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Article(id=1240633240785056634, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240633237542851387, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202401296, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1705420800000, receivedDateStr=2024-01-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773719614453, onlineDateStr=2026-03-17, pubDate=1716566400000, pubDateStr=2024-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773719614453, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773719614453, creator=13701087609, updateTime=1773719614453, updator=13701087609, issue=Issue{id=1240633237542851387, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='10', pageStart='1729', pageEnd='1920', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773719613680, creator=13701087609, updateTime=1773720039302, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240635022806405370, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240633237542851387, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240635022806405371, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240633237542851387, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1748, endPage=1753, ext={EN=ArticleExt(id=1240633241108018043, articleId=1240633240785056634, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Immune cells and myocarditis: a two-sample and multivariate Mendelian randomization study, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

Using Mendelian randomization analysis to explore the immune cells involved in myocarditis(MC).

Methods

Genome-wide association study (GWAS) was used to mine the data, and the exposure factors were 731 immune cell traits, and the outcome factor was myocarditis. Regression models such as Inverse-Variance Weighted method (IVW), MR-Egger, Simple Mode, weighted median and Weighted Mode were used for Mendelian randomization analysis. At the same time, heterogeneity tests, horizontal multiple validity analyses, and sensitivity analyses were also conducted. Multivariate Mendelian randomization analysis of the relevant immune cell traits was performed by Inverse-Variance Weighted method (IVW) to correct the effect of seven positive immune cell traits on the outcome.

Results

(1)The results of Mendelian randomization showed that there was a causal relationship between 7 immune cell traits that include CD39+resting Treg %resting Treg (OR=1.237, 95%CI:1.039-1.474), CD4+CD8dim %leukocyte (OR=0.737, 95%CI:0.543-0.100), CD28-CD8dim AC (OR=0.868, 95%CI:0.753-0.100), CD28-CD8br AC (OR=1.398, 95%CI:1.097-1.780), CD20 on CD20-CD38- (OR=1.295, 95%CI:1.012-1.659), CCR2 on monocyte (OR=1.010, 95%CI:1.000-1.208), CD11b on basophil (OR=0.852, 95%CI:0.727-0.998) and MC.(2)The results of multivariate Mendelian randomization showed that CD39+ resting Treg %resting Treg (OR=1.228, 95%CI:1.059-1.423), CD28-CD8dim AC (OR=0.629, 95%CI:0.428-0.924), CCR2 on monocyte (OR=0.661, 95%CI:0.488-0.895) were correlated with MC.(3)The results of reverse Mendelian randomization did not find a causal relationship between 7 positive immune signatures and MC.

Conclusion

This study confirm the close relationship between immune cells and MC through genetics, which will provide a reference for future research.

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目的

采用孟德尔随机化分析方法，探究参与心肌炎（MC）的相关免疫细胞。

方法

对全基因关联研究数据库（GWAS）进行数据挖掘，暴露因素为731种免疫细胞特征，结局因素为心肌炎。采用逆方差加权法（IVW）、MR-Egger 法、Simple Mode法、加权中位数法和 Weighted Mode 法等回归模型进行孟德尔随机化分析。同时进行异质性检验、水平多效性分析、敏感性分析。通过逆方差加权法（IVW）对筛选出的相关免疫细胞特征进行多变量孟德尔随机化分析，以矫正7种阳性免疫细胞特征对结局的影响。

结果

（1）两样本孟德尔随机化IVW法结果显示：CD39+ resting Treg %resting Treg（OR=1.237，95%CI:1.039~1.474）、CD4+CD8dim %leukocyte（OR=0.737，95%CI:0.543~0.100）、CD28-CD8dim AC（OR=0.868，95%CI:0.753~0.100）、CD28-CD8br AC（OR=1.398，95%CI:1.097~1.780）、CD20 on CD20- CD38-（OR=1.295，95%CI:1.012~1.659）、CCR2 on monocyte（OR=1.010，95%CI:1.000~1.208）、CD11b on basophil（OR=0.852，95%CI:0.727~0.998）7种免疫细胞特征与MC存在因果关系。（2）多变量孟德尔随机化结果显示，CD39+ resting Treg %resting Treg（OR=1.228，95%CI:1.059~1.423）、CD28-CD8dim AC（OR=0.629，95%CI:0.428~0.924）、CCR2 on monocyte（OR=0.661，95%CI:0.488~0.895）与MC存在相关性。（3）反向孟德尔随机化结果未发现7种阳性免疫细胞特征与MC存在因果关系。

