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Article(id=1241102741431439614, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202403445, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1711296000000, receivedDateStr=2024-03-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773831552130, onlineDateStr=2026-03-18, pubDate=1721836800000, pubDateStr=2024-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773831552130, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773831552130, creator=13701087609, updateTime=1773831552130, updator=13701087609, issue=Issue{id=1241102730337505325, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='14', pageStart='2497', pageEnd='2688', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773831549486, creator=13701087609, updateTime=1773831697291, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241103350322745680, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241103350322745681, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2528, endPage=2534, ext={EN=ArticleExt(id=1241102741976699158, articleId=1241102741431439614, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=A two-step and two-sample mendelian randomization study on the causal relationship between liposomes and immune cells with non-small cell lung cancer, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the causal relationship between immune cell mediated liposomes and non-small cell lung cancer (NSCLC) using two-sample Mendelian randomization and two-step analysis.

Methods

Summary data of GWAS for plasma liposomes were obtained from the GWAS Catalog as exposure data. Summary data of GWAS for 731 types of immune cells were selected as potential mediators, and NSCLC data from the ninth release of the FinnGen database were used as outcome data. Inverse-variance weighted (IVW) was used for two-step. Two-sample Mendelian randomization analysis was used to investigate the causal relationship between liposomes and NSCLC and the mediating role of immune cells in the lipid-NSCLC association. Weighted median and MR-Egger methods were used as supplements, along with pleiotropy and heterogeneity tests to ensure result stability.

Results

The IVW method identified 36 liposomes associated with NSCLC, with no evidence of reverse causation. A total of 47 immune cell types were strongly associated with NSCLC. Notably, triglyceride (TG) (58:8) had a causal effect on NSCLC (OR=1.183, 95%CI: 1.061-1.319). The mediation effect mediated by Effector Memory CD8+ T cell %CD8+ T cell was 0.003 (95%CI: -0.007-0.013), accounting for 1.94% of the total effect, while the mediation effect mediated by CD8+ and CD8dim T cell %leukocyte was 0.012 (95%CI: -0.004-0.028), accounting for 7.24% of the total effect.

Conclusion

This study suggests a causal relationship between liposomes and NSCLC, identifying TG as a risk factor for NSCLC progression. Effector Memory CD8+ T cell %CD8+ T cell and CD8+ CD8dim T cell %leukocyte play a mediating role in this process.

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目的

本研究旨在使用双样本孟德尔随机化以及两步法分析来研究免疫细胞介导脂质体与非小细胞肺癌(NSCLC)之间的因果关系。

方法

本研究从GWAS Catalog中获取了血浆脂质的GWAS汇总数据作为研究的暴露数据，选用了731种免疫细胞的GWAS汇总数据作为潜在的中介变量以及FinnGen数据库第九版发布的NSCLC数据作为结局数据。采用逆方差加权法(IVW)进行了两步、双样本孟德尔随机化分析，以研究脂质对NSCLC的因果关系以及免疫细胞在脂质体和NSCLC关联之间的介导作用。加权中位数法、MR-Egger等方法进行补充，同时进行水平多效性和异质性的检验保证结果的稳定性。

结果

IVW方法确定了36种脂质体与NSCLC相关，且无反向因果关系。与NSCLC具有强相关性的免疫细胞共有47种。值得注意的是，三酰甘油(TG)(58:8)与NSCLC存在因果效应(OR=1.183,95%CI：1.061~1.319)，由CD8+ T细胞中效应记忆CD8+T细胞介导的中介效应为0.003(95%CI：-0.007~0.013)，占总效应的1.94%，由白细胞中CD8+CD8dim T细胞介导的中介效应为0.012(95%CI：-0.004~0.028)，占总效应的7.24%。

结论

该研究表明，脂质体和NSCLC之间存在因果关系，TG是NSCLC进展当中的危险因素，并且在此过程中CD8+ T细胞中效应记忆CD8+T细胞和白细胞中CD8+CD8dim T细胞发挥了介导作用。

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于琦，E-mail：
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=Zpk4r8ajL6R6TPLoALJyIA==, magXml=mdWZnZrPetVAhI/Pp/YSaw==, pdfUrl=null, pdf=vFwbuC6EksfULyh/naZ8hg==, pdfFileSize=1010181, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=iaFE9vU+rqDmNR8wttXl0w==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=gaTf47fLqJ89kMJ9IA+46g==, mapNumber=null, authorCompany=null, fund=null, authors=

侯雅琪（1999—）,女，硕士在读，研究方向：生物信息学

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侯雅琪（1999—）,女，硕士在读，研究方向：生物信息学

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侯雅琪（1999—）,女，硕士在读，研究方向：生物信息学

