代谢紊乱与心肌梗死的因果关系:双向两样本孟德尔随机化分析  

Causality between Metabolic Disorders and Myocardial Infarction:a Two-Way Two-Sample Mendelian Randomization Analysis

作　　者：姜清陆 郑在勇 李妍漫 崔扬扬 许辉 周飞杰 胡厚祥[1,2] JIANG Qinglu;ZHENG Zaiyong;LI Yanman;CUI Yangyang;XU Hui;ZHOU Feijie;HU Houxiang(Academician Workstation,Affiliated Hospital of North Sichuan Medical College,Nanchong 637000,China;Department of Cardiology,Affiliated Hospital of North Sichuan Medical College,Nanchong 637000,China;Department of Cardiology,the Affiliated Hospital of Southwest Medical University,Luzhou 646000,China)

机构地区：[1]川北医学院附属医院院士工作站,四川省南充市637000 [2]川北医学院附属医院心内科,四川省南充市637000 [3]西南医科大学附属医院心内科,四川省泸州市646000

出　　处：《实用心脑肺血管病杂志》2024年第8期37-42,共6页Practical Journal of Cardiac Cerebral Pneumal and Vascular Disease

基　　金：四川省卫生健康委员会医学科技项目(21ZD004)。

摘　　要：目的采用双向两样本孟德尔随机化(MR)分析方法探讨代谢紊乱与心肌梗死的因果关系。方法在全基因组关联研究(GWAS)网站选取代谢紊乱数据集和心肌梗死数据集,均为2021年欧洲人群。其中代谢紊乱数据集样本量为218792例,单核苷酸多态性(SNP)数量为16380466个;心肌梗死数据集样本量为461823例,SNP数量为24172914个。本研究以逆方差加权法(IVW)分析结果为主,MR-Egger回归、简单模式、加权模式、加权中位数法分析结果为补充。采用Cochran's Q检验分析SNP间的统计学异质性,采用MR-Egger回归的截距项分析SNP的水平多效性,采用留一法分析单个SNP对IVW分析结果的影响。结果本研究最终纳入12个与代谢紊乱高度相关的SNP,55个与心肌梗死高度相关的SNP。正向MR分析的IVW分析结果显示,代谢紊乱可增加心肌梗死发生风险〔OR=1.898,95%CI(1.589~2.268),P<0.01〕;MR-Egger回归、简单模式、加权模式、加权中位数法分析结果亦显示,代谢紊乱可增加心肌梗死发生风险(P<0.01)。反向MR分析的IVW分析结果显示,心肌梗死可增加代谢紊乱发生风险〔OR=1.157,95%CI(1.099~1.218),P<0.01〕;MR-Egger回归、简单模式、加权中位数法分析结果亦显示,心肌梗死可增加代谢紊乱发生风险(P<0.01)。Cochran's Q检验结果显示,与代谢紊乱、心肌梗死高度相关的SNP间均存在统计学异质性(P<0.01)。MR-Egger回归的截距项分析结果显示,与代谢紊乱、心肌梗死高度相关的SNP不存在水平多效性(P>0.05)。留一法分析结果显示,逐一剔除与代谢紊乱、心肌梗死高度相关的SNP后,MR分析结果均无明显改变。结论代谢紊乱可增加心肌梗死发生风险,心肌梗死也可增加代谢紊乱发生风险,二者互为因果。Objective To explore the causal relationship between metabolic disorders and myocardial infarction by two-way two-sample Mendelian randomization(MR)analysis.Methods On the genome-wide association study(GWAS)website,the metabolic disorder dataset and the myocardial infarction dataset from the European population in 2021 were selected.The sample size of the metabolic disorder dataset was 218792,and the number of single nucleotide polymorphisms(SNP)was 16380466.The sample size of myocardial infarction dataset was 461823,and the number of SNP was 24172914.In this study,the results of inverse variance weighting(IVW)analysis were the main results,and by the supplemented results of MR-Egger regression,simple model,weighted model and weighted median method.Cochran's Q test was used to analyze the statistical heterogeneity among SNPs.The intercept term of MR-Egger regression was used to analyze the level pleiotropy of SNP.The effect of single SNP on MR analysis results was analyzed by leave-one-out method.Results Finally,12 SNPs highly associated with metabolic disorders and 55 SNPs highly associated with myocardial infarction were included in this study.IVW analysis of positive MR analysis showed that metabolic disorders could increase the risk of myocardial infarction[OR=1.898,95%CI(1.589-2.268),P<0.01];the results of MR-Egger regression,simple model,weighted model and weighted median method analysis also showed that metabolic disorder could increase the risk of myocardial infarction(P<0.01).IVW analysis of reverse MR analysis showed that myocardial infarction could increase the risk of metabolic disorders[OR=1.157,95%CI(1.099-1.218),P<0.01];the results of MR-Egger regression,simple model and weighted median method analysis also showed that myocardial infarction could increase the risk of metabolic disorders(P<0.01).Cochran's Q test results showed that there was statistical heterogeneity among SNPs highly associated with metabolic disorders and myocardial infarction(P<0.01).The results of intercept analysis of MR-Egger

关 键 词：心肌梗死 代谢紊乱 孟德尔随机化分析 因果关系 

分 类 号：R542.22[医药卫生—心血管疾病]