Edwards, Digna R. Velez

Background Admixture mapping can be leveraged to identify genomic loci associated with disease traits in admixed individuals such as Hispanic Americans. Methods and Results We characterized fine‐scale population structure of participants (n=105 108) in the multiethnic eMERGE‐III (electronic Medical Records and Genomics) cohort, using reference panels from the 1000 Genomes Project and a Native American cohort. We defined “genetically admixed Hispanic Americans” as those having ≥10% Native American genetic ancestry (n=5025), in addition to European (specifically, Iberian) and African genetic ancestry. This population descriptor was subsequently applied to 3 other cohorts: the MESA (Multi‐Ethnic Study of Atherosclerosis; n=1176), WHI (Women’s Health Initiative; n=2873), and the HCHS/SOL (Hispanic Community Health Study/Study of Latinos; n=7804). We inferred local ancestry along the genome in genetically admixed Hispanic Americans in each cohort using RFMix2 with phased haplotypes from SHAPEIT2. Local ancestry proportions were used for admixture mapping of lipid traits (low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, total cholesterol, and triglycerides) using extended linear mixed models that incorporated multiple or single ancestries. After accounting for fixed‐effect covariates and random effects, ancestry proportions at the following loci were associated with lipid traits in the HCHS/SOL cohort: 11q12.2 ( P =6.8×10 −7 ) with low‐density lipoprotein cholesterol, 2p23.3 ( P =5.2×10 −7 ) with total cholesterol, and 11q23.3 ( P =7.3×10 −12 ) with triglycerides. The LDL cholesterol and triglyceride loci replicated in at least one independent cohort, whereas the total cholesterol locus showed suggestive evidence for replication in the eMERGE cohort ( P =0.073). Native American (NAMR) ancestry appeared to drive the LDL‐C association, whereas both NAMR and Iberian population in Spain (IBS) ancestries contributed to the triglyceride signal. Conclusions Admixture mapping in genetically admixed Hispanic Americans identified genomic loci influencing lipid traits and the different ancestral origins driving these associations.

AbstractBackgroundKnown risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.MethodsSingle nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer–related cell types.ResultsWe identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.ConclusionsCNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

Abstract Background: Many loci have been found to be associated with risk of epithelial ovarian cancer (EOC). However, although there is considerable variation in progression-free survival (PFS), no loci have been found to be associated with outcome at genome-wide levels of significance. Methods: We carried out a genome-wide association study (GWAS) of PFS in 2,352 women with EOC who had undergone cytoreductive surgery and standard carboplatin/paclitaxel chemotherapy. Results: We found seven SNPs at 12q24.33 associated with PFS (P < 5 × 10–8), the top SNP being rs10794418 (HR = 1.24; 95% CI, 1.15–1.34; P = 1.47 × 10–8). High expression of a nearby gene, ULK1, is associated with shorter PFS in EOC, and with poor prognosis in other cancers. SNP rs10794418 is also associated with expression of ULK1 in ovarian tumors, with the allele associated with shorter PFS being associated with higher expression, and chromatin interactions were detected between the ULK1 promoter and associated SNPs in serous and endometrioid EOC cell lines. ULK1 knockout ovarian cancer cell lines showed significantly increased sensitivity to carboplatin in vitro. Conclusions: The locus at 12q24.33 represents one of the first genome-wide significant loci for survival for any cancer. ULK1 is a plausible candidate for the target of this association. Impact: This finding provides insight into genetic markers associated with EOC outcome and potential treatment options. See related commentary by Peres and Monteiro, p. 1604

Abstract Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

AbstractAn association between genetic variants in the vitamin D receptor (VDR) gene and epithelial ovarian cancer (EOC) was previously reported in women of African ancestry (AA). We sought to examine associations between genetic variants in VDR and additional genes from vitamin D biosynthesis and pathway targets (EGFR, UGT1A, UGT2A1/2, UGT2B, CYP3A4/5, CYP2R1, CYP27B1, CYP24A1, CYP11A1, and GC). Genotyping was performed using the custom‐designed 533,631 SNP Illumina OncoArray with imputation to the 1,000 Genomes Phase 3 v5 reference set in 755 EOC cases, including 537 high‐grade serous (HGSOC), and 1,235 controls. All subjects are of African ancestry (AA). Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI). We further evaluated statistical significance of selected SNPs using the Bayesian False Discovery Probability (BFDP). A significant association with EOC was identified in the UGT2A1/2 region for the SNP rs10017134 (per allele OR = 1.4, 95% CI = 1.2‐1.7, P = 1.2 × 10−6, BFDP = 0.02); and an association with HGSOC was identified in the EGFR region for the SNP rs114972508 (per allele OR = 2.3, 95% CI = 1.6‐3.4, P = 1.6 × 10−5, BFDP = 0.29) and in the UGT2A1/2 region again for rs1017134 (per allele OR = 1.4, 95% CI = 1.2‐1.7, P = 2.3 × 10−5, BFDP = 0.23). Genetic variants in the EGFR and UGT2A1/2 may increase susceptibility of EOC in AA women. Future studies to validate these findings are warranted. Alterations in EGFR and UGT2A1/2 could perturb enzyme efficacy, proliferation in ovaries, impact and mark susceptibility to EOC.

Abstract 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 × 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.

Abstract 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 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 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 × 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. Cancer Res; 78(18); 5419–30. ©2018 AACR.

Abstract Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932