary of Health and Human
Services (HHS) on issues related to autism. The Committee was established by Congress under the Children's Health Act
of 2000, reconstituted under the Combating Autism Act (CAA) of 2006, and renewed most recently under the Autism
Collaboration, Accountability, Research, Education, and Support (CARES) Act of 2014.
Membership of the Committee includes a wide array of Federal agencies involved in ASD research and services, as well as
public stakeholders, including self-advocates, family members of children and adults with ASD, advocates, service providers,
and researchers, who represent a variety of perspectives from within the autism community. The IACC membership is
composed to ensure that the Committee is equipped to address the wide range of issues and challenges faced by individuals
and families affected by autism.
Under the CAA and subsequent authorizations, the IACC is required to (1) develop and annually update a strategic plan
for ASD research, (2) develop and annually update a summary of advances in ASD research, and (3) monitor Federal
activities related to ASD.
Through these and other activities, the IACC provides guidance to HHS and partners with other Federal departments,
Federal agencies, research and advocacy organizations, and the broader autism community to accelerate research and
enhance services with the goal of profoundly improving the lives of people with ASD and their families.
For more information about the IACC, see http://www.iacc.hhs.gov.
V
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
INTRODUCTION
The Interagency Autism Coordinating Committee (IACC)
is a Federal advisory committee that advises the Secretary
of Health and Human Services on issues related to
autism spectrum disorder (ASD). It was established
by the Children’s Health Act of 2000 (Public Law 106-310),
reconstituted under the Combating Autism Act of 2006
(CAA; Public Law 109-416), and was most recently renewed
in 2014 under the Autism Collaboration, Accountability,
Research, Education, and Support Act (Autism CARES Act;
Public Law 113-157). One of the statutory responsibilities
of the IACC under the CAA and subsequent authorizations
is the development of a strategic plan for ASD, to be updated
annually. The IACC Strategic Plan, first issued in 2009, was
developed by the IACC – including Federal officials and
public stakeholder members – and each edition has been
informed by extensive input from researchers, adults on
the autism spectrum, parents, advocates, and the general
public. This inclusive process has ensured that the IACC
Strategic Plan reflects diverse perspectives from across the
autism community. The Autism CARES Act requires that the
IACC include in the Strategic Plan information concerning,
“as practicable…services and supports, for individuals with
an autism spectrum disorder and the families of such
individuals,” along with information about ASD research.
In this edition, which includes an entirely new set of
strategic objectives, the IACC Strategic Plan for Autism
Spectrum Disorder addresses this new requirement by
taking a more comprehensive approach that not only
addresses autism research, but also incorporates more
information about gaps, opportunities, and implications
related to autism services, supports, and policies.
This 2016-2017 revision of the IACC Strategic Plan is the
work of the IACC membership appointed under the CARES
Act. The CARES Act increased the required number of public
members on the Committee, which includes at least two
members on the autism spectrum, at least two parents or
legal guardians of individuals with autism, and at least two
advocacy, services, or research organization representatives.
Several of the members have dual roles as professionals in
fields related to ASD as well as having personal experience
with ASD. The slate of new and returning IACC members
was announced in October 2015 and embodies a wide
variety of views, perspectives, and expertise.
As in previous years, the IACC Strategic Plan is
organized around seven general topic areas that are
represented in the Plan as community-focused questions
(e.g., Question 1, “How can I recognize the signs of ASD,
and why is early detection so important?,” which covers
the topic of screening and diagnosis). Each question is
assigned a chapter in the Strategic Plan that provides an
Aspirational Goal, or long-term vision for the question, and
includes: a description of the state of the field; the needs
and opportunities in research, services, and policy; and
three to four broad objectives for each question topic.
There is also one cross-cutting objective on the topic of
ASD in females.
For the 2016-2017 IACC Strategic Plan, the Committee
agreed that given the recent advances in the autism field,
it was an appropriate time to re-evaluate the autism
landscape and formulate new objectives for each question.
With access to an extensive portfolio analysis conducted
by the National Institutes of Health (NIH) Office of
Autism Research Coordination (OARC), as well as the
annual IACC Summary of Advances documents from past
years, the IACC reviewed what has been invested in ASD
research in the United States since 2008. The 23 new
objectives in this Plan were created by the Committee to
VI
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
address critical gaps and potential advances they perceived
in the current research landscape. Because the objectives
have been updated and broadened from the previous
Strategic Plan’s 78 research objectives, the IACC expects
that multiple funder portfolios will play key roles in
addressing different aspects of each objective in this Plan.
Furthermore, in light of the wide range of needs in autism
research and services, the IACC recommends doubling
the 2015 overall autism research budget level of $343
million to $685 million by the year 2020. Although this
funding would not be sufficient to accomplish all of the
objectives described in this Plan, it would represent an
aggressive step toward progress.
In formulating this new Plan for ASD activities, the IACC
has moved toward a paradigm shift in how we approach
autism. A few years ago, scientists saw autism as a disorder
to be detected, treated, prevented, and cured. The majority
of research was directed at understanding the genetic and
biological foundations of autism, and toward early detection
and intervention. Today, our understanding of autism is
more nuanced. We realize that there are many different
“autisms” – some severe, and some comparatively mild – and
that ASD affects several distinct domains of functioning
differently in each individual. We have come to understand
that autism is far more common than previously suspected
and there are most likely many undiagnosed children,
adolescents, and adults in the population, as well as
under-identified and underserved individuals and groups,
such as girls/women with ASD, people in poorly resourced
settings, members of underserved minority communities,
and individuals on the autism spectrum with language
and/or intellectual disabilities. Most importantly, individuals
on the autism spectrum have become leading voices in
the conversation about autism, spurring acknowledgment
of the unique qualities that people on the autism
spectrum contribute to society and promoting self-direction,
awareness, acceptance, and inclusion as important
societal goals.
Research on genetic risk and the underlying basic biology
of ASD remains a primary focus of the research portfolio
and does play an important long-term role in the potential
to develop new and broadly beneficial therapies and
interventions. These advances may one day mitigate or
even eliminate some of the most disabling aspects of
autism, especially for those on the spectrum who are most
severely impacted. However, balanced with the potential
for long-term efforts to lead to significant future advances
and opportunities is the importance of efforts that can
have a more immediate impact. Individuals on the autism
spectrum today will remain autistic for the foreseeable
future; most of them have significant unmet needs.
To help those people – who range in age from infants to
senior citizens – we must in the short-term translate
existing research to develop effective tools and strategies
to maximize quality of life, and minimize disability, while
also ensuring that individuals on the autism spectrum
are accepted, included, and integrated in all aspects of
community life.
The community has been very clear in its calls for more
research into adult issues and better services and supports
for the millions of Americans living with autism today.
Recent studies of adult mortality have indicated that
people with ASD are at higher risk of premature death than
people in the general population, painting a very
disturbing picture that bears investigation. In light of data
and insights from the community, the IACC proposes a
comprehensive research agenda that addresses the needs
of autistic people across the spectrum and across the
lifespan, including improvements to services, supports,
and policies. The IACC also believes that, as many in
the autism community have indicated, efforts to address
the many co-occurring conditions that accompany autism
should be made a greater priority.
Though this 2016-2017 IACC Strategic Plan for Autism
Spectrum Disorder cannot possibly capture all the changes
in the ASD field since 2008, the IACC has endeavored to
deliver an updated picture of the evolving landscape of
VII
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
autism, as well as a new, broad vision of the current and
future challenges and opportunities in autism research,
services, and policy. To provide a more complete and detailed
view of autism research progress, this update accompanies
two other annual IACC publications. The IACC Autism
Spectrum Disorder Research Portfolio Analysis Report describes
Federal and non-Federal investments in autism research.
The annual IACC Summary of Advances in ASD Research
describes specific scientific findings that members of the
IACC identify as having significantly advanced the field
and as having the potential to impact public health and
quality of life in the ASD community. Together, with this
2016-2017 IACC Strategic Plan for ASD, the Committee
hopes that these documents will provide an insightful
overview of the state of autism in 2017, as well as outline
a strategic agenda for future progress.
VISION STATEMENT
The IACC Strategic Plan for ASD will accelerate and inspire research, and enhance service provision and access,
that will profoundly improve the health and quality of life of every person on the autism spectrum across the
lifespan. The Plan will provide a blueprint for ASD research and services efforts, engaging the participation and
input of government agencies, private organizations, and the broader autism community.
MISSION STATEMENT
The purpose of the Strategic Plan is to focus, coordinate, and accelerate innovative research and foster
development of high-quality services in partnership with stakeholders to address the urgent questions and
needs of people on the autism spectrum and their families.
CORE VALUES
The IACC adopted the below core values and emphasized their significance to the 2016-2017 Strategic Plan
development and implementation:
Sense of Urgency: We will focus on responding rapidly and efficiently to the needs and challenges of people on
the autism spectrum and their families.
Excellence: We will pursue innovative scientific research of the highest quality and development and dissemination
of evidence-based services and practices to maximize the quality of life for people on the autism spectrum.
Spirit of Collaboration: We will treat others with respect, listen with open minds to the diverse views of people on
the autism spectrum and their families, thoughtfully consider community input, and foster discussions where
participants can comfortably offer opposing opinions.
Community Focus: We will focus on making a difference in the lives of people affected by ASD, including people
with ASD, their families, medical practitioners, educators, and scientists. It is important to consider the impact of
research on the quality of life, human rights, and dignity of people with ASD, from prenatal development forward.
VIII
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Partnerships in Action: We will value cross-disciplinary approaches, data sharing, teamwork, and partnerships to
advance ASD research and service activities.
Equity: We will prioritize improved access to detection, intervention, and other services and supports for
individuals with ASD, and commit to the goal of reducing disparities across the lifespan, spectrum of ability
and disability, sex and gender, racial and cultural boundaries, socioeconomic status, and geographic location
to improve the health and quality of life of all individuals with ASD.
Please note: The terms “person with autism,” “person with ASD,” “autistic person,” and “person on the autism
spectrum” are used interchangeably throughout this document. Some members of the autism community prefer one term,
while others prefer another. The Committee respects the different opinions within the community on the use of this
language and does not intend to endorse any particular preference. In addition, the terms “autism” and “autism spectrum
disorder (ASD)” are used interchangeably throughout this document unless otherwise noted.
IX
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OVERVIEW OF PROGRESS ON STRATEGIC
PLAN OBJECTIVES
The Interagency Autism Coordinating Committee (IACC)
launched its first Strategic Plan for Autism Spectrum Disorder
Research in 2009, providing a framework to guide the autism
research efforts of Federal and private funders. The IACC
Strategic Plan organizes research priorities around seven
general topic areas represented as community-focused
“questions.” The questions are divided further into research
objectives that address key research needs, gaps, and
opportunities identified by the Committee. Prior to the
2016-2017 IACC Strategic Plan, the most recent update
to the IACC Strategic Plan’s objectives occurred in 2011,
leading to a total of 78 objectives for autism research.
The 2014-2015 IACC ASD Research Portfolio Analysis
Report provides the most recent progress on the previous
IACC Strategic Plan objectives. In 2015, significant progress
was made toward completing the objectives in the
2011 Strategic Plan, with 97% (76 objectives) of the 78
objectives either partially or fully completed – meaning
objectives had all or some of the required funded projects.
Considering the period from 2008-2015, only 3%
(2 objectives) of the 2011 Strategic Plan objectives were
not active at any point across this eight-year window.
This indicates that the vast majority of priority areas
identified by the IACC were deemed by Federal and private
research funders to be worthy of investment and were
implemented either partially or fully. However, many
areas of partial funding in autism research initiatives left
significant gaps over this period.
In 2015, ASD research funding supported projects relevant
to all seven questions in the IACC Strategic Plan for ASD
Research. However, some questions received greater
proportions of funding than others due to the activities of
the funders included in the analysis. As in previous years,
Question 2 (Biology) received the largest portion of funding
(32%) in 2015, encompassing projects supported by nine
funders. Research in this field focuses on identifying the
biological differences and mechanisms in early development
and throughout life that contribute to ASD, as well as the
characterization of the behavioral and cognitive aspects
of ASD. Projects ranged from basic neuroscience using
cellular and animal models to clinical studies. Question 3,
research which aimed at identifying potential causes and
risk factors for the disorder, had the second largest portion
of funding (18%). Question 3 research projects addressed
topics such as identifying genetic mutations that increase
the risk of autism, developing improved approaches to
studying environmental exposures and gene-environment
interactions, and exploring the potential roles of the
microbiome and epigenetics on etiology. Treatments
and interventions (Question 4) followed closely with 17%
of total funding, which included research on behavioral
therapies, pharmacological treatments, and technology-
based interventions. Research projects in Question 4
encompass the development of new treatments using
model systems and small-scale experiments as well as
full-scale clinical trials. Investment in research infrastructure
and surveillance (Question 7) had a significant proportion
of funding at 16%. Projects in Question 7 covered data
sharing, workforce development, ASD surveillance, and
communication/dissemination of research findings and
evidence-based practices. Research to improve screening
and diagnosis (Question 1) of ASD was 9% of funding in
2015. Question 1 objectives focused on research to develop
biomarkers, screening tools, and diagnostic instruments
X
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
to aid in early identification. Research focused on services
(Question 5) and lifespan issues (Question 6) remained
the smallest areas of funding (6% and 2%, respectively).
Question 5 objectives addressed issues surrounding access
to services, coordination of community-based supports,
assessment of health and safety, and improving efficacy,
cost-effectiveness, and dissemination of evidence-based
practices. Research projects within Question 6 attempted
to identify and address gaps in transition to adulthood
and long-term outcomes in quality of life for people on
the autism spectrum.
While each question’s funding amount varied throughout
the eight-year span, the overall ASD funding proportions
remained relatively the same from 2008-2015. The
underlying biology (Question 2) of ASD, the detection
of risk factors (Question 3), and the development of
treatments and interventions (Question 4) consistently
received the greatest investments in research. Research
focused on services (Question 5) and lifespan issues
(Question 6) remained relatively low in funding throughout
the years. Question 2 (Biology) is the only research area
that received significant increases in funding over most
of the time period from 2008-2015.
$120,000,000
$100,000,000
$80,000,000
$60,000,000
$40,000,000
$20,000,000
$0
2008-2015 ASD RESEARCH FUNDING
2008 2009 2010 2011 2012 2013
Question 1 – Diagnosis
Question 5 – Services
Question 3 – Risk Factors
Question 2 – Biology
Question 6 – Lifespan
Question 7 – Infrastructure
Question 4 – Interventions
Question 5 – Services Estimated
2014
2015
Figure 1. ASD research funding from 2008-2015 by Strategic Plan question area.
XI
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
In 2008, the reported autism research funding for Federal
agencies and private organizations was $222.2 million and
745 projects. In 2015, funding for ASD research among
both Federal and private funders totaled $342.6 million
and spanned 1,410 research projects. Over the eight years,
autism research showed a general upward trend in funding,
increasing by 35% since 2008. Looking over the last eight
years, significant advances have been made in autism
research in each of the question areas prioritized by the
Committee. But, there are still some areas of research that
lack the support needed to foster significant progress.
Since the development of the last IACC Strategic Plan,
autism researchers have made several important discoveries
and reached many milestones, but have also uncovered
emerging areas in need of investments. While additional
investment is particularly needed in these emerging
areas of ASD research, an overall increase in funding to
support the entire autism portfolio will be critical to move
the field forward and capitalize on scientific opportunity,
as is described in the IACC Strategic Plan’s budget
recommendation. This new edition of the IACC Strategic
Plan builds on the priorities established in the previous
editions of the Strategic Plan, identifies the gaps in research,
and provides recommendations for future research and
services endeavors so that we continue to make a difference
in the lives of people with ASD and their families.
XII
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
2016-2017 STRATEGIC PLAN OBJECTIVES
QUESTION 1 HOW CAN I RECOGNIZE THE SIGNS OF ASD, AND WHY IS
EARLY DETECTION SO IMPORTANT?
1
Strengthen the evidence base for the benefits of early detection of ASD.
2
Reduce disparities in early detection and access to services.
3
Improve/validate existing, or develop new tools, methods, and service delivery models for detecting ASD in order
to facilitate timely linkage of individuals with ASD to early, targeted interventions and supports.
CROSS-CUTTING
1
Support research to understand the underlying biology of sex differences in ASD, possible factors that may be
contributing to underdiagnosis, unique challenges that may be faced by girls/women on the autism spectrum,
and develop strategies for meeting the needs of this population.
QUESTION 2 WHAT IS THE BIOLOGY UNDERLYING ASD?
1
Foster research to better understand the processes of early development, molecular and neurodevelopmental
mechanisms, and brain circuitry that contribute to the structural and functional basis of ASD.
2
Support research to understand the underlying biology of co-occurring conditions in ASD and to understand
the relationship of these conditions to ASD.
3
Support large-scale longitudinal studies that can answer questions about the development of ASD from
pregnancy through adulthood and the natural history of ASD across the lifespan.
QUESTION 3 WHAT CAUSES ASD, AND CAN DISABLING ASPECTS OF ASD
BE PREVENTED OR PREEMPTED?
1
Strengthen understanding of genetic risk and resilience factors for ASD across the full diversity and heterogeneity
of those with ASD, enabling development of strategies for reducing disability and co-occurring conditions in ASD.
2
Understand the effects on ASD risk and resilience of individual and multiple exposures in early development,
enabling development of strategies for reducing disability and co-occurring conditions in ASD.
3
Expand knowledge about how multiple environmental and genetic risk and resilience factors interact
through specific biological mechanisms to manifest in ASD phenotypes.
XIII
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION 4 WHICH TREATMENTS AND INTERVENTIONS WILL HELP?
1
Develop and improve pharmacological and medical interventions to address both core symptoms and
co-occurring conditions in ASD.
2
Create and improve psychosocial, developmental, and naturalistic interventions for the core symptoms and
co-occurring conditions in ASD.
3
Maximize the potential for technologies and development of technology-based interventions to improve
the lives of people on the autism spectrum.
QUESTION 5 WHAT KINDS OF SERVICES AND SUPPORTS ARE NEEDED TO
MAXIMIZE QUALITY OF LIFE FOR PEOPLE ON THE AUTISM SPECTRUM?
1
Scale up and implement evidence-based interventions in community settings.
2
Reduce disparities in access and in outcomes for underserved populations.
3
Improve service models to ensure consistency of care across many domains with the goal of maximizing
outcomes and improving the value that individuals get from services.
QUESTION 6 HOW CAN WE MEET THE NEEDS OF PEOPLE WITH ASD AS
THEY PROGRESS INTO AND THROUGH ADULTHOOD?
1
Support development and coordination of integrated services to help youth make a successful transition to
adulthood and provide supports throughout the lifespan.
2
Support research and implement approaches to reduce disabling co-occurring physical and mental health conditions
in adults with ASD, with the goal of improving safety, reducing premature mortality, and enhancing quality of life.
3
Support research, services activities, and outreach efforts that facilitate and incorporate acceptance,
accommodation, inclusion, independence, and integration of people on the autism spectrum into society.
QUESTION 7 HOW DO WE CONTINUE TO BUILD, EXPAND, AND ENHANCE THE
INFRASTRUCTURE SYSTEM TO MEET THE NEEDS OF THE ASD COMMUNITY?
1
Promote growth, integration, and coordination of biorepository infrastructure.
2
Develop, enhance, and link data repositories.
3
Expand and enhance the research and services workforce, and accelerate the pipeline from research to practice.
4
Strengthen ASD surveillance systems to further understanding of the population of individuals with ASD,
while allowing comparisons and linkages across systems as much as possible.
QUESTION
1
HOW CAN I RECOGNIZE THE SIGNS
OF ASD, AND WHY IS EARLY
DETECTION SO IMPORTANT?
1
Aspirational Goal: Provide the earliest possible diagnosis for people on the
autism spectrum, so they can be linked to appropriate interventions, services,
and supports in as timely a manner as possible to maximize positive outcomes.
INTRODUCTION
Observational studies of infants at risk for ASD reveal
that, although timing of the emergence of ASD features
is variable, subtle signs can be detected within the first
few years of life. Experienced clinicians who are trained to
use validated diagnostic tools can diagnose ASD by 18-24
months of age. Still, most children are not diagnosed in the
U.S. until four years of age, with disparities in diagnosis
related to socioeconomic factors, geographic location, and
race/ethnicity.
1
Given the unprecedented growth and
organization of the brain during the first three years of life,
2
behavioral interventions initiated in ASD toddlers within
this time period result in a range of positive changes
including increases in social attention, language ability,
and overall IQ.
3,4,5
However, due to the lag in diagnosis,
many children miss the opportunity to receive treatment
during this critical period of neuroplasticity. This chapter
reviews the state of knowledge about screening and
diagnostic tools, as well as the current state of service
delivery and challenges families face when trying to
access screening and diagnostic services.
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
2
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
IMPLEMENTATION OF ASD SCREENING
AND DIAGNOSTIC TOOLS
Although studies consistently report that screening using
validated autism-specific parent-report tools can result in
ASD detection as young as 12-18 months,
6
these tools are
only used systematically within about 50% of primary care
settings.
7
Reliance on using a standardized screening tool
has even been shown to be more effective than pediatrician
clinical judgment alone.
8
Thus, the American Academy
of Pediatrics (AAP)
9
has embraced using universal ASD
screening
10
standardized tools as the gold standard for
detecting ASD and recognizes screening as a critical service
need to improve early access to care. Barriers that prevent
widespread uptake of parent-report and other screening
tools within primary care settings include: lack of education
and understanding of ASD,
11,12
lack of familiarity with
screeners,
11,13
uncertainty about where to send a toddler
with a test-positive screen,
14
lack of effective and timely
means of connecting families of individuals with ASD to
available resources,
12,15
and the extra time and resources
required to utilize standardized screening tools.
14,11
Given that many parents take their child for well-baby visits
within a primary care setting, recent research has utilized
this context to improve screening. To accommodate the
dynamic and busy environment of a primary care setting,
parent-report screening tools are designed to be very
brief. A new revision to the Modified Checklist for Autism in
Toddlers, Revised, (M-CHAT-R), the most commonly used
parent-report screening tool, shows that with the
administration of follow-up questions (M-CHAT-R/F),
50% of children who test positive are later diagnosed with
ASD, and if all developmental delays are also considered,
then over 95% of children who test positive are diagnosed
with either autism or some other type of developmental
delay or disability.
16
However, administering follow-up
questions in the M-CHAT-R/F procedure can take anywhere
from 5 to 30 minutes and as such does not overcome the
barrier of time limits in primary care settings.
14
Leveraging
technology, recent studies have shown that a full
administration of the M-CHAT-R/F on a computer tablet not
only resulted in greater and more accurate documentation of
the screening results within electronic medical record
systems, but also eliminated the time barrier because parents
answered the follow-up questions directly on the tablet,
thus bypassing the need to engage medical personnel.
17
Large-scale studies examining the M-CHAT
1,18
and its
revisions
16,19,20
compared to the estimated prevalence
rates suggest that many cases of ASD may be missed
using the screening tool, especially in 18-month olds. This
may be due to many factors, including: the accuracy of
the screening tool, ability of parents to notice and report
early signs of autism, readiness of parents to act on a
positive autism screen, and the heterogeneity in symptom
presentation at this young age, suggesting that screening
efforts may need to go beyond simple parent-report tools.
One such approach is a two-stage screening model that
combines a general developmental screening tool based
on parent report, the Infant Toddler Checklist (ITC),
21
with
subsequent observational ratings to screen for ASD. Using
this approach, detection rates have been reported as 15.1
per 1,000 children at a mean age of 20.8 months,
22
which
is very close to the expected prevalence rates for ASD.
1
Children identified through the M-CHAT-R/F alone display
a lower developmental level than children ascertained with
the ITC and follow-up observational rating,
22,23
and a lower
developmental level than those evaluated in a prospective
3
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
sample of younger siblings at familial risk for ASD,
24
suggesting that this tool may be better at detecting children
at a lower developmental level and may sometimes miss
less severely affected children. Continued improvement
in screening approaches may be achieved by better
understanding the psychometric features of parent-report
screening tools in relation to observational measures,
23,25
and by examining the effectiveness of different screening
thresholds in relation to diagnostic accuracy and cost-
effectiveness.
26
Additional new innovations in parent-report
screening approaches include the incorporation of
photographs into the questionnaire to illustrate items in
a culturally unbiased manner,
27
combining multiple
screening tools to improve sensitivity and specificity,
28
and free mobile applications (apps), such as ASDetect that
augment descriptions of ASD characteristics with video
examples and provide a video-led assessment of child
behaviors. Studies are needed to validate the usability and
accuracy of these apps, although there is empirical
support demonstrating that the markers highlighted within
the apps (e.g., pointing and showing) are predictive of
an ASD diagnosis.
29,30
A growing appreciation of ASD as a condition marked by
unique behavioral, neural, and genetic signatures that may
precede noticeable clinical symptoms has resulted in
a surge of prodromal and biomarker-seeking research
which broadens the scope of future screening efforts.
Of particular interest are potential biomarkers likely to
facilitate gene-brain-behavior studies, diagnosis, or those
that may act as prognostic markers. Observational studies
continue to reveal that signs of ASD are subtle, but may
emerge within the first year of life, particularly in the
areas of social communication, attention, and motor
development.
24,31,32
Preliminary studies deploying eye-
tracking technology to measure social visual engagement
have demonstrated utility and accuracy in detecting
markers of ASD in the first year of life.
33,34
For the first time,
structural and functional magnetic resonance imaging
(fMRI) studies of infants are beginning to predict later
ASD diagnosis and core characteristics such as language
outcome.
35,36,37,38
Additionally, RNA expression profiles
can classify toddlers with ASD at levels exceeding 80%
accuracy.
39
While these findings suggest a future of
exciting new tools for screening and diagnosis, they must
be validated in other high-risk groups and in the general
population, and they must be adjusted for broader use in
order to be beneficial to the wider community.
Although engagement in early treatment has been
associated with a range of positive changes including
increases in social orienting, language ability, and overall
IQ,
3-5,40
no study has directly examined if children with
ASD detected by early screening have better outcomes
than those detected by other means, (e.g., parent or
provider concern) an issue highlighted by the recent US
Preventive Services Task Force (USPSTF) report
10
on
universal early screening. However, as noted by Dawson
(2016),
41
such a study would require large representative
samples from across the country to be randomly assigned
to either a screening or non-screening condition, and then
followed to determine long-term outcomes and societal
costs. Given that early treatment for children under age 3
years has been shown to result in positive gains,
42
and has
even been associated with an increased potential to lose
an ASD diagnosis altogether,
43
such a study can
be controversial.
While a considerable investment of time and resources
would be required to conduct new randomized controlled
trial (RCT) studies to specifically address concerns raised
by the USPSTF, there are opportunities and study designs
that could be leveraged using existing resources in the
short term. First, data could be examined from within sample
cohorts that include clinical longitudinal data from toddlers
detected via screening as well as toddlers detected via
other means (e.g., parent or clinician concern). Second,
exclusively within cohorts of screen-detected toddlers,
researchers could examine outcomes of children detected
4
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
at identical early ages via screening but that contained a
subgroup of toddlers who started treatment well beyond
the screen-detected age. In this way, the impact of very
early treatment engagement as afforded by screening
could be more directly examined. In terms of new, future
studies, in instances where a traditional RCT design
(intervention versus no intervention) may not be feasible
and the health impact is high, other complex forms of RCT
models could be used as well as utilizing administrative
data. Several states collect state-level data on youth who
receive ASD screening and subsequent developmental
outcomes. This may afford an opportunity to compare
children with and without early screening in terms of
variations in developmental outcomes.
While early detection, whether achieved through universal
screening or by other mechanisms such as parent or clinician
concern, is an essential step in the health care process for
ASD and deserves more research attention, it is just one
step on the path to identification and eventual treatment.
Screening in and of itself does not determine if and when
parents actually follow through with subsequent diagnostic
evaluation and treatment engagement, nor does it determine
the quality and benefits of such treatment. Another key gap in
the field is the lack of studies examining the many important
factors that follow after screening has occurred.
44
There is indeed a growing appreciation of the importance
of implementation science methods to examine contextual
factors (e.g., mode of screening delivery) that may impact
successful screening uptake. Some studies are currently
underway, performed by researchers funded through the
National Institute of Mental Health ASD Prevention, Early
Detection, Engagement and Services (ASD-PEDS) Network.
Another important factor is comprehensive tracking of
treatment participation, which is essential to determine the
long-term outcomes of children detected early by screening.
To date, most studies do not report treatment engagement,
and if it is reported, it is often at a very coarse level
(e.g., number of hours).
In order for screening to be effective, ample evaluation
centers must be available with appropriate ASD diagnostic
expertise. Indeed, uncertainty regarding where to send a
toddler for an evaluation is a barrier to screening noted by
over 75% of pediatricians.
14
Therefore, an increase in the
number and accessibility of evaluation centers is necessary,
based on population and expected rates of ASD. Likewise,
significant enhancement of the screening and evaluation
system is meaningful only if high-quality treatment
providers are available and affordable. Some efforts have
been made, such as “Birth to Five: Watch Me Thrive!”,
which is a coordinated Federal effort to raise awareness
about the importance of universal early behavioral and
developmental screening. This resource offers a collection
of research-based screening tools for children under the
age of 5. However, there is still a need to investigate more
cost-effective modes of treatment delivery, such as those
that are either partially or fully deployed by parents.
3
An increase in the number of toddlers screened and identified
as possible ASD
20
also calls for the need to standardize
policies regarding eligibility for IDEA Part C services, the
Federal program that funds intervention services for children
showing delays, including autism, from birth through 2
years of age. Generally, toddlers must first qualify for basic
Part C services by exhibiting a particular state-mandated
level of delay (usually a 25% delay in two or more areas),
which often provides for just a few hours of speech or
occupational therapy. Although autism is an automatic
eligibility category, a child must be identified as either
ASD or showing signs of ASD in a separate evaluation
visit in order to be eligible to receive ASD-specific treatment.
Currently, there are no guidelines mandating that all
toddlers receiving Part C services should be examined for
possible ASD. Even once a child is referred for an in-depth
ASD evaluation, there are no policies regarding specific
diagnostic and other evaluation tools that should be used
to determine if a child is eligible for ASD-specific services.
Unsurprisingly, many toddlers already receiving Part C
5
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
services for a developmental delay have not been properly
evaluated for ASD. Even more concerning, the vast majority
of toddlers with ASD (at least 75%)
45
who will go on to
qualify for special education at school-age are still not
identified in time to receive early intervention. Providing
clear guidelines regarding ASD detection and subsequent
treatment eligibility through Part C will help to eliminate
these deficiencies.
DISPARITIES IN ASD SCREENING AND DIAGNOSIS
DISPARITIES IN ASD SCREENING
The barriers that limit screening during well-child visits
have immediate service access implications for children
from diverse backgrounds. Overall, ASD screening rates
during primary care visits range from 1-60%;
7,13,46
some
of the variability in use of standardized screening is
based on children’s sociodemographic characteristics.
For example, screening may occur less frequently among
Spanish-speaking families compared to English-speaking
families.
47
Families with low levels of maternal education
exhibit higher screen positive rates on the M-CHAT(-R);
48,49
but are less likely to follow up with diagnostic evaluation,
suggesting that these families are at risk for being under-
served.
50
Additionally, consistent use of screening tools
may depend on insurance reimbursement; children from
low-income families may be more likely to be screened
during check-ups since it is often reimbursed by Medicaid,
51
but may not be covered by private insurance.
Research has shown that children from minority backgrounds
are diagnosed on average more than a year later than their
White peers.
52
However, it has been demonstrated that
when physicians follow a standardized screening protocol,
including immediate referral for screen-positive cases,
disparities in age of diagnosis are reduced to approximately
1 month.
53
Therefore, access to screening for all children,
regardless of sociodemographic characteristics, language
spoken at home, and geographic locale, is crucial to
reduce existing disparities that impact life-long outcomes.
In addition to dedicating more resources to early screening
in underserved communities, a corresponding increase in
funding adequate evidence-based diagnostic evaluations
will avoid lengthening waitlists.
54
VALIDITY OF SCREENING INSTRUMENTS
IN DIVERSE GROUPS
A number of studies have examined ASD screening
tools in different languages and cultural settings within
the US and across the world.
50,55,56,57,58
The variability of
results from these studies indicate that there is a need
for additional research to adapt tools that will be valid
(i.e., demonstrate adequate sensitivity and specificity)
in diverse populations. Factors including low educational
attainment, language/literacy, rural versus urban locale,
race, and ethnicity also impact screening reliability and
validity
57
as well as screen-positive rates.
50,58
Studies
examining medical or state records for specific
mention of ASD screening and diagnosis would be
helpful in documenting disparities and also in tracking
improvements based on policy changes or improved
access to care.
The recent USPSTF report on universal ASD screening
10
specifically highlighted the gaps in research on health
outcomes of children detected through screening, particularly
in those from minority and low-income families. It will be
critical to evaluate the quality of screening instruments
and programs in diverse samples of children, including
6
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
long-term outcomes. Implementation studies examining
the translation from research settings to community settings
with diverse populations, including examining fidelity of
adhering to screening protocols, also is a critical gap in
the existing literature.
58,59,60,61
DISPARITIES IN ACCESS TO DIAGNOSTIC
SERVICES AND AGE OF DIAGNOSIS
Differences both in prevalence rates and age of
diagnosis by sociodemographic characteristics likely
relate to disparities in access to expert services. According
to the most recent surveillance study by the Centers for
Disease Control and Prevention’s (CDC) Autism and
Developmental Disorders Monitoring (ADDM) Network
study,
1
White children were 20% more likely to have
indicators of ASD in their school and health records than
Black children, 40% more likely than Asian and Pacific
Islander children, and 50% more likely than Latino children.
A variety of factors, including economic challenges,
50
geographic distance between families and service providers,
62
reduced professional resources and capacity,
63
and
characteristics impacted by cultural knowledge, such as
stigma
64
often contribute to diminished service availability
and utilization in rural, minority, or other disadvantaged
communities. A primary barrier to ASD early diagnosis is
the limited availability of diagnostic clinics with providers
trained in ASD diagnosis, leading to long waiting lists
and poor reimbursement for comprehensive diagnosis.
54
This limited availability is especially pronounced in
resource-poor and rural areas, with many children not
diagnosed until entry into the school system.
In addition, family level variables such as insufficient
financial resources, lack of insurance coverage, language
barriers, geographic isolation, and limited knowledge of
or experience with complex healthcare systems, may be
barriers to the timely diagnostic evaluation of an at-risk
child.
65
Overall, there is limited research that documents
these systemic- and individual-level barriers that exist
from early ASD screening to appropriate diagnosis to early
intervention.
66
Finally, and perhaps most importantly, there
is a need for prospective studies that demonstrate that
equal access to high-quality screening, with immediate
referral for screen-positive cases to diagnostic evaluation
and early intervention services, will reduce disparities in
prevalence, as well as any disparities in long-term outcomes
for children with ASD.
Practitioner efforts that can help to reduce disparities
in diagnosis include increasing psychoeducation to raise
awareness and reduce stigma, building external
professional networks, promoting continuing education
programs, using alternative service delivery models
(e.g., telehealth, web-based, community health workers)
or settings (e.g., schools, child care centers, mobile clinics)
for screening/diagnosis, and providing wraparound services
that address additional stresses (e.g., chronic illness,
unemployment, lack of insurance) often faced by individuals
in underserved communities. Finally, it is clear that children
are not often well-tracked from the time of ASD screening
to receipt of services.
52
It is imperative to have a system
in place that can assure children and families adequate,
timely, and appropriate services as they move through
the identification, referral, and treatment process.
VALIDITY OF DIAGNOSTIC INSTRUMENTS
ACROSS SPECIAL POPULATIONS
There is general agreement that the best approach
to ASD diagnosis includes both parent interview and an
observational assessment of the child,
67
such as the
Autism Diagnostic Interview-Revised (ADI-R) and the
Autism Diagnostic Observation Schedule (ADOS-2). The
ADI-R has been translated into 17 languages, and a small
number of studies have examined the validity of the ADI-R
in different countries with varying results.
68,69,70,71
With
respect to validation studies with diverse populations in the
US, researchers found that the sensitivity and specificity of
the ADI-R with a US-based Spanish-speaking population
7
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
of parents of children with ASD were lower
72
than values
previously reported for mostly White, middle-class
respondents.
73
The communication domains were found
to be especially problematic for parents whose primary
language was Spanish when reporting on children who
spoke mainly English.
72
Little is known about the validity
of the ADI-R among low-income families in the US. The
ADOS-2 has been translated into 19 different languages;
however, cross-cultural validation studies of the ADOS-2
have not been identified.
The development of screening and diagnostic tools has
largely been accomplished using data from boys, which
might put other underserved populations of ASD at a
disproportionate risk of not receiving a clinical diagnosis.
Based on recent literature, there appears to be a diagnostic
gender bias, which means that girls are less likely than
boys to meet diagnostic criteria for ASD at comparatively
high levels of autistic-like traits.
74,75
Girls may also exhibit
different symptoms from boys, which may make current
screening and diagnostic tools more likely to miss ASD
in girls.
76,77,78
It is important that future research addresses
the gender differences in ASD, both biological and
behavioral, in the development of diagnostic tools. Also at
risk of being underdiagnosed are individuals with ASD that
have other co-occurring developmental conditions. A third
of children with ASD also have an intellectual disability,
1
and many individuals with ASD have a dual diagnosis of
attention-deficit/hyperactivity disorder (ADHD); having
multiple conditions often leads to a misdiagnosis or a
delayed ASD diagnosis.
79
While research is necessary to
develop tools that account for the overlap in symptomology,
health providers must consider multiple diagnoses
during evaluation.
In addition, increasing numbers of adults are presenting
to clinics for first-time diagnoses of ASD, and recent studies
suggest that many adults with ASD may be unidentified and
living in the community without appropriate supports.
80,81
There is a need to improve diagnostic tools that are
specific for adults; this will be discussed in more detail in
Chapter 6: How can we meet the needs of people with
ASD as they progress into and through adulthood?
WORKFORCE
The increased prevalence of diagnosed ASD cases over
the past two decades has led to a need for a larger workforce
trained in the identification and diagnosis of these disorders,
including psychologists, psychiatrists, developmental
pediatricians, neurologists, and speech and language
pathologists. Early detection of ASD will require training
those professionals who come in regular contact with
young children, including primary care providers and child
care providers, to incorporate effective screening and
referrals in their daily practice patterns. In response to
this need, CDC, in collaboration with the Health Resources
and Services Administration (HRSA), developed a web-
based education program, the Autism Case Training, to
inform healthcare providers on fundamental components
of identifying, diagnosing, and managing ASD through
real- life scenarios. Promoting, refining, and delivering
similar education programs is a critical factor in building
a workforce that can effectively serve individuals with
ASD and their families.
8
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Evidence demonstrates that healthcare professionals are
less likely to detect ASD using developmental surveillance
without the use of screening tools. Even experienced
professionals may miss or misjudge symptoms during a brief
observation.
18
However, primary care providers face barriers
to implementing screening that include the time necessary
to identify ASD, the cost of conducting screening and the
reimbursement for this work, and having appropriately
trained personnel in their offices or referral networks.
Also, practitioners may lack the technical training to review
and compare complex psychometric information on the
quality of developmental screening tools. Training for this
workforce is needed to improve their ability to screen
effectively, recognize ASD symptoms, communicate clearly
with parents, and refer appropriately for evaluation and
intervention services.
Parents may not recognize signs of developmental delay,
or may have concerns about their child’s development
but do not know how or when to act on those concerns.
There is a need to raise public awareness of the early signs
of ASD, to encourage parents to observe and track their
child’s development, and to encourage them to discuss
their concerns with their child’s doctor, teachers, and other
care providers. The “Learn the Signs. Act Early.” campaign
developed by CDC, and the “16 Gestures by 16 Months
series developed by the First Words Project are examples
of strategies that can be utilized to raise awareness and
facilitate parent-provider collaborations. However, there is
still a critical research gap on understanding how parent
concerns can impact parent engagement in acting on
referral for diagnosis and early intervention.
Addressing gaps in our understanding of how healthcare
professionals can best reach families from underserved
communities continues to be a challenge. There is an
opportunity to improve the identification of ASD through
materials prepared in languages spoken by target groups
within these communities, but even more important are
efforts to implement culturally competent practices and
engage a workforce with greater cultural diversity in order
to better address the needs of culturally diverse populations.
For example, outreach activities held in places of worship
and other community gatherings where families feel more
comfortable may improve parent-provider partnerships
and lead to increased identification of ASD.
Some important service initiatives to address screening
and diagnosis training are ongoing, but there is a need for
additional efforts. The AAP supports universal screening
for ASD and provides training to pediatric providers through
several formats (publications, webinars, and face-to-face
conferences). Leadership Education in Neurodevelopmental
and Related Disabilities (LEND) and the University Centers
of Excellence in Developmental Disabilities (UCEDDs)
also provide training to practitioners from over a dozen
healthcare disciplines. Despite the recommended guidelines
for utilizing these resources, the professional community
is not reaching most of the families and children in need
of early intervention. Therefore, service-relevant policies
need to make professional development and training more
available as well as dedicate more resources in order to
expand the workforce to address unmet needs for early
screening and diagnostic services, including access to care.
Furthermore, there is a need for improved policies to
facilitate the collaboration of community-based programs
and social supports with professional services.
9
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
LINKAGE TO INTERVENTION SERVICES AND
OTHER SUPPORTS
It is critically important that children with ASD are identified
early so they can be referred to intervention programs that
address their individual needs. Eligibility criteria and the
lead agency for early intervention vary by state (health
agencies in some states, and child welfare or education
agencies in other states). Similarly, some states or regions
have more comprehensive insurance coverage and/or
more coordinated systems of healthcare than others.
Even in better-resourced areas, families are often faced
with many complex steps from screening to diagnosis to
treatment. Most infants and toddlers with a diagnosis of
ASD miss the opportunity to receive early intervention
services.
45
This service need is unmet to an even greater
degree in children from minority backgrounds.
52
There is
a need to improve access to early screening and to increase
the accuracy of screening tools because these are the
gateway to early intervention services. Coordination of a
care team that includes healthcare and childcare providers
is critical to address gaps in screening, begin to break
down barriers for families to act on screening results, and
support family engagement in intervention services.
Nearly half of children with ASD have private insurance;
the other half have insurance provided by Medicaid or the
state-based Children’s Health Insurance Program (CHIP),
or dual private and public coverage.
82
However, about half
of families of children with ASD report that their insurance
coverage is inadequate to meet their myriad of complex
needs and costs. As noted earlier, reimbursement for ASD
screening may improve screening rates and more readily
become a standard procedure in practices. A systemic
issue is that some insurance plans do not cover quality
treatments, such as applied behavior analysis (ABA), or
may place limits on essential behavioral, medical, or other
healthcare. Additionally, family social service supports,
which contribute greatly to meeting the needs of the child,
are not covered. These limitations often leave families
struggling in many ways, which results in significant
financial and familial burdens. In fact, nearly half of families
of children with ASD say their child’s health condition has
caused major problems for the family and in some cases
bankruptcy and other family disruptions, such as divorce
or job loss.
83,84
Currently, families must navigate different sectors of service
in terms of information, provision, and funding (e.g., medical
providers, local government, education) all within a very
short period of time (from noted concern to early intervention
age eligibility cut-offs). The different service sectors are
not coordinated and often do not communicate with each
other, particularly across health and social service agencies.
Systematic barriers for families include considerable
differences in the type and amount of services supported
by insurance plans, geographic differences in type and
amount of services available, and inequities and disparities
existing across counties and states. Lastly, systems do
not take into account families’ concerns about stigma, the
reluctance of professionals to make a diagnosis or share
concerns about red flags of ASD in very young children,
missed or false positive diagnoses, and the need for earlier
evaluations and re-evaluations of very early assessments
as symptoms are unfolding.
10
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
SUMMARY
Significant advances have been made toward early
identification of individuals with ASD, so they can be linked
to appropriate interventions, services, and supports in as
timely a manner as possible. However, gaps still remain.
There is a need to validate tools in diverse settings and
populations. There is a need to evaluate the effectiveness
of universal screening for improving outcomes in ASD.
There is a great need to understand the disparities in access
and/or utilization of screening and diagnostic tools, and
entry into intervention services. In addition, research is
needed to develop, adapt, and validate tools that will enable
detection of autism in children with intellectual disabilities,
girls, and adults. The challenges and barriers include gaps
in the evidence base for the benefits of early detection in
diverse populations and settings; an insufficient workforce
with expertise in ASD diagnosis and intervention; lack of
medical home for families of children with ASD; the need for
continued insurance reform; disparate and uncoordinated
service sectors; and the lack of an infrastructure to track
children and families in order to evaluate the efficacy
of service systems. There have been important strides
in the area of early detection of ASD features and in
demonstrating the impact of early intervention. Yet, there
are significant challenges and barriers to implementing
screening, diagnostic, and treatment services broadly and
reducing disparities in access and utilization. The way forward
is reflected in the three objectives proposed for Question 1.
OBJECTIVES
OBJECTIVE 1: Strengthen the evidence base for the benefits of early detection of ASD.
Examples:
Implement innovative designs to evaluate the benefit of universal screening for ASD, including research that
addresses the specific research gaps noted by the USPSTF report.
Conduct studies focusing on the differences and needs of special populations such as girls and individuals with
intellectual disabilities.
OBJECTIVE 2: Reduce disparities in early detection and access to services.
Examples:
Improve family engagement and help build an awareness of healthy developmental milestones and warning signs of concern.
Demonstrate the validity of different screening and diagnostic tools for culturally diverse communities.
Increase services in high-poverty and underserved regions; improve inclusion of these populations in research.
Address differences in state policy requirements for Medicaid and the requirement of a diagnosis to receive services.
Develop a culturally competent and more culturally diverse workforce.
11
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVE 3: Improve/validate existing, or develop new tools, methods, and service delivery
models for detecting ASD in order to facilitate timely linkage of individuals with ASD to early,
targeted interventions and supports.
Examples:
Continue research on the potential translation of biomarker findings into feasible and valid screening or diagnostic tools.
Increase coordination and personalization of screening, diagnosis, and early intervention services through use of
the medical home model, person-centered planning, or other service models.
Conduct research to better understand and develop strategies to address reasons for lack of compliance with
screening recommendations; address barriers to universal screening.
Analyze the impact of insurance reform and national policy on coverage for screening, diagnosis, and intervention
for children with ASD and their families.
Evaluate innovative service delivery methods (e.g., use of technology) to improve detection methods and increase access.
CROSS-CUTTING OBJECTIVE
The topic of girls and women with ASD is mentioned in several chapters of the Strategic Plan, indicating the Committee’s
strong interest in this area. To combine the priorities for research and services to understand and better serve the needs of
girls on the autism spectrum, this “cross-cutting” objective was developed. Individual projects assigned to this objective
will be coded to different questions of the Strategic Plan depending on which aspect of ASD in girls and women is being
studied. This will ensure the funding associated with those projects will be counted toward the totals of their respective
questions, but also allows the projects to be added together into a single objective. The goal of a single “cross-cutting”
objective on girls and women with ASD is to encompass the numerous research and services priorities identified by the
Committee throughout the Strategic Plan and allow for this area to be identified as a priority for funders.
CC1. Support research to understand the underlying biology of sex differences in ASD, possible factors that may
be contributing to underdiagnosis, unique challenges that may be faced by girls/women on the autism spectrum,
and develop strategies for meeting the needs of this population.
Examples:
Conduct research on the underlying biology of ASD in girls/women (differences in brain structure, function, physiology)
and how this may create differences in phenotype.
Identify risk and resilience factors that contribute to sex differences.
Develop, adapt, or validate screening and diagnostic tools to detect ASD in girls.
Develop strategies to meet the intervention, service, and support needs of girls/women with ASD.
QUESTION
2
WHAT IS THE BIOLOGY
UNDERLYING ASD?
13
Aspirational Goal: Discover how alterations in brain development and the function
of physiological systems lead to ASD in order to enable the development of
effective, targeted interventions and societal accommodations that improve
quality of life for people on the autism spectrum.
INTRODUCTION
Current scientific evidence suggests that ASD results
from subtle alterations during brain development that affect
brain structure, function, and connectivity. However, our
knowledge about its causes remains incomplete and
significant gaps in science have hindered attempts to develop
therapies to improve quality of life for individuals with
ASD. Over the course of the last decades, several studies
have revealed the role of prenatal or perinatal stressors
and genetic contributors to the risk of developing ASD,
possibly acting through changes in early brain development.
The biological mechanisms by which known gene mutations
cause syndromic ASD (i.e., the subtypes of ASD that are
usually caused by a single genetic abnormality) by altering
the underlying neural circuitry of the brain are under
intense study. These genetic variants are associated
with remodeling of genetic material, changes to ion
channels (which are the basis for cellular function and
communication), and proteins that regulate cell-to-cell
communication. Taken together, this research suggests
there may be shared features of the underlying biology
across the spectrum of autism. However, we currently
know very little about the precise pathways that cause
the circuit changes driving the core behavioral features
in ASD, but new tools promise to accelerate this area of
investigation. In addition, while there have been recent
gains in understanding ASD developmental trajectories
and the nature and prevalence of co-occurring conditions
in persons with ASD, more work is needed to understand
these aspects of ASD and develop strategies to target
them successfully.
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
14
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
MOLECULAR MECHANISMS AFFECTED BY
GENES IMPLICATED IN ASD
Genetic studies of ASD have identified more than
100 high-risk genes and estimate that several hundred
additional genes of this type will be identified in the future.
1
It seems likely that over 1,000 genes conferring lower
degrees of autism susceptibility will also be identified in
the future.
2,3,4,5,6,7
At present, the known functions of
these genes converge on biological processes important
for neuronal communication and regulation of the
expression of genes and proteins.
The discoveries of gene mutations that cause syndromic
ASD (e.g., tuberous sclerosis complex (TSC), Rett syndrome,
Fragile X syndrome, Phelan McDermid syndrome), and
the dozens of rare de novo (spontaneous) mutations that
disrupt gene function in ASD
8
have enabled scientists to
explore the biological effects of the various involved genes
in cellular and animal experiments. This has led to an
explosion of research examining how these mutations alter
the biology of cells and investigating their effects on neural
circuitry and behavior. On the horizon are genetic tools
that will enable the introduction of mutations into
non-human primates,
9,10
which possess a much greater
behavioral repertoire and a more human-like brain than
rodents or other animal models. However, these experiments
will need to be designed carefully because the numbers
of matched control and mutant animals need to be very
small as compared to rodent studies.
A major advance over the last few years is the ability to
take skin or blood cells from persons with ASD, create
induced pluripotent stem cells (iPSCs), and differentiate
these cells into neurons, which can enable the study of
neural function at the cellular level. This new technology
allows scientists to study the effects of ASD mutations in
human brain cells in addition to commonly used transgenic
animal models. Furthermore, iPSCs are attractive models
for identifying molecular phenotypes linked to syndromic
ASD, but a more high-throughput means of identifying and
validating their relevance to ASD is needed. A strategy for
identifying relevant molecular phenotypes in iPSCs from
the much more common idiopathic ASD (ASD of unknown
cause) remains a daunting task. In addition, new research
may make it possible to grow “brain organoids,” which are
clumps of brain tissue partially organized to have some
features of the human brain, from iPSCs. These partially
matured “mini-brains” can be grown in a culture dish and
can be used to enable the study of the early development
of brain structures that occurs in utero, as well as the
cellular and circuit abnormalities related to ASD-linked
mutations.
11,12
However, these in vitro studies will introduce
a number of variables related to culture conditions, and
deliberate actions will be required to evaluate reproducibility.
Though new iPSC and brain organoid technologies
allow for the study of human cells and circuits derived
from persons with ASD, there is no substitute for careful
structural and transcriptomic studies in postmortem
tissue which remains exceptionally rare. Efforts need to
be redoubled to increase the accessibility of brain tissue
from well-characterized ASD cases. The establishment of
collaborations like the National Institutes of Health (NIH)
NeuroBioBank and Autism BrainNet facilitates the
distribution of high-quality, well-characterized human
postmortem brain tissue for the research community.
15
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Enhancing efforts to increase public awareness about the
value of tissue donation for understanding brain disorders
like autism will most effectively advance the science.
Studies of postmortem brain tissue from persons with
ASD have demonstrated decreased expression of sets of
genes related to synaptic function, including many of the
known ASD risk genes. Surprisingly, despite the 4:1 male
to female ratio in ASD, these changes in synaptic gene
expression were not more evident in males than females.
However, there was an observed upregulation of genes
related to microglial and astrocytic function (brain cells
that provide support for neurons) that was more
pronounced in males.
13
These gene expression differences
may help explain why ASD occurs more frequently in
males. Moving forward, new gene expression mapping
technologies have the potential to better characterize
altered patterns of gene expression in specific brain
cell types, offering the opportunity to precisely associate
gene expression differences at a cellular level. In these
studies, it will be critical to include an examination of
gender-related differences in gene expression.
The impact of sex chromosomes on differences in gene
expression between males and females – and how this may
contribute to ASD – is also an area of research needing
additional attention. The role of genes on the Y (male) and X
(female) chromosomes extends beyond reproduction-related
functions. Studies have suggested that genes on the sex
chromosomes may act as broad regulators of gene
expression. Therefore, differences in gene regulation by
X-X gene pairs in females versus X-Y gene pairs in males
may have different effects on the dosage-dependent
expression of other genes, including those implicated in
ASD-relevant molecular pathways.
14,15,16
Another remaining challenge is to understand how the
effects of hundreds of implicated genes converge to cause
ASD’s common features. And conversely, more work is
needed to determine how individual genes and their
interactions with early life events explain the biological
basis of the heterogeneity of ASD symptoms, which range
from severe intellectual disability and absence of verbal
language, to mild social deficits with normal cognitive
function. With regard to the 4:1 male to female ratio in
ASD mentioned above, further work is also needed to
understand the phenotypic differences between girls and
boys with ASD, and how these differences should inform
development of screening and diagnostic tools, interventions,
and services that meet the needs of both girls and boys
on the autism spectrum.
16
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
STRUCTURE AND FUNCTION OF BRAIN
CIRCUITS IN ASD
STRUCTURE AND FUNCTION
Autism is characterized by atypical patterns in physical
brain connections (structure) and in how regions
communicate with each other (function). Brain structure
in individuals with ASD can be compared to typically
developing children using advanced magnetic resonance
imaging (MRI) techniques to measure size and shape
of brain regions over time, as well as diffusion tensor
imaging (DTI) to examine the structures of the major
connections between brain regions. Brain circuit function
can be investigated using non-invasive markers, such as
functional magnetic resonance imaging (fMRI),
magnetoencephalography (MEG), electroencephalography
(EEG), and functional near-infrared spectroscopy (fNIRS).
These studies have shown differences in activation patterns
in individuals with ASD in response to sensory processing
of visual, tactile, auditory, and verbal stimuli.
17,18,19,20
Although non-invasive measures of brain connectivity
have demonstrated differences between brain regions in
persons with ASD compared to controls, it is unclear how
these differences account for the heterogeneity in ASD
symptoms. Earlier findings from fMRI, DTI, and pathological
studies highlighted a pattern of reduced long-distance
connectivity and increased local connectivity.
21
While these
principles still largely hold, newer research has revealed
greater nuance and specificity.
22,23
On the gross anatomical level, the brains of autistic
individuals appear normal. Microscopic studies have
reported disordered cell organization with smaller, more
densely packed neurons in many regions of the limbic
system, a part of the brain which is known to play an
important role in learning, memory, and emotions. One of
the more reproducible findings is a reduction in the number
of Purkinje cells in the cerebellum.
Current evidence suggests that early brain overgrowth is
present in approximately 15% of 2-year-old boys with ASD,
but is much less common in girls.
24,25
Brain enlargement
relative to body size in this subset of boys persists at least
through 5 years of age
26
and is associated with lower
language ability at age 3 and reduced intellectual ability at
age 5.
27
Currently, the prevailing theory is that early brain
overgrowth normalizes during adolescence and adulthood,
28
although this is based on cross-sectional studies. A truly
longitudinal analysis, where the same individuals are
imaged throughout life, is needed to clearly establish
this. Studies at the cellular level have begun to describe
differences in neuronal growth and organization in
ASD brains.
Interestingly, recent studies have identified significant
inter- and intra-individual variability in neural functioning
in ASD. Heterogeneity in the ASD phenotype also contributes
to greater functional variability within ASD groups.
To address this heterogeneity, a greater number of studies
are examining dimensional traits in large samples of
ASD and neurotypical groups.
Ongoing work is linking these functional and structural
differences to core features of ASD including studies on social
communication, language, and restricted and repetitive
behaviors. Recent work has identified neurobiological
correlates of sensory processing in autism,
29,30,31
including
17
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
findings of reduced modulation of connectivity between
the thalamus (a brain structure responsible for relaying
sensory and motor signals to the cerebral cortex as well as
regulating consciousness, sleep, and alertness) and cortical
regions in response to sound or touch. The extent of this
reduced connectivity was related to parent reports of
sensory over-reactivity.
30
In the domain of touch, reduced
response was seen in ASD children in social-emotional brain
regions to a soft caress compared to typically developing
children, while increased activation was seen in response
to non-caress-like touch in the brain’s primary sensory
cortex. This over-activation may be related to the hyper-
sensitivity to touch seen in some ASD individuals.
There is a need for a greater understanding of the relationship
between intrinsic functional brain organization during rest
and functional connectivity dynamics during task states.
Additionally, there is a need for a better understanding
of brain function and connectivity during tasks that better
capture the complexity of real-world interactions for
individuals with ASD.
32,33
CIRCUIT ACTIVITY IN ASD
As is true of almost all brain disorders, the symptoms
experienced by individuals with ASD are linked to alterations
in brain circuit function. Alterations in the formation of
brain circuits that occur in utero, during infancy, and in
childhood can have long-lasting impacts on circuit function
in adulthood. During these early critical time periods,
connections between brain regions are dramatically molded
by brain activity and may be altered by injury or inflammation.
Identification of genes involved in syndromic autism enable
the study of the human phenotypes associated with those
genetic syndromes as well as phenotypes of genetic animal
models carrying the same mutations. The study of several
forms of syndromic ASD have revealed nervous system
differences such as differences in abundance of certain cell
types, in neural circuits, and in brain activity.
34
Environmental
insults, for example those due to infection in utero, premature
delivery, or perinatal cerebellar hemorrhage also alter the
construction of brain circuits leading to ASD.
There are continuing challenges in applying animal
models to understand the biology of autism. Because, in
many cases, autism impacts uniquely human aspects of
social-communicative behavior (e.g., spoken language),
developing and measuring analogous phenotypes in
animals has proven difficult. Because autism impacts
brain regions not developed in some animal species, some
neural circuitry is not readily amenable to study in these
models. Moving forward, increased use of species more
comparable to humans in both biology and behavior will
be necessary. Notably, genetic tools previously limited in
application to mice can now be applied in rats and even
non-human primates, such as macaques and marmosets.
Furthermore, the circuit alterations that have been described
in ASD models vary considerably. Variability due to
methodological differences among labs may diminish the
value of the research findings. Incorporation of a more
standardized and systematized approach to studying the
altered circuits in ASD models could be valuable to the field.
Fortunately, new powerful technologies for interrogating
and modulating brain circuits are revolutionizing
neuroscience. The BRAIN Initiative is a multi-Federal agency,
public-private partnership in the US to advance brain circuit
neurotechnologies and also engage multiple international
efforts. These technologies promise to expand the ability
to understand brain circuit differences due to genetic and
environmental influences that contribute to many diseases,
including autism. The brain circuit alterations implicated
in ASD in animal models can now be explored in detail using
these new technologies to map neural connections over
large expanses of brain,
35
record from a large number of
neurons during a behavioral task, and turn on or off specific
types of neurons to understand the nature of brain circuit
alterations caused by biological mechanisms tied to ASD.
18
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
ROLE OF IMMUNE SYSTEM IN BRAIN
DEVELOPMENT AND ASD
Increasing evidence suggests immune dysregulation and
neuroinflammation may be implicated in the severity and
pathogenesis of the autism phenotype.
36,37,38
One recent
meta-analysis of 17 studies identified significantly altered
concentrations of immune regulators known as cytokines
in ASD patients compared to healthy controls, adding to
the evidence of increased inflammatory signals in ASD.
39
Despite many studies demonstrating altered levels of
immune biomarkers and abnormal immune function in both
the peripheral and central nervous system in ASD, it is
not clear whether the immune system plays a direct role
in the development of the disorder via an impairment
of neurodevelopmental processes. Several recent studies
suggest that maternal immunological factors may play
a role in the pathogenesis of ASD during prenatal
development.
40,41,42,43,44,45,46
Microglia are innate immune cells that reside in the central
nervous system and are activated in response to infection
or inflammation. Even in their so-called resting state, they
perform critical functions, including regulating the number
of neural precursor cells,
47
maintaining synaptic organization,
and synaptic pruning (removing excess or underutilized
synapses during development).
48,49
Analyses of autism
brain tissue reveal alterations in genes that control microglial
activation states and an association between microglia
dysregulation and neuronal activity.
50
Evidence from human
postmortem studies have found increased microglia
activation, density, or size in various brain regions.
51,52,53
Animal studies have also shown that microglia-mediated
synaptic remodeling is abnormal in a mouse model of
autism.
54
In addition, an increase in activated microglia in
the amygdala, which plays a primary role in the processing of
emotional reactions, was observed in a subset of human
cases (two out of eight).
55
Further investigation of the role of microglia in animal models
of ASD are warranted based on our emerging understanding
of their role in normal development and potential contribution
to ASD phenotypes. In addition, more studies are needed
to identify the roles of molecules secreted by immune cells
on brain development and function.
