Evidence for major pleiotropic effects on bone size variation from a principal component analysis of 451 Caucasian families
Abstract
Aim: To identify pleiotropic quantitative trait loci (QTL) influencing bone size (BS) at different skeletal sites in Caucasians.
Methods: In a sample containing 3899 Caucasians from 451 pedigrees, 410 microsatellite markers spaced ~8.9 cM apart across the human genome were genotyped. Phenotypical and genetic correlations of BS at lumbar spine, hip (femoral neck, trochanter, and intertrochanter regions), and wrist (ultradistal, mid-distal, and one-third distal sites) were determined using bivariate quantitative genetic analysis. A principal component analysis (PCA) was performed to obtain principal component (PC) factors that were then subjected to variance components linkage analysis to identify regions linked to the PC.
Results: Genetic correlations of BS at different skeletal sites ranged fr om 0.40 to 0.7 9 (P<0.001). The PCA yielded a PC named PCtotal, which explained up to 76% of the total (co)variation of all the BS at the 7 skeletal sites for the whole sample. We identified a QTL influencing the BS of multiple skeletal sites on chromosome 7 at 140 cM [logarithm of odds (LOD)=2.85] in the overall sample. Sex-specific evidence for linkage was observed on chromosome 11 at 53 cM (LOD =2.82) in the male-only data subset.
Conclusion: Our study identified several genomic regions that may have pleiotropic effects on different skeletal sites. These regions may contain genes that play a critical role in overall bone development and osteoporosis at multiple skeletal sites, hence are biologically and clinically important.
Keywords:
Methods: In a sample containing 3899 Caucasians from 451 pedigrees, 410 microsatellite markers spaced ~8.9 cM apart across the human genome were genotyped. Phenotypical and genetic correlations of BS at lumbar spine, hip (femoral neck, trochanter, and intertrochanter regions), and wrist (ultradistal, mid-distal, and one-third distal sites) were determined using bivariate quantitative genetic analysis. A principal component analysis (PCA) was performed to obtain principal component (PC) factors that were then subjected to variance components linkage analysis to identify regions linked to the PC.
Results: Genetic correlations of BS at different skeletal sites ranged fr om 0.40 to 0.7 9 (P<0.001). The PCA yielded a PC named PCtotal, which explained up to 76% of the total (co)variation of all the BS at the 7 skeletal sites for the whole sample. We identified a QTL influencing the BS of multiple skeletal sites on chromosome 7 at 140 cM [logarithm of odds (LOD)=2.85] in the overall sample. Sex-specific evidence for linkage was observed on chromosome 11 at 53 cM (LOD =2.82) in the male-only data subset.
Conclusion: Our study identified several genomic regions that may have pleiotropic effects on different skeletal sites. These regions may contain genes that play a critical role in overall bone development and osteoporosis at multiple skeletal sites, hence are biologically and clinically important.