Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Commentary
  • Published:

Statistical false positive or true disease pathway?

Nature Genetics volume 38, pages 731–733 (2006)Cite this article

Three very recent reports provide convincing statistical evidence (P < 10−8), at a genome-wide level, of the association of common polymorphisms with three different common diseases: systemic lupus erythematosus (IRF5), prostate cancer and type 1 diabetes (IFIH1 region). This adds to the trickle—soon to be a flood—of disease association results that are highly unlikely to be false positives. There are other convincing examples in the last 12 months: age-related macular degeneration (CFH), type 1 diabetes (IL2RA, also known as CD25) and type 2 diabetes (TCF7L2). Given 20 years of a literature full of irreproducible results, what has changed?

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

References

  1. Anonymous. Nat. Genet. 37, 1153 (2005).

  2. Dahlman, I. et al. Nat. Genet. 30, 149–150 (2002).

    Article  CAS  Google Scholar 

  3. Manly, K.F., Nettleton, D. & Hwang, J.T. Genome Res. 14, 997–1001 (2004).

  4. Wang, W.Y., Barratt, B.J., Clayton, D.G. & Todd, J.A. Nat. Rev. Genet. 6, 109–118 (2005).

    Article  CAS  Google Scholar 

  5. Anonymous. Nat. Genet. 22, 1–2 (1999).

  6. Graham, R.R. et al. Nat. Genet. 38, 550–555 (2006).

    Article  CAS  Google Scholar 

  7. Amundadottir, L.T. et al. Nat. Genet. 38, 652–658 (2006).

    Article  CAS  Google Scholar 

  8. Smyth, D.J. et al. Nat. Genet. 38, 617–619 (2006).

    Article  CAS  Google Scholar 

  9. Vella, A. et al. Am. J. Hum. Genet. 76, 773–779 (2005).

    Article  CAS  Google Scholar 

  10. Grant, S.F. et al. Nat. Genet. 38, 320–323 (2006).

    Article  CAS  Google Scholar 

  11. Klein, R.J. et al. Science 308, 385–389 (2005).

    Article  CAS  Google Scholar 

  12. Maraganore, D.M. et al. Am. J. Hum. Genet. 77, 685–693 (2005).

    Article  CAS  Google Scholar 

  13. Herbert, A. et al. Science 312, 279–283 (2006).

    Article  CAS  Google Scholar 

  14. Lowe, C.E. et al. Genes Immun. 5, 301–305 (2004).

    Article  CAS  Google Scholar 

  15. Clarimon, J. et al. Am. J. Hum. Genet. 78, 1082–1084 (2006).

    Article  CAS  Google Scholar 

  16. Suarez, B., Hampe, C. & Van Eerdewegh, P. in Genetic Approaches to Mental Disorders (eds. Gershon, E. & Cloninger, C.) 23–46 (American Psychiatric Press, Washington, DC, 1994).

    Google Scholar 

  17. Service, R.F. Science 311, 1544–1546 (2006).

    Article  CAS  Google Scholar 

  18. Anjos, S., Nguyen, A., Ounissi-Benkalha, H., Tessier, M.C. & Polychronakos, C. J. Biol. Chem. 277, 46478–46486 (2002).

    Article  CAS  Google Scholar 

  19. Ueda, H. et al. Nature 423, 506–511 (2003).

    Article  CAS  Google Scholar 

  20. Brassat, D. et al. Genes Immun. advance online publication 20 April 2006 (doi: 10.1038/sj.gene.6364299).

  21. Wong, M.Y., Day, N.E., Luan, J.A., Chan, K.P. & Wareham, N.J. Int. J. Epidemiol. 32, 51–57 (2003).

    Article  CAS  Google Scholar 

  22. Caspi, A. et al. Science 301, 386–389 (2003).

    Article  CAS  Google Scholar 

  23. Moskvina, V., Craddock, N., Holmans, P., Owen, M.J. & O'Donovan, M.C. Hum. Hered. 61, 55–64 (2006).

    Article  Google Scholar 

  24. Clayton, D.G. et al. Nat. Genet. 37, 1243–1246 (2005).

    Article  CAS  Google Scholar 

  25. Raymond, C.K. et al. Genomics 86, 759–766 (2005).

    Article  CAS  Google Scholar 

  26. Groves, C. J et al. Diabetes (in the press).

Download references

Acknowledgements

Work in the author's laboratory is funded by the Wellcome Trust and the Juvenile Diabetes Research Foundation International. The author thanks D. Rubinsztein for helpful comments on an earlier draft of the manuscript.

Author information

Authors and Affiliations

  1. University of Cambridge, Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, Wellcome Trust/Medical Research Council Building, Addenbrooke's Hospital Cambridge, Cambridgeshire, CB2 2XY, UK

    John A Todd

Authors
  1. John A Todd
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Todd, J. Statistical false positive or true disease pathway?. Nat Genet 38, 731–733 (2006). https://doi.org/10.1038/ng0706-731

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng0706-731

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing