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Partitioning heritability by functional category using GWAS summary statistics

Hilary K. Finucane, Brendan Bulik-Sullivan, Alexander Gusev, Gosia Trynka, Yakir Reshef, Po-Ru Loh, Verneri Anttilla, Han Xu, Chongzhi Zang, Kyle Farh, Stephan Ripke, Felix Day, ReproGen Consortium, Schizophrenia Working Group of the Psychiatric Genetics Consortium, The RACI Consortium, Shaun Purcell, Eli Stahl, Sara Lindstrom, John R.B. Perry, Yukinori Okada, Soumya Raychaudhuri, Mark Daly, Nick Patterson, Benjamin M. Neale, Alkes L. Price
doi: https://doi.org/10.1101/014241
Hilary K. Finucane
1Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
2Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
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  • For correspondence: hilaryf@mit.edu aprice@hsph.harvard.edu
Brendan Bulik-Sullivan
3Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
4Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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Alexander Gusev
2Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
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Gosia Trynka
5Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
6Division of Rheumatology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
7Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA.
8Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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Yakir Reshef
9Department of Computer Science, Harvard University, Massachusetts,USA.
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Po-Ru Loh
2Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
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Verneri Anttilla
3Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
4Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
8Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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Han Xu
10Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
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Chongzhi Zang
10Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
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Kyle Farh
3Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
11Epigenomics Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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Stephan Ripke
3Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
4Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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Felix Day
12MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
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ReproGen Consortium
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Shaun Purcell
5Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
6Division of Rheumatology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
13The Department of Psychiatry at Mount Sinai School of Medicine, New York, New York, USA.
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Eli Stahl
13The Department of Psychiatry at Mount Sinai School of Medicine, New York, New York, USA.
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Sara Lindstrom
2Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
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John R.B. Perry
12MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
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Yukinori Okada
14Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo 113-8510, Japan.
15Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
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Soumya Raychaudhuri
5Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
6Division of Rheumatology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
7Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA.
8Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
16Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK.
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Mark Daly
3Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
4Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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Nick Patterson
8Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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Benjamin M. Neale
3Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
4Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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Alkes L. Price
2Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
8Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
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  • For correspondence: hilaryf@mit.edu aprice@hsph.harvard.edu
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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.

Footnotes

  • ↵* Co-first authors

  • ↵** Co-last authors

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted January 23, 2015.
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Partitioning heritability by functional category using GWAS summary statistics
Hilary K. Finucane, Brendan Bulik-Sullivan, Alexander Gusev, Gosia Trynka, Yakir Reshef, Po-Ru Loh, Verneri Anttilla, Han Xu, Chongzhi Zang, Kyle Farh, Stephan Ripke, Felix Day, ReproGen Consortium, Schizophrenia Working Group of the Psychiatric Genetics Consortium, The RACI Consortium, Shaun Purcell, Eli Stahl, Sara Lindstrom, John R.B. Perry, Yukinori Okada, Soumya Raychaudhuri, Mark Daly, Nick Patterson, Benjamin M. Neale, Alkes L. Price
bioRxiv 014241; doi: https://doi.org/10.1101/014241
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Partitioning heritability by functional category using GWAS summary statistics
Hilary K. Finucane, Brendan Bulik-Sullivan, Alexander Gusev, Gosia Trynka, Yakir Reshef, Po-Ru Loh, Verneri Anttilla, Han Xu, Chongzhi Zang, Kyle Farh, Stephan Ripke, Felix Day, ReproGen Consortium, Schizophrenia Working Group of the Psychiatric Genetics Consortium, The RACI Consortium, Shaun Purcell, Eli Stahl, Sara Lindstrom, John R.B. Perry, Yukinori Okada, Soumya Raychaudhuri, Mark Daly, Nick Patterson, Benjamin M. Neale, Alkes L. Price
bioRxiv 014241; doi: https://doi.org/10.1101/014241

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