非霍奇金淋巴瘤与慢性乙型肝炎病毒感染因果关系的双样本双向孟德尔随机化分析  

Causal relationship between non-Hodgkin lymphoma and chronic hepatitis B virus infection:a two-sample bidirectional Mendelian randomization analysis

作　　者：董凉凉 黄涌鉴 叶健强 念紫琳 杨琳[1] 陈婷[1] 刘文彬[1] 赵秋玲[1] 陈菊明 赖丽君 陈琴[1] Dong Liangliang;Huang Yongjian;Ye Jianqiang;Nian Zilin;Yang Lin;Chen Ting;Liu Wenbin;Zhao Qiuling;Chen Juming;Lai Lijun;Chen Qin(Department of Pharmacy,Clinical Oncology School of Fujian Medical University,Fujian Cancer Hospital,Fuzhou 350011,China;School of Pharmacy,Fujian Medical University,Fuzhou 350122,China;PET Center,Fujian Medical University Union Hospital,Fuzhou 350001,China)

机构地区：[1]福建医科大学肿瘤临床医学院福建省肿瘤医院药剂科,福州350011 [2]福建医科大学药学院,福州350122 [3]福建医科大学附属协和医院PET中心,福州350001

出　　处：《白血病.淋巴瘤》2025年第2期85-91,共7页Journal of Leukemia & Lymphoma

基　　金：福建省医学创新课题(2022CXA027);福建省肿瘤医院院内资助项目(2023YN11)。

摘　　要：目的采用双样本双向孟德尔随机化(MR)分析探讨非霍奇金淋巴瘤(NHL)和慢性乙型肝炎病毒(HBV)感染的相关性。方法NHL的遗传变异数据来自芬兰数据库(FinnGen)联盟2021年公开的全基因组关联分析(GWAS)数据集,包括1088例NHL患者和299952例对照受试者。慢性HBV感染的GWAS数据集来自2021年发表的GWAS分析,包括145例NHL患者和351740例对照受试者。先将NHL作为暴露因素,与NHL显著相关的单核苷酸多态性(SNP)作为工具变量,慢性HBV感染作为结局变量,采用逆方差加权(IVW)法进行双样本MR分析。再将慢性HBV感染作为暴露因素,与慢性HBV感染显著相关的SNP作为工具变量,NHL作为结局变量,进行反向双样本MR分析。IVW法利用各工具变量的方差倒数作为权重进行拟合,对SNP进行比值法逐一测算并加权回归,从而获得总体估计值。利用MR⁃Egger回归法、加权中位数(WME)法作为IVW法的补充。在敏感性分析中,采用留一法敏感性分析评估单个SNP的影响;通过Cochran Q检验分析所选工具变量的异质性;利用MR⁃Egger回归法衡量工具变量平均水平多效性的大小,计算出方向性P值;使用MR⁃多效性残差和与异质性(MR⁃PRESSO)Global Test排除可能的水平多效性离群值,减少偏倚。结果在留一法敏感性分析中剔除对因果关联影响较大的SNP。在正向MR分析中,工具变量为10个与NHL相关的SNP;IVW法表明NHL与慢性HBV感染不存在因果关联(OR=0.979,95%CI:0.925~1.036,P=0.465);MR⁃Egger回归法(OR=0.992,95%CI:0.926~1.062,P=0.825)和WME法(OR=0.992,95%CI:0.934~1.055,P=0.805)作为IVW法的补充,获得了一致的结果。在敏感性分析中,Cochran Q检验结果显示工具变量间不存在异质性(IVW法P=0.271,MR⁃Egger回归法P=0.239);在MR⁃Egger回归法(截距为-0.01,P=0.778)和MR⁃PRESSO Global Tes(t P>0.05)中未发现水平多效性,提示结果稳健。在反向MR分析中,工具变量为8个与慢性HBV感染相关的SNP。IVW法(OObjective To investigate the correlation between non-Hodgkin lymphoma(NHL)and chronic hepatitis B virus(HBV)infection by using the method of two-sample bidirectional Mendelian randomization(MR)analysis.Methods Genetic variation data for NHL came from the Finnish database(FinnGen)Consortium 2021 public genome-wide association study(GWAS)dataset including 1088 patients with NHL and 299952 control subjects.The GWAS dataset for chronic HBV infection was derived from GWAS analysis published in 2021,including 145 NHL patients and 351740 control subjects.NHL was used as an exposure factor,single nucleotide polymorphism(SNP)significantly associated with NHL was used as an instrumental variable(IV),chronic HBV infection was used as an outcome variable.The two-sample MR analysis was performed by using inverse-variance weighted(IVW)method.Chronic HBV infection was taken as an exposure factor,SNP significantly associated with chronic HBV infection was taken as IV,and NHL was taken as outcome variable,and then reverse two-sample MR analysis was performed.The IVW method used the inverse variance of each IV as the weight to fit,and the ratio method was used to measure SNP one by one and make weighted regression analysis,so as to obtain the overall estimate.MR-Egger regression and the weighted median(WME)method were also used to supplement the IVW method.In sensitivity analysis,leave-one-out sensitivity analysis was used to evaluate the impact of a single SNP.Cochran Q test was used to analyze the heterogeneity of the selected IV.MR-Egger regression was used to measure the average horizontal pleiotropy of IV,and the P-value of directivity was calculated.The MR-pleiotropy residual sum and outlier(MR-PRESSO)Global Test was used to exclude possible horizontal pleiotropic outliers and reduce bias.Results In the leave-one-out sensitivity analysis,SNP with significant effects on causal associations was excluded.In forward MR analysis,IVs were 10 SNPs associated with NHL;the IVW method indicated that there was no causal association bet

关 键 词：淋巴瘤 非霍奇金 乙型肝炎病毒 孟德尔随机化分析 因果关系 

分 类 号：R73[医药卫生—肿瘤]