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Article(id=1241023854806626652, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202401266, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1705334400000, receivedDateStr=2024-01-16, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812744093, onlineDateStr=2026-03-18, pubDate=1737734400000, pubDateStr=2025-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812744093, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812744093, creator=13701087609, updateTime=1773812744093, updator=13701087609, issue=Issue{id=1241023847537897695, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='2', pageStart='193', pageEnd='384', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812742361, creator=13701087609, updateTime=1773812823817, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024189247845056, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024189247845057, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=355, endPage=361, ext={EN=ArticleExt(id=1241023855339303293, articleId=1241023854806626652, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Exploring the relationship between obstructive sleep apnea and atherosclerosis based on Mendelian randomization, columnId=1228016569138213037, journalTitle=Modern Preventive Medicine, columnName=Clinical Medicine and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the causal relationship between obstructive sleep apnea and atherosclerosis which is not clear through Mendelian randomization.

Methods

Genome-wide associations of different subtypes of obstructive sleep apnea and atherosclerosis were selected from the data published on the IEU Open GWAS (https://gwas.mrcieu.ac.uk/) website. Inverse variance weighting method (IVW), MR-Egger regression, simple model, weighted model and weighted median method were used to determine the causal correlation between them. A variety of sensitivity analysis and calculating F values were used to verify the accuracy of the results.

Results

Five single nucleotide polymorphisms (Single nucleotide polymorphism, SNP) strongly associated with obstructive sleep apnea were included in the study, and the F values were all greater than 10. The results of IVW method showed that coronary atherosclerosis (OR:1.321,95%CI:1.150-1.518,P=8.3×10-5) had significant statistical significance, while cerebral atherosclerosis(OR:0.331,95%CI:0.071-1.536,P=0.158) and peripheral atherosclerosis (OR:1.204,95%CI:0.962-1.508,P=0.106) had no statistical significance. The results of heterogeneity test, horizontal multiplicity analysis, sensitivity analysis and MR-PRESSO analysis made the causal relationship of Mendelian randomized analysis more reliable.

Conclusion

There is a causal correlation between obstructive sleep apnea and coronary atherosclerosis, and there is a positive correlation between obstructive sleep apnea and coronary atherosclerosis; there is no causal relationship between obstructive sleep apnea and cerebral atherosclerosis and peripheral atherosclerosis; reverse MR analysis found no causal correlation between selected atherosclerosis and obstructive sleep apnea.

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目的

本研究旨在通过孟德尔随机化探究阻塞性睡眠呼吸暂停和动脉粥样硬化的因果关系。

方法

在IEU Open GWAS（https://gwas.mrcieu.ac.uk/）网站所公开的数据中选取阻塞性睡眠呼吸暂停和动脉粥样硬化不同亚型的全基因组关联分析。通过逆方差加权法（inverse-variance weighted，IVW）、MR-Egger回归、简单模式(simple mode)、加权模型(weighted mode)和加权中位数法（weight median）来判定两者之间的因果关联，采用多种敏感性分析和计算F值对结果的准确性进行校验。

结果

研究纳入了5个与阻塞性睡眠呼吸暂停强相关的单核苷酸多态性（Single nucleotic polymorphism，SNP），F值均大于10。IVW法结果显示：冠状动脉粥样硬化（OR:1.321，95%CI:1.150~1.518，P=8.3×10-5），具有显著统计学意义；脑动脉粥样硬化（OR:0.331，95%CI:0.071~1.536，P=0.158）；外周动脉粥样硬化（OR:1.204，95%CI:0.962~1.508，P=0.106），均P>0.05不存在统计学意义。异质性检验、水平多效性分析、敏感性分析和MR-PRESSO分析结果使孟德尔随机化分析的因果关系更加可靠。

结论

阻塞性睡眠呼吸暂停与冠状动脉粥样硬化之间存在因果关联，且呈正相关；阻塞性睡眠呼吸暂停与脑动脉粥样硬化和外周动脉粥样硬化之间不存在因果关系；反向MR分析未发现选取的动脉粥样硬化与阻塞性睡眠呼吸暂停存在因果关联。

