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Abstract：
To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.
摘要：
为了确定与不同组织学类型的上皮性卵巢癌（EOC）相关的可信因果风险变异（CCV），我们对来自欧洲的25,981例EOC病例和105,724例对照中的470,825个基因型和10,163,797个估算SNP进行了全基因组关联分析.我们确定了5个组织型特异性EOC风险区域（p值<5×10-8），并确认了先前报道的27个风险区域的关联。条件分析在六个风险区域(p值<10-5)识别出独立于主要信号的另外11个信号。精细作图在这些地区确定了4,008个CCV，其中1,452个CCV位于卵巢癌相关的染色质标记中，活性增强剂显著富集，活性启动子,和来自每个EOC组织型的CCV的活性区域。使用组织特异性和跨组织数据集的组织型全转录组关联和共定位分析确定了已知EOC风险区域中的86个候选易感基因和23个其他基因组区域中的32个基因，这些基因可能代表新的EOC风险基因座（错误发现率<0.05）。最后,通过整合全基因组HiChIP相互作用组分析与全转录组关联研究（TWAS），变异效应预测因子，转录因子ChIP-seq,和motifbreakR数据，我们确定了每个基因座的候选基因-CCV相互作用。这包括风险基因座，其中TWAS鉴定了一个或多个候选易感基因(例如，在2q31的HOXD-AS2，HOXD8和HOXD3）和其他未鉴定出候选基因的基因座（例如，MYC和PVT1在8q24）通过TWAS。总之,这项研究描述了一个功能框架,并对通过全基因组关联研究确定的EOC易感位点的风险等位基因和候选基因靶标的生物学意义提供了更深入的理解.
