Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10-6), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10-8). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10-11). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.
|Original language||English (US)|
|Number of pages||13|
|Journal||American Journal of Human Genetics|
|State||Published - Jan 7 2011|
Bibliographical noteFunding Information:
We thank the researchers, staff, and participants of all of the studies that contributed data. Specific cohort acknowledgements are cited in the Supplemental Acknowledgments . Matthew B. Lanktree is supported by a Canadian Institutes of Health Research (CIHR) M.D.-Ph.D. Studentship Award. Robert A. Hegele is funded by CIHR grant 79533 and by Genome Canada through the Ontario Genomics Institute.