Causal Association Between BMI and Polycystic Ovarian Syndrome: Bidirectional 2-Sample Mendelian Randomization Study

Abstract

Objective: This 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 2-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% 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.