Fasching, P. | Search bioRxiv

bioRxiv2020

Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations

We report a meta-analysis of breast, prostate, ovarian, and endometrial cancer genome-wide association data (effective sample size: 237,483 cases/317,006 controls). This identified 465 independent lead variants (P<5x10-8) across 192 genomic regions. Four lead variants were >1Mb from previously identified risk loci for the four cancers and an additional 23 lead variant-cancer associations were novel for one of the cancers. Bayesian models supported pleiotropic effects involving at least two cancers at 222/465 lead variants in 118/192 regions. Gene-level association analysis identified 13 shared susceptibility genes (P<2.6x10-6) in 13 regions not previously implicated in any of the four cancers and not uncovered by our variant-level meta-analysis. Several lead variants had opposite effects across cancers, including a cluster of such variants in the TP53 pathway. Fifty-four lead variants were associated with blood cell traits and suggested genetic overlaps with clonal hematopoiesis. Our study highlights the remarkable pervasiveness of pleiotropy across hormone-related cancers, further illuminating their shared genetic and mechanistic origins at variant- and gene-level resolution.

genetics↗

bioRxiv2018

Evaluating causal associations between previously reported risk factors and epithelial ovarian cancer: a Mendelian randomization analysis

BackgroundPreviously reported observational associations between risk factors and epithelial ovarian cancer (EOC) could reflect residual confounding, reverse causation, or measurement error. Mendelian randomization (MR) uses genetic variants as proxies for modifiable risk factors to strengthen causal inference in observational studies.\n\nMethodsWe used MR to evaluate the causal role of 13 previously reported risk factors in overall and histotype-specific EOC in up to 25,509 case subjects and 40,941 controls in the Ovarian Cancer Association Consortium. Inverse-variance weighted models were employed to generate effect estimates and MR-Egger, weighted median, and weighted mode were performed to examine evidence of horizontal pleiotropy. 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.\n\nResultsThere was strong or suggestive evidence that 9 of 13 risk factors were causally associated with overall or histotype-specific EOC. Genetic liability to endometriosis was strongly associated with EOC (OR per log odds higher liability: 1.27,95%CI:1.16-1.40;P=6.94x10-7) and lifetime smoking exposure was suggestively associated with EOC (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 that genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone-binding globulin were associated with ovarian cancer or its subtypes.\n\nConclusionsOur comprehensive examination of possible etiological drivers of ovarian carcinogenesis supports a causal role for few of these factors in epithelial ovarian cancer and suggests distinct etiologies across histotypes.

epidemiology↗