AI Article Synopsis

  • Autism spectrum disorder (ASD) is a complex genetic disorder with only about 65 out of several hundred potential causal genes identified.
  • Researchers used a machine-learning approach to predict autism risk genes across the genome, finding many candidates with little prior genetic evidence.
  • The study revealed that ASD genes align with key brain developmental pathways and proposed specific genes linked to autism-associated genetic variations.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5803797PMC
http://dx.doi.org/10.1038/nn.4353DOI Listing

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