结论

本研究通过遗传学手段证实了免疫细胞与MC之间的密切联系，为今后的研究提供参考。

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姜红菊，E-mal：
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薛思杨（1993—），男，硕士，住院医师，研究方向：中西医结合治疗心血管病的临床研究

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薛思杨（1993—），男，硕士，住院医师，研究方向：中西医结合治疗心血管病的临床研究

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薛思杨（1993—），男，硕士，住院医师，研究方向：中西医结合治疗心血管病的临床研究

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The next step in Mendelian randomization[J]. eLife, 2023, 12: e86416., articleTitle=The next step in Mendelian randomization, refAbstract=null)], funds=[Fund(id=1240633246099238968, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, awardId=202103011004, language=CN, fundingSource=山东省医药卫生科技发展计划项目(202103011004), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1240633242093679495, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, xref=null, ext=[AuthorCompanyExt(id=1240633242102068105, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, companyId=1240633242093679495, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Department of Cardiology, Jinan, Shandong 250001, China), AuthorCompanyExt(id=1240633242110456714, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, companyId=1240633242093679495, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=山东中医药大学第二附属医院 心血管病科，山东 济南 250001)])], figs=[ArticleFig(id=1240633243612017626, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, language=EN, label=Fig.1, caption=Univariate MR analysis scatter plots, figureFileSmall=wNZtBYHNdG7Tmp0iMaEY9g==, figureFileBig=gL4w3Kg9ahOyFrCFUmDDYg==, tableContent=null), ArticleFig(id=1240633243721069538, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, language=CN, label=图1, caption=单变量MR分析散点图

注：图A为CD39+ resting Treg %resting Treg、图B为CD4+ CD8dim %leukocyte、图C为CD28- CD8dim AC、图D为CD28- CD8br AC、图E为CD20 on CD20- CD38-、图F为CCR2 on monocyte、图G为CD11b on basophil 7种阳性免疫细胞表型MR分析散点图。

, figureFileSmall=wNZtBYHNdG7Tmp0iMaEY9g==, figureFileBig=gL4w3Kg9ahOyFrCFUmDDYg==, tableContent=null), ArticleFig(id=1240633245428151290, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, language=EN, label=Fig.2, caption=Results of leave-one-out method, figureFileSmall=icsCMl6tZbdW3WonDC5hcQ==, figureFileBig=cjHY4rb6iUMWQx6xzIXuTQ==, tableContent=null), ArticleFig(id=1240633245520424961, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, language=CN, label=图2, caption=留一法敏感性分析图

注：图A为CD39+ resting Treg %resting Treg、图B为CD4+ CD8dim %leukocyte、图C为CD28- CD8dim AC、图D为CD28- CD8br AC、图E为CD20 on CD20- CD38-、图F为CCR2 on monocyte、图G为CD11b on basophil 7种阳性免疫细胞表型留一法敏感性分析图。

, figureFileSmall=icsCMl6tZbdW3WonDC5hcQ==, figureFileBig=cjHY4rb6iUMWQx6xzIXuTQ==, tableContent=null), ArticleFig(id=1240633245637865483, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, language=EN, label=Table 1, caption=

The relevant data information was extracted from the GWAS database

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称分组年份人群样本量（例）SNP数量GWAS ID
暴露
CD39+ resting Treg %resting TregTreg2020欧洲3 43715 144 196ebi-a-GCST90001484
CD4+ CD8dim %leukocyteTBNK2020欧洲3 66815 198 002ebi-a-GCST90001611
CD28- CD8dim ACTreg2020欧洲3 40815 135 292ebi-a-GCST90001663
CD28- CD8br ACTreg2020欧洲3 40815 135 292ebi-a-GCST90001687
CD20 on CD20- CD38-B cell2020欧洲3 60615 039 196ebi-a-GCST90001744
CCR2 on monocyteMonocyte2020欧洲362915 034 296ebi-a-GCST90002008
CD11b on basophilMyeloid cell2020欧洲1 55614 113 011ebi-a-GCST90002096
结局
心肌炎MC2021欧洲427 91124 180 570ebi-a-GCST90018882
), ArticleFig(id=1240633245730140179, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, language=CN, label=表1, caption=

