AbstractBackgroundVarious modifiable risk factors have been associated with epithelial ovarian cancer risk in observational epidemiological studies. However, the causal nature of the risk factors reported, and thus their suitability as effective intervention targets, is unclear given the susceptibility of conventional observational designs to residual confounding and reverse causation. Mendelian randomization uses genetic variants as proxies for modifiable risk factors to strengthen causal inference in observational studies. We used Mendelian randomization to evaluate the causal role of 13 previously reported risk factors (reproductive, anthropometric, clinical, lifestyle, and molecular factors) in overall and histotype-specific epithelial ovarian cancer in up to 25,509 case subjects and 40,941 controls in the Ovarian Cancer Association Consortium.Methods and FindingsGenetic instruments to proxy 13 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) robustly (P<5×10−8) and independently associated with each respective risk factor in previously reported genome-wide association studies. SNPs were combined into multi-allelic inverse-variance weighted fixed or random-effects models to generate causal estimates. Three complementary sensitivity analyses were performed to examine violations of Mendelian randomization assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P-value threshold was used to establish “strong evidence” (P<0.0038) and “suggestive evidence” (0.0038<P<0.05) for associations.In Mendelian randomization analyses, there was strong or suggestive evidence that 9 of 13 risk factors had a causal effect on overall or histotype-specific epithelial ovarian cancer. There was strong evidence that genetic liability to endometriosis increased risk of epithelial ovarian cancer (OR per log odds higher liability:1.27, 95% CI: 1.16-1.40; P=6.94×10−7) and suggestive evidence that lifetime smoking exposure increased risk of epithelial ovarian cancer (OR per unit increase in smoking score:1.36, 95% CI: 1.04-1.78; P=0.02). In histotype-stratified analyses, the strongest associations found were between: height and clear cell carcinoma (OR per SD increase:1.36, 95% CI: 1.15-1.61; P=0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset:1.09, 95% CI: 1.02-1.16; P=0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per log odds higher liability:0.74, 95% CI:0.62-0.90; P=0.002). There was little evidence for an effect of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone-binding globulin on ovarian cancer or its subtypes. The primary limitations of this analysis include: modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the causal effects of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptives, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk.ConclusionsOur comprehensive examination of possible etiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a causal role for few of these factors in epithelial ovarian cancer and suggests distinct etiologies across histotypes. The identification of novel modifiable risk factors remains an important priority for the control of epithelial ovarian cancer.
Genetic variants within the cancer susceptibility region 8q24 and ovarian cancer risk in Han Chinese women
