Breast cancer risk in patients with polycystic ovary syndrome: a Mendelian randomization analysis

Purpose The association between polycystic ovary syndrome (PCOS) and breast cancer remains inconclusive. Conventional observational studies are susceptible to inverse causality and potential confounders. With a Mendelian randomization (MR) approach, we aimed to investigate the causal relationship between genetically predicted PCOS and breast cancer risk. Methods Our study included 11 PCOS-associated single nucleotide polymorphisms as instrumental variables identified by the latest genome-wide association study. Individual-level genetic summary data of participants were obtained from the Breast Cancer Association Consortium, with a total of 122,977 cases and 105,974 controls. The inverse-variance weighted method was applied to estimate the causality between genetically predicted PCOS and breast cancer risk. To further evaluate the pleiotropy, the weighted median and MR-Egger regression methods were implemented as well. Results Our study demonstrated that genetically predicted PCOS was causally associated with an increased risk of overall breast cancer (odds ratio (OR) = 1.07; 95% confidence interval (CI) 1.02–1.12, p = 0.005). The subgroup analyses according to immunohistochemical type further illustrated that genetically predicted PCOS was associated with an increased risk of estrogen receptor (ER)-positive breast cancer (OR = 1.09; 95% CI 1.03–1.15, p = 0.002), while no causality was observed for ER-negative breast cancer (OR = 1.02; 95% CI 0.96–1.09, p = 0.463). In addition, no pleiotropy was found in our study. Conclusions Our findings indicated that PCOS was likely to be a causal factor in the development of ER-positive breast cancer, providing a better understanding for the etiology of breast cancer and the prevention of breast cancer.