文章摘要
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].中华流行病学杂志,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
收稿日期:2011-11-30  出版日期:2014-09-09
DOI:
中文关键词: 过氧化物酶体增殖物激活受体  多态性  体重指数  交互作用
英文关键词: Peroxisome proliferator-activated receptors  Polymorphism  Body mass index  Interaction
基金项目:卫生部科学研究基金项目(WKJ2004-2-014)
作者单位E-mail
骆文书 苏州大学医学部放射医学与公共卫生学院流行病与卫生统计教研室, 215123
江苏省常州市疾病预防控制中心 
 
郭志荣 苏州大学医学部放射医学与公共卫生学院流行病与卫生统计教研室, 215123 guozhiroog28@163.com 
武鸣 江苏省疾病预防控制中心慢病科 jswuming@vip.sina.com 
陈秋 苏州大学医学部放射生物学教研室  
周正元 江苏省常熟市疾病预防控制中心慢病科  
俞浩 江苏省疾病预防控制中心慢病科  
张丽君 苏州市金阊区卫生监督所  
刘景超 苏州大学医学部放射医学与公共卫生学院流行病与卫生统计教研室, 215123  
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中文摘要:
      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.
英文摘要:
      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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