Abstract
Aim
Increasing scientific evidences suggest that common polymorphisms in the CYP1A1 and CYP11A1 genes may contribute to the development and progression of polycystic ovary syndrome (PCOS), but many existing studies have yielded inconclusive results. The aim of this study was to perform a meta-analysis of published studies on the associations between common polymorphisms in the CYP1A1 and CYP11A1 genes and susceptibility to PCOS.
Methods
An extensive literature search for relevant studies was conducted on PubMed, Embase, Web of Science, Cochrane Library, and CBM databases from their inception through 1 June, 2013. This meta-analysis was performed using the STATA 12.0 software. The crude risk ratio (RR) with 95 % confidence interval was calculated.
Results
Thirteen case–control studies were included in this meta-analysis with a total of 1,571 PCOS cases and 1,918 healthy controls. Our meta-analysis revealed that CYP1A1 MspI (rs4646903 T > C) polymorphism may increase the risk of PCOS, especially among Caucasian populations. Furthermore, CYP11A1 microsatellite [TTTA]n repeat polymorphism also showed significant associations with increased risk of PCOS among Caucasian populations. However, there was no statistically significant association between CYP1A1 Ile462Val (rs1048943 A > G) polymorphism and PCOS risk.
Conclusion
Our meta-analysis suggests that CYP1A1 MspI and CYP11A1 microsatellite [TTTA]n repeat polymorphisms may contribute to increasing susceptibility to PCOS among Caucasian populations. Detection of common polymorphisms in the CYP1A1 and CYP11A1 genes might be promising biomarkers for the diagnosis and prognosis of PCOS.
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Acknowledgments
We would like to acknowledge the helpful comments on this paper received from reviewers. We thank all our colleagues working in the Department of Gynecology, the First Hospital of China Medical University.
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We declare that we have no conflict of interest.
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Shen, W., Li, T., Hu, Y. et al. Common polymorphisms in the CYP1A1 and CYP11A1 genes and polycystic ovary syndrome risk: a meta-analysis and meta-regression. Arch Gynecol Obstet 289, 107–118 (2014). https://doi.org/10.1007/s00404-013-2939-0
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DOI: https://doi.org/10.1007/s00404-013-2939-0