@article{2534,
  keywords = {Humans, Gene Regulatory Networks, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease, Genome-Wide Association Study, DNA Copy Number Variations, Autism Spectrum Disorder},
  author = {Arjun Krishnan and Ran Zhang and Victoria Yao and Chandra Theesfeld and Aaron Wong and Alicja Tadych and Natalia Volfovsky and Alan Packer and Alex Lash and Olga Troyanskaya},
  title = {Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder.},
  abstract = {<p>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.</p>
},
  year = {2016},
  journal = {Nat Neurosci},
  volume = {19},
  pages = {1454-1462},
  month = {11/2016},
  issn = {1546-1726},
  doi = {10.1038/nn.4353},
  language = {eng},
}