Abstract
While epidemiological studies have associated endometriosis with ovarian cancer risk, the causal relationships across anatomic subtypes and histotypes remain undefined. Using two-sample Mendelian randomization with 84 genetic instruments (F-statistic = 30.01-228.09), we analyzed genome-wide data from 20,190 endometriosis cases and 25,509 ovarian cancer patients. Genetically proxied endometriosis significantly increased risks of overall ovarian cancer [OR = 1.18, 95% confidence interval (95%CI): 1.10-1.28), high-grade serous (OR:1.12, 95% CI 1.01-1.23), clear cell (OR:1.87, 95% CI 1.44-2.43), and endometrioid carcinomas (OR:1.48, 95% CI 1.30-1.69)]. Anatomic subtype analyses revealed differential effects. Pelvic peritoneal lesions showed the highest risk for clear cell carcinoma (OR = 1.81, 95% CI 1.52-2.16). Deep endometriosis broadly impacted high-grade serous (OR = 1.10, 95% CI 1.04-1.17) and endometrioid carcinomas (OR = 1.25, 95% CI 1.13-1.40). Ovarian endometriosis specifically elevated clear cell (OR = 1.65, 95% CI 1.46-1.86) and endometrioid risks (OR = 1.48, 95% CI 1.30-1.69;). Rectovaginal lesions selectively increased endometrioid carcinoma risk (OR = 1.25, 95% CI 1.04-1.51). No associations were emerged between any type of endometriosis for low-grade serous or invasive mucinous ovarian. Significant heterogeneity was detected in ovarian endometriosis-mucinous cancer associations persisting after MR-PRESSO outlier correction, while other associations retained consistent effect sizes post-adjustment. Funnel plot symmetry, leave-one-out stability, and MR-Egger intercept collectively confirmed result robustness without directional pleiotropy. This study provides novel evidence that endometriosis causally increases risk of specific ovarian cancer histotypes, particularly demonstrating that anatomic subtypes represent distinct etiological entities with differential oncogenic potential, where pelvic peritoneal lesions emerge as a previously underappreciated high-risk subtype for clear cell carcinoma development, thereby offering critical insights for refining risk stratification protocols and guiding targeted surveillance strategies in clinical practice.