Article(id=1324070911091016494, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202506272, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1750089600000, receivedDateStr=2025-06-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793612705251, onlineDateStr=2026-11-02, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793612705251, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793612705251, creator=13701087609, updateTime=1793612705251, updator=13701087609, issue=Issue{id=1324070892967428793, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='24', pageStart='4417', pageEnd='4608', issueExtLink='null', onlineDate='null', pubDate='1766592000000', pubDateStr='2025-12-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793612700931, creator='13701087609', updateTime=1793612772549, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324071193430602023, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324071193430602024, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4431, endPage=4435, ext={EN=ArticleExt(id=1324070912848429872, articleId=1324070911091016494, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=The association of frailty with heart failure risk and the mediating effect of metabolomics, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the association between frailty and heart failure onset, and to identify the metabolomic features mediating the relationship between frailty and heart failure.

Methods

Based on the UK Biobank (UKB), 255 160 participants who underwent baseline testing for 168 metabolites were included. The Fried frailty phenotype assessment data were obtained and divided into three groups: non-frailty (0), pre-frailty (1-2), and frailty (≥3). The Cox proportional hazards model was used to analyze the relationship between frailty and the risk of heart failure. Additionally, a mediation analysis was conducted on metabolites to assess the mediating role of metabolic markers in the relationship between frailty and heart failure.

Results

Compared with non-frail participants, participants in the pre-frailty and frailty states had an increased risk of heart failure, with hazard ratios ( HR) of 1.441 (95% CI: 1.374–1.55) and 2.544 (95% CI: 2.323–2.785), respectively. Mediation analysis revealed that small high-density lipoprotein-related metabolites and low-density lipoprotein components played an important mediating role in the relationship between frailty and heart failure, with corresponding mediation proportions of 3.8%–5.5%.

Conclusion

Frailty is associated with an increased risk of heart failure, and plasma metabolites characterised by small high-density lipoproteins and low-density lipoproteins may be key biomarkers mediating the association between frailty and heart failure.

, authors=Yong-hua YE, Huan XU, Pan CHENG, Xue-wei TANG, Huang-yi YANG, Wei LIAO, Ju-ying ZHANG, Xing ZHAO, authorsList=Yong-hua YE, Huan XU, Pan CHENG, Xue-wei TANG, Huang-yi YANG, Wei LIAO, Ju-ying ZHANG, Xing ZHAO, authorCompany=null, correspAuthors=Ju-ying ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1324070914744255297, articleId=1324070911091016494, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=衰弱对心力衰竭风险的影响和代谢组学的中介效应分析, columnId=1228016567632462653, journalTitle=现代预防医学, columnName=流行病与统计方法, runingTitle=null, highlight=null, articleAbstract=
目的

探究衰弱与心衰发病的关联,同时确定介导衰弱和心衰之间关系的代谢组学特征。

方法

基于英国生物银行(UK Biobank, UKB),纳入255 160名基线检测了168种代谢物的参与者。获取Fried衰弱表型评估数据,分为非衰弱(0)、衰弱前期(1~2)和衰弱(≥3)三组,Cox比例风险模型分析衰弱与心衰风险之间的关系。同时,对代谢物进行中介分析,评估代谢标志物在衰弱与心衰关系间的中介作用。

结果

与非衰弱参与者相比,衰弱前期和衰弱状态参与者的心力衰竭风险增加,风险比(Hazard Ratio, HR)分别为1.441(95% CI:1.374~1.55)和2.544(95% CI:2.323~2.785)。中介分析显示,小的高密度脂蛋白相关代谢物和低密度脂蛋白组分在衰弱与心衰关系中起到重要的介导作用,相应的中介比例为3.8%~5.5%。

结论

衰弱状态与心衰风险增加有关,以小的高密度脂蛋白和低密度脂蛋白为特征的血浆代谢物可能是介导衰弱与心衰关联的关键标志物。

, authors=叶泳华, 许欢, 程盼, 唐雪薇, 杨黄毅, 廖伟, 张菊英, 赵星, authorsList=叶泳华, 许欢, 程盼, 唐雪薇, 杨黄毅, 廖伟, 张菊英, 赵星, authorCompany=null, correspAuthors=张菊英, authorNote=

