CYP17A1 (rs74357) polymorphism and polycystic ovary syndrome risk: a systemic review and meta-analysis

CYP17A1 (rs74357) polymorphism and polycystic ovary syndrome risk: a systemic review and meta-analysis

Authors

Keywords:

Polycystic ovary syndrome, CYP17A1 gene, Single nucleotide polymorphism, rs74357, meta-analysis

Abstract

Background and aim: To investigate the association between CYP17A1 (rs74357) polymorphism and the risk of Polycystic Ovary Syndrome (PCOS).

Methods: Literature on the association of CYP17rs74357 gene polymorphism and susceptibility to PCOS was retrieved by searching databases such as PubMed, Science Direct, Google Scholar and Embase from. The association measure was analyzed using an Odds Ratio (OR) and 95% Confidence Interval (CI). All the statistical analyses were executed using CMA 3.0 Software.

Results: In the present meta-analysis,24 studies including 3462 PCOS and 2898 controls were analyzed. The overall results validated that the 17 CYP17 T/C (rs74357) gene polymorphism was significantly associated with PCOS risk in 5 genetic models: recessive model (fixed and random effect), dominant model (random effect), CC vs. TT (fixed effect), CT vs. TT (fixed effect), and allele contrast (random effect). Stratified analyses by ethnicity/country also detected significant association between Asian and Caucasian under the recessive, dominant, CC vs. TT, CC vs. CT, and the allele contrast models.

Conclusions: In the present study, CYP17 T/C (rs74357) gene polymorphism increase the susceptibility of PCOS, and the recessive C allele, can be proposed as a predictive factor for the risk of PCOS or an important pathway in PCOS associated metabolic and hormonal dysregulation especially insulin resistance.However, larger sample size andmultiracial studies are needed in the future to confirm the findings.

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Published

03-08-2023

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ORIGINAL CLINICAL RESEARCH

How to Cite

1.
Rezgoun ML, El Khour D, Bendaoud H, Chellat D. CYP17A1 (rs74357) polymorphism and polycystic ovary syndrome risk: a systemic review and meta-analysis. Acta Biomed [Internet]. 2023 Aug. 3 [cited 2024 Jul. 18];94(4):e2023167. Available from: https://mattioli1885journals.com/index.php/actabiomedica/article/view/14229