TY - JOUR T1 - Exonic somatic mutations contribute risk for autism spectrum disorder JF - bioRxiv DO - 10.1101/083428 SP - 083428 AU - Deidre R Krupp AU - Rebecca A Barnard AU - Yannis Duffourd AU - Sara Evans AU - Raphael Bernier AU - Jean-Baptist Rivière AU - Eric Fombonne AU - Brian J O'Roak Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/10/26/083428.abstract N2 - Genetic risk factors for autism spectrum disorder (ASD) have yet to be fully elucidated. Somatic mosaic mutations (SMMs) have been implicated in several neurodevelopmental disorders and overgrowth syndromes. Here, we systematically evaluate SMMs by leveraging whole-exome sequencing (WES) data on a large family-based ASD cohort, the Simons Simplex Collection (SSC). We find evidence that ~10% of previously published de novo mutations are potentially SMMs. When using a custom somatic calling pipeline, we recalled all SSC WES data. We validated high and low confidence mutation predictions for a subset of families with single molecule molecular inversion probes. With these validation data, we iteratively developed a high confidence calling approach integrating logistic regression modeling and additional heuristics and applied it to the full cohort. Surprisingly, we found evidence of significant synonymous SMM burden in probands, with mutations more likely to be close to splicing sites. Overall, we observe no strong evidence of missense SMM burden. However, we do observe nominally significant signal for missense SMMs in those families without germline mutations, which strengthens specifically in genes intolerant to mutations. In contrast to missense germline mutations, missense SMMs show potential enrichment for chromatin modifiers. We observe 7-10% of parental mosaics are transmitted germline to a child as occult de novo mutations, which has important implications for recurrence risk for families and potential subclinical ASD features. Finally, we find SMMs in previously implicated high-confidence ASD risk genes, including CHD2, CTNNB1, KMT2C, SYNGAP1, and RELN, further suggesting that this class of mutations contribute to population risk. ER -