RT Journal Article SR Electronic T1 Partitioning heritability by functional category using GWAS summary statistics JF bioRxiv FD Cold Spring Harbor Laboratory SP 014241 DO 10.1101/014241 A1 Hilary K. Finucane A1 Brendan Bulik-Sullivan A1 Alexander Gusev A1 Gosia Trynka A1 Yakir Reshef A1 Po-Ru Loh A1 Verneri Anttilla A1 Han Xu A1 Chongzhi Zang A1 Kyle Farh A1 Stephan Ripke A1 Felix Day A1 ReproGen Consortium A1 Schizophrenia Working Group of the Psychiatric Genetics Consortium A1 The RACI Consortium A1 Shaun Purcell A1 Eli Stahl A1 Sara Lindstrom A1 John R.B. Perry A1 Yukinori Okada A1 Soumya Raychaudhuri A1 Mark Daly A1 Nick Patterson A1 Benjamin M. Neale A1 Alkes L. Price YR 2015 UL http://biorxiv.org/content/early/2015/01/23/014241.abstract AB 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.