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.

  • Article
  • Published:

Genome-wide association analysis identifies 20 loci that influence adult height

Abstract

Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P < 5 × 10−7, with 10 reaching P < 1 × 10−10). Combined, the 20 SNPs explain 3% of height variation, with a 5 cm difference between the 6.2% of people with 17 or fewer 'tall' alleles compared to the 5.5% with 27 or more 'tall' alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Quantile-quantile plots for the 402,951 SNPs from the genome-wide association meta-analysis as more studies are added in.
Figure 2: Manhattan plot for the 402,951 SNPs from the stage 1 genome-wide association meta-analysis of the WTCCC-T2D, DGI, WTCCC-HT, WTCCC-CAD, EPIC-Obesity and WTCCC-UKBS studies.
Figure 3: The combined impact of the 20 SNPs with a P < 5 × 10−7.
Figure 4: Power estimates.
Figure 5: Comparison of results across independent meta-analyses.

Similar content being viewed by others

References

  1. 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  Google Scholar 

  2. Preece, M.A. The genetic contribution to stature. Horm. Res. 45, 56–58 (1996).

    Article  CAS  Google Scholar 

  3. Silventoinen, K., Kaprio, J., Lahelma, E. & Koskenvuo, M. Relative effect of genetic and environmental factors on body height: differences across birth cohorts among Finnish men and women. Am. J. Public Health 90, 627–630 (2000).

    Article  CAS  Google Scholar 

  4. 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  Google Scholar 

  5. Perola, M. et al. Combined genome scans for body stature in 6,602 European twins: evidence for common Caucasian loci. PLoS Genet. 3, e97 (2007).

    Article  Google Scholar 

  6. Palmert, M.R. & Hirschhorn, J.N. Genetic approaches to stature, pubertal timing, and other complex traits. Mol. Genet. Metab. 80, 1–10 (2003).

    Article  CAS  Google Scholar 

  7. Weedon, M.N. et al. A common variant of HMGA2 is associated with adult and childhood height in the general population. Nat. Genet. 39, 1245–1250 (2007).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  9. Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).

    Article  CAS  Google Scholar 

  10. Freedman, M.L. et al. Assessing the impact of population stratification on genetic association studies. Nat. Genet. 36, 388–393 (2004).

    Article  CAS  Google Scholar 

  11. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  12. Dixon, A.L. et al. A genome-wide association study of global gene expression. Nat. Genet. 39, 1202–1207 (2007).

    Article  CAS  Google Scholar 

  13. Malumbres, M. & Barbacid, M. Mammalian cyclin-dependent kinases. Trends Biochem. Sci. 30, 630–641 (2005).

    Article  CAS  Google Scholar 

  14. Southam, L. et al. An SNP in the 5′-UTR of GDF5 is associated with osteoarthritis susceptibility in Europeans and with in vivo differences in allelic expression in articular cartilage. Hum. Mol. Genet. 16, 2226–2232 (2007).

    Article  CAS  Google Scholar 

  15. Miyamoto, Y. et al. A functional polymorphism in the 5′ UTR of GDF5 is associated with susceptibility to osteoarthritis. Nat. Genet. 39, 529–533 (2007).

    Article  CAS  Google Scholar 

  16. Lohmueller, K.E., Pearce, C.L., Pike, M., Lander, E.S. & Hirschhorn, J.N. Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat. Genet. 33, 177–182 (2003).

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  18. Lettre, G. et al. Identification of ten loci associated with height highlights new biological pathways in human growth. Nat. Genet. advance online publication, doi:10.1038/ng.125 (6 April 2008).

  19. Diabetes Genetics Initiative of Broad Institute of Harvard and M.I.T. et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316, 1331–1336 (2007).

  20. Zeggini, E. et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316, 1336–1341 (2007).

    Article  CAS  Google Scholar 

  21. Knight, B., Shields, B.M. & Hattersley, A.T. The Exeter Family Study of Childhood Health (EFSOCH): study protocol and methodology. Paediatr. Perinat. Epidemiol. 20, 172–179 (2006).

    Article  Google Scholar 

  22. Caulfield, M. et al. Genome-wide mapping of human loci for essential hypertension. Lancet 361, 2118–2123 (2003).

    Article  CAS  Google Scholar 

  23. Marques-Vidal, P. et al. Prevalence and characteristics of vitamin or dietary supplement users in Lausanne, Switzerland: the CoLaus study. Eur. J. Clin. Nutr. advance online publication, doi: 10.1038/sj.ejcn.1602932 (17 October 2007).

  24. 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  Google Scholar 

  25. Stirling, W.D. Enhancements to aid interpretation of probability plots. Statistician 31, 211–220 (1982).

    Article  Google Scholar 

  26. Gauderman, W.J. Sample size requirements for association studies of gene-gene interaction. Am. J. Epidemiol. 155, 478–484 (2002).

    Article  Google Scholar 

  27. Sandhu, M.S. et al. LDL-cholesterol concentrations: a genome-wide association study. Lancet 371, 483–491 (2008).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

M.N.W. is a Vandervell Foundation Research Fellow. C.L. is a Nuffield Department of Medicine Scientific Leadership Fellow. R.M.F. is funded by a Diabetes UK research studentship. S.B. is supported by the Giorgi-Cavaglieri Foundation and the Swiss National Science Foundation (grant 3100AO-116323/1), which also supports J.S.B. (grant 310000-112552/1). We would like to thank M. Bochud, Z. Kutalik, G. Waeber, K. Song and X. Yuan for their contribution to the Lausanne study. The WTCCC CAD cohort collection was supported by grants from the British Heart Foundation, Medical Research Council and National Health Service Research & Development. N.J.S. holds a chair supported by the British Heart Foundation. We thank the Wellcome Trust for funding. C.W. is funded by the British Heart Foundation (grant number FS/05/061/19501). The BRIGHT study is supported by the Medical Research Council (grant number G9521010D) and the British Heart Foundation (grant number PG02/128).

Author information

Authors and Affiliations

Authors

Consortia

Contributions

M.N.W., H.L., C.M.L., C.W., D.M.E., M.M., J.R.B.P., S.S., I.P., members of the DGI, WTCCC, the GEM consortium, S.B., T.J. and D.M.W. were responsible for analyzing, quality control checking and cleaning the data from the individual GWA studies. C.W., R.M.F., B.S., M.N.W. and H.L. were responsible for analysis of the stage 2 samples. M.N.W. performed the meta-analyses. A.S.H. and N.J.S. are principal investigators from the WTCCC-CAD study. M.C. and M.F. are principal investigators from the WTCCC-HT study. W.H.O. is principal investigator of the WTCCC-UKBS study. A.T.H. and M.I.M. are principal investigators for the WTCCC-T2D study. J.S.B., P.V. and V.M. are principal investigators of the CoLaus study. M.C., M.F., A.D. and P.B.M. are principal investigators on the BRIGHT study. A.T.H. is principal investigator of the EFSOCH study. C.N.A.P. and A.D.M. are principal investigators of the Tayside UKT2D-GCC study. M.N.W., H.L., A.T.H., M.I.M. and T.M.F. wrote the manuscript. A.T.H., M.I.M., M.N.W. and T.M.F. designed and led the study. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Timothy M Frayling.

Additional information

A full list of authors is provided in the Supplementary Note

A full list of authors is provided in the Supplementary Note

A full list of authors and affiliations appears at the end of this paper.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 1–5, Supplementary Figures 1–3, Supplementary Note (PDF 4393 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Weedon, M., Lango, H., Lindgren, C. et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat Genet 40, 575–583 (2008). https://doi.org/10.1038/ng.121

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.121

This article is cited by

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