19
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
DEVELOPMENT, NATURAL HISTORY, AND
VARIABILITY IN ASD
BRAIN DEVELOPMENT, DEVELOPMENTAL
TRAJECTORIES, AND NATURAL HISTORY
OF ASD
ASD is a developmental disorder, yet most studies of brain
structure and function have focused on data collected
from a discrete ASD population at a specific point in time
or from postmortem brains. More studies are needed
that will enhance our understanding of brain development,
through longitudinal studies that gather imaging data
(using methods such as structural and functional MRI
and electroencephalography) from the same set of subjects
repeatedly over an extended study period. Furthermore,
advances in human imaging technology and longitudinal
study designs may provide an opportunity to better
distinguish true causes from consequences of specific
pathological findings by making it possible to image brain
tissue in live subjects throughout the lifespan. These kinds
of studies will require standardized acquisition parameters
to enable comparability across studies, and robust data
sharing policies should be in place to enable expert analysis
of the data by a variety of computational scientists.
56,577
Although defined behaviorally, the identification of causative
genetic variants has begun to suggest the neurobiological
basis of ASD. Many of these variants have been found
to converge on basic processes in early brain development,
such as cortical organization, synapse formation and function,
the balance between neuronal excitation and inhibition,
and the development of robust, functional neuronal
networks that may impact early perceptual and cognitive
processes.
34,58
These processes may be measured through
functional and structural neuroimaging methods well
before behavioral signs of atypical development emerge.
Historically, research on early markers has focused on
infant siblings of children with ASD, not only because they
are at heightened risk for ASD and other developmental
delays (prevalence estimates of ASD up to 20%), but also
because they are identified prenatally and can be followed
from birth.
59,60,61,62,63,64
This body of research has led to
the identification of atypical behaviors – particularly in the
social domain – within the first years of life,
65
with some
evidence of motor delays
66
and altered patterns of social
attention
67
within the first year.
The brain connectivity changes that underlie autism
are not static; their manifestations appear during the
dramatically dynamic period of brain development and
continue to change over the lifespan of the individual.
Therefore, understanding the biology of autism requires
large longitudinal studies to chart the trajectory of neural
circuits over time, including how they adapt to inborn wiring
errors and environmental exposures. Studies are needed
that include pregnancy and follow maternal exposures and
response, fetal development, and brain response to events
that occur in utero and perinatally. Fortunately, new imaging
techniques may enable safe study of the developing brain
during prenatal development. The genetic and phenotypic
heterogeneity of ASD are daunting, making generalization
of findings dependent upon large numbers of subjects.
Furthermore, the measures in these studies are often
complex and subject to variability in their acquisition or
analysis. This makes them difficult to reproduce and
diminishes their value. To compare among individuals
requires standardization; variability needs to be minimized
and then measured for inclusion in the analysis.
20
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
The Lifespan Connectome Project is one example of
a sophisticated brain imaging study of a large sample
of typically developing individuals across the lifespan.
Methods to examine brain development are now more
powerful, and normative data in typical development are
needed to inform the studies in atypical development.
One such collaborative effort includes the Baby Connectome
Project (BCP), which is a longitudinal study intended to
provide a better understanding of how the brain develops
from infancy through early childhood and the factors
that contribute to healthy brain development. Variables
of interest include patterns of structural and functional
connectivity and their relationship to core behavioral skills
from infancy to early childhood. Additional biological
(e.g., genetic markers) and environmental measures
(e.g., family demographics) are being collected and examined
to provide a more comprehensive picture of the factors
that affect brain development. Study data will be made
available to the scientific community as it is measured.
This knowledge will be tremendously useful in understanding
brain function and how early interventions may shape our
brain throughout our lifespan. Such coordinated efforts,
with standardization of data acquisition and analysis, are
needed in other imaging methods, such as EEG or MEG,
and in the integration of multiple modes of imaging
(structural and functional), particularly as they relate to
later behavior. Ultimately, these studies will lead to the
development of more scalable imaging tools that can be
applied to large, more representative cohorts of infants and
children. Additionally, as ASD manifests during development,
it will be important to understand the critical windows
during which circuit abnormalities may be reversible.
Research has suggested the prenatal period and first years of
life are the critical time period for the onset and development
of autism. Promising results have emerged from the Infant
Brain Imaging Study (IBIS), in which low- and high-risk
(sibling) infants are being examined longitudinally with
structural MRI at ages 6, 12, and 24 months. Differences
in white matter tract development from 6 to 24 months,
particularly a slower change in a measure of fiber density,
have been reported in infants who develop ASD.
68
More
recently, the IBIS Network has identified hyperexpansion
of the cortical surface area between ages 6 and 12 months
in those infants who developed ASD, with brain volume
overgrowth related to autism severity.
69
Another recent
study found that infants who went on to develop ASD
exhibited a significant excess of cerebrospinal fluid
surrounding the brain at 6 to 24 months.
70
These studies
have shown that brain changes can be observed at as early
as 6 months of life, even in children that show a regressive
onset of autism at 18-24 months. At the present time, there
have been virtually no studies in which high-risk children
are studied earlier than 6 months, but this is a challenge
worthy of future research efforts.
Going forward, large, organized longitudinal studies
across the lifespan are needed to better understand
developmental trajectories and natural history of ASD. Early
results underscore the need to track and better understand
longitudinal changes in brain development before autism
symptoms emerge.
68,69
Such measures can help us to
understand the underlying mechanisms of atypical
development and to elucidate the ideal timing and targets
for early interventions. These measures can also link back
to genetic mechanisms implicated in neurodevelopmental
disorders more directly than behavioral assays. However,
new mobile technologies are becoming available to monitor
and quantify behavior over long time periods which should
aid autism research in its integration of behavior with ge-
netics, neuropsychological tests, neuroimaging, and other
measures of biological function. The earliest behavioral and
biological markers of risk, the unfolding of ASD in early
infancy, and the comparison of these developmental
processes in defined genetic syndromes with those found
in familial risk groups remain relatively unexplored and
offer promising avenues for new research. Other key
21
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
questions that can be answered through longitudinal studies
of brain development include how features of ASD change
over time,
71,72
identification of adaptive brain changes in
response to a developmental disturbance, changes that
may be either beneficial or harmful, adaptive changes in
brain function and structure that predict response to
interventions, and developmental changes that inform
core developmental features, such as language or
nonverbal cognition.
PHENOTYPES AND SUBTYPES
Even within genetically determined syndromic ASD, there
is considerable variability in the range and severity of
symptoms. ASD most likely occurs due to a complex genetic
architecture composed of multiple interacting biological
pathways which combine to cause the phenotypic richness
that can be observed even between siblings.
73
In preliminary
studies that require replication, genetic associations have
been found to segregate to some extent with specific
phenotypes such as ASD with and without intellectual
impairment,
3
ASD with motor speech disorder,
74,75
and
other subphenotypes.
76,7
Certain functional and structural
changes in brain circuits are associated with specific
phenotypes. The basic biology of circuits underlying
aggression, anxiety, theory of mind (ability to understand
and reason about the thoughts of others), language
development, attention, and social cognition is still not
completely understood, but fundamental advances would
enable the search for disturbances in persons with ASD to
eventually understand phenotypic variability. To accomplish
this, it is necessary to standardize the classification criteria
and include greater sample size in linking phenotypes to
genetics, brain imaging, and brain tissue examination. In
addition, MRI studies have traditionally been difficult in ASD
individuals with intellectual impairment because of the
requirement to remain still and understand directions in
the MRI scanner; more of these studies have been done on
high-functioning individuals. However, new methodologies
have been developed that capitalize on the large body
of behavioral intervention knowledge that may enable
high-quality imaging in ASD children with intellectual
impairment, thus allowing for imaging studies on cohorts
that are more representative of the heterogeneous
ASD population.
77
Characterizing relevant aspects of heterogeneity is
complex. Some factors, such as biological sex and genetic
contributions, are developmentally stable and represent
viable starting points for constraining and characterizing
heterogeneity. However, within these categories, there is
nested heterogeneity that has not yet been characterized
in a consistent, reliable, or universal fashion. For example,
distinct biological processes may be associated with
cognition, language, social motivation, repetitive behaviors,
or other factors that are challenging to quantify and are
variable across development. Great progress has been
made in developing nuanced and reliable measures of these
constructs, and their integration into large studies of
biology is necessary to elucidate distinct contributors to
varying manifestations of autism. A notable challenge
to autism research is the poor understanding of many of
these factors in typical development; rigorous and
longitudinal approaches to characterization and biological
measurement in control samples are essential
steps to developing a meaningful frame of reference
for understanding atypical development in autism.
A broad challenge to clinical studies is heterogeneity in
the diagnostic entity of autism itself. Rather than a singular
diagnostic construct, autism represents a common
behaviorally defined developmental pathway reflecting
numerous etiologies and an unknown number of involved
mechanisms. Previous studies with small sample
sizes provide limited information and make it difficult
to differentiate between what is true heterogeneity in the
disease mechanism and what is simply variability due to
underpowered statistics, inconsistent approaches, and
diverse methodologies for measuring biological processes.
22
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
It will be important to conduct large studies involving
thousands of individuals with autism with structured
and consistent measurement according to rigorous
methodological standards. For example, the Autism
Biomarkers Consortium for Clinical Trials (ABC-CT)
project is focused on developing biomarkers for ASD
subgroups based on evaluations of brain function, visual
attention, as well as behavior and speech in children aged
6-11. Such studies will enable investigators to determine
the presence of mechanistically meaningful subgroups and,
in the absence of true subgroups, to understand continuous
relationships among biological processes and quantifiable
aspects of the phenotype. It is critical that studies are
designed with longitudinal components that can offer
insight into changes associated with human development
across the lifespan. The National Database for Autism
Research (NDAR) provides a medium for making datasets
publicly available to benefit from the universe of analytic
resources beyond those maintained at individual
laboratories carrying out the research.
BIOMARKERS AND PREDICTION OF ASD
The past few years have seen an increase in large-scale and
longitudinal datasets. This, combined with increasingly
sophisticated analytical techniques, has allowed for a more
refined search for potential biomarkers of ASD. Pre-diagnosis
fMRI response to speech combined with clinical behavioral
measures in toddlers and young children predicted ASD
prognosis.
78
Brain response to social stimuli (biological
motion) accurately predicts whether boys have autism,
but not girls
79
– again highlighting the need for a greater
understanding of the neurobiology of females with ASD.
Potential biomarkers are also being developed to
predict treatment outcome success.
80,81
There have also
been advances in the identification of biomarkers that can
predict autism risk in infants. Utilizing an infant sibling
design, two promising biomarkers have been identified in
infants as young as 6 months of age, including surface area
expansion in specific cortical regions from 6-12 months
of age
69
and the presence of excess cerebrospinal fluid
surrounding the brain at 6-24 months.
70,82
Ongoing work
is using data-driven classification and prediction methods,
which if combined with validation and replication efforts
should further refine and develop these biomarkers.
CO-OCCURRING CONDITIONS IN ASD
ASD is associated with a wide range of co-occurring
conditions that can cause an increased financial
and psychological burden on families and caregivers
as well as decreased quality of life for persons with ASD.
Since 2013, much progress has been made in understanding
the prevalence and underlying biology of conditions that
commonly co-occur with ASD, including gastrointestinal
(GI) disturbances, epilepsy, sleep disorders, psychiatric
disorders, and immune/metabolic co-occurring conditions.
Additionally, more research is needed to investigate the
potential role of these conditions in the underlying causes
of ASD.
GASTROINTESTINAL CONDITIONS
GI symptoms and an inflammatory mucosal pathology
have been demonstrated in several studies of ASD, and it has
been estimated that up to 50% of ASD patients have feeding
and GI conditions.
83,84,85,86
A recent rigorous meta-analysis
23
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
of 15 studies in 2,215 children with ASD indicated a
greater than two-fold elevated risk of GI symptoms among
children with ASD than in those without ASD, and that
children with ASD are more prone to specific symptoms of
abdominal pain, constipation, and diarrhea.
87
Importantly,
many of the genes implicated in autism are also expressed
in the neurons outside of the central nervous system,
including those that innervate the GI system. However,
relatively little is known about autism risk gene functions
in the digestive tract, as well as in sensory perception
and motor function.
88
Genetic changes implicated in ASD
may impact function of both the brain and GI system.
Additionally, alterations in the composition of the gut
microbiome have been implicated as playing a causal role
in ASD pathophysiology. Studies of fecal DNA have found
certain bacterial clusters are overrepresented in children with
ASD and GI complaints compared to neurotypical children
with similar GI complaints, and demonstrate an altered
microbial community with respect to both bacteria and fungi
in ASD.
89,90,91
Current research suggests that disturbances
within the microbiota-gut-brain axis may contribute to
the occurrence and development of ASD and that the
application of modulators such as probiotics, helminths,
and certain special diets may prove useful for the
treatment of ASD.
92
EPILEPSY
Studies have shown that many of the risk genes for epilepsy
and autism overlap.
93
Several studies demonstrate an
increased prevalence of epilepsy in individuals with ASD,
well above the general population risk, and some suggest
that there is an increased risk of epilepsy in females
with ASD when compared to males with ASD.
94,95,96
The largest study to date comparing the autism phenotype
in children with ASD with and without epilepsy found that
children with ASD and epilepsy had significantly more
autism symptoms and maladaptive behaviors than children
without epilepsy.
97
Research in animal models suggests
that early life seizures may result in altered function of
neurotransmitter systems and intrinsic neuronal
properties during neurodevelopment that lead to the
disrupted cortical connectivity that is characteristic of ASD.
98
The PREVeNT trial (Preventing Epilepsy Using Vigabatrin
in Infants with Tuberous Sclerosis Complex) is an
NIH-funded Phase II clinical trial that began in 2017 and
will assess whether anti-epileptic treatment can prevent
development of epilepsy in infants with TSC who display
EEG biomarkers of abnormal brain activity prior to
onset of seizures (NCT02849457).
SLEEP AND SENSORY DISORDERS
ASD is frequently accompanied by a variety of sleep
problems that worsen daytime behaviors and core symptoms
such as stereotypic, self-injurious, and repetitive behaviors.
Studies indicate the prevalence of sleep problems in ASD
are as high as 50-80% and that children with ASD have
higher prevalence of sleep disorders than children with
other neurodevelopmental disorders.
99
The most common
sleep problems reported in ASD are sleep-onset insomnia,
or difficulty initiating sleep, and sleep-maintenance insomnia,
or decreased sleep duration. Several neurotransmitters,
including serotonin, melatonin, and gamma-aminobutyric
acid (GABA) play a vital role in the maintenance of
sleep-wake cycles, and abnormal levels of these
neurotransmitters have been described in ASD.
100
Hyper- and hypo-sensory abnormalities are frequently
observed in individuals with autism and may have negative
impacts on cognitive performance, social interactions,
and stress. Recent work in animal models suggests that
peripheral disorders have widespread impact on behavior
in experimental animals.
88
A question for future research
is whether hard-wired abnormalities that disturb sensory
processing secondarily contribute to alterations in brain
circuits involved in behavioral and social functions.
This may lead to novel ways to therapeutically alter the
developing child’s sensory environment in order to
24
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
improve later-developing social skills. Further, it will be
important to explore whether and how impairments in
sensory processing during infancy may alter early brain
development and contribute to the development of
social and cognitive impairments later in life.
PSYCHIATRIC DISORDERS
It has been estimated that 69% of patients with ASD suffer
from co-occurring psychiatric disorders and symptoms.
101
As with the general population, age appears to be a relevant
factor for psychopathology in patients with ASD. One study
of adults with Asperger’s Syndrome showed that the most
frequent co-occurring conditions were depression and
anxiety disorder, and that obsessive-compulsive disorder
and alcohol abuse/dependence were also observed.
102
Recent studies reveal that consistently high levels of
psychological symptoms and distress occur across the
adult lifespan in ASD, where individuals with more severe
depression and anxiety disorders demonstrated more severe
ASD symptoms.
103,104
At the molecular level, one study
suggests that a variation in the serotonin 2A receptor gene
may modulate the severity of depression symptoms in
children with ASD.
105
RESEARCH POLICY ISSUES
A major challenge for the biological sciences is to utilize
the most sophisticated technologies that produce ever-
enlarging data sets while still ensuring the rigor and quality
of research.
106
Moving forward, the field should embrace
policies that enhance the replicability of findings and promote
transparent reporting of experimental methods, use of
common data elements, and sharing of data and analysis
tools. Follow-up validation studies are a necessary part of
this process, and data sharing should be integrated into
the design of studies from the beginning. The National
Institute of Mental Health NDAR platform is a valuable
repository for high-quality ASD data, tools, and
methodologies that researchers should leverage to
enable re-analysis of data and facilitate collaboration
to accelerate research progress.
Larger longitudinal studies require coordination among
research centers and a shift in focus toward team science
across multiple disciplines. The coordinated collection and
analysis of valuable imaging, behavioral, genetic, pheno-
typic, and iPSC data can be enhanced by the recruitment
of a more diverse workforce that includes not only
neuroscientists, immunologists, and psychiatrists, but also
experts in bioinformatics, machine learning, and behavior
monitoring device engineers.
The inclusion of persons on the autism spectrum in research
plans and messaging is crucial to identifying practical
applications for improving the quality of life for ASD patients
and their families. Standard methods for behavioral
measurements and tracking quality of life across the lifespan
are essential for addressing prescient issues supporting
individuals with ASD in their daily lives.
25
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
SUMMARY
Significant progress in understanding the biological basis of
autism has been made, but considerable challenges remain.
Though there is a desire to demonstrate the impact of
treatment on brain function, fundamental research that
will allow us to fully understand the importance of alterations
in brain function on development is needed. Basic science
on the underlying biology of ASD continues to be critical
to provide the foundation for translational advances that
will lead to effective treatments.
26
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVES
OBJECTIVE 1: Foster research to better understand the processes of early development, molecular
and neurodevelopmental mechanisms, and brain circuitry that contribute to the structural and
functional basis of ASD.
Examples:
Identify neural circuit abnormalities that occur in significant groups of ASD individuals.
Understand the role of the immune system and metabolic processes in ASD, including aspects such as the fever effect
(behavioral improvement coincident with fever).
Identify quantitative and reproducible biomarkers or behavioral monitors for ASD of utility in assessing effectiveness
of future therapeutic or behavioral intervention trials.
OBJECTIVE 2: Support research to understand the underlying biology of co-occurring
conditions in ASD and to understand the relationship of these conditions to ASD.
Examples:
Determine the molecular basis of epilepsy in ASD.
Determine the impact of GI dysfunction on ASD related behaviors and cognitive performance.
Determine the impact of sleep disorders on ASD related behaviors and cognitive performance.
Determine the relationship of co-occurring psychiatric disorders to ASD and their impact on the health
and well-being of people with ASD.
OBJECTIVE 3: Support large-scale longitudinal studies that can answer questions about the
development of ASD from pregnancy through adulthood and the natural history of ASD across
the lifespan.
Example:
Support the creation of large cohorts, characterized both phenotypically and genetically through the collection of
autism-relevant exposure data and medical data on the parents and child from the prenatal period to adulthood.
27
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION
QUESTION
3
WHAT CAUSES ASD, AND CAN
DISABLING ASPECTS OF ASD BE
PREVENTED OR PREEMPTED?
29
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Aspirational Goal: Causes of ASD will be discovered that inform diagnosis,
prognosis, and interventions and lead to prevention or preemption of the
challenges and disabilities of ASD.
INTRODUCTION
Since the last Strategic Plan update published in 2013,
there have been substantial advances in the understanding
of factors that contribute to a diagnosis of autism spectrum
disorder. Few would dispute that the causes of ASD are
many and include both genetic and environmental
factors. There has been an increased appreciation in the
last five years of the incredible complexity and interplay
of these factors in the development of autism. Indeed,
modifications in more than 100 genes are now known to
increase the probability of an autism diagnosis
1,2
and very
reasonable predictions are that 1,000 or more autism risk
genes may ultimately be identified.
1
A plethora of potential
environmental challenges have also been associated with
autism, although studies in this area have not undergone
the same exponential progress as genomics research.
There has also been increasing emphasis on events during
pregnancy, such as influenza infection, as potential causes
of neurodevelopmental disorders. But, these studies have
raised the interesting issue that environmental risks affect
different people differently. This is the so-called “genes by
environment” interaction. More and more modern medical
problems are linked to the combination of a particular
genome and a particular life history of environmental
exposure (the exposome).
The title of this chapter, which has been modified from
the 2013 Strategic Plan Update, emphasizes the desire to
understand the causes of the disabling aspects of autism
spectrum disorder. These go beyond the core symptoms
of deficits in social communication and the occurrence
of restricted patterns of behavior or interests to include
what are typically referred to as co-occurring symptoms.
In many cases, progress on the causes of these co-occurring
symptoms is ahead of that for the core symptoms
of autism. There is a growing appreciation that the causes
of these medical problems urgently need to be addressed.
They may be due to biological factors that are also causal
of autism, manifestations of autistic behavioral problems
such as poor diet that may lead to medical issues, or
medical access issues which lead to poorer medical care.
Regardless of the causes, this is a clear gap in autism
research and intervention and urgently needs additional
research attention and efforts at resolution.
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
30
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
The title to this chapter has changed (from “What caused
this to happen and can it be prevented?”) because the
neurodiversity movement has had a great impact on the
IACC and on the premises of the Strategic Plan enterprise.
It is fully appreciated now that some features of autism
should not necessarily be targets for prevention. As discussed
above, it is the most disabling features of autism that
are now the major targets of prevention or preemption.
Discussions of the causes of ASD always ultimately touch
on efforts at prevention. In the hypothetical situation that
a known cause of autism is identified, the question arises
whether the cause should be eliminated thus preventing
some cases of autism. If the discussion were related to
cancer, the answer would be clear. But, in autism it is not.
There is clearly an increased sensitivity to any procedure
or practice that would be directed at preventing the
totality of autism, and this is reflected in the emphasis
of this chapter.
GENETIC RISK FACTORS
The application of genomic studies has significantly advanced
the understanding of genetic risk factors for ASD. Dozens
of new ASD susceptibility genes have been identified over
the past 5 years and genome-wide technologies have
facilitated a molecular diagnosis in ~5-40% of ASD cases.
This range in the rate of detection depends on the group
of subjects examined and the technology used. Studies
comparing individuals with ASD to typically developing
individuals have indicated that as much as 7-8% of people
with ASD carry either a large pathological DNA deletion
or duplication.
3,4,5,6
Earlier results from DNA sequencing
studies have further confirmed the role of gene-disruptive
mutations in ASD,
7,8,9,10
and more recent data also
support and add to these findings.
11,12,13
The rates of de novo
(new, spontaneous, non-inherited) likely gene-disruptive
(LGD) and missense mutations (which result in amino
acid changes) are significantly higher in individuals with
ASD compared to their unaffected siblings (while the rate
of mutations which do not alter amino acid sequence or
biology does not differ).
12
As much as 21% of autism
diagnoses may be accounted for by de novo single-nucleotide
variant (SNV) and insertion/deletion mutations.
14
Additionally, inherited LGD mutations have been found
to show a preferential transmission from mothers to sons,
indicating another potential risk factor contributing to an
estimated 8% of autism diagnoses.
15
Recent whole genome
sequencing studies of a large diverse ASD collection revealed
a molecular basis in 11.2% of participants, including the
finding that 7.2% carried copy number variations (CNVs;
repeated sequences in the genome that vary between
individuals) or chromosomal abnormalities,
16
which further
emphasize the need to use comprehensive genomic
technologies.
17
Overall, a consistent observation emerging
from genomic studies is the vast genetic heterogeneity
involved in ASD.
18,19,20
Follow-up evaluation of individuals with ASD who have
disruptive mutations to the same gene or genomic region
has further illuminated features and patterns of behaviors
(sub-phenotypes) linked to these genetically defined
subgroups. Clinical characterization of cohorts with
disruptive gene mutations has revealed real, but subtle,
phenotypic patterns tied to particular genes. Patterns of
behavior linked to sub-phenotypes can prove helpful for
establishing guidelines of care for clinicians. While major
advances have been made through the application of genomic
technologies, gaps exist in our understanding of the
contribution of regulatory and other genomic regions to ASD
risk. Whole genome sequencing will begin to illuminate
the role of non-gene coding regions of the genome.
31
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
HERITABILITY
ASD is highly familial, so that siblings of children with autism
are 10-20 times more likely to receive an ASD diagnosis
themselves than non-siblings.
21,22,23
Twin studies beginning
in 1977
24
have provided significant evidence that ASD is
strongly associated with genetic factors. All 13 twin studies
on autism to date have found genetic and environmental
contributions to autism, although the proportions of the
two factors and interpretations have varied substantially.
One research team,
25
for example, concluded that over
50% of the risk for autism in identical twins could be
explained by shared environmental factors, whereas
genetic heritability accounted for 37%. This somewhat
surprising finding—that environmental factors contribute
more substantially than genetics—has been challenged
by a more recent, large-scale twin study,
26
which found
that the largest contribution to autism liability comes from
additive genetic effects. A recent meta-analysis concludes
that the causes of autism are due to strong genetic effects,
and that shared environmental influences are seen only if
the most severe forms of autism are included.
27
A recent
survey of autism twin studies finds that concordance
for monozygotic twins is roughly 45%, versus 16% for
dizygotic twins.
28
Thus, twin and family data suggest that
genetic variation between people accounts for a very
substantial portion of the liability to ASD at a population
level. But, if autism had a completely genetic etiology, we
would expect a much higher concordance (or shared ASD)
rate in monozygotic twins; the lower rate may reflect, in part,
that even monozygotic twins do not share an identical
environment prenatally.
GENOMIC ARCHITECTURE
The recent successes in ASD genetic studies have confirmed
the importance of genetic risk factors. Similar to other
common psychiatric disorders, the genomic architecture
of ASD is complex, involving both common and rare forms of
genetic variation,
29
including common polygenic (multi-gene)
variation, de novo variation, copy number variation, and
inherited rare variation.
11,12,15,19,30,31,32,33
Common polygenic
variation may account for the greatest fraction of genetic
influence, and approximately 20-50% of population liability.
De novo variation accounts for less liability at a population
level, but can have a very strong impact on the individuals
who carry such variants.
12,32
These data represent population
risk; a crucial next step is integrating our understanding
of rare variants of large effect with more common
polygenic risk factors to more accurately predict ASD
on an individual level.
SEX DIFFERENCES
The overrepresentation of males among those diagnosed
with ASD has been observed for decades.
34,35,36
Overall, the
male to female (m:f) ratio is approximately 4:1, but that
ratio varies substantially based on IQ and other features
of ascertainment.
34,37,38
Specifically, in individuals with
ASD and very low IQ, the male:female ratio is commonly
estimated at 2:1 or 3:1; in individuals with ASD and high IQ,
the m:f ratio becomes very large, often 7:1 or greater. This
pattern has been consistently observed during the period
of otherwise rapid changes in the epidemiology of ASD.
There are several theories as to why males and females
might differ in their observed ASD liability.
36
Among
biological theories, the extreme male brain hypothesis posits
that the male brain is predisposed to many features that
are on the ASD spectrum.
39,40
The ‘female protective effect
(FPE) hypothesis in ASD is amongst the most commonly
investigated in recent genomics studies.
41
The FPE hypothesis
suggests that females are ‘protected’ from ASD
(for unspecified reasons) such that, on average, a greater
number of risk factors (or genetic “hits”) is necessary for
a girl to gain a diagnosis of ASD. In the context of de novo
and gene-disruptive inherited variation, that suggestion has
been supported by the recent genetics literature.
6,12,15,42
Deleterious CNVs are three times more likely to be
identified in autistic females when compared to males,
42
32
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
and loss-of-function mutations show a maternal transmission
disequilibrium suggesting mothers are more likely to be
carriers of such mutations than fathers.
15
Similarly, classes
of de novo variation that are strongly associated with ASD
risk are approximately twice as likely to be observed in
female cases, as compared to male cases. Recent gene
expression analysis demonstrates that autism risk genes,
rather than being sexually dimorphic themselves, interact
with pathways and cell types that themselves are
sexually dimorphic.
43
OVERLAP WITH OTHER DISORDERS
Neuropsychiatric and developmental disorders share many
genetic risk factors, and this varies depending on the specific
disorders being compared.
30,44,45
ASD shares common
risk genes with other neuropsychiatric disorders such as
schizophrenia,
46,47
and autism is sometimes a feature of
other neurodevelopmental syndromes such as Fragile X
syndrome, Rett syndrome, tuberous sclerosis, and Phelan
McDermid syndrome.
48,49,50,51
The common, polygenic
influences on ASD risk are similarly associated with multiple
phenotypic outcomes (different combinations of risk genes
can lead to different neuropsychiatric and developmental
conditions). In recent studies, and in contrast to the de
novo findings, common polygenic risk for ASD has been
positively associated with general cognitive ability, logical
memory, and verbal intelligence.
52
On average, ASD shares
most risk with schizophrenia in the population, followed
by bipolar disorder, but very little with substance abuse
or major depression. It does not appear that this overlap
involves the majority of common genetic risk for each
disorder, and the extent to which overlap occurs, and what
biological factors it represents, remain under investigation.
Rare familial mutations that cause syndromic ASD and
de novo (spontaneous) genetic influences on ASD risk are
also strongly associated with intellectual disability,
epilepsy, and global developmental delay;
12,53
neurological
co-occurring conditions are identified in the majority of
children with ASD.
54,55
Some of the ASD-associated de novo
events that result in problems in protein production are
more likely to be seen in cases of intellectual disability than
in ASD itself.
56
Similarly, several CNVs that increase risk
for schizophrenia also increase risk for ASD.
57,58,59,60,61
This is consistent with these mutations having major
effects on brain development, which subsequently can
manifest as different clinical outcomes. However, there
are many intellectual disability genes that do not appear
to increase risk for ASD.
62
So, understanding why some
large-effect mutations that cause intellectual disability
substantially increase risk for ASD, while others may not,
remains an area of future investigation.
63
GENETIC TESTING AND COMMUNICATION
OF RISK
Genetic testing is recommended by the Accreditation Council
for Graduate Medical Education for those at increased risk
for ASD.
64,65
This includes chromosomal microarray (CMA)
followed by Fragile X testing and other specific tests
depending on the symptoms that are observed. Several
studies review the current recommendations for genetic
testing in ASD.
55
In addition to its usage in research studies,
whole exome sequencing (WES) has been shown to have
a high yield in clinical populations with developmental
disorders including ASD. Thus, we expect that WES will
gradually supplant CMA.
66,67
Given the incomplete penetrance of many large effect
or familial genetic risk factors, care must be taken in
pre-symptomatic or prospective risk counseling. Further
understanding of the causal relationship between identified
ASD risk genes and clinical outcomes is needed before
guidelines for genetic counseling can be illuminated.
Understanding parental concerns and attitudes when
communicating complex genetic information that has
an impact on family planning is also important.
68,69
33
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
NEW LARGE-SCALE GENETICS STUDIES
LAUNCHED IN THE LAST 5 YEARS
Studies of the genetic architecture of ASD have resulted
in the appreciation that much larger groups of subjects are
needed to fully understand its complexity. In the last
5 years, several large-scale projects have been initiated.
Recent large-scale efforts include MSSNG (funded by
Autism Speaks), which seeks to sequence the genomes
of 10,000 individuals affected by ASD, and the SPARK
study (funded by the Simons Foundation), which seeks to
sequence exomes of 50,000 families affected by autism.
These studies are expected to not only identify additional
autism risk genes but to also contribute to an understanding
of the common variant patterns that enable expression
of the mutations.
POLICY IMPLICATIONS OF ADVANCES
IN GENOMIC SCIENCE
New technology and testing can also lead to increases
in healthcare disparities; we must be vigilant to avoid this
and support policies that enable access to all. Because of
differences in population histories, understanding
of genetic risk in one population may not be informative
in others. This imparts an imperative to study diverse
populations. Further, given the role of rare variants that
will have very distinct frequencies in different populations,
having information from diverse populations will be
critical for the interpretation of genetic studies. When
predictive testing is performed, care must be taken to
ensure accurate prospective/predictive testing and that
information about accurate probabilities of particular
outcomes are communicated effectively and not mistakenly
understood as absolutes. This requires genetic counselors
or other professionals trained specifically in the
communication of genetic risk to patients. This will be
an increasingly important manpower issue as genetic
information expands over the next decade.
34
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
ENVIRONMENTAL RISK FACTORS, INDIVIDUALLY
AND IN COMBINATIONS OVER TIME
The growing number of studies that are exploring
environmental risk factors reflect an emerging consensus
that non-genetic avenues of research are also likely to
bear fruit. In this Strategic Plan, it is advantageous for
the IACC to adopt a broad definition of studies on
“environment” as encompassing research on all potentially
non-heritable etiologic influences. This includes studies
of exogenous exposures such as pesticides, endocrine
disrupting and other industrial chemicals, pharmaceuticals,
heavy metals, infectious agents, dietary factors, as well
as other factors, such as parental age, maternal medical
conditions, birth complications, and time between
pregnancies. Some of these “environmental” factors
might themselves be genetically influenced, while others
might be mediating the effects of exogenous exposure.
PREVENTION OR AMELIORATION OF
DISABLING ASPECTS OF ASD
Research on environmental contributors to ASD should
routinely collect and make use of data on specific ASD
symptoms, the levels of symptoms and impairment, as well
as co-occurring conditions. As linkages between exposures
and specific impairing aspects of ASD are revealed, public
health strategies can be tailored to prevent or mitigate
these features by reducing harmful exposures and/or
increasing factors that confer protection or resilience.
Additionally, improved understanding of what role
environmental factors play in ASD severity (including
risk for co-occurring conditions) might eventually inform
strategies for identifying children in need of specific
types of early intervention services.
SUSCEPTIBLE PERIODS DURING
DEVELOPMENT
The concept of windows of susceptibility, a central principle
in environmental health sciences, is relevant to studies
of environmental risks in ASD. Many lines of evidence
point to prenatal origins of ASD.
70,71,72,73,74,75
In addition,
very large epidemiological studies link maternal bacterial
or viral infection during specific times of pregnancy to
increased risk for ASD in the offspring.
76
The periods of prenatal development that are most relevant
to environmental risks for ASD are incompletely understood,
however, and may be dosage- and/or exposure-dependent.
77
When considered together, many existing ASD studies
suggest that preconception and early gestation are
vulnerable periods for environmental exposures. This has
been supported by previous reports linking autism symptoms
to maternal ingestion of drugs such as thalidomide
78,79
and valproic acid.
79,80
Other factors associated with ASD
risk include preterm birth,
81,82,83,84
advanced maternal and
paternal age at conception
85,86,87,88
and short inter-pregnancy
interval.
89,90
In addition, the preconception/periconception
period may be critical for the observed association of
decreased ASD risk with maternal folate intake.
91,92
A few of the studies on air pollution exposure
suggest an enhanced risk in the later part of pregnancy.
93,94
Evidence from the broader neurotoxicology literature
95
also indicates that exposures in the late prenatal and early
postnatal periods can exert significant effects on a wide
range of brain and behavior phenotypes during the first
years of life. All of these time windows cover critical stages
35
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
of rapid brain development and are also characterized
by immaturity of both the immune system and metabolic
detoxification mechanisms. These features combine to
offer vulnerability and provide biological plausibility for
environmental impact on ASD risk extending from
preconception into the early postnatal period. Additional
attention to the timing of exposures relative to the cascade
of events that unfold during brain development is needed
to identify and understand the molecular basis of
exposure-associated ASD risk. With this in mind, study
designs and biomarkers of exposure should be chosen
to capture prenatal and early life exposures.
STUDIES IN LARGE AND DIVERSE
POPULATIONS
While the number of ASD epidemiology studies and
the resulting data are growing through efforts such as the
Early Autism Risk Longitudinal Investigation (EARLI) and
Markers of Autism Risk in Babies-Learning Early Signs
(MARBLES), most potential environmental risk factors
have not been investigated sufficiently to draw firm
conclusions.
96
The limitations inherent to observational
studies mean that multiple studies in different populations
and settings, with high-quality measures of exposure
and adequate controls, are needed to reconcile disparate
findings and establish robust linkages of an environmental
exposure to ASD risk. The likelihood that many different
factors, each with modest effect, will contribute to ASD
means that large sample sizes may be needed to detect
associations with exposure, especially for those
exposures with low prevalence.
Under-represented minority communities and low-income
communities often face disproportionate exposure to
harmful environmental chemicals;
97,98,99
additional attention
is needed to ensure that these populations
are represented in ASD research and that disparities in
environmental risk factor exposure are addressed.
Inclusion of these vulnerable population subgroups in ASD
studies may, in some regions, be particularly challenging
when studies recruit from young children with a past
ASD diagnosis. Data from the Autism and Developmental
Disabilities Monitoring (ADDM) Network indicate that
non-Hispanic black (NHB) children are significantly less
likely than non-Hispanic white (NHW) children to receive
an early comprehensive developmental evaluation,
100
and
Hispanic children are less likely to receive an ASD
identification by age 8 in comparison to NHW and NHB
children. These findings underscore the need to carefully
consider case ascertainment strategies that do not rely
solely on previous ASD diagnosis in designing studies
of ASD risk factors.
Given the clear differential in ASD risk in males and females,
studies which examine risk and protective factors within
sex-specific subgroups are especially important. However,
given the lower ASD prevalence in females, nearly all studies
to date have not had a sufficient sample of females to
conduct such analyses. Thus, additional efforts are needed
to increase representation of females in ASD studies to
enable meaningful analyses of sex-specific differences
and the role of both genetic and environmental factors in
affecting those differences. The Environmental Influences
on Children’s Health Outcomes (ECHO) initiative of the
National Institutes of Health is combining data from more
than 78 cohorts comprising approximately 50,000 children
and 40,000 women. Although the extent of ASD-related
measures that are, or will be, included in ECHO has not yet
been established, this initiative represents an exceptional
opportunity to study ASD-related traits in large and
diverse populations.
36
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
EXPOSURE SCIENCE
One of the most significant obstacles facing
epidemiologic studies of environmental risks for ASD
is exposure assessment. In many studies, exposure
measures are not readily available for very early
developmental periods and rely on indirect methods
(e.g., participant recall of prior exposures), or utilize
one or two biologic measurements of compounds with
very short half-lives. Direct exposure assessment,
such as through personal monitoring or use of an adequate
time-course of exposure biomarkers, is expensive
and burdensome for participants. Consequently,
deep characterization of exposure during etiologically
relevant time periods is typically limited to studies with
small numbers of participants, yielding low power.
The recent development and application of the concept
of the “exposome”
101,102
represents a key advance that
could accelerate progress in identifying environmental risks
for ASD. The concept of the exposome calls attention to
the totality of exposures across an individual’s lifespan.
103,104
In addition to the universe of external environmental
factors, the exposome concept can be extended to include
endogenous biomarkers of exposure response – internal
exposures that originate from metabolism and other cellular
processes – as well as more general external factors that
constitute social determinants of health. Measuring the
exposome comes with challenges in capturing and
integrating many individual measures over time. Recognizing
that no single approach or tool likely will suffice, the field
is embracing a multifaceted strategy, using multiple
tools to help characterize the exposome. For example,
use of personal sensors and mobile devices can be harnessed
to capture many aspects of the exposome in real time.
Refinement of more targeted, conventional exposure
assessment tools also has a place in characterizing
the exposome.
General “omics” approaches such as transcriptomics,
proteomics, metabolomics, and epigenomics show
promise in identifying molecular response profiles that
can be linked to exposures,
105,106,107
and in some cases,
these profiles persist over time. These downstream
biomarkers may suggest groupings of exposures that
operate by similar pathways. Linking direct measures of
either individual or classes of exposures or the broad
exposome with early “omic” markers of biological response
in both targeted and non-targeted data analyses can
provide complementary information of potential
etiologic relevance.
Because exposomic approaches have the potential to
generate high-dimensional exposure data, discovery-based
analytic methods analogous to those being used in
genomics can potentially be applied to uncover novel
environmental risk factors – ones that would be missed
by approaches that focus on a small number of established
or suspected neurotoxicants. An exposomic approach also
is well-suited to the simultaneous consideration of multiple
exposures and risk factors; although, as the genomics field
has learned, very large samples are needed to achieve
significance in these kinds of analyses.
37
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
LINKAGES BETWEEN GENES AND ENVIRONMENT
GENE AND ENVIRONMENTAL STUDIES
Despite general agreement that both environment and
genetics contribute to ASD risk, only modest progress has
been made in identifying gene-environment interactions.
A few epidemiology studies, such as the Childhood
Autism Risk from Genes and Environment (CHARGE)
study, have reported an interaction of exposures with
common or rare structural genetic variation.
92,108,109,110,111
However, each study focused on different combinations
of exposures and genes, they lack independent replication,
and two of these studies addressed severity of symptoms
rather than impacts on incidence.
108,111
Many large ASD
genetic collections have been assembled but most include
minimal or no exposure information. On the other hand,
studies focused on environmental risks often feature deep
exposure assessment and have incorporated some genetic
information, but smaller sample sizes constrain the power
of gene-environment interaction analyses.
A major gap has been identified and a concerted effort is
needed to enrich existing, ongoing ASD studies by adding
genetic data collection to environmental studies and
exposure measures to genetic studies. Identifying and
accounting for genetically driven effects on exposure levels
is critical for interpretation of ASD-exposure associations.
In the autism literature, it is notable that the genes
implicated in the folic acid association with decreased
ASD risk have not emerged in any of the genetic studies
using genome-wide screening. Only in mothers who had
low folic acid intake do those one-carbon metabolizing
genes appear to play an etiologic role.
109
At this stage, it
appears that the presence of a ‘main effect’ (a risk factor
not dependent on another factor) is not always detectable
and that investigation of interacting factors should not
require that a main effect of a specific environmental
factor or gene/SNP be known.
Availability of low-burden exposure measures that
can be incorporated in large-scale genetic studies, perhaps
leveraging innovations in exposomics or epigenomics, is
a high priority. Once these data exist in concert in large
sample sets, new statistical and analytic approaches for
gene-environment discovery in human population research
can be applied.
112
Polygenic risk scores have seen increasing
use in complex disease studies and can yield improved
efficiency for detecting interaction of genetic risk with
candidate environmental exposures. The construction of
a “polyenvironment” score, analogous to a polygenic risk
score, could be explored to summarize information from
several exposures thought to be acting through common
mechanisms for use in genetic/genomic studies. Other
approaches might include measures of genomic instability
such as global copy number burden, used in two different
gene-environment interaction studies.
111,113
MECHANISMS OF ENVIRONMENTAL RISK
AND GENE-ENVIRONMENT INTERACTION
Increasing knowledge of genetics has led scientists to
understand gene pathways that affect neural circuits
rather than single genes acting in isolation. Early studies
have demonstrated the convergence of genetic influences
and environmental factors in the activity of these different
gene pathways,
114
providing evidence that genes and
the environment might work synergistically, rather than
additively. Studies that move beyond identification of
genetic and environmental risk factors to reveal functional
biological consequences associated with these risk factors
are a priority. Epigenomics, metabolomics, transcriptomics,
and proteomics can provide useful functional readouts
for this purpose.
38
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Model systems provide an attractive means for supporting
causality and understanding biological mechanisms that
underlie associations observed in human studies. Human
induced pluripotent stem cells (hiPSCs) generated from
individuals affected by ASD with a known genetic background
are being used increasingly to study ASD.
115
These provide
a unique opportunity to assess susceptibility of early
developmental processes to environmental chemicals in the
context of defined genetic risk.
116
There are a few reports
of screening or computational approaches used to identify
possible environmental exposures that could be priorities
for pursuit in human studies.
114,117
The Collaborative Cross
and Diversity Outbred mouse populations
118
represent
important mouse resources that could be harnessed to
dissect the contribution of environment to complex
disorders such as ASD. Additional efforts that bring
together interdisciplinary teams to facilitate integrative
analyses and bidirectional flow of clues from human
observational studies to laboratory-based experiments
in model systems are warranted.
In addition to the utility of epigenomics (the study of
the complete set of epigenetic modifications – such as
methylation – on the genetic material of a cell) as easily
attainable exposure biomarkers, many researchers
recognize the potential for mechanistic roles in ASD.
Epigenomics is a leading candidate for mediating effects
of exposures on regulation of transcription (the first step
in gene expression)
119,120,121
and could provide a point of
convergence for genes and environment in autism risk.
Multiple lines of evidence implicate altered epigenetic
marks in ASD etiology. Several known genetic disorders
with ASD-related presentation, such as Fragile X and
Angelman syndrome, have established epigenetic
mechanisms. Further, results from rare-variant ASD genetic
discoveries point to remodeling of genetic material as
a shared pathway in ASD genetic risk. Few studies have
directly examined chromatin marks or DNA methylation
for association with ASD, but some small studies have
observed associations.
105,122,123
A significant body of work demonstrates that environmental
chemicals can alter DNA methylation, and these alterations
have been linked to changes in gene expression and a
range of behavioral phenotypes.
124,125,126
ASD studies that
integrate methylation, exposure, and phenotype data in
the same population are a priority. Research to establish
whether epigenetic marks measured in peripheral tissues
are predictive of changes in target tissues is especially
important for interpretation of human studies.
127
Also needed
are studies that identify exposure-induced impacts on a
full range of epigenomic mechanisms and that determine
their relevance to ASD. Finally, research to understand
how exposure-induced epigenomic changes may transmit
autism risk across generations is warranted.
MULTIVARIATE RISK ACROSS COMPLEX
SYSTEMS
There is a need to capitalize on findings emerging from
existing studies to examine how genetic and environmental
factors interact to contribute to phenotype, not only at
the molecular and cellular level, but also in the broader
physiological context. For example, a substantial body of
work implicates immune dysregulation in ASD, including
the association of ASD with maternal infections and
autoantibodies, cytokine and other immune biomarker
signatures, functional alterations in immune cell subsets,
128
and differential expression of innate immune and
inflammatory genes.
129
These findings together have
motivated studies exploring how a range of environmental
exposures may contribute to the immune alterations observed
in ASD, some of which have been detectable at birth.
130
The endocrine system is another promising area of
inquiry. The established role of hormonal systems in brain
development, the marked male bias in ASD, and a growing
recognition that many environmental chemicals act as
endocrine disrupting chemicals (EDCs) sets the stage
for investigations exploring possible links between ASD
and EDCs.
131
Some research studies have suggested that
39
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
factors that protect females from autism risk may be found
on hormone-sensitive genes,
132
and these could be targets
for EDCs. Further work elucidating connections across
metabolic, hormonal, and central nervous systems in the
context of EDCs is needed.
The microbiome (the combined genetic material of the
microorganisms in the body) represents a third priority area
of inquiry. There is increasing evidence for links between
the gut microbiome, brain, and behavioral phenotypes
relevant to ASD.
133,134
The microbiome is also emerging as
an important component of response to environmental
exposure. Studies have demonstrated persistent changes in
the function of the microbiome after exposure to immune
activation and environmental chemicals,
135,136
particularly
during early life when the microbiome is being colonized.
A role for the microbiome in metabolism of environmental
chemicals is now established.
137,138
This means that
differences among individuals in microbiome composition
can affect the internal dose and biotransformation of
toxicants and act as susceptibility factors. Small clinical
studies using antibiotics or microbiome transplant support
a potential role for microbial imbalance in contributing to
the cause of core ASD behaviors. Taken together, these
data suggest possible linkages among exposures, microbiome
function, and ASD phenotypes. This is an area that has
only begun to receive research attention which should be
expanded in the foreseeable future.
BROAD DATA AND RESOURCE SHARING
As the number of studies focusing on environmental
risks for ASD increases, attention to broad data access and
sharing becomes critical for enabling reuse and extracting
the maximal value from the data that have been collected.
Consideration of privacy and consent issues in environmental
health data is needed to ensure the development and
implementation of policies that protect privacy while
ensuring the value of shared data. Combining data across
observational studies can yield increased power and
strengthen generalizability, yet heterogeneity of the types
of exposure measures used creates challenges for both
meta-analyses and pooled analyses of primary data. On the
other hand, when different types of measures of exposure
in different studies all lead to consistent findings, that
consistency alone increases confidence in the conclusions.
The development of consensus data standards will make
it possible for investigators to consider, at the outset of
a study, inclusion of common environmental measures/
standards.
139
Use of low burden exposure measures,
such as those available through PhenX
140
or the Early Life
Exposure Assessment Tool (ELEAT), enable genetics
researchers to enrich their analyses to account for
environmental contributions to risk. Increased sharing
of study-specific exposure instruments and methods
is another area of need. The National Database for
Autism Research (NDAR) currently provides a robust
platform for making data – particularly data in standard
formats – easy-to-find and accessible. Implementing
common data standards for exposures could facilitate
the incorporation of these type of data in NDAR.
RESOURCES TO ACCELERATE ENVIRONMENTAL
RISK AND GENE-ENVIRONMENT RESEARCH
40
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
In addition, genetic databases including MSSNG and the
Autism Sequencing Consortium (ASC) are anticipated to
provide mechanisms for expanded data libraries to include
key environmental variables, allowing for assessment of
gene-environment interactions. Recent findings
108,111
illustrate the benefits of incorporating environmental
information in large data resources. With regards to
mechanistic tools, new models of ASD, especially those
with distinguishing genetic mutations of interest, should
be made widely accessible to researchers. This can
include, but is not limited to, sharing breeding pairs of
animal models with commercial vendors for their widespread
distribution. Finally, to realize the potential impact of data
sharing, efforts must be put into the analytic approaches
needed to make gene-environment discoveries from the
aggregation or collective analysis of large heterogeneous
data sources. Efforts that encourage methodological
development as well as bioinformatics implementation
and secondary data analysis funding will be necessary.
INTERDISCIPLINARY TRAINING AND
CAREER DEVELOPMENT
The workforce needs related to environmental research
in ASD align with an increasing recognition that solving
complex questions will require team science approaches.
Programs and opportunities that train scientists and
support research and networking programs in ways that
encourage crosstalk and coordination of efforts spanning
cellular and molecular neurobiology, toxicology, genetics,
epidemiology, and exposure science are needed. Training
opportunities should be created around novel statistical
and big data approaches geared toward complex exposure
data, with the goal of accelerating analyses that address
multivariate risk.
PUBLIC HEALTH IMPLICATIONS
COMMUNICATION AND DISSEMINATION
ACTIVITIES FOR ENVIRONMENTAL
RISK FINDINGS
The multivariate risk structure of ASD, with many factors
contributing modest risks, and different combinations of
risks likely to operate in different individuals with ASD,
presents challenges for communicating findings to affected
families and the broader public. Epidemiologic studies
that report associations of specific exposures with ASD
at the population level can lead to serious misinterpretation
if extrapolated to individual cases, and a focus on individual
risks can mask the importance of exposures whose
modification could have substantive impact when measured
across the population. Moreover, the limitations inherent
to observational studies means that results of a single
study require additional independent studies for replication
and assessment of generalizability. Conflicting findings
among studies are common, and may reflect spurious
results or an unappreciated dependency of the association
on other factors. Additionally, it is particularly difficult to
separate the effects of some exposures from other factors,
due to inherent collinearity – for example, distinguishing
true medication effects from effects due to the underlying
health condition for which medication was required.
For these reasons, communicating environmental and
genetic findings in ASD requires careful attention to context,
including providing information about the strength of any
newly reported finding on the scale most appropriate for
the audience, the difference between cause and association,
41
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
the specific potential limitations of any individual study
including the possibility of unmeasured confounding, the
population attributable risk, and the need for additional
studies to confirm the association.
SUMMARY
In many cases, risk factors for ASD are shared by other
disorders, and additional research is needed to ensure that
corresponding public health efforts will have broad
utility for protecting health beyond the implications for
autism. The hope of identifying and understanding
ASD risk factors is that they can be mitigated to reduce
ASD-related disability.
42
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVES
OBJECTIVE 1: Strengthen understanding of genetic risk and resilience factors for ASD across the
full diversity and heterogeneity of those with ASD, enabling development of strategies for reducing
disability and co-occurring conditions in ASD.
Examples:
Understand the contribution of regulatory and other genomic regions to ASD risk. Whole genome sequencing will
begin to illuminate the role of non-gene coding regions of the genome.
Identify additional autism risk genes but also contribute to an understanding of the common variant patterns that
enable expression of the mutations.
Understand the causal relationship between identified ASD risk genes and clinical outcomes so that guidelines for
genetic counseling can be illuminated. Understand parental concerns and attitudes when communicating complex
genetic information.
OBJECTIVE 2: Understand the effects on ASD risk and resilience of individual and multiple
exposures in early development, enabling development of strategies for reducing disability and
co-occurring conditions in ASD.
Examples:
Understand the timing of exposures relative to the cascade of events that unfold during brain development to identify
and understand the molecular basis of exposure-associated ASD risk.
Conduct multiple studies in different populations and settings, with high-quality measures of exposure and adequate
controls, to reconcile disparate findings and establish robust linkages of environmental exposure to ASD risk.
Refine more targeted, conventional exposure assessment tools to characterize the exposome.
OBJECTIVE 3: Expand knowledge about how multiple environmental and genetic risk and resilience
factors interact through specific biological mechanisms to manifest in ASD phenotypes.
Examples:
Develop low-burden exposure measures that can be incorporated in large-scale genetic studies, perhaps leveraging
innovations in exposomics or epigenomics.
Move beyond identification of genetic and environmental risk factors to reveal functional biological consequences
associated with these risk factors.
Integrate methylation, exposure, and phenotype data in the same population.
43
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION
4
WHICH TREATMENTS AND
INTERVENTIONS WILL HELP?
45
Aspirational Goal: Develop a range of targeted treatments and interventions
that optimize function and abilities across the lifespan to achieve meaningful
outcomes and maximize quality of life for people on the autism spectrum.
INTRODUCTION
The evolution of this Aspirational Goal reflects
the progression of priorities in the autism community.
Over the past several years, the IACC’s focus has shifted from
“preventing disabilities” (2009 IACC Strategic Plan), to
encouraging “building adaptive skills” (2013 IACC Strategic
Plan Update), and now emphasizes the construction of
lifespan approaches and utilization of more meaningful
treatment outcomes for individuals living with ASD and
their families. This change also underscores the shifting
landscape of treatment opportunities driven by exciting
discoveries from cognitive neuroscience, which reveal
breathtaking developmental reorganizations of brain function
in adolescence and young adulthood,
1,2,3
adding new
possibilities for intervention and learning across the lifespan.
Since the 2013 IACC Strategic Plan Update, there has
been an explosion of behavioral intervention studies and
advancements in intervention science, including continued
progress in the development and evaluation of multiple
intervention types. Key advances include improvements
in community implementation of effective interventions,
greater numbers of fully powered randomized trials,
comparative efficacy studies, and implementation science
studies that consider child outcomes as well as best
implementation practices. Additionally, the diversity of
study participants has improved, as researchers more often
strive to include underserved families as well as populations
previously excluded or overlooked in ASD research, such
as girls and minimally verbal children.
There has also been much progress in brain-behavior
measures as predictors of outcomes of interventions,
as well as the development of adaptive interventions,
recognizing that sequential and multiple interventions
are often required to improve child outcomes. Finally,
technology has been used more frequently, as a tool within
an intervention (such as iPads for communication and
storyboarding), to deliver interventions using telehealth
methods, and to collect data in real time that can be used
to guide intervention and gauge treatment response.
The next generation of more precise, personalized
treatments and interventions will be developed with the
benefit of the knowledge gained from neuroscience and
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
46
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
genetics research on the systems biology of ASD. Researchers
are now utilizing the latest discoveries and tools from
these fields to develop and evaluate genetically targeted
pharmacology, neuroimaging-guided direct brain stimulation,
combination drug (or brain stimulation) and behavioral
treatments, and intervention approaches that match the
needs of individuals with ASD. Great progress has been
made, and will continue to be made, by prioritizing the
understanding of the brain basis of ASD and biological
mechanism(s) underlying a given therapeutic approach.
INTERVENTION AND TREATMENT TYPES
The autism community continues to emphasize the
importance of establishing evidence-based practices in
interventions.
4
Evidence-based practice is grounded on
the premise that there are interventions that have evidence
of their positive and strong effects for individuals with
ASD, and that practitioners (e.g., psychologists, psychiatrists,
speech pathologists, teachers) should therefore prioritize
their use while working with families. When strong evidence
for an intervention or treatment to address a specific goal
or outcome does not exist, the practitioner should try the
intervention with the most evidence, although the empirical
efficacy may fall below an established standard. Clinical
and/or professional expertise plays a major role in selecting
an intervention or practice to address a specific goal or more
generalized outcomes and is especially useful for adapting
the intervention for the individual with ASD when needed.
Looking forward, advances in neuroscience and genetics
that provide knowledge of the biobehavioral mechanisms
of treatment efficacy (summarized in Chapter 2 of this
report) support a new principle to guide evidence-based
practice: Preference should be given to those treatments
and interventions for which there is a current or emerging
understanding of the biobehavioral mechanism(s) of action.
This will facilitate highly innovative, randomized, experimental
therapeutics trials in human participants. Such trials will
improve our understanding of the developmental mechanisms
underlying ASD risk and resiliency, thereby enabling the
development of novel treatments and intervention strategies.
BEHAVIORAL INTERVENTIONS
Behavioral interventions fall into two broad classes: focused
intervention practices and comprehensive treatment models
(CTMs). Focused intervention practices are instructional
or therapeutic approaches applied to an individual’s
goals (e.g., making social initiations to peers, reducing
self-injury), designed to produce outcomes related
specifically to the goal, and are implemented over a
relatively short period of time until an individual meets
his or her specific goal. Meanwhile, CTMs address broader
outcomes (e.g., increases in cognitive abilities, adaptive
behavior, social and communication skills). CTMs consist of
many focused intervention practices organized around a
conceptual framework, are documented through treatment
protocols, and exist over a more extended time period.
Examples include the Lovaas Model
5
and the Early Start
Denver Model (ESDM).
6
Practitioners use these two classes of interventions/
treatments in different ways. They may select multiple
focused intervention practices to build individualized
programs for children, youth, and adults with ASD, or they
may fully adopt a comprehensive treatment program in
which the focused interventions and their use are already
prescribed.
7
Although several CTMs have been shown to
be efficacious, they may be implemented less often by
practitioners than focused intervention practices.
8,9
The
National Standards Project and the National Professional
47
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Development Center on ASD (NPDC) have conducted
critical and rigorous reviews of the intervention research
literature and identified sets of focused intervention
practices that have evidence of efficacy.
10
The NPDC work specifically focused on practices that
could be implemented in school and/or community settings.
Similarly, deBruin and colleagues conducted a meta-analysis
of school-based interventions in high schools, finding
evidence of efficacy for many of the same focused
intervention practices (i.e., antecedent-, video-, and
consequent-based interventions).
11
Other reviews have
documented the efficacy of 1) school-based, focused
interventions on challenging behavior, 2) the use of peer-
networks to foster social engagement, 3) social skills training,
and 4) academic interventions.
12,13,14,15,16,17
Research on
the efficacy of several behavioral interventions continues
today, including the Lovaas Model, ESDM, JASPER
(Joint Attention, Symbolic Play, Engagement, and Regulation),
LEAP (Learning Experiences and Alternative Program for
Preschoolers and Their Parents), PRT (Pivotal Response
Treatment), First Words Project, DIR/Floortime
(Developmental, Individual-Difference, Relationship-Based),
EMT (Enhanced Milieu Teaching), and STAR (Strategies for
Teaching based on Autism Research).
5,6,18,19,20,21,22,23,24,25,26
School-Based Interventions It can take over a decade
and a half for evidence-based interventions to become widely
implemented in the community when developed in the
laboratory. Thus, researchers are increasingly developing
and testing interventions in school-based settings, with
the added goal of sustaining the intervention beyond the
study period. Two recent studies demonstrate that similar
outcomes can be obtained in the community and the
lab.
27, 28
Both of these studies implemented JASPER aimed
at improving core impairments in social communication,
and noted sustainability of the intervention over a short-term
follow-up. As a whole, these and other findings highlight
the effectiveness of teacher-implemented interventions
in school settings on improving one of the core features
of ASD and pave the way for more school-based
intervention research.
Parent-Mediated Interventions As diagnostic
advances have made it possible to identify children with
ASD at earlier ages, researchers have tested a number of
parent-mediated interventions in order to meet the need for
interventions that can be implemented as early as possible.
Most of these are labeled Naturalistic Developmental
Behavioral Interventions (NDBIs), a newly vetted grouping
of early interventions based on applied behavior analysis
(ABA).
29
Several recent studies have yielded significant
improvements over earlier studies by comparing
the experimental treatment to an active control group
involving parent education but no hands-on coaching,
versus comparing an experimental treatment to
treatment as usual.
30,31,32
One conclusion of these recently completed studies
is that active hands-on parent coaching for social
communication outcomes is more effective than parent
education models where the same information is provided
without active coaching. This conclusion is further supported
by another recent study of toddlers at risk for ASD,
finding that initial gains in parent responsiveness did not
sustain to the follow-up, speaking to the need for longer-term,
more intense, or more hands-on intervention.
33
A recent
parent-mediated intervention study based on the DIR/
Floortime intervention approach suggests efficacy of this
model for improving parent and child outcomes.
22
Researchers have also studied the benefits of parent group
interventions, where groups of parents are coached to deploy
interventions. In a recent study of the PRT approach,
researchers found that parent group interventions yielded
significant parent and child benefit.
34
While more cost
effective than 1:1 therapy sessions, more research is needed
to determine the generalizability and sustainability of parent
group interventions to foster meaningful improvement in
child behaviors, communication, and functioning.
48
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Altogether, the foregoing studies add to the positive
outcomes attained through parent-mediated interventions
but raise issues about meaningful outcomes (i.e., spontaneous
versus prompted outcomes) and the specific “active
ingredients” – or essential components – of treatment
(i.e., hands-on coaching, dose, approach). In the future,
researchers will need to better understand for whom
an intervention works best, and why an intervention
provides benefit. Understanding the mechanisms behind
effective behavioral interventions helps researchers to
identify the essential components of an intervention, making
it possible to develop a repertoire of components that can
be combined in various ways to customize treatment.
