Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We meta-analyzed >22 million variants for 398,238 women from the Ovarian Cancer Association Consortium (OCAC), UK Biobank (UKBB) and Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA) to identify novel HGSOC susceptibility loci. Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was TP53 3'-UTR SNP rs78378222-T's association with HGSOC (per-T-allele relative risk (RR)=1.44, 95% CI:1.28-1.62, P=1.76*10-9). Polygenic scores (PGS) were developed using OCAC and CIMBA data and trained on FinnGen data. The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95% CI:1.37-1.54) per standard deviation when validated in the UKBB. This study represents the largest HGSOC GWAS to date - demonstrating that improvements in imputation reference panels and increased sample sizes help to identify HGSOC associated variants that previously went undetected, ultimately improving PGS which can improve personalized HGSOC risk prediction. © 2025. The Author(s).

Objective:While cardiometabolic abnormalities are associated with elevated risk of morbidity, they may not occur in all individuals with obesity. Less is known about associations with mortality, especially cancer mortality. This study examined associations between cardiometabolic-weight categories and mortality from cardiovascular disease (CVD), cancer, and all causes. Methods:Cox proportional hazards regressions of time to all-cause, CVD, and cancer mortalities were used to examine associations with cardiometabolic-weight status, in the Multiethnic Cohort (n=157,865). Cardiometabolic-weight status categories were: Metabolically Healthy Normal Weight, Metabolically Healthy Obese, Metabolically Healthy Overweight, Metabolically Unhealthy Normal Weight, Metabolically Unhealthy Obese, and Metabolically Unhealthy Overweight. Results:Higher mortality, especially for all-cause and CVD, was found for all metabolically unhealthy groups no matter the weight classification when compared to the Metabolically Healthy Normal Weight category across sex-ethnic groups. For all-cause mortality, a reduction in mortality was seen for males in the Metabolically Healthy Overweight category (HR: 0.88, 95% CI: 0.84, 0.93), especially for African American, Native Hawaiian, and Latino males. Mortality was elevated in the Metabolically Healthy Obese category for all-cause and CVD mortality in both sexes (HRrange: 1.08-1.93). Few associations were seen with cancer mortality. Conclusions:Past examinations of cardiometabolic-weight status and mortality have been hampered by a lack of diversity. In a racially/ethnically diverse population, metabolically unhealthy groups exhibited a substantially higher risk of death from all causes and CVD than metabolically healthy groups. A reduction in all-cause mortality was seen for some males classified as Metabolically Healthy Overweight; however, being classified as Metabolically Healthy Obese elevated mortality risk for males and females compared to Metabolically Healthy Normal Weight. Future research is needed to examine how sex-ethnic differences in body fat distribution and changes in weight over time influence associations between cardiometabolic-weight status and mortality.

Background: More than 180 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified; these SNPs can be combined into polygenic risk scores (PRS) to predict breast cancer risk. Because most SNPs were identified in predominantly European populations, little is known about the performance of PRS in non-Europeans. We tested the performance of a 180-SNP PRS in Latinas, a large ethnic group with variable levels of Indigenous American, European, and African ancestry.Methods: We conducted a pooled case-control analysis of US Latinas and Latin American women (4658 cases and 7622 controls). We constructed a 180-SNP PRS consisting of SNPs associated with breast cancer risk (P < 5 x 10(-8)). We evaluated the association between the PRS and breast cancer risk using multivariable logistic regression, and assessed discrimination using an area under the receiver operating characteristic curve. We also assessed PRS performance across quartiles of Indigenous American genetic ancestry. All statistical tests were two-sided.Results: Of 180 SNPs tested, 142 showed directionally consistent associations compared with European populations, and 39 were nominally statistically significant (P < .05). The PRS was associated with breast cancer risk, with an odds ratio per SD increment of 1.58 (95% confidence interval [CI = 1.52 to 1.64) and an area under the receiver operating characteristic curve of 0.63 (95% CI = 0.62 to 0.64). The discrimination of the PRS was similar between the top and bottom quartiles of Indigenous American ancestry.Conclusions: The 180-SNP PRS predicts breast cancer risk in Latinas, with similar performance as reported for Europeans. The performance of the PRS did not vary substantially according to Indigenous American ancestry.

