Causal association between BMI and polycystic ovarian syndrome: Bidirectional two-sample Mendelian randomization study

Abstract Objective The study aimed to explore the causal effect of body mass index (BMI) on polycystic ovarian syndrome (PCOS). Methods Genome-wide association data for BMI and PCOS were sourced from the Mendelian randomization (MR) base platform. Significantly associated single nucleotide polymorphisms (SNPs) for BMI served as instrumental variables in bidirectional two-sample MR analyses to investigate the causal relationship between BMI and PCOS. Analytical techniques utilized encompassed the inverse-variance weighted (IVW) method, weighted median estimator, and MR-Egger regression. Results We identified 427 SNPs significantly associated with BMI (P < 5 × 10−8; linkage disequilibrium r2 < 0.001). Various methods consistently revealed a positive association between BMI and PCOS (IVW: odds ratio (OR) 2.027, 95% confidence interval (CI) 1.599–2.596; weighted median estimator: OR 2.368, 95% CI 1.653-3.392; MR-Egger Method: OR 3.610, 95% CI 1.795–7.263), indicating that higher BMI correlates with an increased risk of PCOS. Additionally, we observed a causal effect of genetic predisposition to PCOS on BMI (IVW: OR 1.020, 95% CI (1.019–1.022); weighted median estimator: OR 1.017, 95% CI (1.015–1.019); MR-Egger Method: OR 1.000, 95% CI (0.995–1.005)). Conclusion The MR analysis furnished compelling evidence suggesting a causal relationship between elevated BMI and the risk of PCOS, as well as indicating that the severity of PCOS may contribute to elevated BMI levels.