Two recent studies suggest that parent synchronization
(attuning of the parent’s behavior to the child’s attention)
and mirrored pacing (following the child’s lead) are
important components or active ingredients of parent-
mediated interventions.
35,36
Behavioral Interventions in Understudied
Populations
Developing interventions for minimally
verbal children has been very challenging. A recent study
tested whether JASPER combined with a behavioral
language intervention with or without an augmentative
and alternative communication (AAC) device facilitated
greater spoken language over 6 months.
32
This study took
an adaptive treatment approach, adjusting the treatment
midway through the study based on an individual’s progress.
The results of this study suggest important implications
about the treatment approach and timing of providing an
AAC device in treating minimally verbal children with ASD.
For instance, the approach focused on developmental
pre-requisites to spoken language, including joint attention,
joint engagement, and play along with systematic
modeling and prompting for spoken language.
The researchers utilized a developmental, child-directed
approach with strong naturalistic reinforcement strategies.
Adults were contingently responsive to child attempts
at communication and provided expansion of language
through models that matched the child’s communicative
intent. This may have provided the combination of supports
needed for minimally verbal children with ASD to
successfully increase their spoken communication. Earlier
access to speech-generating devices along with naturalistic
behavioral interventions at the start of treatment may be
most beneficial to minimally verbal children. This is an
area that demands much greater research attention.
Girls with ASD are another understudied and
underserved group. Recent studies find subtle but important
developmental differences between preschool-aged boys
and girls with ASD.
37
Studies of older children find girls
with ASD who have lower IQs also have more impairing
symptoms of ASD than boys. Girls with higher IQs report
better friendships and social skills and fewer repetitive
behaviors than boys.
38
School playground observations of
girls with ASD find they are overlooked and neglected by
their classmates in more subtle ways, whereas boys with
ASD are often overtly rejected.
39
In part, these differences
between girls and boys with ASD are due to the ability of
girls to camouflage their interaction difficulties.
40
These
findings suggest that gender should be included as a
tailoring variable when individualizing interventions for
children with ASD.
Groundbreaking brain imaging and genetics studies
have revealed important differences between males and
females in the brain and genetic mechanisms underlying
autism. For instance, genomic studies have provided
tantalizing evidence for a “Female Protective Effect” (FPE)
hypothesis in ASD,
41
such that a greater amalgamation
(more and/or more intense) of risk factors is necessary
in females versus males to lead to autism. To illustrate,
deleterious copy number variations (CNVs) are three times
more likely in autistic females than in males.
42
Furthermore,
recent gene expression work from postmortem brain
samples demonstrates that autism risk genes, rather than
being sexually dimorphic themselves, interact with pathways
and cell types that themselves are sexually dimorphic.
43
49
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Looking ahead, as it is becoming increasingly clear that
females and males with ASD differ in terms of causes,
developmental profiles, and symptom profiles, we need
to understand how they respond differently to treatment
approaches. At present, there are no adequately powered
studies that focus on sex differences in behavioral and/
or neural-systems-level treatment response. Such studies
should be a major priority for the research community.
Discoveries of neuroplasticity in the adult brain have
opened new opportunities to consider autism interventions
for use in adulthood. Very few studies of behavioral
interventions have been performed in adolescents or adults
with ASD, and most of these have focused on training
adults to read social cues.
44
Executive and social brain
networks exhibit the greatest rates of functional maturation
during adolescence, establishing adolescence and young
adulthood as a sensitive period for socio-emotional and
self-control development.
45
These new findings suggest
that the period from adolescence into young adulthood
may offer an important new window of opportunity for
individuals with ASD, their families, scientists, and clinicians
to design novel approaches for improved outcomes and
superior quality of life.
MEDICAL INTERVENTIONS
Pharmacological Treatments
In contrast to the
many behavioral intervention options available, only two
drugs, risperidone and aripiprazole, currently have Food
and Drug Administration (FDA) indication for use in ASD,
specifically for the symptom of irritability. There are no
approved treatments for the core symptoms of ASD, which
include social communication difficulties and restricted,
repetitive patterns of behavior, interests, or activities.
Although clinical trials of pharmacological interventions
for core symptoms of ASD are now underway, they will
require several years for completion, analysis, and reporting;
thus, there are few published findings to date. Advances in
genetics and neurobiology have led to an increase in the
number of clinical trials testing medical treatments for ASD.
While the majority of such trials are testing pharmacological
treatments, neurostimulation (discussed separately below)
is also gaining momentum as a modality to alter brain
activity and neuronal connectivity, as is the development
of approaches based on stem cell technologies.
There has been an abundance of open-label, single-center
drug trials that report effectiveness in small samples.
Unfortunately, many of these results were not replicated
when tested in subsequent larger, randomized, placebo-
controlled trials. Many of the drug trials in ASD exclude
individuals with intellectual disability and very young children
due to ethical and/or practical challenges. However, a
mechanism-based intervention intended to improve core
symptoms of ASD may be more effective if administered
relatively early in life and may be most effective in those
most severely affected. Thus, it is crucial that such individuals
are included in upcoming trials. This will require researchers
to carefully consider how interventions can be adapted to
accommodate children or individuals with intellectual
disability, and to identify age- and ability-appropriate
outcomes and outcome measures. Additionally, researchers
must ensure that parents and families are well-informed
and actively engaged through all stages of the trial.
Many different genes may contribute to the susceptibility
of developing ASD. This heterogeneity of underlying causal
mechanisms makes it challenging to identify convergent
molecular pathways and brain circuits involved in all
individuals with ASD, although there has been recent
progress. One promising target is oxytocin, a neuropeptide
involved in social cognition that has been investigated in
a number of ASD studies.
46,47,48
However, its molecular
properties pose challenges for potential therapeutic use;
thus, further work is needed to determine the best doses
and compare methods of delivery. Moreover, given the
variation of oxytocin’s effects based on behavioral context,
studies aimed at understanding how oxytocin might
enhance responses to evidence-based behavioral
interventions are recommended.
49
50
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Other randomized, placebo-controlled treatment trials
have targeted additional mechanisms proposed to
contribute to the pathophysiology of ASD, with varying
successes.
50,51,52,53,54
N-acetylcysteine (NAC), an antioxidant
treatment, was well-tolerated and had the expected effect
of modulating oxidative stress markers, but had no impact
on social impairment in youth with ASD.
50
D-cycloserine,
a partial agonist of the N-methyl-D-aspartate (NMDA)
glutamate receptor, was tested in combination with social
skills training. No difference was found in the drug treatment
group compared with placebo.
51
The serotonin partial agonist
buspirone was used to target core symptoms during the
developmental period of low serotonin synthesis capacity in
young children with ASD. Low-, but not high-, dose buspirone
showed significant improvement in a measure of restricted
and repetitive behaviors.
52
Finally, a double-blind clinical trial
using the diuretic bumetanide that reduces intracellular
chloride, thereby augmenting GABAergic inhibition,
showed that bumetanide significantly reduced clinical
symptoms of ASD in children 3-11 years old and was
well-tolerated.
53
Furthermore, bumetanide combined with
a behavioral intervention resulted in a better outcome in
children with ASD than a behavioral intervention alone.
54
Larger trials are needed to validate these initial findings.
Moreover, given the importance of context and a
developmental perspective on ASD, it will be very important
to conduct well-powered studies that combine
pharmacological treatments with evidence-based practices
including behavioral approaches, cognitive behavioral
therapy, and social skills training. This issue is discussed
in detail below.
A number of treatment trials are targeting the associated
or co-occurring conditions of autism. One of the most
prominent is anxiety, which affects at least 40% of individ-
uals with ASD.
55
Treatments range from cognitive behav-
ioral therapy (CBT)
56,57
to medications.
58,59,60,61
While
there have been some notable successes, there is also
substantial variation in outcome. The variation in success
may be due, in part, to the difficulty in assessing anxiety
symptoms in autism and to the inappropriate stratification
of appropriate subjects. When individuals with and without
anxiety are grouped together as the "experimental" group,
it is often difficult to attain a high enough level of response
to consider the trial a success. This is an issue that relates
to all treatment trials of the co-occurring conditions. And,
additional research efforts must be directed to adequately
subdividing individuals with autism into more homogeneous
subgroups that have common symptom profiles.
Given that the rates of diagnosed ASD cases are
rising and that there are no effective drugs to treat its
core symptoms, it is imperative to further develop
pharmacological treatments. Involvement of private industry
will be crucial to help address this unmet need, including
in industry-academic collaborations. Important private
partners include the pharmaceutical industry, as well as those
in software, electronics, and robotics development. As much
as possible, multi-site, longer-duration, placebo-controlled
studies should be prioritized in order to produce more
reproducible results, such that private industry will take
on the challenges of conducting large Phase III
registration studies.
Direct Brain Stimulation Transcranial magnetic
stimulation (TMS) is a potentially promising method for
identifying neural mechanisms and treating aspects of
altered brain function in ASD.
62
TMS can offer a non-invasive
tool to study aspects of the altered physiology underlying
ASD. Treatment strategies involve using TMS to modulate
brain plasticity and network activity.
63,64,65
In particular,
repetitive TMS (rTMS) can alter brain excitability and
network activity beyond the duration of a stimulation
session or treatment study, and is being examined as a
treatment that could potentially reduce both core and
associated ASD symptoms.
66
51
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Recent studies have investigated whether neuromodula-
tion via rTMS or transcranial direct current stimuli (tDCS)
can induce neurophysiological and clinical benefits in
individuals with ASD.
67,68,69,70,71
Preliminary results suggest
that TMS might be of therapeutic value for improving core
and associated symptoms of ASD. However, work on brain
stimulation as a therapeutic technique for ASD is still in
the very earliest stages of development. There remain
many unanswered questions and potential barriers for
widespread application of these techniques. In particular,
the mechanisms by which these techniques might improve
brain and behavioral function in ASD are not yet known.
Most studies to date have been based on small samples,
employed open-label designs, and provided mixed results;
some people with autism appear to benefit while others
do not. There is a need for well-controlled, randomized trials
with adequate sample sizes to better understand whether
brain stimulation is efficacious and safe and whether there
are subgroups of individuals with ASD that might benefit
from treatments based on brain stimulation. In particular,
one major barrier to the widespread application of brain
stimulation in treating ASD is the potential to cause epileptic
seizure activity, especially in people who are already at
risk for developing seizures. Epilepsy is a potentially
devastating condition that is much more common among
individuals with ASD, especially those people with ASD
and lower intellectual abilities.
Stem Cells Stem cell technology has greatly advanced
our understanding of typical and atypical neurobiological
processes, thereby offering new opportunities for treating
neurodevelopmental disorders including autism. Increasing
evidence suggests that the pathophysiology of autism may
involve neuroinflammation, at least in a subgroup of cases.
72
Immune pathology in individuals with ASD is evident in
overexpression of immune-related gene networks in
postmortem brain tissue,
73
presence of maternal antibodies
to fetal brain tissue,
74
atypical levels of proinflammatory
cytokines (IL-6, TNF-α) in the cerebral spinal fluid,
75
and
excessive microglial activation leading to aberrant neural
connectivity pathways.
76,77
Stem cell therapies have been
shown to modulate immune activity and facilitate neural
connectivity and are being tested in autism populations.
Preclinical models have shown that umbilical cord blood
contains effector cells that, through paracrine signaling,
can alter brain connectivity and suppress inflammation.
78,79
Infusions of stem cells in mouse models of autism have
resulted in improvements in autism-like symptoms.
80,81
In humans, infusions of autologous cord blood cells have
been shown to be safe and beneficial in patients with cerebral
palsy and other acquired brain injuries.
82,83,84
A Phase I,
open-label trial assessed the safety and feasibility of
a single intravenous infusion of autologous umbilical cord
blood in 25 children with ASD, 2-6 years of age.
85
Assessment of adverse events across a 12-month period
suggested that the treatment was safe and well-tolerated.
Significant improvements in children's behavior were
observed on parent-report measures of social
communication skills and autism symptoms, clinician
ratings of overall autism symptom severity and degree of
improvement, standardized measures of expressive
vocabulary, and objective eye-tracking measures of children's
attention to social stimuli, indicating that these measures
may be useful endpoints in future studies. Behavioral
improvements were observed during the first 6 months after
infusion and were greater in children with higher baseline
nonverbal intellectual ability. Double-blind, placebo-
controlled studies of the efficacy of umbilical cord blood
for improving autism symptoms are currently underway.
As with brain stimulation, this research is only just
beginning, and there are many hurdles to overcome and
unanswered questions to address before the field will
know whether stem cell techniques can provide safe and
useful treatments for ASD. This will be an important area
of investigation to monitor as researchers work to
replicate and expand these initial, encouraging findings.
52
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
TARGETING SPECIFIC BIOLOGICAL
MECHANISMS
The prospect of precision medicine in ASD, i.e., specific,
targeted treatments developed after gaining a better
understanding of specific disease pathophysiology, is a
tantalizing one. Genetically defined disorders such as
Rett syndrome (RTT), Fragile X syndrome (FXS) and
tuberous sclerosis complex (TSC) provide a unique
opportunity to develop mechanism-based treatments for
ASD. Thanks to basic science discoveries describing the
molecular pathogenesis of these disorders, researchers
have begun efforts to evaluate treatments targeting
specific proteins in the implicated biological pathways.
86
In future work, biomarkers should be incorporated in order
to help detect objective improvements in response to
treatment and to identify optimal developmental periods
to apply the treatment trials.
The most common cause of classic RTT is a de novo mutation
in the X-linked gene MECP2 (methyl-CpG-binding protein 2).
MECP2 mutations are inherited in X-linked dominant fashion,
and females are almost exclusively affected. In light of
the basic science discoveries in the pathogenesis of RTT,
87
researchers have proposed multiple routes to treatment
for the disorder based on knowledge of MECP2 function.
These strategies are designed to address either the
underlying gene defect or downstream pathways implicated
in the disorder. Clinical trials are underway evaluating
the use of two different NMDA receptor antagonists,
dextromethorphan and ketamine, to improve outcomes
like epilepsy in RTT.
88
Among neurotrophic factor effectors
downstream of MECP2, IGF-1 has been studied.
89
Double-blind, placebo-controlled trials of rhIGF-1 and
NNZ-2566 (a synthetic version of the terminal tripeptide
fragment of IGF-1) have recently finished and are being
prepared for publication. The cholesterol pathway has
recently been identified as being involved in RTT,
90
and
lovastatin is currently under investigation in an open-label
trial for females with RTT. Finally, directly or indirectly
manipulating faulty copies of the MECP2 gene, transcript,
or protein is an appealing approach for treating RTT.
Read-through strategies as well as gene transfer approaches
using adeno-associated viral vectors are being actively
pursued.
FXS is an X-linked, trinucleotide repeat expansion disorder
involving the FMR1 (fragile X mental retardation 1) gene.
This is a leading single-gene cause of ASD. The FMRP
protein encoded by this gene regulates protein synthesis
in neurons. Advances in our understanding of the patho-
physiology of FXS have led to the development of numerous
targeted trials. The most prominent theory of FXS, the
metabotropic glutamate receptor (mGluR) theory, posits
that many symptoms of FXS are due to exaggerated
responses to activation of mGluRs. The prediction of this
model was that reduced activation of mGluR would
remedy the symptoms of FXS. However, recent clinical
trials (Phase II and III) with two different mGlu5 inhibitors
(basimglurant and mavoglurant) showed no therapeutic
benefit in FXS patients for reasons that are as yet unclear.
91
Driven by lessons learned from previous trials of mGluR
antagonists, investigators are planning a multicenter
placebo-controlled trial of mavoglurant for children with
FXS ages 2 ½ to 6 years of age. This trial will examine
outcome measures, including language, for all participants
with a parent-implemented language intervention
provided to all participants and psychopharmacologic
intervention provided only to some.
92
Approximately 50% of the patients affected with TSC
also develop ASD, and 90% will have seizures sometime
in their life. Importantly, many patients with TSC will be
diagnosed with this disease very early in life, usually in the
newborn period, due to the presence of heart tumors.
This provides the unique opportunity to investigate the
development of ASD in this high-risk group during the
first year of life. A recent study shows that an abnormal
electroencephalography (EEG) signature has 100% positive
predictive value for clinical seizures, 2-3 months prior to
53
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
the onset of these seizures.
93
These data have led to the
initiation of a “prevention” trial in the high-risk infants with
TSC using the anti-seizure medication vigabatrin. TSC
patients have hyperactivation of the mTOR pathway, which
controls neuronal protein synthesis similar to FMRP. The
hypothesis that overactive mTOR signaling in TSC may be
amenable to mTOR inhibitors has led to trials involving the
use of this class of medications in patients with TSC. A large
Phase III trial demonstrated that adjunctive mTOR inhibitor
treatment was effective for refractory focal epilepsy in TSC
patients.
94
Whether mTOR inhibitors will also be effective
in improving neurodevelopmental symptoms including ASD
is not yet known. A Phase II trial was recently completed;
results are pending.
Taken together, advances in the study and treatment
of RTT, FXS, and TSC have laid the groundwork for similar
mechanism-based treatment trials in genetic disorders
associated with ASD. Translating successes from animal
studies have not been straightforward to date.
Intellectual disability commonly affecting individuals
with these neurogenetic disorders is an additional
obstacle in study design in this field. Next steps will
need to include biomarkers to help detect objective
improvements in response to treatment and to identify
optimal developmental periods to apply the
treatment trials.
TECHNOLOGY-BASED INTERVENTIONS
Digital-based technology interventions for individuals
with ASD have continued to increase in accessibility,
breadth, and depth of use. Scientific evidence for the
effectiveness of technology-based or technology-enhanced
interventions has increased, with a larger number of ran-
domized controlled trials (RCTs) appearing in recent years
that highlight the breadth of technology applications in
ASD research as well as their increasing rigor.
95
In the field
of robotics, recent work has highlighted potential advan-
tages of robots over human agents for accelerating several
aspects of intervention research. Yet a number of challeng-
es and gaps have been highlighted, which are also shared
by speech-generating devices, virtual reality,
video games and computer-assisted instruction, mobile
applications, and telemedicine.
96,97,98
It will be essential
for future studies to address these challenges, as the
development of interventions using digital technologies
offers new opportunities to accelerate research progress.
Furthermore, the proliferation of technology-based
platforms purporting to help individuals with ASD points
to a need for new, efficient, and scalable methods and
infrastructure for evaluating technology-based interventions.
Technology-based interventions have tremendous potential
to benefit individuals on the autism spectrum in many
ways, including by helping them improve social and
communication skills and gain greater independence,
all of which can improve the overall quality of life.
54
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OUTCOME MEASURES AND BIOMARKERS
Over the past few decades, significant progress has been
made in the development of new behavioral interventions
and identification of novel drug targets aimed at reducing
core and associated ASD symptoms and improving quality
of life across the lifespan. A major challenge in determining
whether new treatment approaches are efficacious has
been the measurement of treatment response. Measurement
of treatment response is particularly complex in ASD
due to the heterogeneity resulting from an individual’s
symptom profile, sex, cognitive and language abilities, and
development level. Moreover, many existing assessment
measures were developed for screening and diagnosis
and are not sensitive to assessing change in symptoms
over time.
Considerable effort has been directed toward evaluating
which existing measures are suitable for clinical trials
and for developing quantitative, objective, and sensitive
measures of treatment response. Increasingly, the input
of key stakeholders, including caregivers and persons on
the autism spectrum, is solicited to ensure that outcome
measures reflect the priorities and needs of persons for
which the treatments are being developed. Several reviews
and consensus statements have been published that have
evaluated the appropriateness of existing parent report
and observational measures for clinical trials, including
measures of social communication, anxiety, and repeti-
tive behaviors.
99,100,101,102
Studies validating observational
measures of ASD symptom severity based on the Autism
Diagnostic Observation Schedule (ADOS) have also
been published,
103
and a brief observational assessment
of social communication change has also been recently
developed.
104
Biomarkers of treatment success are needed, as are
“stratification” biomarkers for matching people to the best
treatment for them at the best time. For example, while
oxytocin (OXT) has been a promising target for treating core
social communication symptoms in ASD, trials have not
produced consistently positive or negative results. This is
widely thought to be due to genetic and phenotypic
heterogeneity among trial participants who nonetheless
all receive the same diagnostic label of ASD. A recent
study demonstrated the potential for pretreatment blood
levels of OXT to serve as a stratification biomarker.
Individuals with the lowest pretreatment blood OXT
concentrations benefited the most from intranasal OXT
administration.
105
Until it becomes possible to biologically
measure treatment response, negative results from
pharmacological and behavioral interventions will be difficult
to interpret, and positive results may not definitively indicate
the requisite dose or duration of treatment. Predictive
biomarkers (those that help to match individuals to particular
treatments) will help to create more precise treatments
and help individuals with ASD and their families to avoid
wasted time and resources.
BIOMARKER DISCOVERY
Initial efforts have focused on developing measures that
are linked indirectly or directly to underlying neural circuitry,
which can offer insight regarding whether the treatment
is influencing specific aspects of neural circuitry, inform
researchers of the neural mechanisms that might underlie
the treatment effects, and predict treatment response.
These measures include eye tracking, electrophysiological
responses, and magnetic resonance imaging, among others.
Such measures can also serve as an early efficacy signal
that can detect response to treatment before changes in
55
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
more distal measures such as language and social abilities
are evident. Early efficacy markers can be used to identify
which individuals are most likely to benefit from a given
treatment and/or in adaptive study designs to indicate
early in the trial whether modifications in the treatment
(e.g., dose) should be made.
Eye Tracking (ET) ET has great potential for acting as
an early indicator of treatment efficacy by tracking changes
in social attention.
106
While applications of ET to clinical
trials and interventions are still relatively new, results
have been encouraging and suggest that ET can be used
as a method for measuring response across a wide range
of treatments. Promising future directions for developing
ET as a marker of change include: furthering data-driven,
computational, and machine learning approaches towards
subtyping and stratification within the autism spectrum
and for improved discrimination between individuals with
ASD and controls; the design of ET batteries with the
express goal of treatment measurement; the adaptation
and advancement of ET metrics in technology-driven/
technology-interactive interventions, such as virtual
reality, robotics, and simulators, as well as in novel adaptive
paradigms designed to change gaze strategies; and
advancement of methodological considerations including
the promotion of big data studies, facilitation of replication,
and increasing adherence to more rigorous and universal
technical and methodological standards.
Electrophysiological Measures Recent studies
suggest that EEG, a non-invasive measure that can record
patterns of brain activity throughout the lifespan, offers
promise as a metric of treatment response related to neural
circuitry.
107
Children and adults with ASD have distinct
electrophysiological signatures, offering the possibility of
using such measures to detect treatment response.
Furthermore, distinct EEG signatures have been found
among genetic subtypes of individuals with ASD and
related disorders, and these signatures could be used in
future clinical trials to test drugs targeted to individuals
with ASD associated with specific genetic syndromes.
In future work, prior to these measures being useful as
potential biomarkers, it will be important to demonstrate
their ability to reliably predict a signature of dysfunction
at the individual subject level, as opposed to group
averaged data.
Magnetic Resonance Imaging (MRI) MRI techniques,
including functional MRI (fMRI) and Diffusion Tensor
Imaging (DTI), have provided a wealth of information
regarding the neurobiological underpinnings of ASD.
Specifically, task-based fMRI studies have pointed to
atypical social-brain functioning and activation in ASD,
while resting-state functional MRI and DTI have pointed
to deficiencies in integrative social information processing
as indicated by white matter atypicalities and diminished
long-range connectivity.
108,109
Despite the potential for
brain imaging techniques to elucidate mechanisms
underlying behavioral treatment response, few studies
have directly used it for treatment monitoring or prediction
of treatment efficacy. However, this appears to be rapidly
changing, with several recent studies expanding on earlier
work.
110,111
Considerable progress has also been made
recently in regards to the use of brain imaging techniques
for understanding in vivo pharmacological neural action
in individuals with ASD. Altogether, these advancements
are beginning to provide the context for expanding the
scope and applicability of brain imaging techniques for
monitoring treatment across the lifespan, including before
the signs of ASD are overtly apparent. Given the many
successes yielded from the application of MRI methods to
the development of biomarkers in ASD and related fields,
considerable opportunity exists for further research and
development in this area.
Advances in Developing Measures of Treatment
Response
Digital technologies, such as mobile devices,
provide another approach for developing quantitative,
objective, and sensitive measures of treatment response.
112
These tools provide opportunities to study biomarkers in
56
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
combination with self-report data, often in more naturalistic
contexts such as the home. The ability of technology-based
systems, such as mobile applications, wearables, and
internet resources, to automatically record and generate
data will increasingly provide richer, denser, and more
meaningful information to researchers. Novel analytic
methods, such as machine learning and computer vision
analysis, can provide new insights into patterns of behavior.
Although early in their development and application to ASD
populations, such measures have the advantages of being
scalable, objective, and feasible. Thus, studies that explore
their utility as a method of treatment monitoring should be
pursued. Additional emphasis should also be placed on
transforming these signals into useful forms to maximally aid
and personalize ongoing, real-world treatment of issues faced
by individuals with ASD. As the understanding of these data
streams matures, new methods and systems will need to be
created to harness the power of this data and to manage the
massive flows of information reaching data consumers.
Recently, a number of substantial investments have been
made to support large, collaborative efforts aimed at
validating biomarkers and outcome measures for use in
ASD clinical trials. These consortia involve public-private
partnerships among academia, advocacy and other non-
profit organizations, government, and industry, with a goal
of de-risking investments into pharmacological ASD trials
and optimizing the success of such trials. These projects
are examining a wide range of potential biomarkers and
their relationships with observational and caregiver-report
measures of behavior in large samples of individuals with
ASD versus typical development over time. Furthermore,
regular communication, data sharing agreements, and
shared measures across the existing consortia will increase
the scientific utility of these investments. One example
is ABC-CT (Autism Biomarkers Consortium for Clinical
Trials), a National Institutes of Health (NIH)-, Foundation
for the NIH-, and Simons Foundation-funded consortium
of sites that aims to develop, validate, and disseminate
objective measures of social function and communication
for ASD with the ultimate goal of advancing these measures
as markers and predictors of treatment response.
In sum, multiple laboratories are conducting studies to
develop better ways of measuring treatment response.
Continued investment in such studies will ensure that, as
new behavioral and medical treatments are developed,
we will have the capability of testing their efficacy. Such
investments will also be essential for developing improved
methods for identifying subgroups that are responsive to
specific treatments and identifying neural mechanisms
underlying treatment response.
INNOVATIVE COMBINATIONS OF
THERAPEUTIC MODALITIES
There are now tremendous opportunities for combining
therapeutic modalities in ways that allow for positive
impacts from the amalgamation that are greater than the
sum of the parts. One example would be the combination
of psychopharmacology and behavioral treatments. The
core impairments of ASD (e.g., social communication)
have not been responsive to drug therapies yet. But, the
possibility of combining drugs with behavioral interventions
still holds promise for improvement in these core areas.
A few of these studies are in progress, but none have been
reported during this review period.
57
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Advancement of new or reconceptualization of existing
treatments into modular therapies (where therapies are
organized into therapeutic modules that can be combined
and reused in flexible arrangements) can provide
finer granularity and more tractable opportunities for
understanding change in individuals. This is an area of
great need and can especially help address co-occurring
conditions, such as anxiety, aggression, and depression.
Similarly, adaptive interventions, which incorporate more
flexible study designs, can make more efficient use of existing
clinical, research, and participant resources, providing more
information to researchers and potentially greater benefit
to participants. To encourage adoption, investment in
study design methodology research (including dissemination
of methods and development of trial design resources)
will be of significant value.
ACCELERATING RESEARCH AND INCREASING
ACCESS TO EVIDENCE-BASED INTERVENTIONS
While research in interventions for individuals with
autism has shown consistent growth and advancement,
opportunities exist for accelerating the pace of research.
First, high-quality intervention studies are expensive to
conduct and require substantial specialized expertise to
oversee. Additional investment in human and research
infrastructure is likely to yield compounding gains in autism
intervention research progress. Creating and sustaining
networks of institutions, investigators, clinicians, and
families committed to shared, large-scale implementation
of interventions or experimental research will combat
fundamental heterogeneity issues in ASD research, leading
to more reproducible and robust scientific findings. These
networks can be leveraged to promote testing of novel
interventions, exploration of unique scientific perspectives,
and commitment to a culture of non-exclusive innovation
transcending traditional boundaries. Additional investment
should focus on bridging gaps between scientific evidence
and clinical and/or community applications of interventions.
Additional opportunities may emerge from standardization
of reporting and protocols so as to facilitate aggregation
or comparison of clinical trial data at meta-analytic levels.
Examination of evidence at a higher analytical level may
provide more comprehensive information about treatment
effectiveness when clinical uncertainty is matched with
appropriate variation along key implementation parameters.
Similarly, sharing data at finer level of detail may additionally
facilitate data mining investigations that may help to identify
more streamlined assessment or nuanced precursors and
predictors of treatment response.
Further resources should be directed towards promoting
the development of applied scientific tools, including more
robust statistical methods, data mining techniques, basic
science methods, laboratory techniques, and optimized
pipelines for discovery. Additional resources could also be
spent at the tail end of intervention science, on the wider
dissemination of implementable discoveries. Examples
would include encouraging Phase II transitions to Phase
III trials, identifying appropriate industry partnerships to
foster larger-scale intervention implementation, and in vivo
studies of ongoing new intervention integration efforts.
Incorporation of business and operations perspectives
into autism research infrastructure development may help
to optimize intervention deployment efficiency, enabling
more studies to be conducted in a sustainable fashion.
By focusing on practical barriers to ultimate treatment
58
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
deployment (including insurance, provider adoption
willingness, and marginal expenses), a more robust, efficient,
and complete pipeline from idea to effective individual
treatment can be realized.
INCLUSION AND EMPOWERMENT OF
STAKEHOLDERS IN INTERVENTION RESEARCH
Empowering individuals with ASD and their families to act as
active directors in the research process can also accelerate
scientific progress. Development of tools to help stakeholders
manage and maintain research, educational, behavioral,
and clinical records could help them better advocate for
participation in studies most relevant to their needs or most
aligned with their personal goals. With a focus on usability
and controlled data sharing, such tools could become
interfaces by which information could be bi-directionally
shared with researchers and relevant providers, reducing
redundancy in information requests, streamlining study
deployments, and reducing participant burden.
Currently, several incarnations of such systems have been
developed, including Microsoft HealthVault and Apple
HealthKit. However, efforts towards tailoring interfaces,
cross-platform interoperability, and common standards
must be pursued so as to best meet the specific needs of
the autism community, to prevent data from becoming
unnecessarily locked to proprietary platforms or formats,
and to better enable data exchange. Creation of user-friendly
research registries that promote awareness of relevant
ongoing intervention studies or technologies, that can be
personalized by user preferences (including constraints
on geography, participation characteristics, and study facets),
that are updated regularly and managed in a sustainable
fashion, and that facilitate connections between
legitimate researchers and qualified research participants
(with appropriate governance of privacy and participant
rights) would further enable stakeholders to direct their
research agenda. Adaptation of stakeholder-held records,
including genomic information, for the purposes of creating
an interface that would facilitate recruitment of participants
with extremely specific characteristics (e.g., pharmacological
trials targeting specific gene mutations) may be critical for
appropriately powering highly targeted studies and for
providing stakeholders access to the most tailored and
innovative science.
113
Throughout the research process,
the involvement and feedback from the autism commu-
nity should be emphasized so as to provide continuous
context for research endeavors.
Much more attention has recently been given to quality
of life outcomes for addressing the needs of individuals
with ASD, including: academic success, autonomy and
self-sufficiency, financial stability, health and well-being,
inclusion, independent living, meaningful employment
with fair wages, pursuit of dreams, recreation and leisure,
respect and dignity, safety, self-identity and acceptance,
social connections, and subjective well-being. Using such
outcomes allows professionals, parents, and individuals
to develop intervention plans that will allow a person with
ASD to advance daily in each of the quality of life indicators.
Measuring such outcomes can occur both in the short- and
long-term and can be developed based on the needs of the
individual in terms of their level of skills, functioning, and
ability. When such indicators are maximized, the individual
will be able to fully live a life maximizing long-term success.
59
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
SUMMARY
While there have been multiple, important advances in
the field of autism interventions and treatments, there is still
much progress to be made. Researchers must continue to
develop new treatments as well as adapt existing treatments
for diverse settings and populations, including males and
females, individuals with co-occurring conditions and
varying levels of ability across multiple domains, individuals
across the lifespan, and those in settings or communities
that are under-resourced or underserved. Moving forward,
there are several important issues to consider. First, it will
be important to leverage advances in our understanding
of the neuroscience and neurobiological mechanisms
underlying all therapeutic approaches. Second, researchers
need to consider designs and recruitment strategies that
allow for testing ways to maximize effectiveness and
precise matching of treatment plans to individual needs
and neurobehavioral profiles by combining therapeutic
approaches. More robust, standardized outcome measures
should be developed, including adaptive measures, predictive
measures, biologically based metrics, measures that
address heterogeneity, and measures of practical outcomes
and quality of life that will help better target therapies
to individual needs and goals. It will also be important to
study combination therapies that mimic how therapies
may be delivered in real-world settings, and that offer the
opportunity to provide greater benefits than any individual
therapy alone. To realize the goal of developing the next
generation of ASD therapies, funders will need to devote
significant investment to building and enhancing the research
pipeline to train of the next generation of multidisciplinary
intervention scientists. Finally, it will be essential to
provide more tools to practitioners through translation
of research to community-based practice and to deploy
effective, novel dissemination strategies.
60
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVES
OBJECTIVE 1: Develop and improve pharmacological and medical interventions to address both
core symptoms and co-occurring conditions in ASD.
Examples:
Advance the study and treatment of genetic syndromes related to ASD, including RTT, FXS, TSC, and utilize the
groundwork provided by investigations of these disorders to develop similar mechanism-based, genetically targeted
pharmacology treatment trials for ASD.
Explore innovative treatment modalities and combination therapies.
Develop therapies to address challenges across the spectrum and across the lifespan.
Investigate treatment response, including how females with ASD respond differently to treatment approaches,
with a focus on the use of cognitive neuroscience tools to examine alternative mechanisms of change underlying
symptom change.
Develop biomarkers that can help inform decisions about the most appropriate interventions for particular individuals
from across the autism spectrum and provide objective, early assessments of treatment response, prior to overt
symptom change.
OBJECTIVE 2: Create and improve psychosocial, developmental, and naturalistic interventions
for the core symptoms and co-occurring conditions in ASD.
Examples:
Support research to ensure that interventions include the whole autism spectrum and diverse populations, including
females, minimally verbal individuals, intellectually disabled individuals, adults, and individuals in under-resourced and
underserved communities.
Leverage the neuroscience of neuroplasticity of the adolescent and adult brain to develop psychosocial interventions
targeting these age groups, meeting their specific needs, offering a path toward continued development of life skills,
and enhancing quality of life.
Define the “active ingredients” of successful therapeutic approaches as a basis for future innovation and tailoring of
interventions to particular populations or settings.
Explore combination therapies.
Develop outcome measures that include biomarkers of treatment success, measures of improvement across multiple
domains, and improvements in quality of life.
61
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVE 3: Maximize the potential for technologies and development of technology-based
interventions to improve the lives of people on the autism spectrum.
Examples:
Develop tools allowing individuals with ASD to track and direct their own treatment.
Develop technology-based interventions that help people with ASD improve their social and communication skills,
increase their independence, and in many other ways help improve the quality of their lives.
Develop interventions for minimally verbal children and those with intellectual delay, with a focus on the use of
technology to augment communication (for minimally verbal children) as well as adaptive, individualized treatment
approaches for both groups of underserved children.
Increase access to interventions by developing technology-based treatments that can be deployed outside of primary
care or clinical settings.
QUESTION
5
WHAT KINDS OF SERVICES AND
SUPPORTS ARE NEEDED TO
MAXIMIZE QUALITY OF LIFE FOR
PEOPLE ON THE AUTISM SPECTRUM?
63
Aspirational Goal: Communities will develop, access, and implement high-quality,
evidence-based services and supports that maximize quality of life and health
across the lifespan for all people with ASD and their families.
INTRODUCTION
In previous editions of the IACC Strategic Plan, Question 5
(Services) addressed access and coordination of services
for individuals with ASD and their families. Research
on services and supports focuses on self-directed care,
coordination of funding and services among state and local
agencies, community-based supports, and the need to
better measure the health, safety, and mortality of people
with ASD. Previous Question 5 Strategic Plan objectives
included support for research to develop and evaluate the
training of service providers who work with individuals
with ASD, and to improve the efficacy, cost-effectiveness,
dissemination, and implementation of evidence-based
practices. In 2015, 6% ($21 million) of ASD-related research
funding from Federal agencies and private organizations
addressed issues related to services.
1
A lack of sufficient
funding raises considerable barriers for researchers to
develop, test, and implement service system delivery models
that increase the supply of care and address the gaps
between research and practice.
2
There have been several notable positive changes over
the last few years regarding services research and planning,
particularly due to an increased focus on the needs
of individuals with autism as they age out of childhood.
For example, the U.S. Government Accountability Office
(GAO) released two reports, the first entitled Youth with
Autism: Roundtable Views of Services Needed during the
Transition into Adulthood in 2016
3
and the second entitled
Federal Agencies Should Take Additional Action to Support
Transition-Age Youth,
4
that described the needs of youth
with ASD transitioning to adulthood and ways in which
Federal agencies might fill current service gaps.
New research on the cost of ASD across the lifespan has
contributed to the knowledge base around ASD services.
Researchers estimate that the lifetime cost of supporting
an individual with ASD without intellectual disability in the
United States is approximately $1.4 million.
5
Contributors to
total costs for children with ASD were direct nonmedical
costs, such as special education (including early intervention
services), and indirect nonmedical costs, such as parental
productivity loss. For adults with ASD, contributors include
accommodation (residential care or supportive living
accommodation), direct medical costs, and individual
productivity loss. Others studies show that caring for a child
with ASD can cost over $17,000 per year more than caring
for a child without ASD, with 18% of these costs associated
with increased use of healthcare services.
6
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
64
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
While these studies highlighted some of the areas in which
the needs of individuals with ASD are not being met,
they have not defined solutions. Adequate, cost-effective
services are still lacking, as are strategies to decrease
financial stress for families.
In this chapter, we describe gains and opportunities in
specific service-related areas. For all the recent successes
in ASD services research, gaps in services remain for
children and adults with autism and their families.
PROGRESS IN THE FIELD
EDUCATION SYSTEM
Most school-aged children with autism receive the
majority of their ASD-related services through the public
education system.
7
The number of children receiving these
services, as well as the cost of their education, is increasing.
A growing body of research suggests a nationwide problem
of ineffective educational programming and the need for
stronger educational workforce development, support,
training, and supervision. With relatively little research on
developing specific guidance for addressing challenges
within the education system, it is necessary for educators
working with students on the autism spectrum to address
the complex and growing set of challenges.
While Federal and state legislation has placed a greater
focus on accountability and performance standards, there
is little agreement or standardization of how performance
should be measured. The No Child Left Behind Act and
the Individuals with Disabilities Education Improvement Act
(IDEA) both state that students with ASD must have
access to high-quality, research-based interventions
that help keep them in the least restrictive instructional
environment that can meet their learning needs. National
programs such as the SWIFT (School-Wide Integrated
Framework for Transformation) Center have documented
change strategies and instructional approaches that can
be used to meet these legal requirements. Federally funded
programs such as the National Professional Development
Center on ASD have demonstrated improved outcomes
when students are the recipients of evidence-based
practices, and they have begun to develop practices to
assist with the scale-up of these interventions. Unfortunately,
implementation of evidence-based practices remains the
exception rather than the rule; implementation of innovative
interventions is challenging due to limited fit with classroom
needs and lack of professional support. New research in
implementation science highlights the need for a systems
approach that includes involving leadership in and across
schools to develop a strong culture and climate for
quality implementation.
Our definition of autism and our understanding of how
autism co-occurs with other mental health challenges
has expanded. Eighty percent of students with ASD have
co-occurring physical or mental health challenges,
8
requiring
new education strategies and coordination across multiple
service systems. Recent research has focused attention
on co-occurring anxiety
9,10,11
and depression,
12,13
as well as
suicide risk.
14,15,16,17
Models for recognizing and addressing
these challenges in schools have not yet been developed
or disseminated.
Many schools have not fulfilled the promise of educating
children with autism in the least restrictive and most
integrated environment suited to their needs. While
several models of inclusion have demonstrated efficacy,
18
the type and quality of inclusion programming to which
65
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
children with ASD have access is highly reflective of local
policies, resources, and expertise rather than reflective of
evidence-based practices grounded in research. There is
also a need for quality interventions to help keep children
with ASD in an instructional environment that maximizes
their potential; because of the range of learning styles of
children with ASD, students often need options such as
distance learning and smaller group instruction.
Currently, the public education system is not adequately
preparing all children with autism for adulthood. Although
there have been improvements in recent years, approximately
half of students with ASD leave secondary school without
employment or plans for further education.
19
While much
of school programming is focused on those who will attend
college, this is not an option for many students with ASD,
who will also leave school without the skills needed to
enter the workforce. During the transition to adulthood it
is important to teach youth with autism the social and
vocational skills necessary to have successful outcomes
after leaving the education system.
HEALTHCARE SYSTEM
There has been considerable progress in some areas of
ASD services-related research within the healthcare system.
One important funding stream for reimbursement of services
provided to individuals with ASD is the Medicaid program.
Jointly operated between the states and the Federal
government, Medicaid provides healthcare coverage for
individuals below certain income thresholds and
encompasses a wide array of benefits, such as case
management; physical, occupational, and speech therapies;
and rehabilitative services that are often used by individuals
with ASD. The Early and Periodic Screening, Diagnostic
and Treatment (EPSDT), the child health portion of
Medicaid, mandates the provision of medically necessary
services found at section 1905(a) of the Social Security
Act to Medicaid beneficiaries under the age of 21.
EPSDT ensures that children and adolescents receive
appropriate mental health, developmental, and specialty
health services. In 2014, the Centers for Medicare and
Medicaid Services (CMS) issued guidance affirming the
applicability of EPSDT standards to the treatment of
ASD. Outside of Medicaid, there are large disparities in
insurance coverage and reimbursement rates based on
differences in state health coverage mandates. The effects
of the discrepancies in billing rates and reimbursement
prevent implementation of evidence-based practices and
interventions for individuals with ASD and their families.
There is a continued need for ASD insurance reform.
Families of children with ASD who have a medical home
a partnership with their primary care doctor to provide
personalized treatment plans - report fewer unmet needs
and more shared decision making with healthcare
providers.
20
The Affordable Care Act (ACA) of 2010, Section
2703, created an optional Medicaid State Plan benefit for
states to establish Health Homes to coordinate care for
people with Medicaid who have chronic conditions. While
ASD is not a chronic condition listed in the statute, it is
subject to state application, then review and approval.
State ASD insurance mandates increase ASD diagnosis
and treatment rates by 13%, after controlling for other
variables.
21
This effect increases the longer the insurance
mandates are in place. However, the number of children
receiving ASD services is still fewer than would be expected
given current prevalence estimates, though this does not
control for public versus private service utilization.
Mounting research shows that Medicaid Home and
Community Based Services (HCBS) waivers can
significantly meet the service needs of people with ASD
and decrease their unmet healthcare needs, especially
among those who would not otherwise qualify for
Medicaid.
22
Those with ASD who access services through
waivers are also less likely to use inpatient and long-term
services care.
23
Since 2010, CMS has undertaken several
activities that have provided new information about ASD
66
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
services available in the community. Among these is a report
published in 2014, Autism Spectrum Disorders (ASD): State
of the States of Services and Supports for People with ASD,
which assesses existing state programs and supports for
families living with ASD in all 50 states and the District
of Columbia.
24
This CMS study provides a comprehensive
view of services that received support from various Federal
sources and were made available through state programs
across the country.
APPROPRIATE SERVICES TO ADDRESS
HEALTH AND SAFETY CONCERNS
Recent studies have shown that people on the autism
spectrum are at increased risk of many health challenges
and premature mortality.
17,25
Research is needed to both
understand what causes poor health and safety outcomes
and to develop strategies to improve outcomes. Among
the most pressing health concerns for children and adults
diagnosed with ASD is ensuring adequate support to
address co-occurring conditions, which may include mental
disorders, sleep problems, gastrointestinal disturbances, or
other issues.
26
Unfortunately, there is a lack of understanding
and awareness among service providers regarding the
challenges these conditions pose to individuals with
ASD and their families.
27
This often leads to a lack of
appropriate services and multifaceted interventions.
Parents of children with ASD and co-occurring psychiatric
conditions are more likely than other parents of children
with ASD to report that their child’s needs are not being
met.
26
A broad assessment of mental health, learning,
and cognition problems associated with ASD is crucial to
determine appropriate services and treatments for people
with ASD throughout the lifespan.
28
There is mounting evidence that these co-occurring
conditions contribute to premature death among
individuals with ASD. A Swedish study showed that the
average death for an adult with autism is 54 years, and
that loss of life years is mostly attributable to suicide,
seizures, and metabolic disease, among other conditions.
29
To address these significant health disparities, it is
necessary to increase implementation of services and
evidence-based approaches in addition to research to
improve services for co-occurring conditions.
Wandering behavior presents additional safety risks
for some individuals with ASD. Recently, the National
Autism Association (NAA) released a report stating a
third of reported ASD wandering/elopement cases in the
United States were either fatal or required some level of
medical attention, while encounters with water, traffic,
and other threats accounted for an additional 38% of
cases.
30
Among emergency care visits, adolescents with
ASD accessed emergency department services four times
as often as adolescents without ASD.
31
There are also
disparities in emergency department visits among children
with ASD living in rural areas compared to urban places.
32
Ensuring broad access to services through more innovative
strategies is necessary to close the gaps in health and
safety for children and people with ASD. One strategy that
has seen success is ECHO Autism, a University of Missouri
telehealth program aimed at reducing wait times and
improving primary care for children with autism living in
remote areas.
33
The program has seen success in Missouri
and plans to replicate and expand the model to isolated
areas throughout the country and world.
The healthcare system needs to emphasize increasing
access in underserved populations and increasing
cultural competency among service providers. The literature
suggests disparities in utilization and access to healthcare
and educational services for those with ASD from minority
populations and families from lower socioeconomic status
(SES).
34,35,36,37,38
Ethnic minority children with ASD tend
to receive diagnoses almost one year later than White
children and often receive fewer specialty services.
39
Despite initiatives to increase the quality of healthcare
provider interactions with families of children with ASD
67
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
and developmental disabilities, the health service systems
do not meet the needs of minority populations.
40
Disparities
in access and utilization may be due to the lack of cultural
competency of providers, perceived low quality of care,
or the lack of family-centered care, among other factors.
35
While research has been funded to assess variations in and
access to services in relation to health disparities, the
research needs to be taken a step further to study how to
address what we have learned. We need to better understand
what portfolio of services will result in the best outcomes
for diverse populations.
Overall, it is important to continue to support research to
test quality services and supports as well as evidence-based
interventions that can eventually be implemented in a
community setting and be accessible through medical
coverage. A systematic, evidence-based, collaborative
approach can facilitate the scaling up of evidence-based
practices in community settings.
41
Factors identified to aid
in scaling up evidence-based interventions in community
settings are organizational support and readiness, program
and implementer characteristics, and sustainability
planning.
42
ENSURING INDIVIDUALIZATION,
CHOICE, PERSON-CENTERED PLANNING,
AND SELF-DIRECTION
Often, service systems approach the needs of individuals
with autism as one-size-fits-all, yet the heterogeneity of
autism requires different supports for different people.
Individuals with ASD and their families want to be able to
make choices about their lives and actively engage in the
planning of their services and supports. According to a
National Core Indicators survey, the number of adults
with autism receiving services through developmental
disability (DD) agencies increased from 10% to 15%
between 2008/2009 and 2013/2014.
43
Further, of the
adults who used DD services, those with ASD had
significantly less input into all measured life choices
(e.g., choosing roommates, choosing day activities)
compared with those without autism. Also, fewer adults
with autism were legally independent adults without
guardianship (37%) than were adults without autism (53%).
In recent years, there have been greater efforts to advocate
for use of person-centered planning models, particularly in
Federal service systems. Medicaid-funded HCBS waivers
are required to be furnished according to a person-centered
plan of care, reflecting the services and supports that are
important for the individual to meet needs identified through
a functional assessment, as well as what is important to
the individual in terms of preferences for the delivery of
those services and supports. However, there are
many individuals with ASD who are not using HCBS
waivers but still need the right tools and services to achieve
person-centered care throughout their lifespan. While
research has identified some of the barriers to person-
centered planning, the services community has yet to
develop successful strategies to ensure individualization
and choice for individuals with ASD to lead independent
and meaningful lives.
CAREGIVER SUPPORTS
Caregivers may experience significant levels of stress
as they support an individual’s needs and manage medical
and therapy appointments, while also engaging in work and
other responsibilities.
44,45
The high cost of services also
creates increased financial strain for families, who often are
the main caregivers across the lifespan. Families often
need respite services to be able to take care of themselves,
have breaks from caregiving, and increase their own social
and emotional well-being so they are in turn able to support
and care for their family member with ASD.
46
Also, respite
care has been shown to reduce hospitalizations among
children with ASD.
47
Mindfulness-Based Stress Reduction
interventions have been shown to be helpful for families
of individuals with disabilities, but those studies have
primarily focused on families of children.
48
68
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Parent education about autism and parent training focused
on teaching behavior management strategies are both
effective in reducing disruptive behavior – with parent training
having a slight advantage in one study.
49
More research is
needed regarding the effectiveness of these services for
different parent populations and across different types of
parent educators.
Further, studies are needed to examine the transition of
care from parents to other family members, once parents
are no longer able to provide care. There is a rich history of
caregiver transition research among adults with intellectual
disability, but little is known about how this process occurs
in families caring for a relative with ASD.
OUTCOMES, QUALITY OF SERVICES,
AND SERVICE NEEDS
One size does not fit all when addressing unmet service
needs. Even though parents from both low- and high-income
homes have awareness of their child’s service needs,
parents from lower-income homes report more barriers to
accessing services. Specifically, they report needing more
information about services and more in-home services,
while higher-income parents report needing higher-quality
services.
50
Despite public investment in special education, studies
show high rates of disconnection from jobs and continued
education after high school. Of young adults who were
not working or attending school, 28% also received no
ASD-related services.
51
Overall, one-fourth (26%) of
young adults with autism received no services between
high school and their early twenties.
51
A qualitative study of service receipt and unmet service
needs during the last year of high school found that youth
with ASD in this cohort were receiving fewer services
than youth with ASD captured in earlier data from the
Department of Education’s National Longitudinal Transition
Study-2 (NTLTS2).
52
Two-thirds of the sample from the
2015 study had unmet service needs during the last year
of high school, with 30% having three or more unmet
needs. Specific needs included career counseling/job skills
training and life skills training. Youth with autism without
ID were far less likely to receive these services. Barriers
included cost, geographic access to services, and lack of
providers who accepted their insurance.
Results from the Pennsylvania Autism Needs Assessment
survey, which represented people with autism ages 2-59
years indicated that, compared to other age groups, adults
received fewer services for their specific unmet needs
in social skills training (43%), speech-language therapy
(22%), individual supports (21%), and occupational therapy
(21%).
53
Focus groups of Pennsylvania adults with ASD
who use Medicaid-funded services and those who care for
them identified a specific set of needs: training (co-occurring
diagnosis, sexuality, long-term planning), community
engagement (individualized community activities geared
to interests of individuals), socialization, and employment.
54
The complex needs of the service system make it difficult to
sustain implementation science. For example, organizations
trying to implement evidence-based practices might not
be able to maintain the cost to fund these services and
supports long-term. Current and future research initiatives
need to consider improving the service infrastructure.
HOUSING, SUPPORTS, AND OTHER
SERVICES ACROSS A CONTINUUM OF
SEVERITY AND NEED
Residential services, postsecondary education, employment
supports, behavioral and communication supports, lifetime
learning supports, and other services are discussed in
more detail in Questions 4 and 6 of the Strategic Plan, but
they are important to mention here in that these services
must also be provided based on the continuum of severity
and need, and they must be integrated with other services
as part of a coordinated system of services and care for
individuals with ASD.
69
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
WORKFORCE
Underlying many of the challenges described in the
above sections is the lack of a well-trained, supervised, and
motivated workforce. Several studies have documented
practitioners’ insufficient use of evidence-based practices
in community settings, as well as the difficulties associated
in implementing these practices because practitioners lack
appropriate pre-service training and preparation, oversight
in the field, or a sense that the use of these practices is
expected, supported, and rewarded.
55,56
The field of
implementation science has begun to address how to
impact practitioner behavior through organizational change
and direct-to-practitioner support. However, these
strategies do not address more fundamental issues related
to attracting highly qualified individuals to relevant
professions, creating pre-service training programs that
prepare individuals to deliver evidence-based care, and
keeping individuals in the field once they complete their
education and/or training.
COORDINATION OF SERVICES
There is also a need for systematic analyses of the
complexities of accessing the service systems. While there
is a lack of research in this area, families face multifaceted
challenges to access services that often delay the receipt of
early intervention services for a child. Expansion of Section
2703 of the ACA to include ASD and other developmental
disabilities may increase the number of families who
have a medical provider and a medical home and improve
access to and coordination of care. Coordination of service
sectors is urgently needed. Also, families must deal with
different sources of funding for services, frequently with
different rules for who, what, and how many services
can be provided, with no clear sources of information
about what these sources are and how they interact. The
different service sectors are not coordinated and often
do not communicate with each other, particularly across
health and social service agencies. In most instances,
there is not funding to support coordination or an assigned
liaison. There are other systematic barriers for families
such as differences in the type and amount of services
supported by insurance plans and the inequities and
disparities in type and amount of services available among
geographic location.
Individuals with autism often require services provided
through different agencies and paid for through different
systems. Care delivered across these systems often is
inefficiently and ineffectively coordinated. Some of the
challenges are endemic to systems that are providing care
concurrently (e.g., the education and healthcare systems);
other challenges are endemic to hand-offs between
systems as individuals age out of one set of programs
into another.
Some service models have been shown to promote better
integration of care. For example, health home models and
medical home models provide conceptual frameworks to
coordinate and integrate services, as well as build systems
of care for persons with ASD and their families.
57
Use of
these models is not widespread, however, nor do these
models address a host of other coordination challenges.
For example, analysis of the National Longitudinal Transition
Study-2 found that only 58% of youth with ASD reported
having received a transition plan by the Federally required
age.
51
The transition plan is a critical document that offers
a template for coordination between the school system
and systems that serve adults. In a 2012 report, GAO found
that youth and their families faced challenges in identifying,
navigating, and establishing eligibility for services for
adults with disabilities, including autism
58
(GAO-12-594).
The same report found that adult service systems did
not routinely provide a coordinated plan of services or
objectives for youth making transition to adulthood.
There is a particular gap in implementing and evaluating
the coordination between policy and practice for the
services needs of individuals with ASD.
70
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
SUMMARY
There are many opportunities for increased investment in
ASD services research to fill important gaps in knowledge
about what services are needed, how to best deliver
them, which services work for which communities, and
strategies to increase implementation of best practices
across settings. The Committee continues to highlight
the need for researchers to focus on developing practical,
affordable, and culturally competent services and support
approaches that can be used in a variety of settings, and
for these approaches to be able to be adapted to the
required scale to meet community needs. There also needs
to be an understanding of what portfolio of services will
result in the best outcomes for diverse populations. More
innovative research approaches and the resulting data will
be needed in the future to support progress toward the
IACC Question 5 Aspirational Goal of creating an
environment where "communities will develop, access,
and implement high-quality, evidence-based services and
supports that maximize quality of life and health across
the lifespan for all people with ASD and their families.
71
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVES
OBJECTIVE 1. Scale up and implement evidence-based interventions in community settings.
Examples:
Identify best practices, including systematic evidence-based collaborative approaches, to scale up existing services
and increase access to evidence-based interventions in communities.
Test and implement cost-effective healthcare services that increase the supply of care.
Develop approaches that scale up the use of evidence-based practices in the educational setting and address the gaps
between research and practice.
Funding for provider training is a part of Question 7 Objective 2, but is cross-referenced here because
successfully growing the service workforce is necessary to achieve this objective to successfully scale up and
deliver evidence-based ASD interventions.
OBJECTIVE 2. Reduce disparities in access and outcomes for underserved populations.
Examples:
Support research to understand and develop strategies to address health disparities, health inequity, and disparities
in services access and utilization for underserved populations. Underserved communities include families with low
socioeconomic resources, youth and adults with severe intellectual impairment, those who are racial/ethnic minorities,
and women.
Develop culturally competent service provision strategies, improve the quality of care and perception of quality of care
to encourage utilization, and increase family-centered care as well as other best practices to reduce disparities.
OBJECTIVE 3. Improve service models to ensure consistency of care across many domains with
the goal of maximizing outcomes and improving the value that individuals get from services.
Examples:
Develop better metrics and measurement tools for health outcomes of people with ASD across the lifespan.
Develop, test, and implement metrics and measurements for ASD services, as well as Federal, state, and local programs.
Quantify outcomes in order to inform effective service models.
Continue research into determinants of service quality, including accessibility, continuity, and flexibility of services.
QUESTION
6
HOW CAN WE MEET THE NEEDS OF
PEOPLE WITH ASD AS THEY PROGRESS
INTO AND THROUGH ADULTHOOD?
73
Aspirational Goal: All people with ASD will have the opportunity to lead
self-determined lives in the community of their choice through school, work,
community participation, satisfying relationships, and meaningful access
to services and supports.
INTRODUCTION
Each year in the United States, approximately 50,000
individuals with autism spectrum disorder (ASD) turn 18
years old.
1
According to 2016 Centers for Disease Control and
Prevention (CDC) data, prevalence of ASD in 8-year-olds
rose dramatically from 1 in 150 in 2002 to 1 in 68 in 2012.
2
The 2002 cohort is now 23 years of age. Thus, across the
next decade, we can expect a 123% increase in the number
of youth with an ASD diagnosis exiting secondary school.
There are significant concerns about how this increase will
affect the transition and adult disability service systems.
Research to understand the unique needs of this growing
population is urgently needed in order to develop services
and programs that facilitate opportunities for people on the
autism spectrum to lead fulfilling, self-determined lives.
Since the 2013 IACC Strategic Plan Update, there has been
continued progress in understanding adult life for those on
the autism spectrum. Nearly every study finds that adults
with ASD have difficulty accessing disability and medical
services, experience high rates of unemployment and
underemployment, face difficulties in daily living skills and
achieving independence, and contend with elevated rates
of physical and mental health disabilities. However, we
also know that some individuals with autism do experience
positive outcomes. Little progress has been made in
understanding how best to support these individuals and
their families so that good outcomes are the norm rather
than the exception. This leaves providers and policy makers
with an absence of evidence-based knowledge to use
when deciding which services, supports, and programs
will be most beneficial to adults with ASD, and few
resources to implement those programs.
The increasingly influential voice of the self-advocacy
community has highlighted the vast heterogeneity in
strengths, impairments, and functioning among adults with
ASD. Thus, real progress toward achieving the Aspirational
Goal is even more challenging than previously thought, as
it is highly unlikely that any given service or program can
effectively meet the needs of all adults with ASD. Yet,
these same voices also highlight the many and varied ways
that adults with ASD can make rich contributions to society,
making it even more imperative to understand how to
support them in achieving their highest potential.
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
74
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
It is important to note that nearly every study cited in
the following sections focuses on early adulthood and the
transition years, and utilizes samples with little racial/
ethnic or socioeconomic diversity. It is unclear to what
extent these findings apply to individuals in mid- or
later-adulthood, from racial/ethnic minority groups, or
with fewer socioeconomic resources.
PROGRESS IN THE FIELD
TRANSITION TO ADULTHOOD
The years immediately prior to the 2013 IACC Strategic Plan
Update – from 2010 to 2013 – were instrumental to
demonstrating the challenges faced by youth with ASD and
their families during the transition out of secondary school
and into adult life. Studies during this time demonstrated
high rates of unemployment and underemployment,
3,4
difficulties accessing services,
5
disconnection from friendship
and social activities,
6
and the negative impacts of secondary
school exit on behavioral development.
7
Increasing access to vocational rehabilitation (VR) services
for adults with ASD has not significantly improved
employment outcomes across the last decade; only one-
third of adults with ASD receiving VR services achieve
successful employment.
8
These adults earned lower wages
and worked fewer hours than other young adults with
disabilities receiving services. Thus, even when receiving
services, employment outcomes are poor for young
adults with ASD.
Pursuing postsecondary education can be important in
fostering independence, self-determination, and employment
success. Greater numbers of individuals with ASD
are seeking higher education opportunities in vocational/
technical skills, 2-year colleges, and 4-year colleges/
universities.
9,10
Yet, fewer than half of college students with
ASD feel they are able to handle most of the challenges
they encounter.
1
The types of needed supports identified
by individuals with ASD in higher education settings are
not those typically provided by disability services, such as
supports for living on campus or living independently,
training to engage in self-advocacy, and interacting effectively
with peers and instructors.
11
For students with ASD who
have significant mental health concerns, intensive services
addressing emotion regulation in addition to the
organizational and social skills necessary for college success
may be needed. For students with co-occurring intellectual
disability, a college-like transition program with a focus
on independent living skills may be appropriate.
Little has been published on issues related to community
participation, such as housing, social participation, and
community integration, since the 2013 IACC Strategic Plan
Update. There is some evidence to suggest that youth with
ASD tend to become more isolated from structured social/
recreational activities in the community after leaving
secondary school.
12,13
This may be problematic for many,
as the presence of meaningful daytime activity is a key
contributor to quality of life.
14
While no new data has been
published on housing for people with ASD since the
2013 IACC Strategic Plan Update, the most recent study
found 87% of young adults with ASD lived with their
parents or guardian after high school and only 19% had
lived independently.