提取GWAS数据库中相关数据信息

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称分组年份人群样本量（例）SNP数量GWAS ID
暴露
CD39+ resting Treg %resting TregTreg2020欧洲3 43715 144 196ebi-a-GCST90001484
CD4+ CD8dim %leukocyteTBNK2020欧洲3 66815 198 002ebi-a-GCST90001611
CD28- CD8dim ACTreg2020欧洲3 40815 135 292ebi-a-GCST90001663
CD28- CD8br ACTreg2020欧洲3 40815 135 292ebi-a-GCST90001687
CD20 on CD20- CD38-B cell2020欧洲3 60615 039 196ebi-a-GCST90001744
CCR2 on monocyteMonocyte2020欧洲362915 034 296ebi-a-GCST90002008
CD11b on basophilMyeloid cell2020欧洲1 55614 113 011ebi-a-GCST90002096
结局
心肌炎MC2021欧洲427 91124 180 570ebi-a-GCST90018882
), ArticleFig(id=1240633245860163615, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, language=EN, label=Table 2, caption=

Results of univariate Mendelian randomization analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露结局分析方法βsePadjuestPOR(95%CI)
CD39+ resting Treg %resting Treg0.2130.0900.0170.0491.237(1.039~1.474)
CD4+ CD8dim %leukocyte-0.3060.1550.0490.0490.737(0.543~1.000)
CD28- CD8dim AC-0.1420.0720.0480.0490.868(0.753~1.000)
CD28- CD8br ACMCIVW0.3350.1230.0070.0491.398(1.097~1.780)
CD20 on CD20- CD38-0.2590.1260.0400.0491.295(1.012~1.659)
CCR2 on monocyte0.0950.0480.0490.0491.010(1.000~1.208)
CD11b on basophil-0.1610.0810.0470.0490.852(0.727~0.998)
), ArticleFig(id=1240633245981798441, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240633240785056634, language=CN, label=表2, caption=

单变量孟德尔随机化分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露结局分析方法βsePadjuestPOR(95%CI)
CD39+ resting Treg %resting Treg0.2130.0900.0170.0491.237(1.039~1.474)
CD4+ CD8dim %leukocyte-0.3060.1550.0490.0490.737(0.543~1.000)
CD28- CD8dim AC-0.1420.0720.0480.0490.868(0.753~1.000)
CD28- CD8br ACMCIVW0.3350.1230.0070.0491.398(1.097~1.780)
CD20 on CD20- CD38-0.2590.1260.0400.0491.295(1.012~1.659)
CCR2 on monocyte0.0950.0480.0490.0491.010(1.000~1.208)
CD11b on basophil-0.1610.0810.0470.0490.852(0.727~0.998)
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免疫细胞在心肌炎中的因果作用：两样本与多变量孟德尔随机化研究
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薛思杨 , 姜红菊
现代预防医学 | 流行病与统计方法 2024,51(10): 1748-1753
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现代预防医学 | 流行病与统计方法 2024, 51(10): 1748-1753
免疫细胞在心肌炎中的因果作用：两样本与多变量孟德尔随机化研究
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薛思杨, 姜红菊
作者信息
  • 山东中医药大学第二附属医院 心血管病科，山东 济南 250001

    • 薛思杨（1993—），男，硕士，住院医师，研究方向：中西医结合治疗心血管病的临床研究

通讯作者:

姜红菊，E-mal：
Immune cells and myocarditis: a two-sample and multivariate Mendelian randomization study
Si-yang XUE, Hong-ju JIANG
Affiliations
  • The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Department of Cardiology, Jinan, Shandong 250001, China
出版时间: 2024-05-25 doi: 10.20043/j.cnki.MPM.202401296
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摘要
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目的

采用孟德尔随机化分析方法，探究参与心肌炎（MC）的相关免疫细胞。

方法

对全基因关联研究数据库（GWAS）进行数据挖掘，暴露因素为731种免疫细胞特征，结局因素为心肌炎。采用逆方差加权法（IVW）、MR-Egger 法、Simple Mode法、加权中位数法和 Weighted Mode 法等回归模型进行孟德尔随机化分析。同时进行异质性检验、水平多效性分析、敏感性分析。通过逆方差加权法（IVW）对筛选出的相关免疫细胞特征进行多变量孟德尔随机化分析，以矫正7种阳性免疫细胞特征对结局的影响。