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Proceedings of theNational Academy of Sciences of the United States of America, 2018, 115(2): 385-390., articleTitle=Mixed signature of activation and dysfunction allows human decidual CD8(+)T cells to provide both tolerance and immunity, refAbstract=null)], funds=[Fund(id=1241102754035323832, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, awardId=HGKY2019057, language=CN, fundingSource=山西省回国留学人员科研资助项目(HGKY2019057), fundOrder=null, country=null), Fund(id=1241102754127598526, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, awardId=202102130501003, language=CN, fundingSource=山西省重点研发计划项目(202102130501003), fundOrder=null, country=null), Fund(id=1241102754232456132, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, awardId=202303021221132, language=CN, fundingSource=山西省基础研究计划（自由探索类）资助项目(202303021221132), fundOrder=null, country=null), Fund(id=1241102754349896649, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, awardId=202304051001017, language=CN, fundingSource=山西省科技创新人才团队(202304051001017), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241102745139204548, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, xref=1., ext=[AuthorCompanyExt(id=1241102745147593157, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, companyId=1241102745139204548, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Management, Shanxi Medical University, Jinzhong, Shanxi 030600, China), AuthorCompanyExt(id=1241102745151787462, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, companyId=1241102745139204548, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.山西医科大学管理学院，山西 晋中 030600)]), AuthorCompany(id=1241102745265033680, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, xref=2., ext=[AuthorCompanyExt(id=1241102745269227985, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, companyId=1241102745265033680, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.临床决策研究大数据山西省重点实验室)]), AuthorCompany(id=1241102745374085591, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, xref=3., ext=[AuthorCompanyExt(id=1241102745382474201, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, companyId=1241102745374085591, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.中国人民解放军总医院第二医学中心血液科，国家老年疾病临床医学研究中心)])], figs=[ArticleFig(id=1241102751090922321, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=EN, label=Fig.1, caption=Diagram of TSMR and two-step MR, figureFileSmall=9RUMv/XyCy5hDliICRbx4w==, figureFileBig=iaFE9vU+rqDmNR8wttXl0w==, tableContent=null), ArticleFig(id=1241102751250305885, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=CN, label=图1, caption=双样本、两步法孟德尔随机化示意图, figureFileSmall=9RUMv/XyCy5hDliICRbx4w==, figureFileBig=iaFE9vU+rqDmNR8wttXl0w==, tableContent=null), ArticleFig(id=1241102752877695852, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=EN, label=Fig.2, caption=Causal relationship betweenliposomes and NSCLC, figureFileSmall=VNFFCux3vFWt3K3sGzlsvA==, figureFileBig=FUAAohrPma8fyjThMyVJ2Q==, tableContent=null), ArticleFig(id=1241102752990942067, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=CN, label=图2, caption=血浆脂质与非小细胞癌的因果关系, figureFileSmall=VNFFCux3vFWt3K3sGzlsvA==, figureFileBig=FUAAohrPma8fyjThMyVJ2Q==, tableContent=null), ArticleFig(id=1241102753099993977, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=EN, label=Fig.3, caption=Leave-one out, figureFileSmall=kBvLqkzYo59QCttnpMPXFg==, figureFileBig=bCQ2ES9mzoWeXvSnmuv6cg==, tableContent=null), ArticleFig(id=1241102753209045889, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=CN, label=图3, caption=留一法图

注：A为三酰甘油 (58:8)；B为磷脂酰胆碱 (14:0_18:2)。

, figureFileSmall=kBvLqkzYo59QCttnpMPXFg==, figureFileBig=bCQ2ES9mzoWeXvSnmuv6cg==, tableContent=null), ArticleFig(id=1241102753322292105, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=EN, label=Fig.4, caption=Causal relationship betweenliposomes and immune cells, figureFileSmall=r0dR3Ktu/Evr5K89iGqY5A==, figureFileBig=6kRMeHoCQbd6ie7PiJH//A==, tableContent=null), ArticleFig(id=1241102753410372497, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=CN, label=图4, caption=血浆脂质与免疫细胞的因果关系图, figureFileSmall=r0dR3Ktu/Evr5K89iGqY5A==, figureFileBig=6kRMeHoCQbd6ie7PiJH//A==, tableContent=null), ArticleFig(id=1241102753515230105, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=EN, label=Table 1, caption=

