GENETIC OF BONE GEOMETRY: FRAMINGHAM COHORTS

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DESCRIPTION (provided by applicant): This supplemental application is an extension of our recently funded R01 (AR050066-01), of which the primary aim is to perform a genome screen to identify multivariate linkage of bone geometry indices with a set of autosomal microsatellite markers. The primary goal of this proposed study is to test for associations of candidate genes with geometrical properties of bone. This study will take advantage of existing hand x-rays and dual x-ray absorptiometry scans of the hip from participants of the Framingham Heart Study, one of the longest running cohort studies in the world. The specific hypotheses of this supplement are: - Genetic factors explain a significant portion of variability in geometric indices that will be derived as part of this project in both the weight-bearing femur and in non weight-bearing metacarpals - Polymorphisms in genes coding for bone matrix proteins, gonadal steroids, growth factors, and cytokines, will be associated with indices of bone geometry at two skeletal sites. In the proposed study, data from both related and unrelated Framingham participants will be used to perform genetic association analyses of bone geometry indices with a number of genes that are likely to play a role in the determination of bone geometry. Our general approach will be to test an association and linkage/association between candidate genetic polymorphisms and bone geometric phenotypes, using a sample of unrelated individuals, as well as a sample of family members from Framingham. Our selection of candidate genes for this work will be determined from three main sources of information: 1) published literature, 2) expression profiling of mouse femora mechanically stimulated ex vivo, and 3) collaboration with mouse geneticists through the use of refined bone imaging data and microarray data from congenic mouse strains. Bone geometry is an important measure of bone fragility and risk of osteoporotic fractures. Elucidation of genetic and molecular mechanisms underlying bone strength will ultimately lead to the identification of the individuals at highest risk of osteoporotic fractures who can be targeted for therapeutic interventions.