结果

（1）两样本孟德尔随机化IVW法结果显示：CD39+ resting Treg %resting Treg（OR=1.237，95%CI:1.039~1.474）、CD4+CD8dim %leukocyte（OR=0.737，95%CI:0.543~0.100）、CD28-CD8dim AC（OR=0.868，95%CI:0.753~0.100）、CD28-CD8br AC（OR=1.398，95%CI:1.097~1.780）、CD20 on CD20- CD38-（OR=1.295，95%CI:1.012~1.659）、CCR2 on monocyte（OR=1.010，95%CI:1.000~1.208）、CD11b on basophil（OR=0.852，95%CI:0.727~0.998）7种免疫细胞特征与MC存在因果关系。（2）多变量孟德尔随机化结果显示，CD39+ resting Treg %resting Treg（OR=1.228，95%CI:1.059~1.423）、CD28-CD8dim AC（OR=0.629，95%CI:0.428~0.924）、CCR2 on monocyte（OR=0.661，95%CI:0.488~0.895）与MC存在相关性。（3）反向孟德尔随机化结果未发现7种阳性免疫细胞特征与MC存在因果关系。

结论

本研究通过遗传学手段证实了免疫细胞与MC之间的密切联系，为今后的研究提供参考。

孟德尔随机化  /  全基因组关联研究  /  心肌炎  /  免疫细胞
Objective

Using Mendelian randomization analysis to explore the immune cells involved in myocarditis(MC).

Methods

Genome-wide association study (GWAS) was used to mine the data, and the exposure factors were 731 immune cell traits, and the outcome factor was myocarditis. Regression models such as Inverse-Variance Weighted method (IVW), MR-Egger, Simple Mode, weighted median and Weighted Mode were used for Mendelian randomization analysis. At the same time, heterogeneity tests, horizontal multiple validity analyses, and sensitivity analyses were also conducted. Multivariate Mendelian randomization analysis of the relevant immune cell traits was performed by Inverse-Variance Weighted method (IVW) to correct the effect of seven positive immune cell traits on the outcome.

Results

(1)The results of Mendelian randomization showed that there was a causal relationship between 7 immune cell traits that include CD39+resting Treg %resting Treg (OR=1.237, 95%CI:1.039-1.474), CD4+CD8dim %leukocyte (OR=0.737, 95%CI:0.543-0.100), CD28-CD8dim AC (OR=0.868, 95%CI:0.753-0.100), CD28-CD8br AC (OR=1.398, 95%CI:1.097-1.780), CD20 on CD20-CD38- (OR=1.295, 95%CI:1.012-1.659), CCR2 on monocyte (OR=1.010, 95%CI:1.000-1.208), CD11b on basophil (OR=0.852, 95%CI:0.727-0.998) and MC.(2)The results of multivariate Mendelian randomization showed that CD39+ resting Treg %resting Treg (OR=1.228, 95%CI:1.059-1.423), CD28-CD8dim AC (OR=0.629, 95%CI:0.428-0.924), CCR2 on monocyte (OR=0.661, 95%CI:0.488-0.895) were correlated with MC.(3)The results of reverse Mendelian randomization did not find a causal relationship between 7 positive immune signatures and MC.

Conclusion

This study confirm the close relationship between immune cells and MC through genetics, which will provide a reference for future research.

