Patterns and rates of exonic de novo mutations in autism spectrum disorders

Benjamin M. Neale, Yan Kou, Li Liu, Avi Ma’ayan, Kaitlin E. Samocha, Aniko Sabo, Chiao Feng Lin, Christine Stevens, Li San Wang, Vladimir Makarov, Paz Polak, Seungtai Yoon, Jared Maguire, Emily L. Crawford, Nicholas G. Campbell, Evan T. Geller, Otto Valladares, Chad Schafer, Han Liu, Tuo ZhaoGuiqing Cai, Jayon Lihm, Ruth Dannenfelser, Omar Jabado, Zuleyma Peralta, Uma Nagaswamy, Donna Muzny, Jeffrey G. Reid, Irene Newsham, Yuanqing Wu, Lora Lewis, Yi Han, Benjamin F. Voight, Elaine Lim, Elizabeth Rossin, Andrew Kirby, Jason Flannick, Menachem Fromer, Khalid Shakir, Tim Fennell, Kiran Garimella, Eric Banks, Ryan Poplin, Stacey Gabriel, Mark Depristo, Jack R. Wimbish, Braden E. Boone, Shawn E. Levy, Catalina Betancur, Shamil Sunyaev, Eric Boerwinkle, Joseph D. Buxbaum, Edwin H. Cook, Bernie Devlin, Richard A. Gibbs, Kathryn Roeder, Gerard D. Schellenberg, James S. Sutcliffe, Mark J. Daly

Research output: Contribution to journalLetterpeer-review

1346 Scopus citations


Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case—control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

Original languageEnglish
Pages (from-to)242-246
Number of pages5
Issue number7397
StatePublished - 10 May 2012


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