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于睿，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=2AKEZ42H+mnCJT4r4jwLww==, magXml=bHA31oYeODNnZGAhnY6AWg==, pdfUrl=null, pdf=HTKTD4frV/1K/H9Cu4iXMA==, pdfFileSize=1076567, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=7PtZV9qlQsUuYlX1SNG+9w==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=1LwHxqf7hqWdQzL6RU+6oQ==, mapNumber=null, authorCompany=null, fund=null, authors=

马海钧（2000—），男，硕士在读，研究方向：中西医结合防治心血管疾病

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马海钧（2000—），男，硕士在读，研究方向：中西医结合防治心血管疾病

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马海钧（2000—），男，硕士在读，研究方向：中西医结合防治心血管疾病

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ArticleFig(id=1241023868186456172, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854806626652, language=EN, label=Table 1, caption=

Basic Information of Sample

, figureFileSmall=null, figureFileBig=null, tableContent=
疾病GWAS ID年份人口样本量病例数对照数SNPs数量
阻塞性睡眠呼吸暂停finn-b-G6_SLEEPAPNO2021欧洲人217 95516 761201 19416 380 465
冠状动脉粥样硬化finn-b-I9_CORATHER2021欧洲人211 20323 363187 84016 380 402
脑动脉粥样硬化finn-b-I9_CERATHER2021欧洲人203 172104203 06816 380 447
外周动脉粥样硬化finn-b-DM_PERIPHATHERO2021欧洲人168 8326 631162 20116 380 247
), ArticleFig(id=1241023868299702390, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854806626652, language=CN, label=表1, caption=

样本基本信息

, figureFileSmall=null, figureFileBig=null, tableContent=
疾病GWAS ID年份人口样本量病例数对照数SNPs数量
阻塞性睡眠呼吸暂停finn-b-G6_SLEEPAPNO2021欧洲人217 95516 761201 19416 380 465
冠状动脉粥样硬化finn-b-I9_CORATHER2021欧洲人211 20323 363187 84016 380 402
脑动脉粥样硬化finn-b-I9_CERATHER2021欧洲人203 172104203 06816 380 447
外周动脉粥样硬化finn-b-DM_PERIPHATHERO2021欧洲人168 8326 631162 20116 380 247
), ArticleFig(id=1241023868408754303, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854806626652, language=EN, label=Table 2, caption=

Specific Information of SNPs

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SNPeffect_allele. exposureother_allele. exposurebeta. exposureSe.exposureeaf.exposurePF
rs10507084TC0.1090.0160.1792.797×10-11151.547
rs10928560TC-0.0880.0160.1952.802×10-8105.710
rs142006783CT0.1780.0330.0384.813×10-8100.985
rs4837016AG-0.0710.0130.4661.527×10-8108.406
rs9937053AG0.1020.0130.4304.319×10-16223.424
), ArticleFig(id=1241023868572332168, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854806626652, language=CN, label=表2, caption=

SNPs具体信息

, figureFileSmall=null, figureFileBig=null, tableContent=
SNPeffect_allele. exposureother_allele. exposurebeta. exposureSe.exposureeaf.exposurePF
rs10507084TC0.1090.0160.1792.797×10-11151.547
rs10928560TC-0.0880.0160.1952.802×10-8105.710
rs142006783CT0.1780.0330.0384.813×10-8100.985
rs4837016AG-0.0710.0130.4661.527×10-8108.406
rs9937053AG0.1020.0130.4304.319×10-16223.424
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基于孟德尔随机化探索阻塞性睡眠呼吸暂停和动脉粥样硬化的关系
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马海钧 1 , 倪萍 1 , 段盈竹 1 , 梁健 1 , 张欢 1 , 于游 2 , 康唯佳 1 , 于睿 1
现代预防医学 | 临床与预防 2025,52(2): 355-361
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现代预防医学 | 临床与预防 2025, 52(2): 355-361
基于孟德尔随机化探索阻塞性睡眠呼吸暂停和动脉粥样硬化的关系
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马海钧1, 倪萍1, 段盈竹1, 梁健1, 张欢1, 于游2, 康唯佳1, 于睿1
作者信息
  • 1．辽宁中医药大学，辽宁　沈阳　110847
  • 2．辽宁中医药大学附属第二医院

    • 马海钧（2000—），男，硕士在读，研究方向：中西医结合防治心血管疾病

通讯作者:

于睿，E-mail：
Exploring the relationship between obstructive sleep apnea and atherosclerosis based on Mendelian randomization
Hai-jun MA1, Ping NI1, Ying-zhu DUAN1, Jian LIANG1, Huan ZHANG1, You YU2, Wei-jia KANG1, Rui YU1
Affiliations
  • Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning 110847, China
出版时间: 2025-01-25 doi: 10.20043/j.cnki.MPM.202401266
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摘要
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目的

本研究旨在通过孟德尔随机化探究阻塞性睡眠呼吸暂停和动脉粥样硬化的因果关系。

方法

在IEU Open GWAS（https://gwas.mrcieu.ac.uk/）网站所公开的数据中选取阻塞性睡眠呼吸暂停和动脉粥样硬化不同亚型的全基因组关联分析。通过逆方差加权法（inverse-variance weighted，IVW）、MR-Egger回归、简单模式(simple mode)、加权模型(weighted mode)和加权中位数法（weight median）来判定两者之间的因果关联，采用多种敏感性分析和计算F值对结果的准确性进行校验。

结果

研究纳入了5个与阻塞性睡眠呼吸暂停强相关的单核苷酸多态性（Single nucleotic polymorphism，SNP），F值均大于10。IVW法结果显示：冠状动脉粥样硬化（OR:1.321，95%CI:1.150~1.518，P=8.3×10-5），具有显著统计学意义；脑动脉粥样硬化（OR:0.331，95%CI:0.071~1.536，P=0.158）；外周动脉粥样硬化（OR:1.204，95%CI:0.962~1.508，P=0.106），均P>0.05不存在统计学意义。异质性检验、水平多效性分析、敏感性分析和MR-PRESSO分析结果使孟德尔随机化分析的因果关系更加可靠。

结论

阻塞性睡眠呼吸暂停与冠状动脉粥样硬化之间存在因果关联，且呈正相关；阻塞性睡眠呼吸暂停与脑动脉粥样硬化和外周动脉粥样硬化之间不存在因果关系；反向MR分析未发现选取的动脉粥样硬化与阻塞性睡眠呼吸暂停存在因果关联。

孟德尔随机化  /  阻塞性睡眠呼吸暂停  /  动脉粥样硬化  /  冠状动脉粥样硬化
Objective

To explore the causal relationship between obstructive sleep apnea and atherosclerosis which is not clear through Mendelian randomization.

Methods

Genome-wide associations of different subtypes of obstructive sleep apnea and atherosclerosis were selected from the data published on the IEU Open GWAS (https://gwas.mrcieu.ac.uk/) website. Inverse variance weighting method (IVW), MR-Egger regression, simple model, weighted model and weighted median method were used to determine the causal correlation between them. A variety of sensitivity analysis and calculating F values were used to verify the accuracy of the results.

Results

Five single nucleotide polymorphisms (Single nucleotide polymorphism, SNP) strongly associated with obstructive sleep apnea were included in the study, and the F values were all greater than 10. The results of IVW method showed that coronary atherosclerosis (OR:1.321,95%CI:1.150-1.518,P=8.3×10-5) had significant statistical significance, while cerebral atherosclerosis(OR:0.331,95%CI:0.071-1.536,P=0.158) and peripheral atherosclerosis (OR:1.204,95%CI:0.962-1.508,P=0.106) had no statistical significance. The results of heterogeneity test, horizontal multiplicity analysis, sensitivity analysis and MR-PRESSO analysis made the causal relationship of Mendelian randomized analysis more reliable.

Conclusion

There is a causal correlation between obstructive sleep apnea and coronary atherosclerosis, and there is a positive correlation between obstructive sleep apnea and coronary atherosclerosis; there is no causal relationship between obstructive sleep apnea and cerebral atherosclerosis and peripheral atherosclerosis; reverse MR analysis found no causal correlation between selected atherosclerosis and obstructive sleep apnea.