叶泳华(2000—),男,硕士在读,研究方向:流行病与卫生统计学

, correspAuthorsNote=
张菊英,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=9DUtFVfq7VH3h+OffR0unA==, magXml=RwLwl5DA7x6f1GIfE5z8Wg==, pdfUrl=null, pdf=H8ro9q0x5BlVB7r7TA33Lw==, pdfFileSize=813863, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=oPqkTi0YgVZtlA3qwYLnnA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=56HadOzfhKA+fHfQhVUcIw==, mapNumber=null, fund=null)}, authors=[Author(id=1324070915163685702, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070911091016494, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1324070915260154696, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070911091016494, authorId=1324070915163685702, language=EN, stringName=Yong-hua YE, firstName=Yong-hua, middleName=null, lastName=YE, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Departmentof Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1324070915339846473, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070911091016494, authorId=1324070915163685702, language=CN, stringName=叶泳华, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=四川大学华西公共卫生学院/华西第四医院流行病与卫生统计学系,四川 成都 610041, bio={"content":"

叶泳华(2000—),男,硕士在读,研究方向:流行病与卫生统计学

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Baseline characteristics of study participants

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基本特征总人数(n=255 160)心衰
不发病(n=247 228)发病(n=7 932)
年龄(岁,)56.5±8.156.3±8.162.2±6.1
性别[n(%)]
女137 784(54.0)134 887(54.6)2 897(36.5)
男117 376(46.0)112 341(45.4)5 035(63.5)
种族[n(%)]
白人242 394(95.0)234 812(95.0)7 582(95.6)
其他11 928(4.7)11 609(4.7)319(4.0)
未知838(0.3)807(0.3)31(0.4)
教育[n(%)]
高中及以上195 742(76.7)190 958(77.3)4 784(60.3)
其他56 934(22.3)53 895(21.8)3 039(38.3)
未知2 484(1.0)2 375(0.9)109(1.4)
体重指数(Kg/m2,)27.4±4.727.3±4.729.8±5.8
Townsend贫困指数(分,)-1.4±3.0-1.4±3.0-0.8±3.3
饮酒[n(%)]
从不10 715(4.2)10 284(4.2)431(5.4)
以前饮酒8 821(3.5)8 313(3.4)508(6.4)
现在饮酒235 375(92.2)228 398(92.4)6 977(88.0)
未知249(0.1)233(0.1)16(0.2)
吸烟[n(%)]
从不139 603(54.7)136 487(55.2)3 116(39.3)
以前吸烟88 319(34.6)84 795(34.3)3 524(44.4)
现在吸烟26 354(10.3)25 108(10.2)1 246(15.7)
未知884(0.3)838(0.3)46(0.6)
饮食评分(分,)2.4±1.22.4±1.22.3±1.1
高血压[n(%)]
否187 749(73.6)184 049(74.4)3 700(46.6)
是67 411(26.4)63 179(25.6)4 232(53.4)
糖尿病[n(%)]
否248 724(97.5)241 614(97.7)7 110(89.6)
是6 436(2.5)5 614(2.3)822(10.4)
衰弱[n(%)]
非衰弱158 219(62.0)154 552(62.5)3 667(46.2)
衰弱前期90 591(35.5)86 969(35.2)3 622(45.7)
衰弱6 350(2.5)5 707(2.3)643(8.1)
衰弱得分(分,)0.5±0.80.5±0.70.9±1.0
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参与者的基本特征描述

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基本特征总人数(n=255 160)心衰
不发病(n=247 228)发病(n=7 932)
年龄(岁,)56.5±8.156.3±8.162.2±6.1
性别[n(%)]
女137 784(54.0)134 887(54.6)2 897(36.5)
男117 376(46.0)112 341(45.4)5 035(63.5)
种族[n(%)]
白人242 394(95.0)234 812(95.0)7 582(95.6)
其他11 928(4.7)11 609(4.7)319(4.0)
未知838(0.3)807(0.3)31(0.4)
教育[n(%)]
高中及以上195 742(76.7)190 958(77.3)4 784(60.3)
其他56 934(22.3)53 895(21.8)3 039(38.3)
未知2 484(1.0)2 375(0.9)109(1.4)
体重指数(Kg/m2,)27.4±4.727.3±4.729.8±5.8
Townsend贫困指数(分,)-1.4±3.0-1.4±3.0-0.8±3.3
饮酒[n(%)]
从不10 715(4.2)10 284(4.2)431(5.4)
以前饮酒8 821(3.5)8 313(3.4)508(6.4)
现在饮酒235 375(92.2)228 398(92.4)6 977(88.0)
未知249(0.1)233(0.1)16(0.2)
吸烟[n(%)]
从不139 603(54.7)136 487(55.2)3 116(39.3)
以前吸烟88 319(34.6)84 795(34.3)3 524(44.4)
现在吸烟26 354(10.3)25 108(10.2)1 246(15.7)
未知884(0.3)838(0.3)46(0.6)
饮食评分(分,)2.4±1.22.4±1.22.3±1.1
高血压[n(%)]
否187 749(73.6)184 049(74.4)3 700(46.6)
是67 411(26.4)63 179(25.6)4 232(53.4)
糖尿病[n(%)]
否248 724(97.5)241 614(97.7)7 110(89.6)
是6 436(2.5)5 614(2.3)822(10.4)
衰弱[n(%)]
非衰弱158 219(62.0)154 552(62.5)3 667(46.2)
衰弱前期90 591(35.5)86 969(35.2)3 622(45.7)
衰弱6 350(2.5)5 707(2.3)643(8.1)
衰弱得分(分,)0.5±0.80.5±0.70.9±1.0
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Associations of frailty with HF risk in the UK Biobank study

