Luo Wen-Shu, Guo Zhi-Rong, Wu Ming, Chen Qiu, Zhou Zheng-Yuan, Yu Hao, Zhang Li-Jun, Liu Jing-Chao
Department of Radiology & Public Health, Soochow University, Suzhou 215123, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2012 Jul;33(7):740-5.
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.
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. Ten 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).
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 < 0.01). The frequency of the mutant alleles of rs10865710 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 rs10865170 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 rs10865170 in all the two-dimensional models (P = 0.0010), in which predictive accuracy was 0.5746 and cross-validation consistency was 9/10.
Our data showed that rs2016520 was associated with lower obesity risk, as well as interactions among rs2016520, rs9794 and rs10865170 on incident obesity.
研究过氧化物酶体增殖物激活受体(α、δ、γ)中的十个单核苷酸多态性(SNP)与肥胖的关联以及这10个SNP之间基因-基因相互作用的额外作用。
在中国江苏省城市社区的PMMJS(江苏省多重代谢紊乱和代谢综合征预防)队列人群调查框架内招募参与者。随机选择820名受试者(513名非肥胖受试者,307名肥胖受试者),且个体之间无亲属关系。从HapMap数据库中选择了十个SNP(rs135539、rs4253778、rs1800206、rs2016520、rs9794、rs10865710、rs1805192、rs709158、rs3856806、rs4684847),这些SNP涵盖了PPARα、PPARδ和PPARγ。采用逻辑回归模型检验PPARs中的十个SNP与肥胖之间的关联。计算比值比(OR)和95%置信区间(95%CI)。通过广义多因素降维法(GMDR)探索相互作用。
纳入了一组820名参与者(平均年龄为50.05±9.41)。肥胖人群中rs2016520突变等位基因的频率低于非肥胖人群(26%对33%,P<0.01)。肥胖人群中rs10865710突变等位基因的频率高于非肥胖人群(37%对31%,P = 0.01)。对于rs2016520,C等位基因携带者的肥胖发生率显著低于TT纯合子[OR(95%CI)= 0.63(0.47 - 0.84)],但未观察到其他SNP与新发肥胖之间存在显著关联。GMDR分析显示,在三维模型中rs2016520、rs9794和rs10865170之间存在显著的基因-基因相互作用(P = 0.0010),其中预测准确率为0.5834,交叉验证一致性为9/10。在所有二维模型中也显示rs2016520和rs10865170之间存在显著的基因-基因相互作用(P = 0.0010),其中预测准确率为0.5746,交叉验证一致性为9/10。
我们的数据表明,rs2016520与较低的肥胖风险相关,以及rs2016520、rs9794和rs10865170之间对新发肥胖存在相互作用。