Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10^-8, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

One of the authors did not declare a potential conflict of interest. The statement in the article should have read: “Conflict of interest: Patricia Moorman has received compensation for work related to litigation in regard to talc and ovarian cancer. The other authors declare no conflicts"

The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10-12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies <0.5%. The area under the receiver operating characteristic curve (AUC) for REVEL was 0.046-0.182 higher in an independent test set of 935 recent SwissVar disease variants and 123,935 putatively neutral exome sequencing variants and 0.027-0.143 higher in an independent test set of 1,953 pathogenic and 2,406 benign variants recently reported in ClinVar than the AUCs for other ensemble methods. We provide pre-computed REVEL scores for all possible human missense variants to facilitate the identification of pathogenic variants in the sea of rare variants discovered as sequencing studies expand in scale.

Limited estimates exist on risk factors for epithelial ovarian cancer (EOC) in Asian, Hispanic, and Native Hawaiian/Pacific Islander women. Participants in this study included 1734 Asian (n = 785 case and 949 control participants), 266 Native Hawaiian/Pacific Islander (n = 99 case and 167 control participants), 1149 Hispanic (n = 505 case and 644 control participants), and 24 189 White (n = 9981 case and 14 208 control participants) from 11 studies in the Ovarian Cancer Association Consortium. Logistic regression models estimated odds ratios (ORs) and 95% CIs for risk associations by race and ethnicity. Heterogeneity in EOC risk associations by race and ethnicity (P ≤ .02) was observed for oral contraceptive (OC) use, parity, tubal ligation, and smoking. We observed inverse associations with EOC risk for OC use and parity across all groups; associations were strongest in Native Hawaiian/Pacific Islander and Asian women. The inverse association for tubal ligation with risk was most pronounced for Native Hawaiian/Pacific Islander participants (odds ratio (OR) = 0.25; 95% CI, 0.13-0.48) compared with Asian and White participants (OR = 0.68 [95% CI, 0.51-0.90] and OR = 0.78 [95% CI, 0.73-0.85], respectively). Differences in EOC risk factor associations were observed across racial and ethnic groups, which could be due, in part, to varying prevalence of EOC histotypes. Inclusion of greater diversity in future studies is essential to inform prevention strategies. This article is part of a Special Collection on Gynecological Cancers.

Background

Parity is associated with decreased risk of invasive ovarian cancer; however, the relationship between incomplete pregnancies and invasive ovarian cancer risk is unclear. This relationship was examined using 15 case-control studies from the Ovarian Cancer Association Consortium (OCAC). Histotype-specific associations, which have not been examined previously with large sample sizes, were also evaluated.

Methods

A pooled analysis of 10 470 invasive epithelial ovarian cancer cases and 16 942 controls was conducted. Odds ratios (ORs) and 95% confidence intervals (CIs) for the association between incomplete pregnancies and invasive epithelial ovarian cancer were estimated using logistic regression. All models were conditioned on OCAC study, race and ethnicity, age, and education level and adjusted for number of complete pregnancies, oral contraceptive use, and history of breastfeeding. The same approach was used for histotype-specific analyses.

Results

Ever having an incomplete pregnancy was associated with a 16% reduction in ovarian cancer risk (OR = 0.84, 95% CI = 0.79 to 0.89). There was a trend of decreasing risk with increasing number of incomplete pregnancies (2-sided Ptrend < .001). An inverse association was observed for all major histotypes; it was strongest for clear cell ovarian cancer.

Conclusions

Incomplete pregnancies are associated with a reduced risk of invasive epithelial ovarian cancer. Pregnancy, including incomplete pregnancy, was associated with a greater reduction in risk of clear cell ovarian cancer, but the result was broadly consistent across histotypes. Future work should focus on understanding the mechanisms underlying this reduced risk.

Background

Ovarian cancer incidence differs substantially by race/ethnicity, but the reasons for this are not well understood. Data were pooled from the African American Cancer Epidemiology Study (AACES) and 11 case-control studies in the Ovarian Cancer Association Consortium (OCAC) to examine racial/ethnic differences in epidemiological characteristics with suspected involvement in epithelial ovarian cancer (EOC) aetiology.