Sensitivity analysis results

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露结局Cochrane’s QMR-Egger截距MR-PRESSO
Q（IVW）Pegger_interceptPGlobal PDistort P
磷脂酰胆碱(O-18:2_16:0)NSCLC21.1010.5140.0190.1470.502NA
固醇酯 (27:1/20:4)NSCLC34.4560.263-0.0140.1290.236NA
磷脂酰胆碱(16:0_20:4)NSCLC22.5600.487-0.0070.5050.366NA
磷脂酰胆碱(18:0_20:4)NSCLC35.7670.096-0.0130.1500.150NA
三酰甘油(58:8)NSCLC40.4730.046-0.0020.9010.185NA
磷脂酰胆碱(14:0_18:2)NSCLC40.3930.0270.0160.3830.113NA
磷脂酰胆碱(O-18:1_20:4)NSCLC20.2770.441-0.0230.0640.264NA
), ArticleFig(id=1241102753687196577, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=CN, label=表1, caption=

敏感性分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露结局Cochrane’s QMR-Egger截距MR-PRESSO
Q（IVW）Pegger_interceptPGlobal PDistort P
磷脂酰胆碱(O-18:2_16:0)NSCLC21.1010.5140.0190.1470.502NA
固醇酯 (27:1/20:4)NSCLC34.4560.263-0.0140.1290.236NA
磷脂酰胆碱(16:0_20:4)NSCLC22.5600.487-0.0070.5050.366NA
磷脂酰胆碱(18:0_20:4)NSCLC35.7670.096-0.0130.1500.150NA
三酰甘油(58:8)NSCLC40.4730.046-0.0020.9010.185NA
磷脂酰胆碱(14:0_18:2)NSCLC40.3930.0270.0160.3830.113NA
磷脂酰胆碱(O-18:1_20:4)NSCLC20.2770.441-0.0230.0640.264NA
), ArticleFig(id=1241102753792054181, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=EN, label=Table 2, caption=

Results of reverse analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露结局方法POR(95%CI)
NSCLC磷脂酰胆碱 (O-18:2_16:0)IVW0.4120.931（0.785~1.105）
NSCLC固醇酯 (27:1/20:4)IVW0.2521.179（0.890~1.561）
NSCLC磷脂酰胆碱 (16:0_20:4)IVW0.2781.157（0.889~1.505）
NSCLC磷脂酰胆碱 (18:0_20:4)IVW0.2461.192（0.886~1.604）
NSCLC三酰甘油 (58:8)IVW0.9921.000（0.938~1.067）
NSCLC磷脂酰胆碱 (14:0_18:2)IVW0.7560.986（0.901~1.078）
NSCLC磷脂酰胆碱 (O-18:1_20:4)IVW0.1041.108（0.979~1.253）
), ArticleFig(id=1241102753871745964, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102741431439614, language=CN, label=表2, caption=

反向分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露结局方法POR(95%CI)
NSCLC磷脂酰胆碱 (O-18:2_16:0)IVW0.4120.931（0.785~1.105）
NSCLC固醇酯 (27:1/20:4)IVW0.2521.179（0.890~1.561）
NSCLC磷脂酰胆碱 (16:0_20:4)IVW0.2781.157（0.889~1.505）
NSCLC磷脂酰胆碱 (18:0_20:4)IVW0.2461.192（0.886~1.604）
NSCLC三酰甘油 (58:8)IVW0.9921.000（0.938~1.067）
NSCLC磷脂酰胆碱 (14:0_18:2)IVW0.7560.986（0.901~1.078）
NSCLC磷脂酰胆碱 (O-18:1_20:4)IVW0.1041.108（0.979~1.253）
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脂质体和免疫细胞与非小细胞肺癌因果关系的两步双样本孟德尔随机化研究
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侯雅琪 1, 2 , 龚万里 1, 2 , 李渊 1, 2 , 齐荣暄 1, 2 , 王洋 1, 2 , 卢学春 3 , 贺培凤 1, 2 , 于琦 1, 2
现代预防医学 | 流行病与统计方法 2024,51(14): 2528-2534
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现代预防医学 | 流行病与统计方法 2024, 51(14): 2528-2534
脂质体和免疫细胞与非小细胞肺癌因果关系的两步双样本孟德尔随机化研究
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侯雅琪1, 2, 龚万里1, 2, 李渊1, 2, 齐荣暄1, 2, 王洋1, 2, 卢学春3, 贺培凤1, 2, 于琦1, 2
作者信息
  • 1.山西医科大学管理学院，山西 晋中 030600
  • 2.临床决策研究大数据山西省重点实验室
  • 3.中国人民解放军总医院第二医学中心血液科，国家老年疾病临床医学研究中心

    • 侯雅琪（1999—）,女，硕士在读，研究方向：生物信息学

通讯作者:

