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Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer

机译:全基因组关联研究数据的途径分析突出了胰腺发育基因作为胰腺癌的易感因素

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Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lactoeolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10?6, 1.6 × 10?5, 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10?5), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H.pylori lactoeolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer.
机译:通过全基因组关联研究(GWAS),四个基因位点与胰腺癌相关。基于路径的GWAS数据分析是一种补充方法,可用于鉴定富含疾病相关单核苷酸多态性(SNP)的基因或生物途径组,其个体效应大小可能太小而无法通过标准单基因座方法检测到。我们在12个队列研究和8个病例对照研究(PanScan)中收集的3851个胰腺癌病例和3934个对照参与者的GWAS数据的基于路径的分析中,使用了自适应秩截短乘积法。我们编辑了假设与胰腺癌相关的23条生物学途径,并观察到胰腺癌与五种途径之间的名义关联(P <0.05),即胰腺发育,幽门螺杆菌乳/神经,刺猬,Th1 / Th2免疫应答和凋亡(P分别为2.0×10?6、1.6×10?5、0.0019、0.019和0.023)。在通过三个途径(NR5A2,ABO和SHH)从原始GWAS中排除先前鉴定的基因后,胰腺发育途径仍然很重要(P = 8.3×10?5),而其他则没有。这五个途径中最重要的基因(P <0.01)是胰腺发育的NR5A2,HNF1A,HNF4G和PDX1。幽门螺杆菌/乳杆菌的ABO;刺猬SHH; TGFBR2和CCL18用于Th1 / Th2免疫应答,MAPK8和BCL2L11用于凋亡。我们的结果提供了对胰腺发育和癌症重要的基因的遗传变异之间的联系,并表明基于途径的GWAS数据分析方法可以对遗传风险变异在癌症中的集体作用产生重要的见解。

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