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. 2008 May;40(5):575-83.
doi: 10.1038/ng.121. Epub 2008 Apr 6.

Genome-wide Association Analysis Identifies 20 Loci That Influence Adult Height

Free PMC article

Genome-wide Association Analysis Identifies 20 Loci That Influence Adult Height

Michael N Weedon et al. Nat Genet. .
Free PMC article


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 x 10(-7), with 10 reaching P < 1 x 10(-10)). Combined, the 20 SNPs explain approximately 3% of height variation, with a approximately 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.


Figure 1
Figure 1
Quantile-quantile plots for the 402,951 SNPs from the genome-wide association meta-analysis as more studies are added in. (a) n = 1,914 (WTCCC-T2D). (b) n = 4,892 (adding DGI). (c) n = 6,788 (adding WTCCC-HT). (d) n = 8,668 (adding WTCCC-CAD). (e) n = 12,228 (adding EPIC-Obesity). (f) n = 13,665 (adding WTCCC-UKBS). Blue line represents the observed P values. The black line is the expected line under the null distribution. The gray bands are 95% concentration bands, which are an approximation to the 95% confidence intervals around the expected line.
Figure 2
Figure 2
Manhattan plot for the 402,951 SNPs from the stage 1 genomewide association meta-analysis of the WTCCC-T2D, DGI, WTCCC-HT, WTCCC-CAD, EPIC-Obesity and WTCCC-UKBS studies. The red dots represent the SNPs that reached a P < 5 × 10−7 in a joint analysis of stage 1 and stage 2 samples.
Figure 3
Figure 3
The combined impact of the 20 SNPs with a P < 5 × 10−7. Subjects were classified according to the number of ‘tall’ alleles at each of the 20 SNPs; the mean height for each group is plotted (blue dots). The black line is a linear regression line through these points. The gray bars represent the proportion of the sample with increasing numbers of ‘tall’ alleles. The approximate height difference (cm) was obtained by multiplying the mean Z-score height for each group by 6.82 cm (the approximate average s.d. of height across the samples used in this study).
Figure 4
Figure 4
Power estimates. (a) The power of the genome-wide study to identify the variants that had a P < 5 x 10−7 in the joint analysis at P < 1 × 10−5 using the effect size estimates from the follow-up samples only. (b) The sample size required to identify these variants using the effect size estimates from the follow-up samples only at a P < 5 ~ 10−7 with 80% power. Effect sizes ranged from 0.083s.d. with MAF ~0.44 for rs6440003 to 0.033s.d. with MAF of 0.35 for rs8099594.
Figure 5
Figure 5
Comparison of results across independent meta-analyses. Quantile-quantile plot for the P values from the accompanying Lettre et al. study of the most associated 10,000 SNPs from our study (excluding the DGI component to make the observations independent), including (dark blue dots) and excluding known loci (light blue dots). The black line is the expected line under the null distribution. The gray band represents the 95% concentration bands, which are an approximation to the 95% confidence intervals around the expected line.

Comment in

  • Sizing up human height variation.
    Visscher PM. Visscher PM. Nat Genet. 2008 May;40(5):489-90. doi: 10.1038/ng0508-489. Nat Genet. 2008. PMID: 18443579 No abstract available.

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