Methods

We used multivariable logistic regression to estimate associations for 17 reproductive, hormonal and lifestyle characteristics and EOC risk by race/ethnicity among 10 924 women with invasive EOC (8918 Non-Hispanic Whites, 433 Hispanics, 911 Blacks, 662 Asian/Pacific Islanders) and 16 150 controls (13 619 Non-Hispanic Whites, 533 Hispanics, 1233 Blacks, 765 Asian/Pacific Islanders). Likelihood ratio tests were used to evaluate heterogeneity in the risk factor associations by race/ethnicity.

Results

We observed statistically significant racial/ethnic heterogeneity for hysterectomy and EOC risk (P = 0.008), where the largest odds ratio (OR) was observed in Black women [OR = 1.64, 95% confidence interval (CI) = 1.34-2.02] compared with other racial/ethnic groups. Although not statistically significant, the associations for parity, first-degree family history of ovarian or breast cancer, and endometriosis varied by race/ethnicity. Asian/Pacific Islanders had the greatest magnitude of association for parity (≥3 births: OR = 0.38, 95% CI = 0.28-0.54), and Black women had the largest ORs for family history (OR = 1.77, 95% CI = 1.42-2.21) and endometriosis (OR = 2.42, 95% CI = 1.65-3.55).

Conclusions

Although racial/ethnic heterogeneity was observed for hysterectomy, our findings support the validity of EOC risk factors across all racial/ethnic groups, and further suggest that any racial/ethnic population with a higher prevalence of a modifiable risk factor should be targeted to disseminate information about prevention.

Cigarette smoking is associated with an increased risk of developing mucinous ovarian tumors but whether it is associated with ovarian cancer survival overall or for the different histotypes is unestablished. Furthermore, it is unknown whether the association between cigarette smoking and survival differs according to strata of ovarian cancer stage at diagnosis. In a large pooled analysis, we evaluated the association between various measures of cigarette smoking and survival among women with epithelial ovarian cancer. We obtained data from 19 case-control studies in the Ovarian Cancer Association Consortium (OCAC), including 9,114 women diagnosed with ovarian cancer. Cox regression models were used to estimate adjusted study-specific hazard ratios (HRs), which were combined into pooled hazard ratios (pHR) with corresponding 95% confidence intervals (CIs) under random effects models. Overall, 5,149 (57%) women died during a median follow-up period of 7.0 years. Among women diagnosed with ovarian cancer, both current (pHR = 1.17, 95% CI: 1.08-1.28) and former smokers (pHR = 1.10, 95% CI: 1.02-1.18) had worse survival compared with never smoking women. In histotype-stratified analyses, associations were observed for mucinous (current smoking: pHR = 1.91, 95% CI: 1.01-3.65) and serous histotypes (current smoking: pHR = 1.11, 95% CI: 1.00-1.23; former smoking: pHR = 1.12, 95% CI: 1.04-1.20). Further, our results suggested that current smoking has a greater impact on survival among women with localized than disseminated disease. The identification of cigarette smoking as a modifiable factor associated with survival has potential clinical importance as a focus area to improve ovarian cancer prognosis.

Purpose

Socioeconomic status (SES) is a known predictor of survival for several cancers and it has been suggested that SES differences affecting tumour stage at diagnosis may be the most important explanatory factor for this. However, only a limited number of studies have investigated SES differences in tumour stage at diagnosis of ovarian cancer. In a pooled analysis, we investigated whether SES as represented by level of education is predictive for advanced tumour stage at diagnosis of ovarian cancer, overall and by histotype. The effect of cigarette smoking and body mass index (BMI) on the association was also evaluated.

Methods

From 18 case-control studies, we obtained information on 10,601 women diagnosed with epithelial ovarian cancer. Study specific odds ratios (ORs) with corresponding 95% confidence intervals (CI) were obtained from logistic regression models and combined into a pooled odds ratio (pOR) using a random effects model.

Results

Overall, women who completed ≤high school had an increased risk of advanced tumour stage at diagnosis compared with women who completed >high school (pOR 1.15; 95% CI 1.03-1.28). The risk estimates for the different histotypes of ovarian cancer resembled that observed for ovarian cancers combined but did not reach statistical significance. Our results were unchanged when we included BMI and cigarette smoking.

Conclusion

Lower level of education was associated with an increased risk of advanced tumour stage at diagnosis of ovarian cancer. The observed socioeconomic difference in stage at diagnosis of ovarian cancer calls for further studies on how to reduce this diagnostic delay.