Partitioning heritability by functional annotation using genome-wide association summary statistics

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Author
Bulik-Sullivan, Brendan
Trynka, Gosia
Reshef, Yakir
Anttila, Verneri
Xu, Han
Farh, Kyle
Day, Felix R.
Consortium, ReproGen
Stahl, Eli
Lindstrom, Sara
Perry, John R. B.
Okada, Yukinori
Patterson, Nick
Note: Order does not necessarily reflect citation order of authors.
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https://doi.org/10.1038/ng.3404Metadata
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Finucane, H. K., B. Bulik-Sullivan, A. Gusev, G. Trynka, Y. Reshef, P. Loh, V. Anttila, et al. 2015. “Partitioning heritability by functional annotation using genome-wide association summary statistics.” Nature genetics 47 (11): 1228-1235. doi:10.1038/ng.3404. http://dx.doi.org/10.1038/ng.3404.Abstract
Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626285/pdf/Terms of Use
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