于琦，E-mail：
A two-step and two-sample mendelian randomization study on the causal relationship between liposomes and immune cells with non-small cell lung cancer
Ya-qi HOU1, 2, Wan-li GONG1, 2, Yuan LI1, 2, Rong-xuan QI1, 2, Yang WANG1, 2, Xue-chun LU3, Pei-feng HE1, 2, Qi YU1, 2
Affiliations
  • School of Management, Shanxi Medical University, Jinzhong, Shanxi 030600, China
出版时间: 2024-07-25 doi: 10.20043/j.cnki.MPM.202403445
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摘要
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目的

本研究旨在使用双样本孟德尔随机化以及两步法分析来研究免疫细胞介导脂质体与非小细胞肺癌(NSCLC)之间的因果关系。

方法

本研究从GWAS Catalog中获取了血浆脂质的GWAS汇总数据作为研究的暴露数据，选用了731种免疫细胞的GWAS汇总数据作为潜在的中介变量以及FinnGen数据库第九版发布的NSCLC数据作为结局数据。采用逆方差加权法(IVW)进行了两步、双样本孟德尔随机化分析，以研究脂质对NSCLC的因果关系以及免疫细胞在脂质体和NSCLC关联之间的介导作用。加权中位数法、MR-Egger等方法进行补充，同时进行水平多效性和异质性的检验保证结果的稳定性。

结果

IVW方法确定了36种脂质体与NSCLC相关，且无反向因果关系。与NSCLC具有强相关性的免疫细胞共有47种。值得注意的是，三酰甘油(TG)(58:8)与NSCLC存在因果效应(OR=1.183,95%CI：1.061~1.319)，由CD8+ T细胞中效应记忆CD8+T细胞介导的中介效应为0.003(95%CI：-0.007~0.013)，占总效应的1.94%，由白细胞中CD8+CD8dim T细胞介导的中介效应为0.012(95%CI：-0.004~0.028)，占总效应的7.24%。

结论

该研究表明，脂质体和NSCLC之间存在因果关系，TG是NSCLC进展当中的危险因素，并且在此过程中CD8+ T细胞中效应记忆CD8+T细胞和白细胞中CD8+CD8dim T细胞发挥了介导作用。

脂质体  /  免疫细胞  /  非小细胞肺癌  /  孟德尔随机化  /  中介分析
Objective

To investigate the causal relationship between immune cell mediated liposomes and non-small cell lung cancer (NSCLC) using two-sample Mendelian randomization and two-step analysis.

Methods

Summary data of GWAS for plasma liposomes were obtained from the GWAS Catalog as exposure data. Summary data of GWAS for 731 types of immune cells were selected as potential mediators, and NSCLC data from the ninth release of the FinnGen database were used as outcome data. Inverse-variance weighted (IVW) was used for two-step. Two-sample Mendelian randomization analysis was used to investigate the causal relationship between liposomes and NSCLC and the mediating role of immune cells in the lipid-NSCLC association. Weighted median and MR-Egger methods were used as supplements, along with pleiotropy and heterogeneity tests to ensure result stability.

Results

The IVW method identified 36 liposomes associated with NSCLC, with no evidence of reverse causation. A total of 47 immune cell types were strongly associated with NSCLC. Notably, triglyceride (TG) (58:8) had a causal effect on NSCLC (OR=1.183, 95%CI: 1.061-1.319). The mediation effect mediated by Effector Memory CD8+ T cell %CD8+ T cell was 0.003 (95%CI: -0.007-0.013), accounting for 1.94% of the total effect, while the mediation effect mediated by CD8+ and CD8dim T cell %leukocyte was 0.012 (95%CI: -0.004-0.028), accounting for 7.24% of the total effect.

Conclusion

This study suggests a causal relationship between liposomes and NSCLC, identifying TG as a risk factor for NSCLC progression. Effector Memory CD8+ T cell %CD8+ T cell and CD8+ CD8dim T cell %leukocyte play a mediating role in this process.