15
There is a growing number of small intervention trials,
funded through the National Institutes of Health, aimed
at smoothing the transition process and improving adult
outcomes for people with ASD. Targeted initiatives
75
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
responsive to objectives in the previous IACC Strategic Plan
are supporting many of these new interventions. Ongoing
studies are testing programs to: improve transition planning
in schools; train parents how to advocate more effectively
for adult disability services;
16
improve family climate
through group psychoeducational intervention;
17
target
self-regulation and social competence among college
students with ASD;
18
improve employment supports;
19
increase social skills,
20
and build job interviewing skills
and customized employment supports.
21,22,23
Those
interventions that show promising initial results ideally
will be tested in large-scale randomized controlled
trials, with the ultimate goal of incorporating them into
intervention options to improve adult outcomes.
Despite these promising new directions for research,
important gaps in knowledge remain. First, much of our
information about the transition to adulthood comes from
large, population-based studies such as the National
Longitudinal Transition Study-2 (NLTS-2). These studies
have provided seminal information about the range and
scope of needs of youth with ASD exiting secondary
school in the United States. Yet, the measurement in these
datasets does not have the detailed, personalized information
needed to provide targeted recommendations to disability
service workers on college campuses, parents who
want their sons and daughters to succeed in college or
employment, or adults themselves who are searching for
the most appropriate services and supports based on
their unique situations. Coupling high-level snapshots like
the NLTS-2 with “deep-dive” data collection into the lives
of adults with ASD of all ages will likely provide the
best evidence about how to support these individuals.
Furthermore, the ASD community could benefit from a close
examination of research and services strategies that have
been effective with other vulnerable youth (e.g., exiting
foster care) and adult (e.g., those with severe mental illness)
populations to identify policy and practice approaches
that could be adapted for people on the autism spectrum.
Given the high level of need, many publicly and privately
funded initiatives are in place to improve post-secondary
educational and employment participation and retention.
College support programs for students with ASD are
developing across the country, and college and universities
without these programs consistently express a need for
greater ASD-related support services. Yet, the effectiveness
of these post-secondary education and employment
programs is almost never evaluated. It is important to
determine which of these many initiatives are producing
positive results and for whom, so that an evidence base can
be developed to guide service providers and policy makers
as they are deciding which programs to implement.
Many of the cohort studies that inform our knowledge
base about transition and adult outcomes involve samples
of individuals who were diagnosed with ASD 20, 30, or even
40 years ago.
24,25,26
With the many fast-moving initiatives
around transition services and supports, community
employment, and access to post-secondary education, it
is unclear whether the post-school activities of youth with
ASD who left secondary school 10 or more years ago are
representative of today’s youth. Thus, it will be important
to follow existing cohorts in the future, as well as
continue to develop and follow new cohorts of youth with
ASD as they transition to adulthood. This combination
of strategies will allow us to understand development
throughout adulthood, and ensure that recommendations
for transition-related interventions and services do not
reflect outdated needs of individuals and families.
LIFE COURSE OUTCOMES BEYOND
TRANSITION: EMPLOYMENT, VOCATIONAL
SKILLS, AND COMMUNITY INTEGRATION
Although most studies on adult outcomes since the last
IACC Strategic Plan update have focused on the
transition years, a handful have examined outcomes beyond
early adulthood. Discoveries in the employment realm
have centered on understanding patterns over time.
76
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
For many people with ASD, maintaining work or post-
secondary educational positions once they are obtained
is a significant challenge.
27, 28
The few studies that have
examined employment beyond young adulthood do not
find patterns of improvement over time; most adults who
are unemployed or underemployed in early adulthood
tend to stay that way, and independence in vocation-
al positions declines over time for some.
25,29
Also, many
adults with ASD are working in segregated work settings.
In 2014, the Workforce Innovation and Opportunity Act
(WIOA) was signed into law to help increase competitive
employment opportunities for individuals with disabilities.
However, there is limited research focused on adults with
ASD transitioning from segregated work settings into
integrated employment. It is important to note, however,
that poor employment outcomes are not universal; some
adults with ASD successfully obtain and maintain jobs.
Little is known about the factors that distinguish those
adults who have greater versus fewer struggles with
employment; those factors that have been identified are
difficult or impossible to change, such as IQ or early
language. One notable exception is self-care skills, which
consistently predict employment and are amenable to
intervention.
3,29
There is a limited body of research
examining employment supports available to some adults
with ASD and how they can be beneficial to maintaining
employment, such as the use of low- and high-tech
assistive technologies and communication aids, natural
supports, and mentoring. A wide variety of employment
service options are needed, including expanding current
models of job finding and development services, long-term
intensive services and supports, and long-term but
minimal supports (e.g., a few hours/month).
There is almost no research on the community participation
of adults with ASD in middle or later adulthood. The needs
of individuals with ASD in terms of employment, housing,
social participation, and community integration almost
certainly change as they age. There is also a need for research
on transportation access for adults with ASD, including for
commuting to work and traveling to school, healthcare
services, and community life activities. Yet, evidence to
support the development of targeted programs and support
is woefully lacking. Families and corporations are leading
the way in innovations to find and sustain meaningful
employment and community housing for adults with ASD,
but further research as well as state and Federal government
programs are needed to address current and future needs.
The heterogeneity of ASD traits and severity for those on
the spectrum necessitates a variety of housing options to
fit the specific service needs of each individual. Perhaps
by virtue of the required infrastructure, housing options
have been slow to respond to changing needs, values, and
research findings regarding adults with ASD. Lakin and
colleagues (2008)
30
describe the national agenda to
increase the number of community-based housing options
for individuals with intellectual disabilities as a way of
increasing community participation and self-determined
choice making. The recent final rule from CMS gives clear
preference to small, community-based homes over larger
congregate care settings and intentional communities.
Some advocates have hailed this ruling as a victory that
will increase community participation; others, especially
those who care for severely impaired and medically
fragile individuals, have expressed grave concerns that
appropriate care will not be available under this new
financing arrangement. There are remarkably little data
available to support which housing options work best for
which individuals, with studies presenting contradictory
findings regarding the level of community participation
and choice making that individuals with ASD or ID have
in different housing options.
31,32
Research is desperately
needed on the most appropriate housing arrangements
and in-home supports, and perhaps more importantly,
strategies to better observe what happens in these
arrangements, to increase community engagement,
and to maximize quality of life.
77
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Longitudinal studies of adults with ASD remain rare, but
those that have been conducted provide some suggestion
that many adults move into and out of “successful
outcomes” across adulthood.
25,27,28,29
To make progress
toward the Aspirational Goal, there needs to be more
focus on understanding how outcomes and needs of adults
with ASD change over time, and how these variations
compare to the general population. A one-dimensional look
at outcomes such as vocation, health, illness, or quality
of life at a specific point in time will not capture the rich
diversity of life course trajectories. Further, it is almost
certainly the case that interventions and programs to
improve outcomes are more or less effective depending
on when during adulthood they are delivered (right out of
secondary school, for example, versus later in adulthood).
However, we lack the basic, large-sample, descriptive
studies to understand which types of interventions and
services might be most effective for which adults, and
when in the life course they have the most influence.
Another barrier that slows progress in adult ASD research
is the inadequacy of current measurement tools. Without
valid, sensitive outcome measures, it becomes exponentially
more difficult to detect whether an intervention or service
is effective and should be pursued. Further, it may be
necessary to reconsider indicators of outcome altogether.
Studies have typically defined what constitutes a “good
outcome” (e.g., community employment, spending time
with friends) and thus should be the target of services and
supports. However, it is unknown whether these outcomes
are the most meaningful to individuals with ASD or their
families. It may be that the fit of the activities to the
individuals’ interests and abilities is most important, or it
may be that subjective quality of life should be an equal or
greater focus as objective indicators like employment or
post-secondary education. To reach the Aspirational Goal,
careful research is needed to understand how to define
“good” outcomes in a systematic yet personalized way,
and then measurement tools are needed that reliably capture
those outcomes. Once outcomes can be assessed in a way
that takes into account the desires, skills, and abilities of
adults with ASD and their families, then the Aspirational
Goal of developing programs and supports that allow
adults on the autism spectrum to reach those outcomes
will be more feasible.
HEALTH AND HEALTHCARE
Current knowledge about mental health, physical health,
and healthcare experiences among adults with ASD is also
limited. Co-occurring psychiatric conditions (i.e., two or
more mental health diagnoses co-occurring in an individual),
known to be high among children and adolescents with
ASD, remains challenging in adulthood. Most children with
ASD who have other psychiatric disorders continue to
have at least one co-occurring diagnosis in adolescence and
early adulthood.
33
More than half of adults with ASD have
at least one additional psychiatric disorder, a rate that is
considerably higher than in the general population.
34
Difficulties with mood and anxiety appear to be most
problematic,
35,36,37
and failing to address these mental
health symptoms adequately can lead to poor outcomes.
For example, individuals with ASD with higher levels
of anxiety and depressive symptoms are more likely to
experience difficulties in adaptive functioning.
38
Even
more sobering, recent research has indicated the rate of
suicidality is estimated to be nine times higher among
adults with ASD than in the general population.
39
Outside
of person-level factors such as gender, verbal ability, and
ASD severity,
33,35
little is known about the full range of
factors related to stability or emergence of co-occurring
psychopathology among these adults.
Co-occurring physical conditions are also a concern.
Compared to adults without ASD, those with ASD have
increased rates of common physical health conditions
(e.g., sleep disorders, gastrointestinal disorders,
and diabetes), as well as rarer conditions (e.g., stroke,
Parkinson’s disease, and genetic disorders).
34
Children and
adults with ASD in the United States have a higher risk of
78
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
being overweight or obese than the general population,
putting them at risk for cardiovascular disease, cancer, and
other chronic conditions across the lifespan. More work
must be done to develop and test interventions that
prevent, control, and/or moderate the effects of physical
and mental health disabilities.
40
While adults with ASD experience increased rates of
co-occurring conditions, individuals with ASD are also at
greater risk of injuries such as falls, suffocation, drowning,
and self-harm.
42,49
Unintentional injuries and wandering
can often lead to premature mortality, indicating the critical
need for prevention programs targeting these risks.
49
There is also a lack of research on understanding alcohol
and substance abuse disorders among adults with ASD,
but this will be necessary for developing and implementing
prevention and treatment strategies.
41
Other health
concerns related to safety and risk, such as wandering
and victimization, are discussed later in this chapter.
Studies on healthcare utilization indicate adults with ASD
utilize a disproportionate amount of outpatient, inpatient,
prescription, and emergency department services.
31,42,43,44
Only one study has examined self-reported utilization of
preventive services, finding that adults with ASD were
significantly less likely to report tetanus vaccination and
pap (Papanicolaou) smears than adults without ASD.
44
Further, adults with ASD experience more barriers to
service use and participation in the medical visit, as well as
lower satisfaction.
40,44,45
Specific barriers include anxiety
related to the medical visit, as well as unmet needs for
additional time to process information and ask questions,
additional modes of communication, and reduction of
sensory stimulation. It is important to note that self-report
is a substantial challenge for many adults with ASD when
visiting medical settings. The physician-patient dynamic
is highly dependent upon the patient describing specific
details of acute and chronic conditions, including pain and
injury; it is often difficult for adults with ASD to engage in
the same manner of self-report of medical conditions.
45
Relatively little is known about the aging process in people
with ASD and what types of interventions, services, and
supports might foster health maintenance as individuals
age. Several studies have suggested that people on the
autism spectrum are vulnerable to premature death due
to a number of causes, including epilepsy, late diagnosis
of medical conditions, and accidents.
39,46,47,48,49
More
research is needed to understand causal and risk factors
and develop strategies to prevent early death. In addition,
research on how autism characteristics, co-occurring
conditions, and physical and social functioning change
during the aging process will be needed to develop
evidence-based practices to support the needs of people
with ASD as they age. We anticipate that the needs of
those who are currently older adults, who may not have
received interventions and services earlier in life, may also
be different from the needs of current youth and young
adults who received different types of interventions and
services in the period before reaching adulthood.
50
Thus,
research on current older adults with ASD and longitudinal
research to follow the trajectories of youth and young
adults will both be necessary to meet the needs of the
population of adults with ASD.
51,52
Although there is a reasonably good understanding of
the prevalence and disparities in various health states
for adults with ASD, there are several gaps in this
knowledge base, including how best to screen for and
clinically assess secondary conditions and monitor
progress, as well as treatment dissemination and provider
training.
25, 53
There have been few attempts to establish
the validity of instruments commonly used to assess other
psychiatric conditions in individuals with ASD. There has
also been limited consideration of differences in how
the manifestations, course, or treatment of psychiatric
disorders might differ for these adults. Further, the majority
of studies on physical health needs of adults with ASD
utilize retrospective point-in-time data and lack objective
79
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
health assessment measures. Better measurement tools
and methods are necessary to understand the scope of
physical and mental health needs and design appropriate
services and supports.
Research involving adults with ASD clearly show that
they desire and are often capable of more independent
management of their health.
44,54
To ensure these adults
are able to participate in their care to their fullest
abilities, the healthcare system must increase health
professionals’ knowledge about ASD in general and risk
factors for co-occurring conditions. Similar to the
general population, providers should examine the adult’s
general physical and mental health needs and provide
guidance on how to ensure the person is living the healthiest
and highest quality of life possible. Small adjustments to
the clinic setting (e.g., preparatory written/verbal
communication about visit procedures, private waiting
rooms, use of alternative forms of communication, care
coordination, and extended time) can greatly improve
the healthcare experience, compliance, and involvement
for adults with ASD. Previous initiatives to improve care
for those with ASD in the United States have fallen
short in allocating funding and provide little guidance
regarding appropriate care for this population.
ADULT DIAGNOSIS
Longitudinal studies demonstrate clear evidence that
ASD-related difficulties persist well into adulthood. In several
cohorts of children diagnosed with ASD in early childhood,
80-90% of individuals continued to meet criteria for
clinical diagnoses of ASD as adults.
24,55
Simultaneously,
increasing numbers of adults are presenting to clinics for
first-time diagnoses, and recent epidemiological work
suggests that many adults with ASD may be unidentified
and living in the community without appropriate supports.
56
In addition, as development of screening and diagnostic
tools, as well as other autism research, has largely been
accomplished using data from boys and men, girls and
women on the autism spectrum may be underdiagnosed,
and we know little about their ASD trajectories across
the lifespan.
34,57,58
Research to improve adult diagnosis is very new and, as such,
there are many important gaps and areas for future study.
First, there is limited knowledge of the manifestations of
ASD in adults. Longitudinal studies have found that some
adults with ASD show “improvement” in autism severity
compared to estimates obtained during earlier childhood
or young adulthood.
25,59,60
However, an extensive body of
child research has shown that ASD characteristics differ
depending on a child’s developmental stage (i.e., language
and cognitive abilities, as well as chronological age), and
the types of behaviors that best differentiate children from
neurotypical peers are somewhat different from behaviors
that differentiate adults with ASD from neurotypical
peers.
61,62
Thus, apparent “decreases” in autistic
characteristics may simply reflect that instruments
designed for use with children do not adequately query
the types of behaviors or deficits most relevant to adults
with ASD. Currently, there is not a standard tool or
measurement used for diagnosing ASD in adults. However,
there is an ongoing study to adapt the Autism Diagnostic
Observation Schedule-2 (ADOS-2) Module 4 for use in
diagnosing adults.
62,63
There is also hope that work being
done to create biomarkers that predict ASD, such as
perceptual computing measurements of quantitative traits,
will be able to be adapted as tools for diagnosing adults
as well.
64
Research is needed to understand how ASD
characteristics change across development and how core
deficits manifest in adults. Studies must include consideration
of young, middle-aged, and older adults, including those
diagnosed as children and those identified in later life.
Second, little is known about individuals who obtain
first-time ASD diagnoses as adults. Many of these adults
have other mental health concerns; in one study of young
adults seeking a first-time ASD diagnosis, 46% had a
previous psychiatric diagnosis, and 53% had contact with
80
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
mental health services.
65
These findings suggest that a
population of individuals with high needs is being
misdiagnosed or “missed” as children. Research is needed
to understand profiles of strengths and challenges of this
population, to inform development of screening and
diagnostic tools and best diagnostic practices for adult
ASD referrals. Such research will need to take into account
that adult psychiatric assessment traditionally relies on
self-report, whereas ASD diagnostic practices rely more
on direct observation in structured clinical settings and/
or caregiver report. Childhood caregivers may not be
available or may have difficulty recalling specific behaviors
occurring many decades ago. Exclusive reliance on self-report
may also not be ideal, due to possible limitations in insight,
communicative difficulties, or over-reporting of autism
characteristics to achieve secondary gain (e.g., involvement
in legal system, to obtain financial assistance).
Third, currently it is not known if and how later-life diagnosis
affects mental health or well-being, or fosters identification
of supports or interventions. Considering that state-funded
support programs often require documentation of
diagnosis prior to 18 or 22 years of age, it is unlikely that
someone diagnosed in middle adulthood would be able
to access ASD-related supports. Obtaining a diagnosis
in the absence of appropriate services and supports may
be detrimental to well-being for some individuals. On the
other hand, they may benefit from private services,
participation in online communities for individuals with
ASD, etc. Research in this area is needed to educate adults
self-referring for diagnosis about the possible benefits
and risks of obtaining an ASD diagnosis, as well as to
provide insights into the types of services that should be
developed to support the adult’s integration of diagnosis
into their self-perceptions.
SERVICE DELIVERY FOR ADULTS
As the research base continues to build, there are
improvements in service delivery that can be made to reach
the Aspirational Goal more quickly. First, it is critical that
additional funding is provided for adult disability services.
Currently, waiting lists for services in most states are very
long, and adults with ASD rarely receive the range and
extent of services that would allow them to reach their
potential. Adults with ASD and their families who are more
vulnerable to poor outcomes in adulthood – by virtue of
having fewer socioeconomic resources or being of a racial/
ethnic minority group – also have the greatest difficulty
accessing needed services.
3,5
It will be nearly impossible
to reach the Aspirational Goal of self-determination,
choice, and meaningful access to services – especially
for those who are most vulnerable – without a significant
investment in the quantity and quality of adult disability
services and actively working to reduce barriers to access.
One way to increase quality is to invest more in the training
of professionals, across disciplines, to work effectively
with adults with ASD. Few adult care providers (healthcare,
mental health, employment supports, etc.) have received
training on how to support adults with ASD. The implications
of this lack of training are far-reaching. Staff turnover is a
significant issue in vocational and residential support
services, and likely stems (at least in part) from inadequate
training. Many adults with ASD receive their healthcare
in pediatric settings, due to a dearth of adult providers
who feel competent and comfortable treating them. This
can pose a health risk, as pediatric providers are not
trained to treat adult health issues. In terms of diagnostic
issues, few validated screening and diagnostic instruments
are available for use in identification of ASD in adults, and
few clinicians specializing in adult screening and diagnosis
are available to provide services. Neither Psychology nor
Psychiatry educational programs (as well as other disciplines)
are adequately preparing trainees to diagnose adults
with ASD. The few programs that offer clinical rotations
81
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
through specialty clinics often focus on persons under
the age of 18 or 22, due to their presence in pediatric
departments. As such, there is a need for training grants
and initiatives focused on training professionals who will be
working with adults to detect, diagnose, and address mental
and physical health-related needs in this population.
Progress will be achieved more quickly if greater focus
is placed on the coordination of services between states,
between agencies that provide adult services, and
between school-based and adult services. Currently,
Medicaid-funded services do not transfer between states,
limiting people’s mobility when relocation to another state
would serve them well. Given that most adults with
autism have complex needs that bring them into contact
with multiple public service systems, there is an urgent
need for research and initiatives focused on care
coordination, interagency collaboration, strategies for
integrating extant funding streams, and community-based
collective impact strategies. WIOA specifies that state
VR agencies must set aside 15% of their funding to provide
pre-employment transition services (pre-ETS) to secondary
school students who are eligible under either the Individuals
with Disabilities Education Act or Rehabilitation Act Section
504. However, it remains to be seen if state agencies will
be able to carry out the responsibilities associated with
legislation such as WIOA. It will be important to monitor
the effectiveness of these initiatives with careful data
collection and analyses. Also, WIOA is designed to
encourage state-level experimentation and variability in
program design. This presents a unique opportunity to
study emerging practices and capitalize on this variability
to learn what works for whom.
SAFETY, VICTIMIZATION, AND
INTERACTIONS WITH LAW ENFORCEMENT
In the past 5 years, safety issues have emerged as a
key concern in the autism spectrum community, yet the
research evidence on this topic has lagged far behind.
Elopement and peer victimization (social, verbal, and
physical) are common in children and adolescents with
ASD, but there is limited research on these topics as they
relate to adults.
66,67
A 2012 survey conducted by the
National Autistic Society in the UK found over a third of
adults with ASD experienced bullying or discrimination at
work.
68
A recent report suggested that, relative to adults
in the general population, adults with ASD were twice as
likely to experience sexual coercion or rape.
69
Although
there is some suggestion that adults on the autism
spectrum might more often be involved in the criminal
justice system, recent data from the NLTS-2 suggests that
transition-aged youth with ASD were actually less likely
than those with other disabilities to be stopped by police
or arrested.
70
It might be that when they are engaged with
police, impairments related to ASD make those interactions
more difficult, leading to negative outcomes.
Careful research is needed to understand the experiences
of victimization in adulthood – sexual victimization, physical
victimization, and being taken advantage of – as well as
the prevalence of other safety risks, such as wandering and
the often adverse outcomes that unfold from wandering.
While little is known about adults with ASD wandering
behaviors, a recent report found 27% of adolescents
engaged in wandering behavior within the past year.
10
Wandering from safe places and situations can lead to
individuals with ASD being lost, missing, or injured.
Studies are needed to understand the characteristics of
those adults whose safety is at risk, so that preventative
efforts can be put into place. Research focused on adults
in the criminal justice system is also important to
understand precipitating factors for criminality or adverse
interactions with law enforcement; Helverschou et al.
(2015)
71
found that among criminal offenders with ASD
in Norway, 67% of crimes were related to obsessions or
special interest. A recent study assessing the experiences
of adults with ASD and police officers in England showed
conflicting views on the quality of the interaction;
72
82
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
police officers expressed satisfaction with how they
had worked with individuals with ASD, whereas the
individuals with ASD were largely dissatisfied with their
police interaction. Research strategies to develop a better
understanding among law enforcement might lead to less
adverse interactions and result in treatment rather than
incarceration, which does not improve the situation
for people with disabilities. Long-term studies should also
examine the impact of childhood victimization or other
threats to safety, as these might lead to mental health
concerns among adults with ASD.
73
Intervention studies
to improve awareness and safety are necessary.
There are currently a limited number of programs to improve
safety for individuals with ASD. In some communities,
policy officers and judges receive training on autism spectrum
features, so that impairments associated with ASD are
appropriately considered in interactions. Despite this, the
current research is insufficient to understand the types
and extent of need, or to inform evidence-based programs
to ensure safety among adults on the autism spectrum.
LONG-TERM AND CAREGIVER SUPPORTS
One of the best understood predictors of outcomes in
adulthood is level of cognitive functioning: relative to those
with ASD without an intellectual disability, adults with
ASD who have an intellectual disability are significantly
less likely to be employed or living in the community
(e.g., Howlin and Magiati, 2017).
74
However, little is known
about how to support adults with ASD and co-occurring
intellectual disability in reaching their maximum potential.
More work is needed to understand and evaluate the
effectiveness of long-term supports for those with high
support needs (such as those with significant cognitive
impairments). As many of these adults will be receiving
some sort of formal adult disability service, more rapid
headway can be made in this area if service providers
systematically collect outcome data. As with other areas,
the results will not be one-size-fits-all: the most
appropriate supports will depend on the skills and desires
of the adult, as well as the specific area being targeted
(e.g., vocational skills versus mental health). Supports should
also take a lifespan developmental perspective, encouraging
the development of new skills and abilities throughout
adulthood. For those adults with difficulty communicating,
parents and other care providers can play a key role in
relaying their sons’ and daughters’ preferences and
interests. Person-Centered Planning tools such as PATHs
75
and MAPs
76
can be useful to incorporate the perspectives
of adults with ASD with more significant impairments.
Further, the knowledge base about how to support
individuals with ASD as they move into middle and later
adulthood is almost non-existent. Small-sample studies
have provided some suggestion that needed supports will
likely intensify in old age; relative to typically developing
controls, older adults with ASD experienced more severe
cognitive declines in some domains and higher frequency
of Parkinsonism.
77,78
Housing needs will surely intensify
when parents are no longer able to provide care.
Often families play a critical role in providing support
to their adult sons and daughters on the autism spectrum.
Once youth with ASD leave the school system, responsibility
for finding and coordinating services tends to fall to parents
and siblings. In many cases, adults with ASD continue
to live with their parents until parents are no longer able
to care for them. Even when adults live independently or
semi-independently, parents often provide supports
(e.g., financial, tangible) that facilitate the son or daughter
remaining in that residential situation. For many adults
who are better integrated into their communities, high
support needs can greatly exceed available resources of
family members for coordinating and organizing
community-based life activities.
12,79
Exceedingly high
levels of stress among parents of adults with ASD have
been found via self-report measures as well as biological
indicators of stress (e.g., cortisol).
80
However, there
are few interventions aimed at supporting families.
83
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Most parent-focused interventions, when their children with
ASD are adults, provide caregivers with skills or knowledge
to better support their sons and daughters, and not
necessarily to improve their own stress and well-being.
16,17
Despite the prominent role of families in the lives of their
adult sons and daughters with ASD, their influence is often
ignored in research. There is a significant research gap in
understanding which families are most effective in
supporting their adult offspring with ASD, as well as in
how to provide services and supports so that families can
continue to provide care.
81
These research questions
become even more important in the face of an underfunded
adult service system. Because housing and other adult
services are limited in availability, it is even more critical
for policy makers and providers to ensure that families are
well-supported so that they can continue their caregiving
role as long as possible.
SUMMARY
To understand how to support adults with ASD, it is first
necessary to investigate the specific areas in which adults
might need supports. This is, perhaps, where the greatest
progress toward the Aspirational Goal has been made.
We have reasonably strong evidence about the struggles
faced by adults with ASD in acquiring needed disability
services, accessing healthcare, finding appropriate
employment or vocational activities, and achieving good
mental health – at least during young adulthood.
3,5,26,35,38,82
Yet beyond basic description, there are numerous gaps in
knowledge that limit our ability to support these adults
effectively. The vast majority of what is known about
autism spectrum disorders in adulthood has come from
samples of primarily white, middle-class, well-resourced
families of males with ASD who are of average or above
average intellectual functioning. It is unclear how much of
our current knowledge about how to achieve the Aspirational
Goal would translate to those adults and families who are
under-represented in research. Thus, studies should focus
on including more diverse participants, including families
with low socioeconomic resources, youth and adults with
severe intellectual impairment, those who are of racial/
ethnic minorities, and women on the autism spectrum.
It is unlikely that we will make meaningful progress toward
the Aspirational Goal without substantially increasing
funding for autism research and services focused on adults.
Research focused on adult issues has lagged far behind
other types of ASD-related research, comprising only
2% of all autism research spending in 2015.
83
Many fundamental questions about the life course that
are unanswered among adults with ASD – such as
basic understandings of how core and related autism
characteristics, functional outcomes (e.g., employment,
education, independent living), and health change across
adulthood, along with the variable factors that predict
improving life course trajectories and quality of life – have
been well-researched in other groups and conditions.
These questions form the necessary building blocks for
effective and efficient interventions and services;
nevertheless, these questions can be seen as lacking
significance or innovation for those outside the autism field
(who assume the answers are known). This can be a
significant barrier when attempting to obtain funding for
adult autism research. We will make more rapid progress
toward realizing the Aspiration Goal once it is clear that
a range of studies – from understanding biological and
cognitive processes underlying outcomes, to more “natural
history” studies of the life course, to evaluating existing
services, to intervention trials to improve outcomes – are
critical to support adults with ASD in reaching their
maximum potential.
84
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVES
OBJECTIVE 1: Support development and coordination of integrated services to help youth make
a successful transition to adulthood and provide supports throughout the lifespan.
Examples:
Use population-level data to understand unmet needs, disparities in access and outcomes, emerging usage trends,
cost issues and the effectiveness of services in achieving their desired outcomes.
Conduct research to determine the prevalence of autism in adults and the scope and distribution of service needs
among the population to inform policy and program planning.
Develop strategies for reducing socioeconomic or racial/ethnic disparities in service access and related outcomes
for adults with ASD.
Investigate social capital, the network of supports, and community integration provided by families, service providers,
and others to understand the range of formal and informal supports needed to achieve successful adult outcomes.
Develop additional service coordination across agencies (e.g., educational and vocational rehabilitation; mental health
and vocational rehabilitation).
OBJECTIVE 2: Support research and implement approaches to reduce disabling co-occurring
physical and mental health conditions in adults with ASD, with the goal of improving safety, reducing
premature mortality, and enhancing quality of life.
Examples:
Conduct large-scale longitudinal studies across adulthood into older age to examine trajectories of physical and
mental health conditions, and address the additive and interactive effects of biological, cognitive, behavioral, and
environmental factors that lead to co-occurring conditions.
Conduct studies to improve self-management of co-occurring mental health disabilities, including anxiety, depression,
and/or suicidality.
Engage adults on the autism spectrum and their families, through collaborative and participatory research, to be
involved in the development of ecologically valid measures of quality of life, which can be used to understand the
factors associated with positive quality of life throughout adulthood.
Create programs to recruit and train more general physical and mental health providers to be knowledgeable about
and willing to treat adults with ASD. This applies to primary care providers, community mental health providers,
and specialists.
85
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVE 3: Support research, services activities, and outreach efforts that facilitate and
incorporate acceptance, accommodation, inclusion, independence, and integration of people on
the autism spectrum into society.
Examples:
Examine factors and support strategies that promote successful participation and retention in post-secondary
education, employment, and/or community living activities across the spectrum of ASD and across the adult lifespan.
Develop reliable outcome measures that take into account the desires of the individual and his/her family, as well as
the match of the activity with the interests, skills, and abilities of the adult.
Conduct long-term follow-up studies examining the effects of interventions and services delivered in childhood on
later adult outcomes.
Conduct large-scale studies of programs to improve the skills that may underlie many aspects of community
integration (e.g., adaptive behavior, executive function)
Better understand the needs of adult service providers, as well as the characteristics of effective providers.
Encourage more skilled workers to enter and remain in the adult disability service provider field, which is critical to
improving self-determination of adults with ASD.
QUESTION
7
HOW DO WE CONTINUE TO BUILD,
EXPAND, AND ENHANCE THE
INFRASTRUCTURE SYSTEM TO MEET
THE NEEDS OF THE ASD COMMUNITY?
87
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Aspirational Goal: Develop, enhance, and support infrastructure and
surveillance systems that advance the speed, efficacy, and dissemination
of ASD research and services.
INTRODUCTION
Appropriate research infrastructure is critically important
to the success of the IACC Strategic Plan, and progress
toward the Aspirational Goal has been rapid over the past
8 years. New databases are being built to leverage recent
genetics findings, and efforts to share biospecimens
among multiple research efforts are intensifying.
This increased availability of resources has advanced
the efficacy and speed of ASD research. Surveillance
systems have also progressed over the past 8 years, with
new efforts focused on tracking more descriptive symptoms
as well as a binary diagnosis. As the diagnosis of autism
has broadened, more children are being identified who
do not have co-occurring cognitive disability, and
additional resources have been focused on serving the
needs of people across a diverse spectrum. Furthermore,
many government and private organizations regularly share
lay-audience-friendly summaries of research findings to
raise community awareness, including Simons Foundation,
Autism Science Foundation, Autism Speaks, the Interactive
Autism Network (IAN), the National Institutes of
Health (NIH), and the Centers for Disease Control
and Prevention (CDC).
In 2010, the IACC decided to track investments and evaluate
progress in this area in the same organized, rigorous manner
that is used in the rest of its Strategic Plan. From 2009-2015,
a total of $302 million dollars has been invested in building
and maintaining ASD research infrastructure, including
surveillance efforts. While many of the original infrastructure
needs identified in 2010 have been accomplished, continued
investment is critical in order to maintain, develop, and
build on these valuable resources. Specifically, there must
be a focus on enhancing the biorepository infrastructure,
the data infrastructure, the human infrastructure,
and surveillance activities in order for autism research
to be successful.
88
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
BIOREPOSITORY INFRASTRUCTURE
Biological materials repositories collect, process, store, and
distribute biospecimens to support scientific investigation.
In the autism research community, biorepositories have
been developed to support collection and dissemination
of brain tissue, fibroblasts, and other tissues. Greater
participation in brain and tissue banking is needed from
members of the autism community in order to obtain
enough samples to meet research requests. Outreach
campaigns to encourage families to donate brain and
other tissue need to be expanded and enhanced.
BRAIN BANKING
The NIH NeuroBioBank was formed in 2013 to address
the increasing demand for postmortem human brain tissue
for research purposes.
1
Although this resource
provides tissues for wide-ranging neurological and
neurodevelopmental disorders, there is high demand
for tissue from donors diagnosed with autism spectrum
disorders. The NIH NeuroBioBank supports six
independent brain and tissue repositories; the University
of Maryland site collects and distributes the majority of
ASD tissue. The collection has been highly sampled over
the years and continues to grow through outreach
activities and collaborations with other organizations.
A more autism-focused effort was undertaken in 2015 by
the Autism BrainNet, supported by the Simons Foundation.
Autism BrainNet is focused exclusively on creating a
collection of ASD and control brains. The program supports
four nodes throughout the United States (New York,
Massachusetts, Texas, and California) and one in the United
Kingdom that share standardized protocols for tissue
harvesting, storage, and tissue dissemination. Autism
BrainNet has a robust public awareness campaign to
encourage donation, led by the Autism Science Foundation,
fulfilling one of the longstanding goals of the IACC Strategic
Plan. The NIH NeuroBioBank and Autism BrainNet work
closely together to ensure that tissue acquisition, processing,
and distribution from both resources are conducted with
the highest standards possible.
TISSUE BANKING
The NIMH Repository and Genomics Resource (NRGR)
provides a centralized national biorepository that plays
a key role in facilitating ASD research. The repository
contains thousands of biospecimens from ASD families,
and accompanying genotypic and phenotypic data are
available to qualified researchers worldwide. Biomaterials
are stored at the Rutgers University Cell and DNA Repository,
supported through a cooperative agreement from the
National Institute of Mental Health (NIMH). Clinical projects
funded by NIMH that propose to collect biospecimens
are strongly encouraged to submit the samples to NRGR.
Submissions typically consist of whole blood draws along
with the necessary phenotypic data relevant to these
samples. The NRGR also accepts plasma, DNA/RNA/
cDNA, biopsied material, and human-derived cell
lines such as induced pluripotent stem cells (iPSCs)
and lymphoblastoid cell lines (LCLs). Other types of
biospecimens (e.g., saliva) may be accepted on a case-
by-case basis. There are currently 18,822 ASD samples
across all diagnoses of ASD in the NRGR Autism
distribution. Another 12,606 have been received and
will be released in future distributions.
89
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
DATA INFRASTRUCTURE
Data infrastructure refers to data collection, storage, sharing,
and consumption to support autism research, services,
and policy development. Autism is a highly heterogeneous
disorder requiring large sample sizes to make significant
findings. Thus far, tens of thousands of research subjects
have consented to make their genomics, imaging, and clinical
research data available to scientists in the hope that those
data will help lead to important research discoveries.
These datasets have become very large (i.e., millions of
gigabytes) and will likely grow exponentially in the coming
years with the rapid advances in technology (e.g., raw
imaging, whole genome sequencing), new methods of data
acquisition (bio-tracking), and the integration of patient-
directed reporting applications (e.g., IAN and SPARK).
Other research communities have established related data
repositories and funded data sharing initiatives making
those datasets broadly available for use by the autism
research community. Given the size of these data and the
complexity of the software, algorithms, and analytic methods
used, it is essential that all the data and associated
metadata be shared when a result is published or a
significant finding is announced. Ensuring that all data is
shared will increase the rigor and reproducibility of findings,
a core responsibility of publicly funded research.
DATA BANKS
New findings, technologies, and research methods have
emerged that can drive autism research forward, capitalizing
on advances in participant engagement through electronic
portals and the collection of large data sets. Together,
these participant-powered and clinical data networks can
be further leveraged for rapid research on large numbers
of participants throughout the country, offering the potential
for a broad and rich view of the health and well-being of
those with ASD and their families.
The National Database for Autism Research (NDAR) was
implemented in 2008 to harmonize research data and share
results for all human subject research studies, by supporting
a de-identified research subject identifier – the NDAR
Global Unique Identifier (GUID), and a precise method
for associating research data with publications/results.
2
NDAR also supports common data definitions, a
standardized set of data collection measures ensuring
that results across studies can be accurately combined or
compared. Initially implemented to support data sharing
for the NIH Autism Centers of Excellence, NDAR was
expanded to support data sharing of any autism research
data funded by NIH extramural programs beginning in
2010. In 2013, NDAR was rebranded as the NIMH Data
Archive (NDA) and now supports data sharing of all human
subject research data related to mental health. Today,
research data from over 600 research projects, representing
a public research investment of over $1.4 billion, are being
shared. Overcoming limitations on restricted use datasets
or the sharing of human subject research data across
international borders, the NDA allows for the availability
of research data funded by Autism Speaks, the Simons
Foundation, and the Autism Science Foundation. Investment
is still needed to extend this infrastructure to support
big data analytics better and to integrate with biobanks
and genomics data repositories more fully.
Another mechanism for data sharing is the Autism
Sequencing Consortium (ASC), an international group of
scientists who share autism samples and genetic data.
3
Currently, ASC has whole exome sequencing (WES)
data for 29,000 samples, many of which are derived from
DNA samples in the NIMH repository. Summary data is
available for all samples, as is raw and called data for
90
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
samples with appropriate consents. Permission to
re-contact research participants from completed studies
exists for many of the samples within the ASC, managed
by the contributing site.
In 2016, the Simons Foundation launched SPARK (Simons
Foundation Powering Autism Research for Knowledge) to
recruit, engage and retain a cohort of 50,000 individuals
with ASD, as well as their family members, to participate
in autism research. To participate in SPARK, families enroll
online, provide saliva samples for genetic analysis, and
agree to be re-contacted for future research opportunities.
SPARK participants are being sequenced and genotyped
to identify new genes associated with autism risk. Clinical,
behavioral, and genetic data on the SPARK cohort are
available to all qualified investigators, and SPARK participants
can be invited to participate in other ASD research studies.
Thus far, SPARK has enrolled over 48,000 individuals,
including 19,000 individuals with ASD.
In 2016, the Autism Science Foundation launched the
Autism Sisters Project to collect and distribute DNA from
the unaffected female siblings of individuals with autism.
Current research suggests that genes implicated in autism
are equally distributed in boys and girls, but that many girls
who carry the autism genes do not express clinical
symptoms of autism due to a “female protective effect.
The goal of this new project is to collect DNA samples
to enable researchers to discover and characterize
this “female protective effect.
4,5
DATA SHARING
When all research projects share their data, the quality
of the accumulated data increases. For example, when a
new research participant is enrolled in a research study,
that person may also have registered previously with one
or more data or biorepositories. If the data are linked
and widely accessible to researchers (with appropriate
privacy protections in place), the potential richness of
the information available on that participant is thereby
enhanced. Care should be taken to ensure that all
stakeholders across the research enterprise understand
the importance of data sharing and that those sharing
the most used and highest quality datasets be credited for
their contributions. To facilitate data sharing in research
involving human participants, an identifier or code is used
to identify and link each individual to his or her specimens
and perhaps also to associated medical information;
use of a de-identified code (i.e., a code that does not reveal
the identity of the individual) maintains privacy of the
individual’s information. The GUID was developed to
provide an easy method of identifying the same research
participant across various data repositories and biobanks
while maintaining the privacy of their personal information.
The advantage of the GUID is that it enables linkage of data
and specimens for a given individual over multiple studies,
which can enrich the data set and prevent unnecessarily
repeating the collection of the same types of samples from
a given individual for multiple studies. While most data
repositories have standardized identification of research
participants using the GUID, adoption of this method
has been less consistent across biobank repositories.
Compounding this problem is the fact that most of the
biobanks hold samples that are consented for restricted use
(e.g., a study of autism and schizophrenia would require
separate access) and are shared in separate repositories
with different access restrictions and policies. The result is
that it is often easier to request a tissue or sample from
a biobank, re-sequence or re-analyze it, and then share the
data with a new and different identifier, causing unnecessary
(and often undetectable) duplication. For genomics, tools
have been developed to eliminate this duplication, and
attempts have been made to provide similar safeguards
for imaging data. Though these additional tools exist, it is
strongly encouraged that all data and biobank repositories
maintain the use of the GUID and that those publishing
genomics- or biobank-related studies provide a publicly
available manifest of subject GUIDs and links to phenotypic
91
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
data locations when publishing, even if the data are only
available as restricted use datasets. This action will provide
standardization allowing data from the same individual
to be linked across repositories, eliminate data duplication,
and help minimize redundant sample and tissue requests,
thereby conserving precious resources.
Supporting the increasing emphasis on the importance
of data sharing, NIH has established a two-tiered
approach for the sharing of NDA research data involving
human subjects. First, observational and raw data is
to be defined and shared using established data standards
(data dictionary and a GUID). All data related to research
results are expected to be submitted prior to publication.
Data supporting other aims remain embargoed until
publication, protecting ongoing research. This approach
directly follows the long-established research process of
sharing results and data at the time of publication. Where
data collected by other researchers are used, this system
automatically provides a mechanism showing data
provenance and providing credit. All repositories supporting
autism research should implement a similar program, even
if the datasets shared are summary datasets, are not easily
harmonized with established data repositories, or have
restricted use limitations. As a community, by responsibly
sharing high quality data at the appropriate times, it will
increase the return on the collective research investment,
protect the intellectual contribution of the best scientists,
and help accelerate research discovery in autism and
related disorders. Collectively, open data sharing offers
the best opportunity to reach the sample sizes that
are likely needed to improve understanding of autism
and related disorders.
Several national surveys and administrative efforts collect
information about people with ASD. Many of these surveys
are Federally funded through agencies such as CDC
[National Health Interview Survey (NHIS)], the Health
Resources and Services Administration (HRSA)
[National Survey of Children's Health (NSCH)], and the
Department of Education [National Longitudinal Transition
Study 2012 (NLTS 2012)]. Although each responsible
agency may focus on its own research priorities when
collecting and analyzing the data, synchronization of
the national data sources will maximize their utility.
Concordance of questions and sampling across surveys
and administrative data could add greatly to the
comparability of research undertaken across these national
platforms. Additionally, infrastructure for linking these
surveys to other sources of data is essential. The precedent
for linkage already exists: for example, the CDC links the
NHIS to administrative records from the Department of
Housing and Urban Development (HUD), which allows
for the addition of detailed housing information for those
NHIS participants who use HUD services. Additionally,
Federal Statistical Research Data Centers make national
data from the Census bureau, CDC, and the Agency for
Healthcare Research and Quality (AHRQ) available
to researchers in one place. More projects like these, and
additional means of capitalizing on the data that has already
been collected and funded, are a key priority in order to
generate an expansion of the information available on
autism to a nationally representative sample.
92
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
HUMAN INFRASTRUCTURE
Human infrastructure refers to the development of
human resources necessary to support autism research.
These include developing a professional workforce to conduct
research and provide services, as well as encouraging
individuals with autism and their family members to
participate in autism research. In addition, systems must
be developed to share research findings with community
stakeholders and translate research findings into policy
and practice.
Individuals with autism and their families participate in
research studies at relatively low rates, hampering the
ability of researchers to fully understand ASD and
develop interventions. Coordinated efforts are needed to
educate stakeholders from diverse backgrounds on the
importance of participating in research. Research should
also be conducted to understand the barriers that discourage
participation. Efforts should also be made to encourage
families from diverse backgrounds to donate biological
samples for research.
RESEARCH TRAINING AND WORKFORCE
DEVELOPMENT EFFORTS
There are a number of efforts underway to enhance research
training and workforce development. Private funding
agencies such as Autism Speaks and the Autism Science
Foundation support research fellowships that focus on
attracting and nurturing early career investigators as
they pursue innovative ASD research projects and begin
their careers. Great emphasis is placed on building
relationships with experienced mentors and on encouraging
multidisciplinary avenues of exploration. NIH also offers
research training opportunities including, but not limited to,
training and career development grants and travel awards for
early career investigators to attend research conferences.
While these initiatives represent mechanisms for the
general support of trainees and early career ASD
investigators, an area of need and opportunity identified by
the IACC is for these up-and-coming researchers to have
better access to existing datasets for conducting secondary
data analysis. Hundreds of millions of Federal and private
donor dollars have been spent on ASD research, which
has led to the collection or federation of data on tens of
thousands of ASD cases. A modest investment aimed at
improving access to these data would not only maximize
the return on substantial financial and human capital
investments represented by decades of ASD research,
but would also provide a fast-tracked training mechanism
ideally suited to early career investigators, who often
lack the resources to collect primary data.
Workforce development is an area of immense need as
the number of identified individuals with autism continues
to grow. While progress has been made in the area of early
detection and intervention, and in the support of children
on the spectrum, much less effort has been expended on
adult services, as tens of thousands of children with autism
transition to adulthood. Further, there is a dearth of
trained medical professionals that are knowledgeable in
providing care to the autism community, particularly the
adult community. The Autism Collaboration, Accountability,
Research, Education, and Support Act, IDEA Part C, and Title V
Maternal and Child Health Block Grants all provide some
amount of Federal funding intended to target workforce
training and development programs. However, resources
remain scarce, and it is not immediately clear how some
of those resources are being utilized, particularly regarding
whether there is any standardization in the delivery of
workforce development efforts across communities.
In some cases, it is unclear what training programs are
93
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
being implemented, if they are evidence-based, and how
they are evaluated. There seems to be an immediate need for
evidence-based best-practice guidelines in the development
and implementation of such training programs.
INTERNATIONAL COLLABORATION
A 2012 IACC report titled Autism Spectrum Disorder
Research Publication Analysis: The Global Landscape of
Autism Research highlighted the expanding web of ASD
research collaboration and publications across the globe;
researchers from over 50 countries published papers
during the analysis period. While there has been
an increase in ASD research conducted and published
outside of the US and other developed countries, the
report also called attention to the fact that while research
efforts are robust in the US, Canada, Europe, Australia,
and China, many other countries around the world are
lacking in capacity to conduct research or provide
opportunities to participate in research. More attention
and investment toward fostering international research
collaborations have the potential to change this situation
and provide benefits for people with autism and other
developmental disabilities worldwide. Diverse settings can
afford unique research opportunities to investigate risk
factors (e.g., air pollution) and populations (e.g., higher
genetic homogeneity) that may not be present in countries
from which most of ASD research is currently published.
Further, international research collaborations not only
present opportunities to disseminate and implement
evidence-based science and services in diverse settings
around the world, but also allow the ASD research
community to learn about how diverse populations,
including those from low-resource settings, have addressed
issues such as limited research infrastructure and large
service gaps. For these reasons, it is imperative that
international research efforts and collaborations continue
to be promoted and supported.
DISSEMINATION OF SCIENCE
Increasing and improving mechanisms for dissemination
of research findings after publication should be a priority
for the autism community. It is vital that findings and
data become more accessible to researchers, practitioners,
families, and the general public. Training to improve
science communication skills should be more readily
available to researchers who wish to share their work
with lay audiences. Particularly important is risk
communication in the interpretation of research findings,
as the information disseminated to the public is sometimes
contradictory, oversimplified, overstated, or sensationalized.
This misinformation can confuse the risk, disenfranchising
members of the public, and have a negative impact
on research participation. Mechanisms that allow for
the summation of the evidence base into actionable
recommendations such as systematic reviews and
meta-analysis are encouraged, though research funders
often overlook the potential for these types of analyses
because they are based on existing rather than new
data. Much of this work will be more feasible as the
data sharing infrastructure further develops and expands.
NDAR provides an infrastructure to make data broadly
accessible through a universal platform and federation
with other data sources. To make NDAR the most useful
resource possible for the community, autism researchers
must improve both the consistency and quality of data
shared, especially those data supporting published
results, allowing the infrastructure to be better utilized
and supporting the dissemination of scientific advances.
NDAR and similar data sharing efforts can help maximize
the return on Federal and private investment in autism
research made over the last decade by providing the
research community with richer datasets and opportunities
for research that would not have been possible without
the coordination of these data.
Technology can play a key role in improving the
dissemination of science, and advances in technology
have made it increasingly possible to handle the troves
94
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
of “big data” that have been collected in ASD research.
In addition to combining, storing, and analyzing data,
technology affords new avenues of information collection
and dissemination, for example, in the form of mobile
applications (apps). Researchers can better collect data
and do so more consistently across research studies by
utilizing technology-based research platforms. Similarly,
practitioners can better collect clinical data using the same
or similar platforms. Making this technology more accessible
and promoting the development of new technology for
data collection and sharing should be prioritized by
the research community to help optimize autism research
studies. Further, technology to promote dissemination
and implementation of intervention and support services,
via telehealth or e-learning, is critically important to
improving the capacity to deliver the latest in evidence-based
services throughout the US and around the world. Lastly,
with growing awareness of ASD around the world and an
increase in the number of local organizations supporting
people with ASD in their communities, it is an opportune
time to begin building stronger international collaborative
efforts around ASD. Such initiatives have the potential
to enhance communication and cooperation between
governments, researchers, service providers, and advocates
and to aid in dissemination of research findings and best
practices globally.
SURVEILLANCE
Population-based surveillance for autism spectrum
disorder is essential for monitoring time trends in prevalence,
assessing patterns by demographic factors and level of
support necessary, characterizing co-occurring conditions,
estimating resource needs, and stimulating research into
potential risk factors. For the data provided to be used
effectively, surveillance should be as complete and valid as
possible. Population-based studies of the prevalence and
characteristics of autism spectrum disorder in the United
States have been conducted among children, but continued
collection is necessary to monitor trends. In addition, there
is a pressing need for surveillance studies among adults.
There are several different methodologies currently used
for estimating the prevalence and characteristics of autism
spectrum disorder among children, including: 1) use of
administrative records; 2) parent or caregiver surveys;
3) expert review of records from multiple sources; and
4) screening and examination of children. Each of these
methodologies has strengths and limitations. Administrative
records are readily available and cost-effective to use, but
are collected for other purposes and do not always contain
adequate and pertinent information. Health surveys are
nationally representative, generate data relatively quickly,
include extensive questions on service needs and
utilization, include a comprehensive age range of children,
and are cost-effective in terms of the marginal cost
of adding ASD-related questions; however, the validity of
parent/caregiver-reported ASD has not been established,
and declining response rates have raised concerns about
bias. Expert review of records from multiple sources,
including healthcare and education records, can ascertain
records-based data on a number of factors such as
demographics, educational placement, intellectual and
adaptive function, and behavioral phenotype. However, this
methodology is dependent on data in children’s records,
focuses on a few specific ages, and is resource- and
time-intensive and so currently cannot be done at a
national level. Finally, screening and examination of children
using a standardized and validated ASD diagnostic tool is
a rigorous methodology that attempts to give all children
95
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
in the selected population an opportunity for ascertainment.
However, this methodology is also resource- and time-
intensive and cannot currently be done on a national level.
In addition, low response rates in previous studies suggest
a potential for bias.
Continued ASD surveillance among children is essential to
monitor prevalence trends (including disparities in prevalence
by demographic factors), characterize co-occurring
conditions, estimate resource needs, and stimulate research
into potential risk factors. ASD surveillance systems
should be complementary, offering unique strengths and
contributions that will further the understanding of the
population of individuals with ASD. Where appropriate,
data collection should be designed to allow comparisons
across systems. Linkage of surveillance data with other state
and Federal datasets should be encouraged to leverage
the surveillance efforts and expand the scope and utility
of the information collected.
While many research studies are focused on understanding
and meeting the needs of children with ASD, much less
effort has been expended on adults. There is an urgent
need to expand ASD surveillance to adults to characterize
prevalence, adolescent/young adult transition needs,
employment and housing, co-occurring conditions,
premature mortality, and other lifespan issues. In particular,
investigating ASD prevalence in adults will help researchers
understand how the interaction of ASD and co-occurring
conditions impacts the ability to adults with ASD to live
and work.
A systematic community survey in the United Kingdom
estimated that approximately 1% of adults surveyed met
the criteria for ASD, a rate similar to that in children.
6,7
None of the adults with ASD identified in this study had
been previously screened or diagnosed, further confirming
the need for ASD surveillance in adults. The researchers
involved in the study noted several challenges to their
methodology, including low response rates to the survey
and the potential high cost of initial screening. Nevertheless,
a comprehensive adult surveillance in the United States
would be desirable, subject to available funding.
CURRENT SURVEILLANCE PROGRAMS
Autism and Developmental Disabilities
Monitoring Network
The Autism and Developmental Disabilities Monitoring
(ADDM) Network is a population-based surveillance
program for ASD and other developmental disabilities based
on expert review of behavioral characteristics documented
in developmental evaluations contained in children’s
healthcare and educational records. CDC has been
conducting surveillance for ASD among 8-year-old children
through the ADDM Network every 2 years since 2000
at between six and 14 sites throughout the United States.
Recent surveillance cohorts have included approximately
350,000 8-year-old children. In 2010, the ADDM Network
was expanded to include surveillance for ASD among
4-year-old children in six sites of the ADDM Network. Data
have been linked to various sources such as environmental
pollutant monitoring, juvenile justice records, and others.
Additional linkages to data from state and Federal agencies
would enhance the usefulness of the ADDM Network
data. The ADDM Network methodology has remained
stable over time and so is able to assess prevalence trends.
The most recent prevalence estimate for 2012 was 14.6
per 1,000 8-year-old children.
8
The ADDM Network
methodology also allows for assessment of the effect of
changes in diagnostic criteria for ASD, and an evaluation
of the effect on ASD prevalence and characteristics of
the change from DSM-IV-TR to DSM-5 is underway.
National Survey of Children’s Health
The National Survey of Children’s Health (NSCH) is cur-
rently administered by the Maternal and Child Bureau of
HRSA. This nationally representative telephone survey
96
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
of children’s health and development based on parent/
caregiver report includes questions on whether the child
currently had an ASD as well as whether a healthcare
provider ever informed the parent or caregiver that the
child had an ASD. Data are also collected on a variety of
topics including the child’s health, health as an infant,
recent healthcare service, experiences with healthcare
providers, health insurance coverage, sociodemographic
factors, and the child’s learning, home, and family
environment. The most recently published report
presented data for over 90,000 children aged 6-17 years;
ASD prevalence was 2.00% for children aged 6-17 years
in 2011/2012. Beginning in 2016, this survey was moved
to a mail-invitation, online survey based on a US Census
Bureau sampling platform. This survey has been combined
with the previously fielded National Survey of Children
with Special Healthcare Needs. The new combined survey
will be conducted every year and include approximately
100,000 children aged 0-17 years. It is anticipated that
state-level estimates will be available for many variables,
and for other variables data will be combined from several
study years to provide state-level estimates. Linkages to
data from other Federal agencies should be encouraged to
expand the scope and usefulness of the data collected.
National Health Interview Study
CDC conducts the National Health Interview Survey
(NHIS), a nationally representative survey of parents/care-
givers that provides data on the health of children in
the United States, including information on whether a
healthcare provider ever informed the parent or caregiver
that the child had an ASD. The US Census Bureau is the
data collection agent and the data are collected through
personal household interviews. Data are collected on
children aged 0-17 years every year; the most recently
published survey year, 2014, presented data on ASD
prevalence and characteristics for approximately 13,000
children aged 3-17 years. Data are also gathered on a
variety of topics including the child’s health status, healthcare
access and utilization, and a mental health screener
(the Strengths and Difficulties Questionnaire), as well as
family factors, including sociodemographic factors. ASD
prevalence was 2.24% for children aged 3-17 years in
2014. The questions that establish a child’s ASD status
were recently revised to be the same as those in the
NSCH. As with NSCH, linkages to data from other Federal
agencies should be encouraged to expand the scope and
usefulness of the data.
South Carolina SUCCESS
The South Carolina Children’s Educational Surveillance
Study (SUCCESS) is an Autism Speaks-funded
screening-based initiative designed to help improve the
precision of US ASD prevalence estimates by reducing
reliance on service records alone to make ASD diagnoses,
addressing the chief limitation of the ADDM Network
approach. It has been suggested that this methodological
approach is subject to missed cases, particularly among
populations with less access to services, and in sites with
fewer record types. SUCCESS was designed as a replication
of the first-ever total population study of ASD prevalence
in South Korea which found 2.64% of 7-9 year-old children,
or 1 in 38, had an ASD.
9
SUCCESS similarly implements
a direct-screening protocol of all eligible school children
in the catchment area, to both augment and compare
to the records-based case ascertainment methodology
of the South Carolina ADDM Network site. In addition to
improving the estimation of the prevalence of ASD within
a US site, SUCCESS intends to characterize the factors
contributing to why cases may be missed using current best
surveillance practices. It is also the first study to compare
DSM-IV and DSM-5 prevalence using a population-based
methodology in the US. The findings, currently in
preparation, will better guide ASD surveillance practices
in the US, including resource and infrastructure needs,
moving forward.
97
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
SUMMARY
Continuing to build the infrastructure necessary for autism
research is an important priority. In particular, researchers
must make efforts to standardize their data collection and
share with others in order to build higher-powered studies
across multiple areas of research. Research institutions
must continue to support biobanks and databanks, and
to work towards integrating common collection and
processing methods. Efforts to increase the participation
of individuals with autism and their families in research
and contributions to biorepositories are important, as
information and samples gathered have the potential to
make significant contributions to our understanding of
ASD. Inclusion of people on the autism spectrum and their
families in research planning is also important, as it will help
ensure that studies maintain a focus on issues that matter
most to those who are impacted by ASD. Finally, funding
agencies should continue to devote resources to ensuring
dissemination of research findings and best practices,
gaining better understanding of ASD prevalence across
the lifespan, and training the next generation autism
researchers, clinicians, and care providers.
98
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVES
OBJECTIVE 1: Promote growth, integration, and coordination of biorepository infrastructure.
Examples:
Promote biological sample donation to ensure that demand for research studies is met.
Develop and expand programs and outreach campaigns to encourage families from diverse backgrounds to participate
in ASD research, join registries, and donate biological samples.
Create incentives to encourage standardization and sample sharing across data and biorepository banks.
OBJECTIVE 2: Develop, enhance, and link data repositories.
Examples:
Adopt a de-identified research participant/subject identifier, such as the GUID, across all research initiatives in order
to reduce the likelihood of sample duplication.
Use common data definitions in order to standardize data collection, and responsibly share all the data supporting
any findings when those findings are announced.
OBJECTIVE 3: Expand and enhance the research and services workforce, and accelerate the
pipeline from research to practice.
Examples:
Expand and enhance programs that provide funds to train current and future researchers on innovative research techniques.
Provide service providers with training in evidence-based ASD services across multiple settings from clinics to communities.
Develop programs to translate and disseminate ASD research findings into actionable recommendations and
real-world practice.
99
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OBJECTIVE 4: Strengthen ASD surveillance systems to further understanding of the population of
individuals with ASD, while allowing comparisons and linkages across systems as much as possible.
Examples:
Expand surveillance efforts to include the adult population in order to gain a better understanding of needs and
concerns over the lifespan.
Expand surveillance efforts to collect more descriptive data regarding co-occurring conditions, including cognitive
disability, seizure disorders, anxiety, and depression to increase understanding of the prevalence of these conditions
in the ASD population.
100
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
BUDGET RECOMMENDATION
In the preceding chapters, the Interagency Autism Coordinating Committee (IACC) has provided information about recent
research progress and services activities as well as 23 new strategic objectives to guide future efforts to better understand and
address the needs of people on the autism spectrum across the lifespan and all levels of ability and disability. Under the
Autism CARES Act, the IACC is also required to include “proposed budgetary requirements” in the Strategic Plan. The following
information provides supporting background information and the IACC budget recommendation for the 2016-2017 Strategic
Plan for Autism Spectrum Disorder (ASD).
ASD is a lifelong condition, and as such, it results in significant human costs across the lifespan, not only in healthcare
and services costs, but also in lost economic productivity, and reduced individual quality of life. These true costs reflecting
lost human potential have recently begun to be described by thorough analyses. One of the most notable studies to date
has estimated that the total lifetime cost (including spending and lost productivity) for supporting a person with ASD
in the United States averages $2.4 million for ASD with intellectual disability, and $1.4 million for ASD without intellectual
disability.
1
Another study estimated that the additional costs of healthcare, education, therapy, services, and caregiver
time associated with caring for a child with ASD aged 3 to 17 years is about $17,000 per year.
2
The total annual cost of ASD in the United States – including medical, non-medical, economic, and lifetime costs, among
others – has been estimated to be at least $236 billion. Of the estimated $236 billion, the cost of supporting children with
ASD was at least $61 billion per year, and the annual cost for adults with ASD was at least $175 billion.
1
Another study has
suggested that in 2015 the combined medical, non-medical, and lost productivity costs were in the range of $162-$367
billion, or 0.89-2.0% of the US gross domestic product.
3
By contrast, the Interagency Autism Coordinating Committee
(IACC) portfolio analysis data from 2015 indicates that combined autism research funding among Federal and private
sources totaled $343 million – only 0.09-0.21% of the estimated total annual cost of ASD.
While it is evident that more work needs to be done to fully understand the impacts of ASD on our society, there are
several ways in which investment in research may be able to effect long-term benefits to individuals and society, as well
as cost savings. Research on the biological basis of ASD may lead to the identification of modifiable risk factors that could
reduce disability associated with ASD, as well as enable earlier diagnosis and improved interventions. There is already
evidence that the costs of research and services that enable delivery of effective early intensive behavioral interventions
in childhood can result in cost savings over the lifespan by reducing the need for costly long-term care and support.
