Journal
EUROPEAN JOURNAL OF HUMAN GENETICS
Volume 17, Issue 2, Pages 258-266Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/ejhg.2008.152
Keywords
body height; body mass index; linkage mapping; quantitative trait loci
Funding
- European Commission [QLG2-CT-2002-01254]
- Center of Excellence in Disease Genetics of the Finnish Academy, Biocentrum Helsinki
- NIH [DK55523, AR062277, AR042460, AI024717]
- National Heart, Lung, and Blood Institute (NHLBI)
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Stature (adult body height) and body mass index (BMI) have a strong genetic component explaining observed variation in human populations; however, identifying those genetic components has been extremely challenging. It seems obvious that sample size is a critical determinant for successful identification of quantitative trait loci (QTL) that underlie the genetic architecture of these polygenic traits. The inherent shared environment and known genetic relationships in family studies provide clear advantages for gene mapping over studies utilizing unrelated individuals. To these ends, we combined the genotype and phenotype data from four previously performed family-based genome-wide screens resulting in a sample of 9.371 individuals from 3.032 African-American and European-American families and performed variance-components linkage analyses for stature and BMI. To our knowledge, this study represents the single largest family-based genome-wide linkage scan published for stature and BMI to date. This large study sample allowed us to pursue population- and sex-specific analyses as well. For stature, we found evidence for linkage in previously reported loci on 11q23, 12q12, 15q25 and 18q23, as well as 15q26 and 19q13, which have not been linked to stature previously. For BMI, we found evidence for two loci: one on 7q35 and another on 11q22, both of which have been previously linked to BMI in multiple populations. Our results show both the benefit of (1) combining data to maximize the sample size and (2) minimizing heterogeneity by analyzing subgroups where within-group variation can be reduced and suggest that the latter may be a more successful approach in genetic mapping.
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