Mendelian randomization  /  Obstructive sleep apnea  /  Atherosclerosis  /  Coronary atherosclerosis
马海钧, 倪萍, 段盈竹, 梁健, 张欢, 于游, 康唯佳, 于睿. 基于孟德尔随机化探索阻塞性睡眠呼吸暂停和动脉粥样硬化的关系. 现代预防医学, 2025 , 52 (2) : 355 -361 . DOI: 10.20043/j.cnki.MPM.202401266
Hai-jun MA, Ping NI, Ying-zhu DUAN, Jian LIANG, Huan ZHANG, You YU, Wei-jia KANG, Rui YU. Exploring the relationship between obstructive sleep apnea and atherosclerosis based on Mendelian randomization[J]. Modern Preventive Medicine, 2025 , 52 (2) : 355 -361 . DOI: 10.20043/j.cnki.MPM.202401266
正文
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动脉粥样硬化（Atherosclerosis，AS）是一类涉及到大、中动脉的慢性进行性的血管炎性病变，主要在血管内壁下发生脂质沉积，形成纤维脂肪病变，降低动脉弹性使动脉管腔狭窄[1]。AS是许多缺血性心血管疾病的病理基础，在世界范围内很多不良心血管事件的发生和病死率均与AS形成有关[2]。根据《中国心血管健康与疾病报告2022》显示中国心血管病（cardiovascular diseases, CVD）患病率处于持续上升阶段。推算CVD现患人数3.3亿，其中冠状动脉粥样硬化性心脏病1139万，且中国城乡居民冠心病死亡率呈上升趋势，造成了较大的社会和经济负担[3]，防治AS至关重要。目前AS形成和发展的危险因素很多，例如吸烟、衰老、肥胖、高血压、糖尿病等。聚焦于危险因素对于AS变化的影响，可以为AS的防治和机制研究提供一定的理论支持。
阻塞性睡眠呼吸暂停（Obstructive sleep apnea，OSA）是一种非常普遍的睡眠呼吸障碍，指在睡眠过程中上气道反复发生完全或部分阻塞而引起的打鼾、自主神经功能紊乱、睡眠片段化和间接性缺氧[4]。一项国外报道称大约10%~20%的中老年人正在受OSA困扰且OSA患病率逐年提升[5]，我国的OSA患者数量为世界第一位。OSA是一种重要的公共卫生问题，能够引起并加重循环系统、神经系统、代谢障碍等疾病，尤其与心血管疾病患者的发病率和死亡率增加有关[6]。
在临床中观察到一部分动脉粥样硬化患者同时合并了阻塞性睡眠呼吸暂停，经文献检索与分析后发现两者之间的观察性研究较少，且存在样本量小和选择偏倚等问题，结果受到影响并不可靠[7]。观察性流行病学研究容易出现混淆、反向因果关系和各种偏倚，导致暴露对于结局的因果关系并不十分可靠[8]。孟德尔随机化（Mendelian randomization，MR）是一种利用与暴露密切相关的遗传变异来产生更可靠的证据的方法[9]。它使用单核苷酸多态性（Single nucleotic polymorphism，SNP）作为工具变量（IV），用来推断暴露和结局之间的因果关系，能够最小化混杂因素和反向因果关系的偏差[10]，是一种天然的随机对照试验，比传统的观察性研究更具优势。MR还提供了多种敏感性分析的检验方法，对结果进行多重验证校对。本研究旨在利用孟德尔随机化探讨阻塞性睡眠呼吸暂停和动脉粥样硬化是否存在因果关系，为动脉粥样硬化发病机制研究提供新的可靠的生物信息学证据，为临床疾病诊疗提供新思路。
1　材料和方法
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1.1　研究设计
MR研究须满足三个核心假设：(1)工具变量必须与暴露因素OSA强相关。(2)工具变量不能和任何潜在的混杂因素相关。(3)工具变量只能通过唯一途径暴露因素OSA来影响结局AS，具体关联见图1。本研究采用两样本孟德尔随机化方法探讨阻塞性睡眠呼吸暂停和动脉粥样硬化的因果关系。暴露因素为OSA。结局我们选取了AS的不同亚型，主要包括冠状动脉粥样硬化（Coronary atherosclerosis，CoAS）、脑动脉粥样硬化（Cerebral atherosclerosis，CeAS）和外周动脉粥样硬化（Peripheral atherosclerosis，PAS）。IV的筛选的参数设置为：选择与OSA相关的且显著性P<5×10-8的SNPs，设置连锁不平衡参数（r2=0.001），物理遗传距离（kb=10 000）。通过Phenoscanner数据库查询，剔除不满足核心假设（2）的SNPs。F检验挑选F>10的工具变量，以排除弱工具变量偏倚[11]。F值计算公式如下：
