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Pharmacogenomics in osteoporosis: Steps toward personalized medicine

Authors Greene R, Mousa SS, Ardawi M, Qari M, Mousa SA

Published 10 September 2009 Volume 2009:2 Pages 69—78

DOI https://doi.org/10.2147/PGPM.S5803

Review by Single anonymous peer review

Peer reviewer comments 6



Robert Greene1, Shaymaa S Mousa, Mohamed Ardawi2, Mohamed Qari2, Shaker A Mousa1

1The Pharmaceutical Research Institute, Albany College of Pharmacy and Health Sciences, Albany, NY, USA; 2Center of Excellence in Osteoporosis Research, King Abdul Aziz University, Jeddah, Saudi Arabia

Abstract: Osteoporosis is a complicated and preventable disease with major morbidity complications that affects millions of people. In the last 15 years, there have been numerous studies and research in the new fields of pharmacogenetics and pharmacogenomics related to osteoporosis. Numerous “candidate genes” have been identified and have been found to be associated with osteoporosis as well as the treatment of osteoporosis. Many studies have found conflicting results on different polymorphisms and whether or not they are related to bone mineral density and osteoporosis. There is a need for larger and better designed pharmacogenomic studies related to osteoporosis incorporating a greater variety of candidate genes. The evaluation of osteoporosis and fracture risk is moving from a risk stratification approach to a more individualized approach, in which an individual’s absolute risk of fracture is evaluable as a constellation of the individual’s environmental exposure and genetic makeup. Therefore, the identification of gene variants associated with osteoporosis phenotypes or response to therapy might help individualize the prognosis, treatment, and prevention of fracture. This review focuses on major candidate genes and what needs to be done to take the genetics of osteoporosis and incorporate them into the pharmacogenomics of the management of osteoporosis.

Keywords: pharmacogenomics, osteoporosis, VDR, ER-alpha, CYP19 Gene, LRP5, COLIA1, polymorphisms, genetics

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