Assessment of Bidirectional Relationship between Polycystic Ovary Syndrome and Depression: A Two-Sample Mendelian Randomization Study

Abstract

Background: Evidence from observation studies has implied an association between polycystic ovary syndrome (PCOS) and risk of depression. Nevertheless, it remains elusive if the identified correlation is causal or owing to biases in observation researches. Hence, we utilized a bidirectional two-sample Mendelian randomization (MR) method to evaluate the potential causal relationship between PCOS and depression. Methods: Genetic instruments for PCOS and depression were acquired from two large genome-wide association studies (GWASs). MR analyses were completed via the inverse-variance weighted (IVW) method and weighted median approaches. The underlying pleiotropy was tested by MR-Egger regression, and leave-one-out method was used to evaluate the stability of MR results. Results: Using the IVW analyses (odds ratio (OR) = 1.07, 95% confidence interval (CI) = 1.01–1.06, p < 0.01) and weighted median approach (OR = 1.04, 95% CI = 1.00–1.08, p < 0.05), we found that PCOS was related to an elevated risk of depression. MR-Egger regression did not identify potential horizontal pleiotropy. Sensitivity analyses using leave-one-out method also provided supportive evidence. In the reverse MR analyses, we did not observe causal effect of depression on PCOS (p > 0.05). Conclusions: The present study provides evidence to support a potential causal association between PCOS and an elevated risk of depression. Hence, early psychological intervention for PCOS might show anti-depression benefits.