Publications

Abstract

Over the past decade, several genetic variants or genes for osteoporosis have been identified through genome-wide association studies and candidate gene association studies. These genetic variants are common in the general population but have modest effect sizes, with odds ratio ranging from 1.1 to 1.5. Thus, the utility of any single variant is limited. However, theoretical and empirical studies have suggested that a profiling of multiple variants that are associated with bone phenotypes (i.e., "osteogenomic profile") can improve the accuracy of fracture prediction and classification beyond that obtained by conventional clinical risk factors. These results support the view that an osteogenomic profile, when integrated into existing models, can help clinicians and patients alike to better assess the risk fracture for an individual, and raise the possibility of personalized osteoporosis care.