While there has been great progress in understanding the genomic architecture of autism, only a moderate number of the hundreds of genes and genomic regions thought to be involved in ASD have been identified. Next-generation sequencing (NGS) has proven its utility to rapidly identify variants underlying ASD, and this approach is being carried out in ca. 6,000 independent ASD samples through multiple studies. There is an urgent need to develop a framework to integrate and expand these current studies, and to jointly analyze emerging data to maximize the identification of valid ASD loci, because validated risk variants present opportunities for genetic counseling, understanding pathogenesis, and drug development. The Autism Sequencing Consortium (ASC) represents a coordinated effort by more than 20 independent groups to rapidly identify and validate ASD risk genes, which represent lead targets for neurobiological analyses and drug discovery. The long-term goal of the ASC is to make use of genetics to identify therapeutic targets in ASD, while contributing to translating such research findings to clinical practice. The overall objective of tis proposal is to rapidly identify ASD genes representing lead targets for high impact neurobiological studies and drug discovery. Our central hypothesis - formulated based on data with SNV, indels, and CNV, as well as review of medical genetic conditions in ASD and targeted sequencing in ASD - is that multiple independent rare variants account for a very significant proportion of risk to ASD. Our rationale for this proposal is that the identification of genetic variants conferring high-risk risk to ASD and associated neurodevelopmental disorders can form the bases of studies to understand pathogenesis as well as the bases for novel therapies. Moreover, such variants have direct implications for patients and their families in terms of etiological diagnosis, genetic counseling and patient care. These objectives will be accomplished with the following Specific Aims: 1) Maintain the infrastructure to support the ASC objectives;2) Deploy pipelines for data cleaning and harmonization and variant calling;3) Implement novel statistical methods for identifying ASD-associated genes;and, 4) Carry out whole-exome sequencing of 3,000 ASD subjects and parents. This contribution is significant because it represents the first step in research to understand pathogenesis of ASD and to the development of pharmacological strategies for treatment of core symptoms of ASD and etiologically related neurodevelopmental disorders. The research proposed in this application is innovative, in our opinion, because it involves an entirely new model of sharing data before publication, uses state-of-the-art methods for calling diverse types of variants in NGS data, incorporates novel methods for updating variant calling and sharing data, and includes highly innovative statistical methods to identify risk loci. This is a new and substantively different approach to gene discovery in ASD that departs significantly from the status quo and provides the means to achieve these important goals.

Public Health Relevance

The proposed research is relevant to public health because a better understanding of risk in autism will lead to improved methods for prevention and treatment. It is also relevant to the NIH mission and to the IACC recommendations around identifying genetic risk in at least 50% of people with ASD, including an exploration of de novo variation.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project--Cooperative Agreements (U01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-PSE-P (60))
Program Officer
Koester, Susan E
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Broad Institute, Inc.
United States
Zip Code
Werling, Donna M; Brand, Harrison; An, Joon-Yong et al. (2018) An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder. Nat Genet 50:727-736
Kosmicki, Jack A; Samocha, Kaitlin E; Howrigan, Daniel P et al. (2017) Refining the role of de novo protein-truncating variants in neurodevelopmental disorders by using population reference samples. Nat Genet 49:504-510
Lim, Elaine T; Uddin, Mohammed; De Rubeis, Silvia et al. (2017) Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder. Nat Neurosci 20:1217-1224
Ware, James S; Samocha, Kaitlin E; Homsy, Jason et al. (2015) Interpreting de novo Variation in Human Disease Using denovolyzeR. Curr Protoc Hum Genet 87:7.25.1-15
Sanders, Stephan J; He, Xin; Willsey, A Jeremy et al. (2015) Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci. Neuron 87:1215-1233
De Rubeis, Silvia; He, Xin; Goldberg, Arthur P et al. (2014) Synaptic, transcriptional and chromatin genes disrupted in autism. Nature 515:209-15
Samocha, Kaitlin E; Robinson, Elise B; Sanders, Stephan J et al. (2014) A framework for the interpretation of de novo mutation in human disease. Nat Genet 46:944-50
He, Xin; Sanders, Stephan J; Liu, Li et al. (2013) Integrated model of de novo and inherited genetic variants yields greater power to identify risk genes. PLoS Genet 9:e1003671
Buxbaum, Joseph D; Daly, Mark J; Devlin, Bernie et al. (2012) The autism sequencing consortium: large-scale, high-throughput sequencing in autism spectrum disorders. Neuron 76:1052-6