Liposomes  /  Immune cells  /  Non-small cell lung cancer (NSCLC)  /  Mendelian randomization  /  Mediation analysis
侯雅琪, 龚万里, 李渊, 齐荣暄, 王洋, 卢学春, 贺培凤, 于琦. 脂质体和免疫细胞与非小细胞肺癌因果关系的两步双样本孟德尔随机化研究. 现代预防医学, 2024 , 51 (14) : 2528 -2534 . DOI: 10.20043/j.cnki.MPM.202403445
Ya-qi HOU, Wan-li GONG, Yuan LI, Rong-xuan QI, Yang WANG, Xue-chun LU, Pei-feng HE, Qi YU. A two-step and two-sample mendelian randomization study on the causal relationship between liposomes and immune cells with non-small cell lung cancer[J]. Modern Preventive Medicine, 2024 , 51 (14) : 2528 -2534 . DOI: 10.20043/j.cnki.MPM.202403445
正文
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肺癌是全球癌症死亡的主要原因，在大多数国家，其仍然是最致命的恶性肿瘤类型，也是最常诊断的癌症之一[1]。肺癌的两种主要类型是小细胞肺癌(Small Cell Lung Cancer,SCLC,15%)和非小细胞肺癌(Non-small Cell Lung Cancer,NSCLC,85%)[2]。NSCLC可进一步分为3种主要亚型：肺腺癌(Lung adenocarcinoma,LUAD)、鳞状癌和大细胞癌。靶向治疗和免疫治疗等多种治疗策略可供选择，但该病的总体预后仍然很差——5年生存率仅为 25%[3-4]。并且超过70%的NSCLC患者在初次诊断时已经存在远处转移的现象，5年总生存率较低(<10%)[5]。因此，亟需了解NSCLC的发生发展机制，开发更高效的治疗方法。
脂质作为生物膜的主要构成成分，广泛分布于体内各种体液之中。其在生理和病理过程中扮演着至关重要的角色，如细胞间信号传递、细胞增殖与凋亡，以及能量的储存与释放。其代谢的失衡与多种疾病密切相关，如糖尿病、各类癌症以及心血管疾病等。因此，脂质成为了疾病诊断和预后评估的潜在生物标志物[6]。研究报道NSCLC患者血清中不饱和脂肪酸和溶血磷脂酰乙醇胺的显著减少，这些发现为深入了解NSCLC的发病机制和寻找新的治疗靶点提供了重要线索[6-7]。
免疫治疗在肿瘤治疗领域展现出了巨大的前景。对NSCLC肿瘤的研究揭示了其内部免疫细胞的多样性，这些免疫细胞包括T细胞、B细胞、巨噬细胞、自然杀伤(NK)细胞和树突状细胞等[8]。进一步分析显示，NSCLC肿瘤中共有13种不同的免疫细胞类型，其中T细胞在肺癌的免疫应答中占据核心地位，占比约47%。在T细胞群体中，CD4 T细胞是最丰富的亚群，占据了约26%的比例，紧随其后的是CD8 T细胞，占比约为22%。这一发现调了深入研究 NSCLC 肿瘤微环境中免疫细胞的组成和分布对于理解疾病机制和开发有效的免疫治疗策略的重要性[9-10]。脂质体本身并不涉及免疫细胞的激活或抑制过程，而且其效能往往会受到复杂生物环境因素的制约。据相关报道，脂质体能够参与由B细胞和T细胞介导的特异性体液和细胞免疫系统的激活过程，显示出其在免疫调节中的重要作用。然而，血浆脂质是否能通过调节免疫系统来影响NSCLC的进展仍不得而知。
在流行病学中，孟德尔随机化 (Mendelian randomization,MR)是一种分析工具，用于探索病因推断并推断暴露与结果之间的关系。MR是使用遗传变异来评估观察数据的因果关系，同时最大限度地减少混杂和反向因果关系偏差。MR分析遵循以下三个假设：（1）工具变量(instrumental variable,IV)与暴露变量相关；（2）与混淆暴露-结果因素无关联；（3）IV仅通过暴露变量影响结果[11]。本研究旨在探讨血浆脂质对NSCLC的因果作用，并计算了免疫细胞特征介导的血浆脂质对NSCLC的影响比例，以评估血浆脂质是否可以通过调节免疫系统来影响NSCLC的进展。
1　材料与方法
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1.1　研究设计
