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|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.|
|Electronic Publication Date:||1-Aug-2016|
|Citation:||Krishnan, A, Zhang, R, Yao, V, Theesfeld, CL, Wong, AK, Tadych, A, Volfovsky, N, Packer, A, Lash, A, Troyanskaya, OG. (2016). Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder. Nature Neuroscience, 19 (1454 - 1462. doi:10.1038/nn.4353|
|Pages:||1454 - 1462|
|Type of Material:||Journal Article|
|Journal/Proceeding Title:||Nature Neuroscience|
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