Women of African ancestry have lower incidence of epithelial ovarian cancer (EOC) yet worse survival compared to women of European ancestry. We conducted a genome-wide association study in African ancestry women with 755 EOC cases, including 537 high-grade serous ovarian carcinomas (HGSOC) and 1,235 controls. We identified four novel loci with suggestive evidence of association with EOC (p < 1 x 10(-6)), including rs4525119 (intronic to AKR1C3), rs7643459 (intronic to LOC101927394), rs4286604 (12 kb 3 ' of UGT2A2) and rs142091544 (5 kb 5 ' of WWC1). For HGSOC, we identified six loci with suggestive evidence of association including rs37792 (132 kb 5 ' of follistatin [FST]), rs57403204 (81 kb 3 ' of MAGEC1), rs79079890 (LOC105376360 intronic), rs66459581 (5 kb 5 ' of PRPSAP1), rs116046250 (GABRG3 intronic) and rs192876988 (32 kb 3 ' of GK2). Among the identified variants, two are near genes known to regulate hormones and diseases of the ovary (AKR1C3 and FST), and two are linked to cancer (AKR1C3 and MAGEC1). In follow-up studies of the 10 identified variants, the GK2 region SNP, rs192876988, showed an inverse association with EOC in European ancestry women (p = 0.002), increased risk of ER positive breast cancer in African ancestry women (p = 0.027) and decreased expression of GK2 in HGSOC tissue from African ancestry women (p = 0.004). A European ancestry-derived polygenic risk score showed positive associations with EOC and HGSOC in women of African ancestry suggesting shared genetic architecture. Our investigation presents evidence of variants for EOC shared among European and African ancestry women and identifies novel EOC risk loci in women of African ancestry.

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.

BackgroundBreast cancer is a partially heritable trait and genome-wide association studies (GWAS) have identified over 180 common genetic variants associated with breast cancer. We have previously performed breast cancer GWAS in Latinas and identified a strongly protective single nucleotide polymorphism (SNP) at 6q25, with the protective minor allele originating from indigenous American ancestry. Here we report on fine mapping of the 6q25 locus in an expanded sample of Latinas.MethodsWe performed GWAS in 2385 cases and 6416 controls who were either US Latinas or Mexican women. We replicated the top SNPsin 2412 cases and 1620 controls of US Latina, Mexican, and Colombian women. In addition, we validated the top novel variants in studies of African, Asian and European ancestry. In each dataset we used logistic regression models to test the association between SNPs and breast cancer risk and corrected for genetic ancestry using either principal components or genetic ancestry inferred from ancestry informative markers using a model-based approach.ResultsWe identified a novel set of SNPs at the 6q25 locus associated with genome-wide levels of significance (p=3.3x10(-8) - 6.0x10(-9)) not in linkage disequilibrium (LD) with variants previously reported at this locus. These SNPs were in high LD (r(2)>0.9) with each other, with the top SNP, rs3778609, associated with breast cancer with an odds ratio (OR) and 95% confidence interval (95% CI) of 0.76 (0.70-0.84). In a replication in women of Latin American origin, we also observed a consistent effect (OR 0.88; 95% CI 0.78-0.99; p=0.037). We also performed a meta-analysis of these SNPs in East Asians, African ancestry and European ancestry populations and also observed a consistent effect (rs3778609, OR 0.95; 95% CI 0.91-0.97; p=0.0017).ConclusionOur study adds to evidence about the importance of the 6q25 locus for breast cancer susceptibility. Our finding also highlights the utility of performing additional searches for genetic variants for breast cancer in non-European populations.

DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 x 10(-7). Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression.Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 x 10(-6), we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 x 10(-7), the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 x 10(-3)). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. (C) 2018 AACR.