（1）脂质体和NSCLC进行双样本孟德尔随机化分析(Two Sample MR,TSMR)，选择能够代表血浆脂质且无反向因果关系的遗传变异(Single Nucleotide Polymorphism,SNP)。（2）通过贝叶斯加权孟德尔随机化(Bayesian Weighted Mendelian Randomization,BWMR)进行验证。（3）用两步孟德尔随机化研究(two step Mendelian randomization,two step MR)筛选与NSCLC以及脂质体具有强相关性的免疫细胞作为潜在的介质，分别估计脂质对免疫细胞以及免疫细胞对NSCLC的因果效应，并估计免疫细胞在脂质与NSCLC因果关系中的介导作用。当前研究设计的摘要见图1。
1.2　数据来源
本研究使用人类血浆脂质组作为暴露因素，选择了GWAS Catalog(https://www.ebi.ac.uk/gwas/)的汇总数据，汇集了GeneRISK队列的7 174名芬兰个体的GWAS数据，涵盖了13个不同脂类类别，共计179种脂类的基因组关联研究。同样从GWAS Catalog中公开获取了免疫性状的汇总数据，这些数据来源于一项包含3 757名欧洲人的大规模基因组关联研究，特别选用了从GCST90001391(https://www.ebi.ac.uk/gwas/studies/GCST90001391)到GCST90002121(https://www.ebi.ac.uk/gwas/studies/GCST90002121)的系列数据，涵盖了共计731种免疫细胞表型[12]。
FinnGen数据库汇集了芬兰人口的基因组信息以及相关的健康数据，NSCLC数据则来源于FinnGen数据库第九版发布的数据(gs://finngen-public-data-r9/summary_stats/finngen_R9_C3_LUNG_NONSMALL_EXALLC.gz)。该GWAS包括292 308名受试者，其中病例组样本为4 901，控制组样本量为287 137。
1.3　工具变量的筛选
为了获得显著相关的SNP，本研究将全基因组显著性阈值设置为P<5e-8。由于符合要求的SNP位点较少，在阅读相关文献后，将阈值放宽为P<1e-5，通过关联性分析筛选出与暴露因素相关的SNP作为潜在的IV。其次，为了保证每个SNP的独立性，根据连锁不平衡(Linkage disequilibrium,LD)条件(R2=0.001,kb=10 000)[13]保留符合的SNP。从PhenoScanner数据库中剔除了与混杂因素相关的数据以优化遗传IV的准确性。随后，采用孟德尔随机化多效性残差和异常值(MR-PRESSO)模型中的异常值校正方法，进一步清理了IV中的异常值。同时，排除了所有具有回文结构的SNP，从而避免了等位基因对结果可能产生的干扰。最后，为了确保IV的效力，排除了F统计量小于10的弱IV。计算F统计量的具体计算公式为：，其中，β为等位基因效应值，SE为标准误。
1.4　孟德尔随机化的统计分析
1.4.1　孟德尔随机化统计方法
所有统计分析均使用R 4.3.1(https://www.r-project.org)进行。TSMR使用软件包“TwoSampleMR”进行，同时采用逆方差加权法(Inverse-variance Weighted，IVW)、MR Egger、加权中位数、简单模式和加权模式五种分析方法。在MR分析中，当所有IV均有效时，IVW法能提供较为准确的因果关联效应估计值，故主要采用IVW来确定暴露与结局之间的因果关系。P<0.05 被认为暴露与结局之间存在潜在关联。使用这种方法检测到的因果效应，应继续进行敏感性分析，以评估发现对水平多效性假设的稳健性[14]。采用two step MR来研究免疫细胞介导脂质体与NSCLC之间的因果关系。首先使用IVW方法计算脂质体对免疫细胞的因果效应(BetaX)，随后对免疫细胞到NSCLC的因果效应(BetaY)进行计算。利用系数积方法得出免疫细胞的中介效应(BetaXY)并计算其所占的比例，从而更全面地评估了免疫细胞在脂质体与NSCLC关联中的中介作用。中介效应的计算方式为：BetaXY=BetaX*BetaY。
在本研究当中，结果均以比值比(OR)及95％置信区间( 95％CI)表示。设定P<0.05作为判断潜在因果效应是否具备统计学意义的基准。为规避多重测试可能引入的误差，应用Bonferroni方法进行矫正，将P值虽超过Bonferroni矫正的显著性水平(0.05/n，n为总检验次数)但依旧低于0.05的关联视为提示因果关系的信号。
1.4.2　敏感性分析
在敏感性分析中，采用了三种方法以全面评估研究结果的稳健性：异质性检验、水平多效性检验以及留一法(leave-one out)。采用基于IVW和MR Egger方法的Cochran Q统计量评估异质性程度。若Q检验的P值小于0.05，则表明研究间存在异质性，即不同研究的结果并非完全一致，可能存在某种程度的变异或差异。当MR-Egger截距项具有统计学意义时，表明存在水平多效性。使用“MR-PRESSO”R包(https://github.com/rondolab/MR-PRESSO/)进行MR-PRESSO检验，以验证水平多效性的存在[15]。使用留一法分析依次消除每个SNP来确定单个SNP对因果关系的影响。
2　结果