4,5
A recent study found that the health-related costs of the Early Start Denver Model were fully recouped after only a few
years because children receiving the intervention required fewer other services, such as applied behavior analysis.
6
In addition, we know that an estimated four out of ten young adults with autism do not transition to a job within the first
years after completing high school, and those who do find work are often relegated to part-time or low-wage jobs.
7
It is
therefore also likely that more investment in research to improve adolescent and adult services and supports would
improve the economic productivity of individuals over their entire lifetime, while also improving their sense of purpose
and quality of life.
8
101
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Although there was significant growth in autism research funding from 2008 to 2010, and additional Federal funding from
the American Recovery and Reinvestment Act (ARRA) provided a welcome boost in 2009 and 2010, ASD research funding
levels have since become relatively flat. The loss in momentum has been accelerated by the loss of purchasing power over
time due to inflation, resulting in what was effectively 15% of funding that was lost to inflation in 2015 alone (Figure 1).
At the same time, never before have there been such promising scientific advances in ASD research, as well as a recognition
of the full range of ASD research that will require attention and resources in order to truly improve the lives of individuals
across the autism spectrum and lifespan. In the 2016-2017 IACC Strategic Plan, the IACC has identified 23 new strategic
objectives that represent areas of significant opportunity in the autism field and with enhanced funding have the potential
to address critical needs of the autism community.
With these goals in mind, the IACC considered historical ASD funding trends and projected the budgets that will be nec-
essary to propel ASD research forward and ensure there is meaningful progress on the priorities identified in this newly
updated IACC Strategic Plan. Given the tremendous needs of the autism community as well as the promising opportunities
for research and services that have been outlined in this Strategic Plan, the IACC recommends doubling the 2015 combined
Federal and private autism research budget level of $343 million to $685 million by the year 2020. To accomplish this goal
with steady and predictable annual funding increases, a roughly 14.85% increase in the autism research budget would
be required each year (Figure 2). It is important to point out that this budget recommendation applies to ASD research
budgets only; an IACC analysis of services budgets will be forthcoming in future years. Furthermore, the research funding
increases recommended by the IACC would not be sufficient to accomplish all of the research goals identified in this Plan.
However, a specific effort to double the autism research budget in 5 years would represent an aggressive, yet realistic
jump-start to support research that can significantly move the field forward.
As evidenced by the analysis of the autism research portfolio from 2008 to 2015, an infusion of resources would be wisely
and efficiently leveraged, with many areas of autism research well-poised to capitalize on additional investment. While all
areas of the autism research portfolio require increases in funding, the areas identified by the IACC that are in particular
need of resource growth include:
1. Research to support development and delivery of new and improved treatments and interventions
2. Research to enable development and delivery of evidence-based services
3. Research on lifespan issues, especially to understand and address the needs of transition-age youth, young adults, and
older adults on the autism spectrum.
In addition, the investment of resources targeting these areas would serve not only to incentivize research on these topics,
but also to encourage additional well-trained scientists to specialize in these research areas of significant need.
102
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Overall ASD Funding – in 2008 constant dollars
Overall ASD Funding – in actual dollars
Overall ASD Funding (without ARRA) – in actual dollars
Overall ASD Funding (without ARRA) – in 2008 constant dollars
THE OVERALL ASD RESEARCH BUDGET HAS PLATEAUED
AND LOST PURCHASING POWER FROM 2008-2015
2008
$222.2M
2009
Millions
2010
$408.6M
2011 2012 2013 2014 2015
$291.9M
$342.6M
$450
$400
$350
$300
$250
$200
Figure 1. The history of combined Federal and private autism research funding from 2008 to 2015 in actual (blue) dollars and
2008 constant (orange) dollars shows that after experiencing an initial increase, the ASD research budget became relatively flat and
lost purchasing power due to inflation in recent years. The dotted lines indicate funding levels excluding American Recovery and
Reinvestment Act (ARRA) stimulus funds, which provided supplementary funding in 2009 and 2010. Inflation effects were calculated
using the Biomedical Research and Development Price Index (BRDPI).
9
103
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
THE IACC RECOMMENDS DOUBLING THE
ASD RESEARCH BUDGET BY 2020
2015
$343
2016
$394
2017
$452
2018
$519
2019
$596
2020
$685
$0
$100
$200
$300
$400
$500
$600
$700
$800
Millions
Figure 2. The IACC believes doubling the combined Federal and private ASD research budget to $685 million would spark progress on
the 23 new Strategic Plan objectives. A steady and predictable path to doubling the 2015 ASD research budget by the year 2020 would
require an overall budget increase of about 14.85% each year.
104
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
STATEMENT ON DUPLICATION OF EFFORT
The Autism CARES Act requires the IACC in its Strategic Plan to provide “Recommendations to ensure that autism spectrum
disorder research, services and support activities, to the extent practicable, of the Department of Health and Human Services and
of other Federal departments and agencies, are not unnecessarily duplicative.
The 2016-2017 IACC Strategic Plan for ASD offers wide-ranging objectives that are designed to address gaps in ASD
research, services, and support activities. The IACC’s intention is that each broad-based objective will be accomplished
through multiple projects addressing various aspects of these complex issues, which will be funded by multiple agencies
in a coordinated fashion. The IACC is charged with ensuring that coordination, which is achieved by fostering dialogue
among Federal agencies and private organizations and engaging their input in the development of plan objectives. The
IACC believes that in the case of scientific research, coordinated efforts by multiple public and private agencies to fund
different types of projects within the same objective represents cooperation and collaboration, not duplication. In addition,
the scientific process requires that studies be independently replicated in order to ensure reproducibility and validate
findings. Replication of an experiment or approaching a single problem using different methods can corroborate findings
and help researchers distinguish between false leads and important discoveries. Replication also contributes to efficiency
in research funding by ensuring the creation of a solid base of validated findings that establish the rationale for later-stage,
larger, and potentially more costly research efforts. For these important reasons, replication of research is valuable and
should not be considered duplication of effort.
In 2013, the US Government Accountability Office (GAO) released a report entitled Federal Autism Activities: Better Data
and More Coordination Needed to Help Avoid the Potential for Unnecessary Duplication (GAO-14-16). The GAO report suggested
that the IACC should more fully take advantage of research project data collected to identify opportunities to enhance
coordination and prevent duplication. The Autism CARES Act provided more specificity in requiring the IACC to make
recommendations about ways in which duplication could be avoided in its Strategic Plan. In the process of preparing this
Strategic Plan, the IACC reviewed funded research projects to monitor the extent to which strategic objectives are being
accomplished, including changes in funding over time. The IACC explicitly asked each of the seven working groups assisting
with preparation of content for the Strategic Plan to identify issues related to duplication and to propose suggestions
for avoiding unnecessary duplication.
The IACC did not find any specific instances of duplication among projects in the 2013 portfolio of funded autism research
projects, but it noted that there are several instances of the opposite of duplication within the portfolio – gaps in research
where too few projects are being supported to answer key questions in the field. Examples include the lifespan area in
Question 6, which has received relatively little funding over the years that the Strategic Plan has been in place, resulting
in gaps in knowledge about the needs of youth and adults on the autism spectrum and research to develop innovative
services and supports.
105
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
The Committee also identified a broader issue that provides an opportunity to reduce duplication - the need for closer
coordination of large genomic sequencing efforts. Several different research organizations are building genetic databases,
and there is concern that different databases may be sequencing the same individuals, which could result in poor stew-
ardship of funds as well as the time and effort of research participants. To reduce duplication of effort in sequencing, the
IACC encourages organizations building databases to publicly share their “manifests” which include information on whose
DNA is in each database, to use global unique identifiers (GUIDs) to tag data in order to help researchers know when they
are working with an individual who already has been sequenced, and to share data by federating with or contributing to
the National Database for Autism Research. As technology advances, there may be instances where resequencing the
same individual is necessary to expand coverage or gather additional data that were not gathered previously. Ideally, in
an environment where data sharing is maximized, researchers will be able to be more efficient with genomics research
funding and participation of subjects in research so as to reduce duplication of effort.
106
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
CONCLUSION
Much progress has been made in the autism field since the launch of the first IACC Strategic Plan in 2009. At that time,
researchers and other professionals in the field were starting to explore and push toward the possibility of earlier diagnosis
and intervention, to understand whether genetics or the environment play a larger role in etiology, to determine why
autism was becoming a more common diagnosis, and to understand what were the major challenges of autism in adulthood.
Since then, through research and service work in the community, we have learned that: children at risk for ASD can be
identified as early as the first year; early intervention does lead to improved outcomes for many children; myriad genetic
and environmental factors interact closely resulting in the observed heterogeneity of ASD; multiple factors may be
influencing prevalence estimates and more children with milder forms of ASD are being detected; and there are tremendous
unmet service needs for adults on the autism spectrum. While research and services activities have moved the field forward
in many ways, as represented in the aforementioned examples, they have also brought to light many challenges that
still need to be addressed.
Before developing the 2016-2017 IACC Strategic Plan for ASD, the IACC reviewed research progress and analyses of recent
data describing the portfolio of ASD research funding in order to assess trends in funding and determine potential areas
of opportunity. Overall funding for the autism research portfolio increased, from $222 million in 2008 to $343 million
in 2015. Over the years the Committee has monitored the research portfolio, it has not identified any concerns about
unnecessary duplication of effort across the portfolio, but it has monitored gaps and used this information to inform the
development of the 2016-2017 IACC Strategic Plan.
Strategic investments in the autism portfolio have produced promising scientific advances over recent years. For example,
since the last Strategic Plan Update in 2013, research findings have provided several new insights, such as a better picture
of existing autism services and service needs, improved identification of genetic risk factors for ASD, and a more accurate
representation of the broader ASD community – including girls and women, individuals with intellectual and language
disabilities, adolescents, and aging adults. This new knowledge has further illuminated several areas ripe for future efforts
and investments – investments that have the potential to improve quality of life while also producing long-term cost savings
for individuals, families, and society. The 23 new objectives in this Strategic Plan describe priorities for autism research,
services, and supports that reflect the most important opportunities and needs in the current autism landscape. Included
in these objectives are a focus on detecting autism earlier and improving access to early intervention; advancing under-
standing of the biology of autism and co-occurring conditions across the lifespan; integrating genetic and environmental
information to understand autism risk; developing a wide array of new treatments and interventions that will address
needs across the spectrum and across the lifespan; implementing interventions in community settings and improving
access to services; improving transition services and quality of life for adolescents and adults; and enabling data sharing
and expanded surveillance.
107
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
The IACC continues to coordinate autism research efforts and reaffirms its commitment to our core values: responding with
urgency to the needs and challenges presented by ASD, pursuing excellence in research, building a spirit of collaboration,
remaining focused on the needs of the community, developing strategic partnerships, and striving for equity. As the
IACC looks to the future and considers the outlook for its strategic goals, the Committee believes the autism field is poised
to experience significant progress toward addressing the critical needs of the autism community in the coming years.
108
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
REFERENCES
QUESTION 1: HOW CAN I RECOGNIZE THE SIGNS OF ASD, AND WHY IS EARLY DETECTION SO IMPORTANT?
1. Christensen DL, Baio J, Van Naarden Braun K, Bilder
D, Charles J, Constantino JN, Daniels J, Durkin MS,
Fitzgerald RT, Kurzius-Spencer M, Lee LC, Pettygrove
S, Robinson C, Schulz E, Wells C, Wingate MS,
Zahorodny W. Prevalence and Characteristics of
Autism Spectrum Disorder Among Children Aged
8 Years–Autism and Developmental Disabilities
Monitoring Network, 11 Sites, United States, 2012.
MMWR Surveill Summ. 2016 Apr 1;65(3):1-23.
[PMID: 27031587]
2. Huttenlocher PR. Synaptic density in human
frontal cortex - developmental changes and effects
of aging. Brain Res. 1979 Mar 16;163(2):195-205.
[PMID: 427544]
3. Wetherby AM, Guthrie W, Woods J, Schatschneider
C, Holland RD, Morgan L, Lord, C. Parent-
implemented social intervention for toddlers with
autism: an RCT. Pediatrics. 2014 Dec;134(6):1084-
1093. [PMID: 25367544]
4. Dawson G, Rogers S, Munson J, Smith M, Winter
J, Greenson J, Donaldson A, Varley J. Randomized,
controlled trial of an intervention for toddlers with
autism: the Early Start Denver Model. Pediatrics.
2010 Jan;125(1):e17-23. [PMID: 19948568]
5. Brian JA, Smith IM, Zwaigenbaum L, Roberts W,
Bryson SE. The Social ABCs caregiver-mediated
intervention for toddlers with autism spectrum
disorder: Feasibility, acceptability, and evidence
of promise from a multisite study. Autism Res.
2016 Aug;9(8):899-912. [PMID: 26688077]
6. Zwaigenbaum L, Bauman ML, Fein D, Pierce K, Buie
T, Davis PA, Newschaffer C, Robins DL, Wetherby A,
Choueiri R, Kasari C, Stone WL, Yirmiya N, Estes A,
Hansen RL, McPartland JC, Natowicz MR, Carter A,
Granpeesheh D, Mailloux Z, Smith Roley S, Wagner S.
Early Screening of Autism Spectrum Disorder:
Recommendations for Practice and Research. Pediatrics.
2015 Oct;136 Suppl 1:S41-59. [PMID: 26430169]
7. Arunyanart W, Fenick A, Ukritchon S, Imjaijtt W,
Northrup V, Weitzman C. Developmental and Autism
Screening: A Survey Across Six States. Infants and
Young Children. 2012;25(3):175-187.
8. Miller JS, Gabrielsen T, Villalobos M, Alleman R,
Wahmhoff N, Carbone PS, Segura, B. The each child
study: systematic screening for autism spectrum
disorders in a pediatric setting. Pediatrics. 2011
May;127(5):866-871. [PMID: 21482605]
9. Hassink SG. AAP Statement on U.S. Preventive Services
Task Force Draft Recommendation Statement on
Autism Screening. American Academy of Pediatrics.
2015 Aug. Retrieved from: https://www.aap.org/
en-us/about-the-aap/aap-press-room/pages/AAP-
Statement-on-U-S-Preventive-Services-Task-Force-
Draft-Recommendation-Statement-on-Autism-
Screening.aspx
10. Siu AL, Bibbins-Domingo K, Grossman DC, Baumann
LC, Davidson KW, Ebell M, García FA, Gillman M,
Herzstein J, Kemper AR, Krist AH, Kurth AE, Owens
DK, Phillips WR, Phipps MG, Pignone MP. Screening
for Autism Spectrum Disorder in Young Children:
109
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
US Preventive Services Task Force Recommendation
Statement. JAMA. 2016 Feb 16;315(7):691-696.
[PMID: 26881372]
11. Fenikilé TS, Ellerbeck K, Filippi MK, Daley CM.
Barriers to autism screening in family medicine practice:
a qualitative study. Prim Health Care Res Dev. 2015
Jul;16(4):356-366. [PMID: 25367194]
12. Elder JH, Brasher S, Alexander B. Identifying the
Barriers to Early Diagnosis and Treatment in
Underserved Individuals with Autism Spectrum
Disorders (ASD) and Their Families: A Qualitative
Study. Issues Ment Health Nurs. 2016 Jun;37(6):
412-420. [PMID: 27070190]
13. Dosreis S, Weiner CL, Johnson L, Newschaffer CJ.
Autism spectrum disorder screening and management
practices among general pediatric providers. J Dev
Behav Pediatr. 2006 Apr;27(2 Suppl):S88-94.
[PMID: 16685190]
14. Carbone PS, Norlin C, Young PC. Improving
Early Identification and Ongoing Care of Children
With Autism Spectrum Disorder. Pediatrics. 2016
Jun;137(6). [PMID: 27244841]
15. Van Cleave J, Morales DR, Perrin JM. Pediatric
response to court-mandated Medicaid behavioral
screening in Massachusetts. J Dev Behav Pediatr.
2013 Jun;34(5):335-343. [PMID: 23751887]
16. Robins DL, Casagrande K, Barton M, Chen CM,
Dumont-Mathieu T, Fein D. Validation of the
modified checklist for Autism in toddlers, revised
with follow-up (M-CHAT-R/F). Pediatrics. 2014
Jan;133(1):37-45. [PMID: 24366990]
17. Campbell K, Carpenter KL, Espinosa S, Hashemi J,
Qiu Q, Tepper M, Calderbank R, Sapiro G, Egger HL,
Baker JP, Dawson G. Use of a Digital Modified Checklist
for Autism in Toddlers - Revised with Follow-up to
Improve Quality of Screening for Autism. J Pediatr.
2017 Apr;183:133-139.e1. [PMID: 28161199]
18. Gabrielsen TP, Farley M, Speer L, Villalobos M, Baker
CN, Miller J. Identifying autism in a brief observation.
Pediatrics. 2015 Feb;135(2):e330-8. [PMID: 25583913]
19. Stenberg N, Bresnahan M, Gunnes N, Hirtz D,
Hornig M, Lie KK, Lipkin WI, Lord C, Magnus P,
Reichborn-Kjennerud T, Schjølberg S, Surén P, Susser E,
Svendsen BK, von Tetzchner S, Oyen AS, Stoltenberg
C. Identifying children with autism spectrum
disorder at 18 months in a general population sample.
Paediatr Perinat Epidemiol. 2014 May;28(3):255-262.
[PMID: 24547686]
20. Nygren G, Cederlund M, Sandberg E, Gillstedt F,
Arvidsson T, Gillberg IC, Andersson GW, Gillberg
C. The prevalence of autism spectrum disorders in
toddlers: a population study of 2-year-old Swedish
children. J Autism Dev Disord. 2012 Jul;42(7):1491-7.
[PMID: 22048962]
21. Wetherby A, Prizant B. Communication and Symbolic
Behavior Scales Developmental Profile (CSBS DP),
First Normed Edition. Paul H Brookes Publishing; 2002.
22. Guthrie W, Swineford LB, Nottke C, Wetherby AM.
Early diagnosis of autism spectrum disorder:
stability and change in clinical diagnosis and
symptom presentation. J Child Psychol Psychiatry.
2013 May;54(5):582-590. [PMID: 23078094]
23. Dow D, Guthrie W, Stronach ST, Wetherby AM.
Psychometric analysis of the Systematic Observation
of Red Flags for autism spectrum disorder in toddlers.
Autism. 2017 Apr;21(3):301-309. [PMID: 27132013]
110
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
24. Ozonoff S, Young GS, Landa RJ, Brian J, Bryson S,
Charman T, Chawarska K, Macari SL, Messinger D,
Stone WL, Zwaigenbaum L, Iosif AM. Diagnostic
stability in young children at risk for autism spectrum
disorder: a baby siblings research consortium study.
J Child Psychol Psychiatry. 2015 Sep;56(9):988-998.
[PMID: 25921776]
25. Stronach ST, Wetherby AM. Observed and
Parent-Report Measures of Social Communication
in Toddlers with and without Autism Spectrum Disorder
across Race/Ethnicity. Am J Speech Lang Pathol.
2017 May 17;26(2):355-368. [PMID: 28395297]
26. Sheldrick RC, Benneyan JC, Kiss IG, Briggs-Gowan
MJ, Copeland W, Carter AS. Thresholds and
accuracy in screening tools for early detection of
psychopathology. J Child Psychol Psychiatry. 2015
Sep;56(9):936-948. [PMID: 26096036]
27. Perera H, Jeewandara KC, Seneviratne S, Guruge C.
Culturally adapted pictorial screening tool for autism
spectrum disorder: A new approach. World J Clin
Pediatr. 2017 Feb 08;6(1):45-51. [PMID: 28224095]
28. Beranova S, Stoklasa J, Dudova I, Markova D,
Kasparova M, Zemankova J, Urbanek T, Talasek T,
Luukka P, Hrdlicka M. A possible role of the Infant/
Toddler Sensory Profile in screening for autism:
a proof-of-concept study in the specific sample of
prematurely born children with birth weights <1,500 g.
Neuropsychiatr Dis Treat. 2017 Jan;13:191-200.
[PMID: 28182143]
29. Barbaro J, Dissanayake C. Prospective identification of
autism spectrum disorders in infancy and toddlerhood
using developmental surveillance: the social attention
and communication study. J Dev Behav Pediatr. 2010
Jun;31(5):376-385. [PMID: 20495475]
30. Barbaro J, Dissanayake C. Early markers of autism
spectrum disorders in infants and toddlers
prospectively identified in the Social Attention and
Communication Study. Autism. 2013 Jan;17(1):64-86.
[PMID: 22735682]
31. Plumb AM, Wetherby AM. Vocalization
Development in Toddlers with Autism Spectrum
Disorder. J Speech Lang Hear Res. 2013 Apr;56(2):
721-34. [PMID: 23275403]
32. Zwaigenbaum L, Bauman ML, Stone WL, Yirmiya N,
Estes A, Hansen RL, McPartland JC, Natowicz MR,
Choueiri R, Fein D, Kasari C, Pierce K, Buie T, Carter
A, Davis PA, Granpeesheh D, Mailloux Z, Newschaffer
C, Robins D, Roley SS, Wagner S, Wetherby A.
Early Identification of Autism Spectrum Disorder:
Recommendations for Practice and Research. Pediatrics.
2015 Oct;136 Suppl 1:S10-40. [PMID: 26430168]
33. Pierce K, Marinero S, Hazin R, McKenna B,
Barnes CC, Malige A. Eye Tracking Reveals Abnormal
Visual Preference for Geometric Images as an
Early Biomarker of an Autism Spectrum Disorder
Subtype Associated With Increased Symptom
Severity. Biol Psychiatry. 2016 Apr 15;79(8):657-666.
[PMID: 25981170]
34. Jones W, Klin A. Attention to eyes is present but
in decline in 2-6 month old infants later diagnosed
with autism. Nature. 2013 Dec; 504(7480):427-431.
[PMID: 24196715]
35. Shen MD, Nordahl CW, Young GS, Wootton-Gorges
SL, Lee A, Liston SE, Harrington KR, Ozonoff S,
Amaral DG. Early brain enlargement and elevated
extra-axial fluid in infants who develop autism
spectrum disorder. Brain. 2013 Sep;136(Pt 9):2825-
2835. [PMID: 23838695]
111
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
36. Hazlett HC, Gu H, Munsell BC, Kim SH, Styner M,
Wolff JJ, Elison JT, Swanson MR, Zhu H, Botteron KN,
Collins DL, Constantino JN, Dager SR, Estes AM, Evans
AC, Fonov VS, Gerig G, Kostopoulos P, McKinstry RC,
Pandey J, Paterson S, Pruett JR, Schultz RT, Shaw
DW, Zwaigenbaum L, Piven J. Early brain development
in infants at high risk for autism spectrum disorder.
Nature. 2017 Feb 15;542(7641):348-351.
[PMID: 28202961]
37. Lombardo MV, Pierce K, Eyler LT, Carter Barnes C,
Ahrens-Barbeau C, Solso S, Campbell K, Courchesne
E. Different functional neural substrates for good and
poor language outcome in autism. Neuron. 2015
Apr 22;86(2):567-577. [PMID: 25864635]
38. Emerson, RW, Adams, C, Nishino, T, Hazlett, HC,
Wolff, JJ, Zwaigenbaum, L, Constantino JN, Shen
MD, Swanson MR, Elison JT, Kandala S, Estes AM,
Botteron KN, Collins L, Dager SR, Evans AC, Gerig
G, Gu H, McKinstry RC, Paterson S, Schultz RT,
Styner M; Schlaggar BL, Pruett JR Jr, Piven J. Functional
neuroimaging of high-risk 6-month-old infants predicts
a diagnosis of autism at 24 months of age. Sci Transl
Med. 2017 Jun 7;9(393). pii: eaag2882.
[PMID: 28592562]
39. Pramparo T, Pierce K, Lombardo MV, Carter Barnes C,
Marinero S, Ahrens-Barbeau C, Murray SS, Lopez L,
Xu R, Courchesne E. Prediction of autism by
translation and immune/inflammation coexpressed
genes in toddlers from pediatric community practices.
JAMA Psychiatry. 2015 Apr;72(4):386-394.
[PMID: 25739104]
40. Miller M, Iosif AM, Young GS, Hill M, Phelps Hanzel E,
Hutman T, Johnson S, Ozonoff S. School-age outcomes
of infants at risk for autism spectrum disorder. Autism
Res. 2016 Jun;9(6):632-42. [PMID: 26451968]
41. Dawson G. Why It's Important to Continue Universal
Autism Screening While Research Fully Examines Its
Impact. JAMA Pediatr. 2016 Jun 01;170(6):527-528.
[PMID: 26882277]
42. Zwaigenbaum L, Bauman ML, Choueiri R, Kasari C,
Carter A, Granpeesheh D, Mailloux Z, Smith Roley
S, Wagner S, Fein D, Pierce K, Buie T, Davis PA,
Newschaffer C, Robins D, Wetherby A, Stone WL,
Yirmiya N, Estes A, Hansen RL, McPartland JC,
Natowicz MR. Early Intervention for Children With
Autism Spectrum Disorder Under 3 Years of Age:
Recommendations for Practice and Research.Pediatrics.
2015 Oct;136 Suppl 1:S60-81. [PMID: 26430170]
43. Anderson DK, Liang JW, Lord C. Predicting young
adult outcome among more and less cognitively able
individuals with autism spectrum disorders.
J Child Psychol Psychiatry. 2014 May;55(5):485-494.
[PMID: 24313878]
44. Pierce K, Courchesne E, Bacon E. To Screen or Not
to Screen Universally for Autism is not the Question:
Why the Task Force Got It Wrong. J Pediatr. 2016
Sep;176:182-194. [PMID: 27421956]
45. US Department of Education. The 38th Annual Report
to Congress on the Implementation of the Individuals
with Disabilities Education Act. Washington D.C.: U.S.
Department of Education; 2016.
46. Gillis JM. Screening Practices of Family Physicians
and Pediatricians in 2 Southern States. Infants &
Young Children. 2009; 22(4), 321-331.
47. Zuckerman KE, Mattox K, Donelan K, Batbayar O,
Baghaee A, Bethell C. Pediatrician identification of
Latino children at risk for autism spectrum disorder.
Pediatrics. 2013 Sep;132(3):445-53. [PMID: 23958770]
112
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
48. Robins DL, Fein D, Barton M. The Modified Checklist
for Autism in Toddlers (M-CHAT). Self-published.
1999; www.mchatscreen.com.
49. Robins DL, Fein D, Barton M. The Modified
Checklist for Autism in Toddlers, Revised, with
Follow-up (M-CHAT-R/F). Self-published. 2009;
www.mchatscreen.com.
50. Khowaja MK, Hazzard AP, Robins DL.
Sociodemographic Barriers to Early Detection
of Autism: Screening and Evaluation Using
the M-CHAT, M-CHAT-R, and Follow-Up.
J Autism Dev Disord. 2015 Jun;45(6):1797-808.
[PMID: 25488122]
51. Bethell CD, Kogan MD, Strickland BB, Schor EL,
Robertson J, Newacheck PW. A national and
state profile of leading health problems and health
care quality for US children: key insurance disparities
and across-state variations. Acad Pediatr. 2011
May-Jun;11(3 Suppl):S22-33. [PMID: 21570014]
52. Daniels AM, Mandell DS. Explaining Differences
in Age at Autism Spectrum Disorder Diagnosis:
A Critical Review. Autism. 2014 Jul;18(5):583-97.
[PMID: 23787411]
53. Herlihy L, Brooks B, Dumont-Mathieu T, Barton M,
Fein D, Chen C, Robins DL. Standardized screening
facilitates timely diagnosis of autism spectrum
disorder in a diverse sample of low-risk toddlers.
J Dev Behav Pediatr. 2014 Feb-Mar;35(2):85-92.
[PMID: 24509053]
54. Shattuck PT, Grosse SD. Issues related to the
diagnosis and treatment of autism spectrum
disorders. Dev Disabil Res Rev. 2007;13(2):129-35.
[PMID: 17563895]
55. García-Primo P, Hellendoorn A, Charman T, Roeyers
H, Dereu M, Roge B, Baduel S, Muratori F, Narzisi A,
Van Daalen E, Moilanen I, de la Paz MP, Canal-Bedia
R. Screening for autism spectrum disorders: state of
the art in Europe. Eur Child Adolesc Psychiatry. 2014
Nov;23(11):1005-21. [PMID: 24913785]
56. Soto S, Linas K, Jacobstein D, Biel M, Migdal T,
Anthony BJ. A review of cultural adaptations of
screening tools for autism spectrum disorders.
Autism. 2015 Aug;19(6):646-61. [PMID: 25008216]
57. Scarpa A, Reyes NM, Patriquin MA, Lorenzi J,
Hassenfeldt TA, Desai VJ, Kerkering KW. The modified
checklist for autism in toddlers: Reliability in a diverse
rural American sample. J Autism Dev Disord. 2013
Oct;43(10):2269-79. [PMID: 23386118]
58. Windham GC, Smith KS, Rosen N, Anderson MC,
Grether JK, Coolman RB, Harris S. Autism and
Developmental Screening in a Public, Primary Care
Setting Primarily Serving Hispanics: Challenges and
Results. J Autism Dev Disord. 2014 Jul;44(7):1621-32.
[PMID: 24408091]
59. Charman T, Baird, G Simonoff E, Chandler S,
Davison-Jenkins A, Sharma A, O'Sullivan T, Pickles
A. Testing two screening instruments for autism
spectrum disorder in UK community child health
services. Dev Med Child Neurol. 2016 Apr;58(4):
369-75. [PMID: 26303216]
60. Yama B, Freeman T, Graves E, Yuan S, Campbell MK.
Examination of the properties of the Modified Checklist
for Autism in Toddlers (M-CHAT) in a population
sample. J Autism Dev Disord. 2012 Jan;42(1):23-34.
[PMID: 21373956]
113
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
61. Pierce K, Carter C, Weinfeld M, Desmond J,
Hazin R, Bjork R, Gallagher N. Detecting, studying,
and treating autism early: the one-year well-baby
check-up approach. J Pediatr. 2011 Sep;159(3):
458-465.e1-6. [PMID: 21524759]
62. Kiani R, Tyrer F, Hodgson A, Berkin N, Bhaumik S.
Urban–rural differences in the nature and prevalence of
mental ill-health in adults with intellectual disabilities.
J Intellect Disabil Res. 2013 Feb;57(2):119-27.
[PMID: 22292906]
63. Janvier YM, Harris JF, Coffield CN, Louis B, Xie M,
Cidav Z, Mandell, DS. Screening for autism
spectrum disorder in underserved communities:
Early childcare providers as reporters. Autism.
2016 Apr;20(3):364-73. [PMID: 25991845]
64. Bates BR, Graham D, Striley K, Patterson S, Arora
A, Hamel-Lambert J. Examining antecedents of
caregivers’ access to early childhood developmental
screening: Implications for campaigns promoting use
of services in appalachian Ohio. Health Promot Pract.
2014 May;15(3):413-21. [PMID: 23479038]
65. Zuckerman KE, Sinche B, Cobian M, Cervantes M,
Mejia A, Becker T, Nicolaidis C. Conceptualization
of autism in the Latino community and its
relationship with early diagnosis. J Dev Behav
Pediatr. 2014 Oct;35(8):522-32. [PMID: 25186120]
66. Kavanagh J, Gerdes M, Sell K, Jimenez M, Guevara J.
SERIES: An integrated approach to supporting child
development. Evidence to Action. 2012; 1-15. Obtained
from: http://policylab.chop.edu/sites/default/
files/pdf/publications/PolicyLab_EtoA_SERIES_
Developmental_Screening_Summer_2012.pdf
67. Huerta M, Lord C. Diagnostic evaluation of autism
spectrum disorders. Pediatric Clinics of North America.
2012; 59(1), 103-111.
68. Papanikolaou K, Paliokosta E, Houliaras G, Vgenopoulou
S, Giouroukou E, Pehlivanidis A, Tomaras V, Tsiantis I.
Using the Autism Diagnostic Interview-Revised and
the Autism Diagnostic Observation Schedule-Generic
for the diagnosis of autism spectrum disorders in
a Greek sample with a wide range of intellectual
abilities. J Autism Dev Disord. 2009 Mar;39(3):
414-20. [PMID: 18752062]
69. Tsuchiya KJ, Matsumoto K, Yagi A, Inada N, Kuroda
M, Inokuchi E, Koyama T, Kamio Y, Tsujii M, Sakai S,
Mohri I, Taniike M, Iwanaga R, Ogasahara K, Miyachi
T, Nakajima S, Tani I, Ohnishi M, Inoue M, Nomura K,
Hagiwara T, Uchiyama T, Ichikawa H, Kobayashi S,
Miyamoto K, Nakamura K, Suzuki K, Mori N, Takei
N. Reliability and validity of autism diagnostic
interview-revised, Japanese version. J Autism Dev
Disord. 2013 Mar;43(3):643-62. [PMID: 22806002]
70. Lampi KM, Sourander A, Gissler M, Niemelä S,
Rehnström K, Pulkkinen E, Peltonen L, Von Wendt,
L. Brief report: validity of Finnish registry-based
diagnoses of autism with the ADI-R. Acta Paediatr.
2010 Sep;99(9):1425-8. [PMID: 20412100]
71. Becker MM, Wagner MB, Bosa CA, Schmidt C, Longo
D, Papaleo C, Riesgo RS. Translation and validation
of Autism Diagnostic Interview-Revised (ADI-R) for
autism diagnosis in Brazil. Arq Neuropsiquiatr. 2012
Mar;70(3):185-90. [PMID: 22392110]
72. Vanegas SB, Magaña S, Morales M, McNamara E.
Clinical Validity of the ADI-R in a US-Based Latino
Population. J Autism Dev Disord. 2016 May;46(5):
1623-35. [PMID: 26742934]
114
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
73. Lord C, Rutter M, Le Couteur A. Autism Diagnostic
Interview-Revised: a revised version of a diagnostic
interview for caregivers of individuals with possible
pervasive developmental disorders. J Autism Dev
Disord. 1994 Oct;24(5):659-85. [PMID: 7814313]
74. Dworzynski K, Ronald A, Bolton P, Happé F.
How different are girls and boys above and below
the diagnostic threshold for autism spectrum
disorders? J Am Acad Child Adolesc Psychiatry.
2012 Aug;51(8):788-97. [PMID: 22840550]
75. Loomes R, Hull L, Mandy WPL. What Is the Male-
to-Female Ratio in Autism Spectrum Disorder? A
Systematic Review and Meta-Analysis. J Am Acad
Child Adolesc Psychiatry. 2017 Jun;56(6):466-474.
[PMID: 28545751]
76. Mandy W, Chilvers R, Chowdhury U, Salter G,
Seigal A, Skuse D. Sex differences in autism
spectrum disorder: evidence from a large sample
of children and adolescents. J Autism Dev Disord.
2012 Jul;42(7):1304-13. [PMID: 21947663]
77. Hiller RM, Young RL, Weber N. Sex differences in
autism spectrum disorder based on DSM-5 criteria:
evidence from clinician and teacher reporting.
J Abnorm Child Psychol. 2014 Nov;42(8):1381-93.
[PMID: 24882502]
78. Hiller RM, Young RL, Weber N. Sex differences
in pre-diagnosis concerns for children later
diagnosed with autism spectrum disorder. Autism.
2016 Jan;20(1):75-84. [PMID: 25717130]
79. Miodovnik A, Harstad E, Sideridis G, Huntington N.
Timing of the diagnosis of attention-deficit/
hyperactivity disorder and autism spectrum disorder.
Pediatrics. 2015 Oct;136(4):e830-7. [PMID: 26371198]
80. Brugha TS, McManus S, Bankart J, Scott F, Purdon S,
Smith J, Bebbington P, Jenkins R, Meltzer H.
Epidemiology of autism spectrum disorders in adults
in the community in England. Arch Gen Psychiatry.
2011 May;68(5):459-65. [PMID: 21536975]
81. Croen LA, Zerbo O, Qian Y, Massolo ML, Rich S,
Sidney S, Kripke C. The health of adults on the
autism spectrum. Autism. 2015 Oct;19(7):814-23.
[PMID: 25911091]
82. Data Resource Center for Child & Adolescent Health.
National Survey of Children with Special Health Care Needs
2009/2010. Retrieved from: http://childhealthdata.
org/learn/NS-CSHCN
83. Cidav Z, Marcus SC, Mandell DS. Implications
of childhood autism for parental employment and
earnings. Pediatrics. 2012 Apr;129(4):617-23.
[PMID: 22430453]
84. Hartley SL, Barker ET, Seltzer MM, Floyd F, Greenberg
J, Orsmond G, Bolt D. The relative risk and timing of
divorce in families of children with an autism spectrum
disorder. J Fam Psychol. 2010 Aug;24(4):449-57.
[PMID: 20731491]
115
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION 2: WHAT IS THE BIOLOGY UNDERLYING ASD?
1. Sanders SJ, He X, Willsey AJ, Ercan-Sencicek AG,
Samocha KE, Cicek AE, Murtha MT, Bal VH, Bishop SL,
Dong S, Goldberg AP, Jinlu C, Keaney JF 3rd, Klei L,
Mandell JD, Moreno-De-Luca D, Poultney CS, Robinson
EB, Smith L, Solli-Nowlan T, Su MY, Teran NA, Walker
MF, Werling DM, Beaudet AL, Cantor RM, Fombonne
E, Geschwind DH, Grice DE, Lord C, Lowe JK, Mane SM,
Martin DM, Morrow EM, Talkowski ME, Sutcliffe JS,
Walsh CA, Yu TW; Autism Sequencing Consortium,
Ledbetter DH, Martin CL, Cook EH, Buxbaum JD,
Daly MJ, Devlin B, Roeder K, State MW. Insights
into autism spectrum disorder genomic architecture
and biology from 71 risk loci. Neuron. 2015
Sep 23;87(6):1215-33. [PMID: 26402605]
2. Guo H, Peng Y, Hu Z, Li Y, Xun G, Ou J, Sun L, Xiong
Z, Liu Y, Wang T, Chen J, Xia L, Bai T, Shen Y, Tian Q,
Hu Y, Shen L, Zhao R, Zhang X, Zhang F, Zhao J, Zou
X, Xia K. Genome-wide copy number variation analysis
in a Chinese autism spectrum disorder cohort. Sci Rep.
2017 Mar 10;7:44155. [PMID: 28281572]
3. Stessman HA, Xiong B, Coe BP, Wang T, Hoekzema K,
Fenckova M, Kvarnung M, Gerdts J, Trinh S, Cosemans
N, Vives L, Lin J, Turner TN, Santen G, Ruivenkamp C,
Kriek M, van Haeringen A, Aten E, Friend K, Liebelt
J, Barnett C, Haan E, Shaw M, Gecz J, Anderlid BM,
Nordgren A, Lindstrand A, Schwartz C, Kooy RF,
Vandeweyer G, Helsmoortel C, Romano C, Alberti A,
Vinci M, Avola E, Giusto S, Courchesne E, Pramparo
T, Pierce K, Nalabolu S, Amaral DG, Scheffer IE,
Delatycki MB, Lockhart PJ, Hormozdiari F, Harich B,
Castells-Nobau A, Xia K, Peeters H, Nordenskjöld M,
Schenck A, Bernier RA, Eichler EE. Targeted sequencing
identifies 91 neurodevelopmental-disorder risk
genes with autism and developmental-disability
biases. Nat Genet. 2017 Apr;49(4):515-526.
[PMID: 28191889]
4. Brandler WM, Antaki D, Gujral M, Noor A, Rosanio
G, Chapman TR, Barrera DJ, Lin GN, Malhotra D,
Watts AC, Wong LC, Estabillo JA, Gadomski TE,
Hong O, Fajardo KV, Bhandari A, Owen R, Baughn M,
Yuan J, Solomon T, Moyzis AG, Maile MS, Sanders
SJ, Reiner GE, Vaux KK, Strom CM, Zhang K, Muotri
AR, Akshoomoff N, Leal SM, Pierce K, Courchesne E,
Iakoucheva LM, Corsello C, Sebat J. Frequency and
complexity of de novo structural mutation in autism.
Am J Hum Genet. 2016 Apr 7;98(4):667-79.
[PMID: 27018473]
5. Kanduri C, Kantojärvi K, Salo PM, Vanhala R, Buck G,
Blancher C, Lähdesmäki H, Järvelä I. The landscape of
copy number variations in Finnish families with autism
spectrum disorders. Autism Res. 2016 Jan;9(1):9-16.
[PMID: 26052927]
6. C Yuen RK, Merico D, Bookman M, L Howe J,
Thiruvahindrapuram B, Patel RV, Whitney J, Deflaux
N, Bingham J, Wang Z, Pellecchia G, Buchanan JA,
Walker S, Marshall CR, Uddin M, Zarrei M, Deneault
E, D'Abate L, Chan AJ, Koyanagi S, Paton T, Pereira
SL, Hoang N, Engchuan W, Higginbotham EJ, Ho K,
Lamoureux S, Li W, MacDonald JR, Nalpathamkalam
T, Sung WW, Tsoi FJ, Wei J, Xu L, Tasse AM, Kirby E,
Van Etten W, Twigger S, Roberts W, Drmic I, Jilderda S,
Modi BM, Kellam B, Szego M, Cytrynbaum C,
Weksberg R, Zwaigenbaum L, Woodbury-Smith M,
Brian J, Senman L, Iaboni A, Doyle-Thomas K,
Thompson A, Chrysler C, Leef J, Savion-Lemieux T,
Smith IM, Liu X, Nicolson R, Seifer V, Fedele A, Cook
EH, Dager S, Estes A, Gallagher L, Malow BA, Parr JR,
Spence SJ, Vorstman J, Frey BJ, Robinson JT, Strug LJ,
Fernandez BA, Elsabbagh M, Carter MT, Hallmayer
J, Knoppers BM, Anagnostou E, Szatmari P, Ring RH,
Glazer D, Pletcher MT, Scherer SW. Whole genome
116
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
sequencing resource identifies 18 new candidate
genes for autism spectrum disorder. Nat Neurosci.
2017 Apr;20(4):602-611. [PMID: 28263302]
7. Wang T, Guo H, Xiong B, Stessman HA, Wu H, Coe
BP, Turner TN, Liu Y, Zhao W, Hoekzema K, Vives L,
Xia L, Tang M, Ou J, Chen B, Shen Y, Xun G, Long M,
Lin J, Kronenberg ZN, Peng Y, Bai T, Li H, Ke X, Hu Z,
Zhao J, Zou X, Xia K, Eichler EE. De novo genic
mutations among a Chinese autism spectrum
disorder cohort. Nat Commun. 2016 Nov 8;7:13316.
[PMID: 27824329]
8. Sztainberg Y, Zoghbi HY. Lessons learned from
studying syndromic autism spectrum disorders.
Nat Neurosci. 2016 Oct 26;19(11):1408-1417.
[PMID: 27786181]
9. O'Shea DJ, Trautmann E, Chandrasekaran C, Stavisky
S, Kao JC, Sahani M, Ryu S, Deisseroth K, Shenoy KV.
The need for calcium imaging in nonhuman primates:
New motor neuroscience and brain-machine
interfaces. Exp Neurol. 2017 Jan;287(Pt 4):437-451.
[PMID: 27511294]
10. Jennings C, Landman R, Zhou Y, Sharma J, Hyman
J, Movshon JA, Qiu Z, Roberts A, Roe AW, Wang
X, Zhou H, Wang L, Zhang F, Desimone R, Feng G.
Corrigendum: opportunities and challenges in
modeling human brain disorders in transgenic
primates. Nat Neurosci. 2017 Jun 27;20(7):1033.
[PMID: 28653692]
11. Quadrato G, Brown J, Arlotta P. The promises
and challenges of human brain organoids as
models of neuropsychiatric disease. Nat Med. 2016
Nov;22(11):1220-1228. [PMID: 27783065]
12. Renner M, Lancaster MA, Bian S, Choi H, Ku T,
Peer A, Chung K, Knoblich JA. Self-organized
developmental patterning and differentiation in
cerebral organoids. EMBO J. 2017 May
15;36(10):1316-1329. [PMID: 28283582]
13. Parikshak NN, Swarup V, Belgard TG, Irimia M,
Ramaswami G, Gandal MJ, Hartl C, Leppa V,
Ubieta LT, Huang J, Lowe JK, Blencowe BJ,
Horvath S, Geschwind DH. Genome-wide
changes in lncRNA, splicing, and regional gene
expression patterns in autism. Nature. 2016
Dec 15;540(7633):423-427. [PMID: 27919067]
14. Bellott DW, Hughes JF, Skaletsky H, Brown LG,
Pyntikova T, Cho TJ, Koutseva N, Zaghlul S, Graves
T, Rock S, Kremitzki C, Fulton RS, Dugan S, Ding Y,
Morton D, Khan Z, Lewis L, Buhay C, Wang Q, Watt J,
Holder M, Lee S, Nazareth L, Alföldi J, Rozen S, Muzny
DM, Warren WC, Gibbs RA, Wilson RK, Page DC.
Mammalian Y chromosomes retain widely expressed
dosage-sensitive regulators. Nature. 2014
Apr 24;508(7497):494-9. [PMID: 24759411]
15. Bellott DW, Skaletsky H, Cho TJ, Brown L, Locke D,
Chen N, Galkina S, Pyntikova T, Koutseva N, Graves
T, Kremitzki C, Warren WC, Clark AG, Gaginskaya
E, Wilson RK, Page DC. Avian W and mammalian Y
chromosomes convergently retained dosage-sensitive
regulators. Nat Genet. 2017 Mar;49(3):387-394.
[PMID: 28135246]
16. Hughes JF, Page DC. The biology and evolution
of mammalian Y chromosomes. Annu Rev Genet.
2015;49:507-27. [PMID: 26442847]
17. Green SA, Hernandez L, Tottenham N, Krasileva K,
Bookheimer SY, Dapretto M. Neurobiology of sensory
overresponsivity in youth With autism spectrum
disorders. JAMA Psychiatry. 2015 Aug;72(8):778-86.
[PMID: 26061819]
117
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
18. Khan S, Michmizos K, Tommerdahl M, Ganesan S,
Kitzbichler MG, Zetino M, Garel KL, Herbert MR,
Hämäläinen MS, Kenet T. Somatosensory cortex
functional connectivity abnormalities in autism show
opposite trends, depending on direction and spatial
scale. Brain. 2015 May;138(Pt 5):1394-409.
[PMID: 25765326]
19. Modi ME, Sahin M. Translational use of event-related
potentials to assess circuit integrity in ASD. Nat Rev
Neurol. 2017 Mar;13(3):160-170. [PMID: 28211449]
20. Li J, Qiu L, Xu L, Pedapati EV, Erickson CA, Sunar U.
Characterization of autism spectrum disorder with
spontaneous hemodynamic activity. Biomed Opt Express.
2016 Sep 6;7(10):3871-3881. [PMID: 27867699]
21. Courchesne E, Pierce K. Why the frontal cortex
in autism might be talking only to itself: local over-
connectivity but long-distance disconnection.
Curr Opin Neurobiol. 2005 Apr;15(2):225-30.
[PMID: 15831407]
22. Di Martino A, Yan CG, Li Q, Denio E, Castellanos
FX, Alaerts K, Anderson JS, Assaf M, Bookheimer
SY, Dapretto M, Deen B, Delmonte S, Dinstein I,
Ertl-Wagner B, Fair DA, Gallagher L, Kennedy DP,
Keown CL, Keysers C, Lainhart JE, Lord C, Luna B,
Menon V, Minshew NJ, Monk CS, Mueller S,
Müller RA, Nebel MB, Nigg JT, O'Hearn K, Pelphrey
KA, Peltier SJ, Rudie JD, Sunaert S, Thioux M,
Tyszka JM, Uddin LQ, Verhoeven JS, Wenderoth N,
Wiggins JL, Mostofsky SH, Milham MP. The autism
brain imaging data exchange: towards a large-scale
evaluation of the intrinsic brain architecture in autism.
Mol Psychiatry. 2014 Jun;19(6):659-67.
[PMID: 23774715]
23. Mohammad-Rezazadeh I, Frohlich J, Loo SK, Jeste
SS. Brain connectivity in autism spectrum disorder.
Curr Opin Neurol. 2016 Apr;29(2):137-47.
[PMID: 26910484]
24. Chawarska K, Campbell D, Chen L, Shic F, Klin A,
Chang J. Early generalized overgrowth in boys with
autism. Arch Gen Psychiatry. 2011 Oct;68(10):1021-31.
[PMID: 21969460]
25. Nordahl CW, Lange N, Li DD, Barnett LA, Lee A,
Buonocore MH, Simon TJ, Rogers S, Ozonoff S,
Amaral DG. Brain enlargement is associated with
regression in preschool-age boys with autism
spectrum disorders. Proc Natl Acad Sci U S A. 2011
Dec 13;108(50):20195-200. [PMID: 22123952]
26. Libero LE, Nordahl CW, Li DD, Ferrer E, Rogers SJ,
Amaral DG. Persistence of megalencephaly in a
subgroup of young boys with autism spectrum
disorder. Autism Res. 2016 Nov;9(11):1169-1182.
[PMID: 27273931]
27. Amaral DG, Li D, Libero L, Solomon M, Van de Water
J, Mastergeorge A, Naigles L, Rogers S, Wu Nordahl
C. In pursuit of neurophenotypes: the consequences
of having autism and a big brain. Autism Res. 2017
May;10(5):711-722. [PMID: 28239961]
28. Redcay E, Courchesne E. When is the brain enlarged in
autism? a meta-analysis of all brain size reports. Biol
Psychiatry. 2005 Jul 1;58(1):1-9. [PMID: 15935993]
29. Cerliani L, Mennes M, Thomas RM, Di Martino A,
Thioux M, Keysers C. Increased functional connectivity
between subcortical and cortical resting-state networks
in autism spectrum disorder. JAMA Psychiatry. 2015
Aug;72(8):767-77. [PMID: 26061743]
118
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
30. Green SA, Hernandez L, Bookheimer SY, Dapretto M.
Reduced modulation of thalamocortical connectivity
during exposure to sensory stimuli in ASD. Autism
Res. 2017 May;10(5):801-809. [PMID: 27896947]
31. Kaiser MD, Yang DY, Voos AC, Bennett RH, Gordon
I, Pretzsch C, Beam D, Keifer C, Eilbott J, McGlone F,
Pelphrey KA. Brain mechanisms for processing
affective (and nonaffective) touch are atypical in
autism. Cereb Cortex. 2016 Jun;26(6):2705-14.
[PMID: 26048952]
32. Byrge L, Dubois J, Tyszka JM, Adolphs R, Kennedy
DP. Idiosyncratic brain activation patterns are
associated with poor social comprehension in
autism. J Neurosci. 2015 Apr 8;35(14):5837-50.
[PMID: 25855192]
33. Redcay E, Dodell-Feder D, Mavros PL, Kleiner M,
Pearrow MJ, Triantafyllou C, Gabrieli JD, Saxe R.
Atypical brain activation patterns during a
face-to-face joint attention game in adults with
autism spectrum disorder. Hum Brain Mapp.
2013 Oct;34(10):2511-23. [PMID: 22505330]
34. Chen JA, Peñagarikano O, Belgard TG, Swarup V,
Geschwind DH. The emerging picture of autism
spectrum disorder: genetics and pathology. Annu
Rev Pathol. 2015;10:111-44. [PMID: 25621659]
35. Lerner TN, Ye L, Deisseroth K. Communication
in neural circuits: tools, opportunities, and
challenges. Cell. 2016 Mar 10;164(6):1136-50.
[PMID: 26967281]
36. Ricci S, Businaro R, Ippoliti F, Lo Vasco VR, Massoni
F, Onofri E, Troili GM, Pontecorvi V, Morelli M, Rapp
Ricciardi M, Archer T. Altered cytokine and BDNF
levels in autism spectrum disorder. Neurotox Res.
2013 Nov;24(4):491-501. [PMID: 23604965]
37. Mead J and Ashwood P. Evidence supporting an
altered immune response in ASD. Immunol Lett.
2015 Jan;163(1):49-55. [PMID: 25448709]
38. Jyonouchi H, Geng L, Davidow AL. Cytokine profiles
by peripheral blood monocytes are associated with
changes in behavioral symptoms following immune
insults in a subset of ASD subjects: an inflammatory
subtype? J Neuroinflammation. 2014 Oct 27;11:187.
[PMID: 25344730]
39. Masi A, Quintana DS, Glozier N, Lloyd AR, Hickie IB,
Guastella AJ. Cytokine aberrations in autism spectrum
disorder: a systematic review and meta-analysis.
Mol Psychiatry. 2015 Apr;20(4):440-6.
[PMID: 24934179]
40. Nordahl CW, Braunschweig D, Iosif AM, Lee A,
Rogers S, Ashwood P, Amaral DG, Van de Water J.
Maternal autoantibodies are associated with abnormal
brain enlargement in a subgroup of children with
autism spectrum disorder. Brain Behav Immun. 2013
May;30:61-5. [PMID: 23395715]
41. Bauman MD, Iosif AM, Ashwood P, Braunschweig D,
Lee A, Schumann CM, Van de Water J, Amaral DG.
Maternal antibodies from mothers of children
with autism alter brain growth and social behavior
development in the rhesus monkey. Transl Psychiatry.
2013 Jul 9;3:e278. [PMID: 23838889]
42. Braunschweig D, Krakowiak P, Duncanson P,
Boyce R, Hansen RL, Ashwood P, Hertz-Picciotto I,
Pessah IN, Van de Water J. Autism-specific
maternal autoantibodies recognize critical proteins
in developing brain. Transl Psychiatry. 2013
Jul 9;3:e277. [PMID: 23838888]
43. Zerbo O, Iosif AM, Walker C, Ozonoff S, Hansen RL,
Hertz-Picciotto I. Is maternal influenza or fever during
pregnancy associated with autism or developmental
119
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
delays? results from the CHARGE (CHildhood
Autism Risks from Genetics and Environment) study.
J Autism Dev Disord. 2013 Jan;43(1):25-33.
[PMID: 22562209]
44. Brimberg L, Mader S, Jeganathan V, Berlin R, Coleman
TR, Gregersen PK, Huerta PT, Volpe BT, Diamond B.
Caspr2-reactive antibody cloned from a mother of
an ASD child mediates an ASD-like phenotype in mice.
Mol Psychiatry. 2016 Dec;21(12):1663-1671.
[PMID: 27698429]
45. Brimberg L, Sadiq A, Gregersen PK, Diamond B.
Brain-reactive IgG correlates with autoimmunity in
mothers of a child with an autism spectrum
disorder. Mol Psychiatry. 2013 Nov;18(11):1171-7.
[PMID: 23958959]
46. Choi GB, Yim YS, Wong H, Kim S, Kim H, Kim SV,
Hoeffer CA, Littman DR, Huh JR. The maternal
interleukin-17a pathway in mice promotes
autism-like phenotypes in offspring. Science. 2016
Feb 26;351(6276):933-9. [PMID: 26822608]
47. Cunningham CL, Martínez-Cerdeño V, Noctor SC.
Microglia regulate the number of neural precursor
cells in the developing cerebral cortex. J Neurosci.
2013 Mar 6;33(10):4216-33. [PMID: 23467340]
48. Kim HJ, Cho MH, Shim WH, Kim JK, Jeon EY, Kim DH,
Yoon SY. Deficient autophagy in microglia impairs
synaptic pruning and causes social behavioral
defects. Mol Psychiatry. 2016 Jul 12. [Epub ahead
of print] [PMID: 27400854]
49. Schafer DP, Lehrman EK, Kautzman AG, Koyama
R, Mardinly AR, Yamasaki R, Ransohoff RM,
Greenberg ME, Barres BA, Stevens B. Microglia
sculpt postnatal neural circuits in an activity and
complement-dependent manner. Neuron. 2012
May 24;74(4):691-705. [PMID: 22632727]
50. Gupta S, Ellis SE, Ashar FN, Moes A, Bader JS, Zhan J,
West AB, Arking DE. Transcriptome analysis reveals
dysregulation of innate immune response genes and
neuronal activity-dependent genes in autism. Nat
Commun. 2014 Dec 10;5:5748. [PMID: 25494366]
51. Vargas DL, Nascimbene C, Krishnan C,
Zimmerman AW, Pardo CA. Neuroglial activation
and neuroinflammation in the brain of patients
with autism. Ann Neurol. 2005 Jan;57(1):67-81.
[PMID: 15546155]
52. Morgan JT, Chana G, Pardo CA, Achim C, Semendeferi
K, Buckwalter J, Courchesne E, Everall IP. Microglial
activation and increased microglial density observed
in the dorsolateral prefrontal cortex in autism.
Biol Psychiatry. 2010 Aug 15;68(4):368-76.
[PMID: 20674603]
53. Tetreault NA, Hakeem AY, Jiang S, Williams BA,
Allman E, Wold BJ, Allman JM. Microglia in the
cerebral cortex in autism. J Autism Dev Disord. 2012
Dec;42(12):2569-84. [PMID: 22466688]
54. Schafer DP, Heller CT, Gunner G, Heller M, Gordon
C, Hammond T, Wolf Y, Jung S, Stevens B. Microglia
contribute to circuit defects in Mecp2 null mice
independent of microglia-specific loss of Mecp2
expression. Elife. 2016 Jul 26;5. pii: e15224.
[PMID: 27458802]
55. Morgan JT, Barger N, Amaral DG, Schumann CM.
Stereological study of amygdala glial populations
in adolescents and adults with autism spectrum
disorder. PLoS One. 2014 Oct 17;9(10):e110356.
[PMID: 25330013]
56. Wolff JJ, Piven J. Neurodevelopmental disorders:
accelerating progress in autism through
developmental research. Nat Rev Neurol. 2014
Aug;10(8):431-2. [PMID: 25023342]
120
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
57. Varcin KJ, Jeste SS. The emergence of autism spectrum
disorder: insights gained from studies of brain and
behaviour in high-risk infants. Curr Opin Psychiatry.
2017 Mar;30(2):85-91. [PMID: 28009726]
58. de la Torre-Ubieta L, Won H, Stein JL, Geschwind
DH. Advancing the understanding of autism disease
mechanisms through genetics. Nat Med. 2016
Apr;22(4):345-61. [PMID: 27050589]
59. Landa R, Garrett-Mayer E. Development in infants
with autism spectrum disorders: a prospective study.
J Child Psychol Psychiatry. 2006 Jun;47(6):629-38.
[PMID: 16712640]
60. Ozonoff S, Young GS, Carter A, Messinger D,
Yirmiya N, Zwaigenbaum L, Bryson S, Carver LJ,
Constantino JN, Dobkins K, Hutman T, Iverson
JM, Landa R, Rogers SJ, Sigman M, Stone WL.
Recurrence risk for autism spectrum disorders: a
Baby Siblings Research Consortium study. Pediatrics.
2011 Sep;128(3):e488-95. [PMID: 21844053]
61. Rozga A, Hutman T, Young GS, Rogers SJ, Ozonoff S,
Dapretto M, Sigman M. Behavioral profiles of affected
and unaffected siblings of children with autism:
contribution of measures of mother-infant interaction
and nonverbal communication. J Autism Dev Disord.
2011 Mar;41(3):287-301. [PMID: 20568002]
62. Zwaigenbaum L, Bryson S, Rogers T, Roberts W,
Brian J, Szatmari P. Behavioral manifestations of
autism in the first year of life. Int J Dev Neurosci.
2005 Apr-May;23(2-3):143-52. [PMID: 15749241]
63. Charman T, Young GS, Brian J, Carter A, Carver LJ,
Chawarska K, Curtin S, Dobkins K, Elsabbagh M,
Georgiades S, Hertz-Picciotto I, Hutman T, Iverson JM,
Jones EJ, Landa R, Macari S, Messinger DS, Nelson
CA, Ozonoff S, Saulnier C, Stone WL, Tager-Flusberg
H, Webb SJ, Yirmiya N, Zwaigenbaum L. Non-ASD
outcomes at 36 months in siblings at familial risk
for autism spectrum disorder (ASD): a baby siblings
research consortium (BSRC) study. Autism Res. 2017
Jan;10(1):169-178. [PMID: 27417857]
64. Szatmari P, Chawarska K, Dawson G, Georgiades S,
Landa R, Lord C, Messinger DS, Thurm A, Halladay
A. Prospective longitudinal studies of infant siblings
of children with autism: lessons learned and future
directions. J Am Acad Child Adolesc Psychiatry. 2016
Mar;55(3):179-87. [PMID: 26903251]
65. Jones EJ, Gliga T, Bedford R, Charman T, Johnson MH.
Developmental pathways to autism: a review of
prospective studies of infants at risk. Neurosci Biobehav
Rev. 2014 Feb;39:1-33. [PMID: 24361967]
66. Flanagan JE, Landa R, Bhat A, Bauman M. Head
lag in infants at risk for autism: a preliminary study.
Am J Occup Ther. 2012 Sep-Oct;66(5):577-85.
[PMID: 22917124]
67. Jones W, Klin A. Attention to eyes is present but in
decline in 2-6-month-old infants later diagnosed
with autism. Nature. 2013 Dec 19;504(7480):427-31.
[PMID: 24196715]
68. Wolff JJ, Gu H, Gerig G, Elison JT, Styner M, Gouttard
S, Botteron KN, Dager SR, Dawson G, Estes AM,
Evans AC, Hazlett HC, Kostopoulos P, McKinstry
RC, Paterson SJ, Schultz RT, Zwaigenbaum L, Piven J;
IBIS Network. Differences in white matter fiber tract
development present from 6 to 24 months in infants
with autism. Am J Psychiatry. 2012 Jun;169(6):589-
600. [PMID: 22362397]
69. Hazlett HC, Gu H, Munsell BC, Kim SH, Styner M,
Wolff JJ, Elison JT, Swanson MR, Zhu H, Botteron KN,
Collins DL, Constantino JN, Dager SR, Estes AM, Evans
AC, Fonov VS, Gerig G, Kostopoulos P, McKinstry
RC, Pandey J, Paterson S, Pruett JR, Schultz RT, Shaw
121
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
DW, Zwaigenbaum L, Piven J; IBIS Network; Clinical
Sites; Data Coordinating Center; Image Processing
Core; Statistical Analysis. Early brain development
in infants at high risk for autism spectrum disorder.
