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Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease

Nature Genetics volume 33, pages 177–182 (2003)Cite this article

Abstract

Association studies offer a potentially powerful approach to identify genetic variants that influence susceptibility to common disease1,2,3,4, but are plagued by the impression that they are not consistently reproducible5,6. In principle, the inconsistency may be due to false positive studies, false negative studies or true variability in association among different populations4,5,6,7,8. The critical question is whether false positives overwhelmingly explain the inconsistency. We analyzed 301 published studies covering 25 different reported associations. There was a large excess of studies replicating the first positive reports, inconsistent with the hypothesis of no true positive associations (P < 10−14). This excess of replications could not be reasonably explained by publication bias and was concentrated among 11 of the 25 associations. For 8 of these 11 associations, pooled analysis of follow-up studies yielded statistically significant replication of the first report, with modest estimated genetic effects. Thus, a sizable fraction (but under half) of reported associations have strong evidence of replication; for these, false negative, underpowered studies probably contribute to inconsistent replication. We conclude that there are probably many common variants in the human genome with modest but real effects on common disease risk, and that studies using large samples will convincingly identify such variants.

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Figure 1: Funnel plot analysis to detect publication bias.

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Acknowledgements

We thank E. Byrne for help in obtaining manuscripts and D. Stram for help with analysis. J.N.H. is the recipient of a Burroughs Wellcome Career Award in Biomedical Sciences. This work was supported in part by research grants from Bristol-Myers Squibb, Millennium Pharmaceuticals and Affymetrix to E.S.L. and by the University of Southern California/Norris Comprehensive Cancer Center Core Grant from the US National Cancer Institute.

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Authors and Affiliations

  1. Whitehead/Massachuetts Institute of Technology Center for Genome Research, Cambridge, 02139, Massachusetts, USA

    Kirk E. Lohmueller, Eric S. Lander & Joel N. Hirschhorn

  2. Georgetown University, Washington, 20057, DC, USA

    Kirk E. Lohmueller

  3. Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA

    Celeste L. Pearce & Malcolm Pike

  4. Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Eric S. Lander

  5. Department of Genetics, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Joel N. Hirschhorn

  6. Divisions of Genetics and Endocrinology, Enders 561, Children's Hospital, 300 Longwood Avenue, Boston, 02115, Massachusetts, USA

    Joel N. Hirschhorn

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Correspondence to Joel N. Hirschhorn.

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Lohmueller, K., Pearce, C., Pike, M. et al. Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet 33, 177–182 (2003). https://doi.org/10.1038/ng1071

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