bioRxivGenetics
Partitioning heritability by functional category using GWAS summary statistics
Hilary Kiyo Finucane, Brendan Bulik-Sullivan, Alexander GuseviD, Gosia TrynkaiD, Yakir ReshefiD, Po-Ru LohiD, Verneri Anttilla, Han Xu, Chongzhi Zang, Kyle Farh, Stephan RipkeiD, Felix Day, ReproGen Consortium, Schizophrenia Working Group of the Psychiatric Genetics Consortium, RACI Consortium, Shaun PurcelliD, Eli StahliD, Sara Lindstrom, John R.B. Perry, Yukinori OkadaiD, Soumya RaychaudhuriiD, Mark Daly, Nick Patterson, Benjamin M. NealeiD, Alkes L. PriceiD
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 spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling 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. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.
- organism: human
- assay: GWAS summary statistics
- research focus: fine-mapping
- approach: statistical model
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