Mendelian randomization(MR)  /  Genome-wide association study (GWAS)  /  Cardiomyocytes  /  Immune cells
薛思杨, 姜红菊. 免疫细胞在心肌炎中的因果作用：两样本与多变量孟德尔随机化研究. 现代预防医学, 2024 , 51 (10) : 1748 -1753 . DOI: 10.20043/j.cnki.MPM.202401296
Si-yang XUE, Hong-ju JIANG. Immune cells and myocarditis: a two-sample and multivariate Mendelian randomization study[J]. Modern Preventive Medicine, 2024 , 51 (10) : 1748 -1753 . DOI: 10.20043/j.cnki.MPM.202401296
正文
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心肌炎是指心脏中各种病理性免疫过程的临床和组织学表现。免疫细胞数量和功能改变以及抗体介导的损伤通常导致急、慢性心肌炎[1]。然而在众多免疫细胞中何种免疫细胞参与心肌炎（myocarditis，MC）尚不清楚。近年MC发病率持续上升，全球MC患病率从10.2/100 000上升至105.6/100 000[2]。尽管MC已成为全球性的公共卫生问题，但目前尚无针对心肌炎的特效药物。究其原因，可能与对该病发病机制了解欠深入有关。因此明确MC的免疫相关发病机制十分必要。孟德尔随机化（Mendelian randomization，MR）是一种以遗传变异作为工具变量的统计模型[3]，它能规避观察性研究带来的潜在混杂、反向因果等偏倚风险，在一定程度上与随机对照研究相似[4]。该分析方法可用于评估暴露因素与结局因素间因果关系[5]。我们的目的是通过孟德尔随机化确定相关免疫细胞与心肌炎之间的因果关系。基于公开的遗传数据，我们探索了731种免疫细胞特征与MC之间的因果关系。共纳入4种免疫标签：中位荧光强度(median fluorescence intensity, MFI)、相对细胞(relative cell, RC)、绝对细胞(absolute cell, AC)和形态学参数(morphological parameters，MP)。采用双向、多变量MR分析方法深入了解MC免疫相关发病机制。
1　资料与方法
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1.1　研究设计
基于两样本MR分析，我们评估了731个免疫细胞特征组与心肌炎之间的因果关系。MR使用遗传变异来表示风险因素，因此，因果推理中有效的工具变量必须满足三个关键假设：(1)关联性假设：遗传变异与暴露直接相关。(2)独立性假设：遗传变异与暴露和结局之间可能存在的混杂因素无关。(3)排他性假设：遗传变异不通过暴露以外的途径影响结局。
1.2　数据来源
暴露变量为731种免疫细胞特征，每个免疫细胞特征的GWAS汇总统计数据可从GWAS目录中公开获得(GWAS ID从GCST90001391到GCST90002121)[6]。包括绝对细胞(AC)计数(n=118)、反映表面抗原水平的中位荧光强度(MFI)(n=389)、形态参数[MP] (n=32)和相对细胞(RC)计数(n=192)。具体来说，MFI、AC和RC特征包含B细胞、CDCs、成熟阶段的T细胞、单核细胞、骨髓细胞、TBNK (T细胞、B细胞、自然杀伤细胞)和Treg组，而MP特征包含CDC和TBNK组。731种免疫特性GWAS使用了来自3 757名撒丁岛人的数据[6]。结局变量为MC，MC的GWAS汇总统计数据来自Sakaue等[7]的研究。该研究对427 911名英国人(Ncase=633, Ncontrol=427 278)进行了GWAS，共包含24 180 570个SNPs。暴露变量及结局数据均来源于IEU Open GWAS project（https://gwas.mrcieu.ac.uk/）数据库。为保证两样本MR暴露和结果之间的独立性，避免样本重叠造成的偏倚，暴露变量采用撒丁岛人（意大利）的数据，结局变量采用英国人的数据。同时为避免群体分层带来的偏倚，暴露与结局所包含的全部队列都来自欧洲人群。
1.3　工具变量选择
