| 骆文书,郭志荣,武鸣,陈秋,周正元,俞浩,张丽君,刘景超.过氧化物酶体增殖物激活受体单核苷酸多态性以及基因-基因交互作用与体重异常的关系[J].Chinese journal of Epidemiology,2012,33(7):740-745 |
| 过氧化物酶体增殖物激活受体单核苷酸多态性以及基因-基因交互作用与体重异常的关系 |
| Association of both peroxisome proliferator-activated receptor, gene-gene interactions and the body mass index |
| Received:November 30, 2011 |
| DOI： |
| KeyWord: 过氧化物酶体增殖物激活受体 多态性 体重指数 交互作用 |
| English Key Word: Peroxisome proliferator-activated receptors Polymorphism Body mass index Interaction |
| FundProject:卫生部科学研究基金项目(WKJ2004-2-014) |
| Author Name | Affiliation | E-mail | | LUO Wen-shu | Department of Radiology & Public Health, Soochow University, Suzhou 215123, China
Changzhou Center for Disease Control and Prevention | | | GUO Zhi-rong | Department of Radiology & Public Health, Soochow University, Suzhou 215123, China | guozhiroog28@163.com | | WU Ming | Jiangsu Provincial Center for Disease Control and Prevention | jswuming@vip.sina.com | | CHEN Qiu | Department of Radiation Biology, Soochow University | | | ZHOU Zheng-yuan | Changshu Center for Disease Control and Prevention | | | YU Hao | Jiangsu Provincial Center for Disease Control and Prevention | | | ZHANG Li-jun | Jinchang District Institute of Health Inspection and Supervision | | | LIU Jing-chao | Department of Radiology & Public Health, Soochow University, Suzhou 215123, China | |
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| Abstract: |
| 目的 探讨过氧化物酶体增殖物激活受体(PPARs) 10个位点单核苷酸多态性(SNP)以及多个SNP间交互作用与体重异常的关联.方法 研究对象均来自于“江苏省多代谢异常和代谢综合征综合防治研究( PMMJS)”队列人群.采用单纯随机抽样方法抽取其中的820名研究对象的基线血标本进行PPARs的10个SNP(rs 135539、rs4253778、rs1800206、rs2016520、rs9794、rs10865710、rs1805192、rs709158、rs3856806、rs4684847)多态性分析,以随访时所测得的体重指数(BMI)确定体重异常.运用logistic回归模型计算10个SNP对体重异常发生的OR值和95％CI.采用GMDR模型检测10个SNP的基因-基因交互作用.结果 820名研究对象平均年龄(50.05±9.41)岁,体重正常者513人,体重异常者307人.体重异常组rs2016520的C等位基因频率显著低于体重正常组(26％ vs.33％,P＜0.01),而体重异常组rsl0865710的G等位基因频率显著高于体重正常组(37％掷.31％,P=0.01).多因素logistic回归分析显示,与野生型基因(TT)携带人群相比,rs2016520突变等位基因携带人群(TC+CC)发生体重异常的OR=0.63(95％CI:0.47 ～ 0.84),未发现其他SNP与体重异常的发生具有统计学相关性.GMDR模型结果显示,rs2016520和rs10865710的SNP间交互作用有统计学意义(P=0.0010),交叉验证一致性为9/10,平均检验准确度为0.5746.rs2016520、rs9794和rs10865710的SNP间交互作用有统计学意义(P=0.0010),交叉验证一致性为9/10,平均检验准确度为0.5834,其中三阶模型为最佳模型.结论 PPARδ的rs2016520基因多态性与较低BMI的关联具有统计学意义,rs2016520、rs9794和rs10865710三个SNP之间的交互作用对体重异常的发生风险存在显著影响. |
| English Abstract: |
| Objective To investigate the association of ten single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptor ( α,δ,γ) with obesity and the additional role of a gene-gene interaction among 10 SNPs.Methods Participants were recruited within the framework of the PMMJS (Prevention of Multiple Metabolic Disorders and Metabolic Syndrome in Jiangsu Province)-cohort-population-survey in the urban community of Jiangsu province,China.820 subjects (513 non obese subjects,307 obese subjects ) were randomly selected and no individuals were related to each other.Tea SNPs (rs135539,rs4253778,rs1800206,rs2016520,rs9794,rs10865710,rs1805192,rs709158,rs3856806,rs4684847) were selected from the HapMap database,which covered PPARα,PPARδ and PPARγ.Logistic regression model was used to examine the association between ten SNPs in the PPARs and obesity.Odds ratios (OR) and 95％ confident interval (95％CI) were calculated.Interactions were explored by using the Generalized Multifactor Dimensionality Reduction (GMDR).Results A group of 820 participants (mean age was 50.05 ± 9.41) was involved.The frequency of the mutant alleles of rs2016520 in obese populations was less than that in non-obese populations (26％ vs.33％,P＜ 0.0 1 ).The frequency of the mutant alleles of rs 10865710 in obese populations was more than that in non-obese populations (37％ vs.31％,P=0.01 ).C allele carriers had a significantly lower obesity occurrence than TT homozygotes [OR (95％ CI):0.63 (0.47-0.84) ] for rs2016520 but no significant association was observed between other SNP and incident obesity.GMDR analysis showed a significant gene-gene interaction among rs2016520,rs9794 and rs10865710 for the three-dimension models (P=0.0010),in which prediction accuracy was 0.5834 and cross-validation consistency was 9/10.It also showed a significant gene-gene interactions between rs2016520 and rs10865710 in all the two-dimensional models (P=0.0010),in which predictive accuracy was 0.5746 and cross-validation consistency was 9/10.Conclusion Our data showed that rs2016520 was associated with lower obesity risk,as well as interactions among rs2016520,rs9794 and rs 10865710 on incident obesity. |
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