Genome-wide pleiotropy of osteoporosis-related phenotypes: The framingham study

✍ Scribed by David Karasik; Yi-Hsiang Hsu; Yanhua Zhou; L Adrienne Cupples; Douglas P Kiel; Serkalem Demissie

• Publisher: American Society for Bone and Mineral Research
• Year: 2010
• Tongue: English
• Weight: 158 KB
• Volume: 25
• Category: Article
• ISSN: 0884-0431
• DOI: 10.1002/jbmr.38

✦ Synopsis

Abstract

Genome‐wide association studies offer an unbiased approach to identify new candidate genes for osteoporosis. We examined the Affymetrix 500K + 50K SNP GeneChip marker sets for associations with multiple osteoporosis‐related traits at various skeletal sites, including bone mineral density (BMD, hip and spine), heel ultrasound, and hip geometric indices in the Framingham Osteoporosis Study. We evaluated 433,510 single‐nucleotide polymorphisms (SNPs) in 2073 women (mean age 65 years), members of two‐generational families. Variance components analysis was performed to estimate phenotypic, genetic, and environmental correlations (ρ~P~, ρ~G~, and ρ~E~) among bone traits. Linear mixed‐effects models were used to test associations between SNPs and multivariable‐adjusted trait values. We evaluated the proportion of SNPs associated with pairs of the traits at a nominal significance threshold α = 0.01. We found substantial correlation between the proportion of associated SNPs and the ρ~P~ and ρ~G~ (r = 0.91 and 0.84, respectively) but much lower with ρ~E~ (r = 0.38). Thus, for example, hip and spine BMD had 6.8% associated SNPs in common, corresponding to ρ~P~ = 0.55 and ρ~G~ = 0.66 between them. Fewer SNPs were associated with both BMD and any of the hip geometric traits (eg, femoral neck and shaft width, section moduli, neck shaft angle, and neck length); ρ~G~ between BMD and geometric traits ranged from −0.24 to +0.40. In conclusion, we examined relationships between osteoporosis‐related traits based on genome‐wide associations. Most of the similarity between the quantitative bone phenotypes may be attributed to pleiotropic effects of genes. This knowledge may prove helpful in defining the best phenotypes to be used in genetic studies of osteoporosis. © 2010 American Society for Bone and Mineral Research