Suppr超能文献

[遗传因素、年龄和吸烟对心肌梗死发病风险的综合影响]

[Combined Effect of Genetic Factors, Age, and Smoking on the Risk of Developing Myocardial Infarction].

作者信息

Osmak G J, Matveeva N A, Titov B V, Nasibullin T R, Mustafina O E, Shakhnovich R M, Kukava N G, Ruda M Ya, Favorova O O

机构信息

Russian Cardiology Scientific and Production Center, Moscow, Russia.

Pirogov Russian National Research Medical University, Moscow, Russia.

出版信息

Kardiologiia. 2016 Dec;56(12):5-10.

Abstract

OBJECTIVE

to elaborate a complex model for myocardial infarction (MI) risk assessment considering the combined effect of genetic predisposition, age and smoking.

MATERIALS AND METHODS

The study included two independent samples of ethnic Russians: 325 patients with MI and 185 individuals without history of cardiovascular diseases (controls) from the Moscow region, and 220 patients and 197 controls from the Republic of Bashkortostan. Genotyping of polymorphic loci of genes CRP (rs1130864), IFNG (rs2430561), TGFB1 (rs1982073), FGB (rs1800788) and PTGS1 (rs3842787) was performed. To construct the predictive models, we used logistic regression with stepwise inclusion of variables. The predictive value was evaluated by the area under the curve (AUC) in a ROC-analysis. The factor was considered as a marker at pAUC <0.05 calculated by the method of DeLong. The marker was considered effective at AUC >0.60.

RESULTS

Three separate genetic variants FGB rs1800788T, TGFB1 rs1982073TT, CRP rs1130864TT, and biallelic combination IFNG rs2430561A + PTGS1 rs3842787*T whose association with MI we described earlier, were used to construct the composite genetic marker (AUC=0.66 in the training and test samples) by the logistic regression method. Adding to the obtained composite genetic marker such parameters as age and smoking allowed to create a complex MI risk marker, which was characterized by the predictive value stability (AUC=0.77 in the training sample and 0.82 in the test sample).

CONCLUSION

The obtained complex model for MI risk assessment was reproduced in two independent samples of Russian ethnicity individuals from different regions of Russia with different gender identities, and allowed to have a reasonable chance (about 80%) of distinguishing patients and healthy individuals.

摘要

目的

构建一个综合考虑遗传易感性、年龄和吸烟的联合效应的心肌梗死(MI)风险评估复杂模型。

材料与方法

本研究纳入了两个俄罗斯族独立样本:来自莫斯科地区的325例MI患者和185例无心血管疾病史个体(对照组),以及来自巴什科尔托斯坦共和国的220例患者和197例对照组。对CRP(rs1130864)、IFNG(rs2430561)、TGFB1(rs1982073)、FGB(rs1800788)和PTGS1(rs3842787)基因的多态性位点进行基因分型。为构建预测模型,我们使用逐步纳入变量的逻辑回归。通过ROC分析中的曲线下面积(AUC)评估预测价值。根据DeLong方法计算的pAUC <0.05时,该因素被视为一个标志物。当AUC >0.60时,该标志物被认为是有效的。

结果

我们之前描述过的与MI相关的三个独立基因变异FGB rs1800788T、TGFB1 rs1982073TT、CRP rs1130864TT,以及双等位基因组合IFNG rs2430561A + PTGS1 rs3842787*T,通过逻辑回归方法用于构建复合遗传标志物(训练样本和测试样本中的AUC = 0.66)。将年龄和吸烟等参数添加到获得的复合遗传标志物中,得以创建一个复杂的MI风险标志物,其特征是预测价值稳定(训练样本中的AUC = 0.77,测试样本中的AUC = 0.82)。

结论

所获得的MI风险评估复杂模型在来自俄罗斯不同地区、具有不同性别特征的两个俄罗斯族独立样本中得到了重现,并且有合理的机会(约80%)区分患者和健康个体。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验