其中N表示全基因组关联分析（Genome-Wide Association Studies，GWAS）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。
其中MAF表示等位基因的频率（Minor allele frequency）， β表示SNP对暴露因素的效应值。
1.2　数据来源
研究所用数据集均从公开发表的网站IEU Open GWAS（https://gwas.mrcieu.ac.uk/）上面获取。使用FinnGen Study最近发表的GWAS中与OSA相关的已发表遗传变异[12]作为暴露变量。该GWAS包括217 955人，其中16 761名OSA患者使用芬兰全国卫生登记处确定。OSA是根据国际疾病分类第十次修订版（ICD-10）和第九次修订版（ICD-9）代码（ICD-10：G47.3，ICD-9：3472A）诊断的。结局变量AS相关的数据也从FinnGen数据库相关的研究中获取。包括三种不同亚型的AS：CoAS汇总数据样本量为211 203人，其中病例数23 363人，对照数187 840人。CeAS的样本量为203 172人，病例数104，对照数203 068人。PAS的样本量为168 832人，病例数6 631人，对照数162 201人。本研究暴露和结局均采用FinnGen数据库，为了保证研究结果的严谨性，查询数据库（https://risteys.finregistry.fi/）检索finn-b-G6_SLEEPAPNO数据集的全部信息及与其他终点事件的关系，并计算样本重叠率，偏倚大小及1类错误的百分比。所用数据集的GWAS ID及简要信息见表1。
1.3　研究方法
1.3.1　孟德尔随机化分析
本研究拟采用五种孟德尔随机化方法进行OSA和不同亚型AS之间的因果判定，包括逆方差加权法（inverse-variance weighted，IVW）、MR-Egger回归、简单模式(simple mode)、加权模型(weighted mode)和加权中位数法（weight median）。研究将逆方差加权法作为主分析方法，用来判定暴露和结局之间的因果关联[12]，IVW法特点是利用结局方差的倒数作为权重来进行拟合同时不需要考虑截距项是否为0，存在的偏倚相对最小[12-13]。其他四种方法作为IVW法的补充证据。当IVW法P<0.05时，差异具有显著统计学意义，本研究认为暴露和结局之间存在因果关系。当OR>1时，认定暴露和结局之间呈正相关，暴露是结局的危险因素。
1.3.2　异质性检验、敏感性分析、水平多效性分析
异质性检验主要用于检验工具变量之间是否存在较大差异。使用Cochran Q检验来判断IVW模型和MR-Egger回归模型的异质性。当P<0.05时，存在异质性，会对孟德尔随机化结果造成一定影响。敏感性分析使用留一法（Leave-one-out）检测。留一法是逐个剔除SNP后发现是否有非特异性的SNP影响主效应，识别离群值。使用Egger-intercept法作为检测基因水平多效性的主要方法，为了检验遗传变异是否通过核心假设3以外的途径影响结局。当P<0.05时，代表存在水平多效性。
1.3.3　MR-PRESSO分析
使用MR-PRESSO分析进行全局的多效性残差和异质性分析，评估离群值对于暴露和结局之间关联的影响并且校正剔除离群值。
1.3.4　反向MR分析
为了使研究更加全面，本文还探讨了AS是否与OSA有因果关联，进行反向MR分析。采用上述分析方法和多种敏感性分析，暴露因素选用三种不同部位的AS，以OSA作为结局进行评估。
工具变量的选择和孟德尔随机化分析方法，使用的是R 4.2.2版本以及TwoSample MR和MRPRESSO软件包。
2　结果
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2.1　工具变量的选择及F值检验
本次从数据集finn-b-G6_SLEEPAPNO筛选到与暴露OSA强相关的工具变量共有5个。经查询5个SNPs与已知的混杂因素不具有相关性。F统计量的范围100.985 5~223.423 7，均大于10，不存在弱工具变量。分别是rs10507084、rs10928560、rs142006783、rs4837016和rs9937053全部纳入。SNPs具体信息见下方表2。
2.2　孟德尔随机化分析结果
