Zhu Jie, Qi Ping, Li Zhenjie
Cell Physiol Biochem. 2018;49(2):638-644. doi: 10.1159/000493027. Epub 2018 Aug 30.
BACKGROUND/AIMS: To investigate the association of several single nucleotide polymorphisms (SNPs) within XRCC gene and additional gene- environment interaction with papillary thyroid cancer (PTC) risk.
Testing for Hardy-Weinberg equilibrium in controls was conducted using SNPstats (online software: http://bioinfo.iconcologia.net/SNPstats). Generalized multifactor dimensionality reduction (GMDR) was used to screen the best interaction combination among 5 SNPs within XRCC gene and obesity.
Logistic regression analysis showed that the C allele of rs861539 and T allele of rs1799782 were associated with increased PTC risk Adjusted ORs (95%CI) were 1.65 (1.23-2.12) and 1.61 (1.20-2.04). However There was no relation of rs25489 Rs25487 and rs13181 with PTC. The cross-validation consistency and the testing accuracy for each of the models were determined by GMDR analysis. One two-locus model (rs1799782 and obesity) had a testing accuracy of 62.11% Which was significant at the p < 0.01 level. The D' value between rs1799782 and rs13181 within ERCC1 gene was more than 0.75 (0.825). So haplotype analysis was just conducted for rs1799782 and rs13181 using the SHEsis online haplotype analysis software. In all samples The haplotype C- A was observed most frequently in two groups With 49.46% and 55.79% in the PTC patients and controls Respectively. The results also indicated that haplotype T- C was significantly associated with increased PTC risk.
The C allele of rs861539 and T allele of rs1799782 Interaction between rs1799782 and obesity and haplotype T- C were all associated with increased PTC risk.
背景/目的:研究XRCC基因内几个单核苷酸多态性(SNP)以及其他基因-环境相互作用与甲状腺乳头状癌(PTC)风险的关联。
使用SNPstats(在线软件:http://bioinfo.iconcologia.net/SNPstats)对对照组进行哈迪-温伯格平衡检验。采用广义多因素降维法(GMDR)筛选XRCC基因内5个SNP与肥胖之间的最佳相互作用组合。
逻辑回归分析显示,rs861539的C等位基因和rs1799782的T等位基因与PTC风险增加相关,调整后的比值比(95%可信区间)分别为1.65(1.23 - 2.12)和1.61(1.20 - 2.04)。然而,rs25489、rs25487和rs13181与PTC无关。通过GMDR分析确定每个模型的交叉验证一致性和检验准确性。一个双位点模型(rs1799782与肥胖)的检验准确性为62.11%,在p < 0.01水平具有显著性。ERCC1基因内rs1799782与rs13181之间的D'值大于0.75(0.825)。因此,仅使用SHEsis在线单倍型分析软件对rs1799782和rs13181进行单倍型分析。在所有样本中,单倍型C - A在两组中出现频率最高,PTC患者和对照组分别为49.46%和55.79%。结果还表明,单倍型T - C与PTC风险增加显著相关。
rs861539的C等位基因、rs1799782的T等位基因、rs1799782与肥胖之间的相互作用以及单倍型T - C均与PTC风险增加相关。