Association between IGF-1 polymorphisms and risk of osteoporosis in Chinese population: A meta-analysis

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Abstract

Background: Several studies looking into the association between insulin-like growth factor-1 (IGF-1) gene polymorphisms and osteoporosis predisposition have been conducted among Chinese population with conflicting outcomes. The present systematic review and meta-analysis was performed to appraise and synthesize the existing evidence, so as to provide a more precise and reliable association between polymorphisms in IGF-1 gene and osteoporosis. Methods: Five electronic databases including PubMed, EMBASE, ISI Web of Science, CNKI and Wanfang were systematically searched for potential studies. Summary odds ratio (OR) and corresponding 95% confidence interval (95% CI) were calculated to evaluate the association. The best-matching genetic model of inheritance was determined using a genetic-model free approach. Results: Six case-control studies comprising 2068 osteoporosis patients and 2071 healthy controls were obtained for the meta-analysis. Dominant model was confirmed to be the best-matching genetic model (TT + TC versus CC). The overall data suggested that rs35767 polymorphism was significantly associated with osteoporosis vulnerability (OR 1.21, 95% CI 1.07, 1.37; P = 0.002). When stratifying the participants and performing subgroup-analysis according to source of patients, the result suggested that rs35767 was significantly correlated to osteoporosis in post-menopausal women subgroup (OR 1.29, 95% CI 1.08, 1.54; P = 0.005), but the correlation was not established in the subgroup of both gender (OR 1.14, 95% CI 0.96, 1.35; P = 0.12). Conclusion: Taken together, the findings of our current study suggested a significant association between rs35767 polymorphism and risk of osteoporosis in Chinese post-menopausal women.

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Gao, S. T., Lv, Z. T., Zhou, C. K., Mao, C., & Sheng, W. B. (2018). Association between IGF-1 polymorphisms and risk of osteoporosis in Chinese population: A meta-analysis. BMC Musculoskeletal Disorders, 19(1). https://doi.org/10.1186/s12891-018-2066-y

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