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

Hilary K Finucane*, Brendan Bulik-Sullivan*, Alexander Gusev, Gosia Trynka, Yakir Reshef, Po-Ru Loh, Verneri Anttila, Han Xu, Chongzhi Zang, Kyle Farh, Stephan Ripke, Felix R Day, ReproGen Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Shaun Purcell, Eli Stahl, Sara Lindstrom, John R B Perry, Yukinori OkadaSoumya Raychaudhuri, Mark J Daly, Nick Patterson, Benjamin M Neale*, Alkes L Price*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1199 Citations (Scopus)


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 findings 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 the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

Original languageEnglish
Pages (from-to)1228-1235
Number of pages8
JournalNature Genetics
Issue number11
Publication statusPublished - Nov 2015

Research programs

  • EMC MM-01-39-04


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