本研究使用五种MR方法探究OSA与AS不同亚型的因果关系，其中OSA与CoAS存在因果关系，与CeAS和PAS不存在因果关联，见森林图2，IVW法的结果作为因果关联的主要判定依据。IVW法结果表示：CeAS（OR:0.331，95%CI:0.071~ 1.536，P= 0.158）；PAS（OR:1.204，95%CI:0.962~ 1.508，P=0.106），均P>0.05不存在统计学意义。CoAS（OR:1.321，95%CI:1.150~1.518，P=8.3×10-5），具有显著统计学意义，其他四种分析方法结果为：MR-Egger法（OR:1.294，95%CI:0.722~2.318，P= 0.45）；Simple mode法（OR,1.274, 95%CI:1.028~1.580,P= 0.101）；Weighted median法（OR:1.309，95%CI:1.103~1.554，P= 0.002）；Weighted mode法（OR:1.288，95%CI:1.041~1.592，P= 0.08），四种分析方法总体效应方向与IVW法分析性结果效应方向一致，可视化见散点图3。结果表明OSA与CoAS呈正相关，OSA是CoAS的风险因素。为了使阳性结果更具严谨性，研究对样本重叠造成的偏倚和1类错误的百分比进行了计算。结果显示CoAS和OSA的样本重叠率为9.04%，样本重叠带来的偏倚小于0.001，1类错误的百分比为0.05。有研究显示使用小于10%的样本重叠率的数据进行亚群分析，可以保留全样本亚群分析的90%的统计功效[14]。故本研究结果真实准确，不受样本重叠的影响。
2.3　异质性检验、敏感性分析、水平多效性分析结果
根据MR分析结果，接下来对OSA和CoAS的因果关联进行检验。基于异质性结果，IVW法的Cochran Q检验值=0.642，P=0.887，MR-Egger法的Cochran Q检验值=0.647，P=0.958，均无统计学意义，表明结果未受到异质性的影响。敏感性分析采用“Leave-one-out”法。发现逐个剔除SNP后，所得结果均P<0.05，表明不存在会对因果关系估计结果产生影响的非特异性SNP，可视化结果见图4 “Leave-one-out”法结果森林图。水平多效性分析结果显示使用Egger-intercept法得出P=0.947, Egger截距与0无统计学差异，表明水平多效性不会对因果关系结果造成偏倚。以上三种敏感性分析均证明OSA是CoAS的风险因素这一结果更加稳健可靠。
2.4　MR-PRESSO分析结果
最后对OSA和CoAS因果关系进行MR-PRESSO分析，结果P=0.082，全局分析结果一致，不存在离群值变量。充分肯定了暴露因素OSA与结局CoAS之间的关联是严谨可靠的。
2.5　反向MR分析结果
利用上述方法，筛选得到与暴露CoAS强相关SNPs共31个，6个与PAS相关的SNPs，未筛选到与CeAS相关的SNPs。根据反向MR随机化结果显示CoAS和PAS均不与OSA构成因果关系，具体结果如图5所示。
3　讨论
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本研究前期经过严格筛选共纳入5个与OSA相关的SNPs均满足三大核心假设，且F>10，不存在弱工具变量偏倚，不会对MR估计结果造成影响。MR分析结果显示，OSA只与CoAS构成因果关系，能增加CoAS风险，OSA患者患有CoAS的风险跟正常人相比会提高约32%。本研究MR分析结果，为临床上OSA患者同时合并CoAS提供了医学证据，可以作为OSA与CoAS之间基础机制研究的导向。要深入探索两者之间的机制，为临床干预提供新思路新靶点。
研究证据表明，OSA患者发生CoAS的风险明显升高，是冠心病的独立危险因素[15]。Turmel和Tan等人[16-17]的两项研究发现OSA与CoAS斑块体积存在关联，且呈正相关；与无或轻OSA患者相比，中至重度OSA患者冠状动脉内动脉粥样硬化体积更大。现如今发现在AS斑块中高度表达的内皮细胞特异性分子1（Endothelial cell specific molecules-1，ESM-1）已经被认为是内皮细胞障碍的新型标志物[18-19]。Sun等人[20]的研究发现，ESM-1可以作为OSA患者是否患有CoAS的标志物，他们的结果表示，OSA可能通过影响内皮细胞使功能紊乱来介导CoAS的发生。
