Assessment of gene-by-sex interaction effect on bone mineral density

Abstract

Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed expression quantitative trait loci (eQTL) analysis and bioinformatics network analysis. We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS) and femoral neck (FN) BMD in 25,353 individuals from 8 cohorts. In a second stage, we followed up the 12 top single-nucleotide polymorphisms (SNPs; p < 1 × 10(-5) ) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 and p = 3.0 × 10(-5) ; female effect = -0.007 and p = 3.3 × 10(-2) ), and 11 suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (p < 5 × 10(-8) ) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found to influence BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. © 2012 American Society for Bone and Mineral Research.

Figure 1. Power Analysis

This plot presents the relationship between detectable gene-by-sex interaction effect size with 80% power and minor allele frequency. Specifically, we used the parameter estimates of rs1405534 in LSBMD (SD = 0.187 at genome-wide significant level of 5×10⁻⁸) along its relevant parameter estimates (effect size of −0.0048 for SNP and of −0.0219 for SEX), as the setting for our power analysis. The sample size used is 25,353 for discovery cohort and 50,000 (estimated) for discovery + replication cohort. With the sample of size 50,000, we would have 80% power to detect gene-by-sex interaction effect of 0.018 or larger in LSBMD for the SNP with minor allele frequency of 0.25. This would explain 0.08% variation of LSBMD. With 25,353 individuals in the Discovery stage, we did not have adequate power to identify interaction reaching genome-wide significant level (p < 5×10⁻⁸) at any allele frequency.