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基于汉族人群中 RAGE 基因多态性与代谢危险因素预测心肌梗死风险的列线图。

Predictive Nomogram of RAGE Genetic Polymorphisms and Metabolic Risk Factors for Myocardial Infarction Risk in a Han Chinese Population.

机构信息

1 Heart Center, Beijing Chao Yang Hospital, Capital Medical University, Beijing, China.

The first two authors (Weiming Li and Yingxue Li) contributed equally to this work.

出版信息

Angiology. 2017 Nov;68(10):877-883. doi: 10.1177/0003319717696622. Epub 2017 Mar 10.

Abstract

We investigated the association of 4 well-characterized polymorphisms in receptor for the advanced glycation end-product ( RAGE) gene with myocardial infarction (MI) risk and the changes in metabolic risk factors among 717/612 patients/controls, with the aim of constructing a predictive nomogram. The genotype/allele distributions differed significantly between the 2 groups for T-429C ( P = .004/.001) and G1704T ( P < .001/.001). T-429C was significantly associated with MI risk, especially under a recessive model (adjusted odds ratio: 2.24, 95% confidence interval: 1.33-3.79, P = .003). For G1704T, significance was detected under additive (1.37; 1.12-1.67; P = .002) and recessive (3.86; 2.27-6.57; P < .001) models. There were significant differences in blood pressure and low-density lipoprotein cholesterol (LDL-C) across T-429C genotypes and in total cholesterol and LDL-C across G1704T genotypes. The overall best multifactor dimensionality reduction model included dyslipidemia, G1704T, and T-429C. Further predictive nomogram on 2 significant polymorphisms, blood pressure and lipids, showed a better predictive capability (concordance index = 0.716, P < .001). Altogether, we identified 2 polymorphisms of RAGE, T-429C and G1704T, which interacted with metabolic risk factors associated with the occurrence of MI. We also constructed a genetic-metabolic nomogram that can better predict MI risk.

摘要

我们研究了受体晚期糖基化终产物(RAGE)基因中 4 种特征明确的多态性与心肌梗死(MI)风险的关联,以及在 717/612 例患者/对照中代谢危险因素的变化,旨在构建一个预测列线图。2 组间 T-429C(P=0.004/0.001)和 G1704T(P<0.001/0.001)的基因型/等位基因分布存在显著差异。T-429C 与 MI 风险显著相关,尤其是在隐性模型下(调整后比值比:2.24,95%置信区间:1.33-3.79,P=0.003)。对于 G1704T,在加性(1.37;1.12-1.67;P=0.002)和隐性(3.86;2.27-6.57;P<0.001)模型下均有显著性。T-429C 基因型间血压和低密度脂蛋白胆固醇(LDL-C)存在显著差异,G1704T 基因型间总胆固醇和 LDL-C 存在显著差异。多因素维度缩减模型中包含血脂异常、G1704T 和 T-429C。进一步基于 2 个显著多态性(血压和血脂)的预测列线图显示出更好的预测能力(一致性指数=0.716,P<0.001)。总之,我们鉴定出 2 个与 MI 发生相关的 RAGE 多态性,T-429C 和 G1704T,它们与代谢危险因素相互作用。我们还构建了一个遗传-代谢列线图,可更好地预测 MI 风险。

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