Association between fat mass and obesity associated (FTO) gene rs9939609 A/T polymorphism and polycystic ovary syndrome: A systematic review and meta-analysis

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Abstract

Background: Up to now, numerous case-control studies have reported the associations between fat mass and obesity associated (FTO) gene rs9939609 A/T polymorphism and polycystic ovary syndrome (PCOS), however, without a consistent result. Hence we performed current systematic review and meta-analysis to clarify the controversial results. Methods: Case-control studies reporting the relationship of rs9939609 A/T polymorphism and PCOS published before April 2015 were searched in Pubmed database without language restriction. Data was analyzed by Review Manager 5.2. Results: A total of five studies involving 5010 PCOS patients and 5300 controls were included for further metaanalysis. The results of meta-analysis showed that the FTO gene rs9939609 A/T polymorphism was significantly different between PCOS group and control group in different gene models (For AA + AT vs. TT: OR = 1.41, 95% CI = 1.28-1.55, P < 0.00001. For AA vs. AT + TT: OR = 1.54, 95% CI = 1.25-1.89, P < 0.0001. For AA vs. TT: OR = 1. 74, 95% CI = 1.38-2.18, P < 0.00001. For A vs. T: OR = 1.36, 95% CI = 1.25-1.47, P < 0.00001, respectively) suggesting that A allele was a risk factor for PCOS susceptibility. Furthermore, subgroup analysis in Asian and Caucasian ethnicities also found significant association between rs9939609 A/T polymorphism and PCOS (In Asian subgroup: OR = 1.43, 95% CI = 1.29-1.59, P < 0.0001. In Caucasian subgroup: OR = 1.33, 95% CI = 1.08-1.64, P = 0.008) Conclusion: This meta-analysis suggests that rs9939609 A/T polymorphism of FTO gene is associated with PCOS risk, and that A allele is a risk factor for PCOS susceptibility simultaneously.

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Liu, A. L., Xie, H. J., Xie, H. Y., Liu, J., Yin, J., Hu, J. S., & Peng, C. Y. (2017). Association between fat mass and obesity associated (FTO) gene rs9939609 A/T polymorphism and polycystic ovary syndrome: A systematic review and meta-analysis. BMC Medical Genetics, 18(1). https://doi.org/10.1186/s12881-017-0452-1

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