| 周慧,丁一,武鸣,范伟,俞浩,周正元,顾淑君,张丽君,董晨,郭志荣.过氧化物酶体增殖物激活受体多态性及基因-基因交互作用对脉压的影响[J].中华流行病学杂志,2017,38(10):1404-1409 |
| 过氧化物酶体增殖物激活受体多态性及基因-基因交互作用对脉压的影响 |
| Association and effects of gene-gene interactions between peroxisome proliferator-activated receptor and pulse pressure |
| 收稿日期:2017-02-06 出版日期:2017-10-23 |
| DOI：10.3760/cma.j.issn.0254-6450.2017.10.022 |
| 中文关键词: 脉压差 过氧化物酶体增殖物激活受体 广义多因子降维法 交互作用 |
| 英文关键词: Pulse pressure Peroxisome proliferator-activated receptors Generalized multifactor dimensionality reduction Interaction |
| 基金项目:国家自然科学基金（81502869）；苏州市"科教兴卫"青年科技项目（KJXW2014060，KJXW2015063） |
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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（PPAR）单核苷酸多态性（SNP）以及基因-基因交互作用对脉压差的影响。方法 基于江苏省代谢综合征和多代谢异常综合防治研究（PMMJS）队列，采用单纯随机抽样方法随机抽取其中研究对象820例，选取3个PPARα、2个PPARδ和5个PPARγ的SNP位点并进行检测，运用广义多因子降维法（GMDR）模型检测10个SNP的基因-基因交互作用与高血压的关联。结果 PPARγ的rs1805192的突变基因型（PA+AA）携带者与野生型（PP）相比，脉压差水平显著变化（1.341 mmHg，95% CI：0.431~2.252 mmHg）。GMDR模型分析显示，在脉压差≥ 30 mmHg的亚组中，PPARα基因的rs135539、PPARδ的rs2016520、PPARγ的rs10865710、rs1805192、rs709158、rs3856806组成的六阶模型平均检验准确度为0.577，交叉验证一致性为10/10，为最优模型。而在脉压差≤ 40 mmHg的亚组中，二阶交互作用模型与脉压差显著相关，平均检验准确度为0.628，交叉验证一致性为10/10。结论 PPARγ的rs1805192多态性与脉压差水平有关联，PPARα基因的rs135539、PPARδ的rs2016520和PPARγ的rs10865710、rs1805192、rs709158、rs3856806六个SNP间基因-基因交互作用与脉压差间具有显著性关联。 |
| 英文摘要: |
| Objective To investigate the association between ten single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptors and pulse pressure (PP) as well as the relationships between gene-gene interaction between PPARα/δ/γ genes and PP. Methods A total of 820 subjects, with 550 females and 270 males, were recruited from a cohort study of "Prevention of Metabolic Syndrome and Multi-metabolic Disorders in Jiangsu Province of China Study (PMMJS)". Ten SNPs of PPARα/δ/γ genes were selected. GMDR software (version 1.0.1) was used to evaluate the gene-gene interactions among PPARs SNPs associated with PP. Results The mean levels of PP in people with mutant genotype of rs1805192 in PPARγ genes (PA+AA) showed a significant increase by 1.341 mmHg (95% CI:0.431-2.252 mmHg) when compared to the persons with wild genotype (PP). In the subgroup of subjects with more than 30 mmHg levels of PP, a six-locus model comprised rs135539 of PPARα, rs2016520 of PPARδ, rs10865710, rs1805192, rs709158 and rs3856806 of PPARγ showed a highest level of prediction accuracy (0.577) and displayed a better cross-validation consistency (10/10). In the subgroup of subjects with less than 40 mmHg levels of PP, a two-locus model was statistically associated with PP with 0.628 of prediction accuracy and 10/10 of cross-validation consistency. Conclusion PPARγ rs1805192 was associated with the occurrence of PP. Gene-gene interactions among rs135539 of PPARα, rs2016520 of PPARδ, rs10865710, rs1805192, rs709158 and rs3856806 of PPARγ were all significantly related to PP. |
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