Nature. 2017 Feb 15;542(7641):348-351.
[PMID: 28202961]
70. Shen MD, Kim SH, McKinstry RC, Gu H, Hazlett
HC, Nordahl CW, Emerson RW, Shaw D, Elison JT,
Swanson MR, Fonov VS, Gerig G, Dager SR, Botteron
KN, Paterson S, Schultz RT, Evans AC, Estes AM,
Zwaigenbaum L, Styner MA, Amaral DG, Piven J;
Infant Brain Imaging Study Network; Infant Brain
Imaging Study Network, The Infant Brain Imaging
Study (IBIS) Network is a National Institutes of
Health–funded Autism Center of Excellence project
and consists of a consortium of eight universities in
the United States and Canada, Piven J, Hazlett HC,
Chappell C, Dager S, Estes A, Shaw D, Botteron
K, McKinstry R, Constantino J, Pruett J, Schultz R,
Zwaigenbaum L, Elison J, Evans AC, Collins DL, Pike
GB, Fonov V, Kostopoulos P, Das S, Gerig G, Styner
M, Gu H. Increased extra-axial cerebrospinal
fluid in high-risk infants who later develop autism.
Biol Psychiatry. 2017 Aug 1;82(3):186-193.
[PMID: 28392081]
71. Georgiades S, Bishop SL, Frazier T. Editorial Perspective:
Longitudinal research in autism - introducing the
concept of 'chronogeneity'. J Child Psychol Psychiatry.
2017 May;58(5):634-636. [PMID: 28414862]
72. Fountain C, Winter AS, Bearman PS. Six developmental
trajectories characterize children with autism. Pediatrics.
2012 May;129(5):e1112-20. [PMID: 22473372]
73. Reis VN, Kitajima JP, Tahira AC, Feio-Dos-Santos
AC, Fock RA, Lisboa BC, Simões SN, Krepischi AC,
Rosenberg C, Lourenço NC, Passos-Bueno MR, Brentani
H. Integrative variation analysis reveals that a complex
genotype may specify phenotype in siblings with
syndromic autism spectrum disorder. PLoS One. 2017
Jan 24;12(1):e0170386. [PMID: 28118382]
74. Flax JF, Hare A, Azaro MA, Vieland VJ, Brzustowicz
LM. Combined linkage and linkage disequilibrium
analysis of a motor speech phenotype within families
ascertained for autism risk loci. J Neurodev Disord.
2010 Dec;2(4):210-223. [PMID: 21125004]
75. Anitha A, Thanseem I, Nakamura K, Vasu MM,
Yamada K, Ueki T, Iwayama Y, Toyota T, Tsuchiya KJ,
Iwata Y, Suzuki K, Sugiyama T, Tsujii M, Yoshikawa T,
Mori N. Zinc finger protein 804A (ZNF804A) and
verbal deficits in individuals with autism. J Psychiatry
Neurosci. 2014 Sep;39(5):294-303.
[PMID: 24866414]
76. Zhou X, Xu Y, Wang J, Zhou H, Liu X, Ayub Q,
Wang X, Tyler-Smith C, Wu L, Xue Y. Replication of
the association of a MET variant with autism in a
Chinese Han population. PLoS One. 2011;6(11):e27428.
[PMID: 22110649]
77. Nordahl CW, Mello M, Shen AM, Shen MD, Vismara
LA, Li D, Harrington K, Tanase C, Goodlin-Jones
B, Rogers S, Abbeduto L, Amaral DG. Methods for
acquiring MRI data in children with autism spectrum
disorder and intellectual impairment without the
use of sedation. J Neurodev Disord. 2016 May 5;8:20.
[PMID: 27158271]
78. Lombardo MV, Pierce K, Eyler LT, Carter Barnes C,
Ahrens-Barbeau C, Solso S, Campbell K, Courchesne
E. Different functional neural substrates for good
and poor language outcome in autism. Neuron. 2015
Apr 22;86(2):567-77. [PMID: 25864635]
122
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
79. Björnsdotter M, Wang N, Pelphrey K, Kaiser MD.
Evaluation of quantified social perception circuit activity
as a neurobiological marker of autism spectrum
disorder. JAMA Psychiatry. 2016 Jun 1;73(6):614-21.
[PMID: 27096285]
80. Orekhova EV, Elsabbagh M, Jones EJ, Dawson G,
Charman T, Johnson MH; BASIS Team. EEG
hyper-connectivity in high-risk infants is associated
with later autism. J Neurodev Disord. 2014;6(1):40.
[PMID: 25400705]
81. Yang D, Pelphrey KA, Sukhodolsky DG, Crowley MJ,
Dayan E, Dvornek NC, Venkataraman A, Duncan J,
Staib L, Ventola P. Brain responses to biological motion
predict treatment outcome in young children with
autism. Transl Psychiatry. 2016 Nov 15;6(11):e948.
[PMID: 27845779]
82. Shen MD, Nordahl CW, Young GS, Wootton-Gorges
SL, Lee A, Liston SE, Harrington KR, Ozonoff S,
Amaral DG. Early brain enlargement and elevated
extra-axial fluid in infants who develop autism spectrum
disorder. Brain. 2013 Sep;136(Pt 9):2825-35.
[PMID: 23838695]
83. Hsiao EY. Gastrointestinal issues in autism
spectrum disorder. Harv Rev Psychiatry. 2014
Mar-Apr;22(2):104-11. [PMID: 24614765]
84. Gorrindo P, Williams KC, Lee EB, Walker LS,
McGrew SG, Levitt P. Gastrointestinal dysfunction
in autism: parental report, clinical evaluation, and
associated factors. Autism Res. 2012 Apr;5(2):101-8.
[PMID: 22511450]
85. Chaidez V, Hansen RL, Hertz-Picciotto I. Gastrointestinal
problems in children with autism, developmental
delays or typical development. J Autism Dev Disord.
2014 May;44(5):1117-27. [PMID: 24193577]
86. Furuta GT, Williams K, Kooros K, Kaul A, Panzer R,
Coury DL, Fuchs G. Management of constipation
in children and adolescents with autism spectrum
disorders. Pediatrics. 2012 Nov;130 Suppl 2:S98-105.
[PMID: 23118260]
87. McElhanon BO, McCracken C, Karpen S, Sharp
WG. Gastrointestinal symptoms in autism
spectrum disorder: a meta-analysis. Pediatrics.
2014 May;133(5):872-83. [PMID: 24777214]
88. Orefice LL, Zimmerman AL, Chirila AM, Sleboda
SJ, Head JP, Ginty DD. Peripheral mechanosensory
neuron dysfunction underlies tactile and behavioral
deficits in mouse models of ASDs. Cell. 2016 Jul
14;166(2):299-313. [PMID: 27293187]
89. Strati F, Cavalieri D, Albanese D, De Felice C, Donati C,
Hayek J, Jousson O, Leoncini S, Renzi D, Calabrò A,
De Filippo C. New evidences on the altered gut
microbiota in autism spectrum disorders. Microbiome.
2017 Feb 22;5(1):24. [PMID: 28222761]
90. Mulle JG, Sharp WG, Cubells JF. The gut microbiome:
a new frontier in autism research. Curr Psychiatry Rep.
2013 Feb;15(2):337. [PMID: 23307560]
91. Wang L, Christophersen CT, Sorich MJ, Gerber JP,
Angley MT, Conlon MA. Increased abundance of
Sutterella spp. and Ruminococcus torques in feces of
children with autism spectrum disorder. Mol Autism.
2013 Nov 4;4(1):42. [PMID: 24188502]
92. Li Q, Zhou JM. The microbiota-gut-brain axis and
its potential therapeutic role in autism spectrum
disorder. Neuroscience. 2016 Jun 2;324:131-9.
[PMID: 26964681]
123
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
93. Keller R, Basta R, Salerno L, Elia M. Autism, epilepsy,
and synaptopathies: a not rare association. Neurol Sci.
2017 Aug;38(8):1353-1361. [PMID: 28455770]
94. El Achkar CM, Spence SJ. Clinical characteristics of
children and young adults with co-occurring autism
spectrum disorder and epilepsy. Epilepsy Behav. 2015
Jun;47:183-90. [PMID: 25599987]
95. Jokiranta E, Sourander A, Suominen A, Timonen-Soivio
L, Brown AS, Sillanpää M. Epilepsy among children
and adolescents with autism spectrum disorders: a
population-based study. J Autism Dev Disord. 2014
Oct;44(10):2547-57. [PMID: 24803367]
96. Vohra R, Madhavan S, Sambamoorthi U.
Comorbidity prevalence, healthcare utilization,
and expenditures of Medicaid enrolled adults
with autism spectrum disorders. Autism. 2016 Oct
20. pii: 1362361316665222. [PMID: 27875247]
97. Viscidi EW, Johnson AL, Spence SJ, Buka SL, Morrow
EM, Triche EW. The association between epilepsy
and autism symptoms and maladaptive behaviors in
children with autism spectrum disorder. Autism. 2014
Nov;18(8):996-1006. [PMID: 24165273]
98. Buckley AW, Holmes GL. Epilepsy and autism. Cold
Spring Harb Perspect Med. 2016 Apr 1;6(4):a022749.
[PMID: 26989064]
99. Singh K, Zimmerman AW. Sleep in autism spectrum
disorder and attention deficit hyperactivity disorder.
Semin Pediatr Neurol. 2015 Jun;22(2):113-25.
[PMID: 26072341]
100. Souders MC, Zavodny S, Eriksen W, Sinko R, Connell
J, Kerns C, Schaaf R, Pinto-Martin J. Sleep in children
with autism spectrum disorder. Curr Psychiatry Rep.
2017 Jun;19(6):34. [PMID: 28502070]
101. Buck TR, Viskochil J, Farley M, Coon H, McMahon
WM, Morgan J, Bilder DA. Psychiatric comorbidity
and medication use in adults with autism spectrum
disorder. J Autism Dev Disord. 2014 Dec;44(12):
3063-71. [PMID: 24958436]
102. Roy M, Prox-Vagedes V, Ohlmeier MD, Dillo W.
Beyond childhood: psychiatric comorbidities and
social background of adults with Asperger syndrome.
Psychiatr Danub. 2015 Mar;27(1):50-9.
[PMID: 25751431]
103. García-Villamisar D, Rojahn J. Comorbid
psychopathology and stress mediate the relationship
between autistic traits and repetitive behaviours
in adults with autism. J Intellect Disabil Res. 2015
Feb;59(2):116-24. [PMID: 23919538]
104. Lever AG, Geurts HM. Psychiatric co-occurring
symptoms and disorders in young, middle-aged,
and older adults with autism spectrum disorder.
J Autism Dev Disord. 2016 Jun;46(6):1916-30.
[PMID: 26861713]
105. Gadow KD, Smith RM, Pinsonneault JK. Serotonin 2A
receptor gene (HTR2A) regulatory variants: possible
association with severity of depression symptoms in
children with autism spectrum disorder. Cogn Behav
Neurol. 2014 Jun;27(2):107-16. [PMID: 24968012]
106. Steward O, Balice-Gordon R. Rigor or mortis: best
practices for preclinical research in neuroscience.
Neuron. 2014 Nov 5;84(3):572-81. [PMID: 25442936]
124
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION 3: WHAT CAUSES ASD, AND CAN DISABLING ASPECTS OF ASD BE PREVENTED OR PREEMPTED?
1. De Rubeis S, Buxbaum JD. Genetics and genomics
of autism spectrum disorder: embracing complexity.
Hum Mol Genet. 2015 Oct 15;24(R1):R24-31.
[PMID: 26188008]
2. Geschwind DH, State MW. Gene hunting in
autism spectrum disorder: on the path to precision
medicine. Lancet Neurol. 2015 Nov;14(11):1109-20.
[PMID: 25891009]
3. Pinto D, Pagnamenta AT, Klei L, Anney R, Merico D,
Regan R, Conroy J, Magalhaes TR, Correia C,
Abrahams BS, Almeida J, Bacchelli E, Bader GD, Bailey
AJ, Baird G, Battaglia A, Berney T, Bolshakova N,
Bölte S, Bolton PF, Bourgeron T, Brennan S, Brian J,
Bryson SE, Carson AR, Casallo G, Casey J, Chung BH,
Cochrane L, Corsello C, Crawford EL, Crossett A,
Cytrynbaum C, Dawson G, de Jonge M, Delorme R,
Drmic I, Duketis E, Duque F, Estes A, Farrar P, Fernandez
BA, Folstein SE, Fombonne E, Freitag CM, Gilbert J,
Gillberg C, Glessner JT, Goldberg J, Green A, Green
J, Guter SJ, Hakonarson H, Heron EA, Hill M, Holt R,
Howe JL, Hughes G, Hus V, Igliozzi R, Kim C, Klauck SM,
Kolevzon A, Korvatska O, Kustanovich V, Lajonchere
CM, Lamb JA, Laskawiec M, Leboyer M, Le Couteur
A, Leventhal BL, Lionel AC, Liu XQ, Lord C, Lotspeich
L, Lund SC, Maestrini E, Mahoney W, Mantoulan C,
Marshall CR, McConachie H, McDougle CJ, McGrath
J, McMahon WM, Merikangas A, Migita O, Minshew
NJ, Mirza GK, Munson J, Nelson SF, Noakes C, Noor
A, Nygren G, Oliveira G, Papanikolaou K, Parr JR,
Parrini B, Paton T, Pickles A, Pilorge M, Piven J,
Ponting CP, Posey DJ, Poustka A, Poustka F, Prasad A,
Ragoussis J, Renshaw K, Rickaby J, Roberts W, Roeder
K, Roge B, Rutter ML, Bierut LJ, Rice JP, Salt J, Sansom
K, Sato D, Segurado R, Sequeira AF, Senman L, Shah
N, Sheffield VC, Soorya L, Sousa I, Stein O, Sykes N,
Stoppioni V, Strawbridge C, Tancredi R, Tansey K,
Thiruvahindrapduram B, Thompson AP, Thomson S,
Tryfon A, Tsiantis J, Van Engeland H, Vincent JB,
Volkmar F, Wallace S, Wang K, Wang Z, Wassink TH,
Webber C, Weksberg R, Wing K, Wittemeyer K,
Wood S, Wu J, Yaspan BL, Zurawiecki D, Zwaigenbaum
L, Buxbaum JD, Cantor RM, Cook EH, Coon H, Cuccaro
ML, Devlin B, Ennis S, Gallagher L, Geschwind DH,
Gill M, Haines JL, Hallmayer J, Miller J, Monaco AP,
Nurnberger JI Jr, Paterson AD, Pericak-Vance MA,
Schellenberg GD, Szatmari P, Vicente AM, Vieland
VJ, Wijsman EM, Scherer SW, Sutcliffe JS, Betancur
C. Functional impact of global rare copy number
variation in autism spectrum disorders. Nature. 2010
Jul 15;466(7304):368-72. [PMID: 20531469]
4. Sanders SJ, Ercan-Sencicek AG, Hus V, Luo R,
Murtha MT, Moreno-De-Luca D, Chu SH, Moreau
MP, Gupta AR, Thomson SA, Mason CE, Bilguvar
K, Celestino-Soper PB, Choi M, Crawford EL, Davis
L, Wright NR, Dhodapkar RM, DiCola M, DiLullo
NM, Fernandez TV, Fielding-Singh V, Fishman DO,
Frahm S, Garagaloyan R, Goh GS, Kammela S, Klei L,
Lowe JK, Lund SC, McGrew AD, Meyer KA, Moffat
WJ, Murdoch JD, O'Roak BJ, Ober GT, Pottenger RS,
Raubeson MJ, Song Y, Wang Q, Yaspan BL, Yu TW,
Yurkiewicz IR, Beaudet AL, Cantor RM, Curland M,
Grice DE, Günel M, Lifton RP, Mane SM, Martin DM,
Shaw CA, Sheldon M, Tischfield JA, Walsh CA,
Morrow EM, Ledbetter DH, Fombonne E, Lord C, Martin
CL, Brooks AI, Sutcliffe JS, Cook EH Jr, Geschwind D,
Roeder K, Devlin B, State MW. Multiple recurrent de
novo CNVs, including duplications of the 7q11.23
Williams syndrome region, are strongly associated
with autism. Neuron. 2011 Jun 9;70(5):863-85.
[PMID: 21658581]
125
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
5. Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin
C, Walsh T, Yamrom B, Yoon S, Krasnitz A, Kendall J,
Leotta A, Pai D, Zhang R, Lee YH, Hicks J, Spence SJ,
Lee AT, Puura K, Lehtimäki T, Ledbetter D, Gregersen
PK, Bregman J, Sutcliffe JS, Jobanputra V, Chung W,
Warburton D, King MC, Skuse D, Geschwind DH,
Gilliam TC, Ye K, Wigler M. Strong association of de
novo copy number mutations with autism. Science.
2007 Apr 20;316(5823):445-9. [PMID: 17363630]
6. Pinto D, Delaby E, Merico D, Barbosa M, Merikangas
A, Klei L, Thiruvahindrapuram B, Xu X, Ziman R,
Wang Z, Vorstman JA, Thompson A, Regan R, Pilorge
M, Pellecchia G, Pagnamenta AT, Oliveira B, Marshall
CR, Magalhaes TR, Lowe JK, Howe JL, Griswold AJ,
Gilbert J, Duketis E, Dombroski BA, De Jonge MV,
Cuccaro M, Crawford EL, Correia CT, Conroy J,
Conceição IC, Chiocchetti AG, Casey JP, Cai G, Cabrol
C, Bolshakova N, Bacchelli E, Anney R, Gallinger S,
Cotterchio M, Casey G, Zwaigenbaum L, Wittemeyer
K, Wing K, Wallace S, van Engeland H, Tryfon A,
Thomson S, Soorya L, Rogé B, Roberts W, Poustka F,
Mouga S, Minshew N, McInnes LA, McGrew SG, Lord
C, Leboyer M, Le Couteur AS, Kolevzon A, Jiménez
González P, Jacob S, Holt R, Guter S, Green J, Green
A, Gillberg C, Fernandez BA, Duque F, Delorme R,
Dawson G, Chaste P, Café C, Brennan S, Bourgeron
T, Bolton PF, Bölte S, Bernier R, Baird G, Bailey AJ,
Anagnostou E, Almeida J, Wijsman EM, Vieland
VJ, Vicente AM, Schellenberg GD, Pericak-Vance
M, Paterson AD, Parr JR, Oliveira G, Nurnberger JI,
Monaco AP, Maestrini E, Klauck SM, Hakonarson H,
Haines JL, Geschwind DH, Freitag CM, Folstein SE,
Ennis S, Coon H, Battaglia A, Szatmari P, Sutcliffe JS,
Hallmayer J, Gill M, Cook EH, Buxbaum JD, Devlin B,
Gallagher L, Betancur C, Scherer SW. Convergence
of genes and cellular pathways dysregulated in
autism spectrum disorders. Am J Hum Genet. 2014
May 1;94(5):677-94. [PMID: 24768552]
7. O'Roak BJ, Vives L, Fu W, Egertson JD, Stanaway IB,
Phelps IG, Carvill G, Kumar A, Lee C, Ankenman K,
Munson J, Hiatt JB, Turner EH, Levy R, O'Day DR,
Krumm N, Coe BP, Martin BK, Borenstein E, Nickerson
DA, Mefford HC, Doherty D, Akey JM, Bernier R,
Eichler EE, Shendure J. Multiplex targeted sequencing
identifies recurrently mutated genes in autism spectrum
disorders. Science. 2012 Dec 21;338(6114):1619-22.
[PMID: 23160955]
8. O'Roak BJ, Vives L, Girirajan S, Karakoc E, Krumm
N, Coe BP, Levy R, Ko A, Lee C, Smith JD, Turner EH,
Stanaway IB, Vernot B, Malig M, Baker C, Reilly B,
Akey JM, Borenstein E, Rieder MJ, Nickerson DA,
Bernier R, Shendure J, Eichler EE. Sporadic autism
exomes reveal a highly interconnected protein
network of de novo mutations. Nature, 485(7397),
246-250. [PMID: 22495309]
9. Neale BM, Kou Y, Liu L, Ma'ayan A, Samocha KE,
Sabo A, Lin CF, Stevens C, Wang LS, Makarov V,
Polak P, Yoon S, Maguire J, Crawford EL, Campbell NG,
Geller ET, Valladares O, Schafer C, Liu H, Zhao T,
Cai G, Lihm J, Dannenfelser R, Jabado O, Peralta Z,
Nagaswamy U, Muzny D, Reid JG, Newsham I, Wu
Y, Lewis L, Han Y, Voight BF, Lim E, Rossin E, Kirby A,
Flannick J, Fromer M, Shakir K, Fennell T, Garimella K,
Banks E, Poplin R, Gabriel S, DePristo M, Wimbish JR,
Boone BE, Levy SE, Betancur C, Sunyaev S, Boerwinkle E,
Buxbaum JD, Cook EH Jr, Devlin B, Gibbs RA, Roeder K,
Schellenberg GD, Sutcliffe JS, Daly MJ. Patterns and
rates of exonic de novo mutations in autism spectrum
disorders. Nature. 2012 Apr 4;485(7397):242-5.
[PMID: 22495311]
10. Sanders SJ, Murtha MT, Gupta AR, Murdoch JD,
Raubeson MJ, Willsey AJ, Ercan-Sencicek AG, DiLullo
NM, Parikshak NN, Stein JL, Walker MF, Ober GT,
Teran NA, Song Y, El-Fishawy P, Murtha RC, Choi M,
Overton JD, Bjornson RD, Carriero NJ, Meyer KA,
126
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Bilguvar K, Mane SM, Sestan N, Lifton RP, Günel M,
Roeder K, Geschwind DH, Devlin B, State MW. De
novo mutations revealed by whole-exome sequencing
are strongly associated with autism. Nature. 2012
Apr 4;485(7397):237-41. [PMID: 22495306]
11. De Rubeis S, He X, Goldberg AP, Poultney CS,
Samocha K, Cicek AE, Kou Y, Liu L, Fromer M, Walker
S, Singh T, Klei L, Kosmicki J, Shih-Chen F, Aleksic B,
Biscaldi M, Bolton PF, Brownfeld JM, Cai J, Campbell
NG, Carracedo A, Chahrour MH, Chiocchetti AG,
Coon H, Crawford EL, Curran SR, Dawson G, Duketis E,
Fernandez BA, Gallagher L, Geller E, Guter SJ, Hill RS,
Ionita-Laza J, Jimenz Gonzalez P, Kilpinen H, Klauck
SM, Kolevzon A, Lee I, Lei I, Lei J, Lehtimäki T, Lin CF,
Ma'ayan A, Marshall CR, McInnes AL, Neale B, Owen
MJ, Ozaki N, Parellada M, Parr JR, Purcell S, Puura K,
Rajagopalan D, Rehnström K, Reichenberg A, Sabo
A, Sachse M, Sanders SJ, Schafer C, Schulte-Rüther
M, Skuse D, Stevens C, Szatmari P, Tammimies K,
Valladares O, Voran A, Li-San W, Weiss LA, Willsey
AJ, Yu TW, Yuen RK; DDD Study; Homozygosity
Mapping Collaborative for Autism; UK10K
Consortium, Cook EH, Freitag CM, Gill M, Hultman
CM, Lehner T, Palotie A, Schellenberg GD, Sklar P,
State MW, Sutcliffe JS, Walsh CA, Scherer SW,
Zwick ME, Barett JC, Cutler DJ, Roeder K, Devlin B,
Daly MJ, Buxbaum JD. Synaptic, transcriptional and
chromatin genes disrupted in autism. Nature. 2014
Nov 13;515(7526):209-15. [PMID: 25363760]
12. Iossifov I, O'Roak BJ, Sanders SJ, Ronemus M, Krumm
N, Levy D, Stessman HA, Witherspoon KT, Vives L,
Patterson KE, Smith JD, Paeper B, Nickerson DA, Dea J,
Dong S, Gonzalez LE, Mandell JD, Mane SM, Murtha
MT, Sullivan CA, Walker MF, Waqar Z, Wei L, Willsey
AJ, Yamrom B, Lee YH, Grabowska E, Dalkic E, Wang
Z, Marks S, Andrews P, Leotta A, Kendall J, Hakker
I, Rosenbaum J, Ma B, Rodgers L, Troge J, Narzisi G,
Yoon S, Schatz MC, Ye K, McCombie WR, Shendure J,
Eichler EE, State MW, Wigler M. The contribution
of de novo coding mutations to autism spectrum
disorder. Nature. 2014 Nov 13;515(7526):216-21.
[PMID: 25363768]
13. Tammimies K, Marshall CR, Walker S, Kaur G,
Thiruvahindrapuram B, Lionel AC, Yuen RK, Uddin
M, Roberts W, Weksberg R, Woodbury-Smith M,
Zwaigenbaum L, Anagnostou E, Wang Z, Wei J,
Howe JL, Gazzellone MJ, Lau L, Sung WW, Whitten
K, Vardy C, Crosbie V, Tsang B, D'Abate L, Tong
WW, Luscombe S, Doyle T, Carter MT, Szatmari P,
Stuckless S, Merico D, Stavropoulos DJ, Scherer
SW, Fernandez BA. Molecular diagnostic yield of
chromosomal microarray analysis and whole-exome
sequencing in children with autism spectrum disorder.
JAMA. 2015 Sep 1;314(9):895-903. [PMID: 26325558]
14. Ronemus M, Iossifov I, Levy D, Wigler M. The role of
de novo mutations in the genetics of autism spectrum
disorders. Nat Rev Genet. 2014 Feb;15(2):133-41.
[PMID: 24430941]
15. Krumm N, Turner TN, Baker C, Vives L, Mohajeri K,
Witherspoon K, Raja A, Coe BP, Stessman HA, He
ZX, Leal SM, Bernier R, Eichler EE. Excess of rare,
inherited truncating mutations in autism. Nat Genet.
2015 Jun;47(6):582-8. [PMID: 25961944]
16. C Yuen RK, Merico D, Bookman M, L Howe J,
Thiruvahindrapuram B, Patel RV, Whitney J, Deflaux
N, Bingham J, Wang Z, Pellecchia G, Buchanan JA,
Walker S, Marshall CR, Uddin M, Zarrei M, Deneault
E, D'Abate L, Chan AJ, Koyanagi S, Paton T, Pereira
SL, Hoang N, Engchuan W, Higginbotham EJ, Ho K,
Lamoureux S, Li W, MacDonald JR, Nalpathamkalam
T, Sung WW, Tsoi FJ, Wei J, Xu L, Tasse AM, Kirby E,
Van Etten W, Twigger S, Roberts W, Drmic I,
Jilderda S, Modi BM, Kellam B, Szego M, Cytrynbaum
C, Weksberg R, Zwaigenbaum L, Woodbury-Smith
127
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
M, Brian J, Senman L, Iaboni A, Doyle-Thomas K,
Thompson A, Chrysler C, Leef J, Savion-Lemieux T,
Smith IM, Liu X, Nicolson R, Seifer V, Fedele A, Cook
EH, Dager S, Estes A, Gallagher L, Malow BA, Parr JR,
Spence SJ, Vorstman J, Frey BJ, Robinson JT, Strug LJ,
Fernandez BA, Elsabbagh M, Carter MT, Hallmayer
J, Knoppers BM, Anagnostou E, Szatmari P, Ring RH,
Glazer D, Pletcher MT, Scherer SW. Whole genome
sequencing resource identifies 18 new candidate
genes for autism spectrum disorder. Nat Neurosci.
2017 Apr;20(4):602-611. [PMID: 28263302]
17. Talkowski ME, Rosenfeld JA, Blumenthal I, Pillalamarri
V, Chiang C, Heilbut A, Ernst C, Hanscom C, Rossin E,
Lindgren AM, Pereira S, Ruderfer D, Kirby A, Ripke S,
Harris DJ, Lee JH, Ha K, Kim HG, Solomon BD, Gropman
AL, Lucente D, Sims K, Ohsumi TK, Borowsky ML,
Loranger S, Quade B, Lage K, Miles J, Wu BL, Shen
Y, Neale B, Shaffer LG, Daly MJ, Morton CC, Gusella
JF. Sequencing chromosomal abnormalities reveals
neurodevelopmental loci that confer risk across
diagnostic boundaries. Cell. 2012 Apr 27;149(3):
525-37. [PMID: 22521361]
18. Leppa VM, Kravitz SN, Martin CL, Andrieux J, Le
Caignec C, Martin-Coignard D, DyBuncio C, Sanders
SJ, Lowe JK, Cantor RM, Geschwind DH. Rare inherited
and de novo CNVs reveal complex contributions
to ASD risk in multiplex families. Am J Hum Genet.
2016 Sep 1;99(3):540-54. [PMID: 27569545]
19. Sanders SJ, He X, Willsey AJ, Ercan-Sencicek AG,
Samocha KE, Cicek AE, Murtha MT, Bal VH, Bishop SL,
Dong S, Goldberg AP, Jinlu C, Keaney JF 3rd, Klei L,
Mandell JD, Moreno-De-Luca D, Poultney CS, Robinson
EB, Smith L, Solli-Nowlan T, Su MY, Teran NA, Walker
MF, Werling DM, Beaudet AL, Cantor RM, Fombonne
E, Geschwind DH, Grice DE, Lord C, Lowe JK,
Mane SM, Martin DM, Morrow EM, Talkowski ME,
Sutcliffe JS, Walsh CA, Yu TW; Autism Sequencing
Consortium, Ledbetter DH, Martin CL, Cook EH,
Buxbaum JD, Daly MJ, Devlin B, Roeder K, State MW.
Insights into autism spectrum disorder genomic
architecture and biology from 71 risk loci. Neuron.
2015 Sep 23;87(6):1215-33. [PMID: 26402605]
20. Yuen RK, Thiruvahindrapuram B, Merico D, Walker S,
Tammimies K, Hoang N, Chrysler C, Nalpathamkalam T,
Pellecchia G, Liu Y, Gazzellone MJ, D'Abate L, Deneault
E, Howe JL, Liu RS, Thompson A, Zarrei M, Uddin
M, Marshall CR, Ring RH, Zwaigenbaum L, Ray PN,
Weksberg R, Carter MT, Fernandez BA, Roberts W,
Szatmari P, Scherer SW. Whole-genome sequencing
of quartet families with autism spectrum disorder.
Nat Med. 2015 Feb;21(2):185-91. [PMID: 25621899]
21. Constantino JN, Todorov A, Hilton C, Law P, Zhang
Y, Molloy E, Fitzgerald R, Geschwind D. Autism
recurrence in half siblings: strong support for genetic
mechanisms of transmission in ASD. Mol Psychiatry.
2013 Feb;18(2):137-8. [PMID: 22371046]
22. Risch N, Hoffmann TJ, Anderson M, Croen LA,
Grether JK, Windham GC. Familial recurrence of
autism spectrum disorder: evaluating genetic and
environmental contributions. Am J Psychiatry.
2014 Nov 1;171(11):1206-13. [PMID: 24969362]
23. Sandin S, Lichtenstein P, Kuja-Halkola R, Larsson
H, Hultman CM, Reichenberg A. The familial risk of
autism. JAMA. 2014 May 7;311(17):1770-7.
[PMID: 24794370]
24. Folstein S, Rutter M. Infantile autism: a genetic study
of 21 twin pairs. J Child Psychol Psychiatry. 1977
Sep;18(4):297-321. [PMID: 562353]
128
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
25. Hallmayer J, Cleveland S, Torres A, Phillips J, Cohen
B, Torigoe T, Miller J, Fedele A, Collins J, Smith K,
Lotspeich L, Croen LA, Ozonoff S, Lajonchere C,
Grether JK, Risch N. Genetic heritability and shared
environmental factors among twin pairs with autism.
Arch Gen Psychiatry. 2011 Nov;68(11):1095-102.
[PMID: 21727249]
26. Colvert E, Tick B, McEwen F, Stewart C, Curran SR,
Woodhouse E, Gillan N, Hallett V, Lietz S, Garnett T,
Ronald A, Plomin R, Rijsdijk F, Happé F, Bolton P.
Heritability of autism spectrum disorder in a UK
population-based twin sample. JAMA Psychiatry.
2015 May;72(5):415-23. [PMID: 25738232]
27. Tick B, Colvert E, McEwen F, Stewart C, Woodhouse
E, Gillan N, Hallett V, Lietz S, Garnett T, Simonoff E,
Ronald A, Bolton P, Happé F, Rijsdijk F. Autism
spectrum disorders and other mental health problems:
exploring etiological overlaps and phenotypic causal
associations. J Am Acad Child Adolesc Psychiatry. 2016
Feb;55(2):106-13.e4. [PMID: 26802777]
28. Bourgeron T. Current knowledge on the genetics of
autism and propositions for future research. C R Biol.
2016 Jul-Aug;339(7-8):300-7. [PMID: 27289453]
29. Geschwind DH, Flint J. Genetics and genomics
of psychiatric disease. Science. 2015 Sep 25;
349(6255):1489-94. [PMID: 26404826]
30. Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A,
Day FR, Loh PR; ReproGen Consortium; Psychiatric
Genomics Consortium; Genetic Consortium for
Anorexia Nervosa of the Wellcome Trust Case
Control Consortium 3, Duncan L, Perry JR, Patterson
N, Robinson EB, Daly MJ, Price AL, Neale BM. An
atlas of genetic correlations across human diseases
and traits. Nat Genet. 2015 Nov;47(11):1236-41.
[PMID: 26414676]
31. Bulik-Sullivan BK, Loh PR, Finucane HK, Ripke S,
Yang J; Schizophrenia Working Group of the Psychiatric
Genomics Consortium, Patterson N, Daly MJ, Price
AL, Neale BM. LD Score regression distinguishes
confounding from polygenicity in genome-wide
association studies. Nat Genet. 2015 Mar;47(3):291-5.
[PMID: 25642630]
32. Gaugler T, Klei L, Sanders SJ, Bodea CA, Goldberg AP,
Lee AB, Mahajan M, Manaa D, Pawitan Y, Reichert J,
Ripke S, Sandin S, Sklar P, Svantesson O, Reichenberg
A, Hultman CM, Devlin B, Roeder K, Buxbaum JD.
Most genetic risk for autism resides with common
variation. Nat Genet. 2014 Aug;46(8):881-5.
[PMID: 25038753]
33. Stein JL, Parikshak NN, Geschwind DH. Rare inherited
variation in autism: beginning to see the forest and
a few trees. Neuron. 2013 Jan 23;77(2):209-11.
[PMID: 23352155]
34.
Autism and Developmental Disabilities Monitoring
Network Surveillance Year 2008 Principal Investigators;
Centers for Disease Control and Prevention.
Prevalence of autism spectrum disorders–Autism
and Developmental Disabilities Monitoring Network,
14 sites, United States, 2008. MMWR Surveill Summ.
2012 Mar 30;61(3):1-19. [PMID: 22456193]
35. Duvekot J, van der Ende J, Verhulst FC, Slappendel
G, van Daalen E, Maras A, Greaves-Lord K. Factors
influencing the probability of a diagnosis of autism
spectrum disorder in girls versus boys. Autism.
2017 Aug;21(6):646-658. [PMID: 27940569]
36. Werling DM, Geschwind DH. Understanding sex bias
in autism spectrum disorder. Proc Natl Acad Sci U S A.
2013 Mar 26;110(13):4868-9. [PMID: 23476067]
129
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
37. Van Wijngaarden-Cremers PJ, van Eeten E, Groen
WB, Van Deurzen PA, Oosterling IJ, Van der Gaag
RJ. Gender and age differences in the core triad
of impairments in autism spectrum disorders: a
systematic review and meta-analysis. J Autism Dev
Disord. 2014 Mar;44(3):627-35. [PMID: 23989936]
38. Werling DM, Geschwind DH. Recurrence rates
provide evidence for sex-differential, familial genetic
liability for autism spectrum disorders in multiplex
families and twins. Mol Autism. 2015 May 13;6:27.
[PMID: 25973164]
39. Baron-Cohen S. The extreme male brain theory of
autism. Trends Cogn Sci. 2002 Jun 1;6(6):248-254.
[PMID: 12039606]
40. Baron-Cohen S, Knickmeyer RC, Belmonte MK. Sex
differences in the brain: implications for explaining
autism. Science. 2005 Nov 4;310(5749):819-23.
[PMID: 16272115]
41. Robinson EB, Lichtenstein P, Anckarsäter H, Happé F,
Ronald A. Examining and interpreting the female
protective effect against autistic behavior. Proc
Natl Acad Sci U S A. 2013 Mar 26;110(13):5258-62.
[PMID: 23431162]
42. Jacquemont S, Coe BP, Hersch M, Duyzend MH,
Krumm N, Bergmann S, Beckmann JS, Rosenfeld JA,
Eichler EE. A higher mutational burden in females
supports a "female protective model" in
neurodevelopmental disorders. Am J Hum Genet.
2014 Mar 6;94(3):415-25. [PMID: 24581740]
43. Werling DM, Parikshak NN, Geschwind DH.
Gene expression in human brain implicates sexually
dimorphic pathways in autism spectrum disorders.
Nat Commun. 2016 Feb 19;7:10717. [PMID: 26892004]
44. Cross-Disorder Group of the Psychiatric
Genomics Consortium. Identification of risk loci
with shared effects on five major psychiatric
disorders: a genome-wide analysis. Lancet. 2013
Apr 20;381(9875):1371-9. [PMID: 23453885]
45. Cross-Disorder Group of the Psychiatric Genomics
Consortium, Lee SH, Ripke S, Neale BM, Faraone SV,
Purcell SM, Perlis RH, Mowry BJ, Thapar A, Goddard
ME, Witte JS, Absher D, Agartz I, Akil H, Amin F,
Andreassen OA, Anjorin A, Anney R, Anttila V, Arking
DE, Asherson P, Azevedo MH, Backlund L, Badner
JA, Bailey AJ, Banaschewski T, Barchas JD, Barnes
MR, Barrett TB, Bass N, Battaglia A, Bauer M, Bayés
M, Bellivier F, Bergen SE, Berrettini W, Betancur
C, Bettecken T, Biederman J, Binder EB, Black DW,
Blackwood DH, Bloss CS, Boehnke M, Boomsma DI,
Breen G, Breuer R, Bruggeman R, Cormican P, Buccola
NG, Buitelaar JK, Bunney WE, Buxbaum JD, Byerley
WF, Byrne EM, Caesar S, Cahn W, Cantor RM, Casas
M, Chakravarti A, Chambert K, Choudhury K, Cichon
S, Cloninger CR, Collier DA, Cook EH, Coon H,
Cormand B, Corvin A, Coryell WH, Craig DW, Craig
IW, Crosbie J, Cuccaro ML, Curtis D, Czamara D,
Datta S, Dawson G, Day R, De Geus EJ, Degenhardt F,
Djurovic S, Donohoe GJ, Doyle AE, Duan J, Dudbridge
F, Duketis E, Ebstein RP, Edenberg HJ, Elia J, Ennis S,
Etain B, Fanous A, Farmer AE, Ferrier IN, Flickinger
M, Fombonne E, Foroud T, Frank J, Franke B, Fraser C,
Freedman R, Freimer NB, Freitag CM, Friedl M, Frisén
L, Gallagher L, Gejman PV, Georgieva L, Gershon ES,
Geschwind DH, Giegling I, Gill M, Gordon SD,
Gordon-Smith K, Green EK, Greenwood TA, Grice
DE, Gross M, Grozeva D, Guan W, Gurling H, De
Haan L, Haines JL, Hakonarson H, Hallmayer J,
Hamilton SP, Hamshere ML, Hansen TF, Hartmann
AM, Hautzinger M, Heath AC, Henders AK, Herms S,
Hickie IB, Hipolito M, Hoefels S, Holmans PA, Holsboer
F, Hoogendijk WJ, Hottenga JJ, Hultman CM, Hus V,
130
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Ingason A, Ising M, Jamain S, Jones EG, Jones I, Jones
L, Tzeng JY, Kähler AK, Kahn RS, Kandaswamy R,
Keller MC, Kennedy JL, Kenny E, Kent L, Kim Y, Kirov
GK, Klauck SM, Klei L, Knowles JA, Kohli MA, Koller
DL, Konte B, Korszun A, Krabbendam L, Krasucki R,
Kuntsi J, Kwan P, Landén M, Långström N, Lathrop M,
Lawrence J, Lawson WB, Leboyer M, Ledbetter DH,
Lee PH, Lencz T, Lesch KP, Levinson DF, Lewis CM, Li
J, Lichtenstein P, Lieberman JA, Lin DY, Linszen DH,
Liu C, Lohoff FW, Loo SK, Lord C, Lowe JK, Lucae S,
MacIntyre DJ, Madden PA, Maestrini E, Magnusson
PK, Mahon PB, Maier W, Malhotra AK, Mane SM,
Martin CL, Martin NG, Mattheisen M, Matthews K,
Mattingsdal M, McCarroll SA, McGhee KA, McGough
JJ, McGrath PJ, McGuffin P, McInnis MG, McIntosh
A, McKinney R, McLean AW, McMahon FJ, McMahon
WM, McQuillin A, Medeiros H, Medland SE, Meier
S, Melle I, Meng F, Meyer J, Middeldorp CM, Middleton
L, Milanova V, Miranda A, Monaco AP, Montgomery
GW, Moran JL, Moreno-De-Luca D, Morken G,
Morris DW, Morrow EM, Moskvina V, Muglia P,
Mühleisen TW, Muir WJ, Müller-Myhsok B, Murtha
M, Myers RM, Myin-Germeys I, Neale MC, Nelson
SF, Nievergelt CM, Nikolov I, Nimgaonkar V, Nolen
WA, Nöthen MM, Nurnberger JI, Nwulia EA, Nyholt
DR, O'Dushlaine C, Oades RD, Olincy A, Oliveira G,
Olsen L, Ophoff RA, Osby U, Owen MJ, Palotie A,
Parr JR, Paterson AD, Pato CN, Pato MT, Penninx BW,
Pergadia ML, Pericak-Vance MA, Pickard BS, Pimm J,
Piven J, Posthuma D, Potash JB, Poustka F, Propping
P, Puri V, Quested DJ, Quinn EM, Ramos-Quiroga JA,
Rasmussen HB, Raychaudhuri S, Rehnström K, Reif
A, Ribasés M, Rice JP, Rietschel M, Roeder K, Roeyers
H, Rossin L, Rothenberger A, Rouleau G, Ruderfer D,
Rujescu D, Sanders AR, Sanders SJ, Santangelo SL,
Sergeant JA, Schachar R, Schalling M, Schatzberg
AF, Scheftner WA, Schellenberg GD, Scherer SW,
Schork NJ, Schulze TG, Schumacher J, Schwarz
M, Scolnick E, Scott LJ, Shi J, Shilling PD, Shyn SI,
Silverman JM, Slager SL, Smalley SL, Smit JH, Smith
EN, Sonuga-Barke EJ, St Clair D, State M, Steffens
M, Steinhausen HC, Strauss JS, Strohmaier J, Stroup
TS, Sutcliffe JS, Szatmari P, Szelinger S, Thirumalai
S, Thompson RC, Todorov AA, Tozzi F, Treutlein J,
Uhr M, van den Oord EJ, Van Grootheest G, Van
Os J, Vicente AM, Vieland VJ, Vincent JB, Visscher
PM, Walsh CA, Wassink TH, Watson SJ, Weissman
MM, Werge T, Wienker TF, Wijsman EM, Willemsen
G, Williams N, Willsey AJ, Witt SH, Xu W, Young
AH, Yu TW, Zammit S, Zandi PP, Zhang P, Zitman
FG, Zöllner S, Devlin B, Kelsoe JR, Sklar P, Daly MJ,
O'Donovan MC, Craddock N, Sullivan PF, Smoller JW,
Kendler KS, Wray NR; International Inflammatory
Bowel Disease Genetics Consortium (IIBDGC).
Genetic relationship between five psychiatric disorders
estimated from genome-wide SNPs. Nat Genet.
2013 Sep;45(9):984-94. [PMID: 23933821]
46. Autism Spectrum Disorders Working Group of The
Psychiatric Genomics Consortium. Meta-analysis of
GWAS of over 16,000 individuals with autism spectrum
disorder highlights a novel locus at 10q24.32 and a
significant overlap with schizophrenia. Mol Autism.
2017 May 22;8:21. [PMID: 28540026]
47. Jokiranta-Olkoniemi E, Cheslack-Postava K, Sucksdorff
D, Suominen A, Gyllenberg D, Chudal R, Leivonen S,
Gissler M, Brown AS, Sourander A. Risk of psychiatric
and neurodevelopmental disorders among siblings of
probands with autism spectrum disorders. JAMA
Psychiatry. 2016 Jun 1;73(6):622-9. [PMID: 27145529]
48. Gillberg C. Chromosomal disorders and autism.
J Autism Dev Disord. 1998 Oct;28(5):415-25.
[PMID: 9813777]
49. Kielinen M, Rantala H, Timonen E, Linna SL, Moilanen I.
Associated medical disorders and disabilities in children
with autistic disorder: a population-based study.
Autism. 2004 Mar;8(1):49-60. [PMID: 15070547]
131
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
50. Fine SE, Weissman A, Gerdes M, Pinto-Martin J,
Zackai EH, McDonald-McGinn DM, Emanuel BS.
Autism spectrum disorders and symptoms in children
with molecularly confirmed 22q11.2 deletion syndrome.
J Autism Dev Disord. 2005 Aug;35(4):461-70.
[PMID: 16134031]
51. Gillberg IC, Gillberg C, Ahlsén G. Autistic behaviour
and attention deficits in tuberous sclerosis: a
population-based study. Dev Med Child Neurol. 1994
Jan;36(1):50-6. [PMID: 8132114]
52. Clarke TK, Lupton MK, Fernandez-Pujals AM, Starr J,
Davies G, Cox S, Pattie A, Liewald DC, Hall LS,
MacIntyre DJ, Smith BH, Hocking LJ, Padmanabhan S,
Thomson PA, Hayward C, Hansell NK, Montgomery
GW, Medland SE, Martin NG, Wright MJ, Porteous
DJ, Deary IJ, McIntosh AM. Common polygenic risk
for autism spectrum disorder (ASD) is associated
with cognitive ability in the general population. Mol
Psychiatry. 2016 Mar;21(3):419-25. [PMID: 25754080]
53. Moreno-De-Luca D, Sanders SJ, Willsey AJ, Mulle
JG, Lowe JK, Geschwind DH, State MW, Martin CL,
Ledbetter DH. Using large clinical data sets to infer
pathogenicity for rare copy number variants in autism
cohorts. Mol Psychiatry. 2013 Oct;18(10):1090-5.
[PMID: 23044707]
54. Geschwind DH. Advances in autism. Annu Rev Med.
2009;60:367-80. [PMID: 19630577]
55. Jeste SS, Geschwind DH. Disentangling the
heterogeneity of autism spectrum disorder through
genetic findings. Nat Rev Neurol. 2014 Feb;10(2):
74-81. [PMID: 24468882]
56. Laumonnier F, Bonnet-Brilhault F, Gomot M, Blanc R,
David A, Moizard MP, Raynaud M, Ronce N,
Lemonnier E, Calvas P, Laudier B, Chelly J, Fryns JP,
Ropers HH, Hamel BC, Andres C, Barthélémy C,
Moraine C, Briault S. X-linked mental retardation and
autism are associated with a mutation in the NLGN4
gene, a member of the neuroligin family. Am J Hum
Genet. 2004 Mar;74(3):552-7. [PMID: 14963808]
57. Bucan M, Abrahams BS, Wang K, Glessner JT,
Herman EI, Sonnenblick LI, Alvarez Retuerto AI,
Imielinski M, Hadley D, Bradfield JP, Kim C, Gidaya
NB, Lindquist I, Hutman T, Sigman M, Kustanovich
V, Lajonchere CM, Singleton A, Kim J, Wassink TH,
McMahon WM, Owley T, Sweeney JA, Coon H,
Nurnberger JI, Li M, Cantor RM, Minshew NJ, Sutcliffe
JS, Cook EH, Dawson G, Buxbaum JD, Grant SF,
Schellenberg GD, Geschwind DH, Hakonarson H.
Genome-wide analyses of exonic copy number
variants in a family-based study point to novel
autism susceptibility genes. PLoS Genet. 2009
Jun;5(6):e1000536. [PMID: 19557195]
58. Hoeffding LK, Trabjerg BB, Olsen L, Mazin W, Sparsø
T, Vangkilde A, Mortensen PB, Pedersen CB, Werge
T. Risk of psychiatric disorders among individuals
with the 22q11.2 deletion or duplication: a Danish
nationwide, register-based study. JAMA Psychiatry.
2017 Mar 1;74(3):282-290. [PMID: 28114601]
59. Kim HG, Kishikawa S, Higgins AW, Seong IS, Donovan
DJ, Shen Y, Lally E, Weiss LA, Najm J, Kutsche K,
Descartes M, Holt L, Braddock S, Troxell R, Kaplan
L, Volkmar F, Klin A, Tsatsanis K, Harris DJ, Noens
I, Pauls DL, Daly MJ, MacDonald ME, Morton CC,
Quade BJ, Gusella JF. Disruption of neurexin 1
associated with autism spectrum disorder. Am J Hum
Genet. 2008 Jan;82(1):199-207. [PMID: 18179900]
60. Marshall CR, Noor A, Vincent JB, Lionel AC, Feuk
L, Skaug J, Shago M, Moessner R, Pinto D, Ren Y,
Thiruvahindrapduram B, Fiebig A, Schreiber S,
Friedman J, Ketelaars CE, Vos YJ, Ficicioglu C,
132
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Kirkpatrick S, Nicolson R, Sloman L, Summers A,
Gibbons CA, Teebi A, Chitayat D, Weksberg R,
Thompson A, Vardy C, Crosbie V, Luscombe S, Baatjes
R, Zwaigenbaum L, Roberts W, Fernandez B, Szatmari
P, Scherer SW. Structural variation of chromosomes
in autism spectrum disorder. Am J Hum Genet. 2008
Feb;82(2):477-88. [PMID: 18252227]
61. Rujescu D, Ingason A, Cichon S, Pietiläinen OP,
Barnes MR, Toulopoulou T, Picchioni M, Vassos E,
Ettinger U, Bramon E, Murray R, Ruggeri M, Tosato S,
Bonetto C, Steinberg S, Sigurdsson E, Sigmundsson
T, Petursson H, Gylfason A, Olason PI, Hardarsson G,
Jonsdottir GA, Gustafsson O, Fossdal R, Giegling
I, Möller HJ, Hartmann AM, Hoffmann P, Crombie
C, Fraser G, Walker N, Lonnqvist J, Suvisaari J,
Tuulio-Henriksson A, Djurovic S, Melle I, Andreassen
OA, Hansen T, Werge T, Kiemeney LA, Franke B,
Veltman J, Buizer-Voskamp JE; GROUP Investigators,
Sabatti C, Ophoff RA, Rietschel M, Nöthen MM,
Stefansson K, Peltonen L, St Clair D, Stefansson H,
Collier DA. Disruption of the neurexin 1 gene is
associated with schizophrenia. Hum Mol Genet. 2009
Mar 1;18(5):988-96. [PMID: 18945720]
62. Stessman HA, Xiong B, Coe BP, Wang T, Hoekzema K,
Fenckova M, Kvarnung M, Gerdts J, Trinh S, Cosemans
N, Vives L, Lin J, Turner TN, Santen G, Ruivenkamp C,
Kriek M, van Haeringen A, Aten E, Friend K, Liebelt
J, Barnett C, Haan E, Shaw M, Gecz J, Anderlid BM,
Nordgren A, Lindstrand A, Schwartz C, Kooy RF,
Vandeweyer G, Helsmoortel C, Romano C, Alberti A,
Vinci M, Avola E, Giusto S, Courchesne E, Pramparo
T, Pierce K, Nalabolu S, Amaral DG, Scheffer IE,
Delatycki MB, Lockhart PJ, Hormozdiari F, Harich B,
Castells-Nobau A, Xia K, Peeters H, Nordenskjöld M,
Schenck A, Bernier RA, Eichler EE. Targeted sequencing
identifies 91 neurodevelopmental-disorder risk genes
with autism and developmental-disability biases. Nat
Genet. 2017 Apr;49(4):515-526. [PMID: 28191889]
63. Parikshak NN, Luo R, Zhang A, Won H, Lowe JK,
Chandran V, Horvath S, Geschwind DH. Integrative
functional genomic analyses implicate specific
molecular pathways and circuits in autism. Cell. 2013
Nov 21;155(5):1008-21. [PMID: 24267887]
64. Schaefer GB, Mendelsohn NJ; Professional Practice
and Guidelines Committee. Clinical genetics
evaluation in identifying the etiology of autism
spectrum disorders. Genet Med. 2008 Apr;10(4):
301-5. [PMID: 18414214]
65. Schaefer GB, Mendelsohn NJ; Professional Practice
and Guidelines Committee. Clinical genetics
evaluation in identifying the etiology of autism
spectrum disorders: 2013 guideline revisions. Genet
Med. 2013 May;15(5):399-407. [PMID: 23519317]
66. Fogel BL, Lee H, Strom SP, Deignan JL, Nelson SF.
Clinical exome sequencing in neurogenetic and
neuropsychiatric disorders. Ann N Y Acad Sci. 2016
Feb;1366(1):49-60. [PMID: 26250888]
67. Lee H, Deignan JL, Dorrani N, Strom SP, Kantarci S,
Quintero-Rivera F, Das K, Toy T, Harry B, Yourshaw
M, Fox M, Fogel BL, Martinez-Agosto JA, Wong DA,
Chang VY, Shieh PB, Palmer CG, Dipple KM, Grody
WW, Vilain E, Nelson SF. Clinical exome sequencing
for genetic identification of rare Mendelian
disorders. JAMA. 2014 Nov 12;312(18):1880-7.
[PMID: 25326637]
68. Reiff M, Bugos E, Giarelli E, Bernhardt BA, Spinner
NB, Sankar PL, Mulchandani S. "Set in stone" or "ray
of hope": parents' beliefs about cause and prognosis
after genomic testing of children diagnosed with
ASD. J Autism Dev Disord. 2017 May;47(5):1453-
1463. [PMID: 28229350]
133
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
69. Xu L, Mitchell LC, Richman AR, Clawson K. What
do parents think about chromosomal microarray
testing? a qualitative report from parents of children
with autism spectrum disorders. Autism Res Treat.
2016;2016:6852539. [PMID: 27413549]
70. Chess S. Autism in children with congenital rubella.
J Autism Child Schizophr. 1971 Jan-Mar;1(1):33-47.
[PMID: 5172438]
71. Chess S. Follow-up report on autism in congenital
rubella. J Autism Child Schizophr. 1977 Mar;7(1):69-81.
[PMID: 576606]
72. Strömland K, Nordin V, Miller M, Akerström B, Gillberg
C. Autism in thalidomide embryopathy: a population
study. Dev Med Child Neurol. Dev Med Child Neurol.
1994 Apr;36(4):351-6. [PMID: 8157157]
73. Willsey AJ, Sanders SJ, Li M, Dong S, Tebbenkamp
AT, Muhle RA, Reilly SK, Lin L, Fertuzinhos S, Miller
JA, Murtha MT, Bichsel C, Niu W, Cotney J,
Ercan-Sencicek AG, Gockley J, Gupta AR, Han W,
He X, Hoffman EJ, Klei L, Lei J, Liu W, Liu L, Lu C,
Xu X, Zhu Y, Mane SM, Lein ES, Wei L, Noonan JP,
Roeder K, Devlin B, Sestan N, State MW.
Coexpression networks implicate human midfetal
deep cortical projection neurons in the pathogenesis
of autism. Cell. 2013 Nov 21;155(5):997-1007.
[PMID: 24267886]
74. Stoner R, Chow ML, Boyle MP, Sunkin SM, Mouton
PR, Roy S, Wynshaw-Boris A, Colamarino SA, Lein
ES, Courchesne E. Patches of disorganization in the
neocortex of children with autism. N Engl J Med.
2014 Mar 27;370(13):1209-1219. [PMID: 24670167]
75. Voineagu I, Wang X, Johnston P, Lowe JK, Tian
Y, Horvath S, Mill J, Cantor RM, Blencowe BJ,
Geschwind DH. Transcriptomic analysis of autistic
brain reveals convergent molecular pathology. Nature.
2011 May 25;474(7351):380-4. [PMID: 21614001]
76. Atladóttir HO, Thorsen P, Østergaard L, Schendel DE,
Lemcke S, Abdallah M, Parner ET. Maternal infection
requiring hospitalization during pregnancy and
autism spectrum disorders. J Autism Dev Disord. 2010
Dec;40(12):1423-30. [PMID: 20414802]
77. Schmidt RJ, Lyall K, Hertz-Picciotto I. Environment
and autism: current state of the science. Cut Edge
Psychiatry Pract. 2014 Summer;1(4):21-38.
[PMID: 27453776]
78. Rodier PM, Ingram JL, Tisdale B, Croog VJ. Linking
etiologies in humans and animal models: studies of
autism. Reprod. Toxicol. 1997 Jun; 11(2-3):417–422.
[PMID: 9100317]
79. Miyazaki K, Narita N, Narita M. Maternal
administration of thalidomide or valproic acid
causes abnormal serotonergic neurons in the
offspring: implication for pathogenesis of autism.
Int. J. Dev. Neurosci. Off. J. Int. Soc. Dev. Neurosci.
2005 May; 23(2-3):287297. [PMID: 15749253]
80. Christensen J, Grønborg TK, Sørensen MJ, Schendel
D, Parner ET, Pedersen LH, Vestergaard M. Prenatal
valproate exposure and risk of autism spectrum
disorders and childhood autism. JAMA. 2013 Apr;
309(16):1696. [PMID: 23613074]
81. Johnson S, Hollis C, Kochhar P, Hennessy E, Wolke D
Marlow N. Psychiatric disorders in extremely preterm
children: longitudinal finding at age 11 years in the
EPICure study. J. Am. Acad. Child Adolesc. Psychiatry.
2010 May; 49(5):453–463.e1. [PMID: 20431465]
134
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
82. Limperopoulos C, Bassan H, Sullivan NR, Soul JS,
Roberston RL Jr, Moore M, Ringer SA, Volpe JJ, du
Plessis AJ. Positive screening for autism in ex-preterm
infants: prevalence and risk factors. Pediatrics. 2008
Apr; 121(4):758–765. [PMID: 18381541]
83. Pinto-Martin JA, Levy SE, Feldman JF, Lorenz JM,
Paneth N, Whitaker AH. Prevalence of autism
spectrum disorder in adolescents born weighing
<2000 grams. Pediatrics. 2011 Oct; 128(5):883–891.
[PMID: 22007018]
84. Schieve LA, Rice C, Devine O, Maenner MJ, Lee LC,
Fitzgerald R, Wingate MS, Schendel D, Pettygrove S,
van Naarden Braun K, Durkin M. Have secular
changes in perinatal risk factors contributed to the
recent autism prevalence increase? development
and application of a mathematical assessment
model. Ann. Epidemiol. 2011 Dec; 21(12):930–945.
[PMID: 22000328]
85. Sandin S, Hultman CM, Kolevzon A, Gross R, MacCabe
JH, Reichenberg A. Advancing maternal age is
associated with increasing risk for autism: a review
and meta-analysis. J. Am. Acad. Child Adolesc. Psychiatry.
2012 May; 51(5):477–486.e1. [PMID: 22525954]
86. Hultman CM, Sandin S, Levine SZ, Lichtenstein P,
Reichenberg A. Advancing paternal age and risk of
autism: new evidence from a population-based
study and a meta-analysis of epidemiological
studies. Mol. Psychiatry. 2011 Dec; 16(12):1203–1212.
[PMID: 21116277]
87. Puleo CM, Schmeidler J, Reichenberg A, Kolevzon A,
Soorya LV, Buxbaum JD, Silverman JM. Advancing
paternal age and simplex autism. Autism. 2012 Jul;
16(4):367–380. [PMID: 22180389]
88. Reichenberg A, Gross R, Sandin S, Susser ES.
Advancing paternal and maternal age are both
important for autism risk. Am. J. Public Health.
2010 May; 100(5):772–773; author reply 773.
[PMID: 20299637]
89. Cheslack-Postava K, Liu K, Bearman PS. Closely
spaced pregnancies are associated with increased
odds of autism in California sibling births. Pediatrics.
2011 Feb; 127(2):246–253. [PMID: 21220394]
90. Gunnes N, Suren P, Bresnahan M, Hornig M, Lie KK,
Lipkin WI, Magnus P, Nilsen RM, Reichborn-Kjennerud
T, Scholberg S, Susser ES, Oyen AS, Stoltenberg C.
Interpregnancy interval and risk of autistic disorder.
Epidemiology. 2013 Nov; 24(6):906–912.
[PMID: 24045716]
91. Surén P, Susser E, Stoltenberg C. Maternal folic acid
supplementation and risk of autism–reply. JAMA.
2013 Jun 5;309(21):2208. [PMID: 23736721]
92. Schmidt RJ, Tancredi DJ, Ozonoff S, Hansen RL, Hartiala
J, Allayee H, Schmidt LC, Tassone F, Hertz-Picciotto
I. Maternal periconceptional folic acid intake and risk
of autism spectrum disorders and developmental
delay in the CHARGE (CHildhood Autism Risks from
Genetics and Environment) case-control study. Am J
Clin Nutr. 2012 Jul;96(1):80-9. [PMID: 22648721]
93. Kalkbrenner AE, Windham GC, Serre ML, Akita Y,
Wang X, Hoffman K, Thayer BP, Daniels JL. Particulate
matter exposure, prenatal and postnatal windows
of susceptibility, and autism spectrum
disorders. Epidemiology. 2015 Jan;26(1):30-42.
