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Common SNPs explain a large proportion of the heritability for human height

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Abstract

SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date.

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Figure 1: Prediction error of genetic relationship.
Figure 2: Estimates of variance explained by genome-wide SNPs from adjusted estimates of genetic relationships are unbiased.
Figure 3: All pairwise comparisons contribute to the estimate of genetic variance.

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Change history

  • 24 September 2010

    In the version of this supplementary file originally posted online, Supplementary Fig. 2a and 2b were incorrect. The legend stated that in Supplementary Fig. 2a, PC1 versus PC2 was plotted when in fact PC2 versus PC3 was shown. Similarly, in Supplementary Fig. 2b, PC4 versus PC5 was plotted rather than PC3 versus PC4 as stated. This error is purely graphical and does not in any way affect the results or conclusions presented in the article. We thank Andrew Stewart for kindly pointing out this error to us. The authors regret not detecting this error earlier. The error has been corrected in this file as of 24 September 2010.

References

  1. Hindorff, L.A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA 106, 9362–9367 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Donnelly, P. Progress and challenges in genome-wide association studies in humans. Nature 456, 728–731 (2008).

    Article  CAS  PubMed  Google Scholar 

  3. Maher, B. Personal genomes: The case of the missing heritability. Nature 456, 18–21 (2008).

    Article  CAS  PubMed  Google Scholar 

  4. Manolio, T.A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Frazer, K.A., Murray, S.S., Schork, N.J. & Topol, E.J. Human genetic variation and its contribution to complex traits. Nat. Rev. Genet. 10, 241–251 (2009).

    Article  CAS  PubMed  Google Scholar 

  6. Pritchard, J.K. Are rare variants responsible for susceptibility to complex diseases? Am. J. Hum. Genet. 69, 124–137 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Johannes, F., Colot, V. & Jansen, R.C. Epigenome dynamics: a quantitative genetics perspective. Nat. Rev. Genet. 9, 883–890 (2008).

    Article  CAS  PubMed  Google Scholar 

  8. Johannes, F. et al. Assessing the impact of transgenerational epigenetic variation on complex traits. PLoS Genet. 5, e1000530 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Fisher, R.A. The correlation between relatives on the supposition of Mendelian inheritance. Trans. R. Soc. Edinb. 52, 399–433 (1918).

    Article  Google Scholar 

  10. Galton, F. Hereditary stature. Nature 33, 295–298 (1886).

    Article  Google Scholar 

  11. Macgregor, S., Cornes, B.K., Martin, N.G. & Visscher, P.M. Bias, precision and heritability of self-reported and clinically measured height in Australian twins. Hum. Genet. 120, 571–580 (2006).

    Article  PubMed  Google Scholar 

  12. Silventoinen, K. et al. Heritability of adult body height: a comparative study of twin cohorts in eight countries. Twin Res. 6, 399–408 (2003).

    Article  PubMed  Google Scholar 

  13. Visscher, P.M., Hill, W.G. & Wray, N.R. Heritability in the genomics era–concepts and misconceptions. Nat. Rev. Genet. 9, 255–266 (2008).

    Article  CAS  PubMed  Google Scholar 

  14. Dietz, H.C. et al. Marfan syndrome caused by a recurrent de novo missense mutation in the fibrillin gene. Nature 352, 337–339 (1991).

    Article  CAS  PubMed  Google Scholar 

  15. Shiang, R. et al. Mutations in the transmembrane domain of FGFR3 cause the most common genetic form of dwarfism, achondroplasia. Cell 78, 335–342 (1994).

    Article  CAS  PubMed  Google Scholar 

  16. Gudbjartsson, D.F. et al. Many sequence variants affecting diversity of adult human height. Nat. Genet. 40, 609–615 (2008).

