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

316 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

  • General Neuroscience

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