Abstract

We estimate and partition genetic variation for height, body mass index (BMI), von Willebrand factor and QT interval (QTi) using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimate that 45%, 17%, 25% and 21% of the variance in height, BMI, von Willebrand factor and QTi, respectively, can be explained by all autosomal SNPs and a further 0.5–1% can be explained by X chromosome SNPs. We show that the variance explained by each chromosome is proportional to its length, and that SNPs in or near genes explain more variation than SNPs between genes. We propose a new approach to estimate variation due to cryptic relatedness and population stratification. Our results provide further evidence that a substantial proportion of heritability is captured by common SNPs, that height, BMI and QTi are highly polygenic traits, and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein.

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Acknowledgements

Funding support for the Gene, Environment Association Studies (GENEVA) project has been provided through the US National Institutes of Health Genes, Environment and Health Initiative. For the ARIC project, support was from U01 HG 004402 (PI: E.A. Boerwinkle). For the NHS and HPFS support is from U01 HG 004399 and U01 HG 004728 (PIs: F.B. Hu and L.R. Pasquale). The genotyping for the ARIC, NHS and HPFS studies was performed at the Broad Institute of MIT and Harvard with funding support from U01 HG04424 (PI: S. Gabriel). The GENEVA Coordinating Center receives support from U01 HG 004446 (PI: B.S. Weir). Assistance with GENEVA data cleaning was provided by the National Center for Biotechnology Information. D. Crosslin and C. Laurie of the GENEVA project assisted in making the data available for analysis. A Physician Scientist Award from Research to Prevent Blindness in New York City also supports L.R.P. M.C.C. is a recipient of a Canadian Institutes of Health Research Fellowship. We acknowledge funding from the Australian National Health and Medical Research Council (NHMRC grants 389892 and 613672) and the Australian Research Council (ARC grants DP0770096 and DP1093900). We thank D. Posthuma for discussions and the referees for constructive comments.

Author information

Affiliations

  1. Queensland Statistical Genetics Laboratory, Queensland Institute of Medical Research, Brisbane, Australia.

    • Jian Yang
    •  & Peter M Visscher
  2. Office of Population Genomics, National Human Genome Research Institute (NHGRI), Bethesda, Maryland, USA.

    • Teri A Manolio
  3. Massachussetts Eye and Ear Infirmary, Harvard Medical School, Boston, Massachusetts, USA.

    • Louis R Pasquale
  4. Human Genetics Center and Division of Epidemiology, University of Texas Health Science Center, Houston, Texas, USA.

    • Eric Boerwinkle
  5. Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), Bethesda, Maryland, USA.

    • Neil Caporaso
  6. Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.

    • Julie M Cunningham
  7. Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA.

    • Mariza de Andrade
  8. Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark.

    • Bjarke Feenstra
    •  & Mads Melbye
  9. Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

    • Eleanor Feingold
  10. Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.

    • M Geoffrey Hayes
  11. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.

    • William G Hill
  12. Division of Cancer Epidemiology and Genetics, NCI, Bethesda, Maryland, USA.

    • Maria Teresa Landi
  13. Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, USA.

    • Alvaro Alonso
  14. Montréal Heart Institute, Université de Montréal, Montréal, Quebec, Canada.

    • Guillaume Lettre
  15. Human and Statistical Genetics Program, School of Medicine, Washington University, St. Louis, Missouri, USA.

    • Peng Lin
  16. Center for Inherited Disease Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

    • Hua Ling
    •  & Elizabeth Pugh
  17. Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.

    • William Lowe
  18. Department of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

    • Rasika A Mathias
  19. Department of Nutrition, School of Public Health, Harvard University, Boston, Massachusetts, USA.

    • Marilyn C Cornelis
  20. Department of Biostatistics, University of Washington, Seattle, Washington, USA.

    • Bruce S Weir
  21. Department of Food and Agricultural Systems, University of Melbourne, Victoria, Australia.

    • Michael E Goddard
  22. Biosciences Research Division, Department of Primary Industries, Bundoora, Victoria, Australia.

    • Michael E Goddard

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Contributions

P.M.V., M.E.G., B.S.W. and T.A.M. designed the study. J.Y. performed all statistical analyses. J.Y. and P.M.V. wrote the first draft of the paper. L.R.P., E.B., N.C., J.M.C., M.d.A., B.F., E.F., M.G.H., W.G.H., M.T.L., A.A., G.L., P.L., H.L., W.L., R.A.M., M.M., E.P. and M.C.C. contributed by providing genotype and phenotype data, by giving advice on analyses and interpretation of results and/or by giving advice on the contents of the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Peter M Visscher.

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DOI

https://doi.org/10.1038/ng.823