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Nat Genet. 2015 Nov;47(11):1228-35. doi: 10.1038/ng.3404. Epub 2015 Sep 28.

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

Author information

1
Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
2
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
3
Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
4
Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
5
Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
6
Division of Rheumatology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
7
Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA.
8
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
9
Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK.
10
Department of Computer Science, Harvard University, Cambridge, Massachusetts, USA.
11
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
12
Epigenomics Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
13
Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK.
14
Department of Psychiatry, Mount Sinai School of Medicine, New York, New York, USA.
15
Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.
16
Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
17
Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK.

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 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.

PMID:
26414678
PMCID:
PMC4626285
DOI:
10.1038/ng.3404
[Indexed for MEDLINE]
Free PMC Article

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