Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder

Arjun Krishnan, Ran Zhang, Victoria Yao, Chandra L. Theesfeld, Aaron K. Wong, Alicja Tadych, Natalia Volfovsky, Alan Packer, Alex Lash, Olga G. Troyanskaya

Research output: Contribution to journalArticlepeer-review

124 Scopus citations

Abstract

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic basis. Yet, only a small fraction of potentially causal genes - about 65 genes out of an estimated several hundred - are known with strong genetic evidence from sequencing studies. We developed a complementary machine-learning approach based on a human brain-specific gene network to present a genome-wide prediction of autism risk genes, including hundreds of candidates for which there is minimal or no prior genetic evidence. Our approach was validated in a large independent case-control sequencing study. Leveraging these genome-wide predictions and the brain-specific network, we demonstrated that the large set of ASD genes converges on a smaller number of key pathways and developmental stages of the brain. Finally, we identified likely pathogenic genes within frequent autism-associated copy-number variants and proposed genes and pathways that are likely mediators of ASD across multiple copy-number variants. All predictions and functional insights are available at http://asd.princeton.edu.

Original languageEnglish (US)
Pages (from-to)1454-1462
Number of pages9
JournalNature neuroscience
Volume19
Issue number11
DOIs
StatePublished - Oct 26 2016

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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