Association of candidate gene () polymorphism with polycystic ovary syndrome: meta-analysis and statistical power analysis.

J Turk Ger Gynecol Assoc

Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam-603 103, Tamil Nadu, India.

Published: August 2024

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder that impacts women before reaching menopause. In addition to notable features (irregular ovulation, elevated androgen levels, and the existence of numerous ovarian cysts), individuals with PCOS frequently encounter diverse metabolic, cardiovascular, and psychological conditions. The onset of PCOS is influenced by a combination of factors, and various genetic variations are believed to play a significant role in its progression. The objective of the current study was to explore the link between genetic variations in the candidate genes gene and insulin receptor () and susceptibility to developing PCOS. We conducted an extensive search across various databases, including Google Scholar, PubMed, Science Direct, Scopus, and EMBASE, to compile relevant case-control studies and literature reviews for subsequent statistical analysis. In the present study, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was followed, a guideline for Systematic Reviews and Meta-Analysis. While a previous meta-analysis explored the correlation between rs1799817 and rs13429458 and their association with susceptibility to PCOS, our current study did not integrate any findings from these prior investigations. Our research encompassed articles published between 2017 and 2023, and we employed MetaGenyo software to assess the collected data. Statistical power analysis was performed using G*Power 3.1 software. Odds ratios and their corresponding 95% confidence intervals were calculated for each genetic model. Fifteen studies that met the criteria were analyzed. Out of these, ten studies, involving 1,189 cases and 1,005 controls, examined the rs1799817 gene polymorphism, while five studies, including 783 cases and 553 controls, investigated the rs13429458 gene polymorphism. The meta-analysis results indicated that there was no statistically significant association between the rs1799817 gene polymorphism and the risk of PCOS (p>0.05). In contrast, the rs13429458 gene polymorphism showed a significant association with PCOS risk under the over-dominant model (p<0.05). The present meta-analysis demonstrated a notable association between the rs13429458 gene polymorphism and the likelihood of developing PCOS. Further rigorous studies with expanded sample sizes and diverse ethnic representation will be important to comprehensively evaluate and validate these findings.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11576651PMC
http://dx.doi.org/10.4274/jtgga.galenos.2024.2024-1-7DOI Listing

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