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Meta-analysis of the heritability of human traits based on fifty years of twin studies

Nature Genetics volume 47, pages 702709 (2015) | Download Citation


Despite a century of research on complex traits in humans, the relative importance and specific nature of the influences of genes and environment on human traits remain controversial. We report a meta-analysis of twin correlations and reported variance components for 17,804 traits from 2,748 publications including 14,558,903 partly dependent twin pairs, virtually all published twin studies of complex traits. Estimates of heritability cluster strongly within functional domains, and across all traits the reported heritability is 49%. For a majority (69%) of traits, the observed twin correlations are consistent with a simple and parsimonious model where twin resemblance is solely due to additive genetic variation. The data are inconsistent with substantial influences from shared environment or non-additive genetic variation. This study provides the most comprehensive analysis of the causes of individual differences in human traits thus far and will guide future gene-mapping efforts. All the results can be visualized using the MaTCH webtool.

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  1. 1.

    Analysis of gene-gene interactions. Curr. Protoc. Hum. Genet. Chapter 1, Unit 1.14 (2004).

  2. 2.

    , & Data and theory point to mainly additive genetic variance for complex traits. PLoS Genet. 4, e1000008 (2008).

  3. 3.

    & Nature versus nurture: death of a dogma, and the road ahead. Neuron 68, 196–200 (2010).

  4. 4.

    , , & The mystery of missing heritability: genetic interactions create phantom heritability. Proc. Natl. Acad. Sci. USA 109, 1193–1198 (2012).

  5. 5.

    Epistasis—the essential role of gene interactions in the structure and evolution of genetic systems. Nat. Rev. Genet. 9, 855–867 (2008).

  6. 6.

    , , & Five years of GWAS discovery. Am. J. Hum. Genet. 90, 7–24 (2012).

  7. 7.

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

  8. 8.

    , & Progress and promise of genome-wide association studies for human complex trait genetics. Genetics 187, 367–383 (2011).

  9. 9.

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

  10. 10.

    et al. Missing heritability and strategies for finding the underlying causes of complex disease. Nat. Rev. Genet. 11, 446–450 (2010).

  11. 11.

    , & A century after Fisher: time for a new paradigm in quantitative genetics. Trends Genet. 29, 669–676 (2013).

  12. 12.

    Inter-locus interactions: a review of experimental evidence. Theor. Popul. Biol. 16, 323–346 (1979).

  13. 13.

    An extension of the concept of partitioning hereditary variance for analysis of covariances among relatives when epistasis is present. Genetics 39, 859–882 (1954).

  14. 14.

    in Statistical Genetics and Plant Breeding 53–94 (Nat. Acad. Sci. Nat. Res. Council Publ., 1963).

  15. 15.

    On the covariances between relatives under selfing with general epistacy. Proc. R. Soc. Lond. B Biol. Sci. 145, 100–108 (1956).

  16. 16.

    & An Introduction To Population Genetics Theory (Harper and Row, 1970).

  17. 17.

    & Epistasis: too often neglected in complex trait studies? Nat. Rev. Genet. 5, 618–625 (2004).

  18. 18.

    & Quantitative Genetics (Longman Group, 1996).

  19. 19.

    & Genetics and Analysis of Quantitative Traits (Sinauer Associates, 1998).

  20. 20.

    & Operating characteristics of a rank correlation test for publication bias. Biometrics 50, 1088–1101 (1994).

  21. 21.

    , , & Bias in meta-analysis detected by a simple, graphical test. Br. Med. J. 315, 629–634 (1997).

  22. 22.

    The file drawer problem and tolerance for null results. Psychol. Bull. 86, 91–106 (1979).

  23. 23.

    Meta-Analysis: A Comparison Of Approaches (Hogrefe & Huber, 2004).

  24. 24.

    in Encyclopedia of Statistical Sciences (eds. Kotz, S., Read, C.B., Balakrishnan, N. & Vidakovic, B.) Vol. 7, 68–74 (John Wiley & Sons, 2006).

  25. 25.

    Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika 44, 443–460 (1979).

  26. 26.

    The inheritance of liability to certain diseases, estimated from the incidence among relatives. Ann. Hum. Genet. 29, 51–76 (1965).

  27. 27.

    Concordance in twins: methods and interpretation. Am. J. Hum. Genet. 26, 454–466 (1974).

  28. 28.

    & Estimating the proportion of true null hypotheses for multiple comparisons. Cancer Inform. 6, 25–32 (2008).

  29. 29.

    & Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. USA 100, 9440–9445 (2003).

  30. 30.

    & The authorship network of genome-wide association studies. Nat. Genet. 44, 113 (2012).

  31. 31.

    , , & Fast unfolding of community hierarchies in large networks. J. Stat. Mech. 10, P10008 (2008).

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We would like to thank M. Frantsen, M.P. Roeling, R. Lee and D.M. DeCristo for their contribution to collecting the full texts of selected twin studies and data entry. This work was funded by the Netherlands Organization for Scientific Research (NWO VICI 453-14-005, NWO Complexity 645-000-003), by the Australian Research Council (DP130102666) and by the Australian National Health and Medical Research Council (APP613601).

Author information

Author notes

    • Tinca J C Polderman
    •  & Beben Benyamin

    These authors contributed equally to this work.

    • Peter M Visscher
    •  & Danielle Posthuma

    These authors jointly supervised this work.


  1. Department of Complex Trait Genetics, VU University, Center for Neurogenomics and Cognitive Research, Amsterdam, the Netherlands.

    • Tinca J C Polderman
    • , Christiaan A de Leeuw
    •  & Danielle Posthuma
  2. Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia.

    • Beben Benyamin
    •  & Peter M Visscher
  3. Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, the Netherlands.

    • Christiaan A de Leeuw
  4. Center for Psychiatric Genomics, Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA.

    • Patrick F Sullivan
  5. Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA.

    • Patrick F Sullivan
  6. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

    • Patrick F Sullivan
  7. Faculty of Sciences, VU University, Amsterdam, the Netherlands.

    • Arjen van Bochoven
  8. University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia.

    • Peter M Visscher
  9. Department of Clinical Genetics, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands.

    • Danielle Posthuma


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D.P., B.B., P.F.S. and P.M.V. performed the analyses. D.P. conceived the study. D.P., T.J.C.P. and P.M.V. designed the study. T.J.C.P. and D.P. collected and entered the data. D.P. and P.F.S. categorized traits according to standard classifications. A.v.B. and C.A.d.L. checked data entries, and checked and wrote statistical scripts. A.v.B. designed and programmed the webtool. D.P., T.J.C.P. and P.M.V. wrote the manuscript. All authors discussed the results and commented on the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Danielle Posthuma.

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