Association between Gene Polymorphisms of Vitamin D Receptor and Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Int J Environ Res Public Health

Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China.

Published: December 2020

(1) Background: Studies on the association between Vitamin D receptor gene polymorphism and gestational diabetes mellitus have been inconsistent. The aim of this study was to summarize available evidence on the association between polymorphisms of Vitamin D receptor genes and susceptibility to gestational diabetes mellitus. (2) Methods: We searched databases of PubMed, Web of Science, Embase, China national knowledge infrastructure (CNKI), China science and technology journal database (VIP), and Wanfang Data for relevant articles. A systematic review and a meta-analysis were done to compare the distribution of Vitamin D receptor gene polymorphisms in gestational diabetes mellitus patients with those in controls using allelic, codominant, dominant, and recessive models. (3) Results: A total of eight eligible articles were included in the systematic review and of them, six articles were included in the meta-analysis. The vitamin D receptor gene rs7975232 polymorphism was associated with gestational diabetes mellitus under the allelic model (odds ratio = 1.28, 95% confidence interval 1.06-1.56), codominant model (CC vs. AA odds ratio = 1.97, 95% confidence interval 1.28-3.05), and recessive model (odds ratio = 1.83, 95% confidence interval 1.27-2.64) in the case of low heterogeneity. High heterogeneity existed in studies on the association of vitamin D receptor genes , , and with gestational diabetes mellitus, and the most common sources of heterogeneity were the year of publication and matching. (4) Conclusion: Polymorphism of the vitamin D receptor gene may be associated with risk of developing gestational diabetes mellitus. Future studies should be designed to include standardized data collection and matching for important confounding factors such as body mass index, age, and race.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794905PMC
http://dx.doi.org/10.3390/ijerph18010205DOI Listing

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