与暴露因素有关的工具变量应该符合以下要求：（1）所有工具变量应具有全基因组意义（P<5×10-6/P<5×10-8）；（2）连锁不平衡参数r2=0.001，且区域范围在10 000 kb内；（3）F检验挑选F>10的工具变量，以排除弱工具变量偏倚，其公式为：F=(N-k-/k)×(R2/1-R2),其中N表示GWAS分析中的样本量；k表示工具变量的个数；R2表示工具变量解释暴露因素的程度。R2的具体计算方法如下：R2=2×(1-MAF)×MAF×β2。其中MAF表示次等位基因频率（minor allele frequency),β表示SNP对暴露因素的效应值(effect size)。（4）剔除任何可能具有不相容等位基因或回文SNP。（5）与混杂因素相关的SNPs需要被排除，本研究通过Phenoscanner数据库查询并剔除与混杂因素相关的SNPs。剔除混杂因素包括营养不良，剧烈运动，过劳，妊娠，辐射暴露[8-9]。将通过筛选的SNPs作为本研究的工具变量。
我们通过以上标准共筛选出7种相关免疫细胞特征，分别是CD39+ resting Treg %resting Treg、CD4+ CD8dim %leukocyte、CD28- CD8dim AC、CD28- CD8br AC、CD20 on CD20- CD38-、CCR2 on monocyte、CD11b on basophil。见表1。
1.4　MR分析
单变量和多变量分析主要采用逆方差加权法（inverse-variance weighted，IVW），原因是IVW法可以在不存在多效性的条件下获得一个稳健的结果[10]。同时单变量分析使用MR-Egger法、Simple Mode法、加权中位数法（weighted median，WM）和Weighted Mode法作为补充方法检测主分析的稳健性。通过逐一排除法及异常值（MR-PRESSO）方法进行敏感性分析。异常值法可识别和解释可能的重要离群点，这些离群点数值会增加分析的异质性及水平多效性。逐一排除法则可探讨单个SNP对因果关系的影响。通过敏感性分析对每个SNP进行检验，以排除可能对结果产生严重影响的变量。多效性分析通过MR-Egger截距测试，如果P<0.05则说明数据存在多效性。通过IVW和MR-Egger检验Cochran's值评估异质性，Q-Pval<0.1说明研究存在异质性。当研究存在异质性时，则采用随机效应模型进行MR分析。MR分析通过R软件（4.3.2版本）的“Two Sample MR”、“MRPRESSO”、“ggplot2”和“MendelianRandomization”程序包实现。
2　结果
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2.1　单变量MR分析
2.1.1　CD39+ resting Treg %resting Treg分析结果
CD39+ resting Treg %resting Treg分析结果显示五种分析结果方向一致（表2和图1），MR分析前剔除回文SNPrs192831774、rs4918971。异质性检验提示不存在异质性（Q-Pval>0.1），采取固定效应模型IVW法分析，MR-Egger测试无多效性P=0.509。逐一排除法及 MR-PRESSO方法进行敏感性分析未发现对因果关联影响较大的 SNPs（图2）。IVW法结果显示TCD39+ resting Treg %resting Treg是MC的危险性因素（OR=1.237，95%CI：1.039~1.474）。
2.1.2　CD4+ CD8dim %leukocyte分析结果
CD4+ CD8dim %leukocyte分析结果显示四种分析结果方向一致（表2和图1），MR分析前剔除回文SNPrs35290870，异质性检验提示不存在异质性（Q-Pval>0.1），采取固定效应模型IVW法分析，MR-Egger测试无多效性0.312。逐一排除法及 MR-PRESSO方法进行敏感性分析未发现对因果关联影响较大的SNPs（图2）。IVW结果显示CD4+ CD8dim %leukocyte是MC的保护性因素（OR=0.737，95%CI：0.543~0.999）。
2.1.3　CD28- CD8dim AC分析结果
CD28- CD8dim AC分析结果显示五种分析结果方向一致（表2和图1），MR分析前经分析无回文SNP，异质性检验提示不存在异质性（Q-Pval>0.1），采取固定效应模型IVW法分析，MR-Egger测试无多效性P=0.333。逐一排除法及 MR-PRESSO方法进行敏感性分析未发现对因果关联影响较大的SNPs（图2）。IVW法结果显示CD28-CD8dimAC是MC的保护性因素（OR=0.868，95%CI：0.753~0.999）。
2.1.4　CD28- CD8br AC分析结果
CD28- CD8br AC结果显示五种分析结果方向一致（表2和图1），MR分析前剔除回文SNPrs1451433，异质性检验提示不存在异质性（Q-Pval>0.1），采取固定效应模型IVW法分析，MR-Egger测试无多效性P=0.243。逐一排除法及 MR-PRESSO方法进行敏感性分析未发现对因果关联影响较大的SNPs（图2）。IVW法结果显示CD28-CD8br AC是MC的危险因素（OR=1.398，95%CI：1.097~1.780）。