[PMID: 25286049]
94. Raz R, Roberts AL, Lyall K, Hart JE, Just AC, Laden F,
Weisskopf MG. Autism spectrum disorder and
particulate matter air pollution before, during, and
135
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
after pregnancy: a nested case-control analysis
within the Nurses' Health Study II Cohort. Environ
Health Perspect. 2015 Mar;123(3):264-70.
[PMID: 25522338]
95. Bennett D, Bellinger DC, Birnbaum LS, Bradman
A, Chen A, Cory-Slechta DA, Engel SM, Fallin MD,
Halladay A, Hauser R, Hertz-Picciotto I, Kwiatkowski
CF, Lanphear BP, Marquez E, Marty M, McPartland J,
Newschaffer CJ, Payne-Sturges D, Patisaul HB, Perera
FP, Ritz B, Sass J, Schantz SL, Webster TF, Whyatt
RM, Woodruff TJ, Zoeller RT, Anderko L, Campbell C,
Conry JA, DeNicola N, Gould RM, Hirtz D, Huffling K,
Landrigan PJ, Lavin A, Miller M, Mitchell MA, Rubin
L, Schettler T, Tran HL, Acosta A, Brody C, Miller E,
Miller P, Swanson M, Witherspoon NO; American
College of Obstetricians and Gynecologists (ACOG);
Child Neurology Society; Endocrine Society;
International Neurotoxicology Association; International
Society for Children’s Health and the Environment;
International Society for Environmental Epidemiology;
National Council of Asian Pacific Islander Physicians;
National Hispanic Medical Association; National
Medical Association. Project TENDR: targeting
environmental neuro-developmental risks the TENDR
consensus statement. Environ Health Perspect. 2016
Jul 1;124(7):A118-22. [PMID: 27479987]
96. Lyall K, Croen L, Daniels J, Fallin MD, Ladd-Acosta
C, Lee BK, Park BY, Snyder NW, Schendel D, Volk
H, Windham GC, Newschaffer C. The changing
epidemiology of autism spectrum disorders. Annu
Rev Public Health. 2017 Mar 20;38:81-102.
[PMID: 28068486]
97. Gee GC, Payne-Sturges DC. Environmental health
disparities: a framework integrating psychosocial
and environmental concepts. Environ Health Perspect.
2004 Dec;112(17):1645-53. [PMID: 15579407]
98. Evans GW, Kantrowitz E. Socioeconomic status and
health: the potential role of environmental risk
exposure. Annu Rev Public Health. 2002;23:303-31.
[PMID: 11910065]
99. Adamkiewicz G, Zota AR, Fabian MP, Chahine T,
Julien R, Spengler JD, Levy JI. Moving environmental
justice indoors: understanding structural influences
on residential exposure patterns in low-income
communities. Am J Public Health. 2011 Dec;101 Suppl
1:S238-45. [PMID: 21836112]
100. Christensen DL, Bilder DA, Zahorodny W, Pettygrove
S, Durkin MS, Fitzgerald RT, Rice C, Kurzius-Spencer M,
Baio J, Yeargin-Allsopp M. Prevalence and
characteristics of autism spectrum disorder among
4-year-old children in the Autism and Developmental
Disabilities Monitoring Network. J Dev Behav Pediatr.
2016 Jan;37(1):1-8. [PMID: 26651088]
101. Cui Y, Balshaw DM, Kwok RK, Thompson CL, Collman
GW, Birnbaum LS. The exposome: embracing the
complexity for discovery in environmental health.
Environ Health Perspect. 2016 Aug 1;124(8):A137-40.
[PMID: 27479988]
102. Stingone JA, Buck Louis GM, Nakayama SF, Vermeulen
RC, Kwok RK, Cui Y, Balshaw DM, Teitelbaum SL.
Toward greater implementation of the exposome
research paradigm within environmental epidemiology.
Annu Rev Public Health. 2017 Mar 20;38:315-327.
[PMID: 28125387]
103. Wild CP. The exposome: from concept to utility. Int J
Epidemiol. 2012 Feb;41(1):24-32. [PMID: 22296988]
104. Rappaport SM. Implications of the exposome for
exposure science. J Expo Sci Environ Epidemiol. 2011
Jan-Feb;21(1):5-9. [PMID: 21081972]
136
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
105. Ladd-Acosta C, Shu C, Lee BK, Gidaya N, Singer A,
Schieve LA, Schendel DE, Jones N, Daniels JL, Windham
GC, Newschaffer CJ, Croen LA, Feinberg AP, Daniele
Fallin M. Presence of an epigenetic signature of prenatal
cigarette smoke exposure in childhood. Environ Res.
2016 Jan;144(Pt A):139-148. [PMID: 26610292]
106. Houten SM, Chen J, Belpoggi F, Manservisi F,
Sánchez-Guijo A, Wudy SA, Teitelbaum SL. Changes
in the metabolome in response to low-dose exposure
to environmental chemicals used in personal care
products during different windows of susceptibility.
PLoS One. 2016 Jul 28;11(7):e0159919.
[PMID: 27467775]
107. Marsillach J, Costa LG, Furlong CE. Paraoxonase-1
and early-life environmental exposures. Ann Glob
Health. 2016 Jan-Feb;82(1):100-10. [PMID: 27325068].
108. Mazina V, Gerdts J, Trinh S, Ankenman K, Ward T,
Dennis MY, Girirajan S, Eichler EE, Bernier R. Epigenetics
of autism-related impairment: copy number variation
and maternal infection. J Dev Behav Pediatr. 2015
Feb-Mar;36(2):61-7. [PMID: 25629966]
109. Schmidt RJ, Hansen RL, Hartiala J, Allayee H,
Schmidt LC, Tancredi DJ, Tassone F, Hertz-Picciotto
I. Prenatal vitamins, one-carbon metabolism gene
variants, and risk for autism. Epidemiology. 2011
Jul;22(4):476-85. [PMID: 21610500]
110. Volk HE, Kerin T, Lurmann F, Hertz-Picciotto I,
McConnell R, Campbell DB. Autism spectrum
disorder: interaction of air pollution with the MET
receptor tyrosine kinase gene. Epidemiology. 2014
Jan;25(1):44-7. [PMID: 24240654]
111. Webb SJ, Garrison MM, Bernier R, McClintic AM,
King BH, Mourad PD. Severity of ASD symptoms and
their correlation with the presence of copy number
variations and exposure to first trimester
ultrasound. Autism Res. 2017 Mar;10(3):472-484.
[PMID: 27582229]
112. Gauderman WJ, Mukherjee B, Aschard H, Hsu L,
Lewinger JP, Patel CJ, Witte JS, Amos C, Tai CG, Conti
D, Torgerson DG, Lee S, Chatterjee N. Update on the
state of the science for analytical methods for gene-
environment interactions. Am J Epidemiol. 2017 Oct
1;186(7):762-770. [PMID:28978192]
113. Kim D, Volk H, Girirajan S, Pendergrass S, Hall MA,
Verma SS, Schmidt RJ, Hansen RL, Ghosh D, Ludena-
Rodriguez Y, Kim K, Ritchie MD, Hertz-Picciotto I,
Selleck SB. The joint effect of air pollution exposure
and copy number variation on risk for autism. Autism
Res. 2017 Apr 27. [PMID: 28448694]
114. Pearson BL, Simon JM, McCoy ES, Salazar G, Fragola
G, Zylka MJ. Identification of chemicals that mimic
transcriptional changes associated with autism, brain
aging and neurodegeneration. Nat Commun. 2016
Mar 31;7:11173. [PMID: 27029645]
115. Ben-Reuven L, Reiner O. Modeling the autistic cell:
iPSCs recapitulate developmental principles of
syndromic and nonsyndromic ASD. Dev Growth Differ.
2016 Jun;58(5):481-91. [PMID: 27111774]
116. Hogberg HT, Bressler J, Christian KM, Harris G, Makri
G, O'Driscoll C, Pamies D, Smirnova L, Wen Z,
Hartung T. Toward a 3D model of human brain
development for studying gene/environment
interactions. Stem Cell Res Ther. 2013;4 Suppl 1:S4.
[PMID: 24564953]
117. Carter CJ, Blizard RA. Autism genes are selectively
targeted by environmental pollutants including
pesticides, heavy metals, bisphenol A, phthalates and
many others in food, cosmetics or household products.
Neurochem Int. 2016 Oct 27. [PMID: 27984170]
137
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
118. Chesler EJ. Out of the bottleneck: the Diversity
Outcross and Collaborative Cross mouse populations
in behavioral genetics research. Mamm Genome.
2014 Feb;25(1-2):3-11. [PMID: 24272351]
119. Ladd-Acosta C, Fallin MD. The role of epigenetics in
genetic and environmental epidemiology. Epigenomics.
2016 Feb;8(2):271-83. [PMID: 26505319]
120. Keil KP, Lein PJ. DNA methylation: a mechanism
linking environmental chemical exposures to risk of
autism spectrum disorders? Environ Epigenet. 2016
Mar;2(1). pii: dvv012. [PMID: 27158529]
121. Vogel Ciernia A, LaSalle J. The landscape of DNA
methylation amid a perfect storm of autism
aetiologies. Nat Rev Neurosci. 2016 Jul;17(7):411-23.
[PMID: 27150399]
122. Schroeder DI, Schmidt RJ, Crary-Dooley FK, Walker
CK, Ozonoff S, Tancredi DJ, Hertz-Picciotto I, LaSalle
JM. Placental methylome analysis from a prospective
autism study. Mol Autism. 2016 Dec 15;7:51.
[PMID: 28018572]
123. Feinberg JI, Bakulski KM, Jaffe AE, Tryggvadottir R,
Brown SC, Goldman LR, Croen LA, Hertz-Picciotto I,
Newschaffer CJ, Fallin MD, Feinberg AP. Paternal
sperm DNA methylation associated with early signs
of autism risk in an autism-enriched cohort. Int J
Epidemiol. 2015 Aug;44(4):1199-210. [PMID: 25878217]
124. Hou L, Zhang X, Wang D, Baccarelli A. Environmental
chemical exposures and human epigenetics. Int J
Epidemiol. 2012 Feb;41(1):79-105. [PMID: 22253299]
125. Feil R, Fraga MF. Epigenetics and the environment:
emerging patterns and implications. Nat Rev Genet.
2012 Jan 4;13(2):97-109. [PMID: 22215131]
126. Bakulski KM, Fallin MD. Epigenetic epidemiology:
promises for public health research. Environ Mol
Mutagen. 2014 Apr;55(3):171-83. [PMID: 24449392]
127. Bakulski KM, Halladay A, Hu VW, Mill J, Fallin MD.
Epigenetic research in neuropsychiatric disorders:
the "tissue issue". Curr Behav Neurosci Rep. 2016
Sep;3(3):264-274. [PMID: 28093577]
128. Meltzer A, Van de Water J. The role of the
immune system in autism spectrum disorder.
Neuropsychopharmacology. 2017 Jan;42(1):
284-298. [PMID: 27534269]
129. Tylee DS, Hess JL, Quinn TP, Barve R, Huang H,
Zhang-James Y, Chang J, Stamova BS, Sharp FR,
Hertz-Picciotto I, Faraone SV, Kong SW, Glatt SJ.
Blood transcriptomic comparison of individuals
with and without autism spectrum disorder:
A combined-samples mega-analysis. Am J Med
Genet B Neuropsychiatr Genet. 2017 Apr;174(3):181-
201. [PMID: 27862943]
130. Krakowiak P, Goines PE, Tancredi DJ, Ashwood P,
Hansen RL, Hertz-Picciotto I, Van de Water J. Neonatal
cytokine profiles associated with autism spectrum
disorder. Biol Psychiatry. 2017 Mar 1;81(5):442-451.
[PMID: 26392128]
131. Schug TT, Blawas AM, Gray K, Heindel JJ, Lawler
CP. Elucidating the links between endocrine
disruptors and neurodevelopment. Endocrinology.
2015 Jun;156(6):1941-51. [PMID: 25714811]
138
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
132. Park BY, Lee BK, Burstyn I, Tabb LP, Keelan JA,
Whitehouse AJO, Croen LA, Fallin MD, Hertz-Picciotto
I, Montgomery O, Newschaffer CJ. Umbilical cord
blood androgen levels and ASD-related phenotypes
at 12 and 36 months in an enriched risk cohort study.
Mol Autism. 2017 Jan 31;8:3. [PMID: 28163867]
133. Fung TC, Olson CA, Hsiao EY. Interactions between
the microbiota, immune and nervous systems in
health and disease. Nat Neurosci. 2017 Feb;20(2):
145-155. [PMID: 28092661]
134. Vuong HE, Hsiao EY. Emerging roles for the gut
microbiome in autism spectrum disorder. Biol Psychiatry.
2017 Mar 1;81(5):411-423. [PMID: 27773355]
135. Gao B, Chi L, Mahbub R, Bian X, Tu P, Ru H, Lu K.
Multi-omics reveals that lead exposure disturbs
gut microbiome development, key metabolites, and
metabolic pathways. Chem Res Toxicol. 2017 Apr
17;30(4):996-1005. [PMID: 28234468]
136. Lu K, Abo RP, Schlieper KA, Graffam ME, Levine S,
Wishnok JS, Swenberg JA, Tannenbaum SR, Fox JG.
Arsenic exposure perturbs the gut microbiome and its
metabolic profile in mice: an integrated metagenomics
and metabolomics analysis. Environ Health Perspect.
2014 Mar;122(3):284-91. [PMID: 24413286]
137. Alava P, Du Laing G, Tack F, De Ryck T, Van De Wiele
T. Westernized diets lower arsenic gastrointestinal
bioaccessibility but increase microbial arsenic
speciation changes in the colon. Chemosphere. 2015
Jan;119:757-62. [PMID: 25192650]
138. D C Rubin SS, Alava P, Zekker I, Du Laing G,
Van de Wiele T. Arsenic thiolation and the role of
sulfate-reducing bacteria from the human intestinal
tract. Environ Health Perspect. 2014 Aug;122(8):
817-22. [PMID: 24833621]
139. Mattingly CJ, Boyles R, Lawler CP, Haugen AC,
Dearry A, Haendel M. Laying a community-based
foundation for data-driven semantic standards in
environmental health sciences. Environ Health Perspect.
2016 Aug;124(8):1136-40. [PMID: 26871594]
140. Hamilton CM, Strader LC, Pratt JG, Maiese D,
Hendershot T, Kwok RK, Hammond JA, Huggins W,
Jackman D, Pan H, Nettles DS, Beaty TH, Farrer LA,
Kraft P, Marazita ML, Ordovas JM, Pato CN, Spitz
MR, Wagener D, Williams M, Junkins HA, Harlan
WR, Ramos EM, Haines J. The PhenX Toolkit: get the
most from your measures. Am J Epidemiol. 2011 Aug
1;174(3):253-60. [PMID: 21749974]
139
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
1. Paus T, Keshavan M, Giedd JN. Why do many
psychiatric disorders emerge during adolescence?
Nat Rev Neurosci. 2008 Dec;9(12):947-57.
[PMID: 19002191]
2. Blakemore SJ. Imaging brain development: the
adolescent brain. Neuroimage. 2012 Jun;61(2):397-
406. [PMID: 22178817]
3. Gogtay N, Giedd JN, Lusk L, Hayashi KM, Greenstein
D, Vaituzis AC, Nugent TF 3rd, Herman DH, Clasen
LS, Toga AW, Rapoport JL, Thompson PM. Dynamic
mapping of human cortical development during
childhood through early adulthood. Proc Natl Acad
Sci U S A. 2004 May 25;101(21):8174-9.
[PMID: 15148381]
4. McGrew JH, Ruble LA, Smith IM. Autism
Spectrum Disorder and Evidence-Based Practice
in Psychology. Clinical Psychology Science and
Practice. 2016;23(3):239-255. http://doi.org/
10.1111/cpsp.12160
5. Lovaas OI. Behavioral treatment and normal
educational and intellectual functioning in young
autistic children. J Consult Clin Psychol. 1987
Feb;55(1):3-9. [PMID: 3571656]
6. Rogers SJ, Dawson G. Early Start Denver Model for
young children with autism: promoting language,
learning, and engagement. New York: Guilford Press;
2010. xvii, 297 pp.
7. Odom SL, Boyd BA, Hall LJ, Hume KA. Comprehensive
Treatment Models For Children And Youth With
Autism Spectrum Disorders. In: Handbook of autism
and pervasive developmental disorders. Fourth edition.
Fred R. Volkmar, Rhea Paul, Sally J. Rogers, and
Kevin A. Pelphrey, editors. Hoboken, New Jersey:
John Wiley & Sons, Inc.; 2014. p. 770-87.
8. Kasari C. Update on behavioral interventions for autism
and developmental disabilities. Curr Opin Neurol.
2015 Apr;28(2):124-9. [PMID: 25695136]
9. Bernstein A, Chorpita BF, Daleiden EL, Ebesutani CK,
Rosenblatt A. Building an evidence-informed service
array: Considering evidence-based programs as well
as their practice elements. J Consult Clin Psychol. 2015
Dec;83(6):1085-96. [PMID: 26030761]
10. Wong C, Odom SL, Hume KA, Cox AW, Fettig A,
Kucharczyk S, Brock ME, Plavnick JB, Fleury VP,
Schultz TR. Evidence-Based Practices for Children,
Youth, and Young Adults with Autism Spectrum
Disorder: A Comprehensive Review. J Autism Dev
Disord. 2015 Jul;45(7):1951-66. [PMID: 25578338]
11. de Bruin CL, Deppeler JM, Moore DW, Diamond NT.
Public School–Based Interventions for Adolescents
and Young Adults With an Autism Spectrum Disorder.
Review of Educational Research. 2013;83(4):521-50.
https://doi.org/10.3102/0034654313498621
12. Whalon KJ, Conroy MA, Martinez JR, Werch BL.
School-based peer-related social competence
interventions for children with autism spectrum
disorder: a meta-analysis and descriptive review of
single case research design studies. J Autism Dev
Disord. 2015 Jun;45(6):1513-31. [PMID: 25641004]
13. Asmus JM, Carter EW, Moss CK, Biggs EE, Bolt DM,
Born TL, Bottema-Beutel K, Brock ME, Cattey GN,
Cooney M, Fesperman ES, Hochman JM, Huber HB,
Lequia JL, Lyons GL, Vincent LB, Weir K. Efficacy
and Social Validity of Peer Network Interventions for
High School Students With Severe Disabilities.
Am J Intellect Dev Disabil. 2017 Mar;122(2):118-137.
[PMID: 28257242]
QUESTION 4: WHICH TREATMENTS AND INTERVENTIONS WILL HELP?
140
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
14. Laugeson EA, Ellingsen R, Sanderson J, Tucci L, Bates
S. The ABC's of teaching social skills to adolescents
with autism spectrum disorder in the classroom: the
UCLA PEERS (®) Program. J Autism Dev Disord. 2014
Sep;44(9):2244-56. [PMID: 24715256]
15. Stichter JP, Herzog MJ, Owens SA, Malugen E.
Manualization, feasibility, and effectiveness of the
school-based Social Competence Intervention for
Adolescents (SCI-A). Psychology in the Schools.
2016;53(6):583-600. http://dx.doi.org/10.1002/
pits.21928
16. Fleury VP, Hedges S, Hume K, Browder DM, Thompson
JL, Fallin K, El Zein F, Reutebuch CK, Vaughn S.
Addressing the Academic Needs of Adolescents With
Autism Spectrum Disorder in Secondary Education.
Remedial and Special Education. 2014;35(2):68-79.
https://doi.org/10.1177/0741932513518823
17. Keen D, Webster A, Ridley G. How well are children
with autism spectrum disorder doing academically at
school? An overview of the literature. Autism. 2016
Apr;20(3):276-94. [PMID: 25948598]
18. Goods KS, Ishijima E, Chang YC, Kasari C. Preschool
based JASPER intervention in minimally verbal children
with autism: pilot RCT. J Autism Dev Disord. 2013
May;43(5):1050-6. [PMID: 22965298]
19. Strain PS, Bovey EH. Randomized, Controlled Trial
of the LEAP Model of Early Intervention for Young
Children With Autism Spectrum Disorders. Topics in
Early Childhood Special Education. 2011;31(3):133-54.
https://doi.org/10.1177/0271121411408740
20. Koegel RL, Koegel LK. Pivotal response treatments
for autism: communication, social, & academic
development. Baltimore: Paul H. Brookes; 2006.
xiv, 296 pp.
21. Stronach S, Wetherby AM. Examining restricted and
repetitive behaviors in young children with autism
spectrum disorder during two observational contexts.
Autism. 2014 Feb;18(2):127-36. [PMID: 23175750]
22. Pajareya K, Nopmaneejumruslers K. A pilot randomized
controlled trial of DIR/Floortime™ parent training
intervention for pre-school children with autistic
spectrum disorders. Autism. 2011 Sep;15(5):563-77.
[PMID: 21690083]
23. Kaiser AP, Roberts MY. Parent-implemented enhanced
milieu teaching with preschool children who have
intellectual disabilities. J Speech Lang Hear Res.
2013;56(1):295-309. [PMID: 22744141]
24. Roberts MY, Kaiser AP. Early intervention for toddlers
with language delays: a randomized controlled trial.
Pediatrics. 2015;135(4):686-93. [PMID: 25733749]
25. Arick JR, Loos L, Falco R, Krug DA. STAR Program
Manual: Strategies for Teaching Based on Autism
Research: PRO-ED, Incorporated; 2004.
26. Weitlauf AS, McPheeters ML, Peters B, Sathe N, Travis
R, Aiello R, Williamson E, Veenstra-VanderWeele J,
Krishnaswami S, Jerome R, Warren Z. Therapies for
Children With Autism Spectrum Disorder: Behavioral
Interventions Update [Internet]. Rockville (MD):
Agency for Healthcare Research and Quality (US);
2014 Aug. [PMID: 25210724]
27. Chang YC, Shire SY, Shih W, Gelfand C, Kasari C.
Preschool Deployment of Evidence-Based Social
Communication Intervention: JASPER in the Classroom.
J Autism Dev Disord. 2016 Jun;46(6):2211-23.
[PMID: 26936161]
141
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
28. Shire SY, Chang YC, Shih W, Bracaglia S, Kodjoe
M, Kasari C. Hybrid implementation model of
community-partnered early intervention for toddlers
with autism: a randomized trial. J Child Psychol
Psychiatry. 2017 May;58(5):612-622.
[PMID: 27966784]
29. Schreibman L, Dawson G, Stahmer AC, Landa R,
Rogers SJ, McGee GG, Kasari C, Ingersoll B, Kaiser
AP, Bruinsma Y, McNerney E, Wetherby A,
Halladay A. Naturalistic Developmental Behavioral
Interventions: Empirically Validated Treatments for
Autism Spectrum Disorder. J Autism Dev Disord.
2015 Aug;45(8):2411-28. [PMID: 25737021]
30. Wetherby AM, Guthrie W, Woods J,
Schatschneider C, Holland RD, Morgan L, Lord C.
Parent-Implemented Social Intervention for
Toddlers With Autism: An RCT. Pediatrics. 2014.
http://doi.org/10.1542/peds.2014-0757
31. Kasari C, Gulsrud A, Paparella T, Hellemann G,
Berry K. Randomized comparative efficacy study of
parent-mediated interventions for toddlers with
autism. J Consult Clin Psychol. 2015 Jun;83(3):554-63.
[PMID: 25822242]
32. Kasari C, Kaiser A, Goods K, Nietfeld J, Mathy P,
Landa R, Murphy S, Almirall D. Communication
interventions for minimally verbal children
with autism: a sequential multiple assignment
randomized trial. J Am Acad Child Adolesc Psychiatry
2014 Jun;53(6):635-46. [PMID: 24839882]
33. Siller M, Hutman T, Sigman M. A parent-mediated
intervention to increase responsive parental behaviors
and child communication in children with ASD: a
randomized clinical trial. J Autism Dev Disord. 2013
Mar;43(3):540-55. [PMID: 22825926]
34. Hardan AY, Gengoux GW, Berquist KL, Libove RA,
Ardel CM, Phillips J, Frazier TW, Minjarez MB. A
randomized controlled trial of Pivotal Response
Treatment Group for parents of children with autism.
J Child Psychol Psychiatry. 2015 Aug;56(8):884-92.
[PMID: 25346345]
35. Pickles A, Anderson DK, Lord C. Heterogeneity
and plasticity in the development of language:
a 17-year follow-up of children referred early for
possible autism. J Child Psychol Psychiatry. 2014
Dec;55(12):1354-62. [PMID: 24889883]
36. Gulsrud AC, Hellemann G, Shire S, Kasari C.
Isolating active ingredients in a parent-mediated
social communication intervention for toddlers with
autism spectrum disorder. J Child Psychol Psychiatry.
2016 May;57(5):606-13. [PMID: 26525461]
37. Harrop C, Shire S, Gulsrud A, Chang YC, Ishijima E,
Lawton K, Kasari C. Does gender influence core deficits
in ASD? An investigation into social-communication
and play of girls and boys with ASD. J Autism Dev
Disord. 2015 Mar;45(3):766-77. [PMID: 25217088]
38. Frazier TW, Ratliff KR, Gruber C, Zhang Y, Law PA,
Constantino JN. Confirmatory factor analytic structure
and measurement invariance of quantitative autistic
traits measured by the social responsiveness scale-2.
Autism. 2014 Jan;18(1):31-44. [PMID: 24019124]
39. Kasari C, Dean M, Kretzmann M, Shih W, Orlich F,
Whitney R, Landa R, Lord C, King B. Children with
autism spectrum disorder and social skills groups
at school: a randomized trial comparing intervention
approach and peer composition. J Child Psychol
Psychiatry. 2016 Feb;57(2):171-9. [PMID: 26391889]
142
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
40. Dean M, Harwood R, Kasari C. The art of camouflage:
Gender differences in the social behaviors of girls and
boys with autism spectrum disorder. Autism. 2016
Nov 29. [PMID: 27899709]
41. Robinson EB, Lichtenstein P, Anckarsater H, Happe F,
Ronald A. Examining and interpreting the female
protective effect against autistic behavior.
Proc Natl Acad Sci U S A. 2013;110(13):5258-62.
[PMID: 23431162]
42. Jacquemont S, Coe BP, Hersch M, Duyzend MH,
Krumm N, Bergmann S, Beckmann JS, Rosenfeld JA,
Eichler EE. A higher mutational burden in females
supports a “female protective model” in
neurodevelopmental disorders. Am J Hum Genet.
2014;94(3):415-25. [PMID: 24581740]
43. Werling DM, Parikshak NN, Geschwind DH. Gene
expression in human brain implicates sexually
dimorphic pathways in autism spectrum disorders.
Nat Commun. 2016;7:10717. [PMID: 26892004]
44. Bishop-Fitzpatrick L, Minshew NJ, Eack SM. A
Systematic Review of Psychosocial Interventions
for Adults with Autism Spectrum Disorders.
In: Adolescents and Adults with Autism Spectrum
Disorders. Fred R. Volkmar, Brian Reichow, James C.
McPartland, editors. New York, NY: Springer
New York; 2014. p. 315-327.
45. Blakemore SJ, Choudhury S. Development of the
adolescent brain: implications for executive function
and social cognition. J Child Psychol Psychiatry. 2006
Mar-Apr;47(3-4):296-312. [PMID: 16492261]
46. Yatawara CJ, Einfeld SL, Hickie IB, Davenport TA,
Guastella AJ. The effect of oxytocin nasal spray on
social interaction deficits observed in young children
with autism: a randomized clinical crossover trial. Mol
Psychiatry. 2016 Sep;21(9):1225-31. [PMID: 26503762]
47. Gordon I, Vander Wyk BC, Bennett RH, Cordeaux C,
Lucas MV, Eilbott JA, Zagoory-Sharon O, Leckman
JF, Feldman R, Pelphrey KA. Oxytocin enhances brain
function in children with autism. Proc Natl Acad
Sci U S A. 2013 Dec 24;110(52):20953-8.
[PMID: 24297883]
48. Watanabe T, Abe O, Kuwabara H, Yahata N, Takano Y,
Iwashiro N, Natsubori T, Aoki Y, Takao H, Kawakubo
Y, Kamio Y, Kato N, Miyashita Y, Kasai K, Yamasue
H. Mitigation of sociocommunicational deficits of
autism through oxytocin-induced recovery of medial
prefrontal activity: a randomized trial. JAMA Psychiatry.
2014 Feb;71(2):166-75. [PMID: 24352377]
49. Bartz JA, Zaki J, Bolger N, Ochsner KN. Social
effects of oxytocin in humans: context and person
matter. Trends Cogn Sci. 2011 Jul;15(7):301-9.
[PMID: 21696997]
50. Wink LK, Adams R, Wang Z, Klaunig JE, Plawecki MH,
Posey DJ, McDougle CJ, Erickson CA. A randomized
placebo-controlled pilot study of N-acetylcysteine
in youth with autism spectrum disorder. Mol Autism.
2016 Apr 21;7:26. [PMID: 27103982]
51. Minshawi NF, Wink LK, Shaffer R, Plawecki MH,
Posey DJ, Liu H, Hurwitz S, McDougle CJ, Swiezy NB,
Erickson CA. A randomized, placebo-controlled trial
of D-cycloserine for the enhancement of social skills
training in autism spectrum disorders. Mol Autism.
2016 Jan 14;7:2. [PMID: 26770664]
143
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
52. Chugani DC, Chugani HT, Wiznitzer M, Parikh S, Evans
PA, Hansen RL, Nass R, Janisse JJ, Dixon-Thomas P,
Behen M, Rothermel R, Parker JS, Kumar A, Muzik
O, Edwards DJ, Hirtz D; Autism Center of Excellence
Network. Efficacy of Low-Dose Buspirone for
Restricted and Repetitive Behavior in Young Children
with Autism Spectrum Disorder: A Randomized Trial.
J Pediatr. 2016 Mar;170:45-53.e1-4. [PMID: 26746121]
53. Lemonnier E, Degrez C, Phelep M, Tyzio R, Josse F,
Grandgeorge M, Hadjikhani N, Ben-Ari Y. A randomised
controlled trial of bumetanide in the treatment of
autism in children. Transl Psychiatry. 2012 Dec 11;2:e202.
[PMID: 23233021]
54. Du L, Shan L, Wang B, Li H, Xu Z, Staal WG, Jia F.
A Pilot Study on the Combination of Applied Behavior
Analysis and Bumetanide Treatment for Children
with Autism. J Child Adolesc Psychopharmacol. 2015
Sep;25(7):585-8. [PMID: 26258842]
55. Sukhodolsky DG, Scahill L, Gadow KD, Arnold LE,
Aman MG, McDougle CJ, McCracken JT, Tierney E,
Williams White S, Lecavalier L, Vitiello B. Parent-rated
anxiety symptoms in children with pervasive
developmental disorders: frequency and association
with core autism symptoms and cognitive functioning.
J Abnorm Child Psychol. 2008;36(1):117-28.
[PMID: 17674186]
56. Wood JJ, Ehrenreich-May J, Alessandri M, Fujii C,
Renno P, Laugeson E, Piacentini JC, De Nadai AS,
Arnold E, Lewin AB, Murphy TK, Storch EA. Cognitive
behavioral therapy for early adolescents with autism
spectrum disorders and clinical anxiety: a randomized,
controlled trial. Behav Ther. 2015;46(1):7-19.
[PMID: 25526831]
57. Sukhodolsky DG, Bloch MH, Panza KE, Reichow B.
Cognitive-behavioral therapy for anxiety in children
with high-functioning autism: a meta-analysis.
Pediatrics. 2013;132(5):e1341-50. [PMID: 24167175]
58. Walkup JT, Albano AM, Piacentini J, Birmaher B,
Compton SN, Sherrill JT, Ginsburg GS, Rynn MA,
McCracken J, Waslick B, Iyengar S, March JS,
Kendall PC. Cognitive behavioral therapy, sertraline,
or a combination in childhood anxiety. N Engl J Med.
2008;359(26):2753-66. [PMID: 18974308]
59. Buitelaar JK, van der Gaag RJ, van der Hoeven J.
Buspirone in the management of anxiety and irritability
in children with pervasive developmental disorders:
results of an open-label study. J Clin Psychiatry.
1998;59(2):56-9. [PMID: 9501886]
60. Namerow L, Thomas P, Bostic JQ, Prince J,
Monuteaux MC. Use of citalopram in pervasive
developmental disorders. J Dev Behav Pediatr.
2003;24(2):104-8. [PMID: 12692455]
61. Martin A, Koenig K, Anderson GM, Scahill L.
Low-dose fluvoxamine treatment of children and
adolescents with pervasive developmental disorders:
a prospective, open-label study. J Autism Dev Disord.
2003;33(1):77-85. [PMID: 12708582]
62. Oberman LM, Enticott PG, Casanova MF, Rotenberg
A, Pascual-Leone A, McCracken JT; TMS in ASD
Consensus Group. Transcranial magnetic stimulation
in autism spectrum disorder: Challenges, promise,
and roadmap for future research. Autism Res. 2016
Feb;9(2):184-203. [PMID: 26536383]
144
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
63. Shafi MM, Brandon Westover M, Oberman L, Cash
SS, Pascual-Leone A. Modulation of EEG functional
connectivity networks in subjects undergoing repetitive
transcranial magnetic stimulation. Brain Topogr. 2014
Jan;27(1):172-91. [PMID: 23471637]
64. Oberman L, Pascual-Leone A. Changes in plasticity
across the lifespan: cause of disease and target for
intervention. Prog Brain Res. 2013;207:91-120.
[PMID: 24309252]
65. Fox MD, Buckner RL, Liu H, Chakravarty MM, Lozano
AM, Pascual-Leone A. Resting-state networks link
invasive and noninvasive brain stimulation across
diverse psychiatric and neurological diseases.
Proc Natl Acad Sci U S A. 2014 Oct 14;111(41):E4367-75.
[PMID: 25267639]
66. Kobayashi M, Pascual-Leone A. Transcranial
magnetic stimulation in neurology. Lancet Neurol.
2003 Mar;2(3):145-56. [PMID: 12849236]
67. Casanova MF, Baruth JM, El-Baz A, Tasman A, Sears
L, Sokhadze E. Repetitive Transcranial Magnetic
Stimulation (rTMS) Modulates Event-Related Potential
(ERP) Indices of Attention in Autism. Transl Neurosci.
2012 Jun 1;3(2):170-180. [PMID: 24683490]
68. Enticott PG, Fitzgibbon BM, Kennedy HA, Arnold
SL, Elliot D, Peachey A, Zangen A, Fitzgerald PB.
A double-blind, randomized trial of deep repetitive
transcranial magnetic stimulation (rTMS) for autism
spectrum disorder. Brain Stimul. 2014
Mar-Apr;7(2):206-11. [PMID: 24280031]
69. Panerai S, Tasca D, Lanuzza B, Trubia G, Ferri R,
Musso S, Alagona G, Di Guardo G, Barone C,
Gaglione MP, Elia M. Effects of repetitive transcranial
magnetic stimulation in performing eye-hand
integration tasks: four preliminary studies with
children showing low-functioning autism. Autism.
2014 Aug;18(6):638-50. [PMID: 24113340]
70. Amatachaya A, Auvichayapat N, Patjanasoontorn
N, Suphakunpinyo C, Ngernyam N, Aree-Uea B,
Keeratitanont K, Auvichayapat P. Effect of anodal
transcranial direct current stimulation on autism:
a randomized double-blind crossover trial. Behav
Neurol. 2014;2014:173073. [PMID: 25530675]
71. van Steenburgh JJ, Varvaris M, Schretlen DJ,
Vannorsdall TD, Gordon B. Balanced bifrontal
transcranial direct current stimulation enhances
working memory in adults with high-functioning
autism: a sham-controlled crossover study.
Mol Autism. 2017;8:40. [PMID: 28775825]
72. Young AM, Chakrabarti B, Roberts D, Lai MC,
Suckling J, Baron-Cohen S. From molecules to neural
morphology: understanding neuroinflammation in
autism spectrum condition. Mol Autism. 2016;7:9.
[PMID: 26793298]
73. Voineagu I, Wang X, Johnston P, Lowe JK, Tian
Y, Horvath S, Mill J, Cantor RM, Blencowe BJ,
Geschwind DH. Transcriptomic analysis of autistic
brain reveals convergent molecular pathology. Nature.
2011;474(7351):380-4. [PMID: 21614001]
74. Braunschweig D, Krakowiak P, Duncanson P,
Boyce R, Hansen RL, Ashwood P, Hertz-Picciotto I,
Pessah IN, Van de Water J. Autism-specific
maternal autoantibodies recognize critical proteins
in developing brain. Transl Psychiatry. 2013;3:e277.
[PMID: 23838888]
75. Vargas DL, Nascimbene C, Krishnan C,
Zimmerman AW, Pardo CA. Neuroglial activation
and neuroinflammation in the brain of patients
with autism. Ann Neurol. 2005;57(1):67-81.
[PMID: 15546155]
145
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
76. Suzuki K, Sugihara G, Ouchi Y, Nakamura K,
Futatsubashi M, Takebayashi K, Yoshihara Y, Omata
K, Matsumoto K, Tsuchiya KJ, Iwata Y, Tsujii M,
Sugiyama T, Mori N. Microglial activation in young
adults with autism spectrum disorder. JAMA Psychiatry.
2013;70(1):49-58. [PMID: 23404112]
77. Morgan JT, Chana G, Pardo CA, Achim C, Semendeferi
K, Buckwalter J, Courchesne E, Everall IP. Microglial
activation and increased microglial density observed
in the dorsolateral prefrontal cortex in autism. Biol
Psychiatry. 2010;68(4):368-76. [PMID: 20674603]
78. Bachstetter AD, Pabon MM, Cole MJ, Hudson CE,
Sanberg PR, Willing AE, Bickford PC, Gemma C.
Peripheral injection of human umbilical cord blood
stimulates neurogenesis in the aged rat brain. BMC
Neurosci. 2008;9:22. [PMID: 18275610]
79. Shahaduzzaman M, Golden JE, Green S, Gronda AE,
Adrien E, Ahmed A, Sanberg PR, Bickford PC, Gemma
C, Willing AE. A single administration of human
umbilical cord blood T cells produces long-lasting
effects in the aging hippocampus. Age (Dordr).
2013;35(6):2071-87. [PMID: 23263793]
80. Ha S, Park H, Mahmood U, Ra JC, Suh YH, Chang
KA. Human adipose-derived stem cells ameliorate
repetitive behavior, social deficit and anxiety in a
VPA-induced autism mouse model. Behav Brain Res.
2017;317:479-84. [PMID: 27717813]
81. Segal-Gavish H, Karvat G, Barak N, Barzilay R, Ganz
J, Edry L, Aharony I, Offen D, Kimchi T. Mesenchymal
Stem Cell Transplantation Promotes Neurogenesis and
Ameliorates Autism Related Behaviors in BTBR Mice.
Autism Res. 2016;9(1):17-32. [PMID: 26257137]
82. Sun J, Allison J, McLaughlin C, Sledge L, Waters-Pick
B, Wease S, Kurtzberg J. Differences in quality between
privately and publicly banked umbilical cord blood
units: a pilot study of autologous cord blood infusion
in children with acquired neurologic disorders.
Transfusion. 2010;50(9):1980-7. [PMID: 20546200]
83. Cotten CM, Murtha AP, Goldberg RN, Grotegut CA,
Smith PB, Goldstein RF, Fisher KA, Gustafson KE,
Waters-Pick B, Swamy GK, Rattray B, Tan S, Kurtzberg
J. Feasibility of autologous cord blood cells for infants
with hypoxic-ischemic encephalopathy. J Pediatr.
2014;164(5):973-9 e1. [PMID: 24388332]
84. Sun JM, Grant GA, McLaughlin C, Allison J, Fitzgerald
A, Waters-Pick B, Kurtzberg J. Repeated autologous
umbilical cord blood infusions are feasible and had no
acute safety issues in young babies with congenital
hydrocephalus. Pediatr Res. [PMID: 26331765]
85. Dawson G, Sun JM, Davlantis KS, Murias M, Franz
L, Troy J, Simmons R, Sabatos-DeVito M, Durham
R, Kurtzberg J. Autologous Cord Blood Infusions
Are Safe and Feasible in Young Children with Autism
Spectrum Disorder: Results of a Single-Center
Phase I Open-Label Trial. Stem Cells Transl Med.
2017;6(5):1332-9. [PMID: 28378499]
86. Sztainberg Y, Zoghbi HY. Lessons learned from
studying syndromic autism spectrum disorders.
Nat Neurosci. 2016 Oct 26;19(11):1408-1417.
[PMID: 27786181]
87. Katz DM, Bird A, Coenraads M, Gray SJ, Menon DU,
Philpot BD, Tarquinio DC. Rett Syndrome: Crossing
the Threshold to Clinical Translation. Trends Neurosci.
2016;39(2):100-13. [PMID: 26830113]
146
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
88. Katz DM, Menniti FS, Mather RJ. N-Methyl-D-
Aspartate Receptors, Ketamine, and Rett Syndrome:
Something Special on the Road to Treatments? Biol
Psychiatry. 2016;79(9):710-2. [PMID: 27079494]
89. Khwaja OS, Ho E, Barnes KV, O'Leary HM, Pereira
LM, Finkelstein Y, Nelson CA, 3rd, Vogel-Farley V,
DeGregorio G, Holm IA, Khatwa U, Kapur K,
Alexander ME, Finnegan DM, Cantwell NG,
Walco AC, Rappaport L, Gregas M, Fichorova RN,
Shannon MW, Sur M, Kaufmann WE. Safety,
pharmacokinetics, and preliminary assessment of
efficacy of mecasermin (recombinant human IGF-1)
for the treatment of Rett syndrome. Proc Natl Acad
Sci U S A. 2014;111(12):4596-601. [PMID: 24623853]
90. Buchovecky CM, Turley SD, Brown HM, Kyle SM,
McDonald JG, Liu B, Pieper AA, Huang W, Katz DM,
Russell DW, Shendure J, Justice MJ. A suppressor
screen in Mecp2 mutant mice implicates
cholesterol metabolism in Rett syndrome. Nat
Genet. 2013;45(9):1013-20. [PMID: 23892605]
91. Berry-Kravis E, Des Portes V, Hagerman R, Jacquemont
S, Charles P, Visootsak J, Brinkman M, Rerat K,
Koumaras B, Zhu L, Barth GM, Jaecklin T, Apostol G,
von Raison F. Mavoglurant in fragile X syndrome:
Results of two randomized, double-blind, placebo-
controlled trials. Sci Transl Med. 2016;8(321):321ra5.
[PMID: 26764156]
92. Ligsay A, Hagerman RJ. Review of targeted treat-
ments in fragile X syndrome. Intractable Rare Dis Res.
2016;5(3):158-67. [PMID: 27672538]
93. Wu JY, Peters JM, Goyal M, Krueger D, Sahin M,
Northrup H, Au KS, Cutter G, Bebin EM. Clinical
Electroencephalographic Biomarker for Impending
Epilepsy in Asymptomatic Tuberous Sclerosis
Complex Infants. Pediatr Neurol. 2016;54:29-34.
[PMID: 26498039]
94. French JA, Lawson JA, Yapici Z, Ikeda H, Polster
T, Nabbout R, Curatolo P, de Vries PJ, Dlugos DJ,
Berkowitz N, Voi M, Peyrard S, Pelov D, Franz DN.
Adjunctive everolimus therapy for treatment-
resistant focal-onset seizures associated with
tuberous sclerosis (EXIST-3): a phase 3, randomised,
double-blind, placebo-controlled study. Lancet.
2016;388(10056):2153-63. [PMID: 27613521]
95. Grynszpan O, Weiss PL, Perez-Diaz F, Gal E.
Innovative technology-based interventions for autism
spectrum disorders: a meta-analysis. Autism. 2014
May;18(4):346-61. [PMID: 24092843]
96. Begum M, Serna RW, Kontak D, Allspaw J,
Kuczynski J, Yanco HA, Suarez J. Measuring the
Efficacy of Robots in Autism Therapy: How
Informative are Standard HRI Metrics. Proceedings
of the Tenth Annual ACM/IEEE International
Conference on Human-Robot Interaction; Portland,
Oregon, USA. 2696480: ACM; 2015. p. 335-42.
https://doi.org/10.1145/2696454.2696480
97. Diehl JJ, Crowell CR, Villano M, Wier K, Tang K, Riek
LD. Clinical Applications of Robots in Autism Spectrum
Disorder Diagnosis and Treatment. In: Comprehensive
Guide to Autism. Patel VB, Preedy VR, Martin CR,
editors. New York, NY: Springer New York; 2014.
p. 411-22. https://dx.doi.org/10.1007/978-1-4614-
4788-7_14
98. Kim ES, Paul R, Shic F, Scassellati B. Bridging the
Research Gap: Making HRI Useful to Individuals
with Autism. Journal of Human-Robot Interaction.
2012;1(1):26-54. http://humanrobotinteraction.org/
journal/index.php/HRI/article/view/25
147
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
99. Brugha TS, Doos L, Tempier A, Einfeld S, Howlin P.
Outcome measures in intervention trials for adults
with autism spectrum disorders; a systematic review
of assessments of core autism features and associated
emotional and behavioural problems. Int J Methods
Psychiatr Res. 2015 Jun;24(2):99-115.
[PMID: 26077193]
100. McConachie H, Parr JR, Glod M, Hanratty J, Livingstone
N, Oono IP, Robalino S, Baird G, Beresford B, Charman T,
Garland D, Green J, Gringras P, Jones G, Law J,
Le Couteur AS, Macdonald G, McColl EM, Morris C,
Rodgers J, Simonoff E, Terwee CB, Williams K.
Systematic review of tools to measure outcomes
for young children with autism spectrum disorder.
Health Technol Assess. 2015 Jun;19(41):1-506.
[PMID: 26065374]
101. Ashwood KL, Buitelaar J, Murphy D, Spooren W,
Charman T. European clinical network: autism
spectrum disorder assessments and patient
characterisation. Eur Child Adolesc Psychiatry.
2015 Aug;24(8):985-95. [PMID: 25471824]
102. Payakachat N, Tilford JM, Kovacs E, Kuhlthau K.
Autism spectrum disorders: a review of measures for
clinical, health services and cost-effectiveness
applications. Expert Rev Pharmacoecon Outcomes Res.
2012 Aug;12(4):485-503. [PMID: 22971035]
103. Esler AN, Bal VH, Guthrie W, Wetherby A, Ellis
Weismer S, Lord C. The Autism Diagnostic Observation
Schedule, Toddler Module: Standardized Severity
Scores. J Autism Dev Disord. 2015 Sep;45(9):2704-
20. [PMID: 25832801]
104. Grzadzinski R, Carr T, Colombi C, McGuire K,
Dufek S, Pickles A, Lord C. Measuring Changes in
Social Communication Behaviors: Preliminary
Development of the Brief Observation of Social
Communication Change (BOSCC). J Autism Dev
Disord. 2016 Jul;46(7):2464-79. [PMID: 27062034]
105. Parker KJ, Oztan O, Libove RA, Sumiyoshi RD,
Jackson LP, Karhson DS, Summers JE, Hinman KE,
Motonaga KS, Phillips JM, Carson DS, Garner JP,
Hardan AY. Intranasal oxytocin treatment for social
deficits and biomarkers of response in children with
autism. Proc Natl Acad Sci U S A. 2017;114(30):
8119-24. [PMID: 28696286]
106. Dawson G, Bernier R, Ring RH. Social attention: a
possible early indicator of efficacy in autism clinical
trials. J Neurodev Disord. 2012 May 17;4(1):11.
[PMID: 22958480]
107. Jeste SS, Frohlich J, Loo SK. Electrophysiological
biomarkers of diagnosis and outcome in neuro-
developmental disorders. Curr Opin Neurol. 2015
Apr;28(2):110-6. [PMID: 25710286]
108. Philip RC, Dauvermann MR, Whalley HC, Baynham
K, Lawrie SM, Stanfield AC. A systematic review and
meta-analysis of the fMRI investigation of autism
spectrum disorders. Neurosci Biobehav Rev. 2012
Feb;36(2):901-42. [PMID: 22101112]
109. Rane P, Cochran D, Hodge SM, Haselgrove C,
Kennedy DN, Frazier JA. Connectivity in Autism:
A Review of MRI Connectivity Studies. Harv Rev
Psychiatry. 2015 Jul-Aug;23(4):223-44.
[PMID: 26146755]
148
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
110. Stavropoulos KK-M. Using neuroscience as an
outcome measure for behavioral interventions in
Autism spectrum disorders (ASD): A review.
Research in Autism Spectrum Disorders. 2017;35:
62-73. https://doi.org/10.1016/j.rasd.2017.01.001
111. Calderoni S, Billeci L, Narzisi A, Brambilla P, Retico
A, Muratori F. Rehabilitative Interventions and
Brain Plasticity in Autism Spectrum Disorders: Focus
on MRI-Based Studies. Front Neurosci. 2016 Mar
31;10:139. [PMID: 27065795]
112. Adams ZW, McClure EA, Gray KM, Danielson CK,
Treiber FA, Ruggiero KJ. Mobile devices for the
remote acquisition of physiological and behavioral
biomarkers in psychiatric clinical research. J Psychiatr
Res. 2017 Feb;85:1-14. [PMID: 27814455]
113. Nicolaidis C, Raymaker D, McDonald K, Dern S,
Ashkenazy E, Boisclair C, Robertson S, Baggs A.
Collaboration strategies in nontraditional
community-based participatory research partnerships:
lessons from an academic−community partnership
with autistic self-advocates. Prog Community
Health Partnersh. 2011 Summer;5(2):143-50.
[PMID: 21623016]
149
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION 5: WHAT KINDS OF SERVICES AND SUPPORTS ARE NEEDED
TO MAXIMIZE QUALITY OF LIFE FOR PEOPLE ON THE AUTISM SPECTRUM?
1. Office of Autism Research Coordination, National
Institute of Mental Health, on behalf of the Interagency
Autism Coordinating Committee (IACC). 2014-2015
IACC Autism Spectrum Disorder Research Portfolio
Analysis Report. October 2017. Retrieved from the
U.S. Department of Health and Human Services
Interagency Autism Coordinating Committee website:
https://iacc.hhs.gov/portfolio-analysis/2015/
index.shtml
2. Shattuck PT, Roux AM, Hudson LE, Taylor JL,
Maenner å, Trani JF. Services for adults with
an autism spectrum disorder. Can J Psychiatry.
2012 May;57(5):284-91. [PMID: 22546060]
3. United States Government Accountability Office
(GAO). Youth with Autism: Round Table Views of
Services Needed During the Transition into Adulthood.
Oct 2016. Retrieved from: https://www.gao.gov/
assets/690/680525.pdf
4. United States Government Accountability Office
(GAO). Youth with Autism: Federal Agencies Should
Take Additional Action to Support Transition-Age Youth.
May 2017. Retrieved from: https://www.gao.gov/
assets/690/684484.pdf
5. Buescher AV, Cidav Z, Knapp M, Mandell DS.
Costs of autism spectrum disorders in the United
Kingdom and the United States. JAMA Pediatr.
2014 Aug;168(8):721-8. [PMID: 24911948]
6. Lavelle TA, Weinstein MC, Newhouse JP, Munir K,
Kuhlthau KA, Prosser LA. Economic burden of
childhood autism spectrum disorders. Pediatrics.
2014 Mar;133(3):e520-9. [PMID: 24515505]
7. Boyd BA, Hume K, McBee MT, Alessandri M,
Gutierrez A, Johnson L, Sperry L, Odom SL. Comparative
efficacy of LEAP, TEACCH and non-model-specific
special education programs for preschoolers with
autism spectrum disorders. J Autism Dev Disord. 2014
Feb;44(2):366-80. [PMID: 23812661]
8. Levy SE, Giarelli E, Lee LC, Schieve LA, Kirby RS,
Cunniff C, Nicholas J, Reaven J, Rice CE. Autism
spectrum disorder and co-occurring developmental,
psychiatric, and medical conditions among children in
multiple populations of the United States. J Dev Behav
Pediatr. 2010 May;31(4):267-75. [PMID: 20431403]
9. Muris P, Steerneman P, Merckelbach H, Holdrinet I,
Meesters C. Comorbid anxiety symptoms in children
with pervasive developmental disorders. J Anxiety
Disord. 1998 Jul-Aug;12(4):387-93. [PMID: 9699121]
10. Mattila ML1, Hurtig T, Haapsamo H, Jussila K,
Kuusikko-Gauffin S, Kielinen M, Linna SL, Ebeling H,
Bloigu R, Joskitt L, Pauls DL, Moilanen I. Comorbid
psychiatric disorders associated with Asperger
syndrome/high-functioning autism: a community-
and clinic-based study. J Autism Dev Disord.
2010 Sep;40(9):1080-93. [PMID: 20177765]
11. Leyfer OT, Folstein SE, Bacalman S, Davis NO, Dinh E,
Morgan J, Tager-Flusberg H, Lainhart JE. Comorbid
psychiatric disorders in children with autism: interview
development and rates of disorders. J Autism Dev
Disord. 2006 Oct;36(7):849-61. [PMID: 16845581]
150
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
12. Kraper CK, Kenworthy L, Popal H, Martin A,
Wallace GL. The Gap Between Adaptive Behavior and
Intelligence in Autism Persists into Young Adulthood
and is Linked to Psychiatric Co-morbidities. J Autism
Dev Disord. 2017 Jul 14. [PMID: 28710532]
13. Gotham K, Brunwasser SM, Lord C. Depressive
and anxiety symptom trajectories from school age
through young adulthood in samples with autism
spectrum disorder and developmental delay. J Am
Acad Child Adolesc Psychiatry. 2015 May;54(5):
369-76.e3. [PMID: 25901773]
14. Cassidy S, Bradley P, Robinson J, Allison C, McHugh,
M, Baron-Cohen, S. Suicidal ideation and suicide
plans or attempts in adults with Asperger's syndrome
attending a specialist diagnostic clinic: a clinical
cohort study. Lancet Psychiatry. 2014 Jul;1(2):142-7.
[PMID: 26360578]
15. Cassidy S, Rodgers J. Understanding and
prevention of suicide in autism. Lancet Psychiatry.
2017 Jun;4(6):e11. [PMID: 28551299]
16. Pelton MK, Cassidy SA. Are autistic traits
associated with suicidality? A test of the
interpersonal-psychological theory of suicide
in a non-clinical young adult sample. Autism
Res. 2017 Jul 7. [PMID: 28685996]
17. Croen LA, Zerbo O, Qian Y, Massolo ML, Rich S,
Sidney S, Kripke C. The health status of adults on the
autism spectrum. Autism. 2015 Oct;19(7):814-23.
[PMID: 25911091]
18. Nahmias AS, Kase C, Mandell DS. Comparing
cognitive outcomes among children with autism
spectrum disorders receiving community-based
early intervention in one of three placements.
Autism. 2014 Apr;18(3):311-20. [PMID: 23188885]
19. Shattuck PT, Narendorf SC, Cooper B, Sterzing
PR, Wagner M, Taylor, JL. Postsecondary
education and employment among youth with
an autism spectrum disorder. Pediatrics.
2012 Jun;129(6):1042-9. [PMID: 22585766]
20. Golnik A, Maccabee-Ryaboy N, Scal P, Wey A,
Gaillard P. Shared decision making: improving care
for children with autism. Intellect Dev Disabil. 2012
Aug;50(4):322-31. [PMID: 22861133]
21. Mandell DS, Barry CL, Marcus SC, Xie M, Shea K,
Mullan K, Epstein AJ. Effects of Autism Spectrum
Disorder Insurance Mandates on the Treated
Prevalence of Autism Spectrum Disorder. JAMA Pediatr.
2016 Sep 1;170(9):887-93. [PMID: 27399053]
22. Leslie DL, Iskandarani K, Dick AW, Mandell DS,
Yu H, Velott D, Agbese E, Stein BD. The Effects of
Medicaid Home and Community-Based Services
Waivers on Unmet Needs Among Children
with Autism Spectrum Disorder. Med Care. 2017
Jan;55(1):57-63. [PMID: 27547947]
23. Cidav Z, Marcus SC, Mandell DS. Home- and
Community-Based Waivers for Children with Autism:
Effects on Service Use and Costs. Intellect Dev Disabil.
2014 Aug;52(4):239-48. [PMID: 25061768]
24. Centers for Medicare & Medicaid Services. Report
on State Services to Individuals with Autism Spectrum
Disorders (ASD). 2011 Apr. https://www.cms.gov/
apps/files/9-state-report.pdf
25. Bilder D, Botts EL, Smith KR, Pimentel R, Farley M,
Viskochil J, McMahon WM, Block H, Ritvo E,
Ritvo RA, Coon H. Excess mortality and causes of
death in autism spectrum disorders: a follow up of
the 1980s Utah/UCLA autism epidemiologic study.
J Autism Dev Disord. 2013 May;43(5):1196-204.
[PMID: 23008058]
151
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
26. Zablotsky B, Pringle BA, Colpe LJ, Kogan MD, Rice
C, Blumberg, SJ. Service and treatment use among
children diagnosed with autism spectrum disorders.
J Dev Behav Pediatr. 2015 Feb-Mar;36(2):98-105.
[PMID: 25650952]
27. Battaglia M, Detrick S, Fernandez A. Multidisciplinary
Treatment for Adults with Autism Spectrum Disorder
and Co-Occurring Mental Health Disorders: Adapting
Clinical Research Tools to Everyday Clinical Practice.
Journal of Mental Health Research in Intellectual
Disabilities. June 2016; 9(4), 232-249. http://dx.doi.
org/10.1080/19315864.2016.1192708
28. Posserud M, Hysing M, Helland W, Gillberg C,
Lundervold AJ. Autism traits: The importance of
"co-morbid" problems for impairment and contact with
services. Data from the Bergen Child Study. Res Dev
Disabil. 2016 Jan 27. pii: S0891-4222(16)30002-6.
[PMID: 26826893]
29. Hirvikoski T, Mittendorfer-Rutz E, Boman M,
Larsson H, Lichtenstein P, Bölte S. Premature mortality
in autism spectrum disorder. Br J Psychiatry.
2016 Mar;208(3):232-8. [PMID: 26541693]
30. National Autism Association. Mortality & Risk in
ASD Wandering/Elopement 2011-2016. March 2017.
Retrieved from: http://nationalautismassociation.
org/wp-content/uploads/2017/04/NAA
MortalityRiskASDElopement.pdf
31. Liu G, Pearl AM, Kong L, Leslie DL, Murray MJ.
A Profile on Emergency Department Utilization in
Adolescents and Young Adults with Autism
Spectrum Disorders. J Autism Dev Disord. 2017
Feb;47(2):347-358. [PMID: 27844247]
32. Zhang W, Mason AE, Boyd B, Sikich L, Baranek G.
A Rural-Urban Comparison in Emergency Department
Visits for U.S. Children with Autism Spectrum Disorder.
J Autism Dev Disord. 2017 Mar;47(3):590-598.
[PMID: 27909850]
33. Sohl K, Mazurek M, Brown, R. ECHO Autism:
Using Technology and Mentorship to Bridge Gaps,
Increase Access to Care, and Bring Best Practice
Autism Care to Primary Care. Clin Pediatr (Phila).
2017 Jun;56(6):509-511. [PMID: 28497714]
34. Liptak GS, Benzoni LB, Mruzek DW, Nolan KW,
Thingvoll MA, Wade CM, Fryer GE. Disparities
in diagnosis and access to health services for
children with autism: Data from the National Survey
of Children’s Health. J Dev Behav Pediatr. 2008
Jun;29(3):152-60. [PMID: 18349708]
35. Oswald DP, Haworth SM. (2016). Autism
spectrum disorders. In Handbook of Mental Health
in African American Youth (pp. 271-285). Springer
International Publishing.
36. Frieden TR, Jaffe HW, Cono J, Richards CL,
Iademarco MF. Prevalence of autism spectrum
disorder among children aged 8 years—Autism and
developmental disabilities monitoring network,
11 sites, United States, 2010. MMWR Surveill Summ.
2014 Mar 28;63(2):1-21. [PMID: 24670961]
37. Mandell DS, Wiggins LD, Carpenter LA, Daniels J,
DiGuiseppi C, Durkin MS, Giarelli E, Morrier MJ,
Nicholas JS, Pinto-Martin JA, Shattuck PT, Thomas
KC, Yeargin-Allsopp M, Kirby RS. Racial/ethnic
disparities in the identification of children with
autism spectrum disorders. Am J Public Health. 2009
Mar;99(3):493-8. [PMID: 19106426]
152
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
38. Zamora I, Williams ME, Higareda M, Wheeler BY,
Levitt P. Brief report: Recruitment and retention of
minority children for autism research. J Autism Dev
Disord. 2016 Feb;46(2):698-703. [PMID: 26404703]
39. Magaña S, Lopez K, Aguinaga A, Morton H.
Access to diagnosis and treatment services among
latino children with autism spectrum disorders.
Intellect Dev Disabil. 2013 Jun;51(3):141-53.
[PMID: 23834211]
40. Magaña S, Parish SL, Son E. Have racial and
ethnic disparities in the quality of health care
relationships changed for children with developmental
disabilities and ASD? Am J Intellect Dev Disabil. 2015
Nov;120(6):504-13. [PMID: 26505871]
41. Baker J, Sanghvi T, Hajeebhoy N, Martin L,
Lapping K. Using an evidence-based approach
to design large-scale programs to improve infant
and young child feeding. Food Nutr Bull. 2013
Sep;34(3 Suppl):S146-55. [PMID: 24261073]
42. Cooper BR, Bumbarger BK, Moore JE. Sustaining
evidence-based prevention programs: Correlates in
a large-scale dissemination initiative. Prev Sci. 2015
Jan;16(1):145-57. [PMID: 23975240]
43. Hiersteiner D, Bradley V, Ne'eman A, Bershadsky J,
Bonardi A. Putting the Research in Context: The Life
Experience and Outcomes of Adults on the Autism
Spectrum Receiving Services in 29 States. Inclusion.