OSA还可以影响多种机制导致CoAS的发生。OSA的形成包括结构和功能两方面的改变。OSA患者的咽腔均存在一定程度的狭窄；睡眠时，上气道肌肉及其调节神经受损发为OSA。OSA的特征是睡眠期间上气道反复阻塞，导致间歇性缺氧（IH）。IH现在被认为是导致OSA相关合并症发病机制的潜在重要因素[21]。OSA通常被认为是一种与肥胖密切相关的疾病，大多数病态肥胖患者患有OSA[22]。肥胖患者主要增加上呼吸道周围软组织，脂肪组织增加会导致呼吸道狭窄，呼吸功能障碍进一步加重，机体出现严重的IH，可以诱发氧化应激产生活性氧（ROS）。ROS通过引发炎症级联反应促进生成促炎因子（如TNF-α、IL-6、CRP等）和粘附分子，丰富的促炎细胞因子和炎症反应来参与CoAS过程[23]。OSA可以改变患者的代谢状态，显著增加代谢综合征的发生率，IH会诱导葡萄糖代谢异常，糖脂代谢紊乱会加重冠心病患者CoAS程度[24]。Song等人[25]在实验研究中发现选择性抑制内皮细胞NF-κB信号传导可以减轻小鼠由于IH诱导的动脉粥样硬化。另外，Imamura等[26]发现IH可以激活巨噬细胞中IKK-β—NF-κB途径转化成泡沫细胞，泡沫细胞的形成对于CoAS有着重要的作用。循环中的外泌体水平还可能被IH改变，促进内皮细胞的通透性和功能障碍使AS形成[27]。研究发现IH诱导的内皮细胞功能障碍中血清外泌体miR-210水平显著增高，并且miR-210与AS紧密相关[28-29]。由此可见OSA可以通过介导氧化应激、炎症反应、血管内皮细胞功能障碍和代谢紊乱等多途径影响CoAS。
本研究结果所示OSA仅仅与CoAS存在因果关系，原因可能在于不同部位动脉解剖结构不同且需氧量和耗氧量也不同。既往有研究发现OSA与CeAS和PAS存在相关性[30-31]，与本研究结果相悖。推测可能由于相关报道的临床研究规模较小、数量较少和样本量偏小，所得结果存在一定的偏倚，缺乏严谨可靠性。
后续还可以进一步拓展分析，将血脂、血糖水平、炎症因子作为中介因素进行中介MR，以便于更好的对OSA患者病情分级管理。
本研究的优点和创新性：我们的研究首次使用孟德尔随机化方法探讨OSA和全身多部位AS之间的因果关系并证明了OSA是CoAS的风险因素。研究的思路和结果是对目前已有研究两者关联的一个重要补充。在临床预防、诊疗疾病中具有一定的价值。OAS患者要注意预防CoAS的发生，降低心血管事件的发生和死亡率，注意控制CoAS发生的危险因素，起到未病先防的作用。
本研究还存在一定的局限性：（1）使用的数据集纳入对象均为欧洲血统，研究结果可能不具有普适性。（2）研究只讨论了OSA与全身3种部位的动脉粥样硬化，公开网站数据不全如缺少主动脉、颈动脉粥样硬化数据集。（3）数据集所包含的SNPs较少不能使用，使得研究所得阴性结果缺乏严谨性。
综上所述本研究利用孟德尔随机化法探索了阻塞性睡眠呼吸暂停与动脉粥样硬化的因果关系。证明了阻塞性睡眠呼吸暂停与冠状动脉粥样硬化存在因果关系且呈正相关；但是尚未找到证据说明与脑动脉粥样硬化和外周动脉粥样硬化之间的因果关系。反向MR分析表明AS和OSA之间不存在因果效应。本结论还需要接受大量的临床观察研究和动物实验研究来进一步检验。临床医师应当对OSA患者进行全面对症治疗，改变生活方式提早预防或延缓CoAS的发生发展。CoAS患者也应尽早进行OSA筛查，一旦出现OSA要及早干预治疗以防止出现或加重CoAS程，防止患者病情加重，提高患者生存质量。
基金
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  • 国家自然科学基金面上项目(82274494)
  • 辽宁省科学技术计划项目(2023JH2/101600030)
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2025年第52卷第2期
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doi: 10.20043/j.cnki.MPM.202401266
  • 接收时间：2024-01-16
  • 首发时间：2026-03-18
  • 出版时间：2025-01-25
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  • 收稿日期：2024-01-16
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国家自然科学基金面上项目(82274494)
辽宁省科学技术计划项目(2023JH2/101600030)
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    1．辽宁中医药大学，辽宁　沈阳　110847
    2．辽宁中医药大学附属第二医院

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