Spontaneously arising (de novo) mutations have an important role in medical genetics. For diseases with extensive locus heterogeneity, such as autism spectrum disorders (ASDs), the signal from de novo mutations is distributed across many genes, making it difficult to distinguish disease-relevant mutations from background variation. Here we provide a statistical framework for the analysis of excesses in de novo mutation per gene and gene set by calibrating a model of de novo mutation. We applied this framework to de novo mutations collected from 1,078 ASD family trios, and, whereas we affirmed a significant role for loss-of-function mutations, we found no excess of de novo loss-of-function mutations in cases with IQ above 100, suggesting that the role of de novo mutations in ASDs might reside in fundamental neurodevelopmental processes. We also used our model to identify ∼1,000 genes that are significantly lacking in functional coding variation in non-ASD samples and are enriched for de novo loss-of-function mutations identified in ASD cases.
A framework for the interpretation of de novo mutation in human disease
K. Samocha,E. Robinson,Stephan J Sanders,C. Stevens,A. Sabo,L. McGrath,Jack A. Kosmicki,K. Rehnström,Swapan Mallick,Andrew W. Kirby,D. Wall,D. MacArthur,S. Gabriel,M. DePristo,S. Purcell,A. Palotie,E. Boerwinkle,J. Buxbaum,E. Cook,R. Gibbs,G. Schellenberg,J. Sutcliffe,B. Devlin,K. Roeder,B. Neale,M. Daly
Published 2014 in Nature Genetics
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- Publication year
2014
- Venue
Nature Genetics
- Publication date
2014-08-03
- Fields of study
Biology, Medicine
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- External record
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Semantic Scholar, PubMed
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