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衰弱状态模型1模型2
HR (95% CI)P值HR (95% CI)P值
非衰弱1.000(参照组)1.000(参照组)
衰弱前期1.889(1.804~1.978)<0.0011.441(1.374~1.511)<0.001
衰弱5.439(5.000~5.915)<0.0012.544(2.323~2.785)<0.001
衰弱得分1.693(1.657~1.731)<0.0011.353(1.321~1.387)<0.001
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英国生物银行研究中衰弱与心力衰竭风险的关联

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衰弱状态模型1模型2
HR (95% CI)P值HR (95% CI)P值
非衰弱1.000(参照组)1.000(参照组)
衰弱前期1.889(1.804~1.978)<0.0011.441(1.374~1.511)<0.001
衰弱5.439(5.000~5.915)<0.0012.544(2.323~2.785)<0.001
衰弱得分1.693(1.657~1.731)<0.0011.353(1.321~1.387)<0.001
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衰弱对心力衰竭风险的影响和代谢组学的中介效应分析
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叶泳华 , 许欢 , 程盼 , 唐雪薇 , 杨黄毅 , 廖伟 , 张菊英 , 赵星
现代预防医学 | 流行病与统计方法 2025,52(24): 4431-4435
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现代预防医学 |流行病与统计方法 2025 , 52 (24) : 4431 -4435
衰弱对心力衰竭风险的影响和代谢组学的中介效应分析
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叶泳华, 许欢, 程盼, 唐雪薇, 杨黄毅, 廖伟, 张菊英 , 赵星
作者信息
  • 四川大学华西公共卫生学院/华西第四医院流行病与卫生统计学系,四川 成都 610041
通讯作者:
张菊英,E-mail:
作者简介:

叶泳华(2000—),男,硕士在读,研究方向:流行病与卫生统计学

The association of frailty with heart failure risk and the mediating effect of metabolomics
Yong-hua YE, Huan XU, Pan CHENG, Xue-wei TANG, Huang-yi YANG, Wei LIAO, Ju-ying ZHANG , Xing ZHAO
Affiliations
  • Departmentof Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2025-12-25 doi: 10.20043/j.cnki.MPM.202506272
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目的

探究衰弱与心衰发病的关联,同时确定介导衰弱和心衰之间关系的代谢组学特征。

方法

基于英国生物银行(UK Biobank, UKB),纳入255 160名基线检测了168种代谢物的参与者。获取Fried衰弱表型评估数据,分为非衰弱(0)、衰弱前期(1~2)和衰弱(≥3)三组,Cox比例风险模型分析衰弱与心衰风险之间的关系。同时,对代谢物进行中介分析,评估代谢标志物在衰弱与心衰关系间的中介作用。

结果

与非衰弱参与者相比,衰弱前期和衰弱状态参与者的心力衰竭风险增加,风险比(Hazard Ratio, HR)分别为1.441(95% CI:1.374~1.55)和2.544(95% CI:2.323~2.785)。中介分析显示,小的高密度脂蛋白相关代谢物和低密度脂蛋白组分在衰弱与心衰关系中起到重要的介导作用,相应的中介比例为3.8%~5.5%。

结论

衰弱状态与心衰风险增加有关,以小的高密度脂蛋白和低密度脂蛋白为特征的血浆代谢物可能是介导衰弱与心衰关联的关键标志物。

衰弱  /  心力衰竭  /  代谢组学  /  中介分析
Objective

To investigate the association between frailty and heart failure onset, and to identify the metabolomic features mediating the relationship between frailty and heart failure.

Methods

Based on the UK Biobank (UKB), 255 160 participants who underwent baseline testing for 168 metabolites were included. The Fried frailty phenotype assessment data were obtained and divided into three groups: non-frailty (0), pre-frailty (1-2), and frailty (≥3). The Cox proportional hazards model was used to analyze the relationship between frailty and the risk of heart failure. Additionally, a mediation analysis was conducted on metabolites to assess the mediating role of metabolic markers in the relationship between frailty and heart failure.

