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Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

He, X and Sanders, SJ and Liu, L and De Rubeis, S and Lim, ET and Sutcliffe, JS and Schellenberg, GD and Gibbs, RA and Daly, MJ and Buxbaum, JD and State, MW and Devlin, B and Roeder, K (2013) Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes. PLoS Genetics, 9 (8). ISSN 1553-7390

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Abstract

De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support. © 2013 He et al.

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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
He, X
Sanders, SJ
Liu, L
De Rubeis, S
Lim, ET
Sutcliffe, JS
Schellenberg, GD
Gibbs, RA
Daly, MJ
Buxbaum, JD
State, MW
Devlin, Bdevlinbj@pitt.eduDEVLINBJ
Roeder, K
Date: 1 August 2013
Date Type: Publication
Journal or Publication Title: PLoS Genetics
Volume: 9
Number: 8
DOI or Unique Handle: 10.1371/journal.pgen.1003671
Schools and Programs: School of Medicine > Psychiatry
Refereed: Yes
ISSN: 1553-7390
Date Deposited: 23 Sep 2013 17:28
Last Modified: 03 Feb 2019 06:55
URI: http://d-scholarship.pitt.edu/id/eprint/19777

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