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

Nature Genetics volume 47, pages 1228–1235 (2015)Cite this article

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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 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.

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Figure 1: Simulation results for null calibration and power.
Figure 2: Simulation results for model misspecification.
Figure 3: Simulation results for ranking cell type groups and cell types.
Figure 4: Enrichment estimates for the 24 main annotations, averaged over nine independent traits.
Figure 5: Enrichment estimates for selected annotations and traits.
Figure 6: Enrichment of cell type groups.
Figure 7: Comparison of stratified LD score regression to other methods for identifying enriched cell types.

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Acknowledgements

We thank B. Bernstein, M. Finucane, A. Forrest, E. Hodis, D. Kotliar, X.S. Liu, M. Kellis, M. O'Donovan, B. Pasaniuc, A. Sandelin, A. Sarkar, P. Sullivan, B. Vilhjalmsson, A. Veres and the anonymous reviewers for helpful discussions and/or comments. This research was funded by US National Institutes of Health grants R01 MH101244, R01 HG006399, R03 CA173785, R21 CA182821, F32 GM106584 and U01 HG0070033. H.K.F. was also supported by the Fannie and John Hertz Foundation. G.T. is supported by the Wellcome Trust Sanger Institute (WT098051). Y.R. was supported by award T32 GM007753 from the National Institute of General Medical Sciences. S. Raychaudhuri is supported by funding from the Arthritis Foundation and by a Doris Duke Clinical Scientist Development Award. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences or the National Institutes of Health. This study made use of data generated by the Wellcome Trust Case Control Consortium (WTCCC) and the Wellcome Trust Sanger Institute. A full list of the investigators who contributed to the generation of the WTCCC data is available at http://www.wtccc.org.uk/. Funding for the WTCCC project was provided by the Wellcome Trust under award 076113.

Author information

Author notes

  1. Hilary K Finucane, Brendan Bulik-Sullivan and Soumya Raychaudhuri: These authors contributed equally to this work.

  2. Benjamin M Neale and Alkes L Price: These authors jointly supervised this work.

Authors and Affiliations

  1. Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Hilary K Finucane

  2. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

    Hilary K Finucane, Alexander Gusev, Po-Ru Loh, Sara Lindstrom & Alkes L Price

  3. Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    Brendan Bulik-Sullivan, Verneri Anttila, Kyle Farh, Stephan Ripke, Mark J Daly & Benjamin M Neale

  4. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    Brendan Bulik-Sullivan, Verneri Anttila, Stephan Ripke, Mark J Daly & Benjamin M Neale

  5. Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA

    Gosia Trynka, Shaun Purcell & Soumya Raychaudhuri

  6. Division of Rheumatology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA

    Gosia Trynka, Shaun Purcell & Soumya Raychaudhuri

  7. Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA

    Gosia Trynka & Soumya Raychaudhuri

  8. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    Gosia Trynka, Verneri Anttila, Soumya Raychaudhuri, Mark J Daly, Nick Patterson, Benjamin M Neale & Alkes L Price

  9. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK

    Gosia Trynka

  10. Department of Computer Science, Harvard University, Cambridge, Massachusetts, USA

    Yakir Reshef

  11. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

    Han Xu & Chongzhi Zang

  12. Epigenomics Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    Kyle Farh

  13. Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK

    Felix R Day & John R B Perry

  14. Department of Psychiatry, Mount Sinai School of Medicine, New York, New York, USA

    Shaun Purcell & Eli Stahl

  15. Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan

    Yukinori Okada

  16. Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Yukinori Okada

  17. Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK

    Soumya Raychaudhuri

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H.K.F., B.B.-S., A.G., G.T., Y.R., P.-R.L., V.A., S. Raychaudhuri, M.J.D., N.P., B.M.N. and A.L.P. conceived and designed the experiments. H.K.F. and B.B.-S. performed the experiments, performed the statistical analysis and analyzed the data. H.X., C.Z., K.F., S. Ripke, F.R.D., S.P., E.S., S.L., J.R.B.P. and Y.O. contributed reagents. H.K.F., B.B.-S., B.M.N. and A.L.P. wrote the manuscript with feedback from all authors.

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Correspondence to Hilary K Finucane, Brendan Bulik-Sullivan, Benjamin M Neale or Alkes L Price.

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A full list of members appears in the Supplementary Note.

A full list of members appears in the Supplementary Note.

A full list of members appears in the Supplementary Note.

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Finucane, H., Bulik-Sullivan, B., Gusev, A. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat Genet 47, 1228–1235 (2015). https://doi.org/10.1038/ng.3404

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