Abstract

The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale variance explained by associated GWAS SNPs. Using this method, we estimated that, together, thousands of SNPs from rheumatoid arthritis GWAS explain an additional 20% of disease risk (excluding known associated loci). We further tested this method on datasets for three additional diseases and obtained comparable estimates for celiac disease (43% excluding the major histocompatibility complex), myocardial infarction and coronary artery disease (48%) and type 2 diabetes (49%). Our results are consistent with simulated genetic models in which hundreds of associated loci harbor common causal variants and a smaller number of loci harbor multiple rare causal variants. These analyses suggest that GWAS will continue to be highly productive for the discovery of additional susceptibility loci for common diseases.

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Acknowledgements

R.M.P. is supported by grants from the US National Institutes of Health (NIH) (R01-AR057108, R01-AR056768, U01-GM092691 and R01-AR059648) and holds a Career Award for Medical Scientists from the Burroughs Wellcome Fund. S.R. is supported by an NIH Career Development Award (K08AR055688-01A1). The Brigham Rheumatoid Arthritis Sequential Study Registry is supported by a grant from Crescendo and Biogen-Idec. The North American Rheumatoid Arthritis Consortium is supported by the NIH (NO1-AR-2-2263 and RO1-AR44422). This research was also supported in part by the Intramural Research Program of the National Institute of Arthritis, Musculoskeletal and Skin Diseases of the NIH and by a Canada Research Chair and grants to K.A.S. from the Canadian Institutes for Health Research (MOP79321 and IIN-84042) and the Ontario Research Fund (RE01061). We acknowledge S. Purcell, A. Price and N. Zaitlen for help with the design and implementation of the study and analysis.

Author information

Author notes

    • Soumya Raychaudhuri
    •  & Robert M Plenge

    These authors contributed equally to this work.

Affiliations

  1. Division of Rheumatology Immunology and Allergy, Brigham and Women's Hospital, Boston, Massachusetts, USA.

    • Eli A Stahl
    • , Robert Chen
    • , Fina A S Kurreeman
    • , Soumya Raychaudhuri
    •  & Robert M Plenge
  2. Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA.

    • Eli A Stahl
    • , Ron Do
    • , Robert Chen
    • , Fina A S Kurreeman
    • , Sekar Kathiresan
    • , Paul I W de Bakker
    • , Soumya Raychaudhuri
    •  & Robert M Plenge
  3. Division of Genetics, Brigham and Women's Hospital, Boston, Massachusetts, USA.

    • Eli A Stahl
    • , Robert Chen
    • , Fina A S Kurreeman
    • , Paul I W de Bakker
    • , Soumya Raychaudhuri
    •  & Robert M Plenge
  4. Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA.

    • Daniel Wegmann
  5. Department of Genetics, University Medical Center Groningen and University of Groningen, Groningen, The Netherlands.

    • Gosia Trynka
    • , Javier Gutierrez-Achury
    •  & Cisca Wijmenga
  6. Center for Human Genetic Research and Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.

    • Ron Do
    •  & Sekar Kathiresan
  7. Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

    • Benjamin F Voight
  8. Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA.

    • Peter Kraft
  9. Institute of Environmental Medicine, Karolinska Institutet Hospital Solna, Stockholm, Sweden.

    • Henrik J Kallberg
    •  & Lars Alfredsson
  10. The Feinstein Institute for Medical Research, North Shore–Long Island Jewish Health System, Manhasset, New York, USA.

    • Peter K Gregersen
  11. Department of Medicine, University of Toronto, Mount Sinai Hospital and University Health Network, Toronto, Ontario, Canada.

    • Katherine A Siminovitch
  12. Arthritis Research UK Epidemiology Unit, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.

    • Jane Worthington
  13. Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands.

    • Paul I W de Bakker
  14. Department of Epidemiology, University Medical Center Utrecht, Utrecht, The Netherlands.

    • Paul I W de Bakker

Consortia

  1. Diabetes Genetics Replication and Meta-analysis Consortium

    A full list of members is provided in the Supplementary Note.

  2. Myocardial Infarction Genetics Consortium

    A full list of members is provided in the Supplementary Note.

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Contributions

Study design: R.M.P., E.A.S., S.R. and P.I.W.d.B. Analysis: E.A.S. (lead), D.W., G.T., J.G.-A., R.D., B.F.V. (primary contributors), R.C., H.J.K. and F.A.S.K. Samples and data: C.W., S.K., B.F.V., the Myocardial Infarction Genetics Consortium, the Diabetes Genetics Replication and Meta-analysis Consortium, J.W., L.A., P.K.G., K.A.S. and R.M.P. Writing: R.M.P., E.A.S. (leads), D.W., P.K. (primary contributors) and all other authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Eli A Stahl or Robert M Plenge.

Supplementary information

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    Supplementary Text and Figures

    Supplementary Tables 1–4, Supplementary Figures 1–5 and Supplementary Note.

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DOI

https://doi.org/10.1038/ng.2232

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