基于双向两样本孟德尔随机化法分析基础代谢率与衰弱指数的因果关系  

Causal relationship between basal metabolic rate and frailty index based on bidirectional two-sample mendelian randomization

作　　者：梁丽花[1] 袁玉冰 李莉 LIANG Li-hua;YUAN Yu-bing;LI Li(Department of Geratology,the Second Affiliated Hospital of Hainan Medical University,Haikou,Hainan 570311,China)

机构地区：[1]海南医学院第二附属医院老年医学科,海南海口570311

出　　处：《现代预防医学》2024年第12期2127-2132,2139,共7页Modern Preventive Medicine

基　　金：海南省卫生健康科研项目(21A200193)。

摘　　要：目的 本研究旨在应用双向两样本孟德尔随机化(MR)方法分析基础代谢率(BMR)与衰弱指数(FI)之间的因果关系。方法 从公开的全基因组关联研究(GWAS)汇总数据集中提取BMR(n=454 874)和FI(n=175 226)的数据。通过设置条件(以P<5×10^(-8)为筛选条件,连锁不平衡系数设置为0.001,连锁不平衡区域宽度为10 000 kb),筛选出最后作为工具变量的单核苷酸多态性(SNP)。应用MR-Egger回归、加权中位数、逆方差加权(IVW)、简单模式和加权模式五种方法进行MR分析,以IVW为主要分析方法,并采用β值及95%CI对BMR与FI之间的因果关系进行解释。采用MR-Egger截距和MR-PRESSO分析方法进行多效性检验,并且采用MR-Egger的Cochran Q检验进行异质性分析。同时使用留一法检验进行敏感性分析。最后,采用反向MR分析验证结果的稳健性。结果 共筛选到787个与BMR相关的SNP和9个与FI相关的SNP。MR分析结果显示,BMR与FI之间存在因果关系(加权中位数法,β=0.105,95%CI:0.063~0.146,P<0.001;IVW,β=0.110,95%CI:0.808~0.140,P<0.001;加权模式,β=0.145,95%CI:0.047~0.244,P=0.004)。MR-Egge截距为0.000 2(P=0.374),即筛选出的SNP不存在水平多效性,因此MR在本研究中为因果推断的有效方法。Cochran Q检验结果显示,Q=137.053,P=0.188,表明纳入MR分析的SNP之间不存在异质性。MR-PRESSO分析未发现离群的SNP。基于留一法的敏感度分析显示,单一SNP并不影响MR分析结果的稳健性。反向MR分析显示FI与BMR无因果关联(P>0.05)。结论 遗传学预测的高BMR水平与FI升高显著相关,在反向研究中并未发现关联,这可能为采取可行的干预措施来管理衰弱提供了新的思路。Objective To analyze the causal relationships between basal metabolic rate(BMR)and frailty index(FI)based on bidirectional two-sample mendelian randomization(MR).MethodsThe data of BMR(n=454874)and FI(n=175226)were extracted from the published genome-wide association studies(GWAS).By setting conditions with P<5×10^(-8) as the screening criterion,the linkage disequilibrium coefficient set to 0.001 and the width of the linkage disequilibrium region of10000kb,and single nucleotide polymorphisms(SNP)were screened out as the final instrumental variables.Five methods including MR-Egger regression,weighted median,Inverse variance weighted(IVW),simple mode and weighted mode were used for MR analysis,and IVW was used as the main analysis method,andβand 95%CI were used to demonstrate the causal relationship between BMR and FI.MR-Egger intercept and MR-PRESSO analysis were used to test the pleiotropy,and the heterogeneity was analyzed by Cochran Q test of MR-Egger.Leave-one-out test were performed to analyze the sensitivity.Finally,reverse MR analysis was used to verify the robustness of the results.ResultsA total of 787 SNPs associated with BMR and 9 SNPs associated with FI were screened.The MR analysis showed a causal relationship between BMR and FI(Weighted median,β=0.105,95%CI:0.063-0.146,P<0.001;IVW,β=0.110,95%CI:0.808-0.140,P<0.001;weighted mode,β=0.145,95%CI:0.047-0.244,P=0.004).The screened SNPs did not have horizontal pleiotropy because the the MR-Egger intercept was 0.0002(P=0.374),Therefore,the MR was an effective method for causal inference in this study.The Cochran Q-test results showed Q=137.053,P=0.188,indicating no heterogeneity among the SNPs included in the MR analysis.And no outlier SNPs were found by MR-PRESSO analysis.The sensitivity analysis based on the leave-one-out method showed that the individual SNP did not affect the robustness of the MR analysis results.No causal relationship between FI and BMR was found in the reverse MR analysis(P>0.05).ConclusionGenetically predicted high BMR level is s

关 键 词：孟德尔随机化 基础代谢率 衰弱 因果推断 

分 类 号：R195.4[医药卫生—卫生统计学]