2017;5(1), 45-59.
44. Schieve LA, Blumberg SJ, Rice C, Visser SN, Boyle
C. The relationship between autism and parenting
stress. Pediatrics. 2007 Feb;119 Suppl 1:S114-21.
[PMID: 17272578]
45. Sim A, Vaz S, Cordier R, Joosten A, Parsons D, Smith
C, Falkmer T. Factors associated with stress in families
of children with autism spectrum disorder. Dev
Neurorehabil. 2017 Jun 9:1-11. [PMID: 28598245]
46. Cowen PS, Reed DA. Effects of respite care for children
with developmental disabilities: evaluation of an
intervention for at risk families. Public Health Nurs.
2002 Jul-Aug;19(4):272-83. [PMID: 12071901]
47. Mandell DS, Xie M, Morales KH, Lawer L,
McCarthy M, Marcus SC. The interplay of
outpatient services and psychiatric hospitalization
among Medicaid-enrolled children with autism
spectrum disorders. Arch Pediatr Adolesc Med. 2012
Jan;166(1):68-73. [PMID: 22213753]
48. Dykens EM, Fisher MH, Taylor JL, Lambert W,
Miodrag N. Reducing distress in mothers of children
with autism and other disabilities: a randomized
trial. Pediatrics. 2014 Aug;134(2):e454-63.
[PMID: 25049350]
49. Bearss K, Johnson C, Smith T, Lecavalier L, Swiezy
N, Aman M, McAdam DB, Butter E, Stillitano C,
Minshawi N, Sukhodolsky DG, Mruzek DW, Turner
K, Neal T, Hallett V, Mulick JA, Green B, Handen B,
Deng Y, Dziura J, Scahill L. Effect of parent training
vs parent education on behavioral problems in children
with autism spectrum disorder: a randomized
clinical trial. JAMA. 2015 Apr 21;313(15):1524-33.
[PMID: 25898050]
50. Pickard KE, Ingersoll BR. Quality versus quantity:
The role of socioeconomic status on parent-
reported service knowledge, service use, unmet
service needs, and barriers to service use. Autism.
2016 Jan;20(1):106-15. [PMID: 25948601]
153
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
51. Roux AM, Shattuck PT, Rast JE, Rava JA,
Anderson KA. National Autism Indicators Report:
transition into young adulthood. Philadelphia, PA:
Life Course Outcomes Research Program, AJ Drexel
Autism Institute, Drexel University. April 2015.
Retrieved from: http://drexel.edu/autismoutcomes/
publications-and-reports/publications/
National-Autism-Indicators-Report-Transition-
to-Adulthood/#sthash.p272LoRy.dpbs
52. Taylor JL, Henninger NA. Frequency and correlates
of service access among youth with autism
transitioning to adulthood. J Autism Dev Disord. 2015
Jan;45(1):179-91. [PMID: 25081594]
53. Turcotte P, Mathew M, Shea LL, Brusilovskiy E,
Nonnemacher SL. Service needs across the lifespan
for individuals with autism." J Autism Dev Disord.
2016 Jul;46(7):2480-9. [PMID: 27084080]
54. Koffer Miller K H, Mathew M, Nonnemacher
SL, Shea LL. (2017). Program experiences
of adults with autism, their families, and
providers: Findings from a focus group study.
Autism. doi:10.1177/1362361316679000
55. Stahmer AC, Aarons GA. Attitudes toward
adoption of evidence-based practices: A comparison
of autism early intervention providers and
children’s mental health providers. . Psychol Serv
2009 Aug;6(3):223-234. [PMID: 21796262]
56. Stahmer A, Reed S, Shin S, Mandell D. (2010).
Fidelity of implementation of evidence-based
practice in community classrooms. In Presentation
at the 9th international meeting for autism research
(IMFAR).
57. Fueyo M, Caldwell T, Mattern SB, Zahid J, Foley T.
The health home: a service delivery model for
autism and intellectual disability. Psychiatr Serv.
2015 Nov;66(11):1135-7. [PMID: 26129999]
58. United States Government Accountability Office
(GAO). STUDENTS WITH DISABILITIES: Better
Federal Coordination Could Lessen Challenges in
the Transition from High School. July 2012.
Retrieved from: http://www.gao.gov/assets/
600/592329.pdf
154
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION 6: HOW CAN WE MEET THE NEEDS OF PEOPLE WITH ASD
AS THEY PROGRESS INTO AND THROUGH ADULTHOOD?
1. Shattuck PT, Steinberg J, Yu J, Wei X, Cooper BP,
Newman L, Roux AM. Disability Identification
and Self-Efficacy among College Students on
the Autism Spectrum. Autism Res Treat.
2014;2014:924182. [PMID: 24707401]
2. Christensen DL, Baio J, Van Naarden Braun K, Bilder
D, Charles J, Constantino JN, Daniels J, Durkin MS,
Fitzgerald RT, Kurzius-Spencer M, Lee LC, Pettygrove
S, Robinson C, Schulz E, Wells C, Wingate MS,
Zahorodny W, Yeargin-Allsopp M. Prevalence
and Characteristics of Autism Spectrum Disorder
Among Children Aged 8 Years–Autism and
Developmental Disabilities Monitoring Network, 11
Sites, United States, 2012. MMWR Surveill Summ.
2016 Apr 1;65(3):1-23. [PMID: 27031587]
3. Shattuck PT, Narendorf SC, Cooper B, Sterzing PR,
Wagner M, Taylor JL. Postsecondary education and
employment among youth with an autism spectrum
disorder. Pediatrics. 2012 Jun;129(6):1042-9.
[PMID: 22585766]
4. Taylor JL, Seltzer MM. Employment and post-
secondary educational activities for young adults
with Autism Spectrum Disorders during the
transition to adulthood. J Autism Dev Disord. 2011
May;41(5):566-74. [PMID: 20640591]
5. Shattuck PT, Wagner M, Narendorf S, Sterzing P,
Hensley M. Post-High School Service Use among
Young Adults with an Autism Spectrum Disorder.
Arch Pediatr Adolesc Med. 2011 Feb;165(2):141-6.
[PMID: 21300654]
6. Orsmond GI, Shattuck PT, Cooper BP, Sterzing PR,
Anderson KA. Social participation among young
adults with an autism spectrum disorder. J Autism Dev
Disord. 2013 Nov;43(11):2710-9. [PMID: 23615687]
7. Taylor JL, Seltzer MM. Change in the autism
phenotype during the transition to adulthood.
J Autism Dev Disord. 2010 Dec;40(12):1431-1446.
[PMID: 20361245]
8. Burgess S, Cimera RE. Employment Outcomes
of Transition-Aged Adults With Autism Spectrum
Disorders : A State of the States Report.
Am J Intellect Dev Disabil. 2014 Jan;119(1):64-83.
[PMID: 24450322]
9. Gobbo K, Shmulsky S. Faculty Experience with
College Students With Autism Spectrum
Disorders: A Qualitative Study of Challenges and
Solutions. Focus on Autism and Other Developmental
Disabilities. 2014 March. 29(1), 13–22. http://doi.
org/10.1177/1088357613504989
10. Roux AM, Shattuck PT, Rast JE, Rava JA, and
Anderson KA. National Autism Indicators Report:
Transition into Young Adulthood. Philadelphia, PA:
Life Course Outcomes Research Program, A.J.
Drexel Autism Institute, Drexel University. April
2015. Retrieved from: http://drexel.edu/
autismoutcomes/publications-and-reports/
publications/National-Autism-Indicators-
Report-Transition-to-Adulthood/#sthash.
p272LoRy.dpbs
155
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
11. Ellison M, Clark J, Cunningham M, Hansen R.
Academic and campus accommodations that foster
success for college students with Asperger’s Disorder.
Southern Regional Council on Educational Administration
2013 Yearbook: Jazzing It Up. 2013 Sept; 65–76.
12. Myers E, Davis B.E, Stobbe G, Bjornson K.
Community and social participation among
individuals with autism spectrum disorder
transitioning to adulthood. J Autism Dev Disord.
2015 Aug;45(8):2373-81. [PMID: 25725812]
13. Taylor JL, Adams RA, Bishop SL. Social
participation and its relation to internalizing symptoms
among youth with autism spectrum disorder as
they transition from high school. Autism Res. 2017
Apr;10(4):663-672. [PMID: 27739234]
14. Tobin M, Drager K, Richardson L. A systematic
review of social participation for adult with autism
spectrum disorders: Support, social functioning, and
quality of life. Research in Autism Spectrum Disorders.
2014 Mar; 8(3), 214-229. https://doi.org/10.1016/
j.rasd.2013.12.002
15. Anderson KA, Shattuck PT, Cooper BP, Roux
AM, Wagner M. Prevalence and correlates of
postsecondary residential status among young
adults with an autism spectrum disorder. Autism.
2014 Jul;18(5):562-70. [PMID: 23996904]
16. Taylor JL, Hodapp RM, Burke MM, Waitz-Kudla
SN, Rabideau C. Training parents of youth
with autism spectrum disorder to advocate for
adult disability services: Results from a pilot
randomized controlled trial. J Autism Dev Disord.
2017 Mar;47(3):846-857. [PMID:28070786]
17. Smith LE, Greenberg JS, Mailick MR. The family
context of autism spectrum disorders: Influence on
the behavioral phenotype and quality of life. Child
Adolesc Psychiatr Clin N Am. 2014 Jan;23(1):143-55.
[PMID: 24231173]
18. White SW, Richey JA, Gracanin D, Coffman M,
Elias R, LaConte S, Ollendick TH. Psychosocial and
computer-assisted intervention for college students
with autism spectrum disorder: Preliminary support
for feasibility. Educ Train Autism Dev Disabil. 2016
Sep;51(3):307-317. [PMID: 28111607]
19. Wehman P, Schall CM, McDonough J, Graham C,
Brooke V, Riehle JE, Brooke A, Ham W, Lau S, Allen J,
Avellone L. Effects of an employer-based intervention
on employment outcomes for youth with
significant support needs due to autism. Autism.
2017 Apr;21(3):276-290. [PMID: 27154907]
20. Laugeson EA, Gantman A, Kapp SK, Orenski K,
Ellingson R. A randomized controlled trial to
improve social skills in young adults with autism
spectrum disorder: The UCLA PEERS program.
J Autism Dev Disord. 2015 Dec;45(12):3978-89.
[PMID: 26109247]
21. Morgan L, Leatzow A. Clark S, Siller M. Interview skills
for adults with autism spectrum disorder: A pilot
randomized controlled trial. J Autism Dev Disord. 2014
Sep;44(9):2290-300. [PMID: 24682707]
22. Smith MJ, Ginger E, Wright K, Wright M, Taylor
JL, Humm LB, Olson D, Bell MD, Fleming MF.
Virtual reality job interview training in adults with
autism spectrum disorder. J Autism Dev Disord.
2014 Oct;44(10):2450-63. [PMID: 24803366]
156
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
23. Wehman P, Brooke V, Brooke AM, Ham W,
Schall C, McDonough J, Lau S, Seward H. Avellone L.
Employment for adults with autism spectrum
disorders: A retrospective review of a customized
employment approach. Res Dev Disabil. 2016
Jun-Jul;53-54:61-72. [PMID: 26855048]
24. Anderson DK, Liang JW, Lord C. Predicting young
adult outcome among more and less cognitively able
individuals with autism spectrum disorders.
J Child Psychol Psychiatry. 2014 May;55(5):485-94.
[PMID: 24313878]
25. Howlin P, Moss P, Savage S, Rutter M. Social
outcomes in mid- to later adulthood among individuals
diagnosed with autism and average nonverbal IQ
as children. J Am Acad Child Adolesc Psychiatry. 2013
Jun;52(6):572-81.e1. [PMID: 23702446]
26. Taylor JL, Seltzer MM. Developing a vocational
index for adults with autism spectrum disorders.
J Autism Dev Disord. 2012;42(12):2669-2679.
[PMID: 22466690]
27. Taylor JL, Henninger NA, Mailick MR. Longitudinal
patterns of employment and postsecondary
educational activities for adults with ASD and
normal-range IQ. Autism. 2015 Oct;19(7):785-793.
[PMID: 26019306]
28. Wei X, Wagner M, Hudson L, Yu JW, Shattuck P.
Transition to adulthood: Employment, education, and
disengagement in individuals with autism spectrum
disorder. Emerging Adulthood. 2015 Feb; 3(1), 37-45.
https://doi.org/10.1177/2167696814534417
29. Taylor JL, Mailick MR. A Longitudinal Examination of
10-Year Change in Vocational and Educational Activities
for Adults With Autism Spectrum Disorders. Dev
Psychol. 2014 Mar; 50 (3): 699-708. [PMID: 24001150]
30. Lakin KC, Doljanac R, Byun SY, Stancliffe RJ, Taub
S, Chiri G. Factors associated with expenditures
for Medicaid home and community based services
(HCBS) and intermediate care facilities for persons
with mental retardation (ICF/MR) services
for persons with intellectual and developmental
disabilities. Intellect Dev Disabil. 2008 Jun;46(3):
200-14. [PMID: 18578578]
31. McConkey R, Abbott S, Walsh PN, Linehan C, Emerson
E. Variations in the social inclusion of people with
intellectual disabilities in supported living schemes
and residential settings. J Intellect Disabil Res. 2007
Mar;51(Pt 3):207-17. [PMID: 17300416]
32. Tichá R, Hewitt A, Nord D, Larson S. System and
individual outcomes and their predictors in services
and support for people with IDD. Intellect Dev Disabil.
2013 Oct;51(5):298-315. [PMID: 24303819]
33. Verheij C, Louwerse A, van der Ende J, Eussen MLJM,
Van Gool AR, Verheij F, Verhulst FC, Greaves-Lord K.
The stability of comorbid psychiatric disorders: A 7 year
follow up of children with pervasive developmental
disorder-not otherwise specified. J Autism Dev Disord.
2015 Dec;45(12):3939-48. [PMID: 26456972]
34. Croen LA, Zerbo O, Qian Y, Massolo ML, Rich S,
Sidney S, Kripke C. The health of adults on the
autism spectrum. Autism. 2015 Oct;19(7):814-23.
[PMID: 25911091]
35. Gotham K, Brunwasser SM, Lord C. Depressive
and anxiety symptom trajectories from school age
through young adulthood in samples with autism
spectrum disorder and developmental delay.
J Am Acad Child Adolesc Psychiatry. 2015 May;54(5):
369-76.e3. [PMID: 25901773]
157
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
36. Gotham K, Marvin AR, Taylor JL, Warren Z, Anderson
CM, Law PA, Law JK, Lipkin PH. Characterizing the
daily life, needs, and priorities of adults with autism
spectrum disorder from Interactive Autism
Network data. Autism. 2015 Oct;19(7):794-804.
[PMID: 25964655]
37. Maddox BB, White SW. Comorbid social anxiety
disorder in adults with autism spectrum disorder.
J Autism Dev Disord. 2015 Dec;45(12):3949-60.
[PMID: 26243138]
38. Kraper CK, Kenworthy L, Popal H, Martin A, Wallace
GL. The Gap Between Adaptive Behavior and
Intelligence in Autism Persists into Young Adulthood
and is Linked to Psychiatric Co-morbidities. J Autism
Dev Disord. 2017 Jul 14. [Epub ahead of print]
[PMID: 28710532]
39. Hirvikoski T, Mittendorfer-Rutz E, Boman M, Larsson H,
Lichtenstein P, Bölte S. Premature mortality in autism
spectrum disorder. The British Journal of Psychiatry.
2016;208(3):232-238.
40. Cashin A, Buckley T, Trollor JN, Lennox N. A scoping
review of what is known of the physical health of
adults with autism spectrum disorder. Br J Psychiatry.
2016 Mar;208(3):232-8. [PMID: 26541693]
41. Rengit AC, McKowen JW, O'Brien J, Howe YJ,
McDougle CJ. Brief Report: Autism Spectrum Disorder
and Substance Use Disorder: A Review and Case
Study. J Autism Dev Disord. 2016 Jul;46(7):2514-9.
[PMID: 26944591]
42. Vohra R, Madhavan S, Sambamoorthi U. Emergency
Department Use Among Adults with Autism
Spectrum Disorders (ASD). J Autism Dev Disord.
2016 Apr;46(4):1441-54. [PMID: 26762115]
43. Liu G, Pearl AM, Kong L, Leslie DL, Murray MJ.
A Profile on Emergency Department Utilization
in Adolescents and Young Adults with Autism
Spectrum Disorders. J Autism Dev Disord. 2017
Feb;47(2):347-358. [PMID: 27844247]
44. Nicolaidis C, Raymaker D, McDonald K, Dern S,
Boisclair WC, Ashkenazy E, Baggs A. Comparison of
Healthcare Experiences in Autistic and Non-Autistic
Adults: A Cross-Sectional Online Survey Facilitated
by an Academic-Community Partnership. J Gen Intern
Med. 2013 Jun;28(6):761-9. [PMID: 23179969]
45. Raymaker DM, McDonald KE, Ashkenazy E, Gerrity
M, Baggs AM, Kripke C, Hourston S, Nicolaidis C.
Barriers to healthcare: Instrument development and
comparison between autistic adults and adults with
and without other disabilities. Autism. 2016 Sep 22.
[Epub ahead of print] [PMID: 27663266]
46. Pickett J, Xiu E, Tuchman R, Dawson G, Lajonchere
C. Mortality in individuals with autism, with and
without epilepsy. J Child Neurol. 2011 Aug;26(8):
932-9. [PMID: 21471551]
47. Gillberg C, Billstedt E, Sundh V, Gillberg IC.
Mortality in autism: a prospective longitudinal
community-based study. J Autism Dev Disord.
2010 Mar;40(3):352-7. [PMID: 19838782]
48. Bilder D, Botts EL, Smith KR, Pimentel R, Farley M,
Viskochil J, McMahon WM, Block H, Ritvo E, Ritvo
RA, Coon H. Excess mortality and causes of death
in autism spectrum disorders: a follow up of the
1980s Utah/UCLA autism epidemiologic study.
J Autism Dev Disord. 2013 May;43(5):1196-204.
[PMID: 23008058]
158
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
49. Guan J, Li G. Injury mortality in individuals with
autism. Am J Public Health. 2017 May;107(5):791-793.
[PMID: 28323463]
50. Hategan A, Bourgeois JA, Goldberg J. Aging with
autism spectrum disorder: an emerging public health
problem. Int Psychogeriatr. 2017 Apr;29(4):695-697.
[PMID: 27669633]
51. Piven J, Rabins P. Autism spectrum disorders in older
adults: toward defining a research agenda. J Am Geriatr
Soc. 2011 Nov;59(11):2151-5. [PMID: 22091837]
52. Lever AG, Geurts HM. Age-related differences
in cognition across the adult lifespan in autism
spectrum disorder. Autism Res. 2016 Jun;9(6):
666-76. [PMID: 26333004]
53. White SW, DiCriscio AS. Introduction to special
issue ASD in adulthood: Comorbidity and intervention.
J Autism Dev Disord. 2015 Dec;45(12):3905-7.
[PMID: 26519326]
54. Cheak-Zamora NC, Teti M, Maurer-Batjer A, Halloran
D. Snapshots of growing up: Youth with autism explore
adulthood through Photovoice. J Dev Behav Pediatr.
2016 Jul-Aug;37(6):433-41. [PMID: 27355880]
55. Rutter M , Greenfeld D, Lockyer L. A five to
fifteen year follow-up study of infantile psychosis.
Br J Psychiatry. 1967 Nov;113(504):1183-99.
[PMID: 6075452]
56. Brugha TS, McManus S, Bankart J, Scott F, Purdon
S, Smith J, Bebbington P, Jenkins R, Meltzer H.
Epidemiology of autism spectrum disorders in adults
in the community in England. Arch Gen Psychiatry.
2011 May;68(5):459-65. [PMID: 21536975]
57. Dworzynski K, Ronald A, Bolton P, Happé F.
How different are girls and boys above and below
the diagnostic threshold for autism spectrum
disorders? J Am Acad Child Adolesc Psychiatry. 2012
Aug;51(8):788-97. [PMID: 22840550]
58. Loomes R, Hull L, Mandy WPL. What Is the
Male-to-Female Ratio in Autism Spectrum Disorder?
A Systematic Review and Meta-Analysis. J Am Acad
Child Adolesc Psychiatry. 2017 Jun;56(6):466-474.
[PMID: 28545751]
59. Shattuck PT, Seltzer MM, Greenberg JS,
Orsmond GI, Bolt D, Kring S, Lounds J, Lord C.
Change in autism symptoms and maladaptive
behaviors in adolescents and adults with an autism
spectrum disorder. J Autism Dev Disord. 2007
Oct;37(9):1735-47. [PMID: 17146700]
60. McGovern CW, Sigman M. Continuity and change
from early childhood to adolescence in autism.
J Child Psychol Psychiatry. 2005 Apr;46(4):401-8.
[PMID: 15819649]
61. Lord C, Risi S, Lambrecht L, Cook EH, Leventhal BL,
DiLavore P, Pickles A, Rutter M. The autism diagnostic
observation schedule-generic: a standard measure
of social and communication deficits associated with
the spectrum of autism. J Autism Dev Disord. 2000
Jun;30(3):205-23. [PMID: 11055457]
62. Hus V, Lord C. The Autism Diagnostic Observation
Schedule, Module 4: Revised Algorithm and
Standardized Severity Scores. J Autism Dev Disord.
2014 Aug;44(8):1996-2012. [PMID: 24590409]
63. Pugliese CE, Kenworthy L, Bal VH, Wallace GL,
Yerys BE, Maddox BB, White SW, Popal H, Armour
AC, Miller J, Herrington JD, Schultz RT, Martin A,
Anthony LG. Replication and comparison of the
159
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
newly proposed ADOS-2, module 4 algorithm in ASD
without ID: A multi-site study. J Autism Dev Disord.
2015 Dec;45(12):3919-31. [PMID: 26385796]
64. Schultz R. “Digital Clinical Assessment for Diagnosis
and Treatment Outcome Measurement.” Interagency
Autism Coordinating Committee Meeting,
26 April 2017, National Institutes of Health, MD.
Panel Presentation.
65. Geurts HM, Jansen MD. A retrospective chart study:
the pathway to a diagnosis for adults referred for
ASD assessment. Autism. 2012 May;16(3):299-305.
[PMID: 21949003]
66. Anderson C, Law JK, Daniels A, Rice C, Mandell
DS, Hagopian L, Law PA. Occurrence and Family
Impact of Elopement in Children With Autism
Spectrum Disorders. Pediatrics. 2012 Nov;130(5):
870-7. [PMID: 23045563]
67. Humphrey N, Symes W. Peer interaction patterns
among adolescents with autistic spectrum disorders
(ASDs) in mainstream school settings. Autism. 2011
Jul;15(4):397-419. [PMID: 21454385]
68. Bancroft K, Batten A, Lambert S, Madders T. The way
we are: autism in 2012. The National Autistic Society.
(2012). Retrieved from: http://library.autism.org.uk/
Portal/Default/en-GB/RecordView/Index/28271
69. Brown-Lavoie SM, Viecili MA, Weiss JA. Sexual
knowledge and victimization in adults with autism
spectrum disorders. J Autism Dev Disord. 2014
Sep;44(9):2185-96. [PMID: 24664634]
70. Newman L, Wagner M, Knokey A-M, Marder C,
Nagle K, Shaver D, Wei X with Cameto R, Contreras
E, Ferguson K, Greene S, Schwarting M (2011).
The Post-High School Outcomes of Young Adults With
Disabilities up to 8 Years After High School. A Report
From the National Longitudinal Transition Study-2
(NLTS2) (NCSER 2011-3005). Menlo Park, CA: SRI
International. Retrieved from: https://ies.ed.gov/
ncser/pubs/20113005/pdf/20113005.pdf
71. Helverschou SB, Rasmussen K, Steindal K,
Søndanaa E, Nilsson B, Nøttestad JA. Offending
profiles of individuals with autism spectrum disorder:
A study of all individuals with autism spectrum
disorder examined by the forensic psychiatric service
in Norway between 2000 and 2010. Autism. 2015
Oct;19(7):850-8. [PMID: 25976157]
72. Crane L, Maras KL, Hawken T, Mulcahy S, Memon
A. Experiences of Autism Spectrum Disorder and
Policing in England and Wales: Surveying Police and
the Autism Community. J Autism Dev Disord. 2016
Jun;46(6):2028-41. [PMID: 26861714]
73. Taylor JL, Gotham K. Cumulative life events,
traumatic experiences, and psychiatric
symptomatology in transition-aged youth with
autism spectrum disorder. J Neurodev Disord.
2016 Jul 27;8:28. [PMID: 27468315]
74. Howlin P, Magiati I. Autism spectrum disorder:
Outcomes in adulthood. Curr Opin Psychiatry. 2017
Mar;30(2):69-76. [PMID: 28067726]
75. Pearpoint J, O'Brien J, Forest M. Path:
Planning Alternative Tomorrows with Hope for
Schools, Organizations, Business, Families:
A Workbook for Planning Positive Possible Futures.
Inclusion Press, 1993.
76. Vandercook T, York J, Forest M. The McGill Action
Planning System (MAPS): A strategy for building the
vision. Journal of the Association for Persons with Severe
Handicaps. 1989; 14(3), 205-215.
160
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
77. Starkstein S, Gellar S, Parlier M, Payne L, Piven J.
High rates of parkinsonism in adults with autism.
J Neurodev Disord. 2015;7(1):29. [PMID: 26322138]
78. Geurts HM, Vissers ME. Elderly with autism:
executive functions and memory. J Autism Dev Disord.
2012 May;42(5):665-75. [PMID: 21656030]
79. Tint A, Maughan A, Weiss J. Community
participation of youth with intellectual disability
and autism spectrum disorder. J Intellect Disabil Res.
2017 Feb;61(2):168-180. [PMID: 27492816]
80. Seltzer MM, Greenberg JS, Hong J, Smith LE,
Almeida DM, Coe C, Stawski RS. Maternal cortisol
levels and behavior problems in adolescents
and adults with ASD. J Autism Dev Disord. 2010
Apr;40(4):457-69. [PMID: 19890706]
81. Burke MM, Patton KA, Taylor JL. Family support: A
review of the literature on families of adolescents with
disabilities. Journal of Family Social Work. 2016; 19(4),
252-285. DOI: 10.1080/10522158.2016.1214658.
82. Nicholas DB, Attridge M, Zwaigenbaum L, Clarke M.
Vocational support approaches in autism spectrum
disorder: A synthesis review of the literature. Autism.
2015 Feb;19(2):235-45. [PMID: 24449603]
83. Office of Autism Research Coordination, National
Institute of Mental Health, on behalf of the Interagency
Autism Coordinating Committee (IACC). 2014-2015
IACC Autism Spectrum Disorder Research Portfolio
Analysis Report. October 2017. Retrieved from the
U.S. Department of Health and Human Services
Interagency Autism Coordinating Committee website:
https://iacc.hhs.gov/portfolio-analysis/2015/
index.shtml
161
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION 7: HOW DO WE CONTINUE TO BUILD, EXPAND, AND ENHANCE
THE INFRASTRUCTURE SYSTEM TO MEET THE NEEDS OF THE ASD COMMUNITY?
1. Nichols L, Freund M, Ng C, Kau A, Parisi M, Taylor A,
Armstrong D, Avenilla F, Joseph J, Meinecke D,
Wagner A, Roger Little A. The National Institutes of
Health NeuroBioBank: a federated national network
of
human brain and tissue repositories. Biol Psychiatry.
2014 Jun 15;75(12):e21-2. [PMID: 24074636]
2. Johnson SB, Whitney G, McAuliffe M, Wang H,
McCreedy E, Rozenblit L, Evans CC. Using global
unique identifiers to link autism collections. J Am Med
Inform Assoc. 2010 Nov-Dec;17(6):689-95.
[PMID: 20962132]
3. Buxbaum JD, Daly MJ, Devlin B, Lehner T, Roeder
K, State MW; Autism Sequencing Consortium.
The autism sequencing consortium: large-scale,
high-throughput sequencing in autism spectrum
disorders. Neuron. 2012 Dec 20;76(6):1052-6.
[PMID: 23259942]
4. Werling DM, Parikshak NN, Geschwind DH. Gene
expression in human brain implicates sexually
dimorphic pathways in autism spectrum disorders.
Nat Commun. 2016 Feb 19;7:10717. [PMID: 26892004]
5. Werling DM. The role of sex-differential biology in
risk for autism spectrum disorder. Biol Sex Differ. 2016
Nov 16;7:58. eCollection 2016. [PMID: 27891212]
6. Brugha T, McManus S, Meltzer H, Smith J,
Scott FJ, Purdon S, Harris J, Bankart J. Autism
Spectrum Disorders in Adults Living in Households
Throughout England—Report From the Adult
Psychiatric Morbidity Survey 2007. Leeds, England
NHS Information Centre. 2009. http://content.digital.
nhs.uk/pubs/asdpsychiatricmorbidity07
7. Brugha TS, McManus S, Bankart J, Scott F, Purdon S,
Smith J, Bebbington P, Jenkins R, Meltzer H.
Epidemiology of autism spectrum disorders in adults
in the community in England. Arch Gen Psychiatry.
2011 May;68(5):459-65. [PMID: 21536975]
8. Christensen DL, Baio J, Van Naarden Braun K, Bilder
D, Charles J, Constantino JN, Daniels J, Durkin MS,
Fitzgerald RT, Kurzius-Spencer M, Lee LC, Pettygrove
S, Robinson C, Schulz E, Wells C, Wingate MS,
Zahorodny W, Yeargin-Allsopp M; Centers for
Disease Control and Prevention (CDC). Prevalence
and Characteristics of Autism Spectrum Disorder
Among Children Aged 8 Years--Autism and
Developmental Disabilities Monitoring Network,
11 Sites, United States, 2012. MMWR Surveill Summ.
2016 Apr 1;65(3):1-23. [PMID: 27031587]
9. Kim YS, Leventhal BL, Koh YJ, Fombonne E, Laska E,
Lim EC, Cheon KA, Kim SJ, Kim YK, Lee H, Song DH,
Grinker RR. Prevalence of autism spectrum disorders
in a total population sample. Am J Psychiatry. 2011
Sep;168(9):904-12. [PMID: 21558103]
162
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
BUDGET RECOMMENDATION
1. Buescher AV, Cidav Z, Knapp M, Mandell DS.
Costs of autism spectrum disorders in the United
Kingdom and the United States. JAMA Pediatr.
2014 Aug;168(8):721-8. [PMID: 24911948]
2. Lavelle TA, Weinstein MC, Newhouse JP, Munir K,
Kuhlthau KA, Prosser LA. Economic burden of
childhood autism spectrum disorders. Pediatrics.
2014 Mar;133(3):e520-9. [PMID: 24515505]
3. Leigh JP, Du J. Brief Report: Forecasting the economic
burden of autism in 2015 and 2025 in the United
States. J Autism Dev Disord. 2015 Dec;45(12):4135-9.
[PMID: 26183723]
4. Peters-Scheffer N, Didden R, Korzilius H, Matson
J. Cost comparison of early intensive behavioral
intervention and treatment as usual for children
with autism spectrum disorder in The Netherlands.
Res Dev Disabil. 2012 Nov-Dec;33(6):1763-72.
[PMID: 22705454]
5. Penner M, Rayar M, Bashir N, Roberts SW,
Hancock-Howard RL, Coyte PC. Cost-effectiveness
analysis comparing pre-diagnosis autism spectrum
disorder (ASD)-targeted intervention with Ontario's
Autism Intervention Program. J Autism Dev Disord.
2015 Sep;45(9):2833-47. [PMID: 25936527]
6. Cidav Z, Munson J, Estes A, Dawson G, Rogers S,
Mandell D. Cost Offset Associated with Early Start
Denver Model for Children with Autism. J Am Acad
Child Adolesc Psychiatry. [Available online 4 July 2017:
http://www.sciencedirect.com/science/article/
pii/S0890856717303131?via%3Dihub]
7. Roux AM, Shattuck PT, Rast JE, Rava JA, Anderson
KA. National Autism Indicators Report: Transition
into young adulthood. Philadelphia, PA: Life Course
Outcomes Research Program, A.J. Drexel Autism
Institute, Drexel University, 2015. [http://drexel.edu/
autismoutcomes/publications-and-reports/
publications/National-Autism-Indicators-Report-
Transition-to-Adulthood/#sthash.IhJf7Y5P.dpbs]
8. Järbrink K, McCrone P, Fombonne E, Zandén
H, Knapp M. Cost-impact of young adults with
high-functioning autistic spectrum disorder.
Res Dev Disabil. 2007 Jan-Feb;28(1):94-104.
[PMID: 16551499]
9. https://officeofbudget.od.nih.gov/pdfs/FY18/
BRDPI%20Table%20FY%201950%20to%
202022_Jan%202017.pdf
163
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
CHAIR
Joshua Gordon, M.D., Ph.D.
Director
National Institute of Mental Health
National Institutes of Health
Rockville, MD
FEDERAL MEMBERS
James F. Battey, M.D., Ph.D.
Director
National Institute on Deafness and Other
Communication Disorders
National Institutes of Health
Bethesda, MD
Diana W. Bianchi, M.D.
Director
Eunice Kennedy Shriver National Institute of
Child Health and Human Development
National Institutes of Health
Bethesda, MD
Linda Birnbaum, Ph.D., D.A.B.T., A.T.S.
Director
National Institute of Environmental Health
Sciences and National Toxicology Program
National Institutes of Health
Research Triangle Park, NC
Francis S. Collins, M.D., Ph.D.
Director
National Institutes of Health
Bethesda, MD
Ruth Etzel, M.D., Ph.D.
Director
Office of Children’s Health Protection
Environmental Protection Agency
Washington, DC
Tiffany R. Farchione, M.D.
Medical Officer
Division of Psychiatry Products
Center for Drug Evaluation and Research
U.S. Food and Drug Administration
Silver Spring, MD
Melissa L. Harris
Acting Deputy Director
Disabled and Elderly Health Programs Group
Centers for Medicare and CHIP Services
Centers for Medicare and Medicaid Services
Baltimore, MD
Laura Kavanagh, M.P.P.
Director
Division of Research, Training and Education
Maternal and Child Health
Health Resources and Services Administration
Rockville, MD
INTERAGENCY AUTISM COORDINATING
COMMITTEE MEMBER ROSTER
164
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Walter J. Koroshetz, M.D.
Deputy Director
National Institute of Neurological Disorders
and Stroke
National Institutes of Health
Bethesda, MD
Laura Pincock, Pharm.D., M.P.H.
Pharmacist Officer
Agency for Healthcare Research and Quality
Rockville, MD
Marcella Ronyak, Ph.D., L.C.S.W., C.D.P.
Deputy Director
Division of Behavioral Health
Indian Health Service Headquarters
Stuart K. Shapira, M.D., Ph.D.
Associate Director
Science and Chief Medical Officer
National Center on Birth Defects
and Developmental Disabilities
Atlanta, GA
Melissa Spencer
Deputy Associate Commissioner
Office of Disability Policy
Social Security Administration
Baltimore, MD
Larry Wexler, Ed.D.
Director
Research to Practice
Office of Special Education Programs
U.S. Department of Education
Washington, DC
Nicole M. Williams, Ph.D.
Program Manager
Congressionally Directed Medical
Research Programs
U.S. Department of Defense
Frederick, MD
PUBLIC MEMBERS
David Amaral, Ph.D.
Distinguished Professor
Department of Psychiatry & Behavioral Science
University of California, Davis (UC)
Research Director
UC Davis MIND Institute
University of California – Davis
Sacramento, CA
James Ball, Ed.D., B.C.B.A.-D.
President and CEO
JB Autism Consulting
Executive Chair, Board of Directors
Autism Society
Cranbury, NJ
Samantha Crane, J.D.
Legal Director and Director of Public Policy
Autistic Self Advocacy Network
Washington, DC
Geraldine Dawson, Ph.D.
Professor
Department of Psychiatry and Behavioral Science
Duke University Medical Center
Director
Duke Center for Autism and Brain Development
President
International Society for Autism Research
Durham, NC
165
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Amy Goodman, M.A.
Self-Advocate
Charles Town, WV
Shannon Haworth, M.A.
Senior Program Manager
Association of University Centers on Disabilities
Silver Spring, MD
David S. Mandell, Sc.D.
Director
Center for Mental Health Policy
and Services Research
Associate Professor
Psychiatry and Pediatrics
Perelman School of Medicine
University of Pennsylvania
Philadelphia, PA
Brian Parnell, M.S.W.
Administrator, Medicaid Autism Waiver
& Community Supports Waiver
Division of Services for People with Disabilities
Utah Department of Human Services
Draper, UT
Kevin Pelphrey, Ph.D.
Carbonell Family Professor in Autism
and Neurodevelopmental Disorders
Professor in the Department of Pharmacology
and Physiology and Department of Pediatrics
Director, Autism and Neurodevelopmental
Disorders Institute
George Washington University
and Children's National Medical Center
Washington, DC
Edlyn Peña, Ph.D.
Associate Professor, Educational Leadership
and Director of Doctoral Studies
California Lutheran University
Thousand Oaks, CA
Louis Reichardt, Ph.D.
Director
Simons Foundation Autism Research Initiative
New York, NY
Robert H. Ring, Ph.D.
Chief Executive Officer
Vencerx Therapeutics
Princeton, NJ
John Elder Robison
Self-Advocate, Parent, and Author
Amherst, MA
Alison Tepper Singer, M.B.A.
Parent and Family Member
Founder and President
Autism Science Foundation
New York, NY
Julie Lounds Taylor, Ph.D.
Assistant Professor of Pediatrics
and Special Education
Vanderbilt University Investigator, Vanderbilt
Kennedy Center
Nashville, TN
166
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
IACC ALTERNATES
Josie Briggs, M.D.
(for Francis S. Collins, M.D., Ph.D.)
Director, National Center for Complementary
and Integrative Health
National Institutes of Health
Bethesda, MD
Deborah (Daisy) Christensen, Ph.D.
(for Stuart K. Shapira, M.D., Ph.D.)
Epidemiologist, Surveillance Team Lead
Developmental Disabilities Branch
National Center on Birth Defects
and Developmental Disabilities
Centers for Disease Control and Prevention
Atlanta, GA
Judith A. Cooper, Ph.D.
(for James F. Battey, M.D., Ph.D.)
Deputy Director, National Institute on Deafness
and Other Communication Disorders
Director, Division of Scientific Programs
National Institutes of Health
Bethesda, MD
Jennifer Johnson, Ed.D.
(for Administration for Community Living)
Deputy Director, Administration on Intellectual
and Developmental Disabilities
Administration for Community Living
Washington, DC
Alice Kau, Ph.D.
(for Diana W. Bianchi, M.D.)
Program Director, Eunice Kennedy Shriver
National Institute of Child Health
and Human Development
National Institutes of Health
Bethesda, MD
Cindy Lawler, Ph.D.
(for Linda Birnbaum, Ph.D., D.A.B.T., A.T.S.)
Chief, Genes, Environment and Health Branch
National Institute of Environmental Health Sciences
National Institutes of Health
Research Triangle Park, NC
Laura Mamounas, Ph.D.
(for Walter Koroshetz, M.D.)
Program Director, Neurogenetics Cluster
National institute of Neurological Disorders
and Stroke
Bethesda, MD
Shui-Lin (Stan) Niu, Ph.D.
(for Nicole Williams, Ph.D.)
Science Officer, Congressionally Directed
Medical Research Programs
U.S. Department of Defense
Frederick, MD
Robyn Schulhof, M.A.
(for Laura Kavanagh, M.P.P.)
Senior Public Health Analyst, Maternal
and Child Health Bureau
Health Resources and Services Administration
Rockville, MD
167
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
The Committee would like to thank the following individuals who volunteered their time to assist
with the development of the 2016-2017 IACC Strategic Plan for ASD.
QUESTION 1 WORKING GROUP
CO-CHAIRS
Alice Kau, Ph.D*
Health Scientist Administrator
Eunice Kennedy Shriver National Institute of
Child Health and Human Development
National Institutes of Health
Bethesda, MD
Ann E. Wagner, Ph.D
Program Chief
Neurobehavioral Mechanisms of
Mental Disorders Branch
Division of Developmental Translational Research
National Institute of Mental Health
National Institutes of Health
Bethesda, MD
PARTICIPANTS
Daniel Coury, M.D.
Section Chief
Behavioral Health Services
Section Chief
Child Development Center
Physician Team
Developmental and Behavioral Pediatrics
Program Director
Developmental/Behavioral Pediatrics Fellowship
Nationwide Children’s Hospital
Columbus, OH
Shannon Haworth, M.A.
Senior Program Manager
Association of University Centers on Disabilities
Silver Spring, MD
Jennifer Johnson, Ed.D.*
Deputy Director
Administration on Intellectual and
Developmental Disabilities
Administration for Community Living
Washington, DC
Ami Klin, Ph.D.
Director
Marcus Autism Center
Children's Healthcare of Atlanta
Georgia Research Alliance Eminent Scholar
Professor & Chief
Division of Autism and Related Disorders
Department of Pediatrics
Emory University School of Medicine
Center for Translational Social Neuroscience
Emory University
Atlanta, GA
STRATEGIC PLAN WORKING
GROUP MEMBERS
168
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Catherine Lord, Ph.D.
Professor of Psychology
Psychiatry and Founding Director
Center for Autism and Developing Brain
New York-Presbyterian Hospital
Weill Cornell Medical College
New York, NY
Sandy Magaña, Ph.D., M.S.W.
Professor
University of Illinois at Chicago
Department of Disability and Human Development
Chicago, IL
Karen Pierce, Ph.D.
Associate Professor
Department of Neurosciences
Co-Director
Autism Center
University of California – San Diego
La Jolla, CA
Diana L. Robins, Ph.D.
Associate Professor
Program Area Leader in Early Detection
& Intervention
AJ Drexel Autism Institute
Drexel University
Philadelphia, PA
Angela Scarpa, Ph.D.
Founder and Co-Director
VT Autism Clinic (VTAC)
Director
VT Center for Autism Research (VTCAR)
Associate Professor
Department of Psychology
Virginia Tech
Blacksburg, VA
*
indicates IACC Member
Audrey Thurm, Ph.D.
Staff Scientist
Pediatrics and Developmental Neuroscience
National Institute of Mental Health
National Institutes of Health
Bethesda, MD
Debra Wagler, M.A., MComm.
Public Health Analyst
Region VIII
Maternal and Child Health Bureau
Health Resources and Services Administration
Rockville, MD
Amy M. Wetherby, Ph.D.
Dept. of Clinical Sciences
College of Medicine
Distinguished Research Professor
L.L. Schendel Professor of Communication Science
& Disorders
Florida State University
Tallahassee, FL
Lisa D. Wiggins, Ph.D.
Epidemiologist
National Center on Birth Defects
and Developmental Disabilities
Centers for Disease Control and Prevention
Atlanta, GA
Nicole Williams, Ph.D.*
Program Manager
Congressionally Directed Medical Research Programs
U.S. Department of Defense
Frederick, MD
169
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION 2 WORKING GROUP
CO-CHAIRS
Walter Koroshetz, M.D.*
Director
National Institute of Neurological Disorders
and Stroke
National Institutes of Health
Bethesda, MD
Louis Reichardt, Ph.D.*
Director
Simons Foundation Autism Research Initiative
New York, NY
PARTICIPANTS
David Amaral, Ph.D.*
Distinguished Professor
Department of Psychiatry & Behavioral Sciences
Research Director
UC Davis MIND Institute
University of California – Davis
Sacramento, CA
James F. Battey, M.D., Ph.D.*
Director
National Institute on Deafness
and Other Communication Disorders
National Institutes of Health
Bethesda, MD
Katarzyna Chawarska, Ph.D.
Associate Professor
Child Study Center and Pediatrics
Temple Medical Center
New Haven, CT
Graeme Davis, Ph.D.
Professor
Neuroscience Graduate Program
University of California – San Francisco
San Francisco, CA
Guoping Feng, Ph.D.
Poitras Professor of Neuroscience
McGovern Institute for Brain Research
Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology
Director of Model Systems and Neurobiology
Stanley Center for Psychiatric Research
Broad Institute of MIT and Harvard
Cambridge, MA
Heather Cody Hazlett, Ph.D.
Assistant Professor
The University of North Carolina
Chapel Hill, NC
Shafali Spurling Jeste, M.D.
Associate Professor in Psychiatry and Neurology
University of California – Los Angeles
David Geffen School of Medicine
Los Angeles, CA
Eric Klann, Ph.D.
Professor
Center for Neural Science
New York University
New York, NY
170
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
James McPartland, Ph.D.
Associate Professor of Child Psychiatry
and Psychology
Director
Yale Developmental Disabilities Clinic
Yale Child Study Center
New Haven, CT
Christine Nordahl, Ph.D.
Assistant Professor
Department of Psychiatry and
Behavioral Science
UC Davis MIND Institute
University of California – Davis
Sacramento, CA
Kevin Pelphrey, Ph.D.*
Carbonell Family Professor in Autism
and Neurodevelopmental Disorders
Professor in the Department of Pharmacology
and Physiology and Department of Pediatrics
Director, Autism and Neurodevelopmental
Disorders Institute
George Washington University
and Children's National Medical Center
Washington, DC
Elizabeth Redcay, Ph.D.
Assistant Professor of Psychology
Director
Developmental Social Neuroscience Lab
University of Maryland
College Park, MD
Robert H. Ring, Ph.D.*
Chief Executive Officer
Vencerx Therapeutics
Princeton, NJ
Flora Vaccarino, M.D.
Harris Professor
Child Study Center
and Department of Neurobiology
Yale University
New Haven, CT
Nicole Williams, Ph.D.*
Program Manager
Congressionally Directed Medical Research Programs
U.S. Department of Defense
Frederick, MD
QUESTION 3 WORKING GROUP
CO-CHAIRS
David Amaral, Ph.D.*
Distinguished Professor
Department of Psychiatry & Behavioral Sciences
Research Director
UC Davis MIND Institute
University of California – Davis
Sacramento, CA
*indicates IACC Member
Cindy Lawler, Ph.D.
Chief
Genes, Environment and Health Branch
National Institute of Environmental Health Sciences
National Institutes of Health
Research Triangle Park, NC
171
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
PARTICIPANTS
Raphael Bernier, Ph.D.
Associate Professor
Department of Psychiatry & Behavioral Sciences
Clinical Director
Seattle Children's Autism Center
Associate Director
Center on Human Development and Disability
University of Washington
Seattle, WA
Evan Eichler, Ph.D.
Professor and HHMI Investigator
University of Washington
Seattle, WA
Ruth Etzel, M.D., Ph.D.*
Director
Office of Children’s Health Protection
Office of Environmental Protection Agency
Environmental Protection Agency
Washington, DC
Dani Fallin, Ph.D.
Professor
Bloomberg School of Public Health
John Hopkins University
Baltimore, MD
Daniel Geschwind, Ph.D.
Senior Associate Dean
Associate Vice Chancellor
Precision Medicine
University of California – Los Angeles
Los Angeles, CA
Alycia Halladay, Ph.D.
Chief Science Officer
Autism Science Foundation
New York, NY
Irva Hertz-Picciotto, Ph.D.
Director
UC Davis Environmental Health Sciences Core Center
Professor & Vice Chair for Research
Department of Public Health Sciences
Director
MIND Institute Program in Environmental
Epidemiology of Autism and Neurodevelopment
Co-Executive Director
Project TENDR (Targeting Environmental
NeuroDevelopment Risks)
University of California – Davis
Davis, CA
Elaine Hsiao, Ph.D.
Professor
Life Science, Integrative Biology and Physiology
University of California
Los Angeles, CA
Craig Newschaffer, Ph.D.
Professor
Director
A.J. Drexel Autism Institute
Philadelphia, PA
Elise Robinson, Ph.D.
Affiliated Scientist
Broad Institute
Cambridge, MA
Stephan Sanders, Ph.D.
Assistant Professor
Psychiatry
UCSF School of Medicine
University of California – San Francisco
San Francisco, CA
172
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Steve Scherer, Ph.D, F.R.S.C.
Director
The Centre for Applied Genomics
Senior Scientist,
Genetics & Genomic Biology
The Hospital for Sick Children
Director
McLaughlin Centre for Molecular Medicine
Professor
Department of Molecular Genetics
University of Toronto
Toronto, Canada
Laura A. Schieve, Ph.D.
Team Lead
Epidemiology Team
Developmental Disabilities Branch
Division of Congenital and Developmental Disorders
National Center on Birth Defects
and Developmental Disabilities
Centers for Disease Control and Prevention
Atlanta, GA
Joan A. Scott, M.S., C.G.C.
Deputy Director
Division of Services for Children with Special Health Needs
Health Resources and Services Administration
Maternal and Child Health Bureau
Rockville, MD
Alison Tepper Singer, M.B.A.*
President
Autism Science Foundation
New York, NY
QUESTION 4 WORKING GROUP
CHAIR
Kevin Pelphrey, Ph.D.*
Carbonell Family Professor
Autism and Neurodevelopmental Disorders
Professor
Department of Pharmacology and Physiology
and Department of Pediatrics
Director
Autism and Neurodevelopmental Disorders Institute
George Washington University
and Children's National Medical Center
Washington, DC
*indicates IACC Member
173
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
PARTICIPANTS
James Ball, Ed.D.*
President and CEO
JB Autism Consulting
Cranbury, NJ
Timothy Buie, M.D.
Director
Gastroenterology and Nutation
at the Laure Center for Autism
Massachusetts General Hospital
Boston, MA
Samantha Crane, J.D.*
Legal Director and Director of Public Policy
Autistic Self Advocacy Network
Washington, DC
Geraldine Dawson, Ph.D.*
Professor
Department of Psychiatry and
Behavioral Science
Duke University School of Medicine
Director
Duke Center for Autism and
Brain Development
President
International Society for Autism Research
Durham, NC
Tiffany R. Farchione, M.D.*
Deputy Director
Division of Psychiatry Products
Center for Drug Evaluation and Research
US Food and Drug Administration
Silver Spring, MD
Melissa L. Harris*
Acting Deputy Director
Disabled and Elderly Health Programs Group
Center for Medicare and CHIP Services
Centers for Medicare and Medicaid Services
Baltimore, MD
Connie Kasari, Ph.D.
Professor
Psychological Studies
Education and Psychiatry
University of California - Los Angeles
Los Angeles, CA
Elisabeth Kato*
Medical Officer
Agency for Healthcare Research and Quality
Rockville, MD
Alice Kau, Ph.D*
Health Scientist Administrator
Eunice Kennedy Shriver National Institute of
Child Health and Human Development
National Institutes of Health
Bethesda, MD
Christy Kavulic
Associate Division Director
Early Childhood Team
Office of Special Education Program
U.S. Department of Education
Washington, DC
Alex Kolevzon, M.D.
Professor of Psychiatry and Pediatrics
Director
Child and Adolescent Psychiatry
Clinical Director
Seaver Autism Center
Icahn School of Medicine at Mounttn Sinai
New York, NY
Elizabeth Laugeson, Ph.D.
Director
Early Childhood Clubhouse Program
Clinical Instructor
Center for Autism Research and Treatment
David Geffen School of Medicine
Los Angeles, CA
174
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Alexander Leonessa
National Science Foundation
Arlington, Virginia
Beth Malow, M.D.
Professor
Vanderbilt Department of Neurology
Vanderbilt University Medical Center
Nashville, TN
Nancy J. Minshew, M.D.
Endowed Chair in Autism Research
Professor of Psychiatry and Neurology
Department of Psychiatry
University of Pittsburgh
Pittsburgh, PA
Samuel L. Odom, Ph.D.
Director
Frank Porter Graham Child Development Institute
University of North Carolina at Chapel Hill
Chapel Hill, NC
Louis Reichardt, Ph.D.*
Director
Simons Foundation Autism Research Initiative
New York, NY
Robert H. Ring, Ph.D.*
Chief Executive Officer
Vencerx Therapeutics
Princeton, NJ
Mustafa Sahin, M.D., Ph.D.
Associate Professor of Neurology
Harvard Medical School
Assistant in Neurology
Boston Children’s Hospital
Boston, MA
*
indicates IACC Member
Frederick Shic, Ph.D.
Assistant Professor
Child Study Center and Computer Science
Director
Technology and Innovation Laboratory
Associate Director
Yale Early Social Cognition Lab
Yale Child Study Center
Yale School of Medicine
New Haven, CT
Phillip S. Strain, Ph.D.
Director
PELE Center/Professor
ED. Psych & Early Childhood SPED
University of Colorado – Denver
Denver, CO
Denis G. Sukhodolsky, Ph.D.
Assistant Professor
Child Study Center
Yale School of Medicine
New Haven, CT
Zachary Warren, Ph.D.
Associate Professor of Pediatrics, Psychiatry,
& Special Education
Executive Director
Treatment and Research Institute for
Autism Spectrum Disorders
Director
Autism Clinical Services
Department of Pediatrics and Vanderbilt
Kennedy Center
Nashville, TN
175
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
QUESTION 5 WORKING GROUP
CO-CHAIRS
Shannon Haworth, M.A.
Senior Program Manager
Association of University Centers on Disabilities
Silver Spring, MD
David S. Mandell, Sc.D.*
Director
Center for Mental Health Policy and Services Research
Associate Professor
Psychiatry and Pediatrics
Perelman School of Medicine
University of Pennsylvania
Philadelphia, PA
PARTICIPANTS
Lauren Brookman-Frazee, Ph.D.
Associate Professor
Department of Psychiatry
University of California – San Diego
San Diego, CA
Robert Cimera, Ph.D.
Professor
Lifespan Development & Educational Science
Kent State University
Kent, OH
Samantha Crane, J.D.*
Legal Director and Director of Public Policy
Autistic Self Advocacy Network
Washington, DC
Daniel Davis
Health Insurance Specialist
Center for Integrated Programs
Administration for Community Living
U.S. Department of Health and Human Services
Washington, DC
Melissa L. Harris*
Acting Deputy Director
Disabled and Elderly Health Programs Group
Center for Medicare and CHIP Services
Centers for Medicare and Medicaid Services
Baltimore, MD
Peter F. Gerhardt, Ed.D.
President
Peter Gerhardt Associates, LLC
New York, NY
Lisa Goring
Executive Vice President
Programs and Services
Autism Speaks
New York, NY
Laura Kavanagh, M.P.P.*
Deputy Associate Administrator
Maternal and Child Health Bureau
Health Resources and Services Administration
Rockville, MD
176
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Leticia Manning, M.P.H.
Lieutenant Commander
United States Public Health Service
Maternal and Child Health Bureau
Division of Services for Children with
Special Health Needs
Health Resources and Services Administration
Rockville, MD
Cathy Pratt, Ph.D., BCBA-D
Director
Indiana Resource Center for Autism
Indiana University Bloomington
Bloomington, IN
Anne Roux, M.P.H.
Research Scientist
Life Course Outcomes
Research Program
A.J. Drexel Autism Institute
Drexel University
Philadelphia, PA
Aubyn Stahmer, Ph.D.
Associate Professor
Psychiatry and Behavioral Sciences
UC Davis MIND Institute
University of California – Davis
Sacramento, CA
Jane A. Tilly
Administration for Community Living
Administration on Aging
U.S. Department of Health and Human Services
Washington, DC
Larry Wexler, Ed.D.*
Director
Research to Practice Division
Office of Special Education Programs
U.S. Department of Education
Washington, DC
Juliann Woods, Ph.D., CCC-SLP
Professor and Associate Dean
Research School of Communication Science
and Disorders
Florida State University
Tallahassee, FL
QUESTION 6 WORKING GROUP
CHAIR
Julie Lounds Taylor, Ph.D.*
Assistant Professor of Pediatrics and Special Education
Vanderbilt University
Investigator
Vanderbilt Kennedy Center
Nashville, TN
*indicates IACC Member
177
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
PARTICIPANTS
Scott Badesch
President/Chief Executive Officer
Autism Society
Bethesda, MD
Vanessa Hus Bal, Ph.D.
Postdoctoral Scholar
Department of Psychiatry
University of California - San Francisco
San Francisco, CA
Somer L. Bishop, Ph.D.
Assistant Professor
Department of Psychiatry
University of California - San Francisco
San Francisco, CA
Leslie J. Caplan, Ph.D.
Rehabilitation Program Specialist
National Institute on Disability, Independent Living,
and Rehabilitation Research
Administration for Community Living
U.S. Department of Health and Human Services
Washington, DC
Nancy Cheak-Zamora, Ph.D.
Assistant Professor
Department of Health Science
University of Missouri School of Health Professions
Columbia, MO
Samantha Crane, J.D.*
Legal Director and Director of Public Policy
Autistic Self Advocacy Network
Washington, DC
Leann Smith DaWalt, Ph.D.
Senior Scientist
Waisman Center
University of Wisconsin – Madison
Madison, WI
Amy Goodman, M.A.*
Self-Advocate
Laura Grofer Klinger, Ph.D.
Director
TEACCH Autism Program
Associate Professor of Psychiatry
University of North Carolina – Chapel Hill
Chapel Hill, NC
Kevin Pelphrey, Ph.D.*
Carbonell Family Professor
Autism and Neurodevelopmental Disorders
Professor in the Department of Pharmacology
and Physiology and Department of Pediatrics
Director
Autism and Neurodevelopmental Disorders Institute
George Washington University and
Children's National Medical Center
Washington, DC
Edlyn Peña, Ph.D.*
Associate Professor
Educational Leadership
Director of Doctoral Studies
California Lutheran University
Thousand Oaks, CA
JaLynn Prince
President and Founder
Madison House Autism Foundation
Rockville, MD
Robyn Schulhof, M.A.*
Senior Public Health Analyst
Maternal and Child Health Bureau
Health Resources and Services Administration
Rockville, MD
178
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Paul Shattuck, Ph.D.
Associate Professor
Leader – Life Course Outcomes Research Program
A.J. Drexel Autism Institute
Philadelphia, PA
Alison Tepper Singer, M.B.A.*
President
Autism Science Foundation
New York, NY
Susan White, Ph.D.
Faculty
Department of Psychology
Core Faculty
Clinical Science
Co-Director
Virginia Tech Autism Clinic
Virginia Tech
Blacksburg, VA
QUESTION 7 WORKING GROUP
CHAIR
Alison Tepper Singer, M.B.A.*
President
Autism Science Foundation
New York, NY
PARTICIPANTS
Deborah (Daisy) Christensen, Ph.D.*
Epidemiologist
Surveillance Team Lead
Developmental Disabilities Branch
National Center on Birth Defect and
Developmental Disabilities
Centers for Disease Control and Prevention
Atlanta, GA
Samantha Crane, J.D.*
Legal Director and Director of Public Policy
Autistic Self Advocacy Network
Washington, DC
Adriana DiMartino, Ph.D.
Assistant Professor
Department of Child and Adolescent Psychiatry
New York University School of Medicine
New York, NY
Maureen Durkin, Ph.D., DrPH
Professor
Population Health Sciences and Pediatrics
University of Wisconsin School of Medicine
and Public Health
Professor
Population Health Sciences and Pediatrics
Vice-Chair
Department of Population Health Sciences
Director
Population Health Graduate Program
University of Wisconsin School of Medicine
and Public Health
Madison, WI
179
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
Michelle Freund, Ph.D.
Project Officer
National Institute of Mental Health
National institute of Health
Rockville, MD
Dan Hall
Manager
National Database for Autism Research
National Institute of Mental Health
National Institutes of Health
Rockville, MD
Robin L. Harwood, Ph.D.
Health Scientist
Division of Research
Office of Epidemiology and Research
Health Resources and Services Administration
Maternal and Child Health Bureau
Rockville, MD
Paul Lipkin, M.D.
Director
Medical Informatics
Kennedy Krieger Institute
Director
Interactive Autism Network
Kennedy Krieger Institute
Associate Professor of Pediatrics
Johns Hopkins Medicine
Baltimore, MD
David S. Mandell, Sc.D.*
Director
Center for Mental Health Policy and
Services Research
Associate Professor
Psychiatry and Pediatrics
Perelman School of Medicine
University of Pennsylvania
Philadelphia, PA
Gretchen Navidi
Program Coordination Manager
Office of Technology Development and Coordination
Office of the NIMH Director
National Institute of Mental Health
National Institutes of Health
Bethesda, MD
Jessica Rast, M.P.H.
Research Associate
Life Course Outcomes Research Program
A.J. Drexel Autism Institute
Drexel University
Philadelphia, PA
Catherine Rice, Ph.D.
Professor
Psychiatry and Behavioral Sciences
Director, Emory Autism Center
Emory University School of Medicine
Atlanta, GA
Robert H. Ring, Ph.D.*
Chief Executive Officer
Vencerx Therapeutics
Princeton, NJ
Michael Rosanoff, M.P.H.
Director
Public Health Research
Autism Speaks
New York, NY
Andy Shih, Ph.D.
Senior VP
Scientific Affairs
Autism Speaks
New York, NY
180
2016-2017 IACC STRATEGIC PLAN FOR AUTISM SPECTRUM DISORDER
OFFICE OF AUTISM RESEARCH
COORDINATION (OARC)
National Institute of Mental Health, National Institutes of Health
Susan A. Daniels, Ph.D.
Director
Oni Celestin, Ph.D.
Health Science Policy Analyst
Rebecca Martin, M.P.H.
Public Health Analyst
Angelice Mitrakas, B.A.
Management Analyst
Karen Mowrer, Ph.D.
Health Science Policy Analyst
Julianna Rava, M.P.H.
Health Science Policy Analyst
Jeffrey Wiegand, B.S.
Web Development Manager
Email: IACCP[email protected]
Website: http://www.iacc.hhs.gov
U.S. Department of Health and Human Services
www.hhs.gov