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2.1　TSMR及BWMR分析结果
对179种脂质体进行聚类，筛选出896个独立的SNP。IVW分析结果显示，有36种脂质体与NSCLC存在潜在关联，其中磷脂酰胆碱(18:1_20:2)(Phosphatidylcholine,PC)符合Bonferroni矫正后的显著性阈值。同时对脂质体进行BWMR分析以验证是否仍然满足显著相关的条件。结合BWMR的分析，选取两次分析结果显著性均在前10的脂质体进行下一步研究，最终确定了7种脂质体与NSCLC存在潜在的因果关系(见图2)。IVW结果分析表明PC (O-18:2_16:0)、PC (14:0_18:2)与NSCLC呈现负相关性，其OR值分别为0.872、0.845，P值均小于0.05，其余五种血浆脂质与NSCLC呈正相关。其中三酰甘油(58:8)(Triacylglycerol,TG)最为显著(OR=1.183,P=0.002)。
MR-PRESSO分析结果显没有多效性。Cochrane Q检验显示TG (58:8)与PC(14:0_18:2)存在异质性，因此使用IVW进行随机效应分析。存在异质性的原因可能是由于不同的遗传背景、环境因素或存在一些未识别的混杂因素或未考虑到的变量。留一法分析表明未发现单个的SNP会对效应估计值产生较大的影响，表明因果关系具有一定的稳定性[16]。(敏感性分析结果见表1，留一法分析结果见图3)。
2.2　反向分析结果
在NSCLC和脂质体之间的MR分析中，共鉴定出44个SNP。IVW结果显示NSCLC和所选择的7种脂质体之间P值均大于0.05。在其他四种补充算法当中也得出相同的结论：作为暴露的NSCLC与作为结局的7种脂质体水平之间不存在因果关系(P>0.05)。
2.3　two step MR分析结果
对免疫细胞进行中介分析，探讨脂质体对NSCLC的影响是否受其介导。与NSCLC具有强相关性的免疫细胞共有47种，其中B淋巴细胞19种，T淋巴细胞11种，骨髓细胞4种，外周血淋巴细胞7种，树突状细胞2种，单核细胞4种。在此基础上，筛选出与脂质体具有因果关系的6种免疫细胞(见图4)。TG(58:8)与4种免疫细胞具有相关性，其中CD8+ T细胞中效应记忆CD8+ T细胞与白细胞中CD8+CD8dim T细胞没有显示多效性且所有方法方向一致，故采用TG(58:8)作为暴露，NSCLC作为结局，CD8+ T细胞中效应记忆CD8+ T细胞与白细胞中CD8+CD8dim T细胞作为潜在的中介进行接下来的分析。
TG(58:8)对NSCLC的总效应为0.168，反映了该脂质对NSCLC风险的总体影响程度。中介分析进一步揭示了其中的作用机制，效应记忆CD8+ T细胞介导的中介效应为0.003(95%CI:-0.007~0.013)，中介效应占比仅为1.94%，表明其虽具有介导作用，但在整个因果链中的贡献相对较小，而直接效应，即TG(58:8)对NSCLC的直接作用占据总效应的绝大部分，为16.4%。白细胞中CD8+CD8dim T细胞的中介效应为0.012(95%CI：-0.004~0.028)。占总效应的比例为7.24%。表明该免疫细胞在连接TG(58:8)与NSCLC风险之间的作用相对显著。中介效应占比计算公式：中介效应占比=中介效应/总效应。结果表明，CD8+ T细胞中效应记忆CD8+ T细胞与白细胞中CD8+CD8dim T细胞可能是因果效应的中介。
3　讨论
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基于MR分析结果，本研究揭示了欧洲人群TG水平与NSCLC之间存在因果关系。中介分析也强调了CD8+ T细胞中效应记忆CD8+ T细胞与白细胞中CD8+CD8dim T细胞这两种免疫细胞在TG和NSCLC因果关系中的中介作用。这可能为NSCLC的发生和发展机制提供新的视角，并为治疗提供新的干预靶点。
脂质是调节正常和疾病条件下生物过程的重要信号分子。在肺部，这些分子在各种生理和病理过程中具有突出的作用。例如，磷脂酰胆碱是肺表面活性剂的主要磷脂，而鞘脂在炎症和肺胎儿成熟过程中很重要[17]。Fiorenza等人通过深入研究揭示了血浆中TG水平的变化与癌症之间存在的紧密联系。与此同时，多项研究均表明p53相关肿瘤的发生与血脂谱的改变具有密切关系，这进一步凸显了脂质在癌症发展中的重要性。Park[18]利用纳流超高效液相色谱-串联质谱技术，对p53敲除小鼠的肝脏、肺和肾脏中的脂质进行了定量分析。研究发现，p53基因的缺失对肺组织的脂质成分产生了显著的影响。具体而言，磷脂酰胆碱、磷脂酰乙醇胺、鞘磷脂蛋白、二酰基甘油和三酰基甘油的水平显著降低(24%~44%，P<0.05)。这些结果不仅证明了脂质改变与p53缺失及肺癌发生之间的紧密联系，而且强调了脂质在肺癌发展中的关键作用。
