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Genome-wide characterization of genetic and functional dysregulation in autism spectrum disorder

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

Posted 09 Jun 2016
bioRxiv DOI: 10.1101/057828 (published DOI: 10.1038/nn.4353)

Autism spectrum disorder (ASD) is a range of major neurodevelopmental disabilities with a strong genetic basis. Yet, owing to extensive genetic heterogeneity, multiple modes of inheritance and limited study sizes, sequencing and quantitative genetics approaches have had limited success in characterizing the complex genetics of ASD. Currently, only a small fraction of potentially causal genes -about 65 genes out of an estimated several hundred- are known based on strong genetic evidence. Hence, there is a critical need for complementary approaches to further characterize the genetic basis of ASD, enabling development of better screening and therapeutics. Here, we use a machine-learning approach based on a human brain-specific functional gene interaction network to present a genome-wide prediction of autism-associated genes, including hundreds of candidate genes for which there is minimal or no prior genetic evidence. Our approach is validated in an independent case-control sequencing study of approximately 2,500 families. Leveraging these genome-wide predictions and the brain-specific network, we demonstrate that the large set of ASD genes converges on a smaller number of key cellular pathways and specific developmental stages of the brain. Specifically, integration with spatiotemporal transcriptome expression data implicates early fetal and midfetal stages of the developing human brain in ASD etiology. Likewise, analysis of the connectivity of top autism genes in the brain-specific interaction network reveals the breadth of autism-associated functional modules, processes, and pathways in the brain. Finally, we identify likely pathogenic genes within the most frequent autism-associated copy-number-variants (CNVs) and propose genes and pathways that are likely mediators of autism across multiple CNVs. All the predictions, interactions, and functional insights from this work are available to biomedical researchers at asd.princeton.edu. NOTE: The first two authors AK and RZ are co-first authors and are listed alphabetically. The last two authors AL and OGT are co-corresponding authors.

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