2.1.5　CD20 on CD20-CD38-分析结果
CD20 on CD20-CD38-分析结果显示五种分析结果方向一致（表2和图1），MR分析前剔除回文SNPrs2861007、rs572468、rs6930288、rs73015549，异质性检验提示不存在异质性（Q-Pval>0.1），采取固定效应模型IVW法分析，MR-Egger测试无多效性P=0.682。逐一排除法及MR-PRESSO方法进行敏感性分析未发现对因果关联影响较大的SNPs（图2）。IVW法结果显示CD20 on CD20-CD38-是MC的危险因素（OR=1.295，95%CI：1.012~1.659）。
2.1.6　CCR2 on monocyte分析结果
CCR2 on monocyte分析结果显示五种分析结果方向一致（表2和图1），MR分析前剔除回文SNPrs13060505、rs141411805，异质性检验提示不存在异质性（Q-Pval>0.1），采取固定效应模型IVW法分析，MR-Egger测试无多效性P=0.953。逐一排除法及MR-PRESSO方法进行敏感性分析未发现对因果关联影响较大的SNPs（图2）。IVW法结果显示CCR2 on monocyte是MC的危险因素（OR=1.010，95%CI：1.000~1.208）。
2.1.7　CD11b on basophil分析结果
CD11b on basophil分析结果显示五种分析结果方向一致（表2和图1），MR分析前经分析无回文SNP，异质性检验提示不存在异质性（Q-Pval>0.1），采取固定效应模型IVW法分析，MR-Egger测试无多效性P=0.541。逐一排除法及MR-PRESSO方法进行敏感性分析未发现对因果关联影响较大的SNPs（图2）。IVW法结果显示CD11b on basophil是MC的保护因素（OR=0.852，95%CI：0.727~0.998）。
本研究涉及到了多个暴露，为减少I型错误的概率，采用FDR（Benjamini-Hochberg法）法对检验P值进行恰当校正，矫正结果adjuest P分别为0.049，0.049，0.049，0.049，0.049，0.049，0.049（表2），FDR值均低于0.05，7种免疫细胞特征均具有显著性差异。
2.2　多变量MR分析
作为两样本MR的延伸，多变量MR可以通过将所有暴露纳入同一模型来估计各种风险因素对结局风险的因果影响[11]。为此我们将7个筛选出与MC相关的免疫细胞特征通过多变量MR分析以矫正多种阳性免疫细胞特征对结局的影响。结果显示CD39+ resting Treg %resting Treg（OR=1.228，95%CI：1.059~1.423）、CD28-CD8dim AC（OR=0.629，95%CI：0.428~0.924）、CCR2 on monocyte（OR=0.661，95%CI：0.488~0.895）与MC存在因果关系（P<0.05），提示当7种免疫细胞特征同时激活时，此3种免疫细胞特征与MC存在相关性。CD39+ resting Treg %resting Treg是MC的危险性因素，CD28- CD8dim AC、CCR2 on monocyte是MC的保护性因素。估计CD4+ CD8dim %leukocyte、CD28- CD8br AC、CD20 on CD20- CD38-、CD11b on basophil与MC结果具有统计学意义（P>0.05）。
2.3　反向MR分析
为探讨MC对已筛选7种阳性免疫细胞特征的因果关系，采用两样本单变量进行反向MR分析。分析前计算MC每个SNP的F统计量均>10。剔除回文SNPrs11914368、rs138644018。异质性检验提示CD28- CD8dim AC存在异质性，采取固定效应模型IVW法分析。余不存在异质性，采用随机效应模型IVW法分析。逐一排除法及MR-PRESSO方法进行敏感性分析未发现对因果关联影响较大的SNPs。MR-Egger测试均无多效性。IVW法结果显示MC不是已筛选7种阳性免疫细胞特征的影响因素，无因果关联（P>0.05）。
3　讨论
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基于大量公开的遗传数据，我们探索了731种免疫细胞特征与MC之间的因果关系。据我们所知，这是首次探索多种免疫细胞特征与MC之间因果关系的MR分析。本研究发现，两样本MR研究显示7种免疫细胞特征与MC存在相关性，多变量MR显示当7种免疫细胞特征同时激活时只有3种免疫细胞特征与MC存在相关性。反向MR分析显示MC与已筛选7种阳性免疫细胞特征无因果关联。