Kim等人[19]的研究则进一步强调了TG对肺部的影响。他们发现，臭氧暴露与血清中TG的显著相关。这种暴露还会引发肺部的损伤和炎症反应，从而表明TG等脂质成分的增加可能对肺部产生直接的损害作用。此外，溶血磷脂酰甘油酰基转移酶(LPGAT1)在LUAD细胞增殖和凋亡过程中的作用也引起了研究者的关注。由于LPGAT1在调节TG生物合成中起关键作用，这进一步暗示了TG在LUAD发展中的潜在促进作用[20]。事实上，已有研究证明TG是鳞状癌和腺癌的重要生物标志物。
恶性胸腔积液(MPE)是一种常见于恶性肿瘤晚期患者的不良预后症状，其中肺癌，特别是NSCLC为其最常见的病因[21]。研究显示，MPE的CD8+T细胞中PD1、Tim-3、CD39的表达水平上升表明CD8+T细胞的效应功能在很大程度上受损[22]。此外，PD1上调已被证实会诱导CD8+T细胞的耗竭。而MPE中的主要分化阶段是效应记忆T细胞，效应记忆T细胞表达更多的PD1和 CD39。这表明，T细胞耗竭现象在NSCLC中也同样存在。同时，PD1也被用于鉴定浸润人类肿瘤（包括黑色素瘤和NSCLC）的T细胞的反应库[23]。此前有报道称，在LUAD患者的肿瘤浸润淋巴细胞中，穿孔素转录物下调。耗竭的CD8+Tem细胞在增殖、细胞因子产生和细胞毒性方面表现出损害。CD8+T细胞在防御肿瘤细胞中具有重要作用，其胞质溶胶含有颗粒酶和穿孔素，储存在细胞毒性颗粒内[24]。穿孔素会在肿瘤细胞的质膜上形成孔，允许颗粒酶进入细胞，然后激活半胱天冬酶活性，启动肿瘤细胞凋亡[25]。白细胞中CD8+CD8dim T细胞细胞作为中介因素，其比例的升高与NSCLC风险的升高之间存在负相关关系，与之前报道中CD8+T细胞对肿瘤的抑制作用相符合。
这项研究开创性地探讨了免疫细胞作为媒介，连接血浆脂质与NSCLC之间的因果途径。本研究的优势主要体现在几个方面。首先，充分利用了欧洲人群的大规模联盟数据，整合NSCLC、血浆脂质和免疫细胞的公开汇总级数据，大幅提升了数据的统计效能。其次，作为遗传变异的IV位于不同的染色体上，这有助于最小化潜在的基因-基因相互作用对估计值的影响。此外，还运用了中介MR方法，有效减少了因暴露因素、中介、结果和测量误差之间混杂而产生的偏差，获得了新的遗传证据，证实了TG对NSCLC的因果关系，并深入揭示了免疫细胞在这一过程中的关键作用。
然而，这项研究也存在一些局限性。首先，与暴露相关的SNP解释的变异比例相对较小，这在一定程度上限制了在识别遗传预测暴露与结果之间的弱相关性时的统计功效。尽管如此，利用超过10的F统计量值，尽力减少了使用弱工具可能带来的偏差。研究设定了阈值为P<5×10-8，但筛选后得到的SNP数量较少。考虑到后续分析的需求，将其放宽至P<1×10-5，会增加假阳性的概率。其次，尽管观察到了一定的异质性，但由于缺乏不同年龄、性别和健康状况的GWAS数据，无法进一步探索这些异质性资源的来源。最后，由于研究人群主要集中在欧洲血统的个体，这在一定程度上可能限制了研究结果在其他种族和民族群体中的普适性。
基金
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  • 山西省回国留学人员科研资助项目(HGKY2019057)
  • 山西省重点研发计划项目(202102130501003)
  • 山西省基础研究计划（自由探索类）资助项目(202303021221132)
  • 山西省科技创新人才团队(202304051001017)
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2024年第51卷第14期
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文章信息
doi: 10.20043/j.cnki.MPM.202403445
  • 接收时间：2024-03-25
  • 首发时间：2026-03-18
  • 出版时间：2024-07-25
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  • 收稿日期：2024-03-25
基金
山西省回国留学人员科研资助项目(HGKY2019057)
山西省重点研发计划项目(202102130501003)
山西省基础研究计划（自由探索类）资助项目(202303021221132)
山西省科技创新人才团队(202304051001017)
作者信息
    1.山西医科大学管理学院，山西 晋中 030600
    2.临床决策研究大数据山西省重点实验室
    3.中国人民解放军总医院第二医学中心血液科，国家老年疾病临床医学研究中心

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2种不同金属材料的力学参数
科
Family		 属数
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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