Vaidyanathan Venkatesh, Naidu Vijay, Karunasinghe Nishi, Jabed Anower, Pallati Radha, Marlow Gareth, R Ferguson Lynnette
Discipline of Nutrition and Dietetics, FM & HS, University of Auckland, Auckland, New Zealand.
Auckland Cancer Society Research Centre, Auckland, New Zealand.
F1000Res. 2017 May 3;6:621. doi: 10.12688/f1000research.11027.1. eCollection 2017.
Prostate cancer (PCa) is one of the most significant male health concerns worldwide. Single nucleotide polymorphisms (SNPs) are becoming increasingly strong candidate biomarkers for identifying susceptibility to PCa. We identified a number of SNPs reported in genome-wide association analyses (GWAS) as risk factors for aggressive PCa in various European populations, and then defined SNP-SNP interactions, using PLINK software, with nucleic acid samples from a New Zealand cohort. We used this approach to find a gene x environment marker for aggressive PCa, as although statistically gene x environment interactions can be adjusted for, it is highly impossible in practicality, and thus must be incorporated in the search for a reliable biomarker for PCa. We found two intronic SNPs statistically significantly interacting with each other as a risk for aggressive prostate cancer on being compared to healthy controls in a New Zealand population.
前列腺癌(PCa)是全球男性健康领域最受关注的问题之一。单核苷酸多态性(SNP)正日益成为识别前列腺癌易感性的强有力候选生物标志物。我们在全基因组关联分析(GWAS)中鉴定出一些在不同欧洲人群中被报告为侵袭性前列腺癌风险因素的SNP,然后使用PLINK软件,对来自新西兰队列的核酸样本定义SNP-SNP相互作用。我们采用这种方法来寻找侵袭性前列腺癌的基因×环境标志物,因为尽管在统计学上基因×环境相互作用可以进行调整,但在实际中这是极不可能的,因此必须将其纳入寻找可靠的前列腺癌生物标志物的研究中。我们发现,在新西兰人群中,与健康对照相比,有两个内含子SNP在统计学上相互之间存在显著的相互作用,作为侵袭性前列腺癌的一个风险因素。