The role of methylation in pancreatic cancer (PC) risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpGs) with the genetically predicted methylation to be associated with PC risk. We also studied gene expression to understand the identified associations.
Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 PC cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with PC risk. For associated CpGs, we compared their measured levels in pancreatic tumor vs benign tissue.
We identified 45 CpGs at nine loci showing an association with PC risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with PC risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.
We identified methylation biomarker candidates associated with PC using genetic instruments and added additional insights into the role of methylation in regulating gene expression in PC development.
A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for PC risk.
甲基化在胰腺癌(PC)风险中的作用仍不明确。我们整合了基因组和甲基化组数据,以识别具有遗传预测甲基化且与胰腺癌风险相关的CpG位点(CpGs)。我们还研究了基因表达以了解所识别的关联。
利用来自1595名欧洲血统受试者的遗传数据和白细胞甲基化数据,我们构建了遗传模型来预测DNA甲基化水平。经过内部和外部验证后,我们将性能令人满意的预测模型应用于8280例胰腺癌病例和6728名欧洲血统对照的遗传数据,以研究预测的甲基化与胰腺癌风险的关联。对于相关的CpGs,我们比较了它们在胰腺肿瘤组织与良性组织中的测量水平。
我们在9个基因座上识别出45个CpGs与胰腺癌风险相关,其中包括15个CpGs显示出与已识别的风险变异无关的关联。我们观察到45个CpGs中的16个的预测甲基化与8个相邻基因的预测表达之间存在显著相关性,其中6个基因显示出与胰腺癌风险的关联。在这45个CpGs中,我们能够比较其中16个在胰腺肿瘤与良性胰腺组织中的测量甲基化水平。其中,6个显示出差异甲基化。
我们利用遗传工具识别了与胰腺癌相关的甲基化生物标志物候选物,并对甲基化在调节胰腺癌发展过程中基因表达的作用有了更多的了解。
一项利用遗传工具的综合研究确定了9个基因组位点上的45个CpG位点与胰腺癌风险相关。