    Article  CAS  PubMed  Google Scholar 

  17. Lettre, G. et al. Identification of ten loci associated with height highlights new biological pathways in human growth. Nat. Genet. 40, 584–591 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Weedon, M.N. et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat. Genet. 40, 575–583 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Visscher, P.M. Sizing up human height variation. Nat. Genet. 40, 489–490 (2008).

    Article  CAS  PubMed  Google Scholar 

  20. Hayes, B.J., Visscher, P.M. & Goddard, M.E. Increased accuracy of artificial selection by using the realized relationship matrix. Genet. Res. 91, 47–60 (2009).

    Article  CAS  Google Scholar 

  21. Patterson, H.D. & Thompson, R. Recovery of inter-block information when block sizes are unequal. Biometrika 58, 545–554 (1971).

    Article  Google Scholar 

  22. Zhang, X.S. & Hill, W.G. Predictions of patterns of response to artificial selection in lines derived from natural populations. Genetics 169, 411–425 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Haseman, J.K. & Elston, R.C. The investigation of linkage between a quantitative trait and a marker locus. Behav. Genet. 2, 2–19 (1972).

    Article  Google Scholar 

  24. Visscher, P.M., Hill, W.G. & Wray, N.R. Heritability in the genomics era–concepts and misconceptions. Nat. Rev. Genet. 9, 255–266 (2008).

    Article  CAS  PubMed  Google Scholar 

  25. Slatkin, M. Epigenetic inheritance and the missing heritability problem. Genetics 182, 845–850 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Purcell, S.M. et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).

    CAS  PubMed  Google Scholar 

  27. Goddard, M.E. & Hayes, B.J. Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nat. Rev. Genet. 10, 381–391 (2009).

    Article  CAS  PubMed  Google Scholar 

  28. Wray, N.R., Goddard, M.E. & Visscher, P.M. Prediction of individual genetic risk to disease from genome-wide association studies. Genome Res. 17, 1520–1528 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Meuwissen, T.H., Solberg, T.R., Shepherd, R. & Woolliams, J.A. A fast algorithm for BayesB type of prediction of genome-wide estimates of genetic value. Genet. Sel. Evol. 41, 2 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  30. McEvoy, B.P. et al. Geographical structure and differential natural selection among North European populations. Genome Res. 19, 804–814 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

    Article  CAS  PubMed  Google Scholar 

  32. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Dixon, W.J. Simplified estimation from censored normal samples. Ann. Math. Stat. 31, 385–391 (1960).

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to the twins and their families for their generous participation in these studies. We would like to thank staff at the Queensland Institute of Medical Research: D. Statham, A. Eldridge and M. Grace for sample collection, M. Campbell, L. Bowdler, S. Crooks and staff of the Molecular Epidemiology Laboratory for sample processing and preparation, B. Cornes for height data preparation, D. Smyth and H. Beeby for IT support and A. McRae and H. Lee for discussions. We thank N. Wray for helpful comments on the manuscript. We acknowledge funding from the Australian National Health and Medical Research Council (grants 241944, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 496688 and 552485), the US National Institutes of Health (grants AA07535, AA10248, AA014041, AA13320, AA13321, AA13326 and DA12854) and the Australian Research Council (grant DP0770096).

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Authors and Affiliations

Authors

Contributions

P.M.V. and M.E.G. designed the study. J.Y. performed statistical analyses. B.B., B.P.M., A.K.H., D.R.N. and S.G. performed quality control analyses and prepared data. D.R.N., P.A.M., A.C.H. and N.G.M. contributed genotype and phenotype data. J.Y., G.W.M., M.E.G. and P.M.V. contributed to writing the paper.

Corresponding author

Correspondence to Peter M Visscher.

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The authors declare no competing financial interests.

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Supplementary Figures 1–5, Supplementary Tables 1 and 2 and Supplementary Note (PDF 742 kb)

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Yang, J., Benyamin, B., McEvoy, B. et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42, 565–569 (2010). https://doi.org/10.1038/ng.608

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