心肌炎是指心脏中局限性或弥漫性的病理免疫过程的临床和组织学表现。免疫细胞数量和功能的改变以及抗体介导的损伤通常见于急性和慢性心肌炎患者[1]。我们关于免疫细胞特征与心肌炎之间因果关系的研究结果证实了之前的流行病及实验室研究。既往研究结果表明，CD28-CD8T细胞群由各种功能竞争（细胞毒性和免疫抑制性）亚群组成[12]，可进一步分化为多种免疫细胞特征，分别具有免疫抑制性或细胞毒性[13]，其介导的免疫取决于特定亚群的优势，分化为免疫抑制性的CD28-CD8 T细胞不产生细胞因子，没有杀伤能力[13]，限制心肌损害的发展，而分化为细胞毒性CD28-CD8 T细胞亚群通过释放颗粒酶和穿孔素特异性的杀伤病原体感染的细胞，从而清除各种病原微生物，但同时也造成心肌细胞的坏死或凋亡[11]；我们的研究结果表明，CD20-CD38上的CD20与MC风险增加显著相关，其属于B淋巴细胞，最近的研究也强调了B淋巴细胞在MC发展中的重要作用，B淋巴细胞通过分泌细胞因子及抗原呈递作用导致心肌损伤[14]。此外记忆B淋巴细胞因富含自身抗体并且能为浆细胞的分化做好准备，参与慢性感染和自身免疫性疾病。而CD20是一种在B淋巴细胞表面的独特抗原，它被认为在调节B淋巴细胞增殖、分化和信号传导过程中具有重要作用[15]；我们的研究揭示了CD39+ resting Treg %resting Treg水平升高与MC风险之间的正相关性。T细胞可分为三个亚群：辅助性T细胞、细胞毒性T细胞和Treg细胞。Treg 细胞对免疫系统调节、体内平衡和预防自身免疫至关重要。先前对Treg细胞的研究表明，在感染巨细胞病毒（CMV）的内皮细胞中观察到通过Tregs激活的T细胞受体（TCR）诱导CD39活性增强，继而引起胞外核苷酶的上调，局部腺苷产生的增加，产生免疫抑制和抗血栓形成的微环境，使病毒更容易进入靶细胞[16]；心肌炎的特征是心脏的炎症细胞浸润和随后的心脏功能恶化。心肌炎性细胞中单核细胞是最突出的白细胞亚群。单核细胞的一个子集表达为CCR2，CCR2是一种对促炎单核细胞和巨噬细胞亚群积累至关重要的受体[17]。缺乏CCR2的小鼠表现出心肌炎严重程度降低[18]，通过沉默心肌炎小鼠的CCR2表达，可减少心脏中的单核细胞侵润，改善不良的心肌重塑和心功能不全[19]。在心肌炎患者的心脏组织活检中的CCR2及其主要同源趋化因子配体MCP-1（也称为CCL2）mRNA较正常组织分别增加了5.4倍和4.6倍证明了人类心肌炎中CCR2细胞的存在。
本研究通过孟德尔随机化法规避观察性研究带来的潜在混杂、反向因果等偏倚风险，评估暴露因素与结局因素间因果关系，并且采用大样本分析研究，使结果更具有说服力。但本文在分析过程中同时存在局限性，比如①MR分析人群的GWAS数据为欧洲人，在应用时应考虑不同人种之间存在等位基因频率和疾病患病率的差异。②受GWAS数据库限制，疾病严重程度等详尽数据无法获取。③MR分析中，每种方法都有其优点和缺点。该研究使用了5种基于不同假设的方法，这可能导致结果不一致，从而使研究结论模糊不清[20]。
总之，我们通过MR分析证明了几种免疫细胞特征与MC之间的因果关系，强调了免疫系统与MC之间相互作用的复杂模式。此外，我们的研究显著降低了混杂因素、反向因果关系和其他因素的影响。这可能为研究人员探索MC的生物学机制提供新的途径，为探索MC的特异性诊断标志物及药物治疗靶点提供早期研究基础。
基金
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  • 山东省医药卫生科技发展计划项目(202103011004)
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2024年第51卷第10期
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doi: 10.20043/j.cnki.MPM.202401296
  • 接收时间：2024-01-17
  • 首发时间：2026-03-17
  • 出版时间：2024-05-25
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  • 收稿日期：2024-01-17
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山东省医药卫生科技发展计划项目(202103011004)
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    山东中医药大学第二附属医院 心血管病科，山东 济南 250001

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2种不同金属材料的力学参数
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Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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