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XRCC1基因rs1799782多态性与甲状腺癌发病风险相关性的meta分析

Association between XRCC1 rs1799782 polymorphism and thyroid cancer risk:a meta-analysis
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摘要 目的探索X射线交叉互补修复基因-1(X-ray cross complementary repair gene-1,XRCC1)rs1799782位点多态性与甲状腺癌发病风险的相关性。方法检索PubMed、Embase、Web of Science、知网(CNKI)、万方(Wangfang)和中国生物医学文献数据库(CBM),搜索国内外公开发表的有关XRCC1基因rs1799782位点多态性与甲状腺癌发病风险的文献,检索文献的发表日期截止于2021-02-15。根据纳入和排除标准,筛选出符合要求的相关性研究,使用Stata 14.0软件进行meta分析,采用比值比(OR)及95%可信区间(95%CI)作为效应量来评价rs1799782位点多态性与甲状腺癌发病风险的相关性。结果共有12篇文献纳入分析。rs1799782位点多态性与甲状腺癌的发病风险在总人群中没有显示出明显的相关性,其显性模型:CT+TT比CC,OR=1.07,95%CI为(0.84,1.36)。隐性模型:TT比CT+CC,OR=1.48,95%CI为(0.95,2.31);等位基因模型:T比C,OR=1.15,95%CI为(0.93,1.43)。共显性基因模型:TT比CC,OR=1.44,95%CI为(0.83,2.53);CT比CC,OR=1.02,95%CI为(0.82,1.28);TT比CT,OR=1.40,95%CI为(0.98,1.99)。rs1799782位点多态性与甲状腺癌的发病风险在中国人群中显示出明显相关性,其显性模型:CT+TT比CC,OR=1.38,95%CI为(1.11,1.71)。隐性模型:TT比CT+CC,OR=1.97,95%CI为(1.55,2.50);等位基因模型:T比C,OR=1.40,95%CI为(1.16,1.68)。共显性基因模型:TT比CC,OR=2.12,95%CI为(1.66,2.71);CT比CC,OR=1.26,95%CI为(1.09,1.47);TT比CT,OR=1.70,95%CI为(1.31,2.21)。rs1799782位点多态性与甲状腺癌的发病风险在中国人群以外的亚洲人群中显示出明显相关性,其显性模型:CT+TT比CC,OR=0.64,95%CI为(0.49,0.83)。共显性模型:TT比CC,OR=0.50,95%CI为(0.33,0.74);CT比CC,OR=0.65,95%CI为(0.49,0.86)。结论XRCC1基因rs1799782位点多态性与总人群罹患甲状腺癌的风险无明显相关性;rs1799782位点基因多态性可能增加中国人群罹患甲状腺癌的风险;rs1799782位点基因多态性可能降低中国人以外的亚洲人群罹患甲状腺癌的风险;rs1799782位点基因多态性与高加索人的甲状腺癌发病风险无关。 Objective To explore the association between single nucleotide polymorphism(SNP)in the X-ray cross complementary repair gene-1(XRCC1)rs1799782 locus and thyroid cancer.Methods Studies investigating the association between SNP in the XRCC1 gene and thyroid cancer susceptibility were retrieved from the PubMed,Embase,Web of Science,CNKI(Chinese National Knowledge Infrastructure),Wanfang,and CBM(China Biology Medicine)databases(published date up to February 15,2021).Eligible studies were screened according to inclusion/exclusion criteria and principles of quality evaluation.Meta-analysis was performed using Stata 14.0 software.Odds ratios with their corresponding 95%confidence intervals(95%CI)were pooled to assess the association between SNP in the XRCC1 gene rs1799782 locus and thyroid cancer susceptibility.Results Twelve articles were eligible for this meta-analysis.Meta-analysis results were shown as follows:No significant association was found between XRCC1 rs1799782 polymorphism and thyroid cancer in overall population[Dominant model:CT+TT vs CC,OR=1.07,95%CI(0.84,1.36).Recessive model:TT vs CT+CC,OR=1.48,95%CI(0.95,2.31).Allelic model:T vs C,OR=1.15,95%CI(0.93,1.43).Codominant model:TT vs CC:OR=1.44,95%CI(0.83,2.53);CT vs CC,OR=1.02,95%CI(0.82,1.28);TT vs CT,OR=1.40,95%CI(0.98,1.99)].rs1799782 polymorphism was significantly associated with the risk of thyroid cancer in Chinese population[Dominant model:CT+TT vs CC,OR=1.38,95%CI(1.11,1.71).Recessive model:TT vs CT+CC,OR=1.97,95%CI(1.55,2.50);Allelic model:T vs C,OR=1.40,95%CI(1.16,1.68).Codominant model:TT vs CC,OR=2.12,95%CI(1.66,2.71);CT vs CC,OR=1.26,95%CI(1.09,1.47);TT vs CT,OR=1.70,95%CI(1.31,2.21)].rs1799782 polymorphism was significantly associated with the risk of thyroid cancer in Asian population[Dominant model:CT+TT vs CC,OR=0.64,95%CI(0.49,0.83).Codominant model:TT vs CC:OR=0.50,95%CI(0.33,0.74);CT vs CC,OR=0.65,95%CI(0.49,0.86)].Conclusions There is no significant correlation between XRCC1 rs1799782 polymorphism and the risk of thyroid cancer in general population.The XRCC1 rs1799782 polymorphism may be associated with an increased thyroid cancer risk among Chinese,and a tendency for decreased thyroid cancer risk among Asians(Chinese excluded).The XRCC1 rs1799782 polymorphism is not associated with thyroid cancer susceptibility among Caucasians under all genetic models.
作者 武亚运 曹治敏 章凯 刘汝彬 张强 韩飞 WU Yayun;CAO Zhimin;ZHANG Kai;LIU Rubin;ZHANG Qiang;HAN Fei(Department of Head and Neck Surgery,Fuyang Cancer Hospital,Fuyang,Anhui 236000,P.R.China)
出处 《中国普外基础与临床杂志》 CAS 2021年第11期1477-1485,共9页 Chinese Journal of Bases and Clinics In General Surgery
关键词 甲状腺癌 X射线交叉互补修复基因-1 rs1799782位点 多态性 META分析 thyroid cancer X-ray cross complementary repair gene-1 rs1799782 locus polymorphism meta-analysis
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