Results

Compared with non-frail participants, participants in the pre-frailty and frailty states had an increased risk of heart failure, with hazard ratios ( HR) of 1.441 (95% CI: 1.374–1.55) and 2.544 (95% CI: 2.323–2.785), respectively. Mediation analysis revealed that small high-density lipoprotein-related metabolites and low-density lipoprotein components played an important mediating role in the relationship between frailty and heart failure, with corresponding mediation proportions of 3.8%–5.5%.

Conclusion

Frailty is associated with an increased risk of heart failure, and plasma metabolites characterised by small high-density lipoproteins and low-density lipoproteins may be key biomarkers mediating the association between frailty and heart failure.

Frailty  /  Heart failure  /  Metabolomics  /  Mediation analysis
叶泳华, 许欢, 程盼, 唐雪薇, 杨黄毅, 廖伟, 张菊英, 赵星. 衰弱对心力衰竭风险的影响和代谢组学的中介效应分析. 现代预防医学, 2025 , 52 (24) : 4431 -4435 . DOI: 10.20043/j.cnki.MPM.202506272
Yong-hua YE, Huan XU, Pan CHENG, Xue-wei TANG, Huang-yi YANG, Wei LIAO, Ju-ying ZHANG, Xing ZHAO. The association of frailty with heart failure risk and the mediating effect of metabolomics[J]. Modern Preventive Medicine, 2025 , 52 (24) : 4431 -4435 . DOI: 10.20043/j.cnki.MPM.202506272
心力衰竭(heart failure, HF)是全球范围内导致死亡和住院的主要原因之一,其发病率和死亡率逐年攀升,造成了巨大的医疗成本和个人负担[1-2]。尽管近年来在心衰的诊断、治疗和管理方面取得了一定进展[3],但其发病机制尚未完全阐明,探索潜在的危险因素及病理生理机制对于心衰的早期预防和精准治疗具有重要意义。
衰弱(frailty)是一种以多系统生理储备下降和应激适应能力减弱为特征的老年综合征[4-5]。近年来,衰弱已被广泛认为是心血管疾病,尤其是心力衰竭发生和进展的独立危险因素[6]。研究表明,衰弱与心衰密切相关,表现为再入院率升高、生活质量下降及死亡风险增加[7]。然而,二者之间的潜在生物学联系仍不清晰,尤其缺乏从分子和代谢层面对相关机制的系统研究。
与此同时,代谢紊乱被认为是心血管疾病的重要病理生理基础[8-9],而衰弱状态常伴随一系列代谢和内分泌异常,如慢性低度炎症、脂质代谢紊乱及激素水平改变等[10-11]。这提示,特定的代谢生物标志物可能在衰弱与心力衰竭之间的关系中发挥关键的介导作用。现有研究主要集中于一般临床特征和指标,而基于大规模代谢组学数据的系统性探索非常有限。代谢组学的引入有望揭示潜在的分子中介环节,从而为阐明衰弱与心力衰竭的关系提供新的视角。
因此,本研究基于英国生物银行的代谢组学数据,旨在探究衰弱与心衰发病的关联,并确定介导二者关系的血浆代谢生物标志物,为揭示衰弱–心衰关系的潜在代谢机制提供新的科学证据。
英国生物银行(UK Biobank, UKB)是一项前瞻性队列研究,在2006—2010年期间从英国各地的22个评估中心招募50万名40~69岁的参与者。在进行基线研究时,通过触摸屏问卷、身体测量和生物样本检测获得参与者的相关数据。UKB获得了西北多中心研究伦理委员会的批准,所有参与者都签署了知情同意书。本研究中纳入了有代谢组数据的参与者(n=261 031),排除基线患有心衰(n=1 450)、衰弱测量数据和血浆代谢组学数据缺失(n=4 421)的参与者。最终分析包括255 160名参与者。
UKB利用Nightingale Health公司提供的高通量核磁共振代谢组学平台,对基线时采集的血浆样本进行了代谢组学分析,确定了249个代谢生物标志物(包括168个绝对水平和81个衍生比率)[12]。这些指标包括脂质、脂肪酸、氨基酸、酮体等。本研究重点研究168种代谢物的绝对水平。
使用UKB的调查问卷及检测数据,采用由Fried等人提出的衰弱表型来测量身体衰弱。该表型有5个标准,包括无意的体重减轻、体力活动少、行走速度慢、疲劳和握力弱[13]。根据符合标准的数量,参与者被进一步分为非衰弱(0)、衰弱前期(1~2)和衰弱(≥3)[14]。
随访期间的心衰诊断根据国际疾病分类-第10版(International Classification of Diseases-10th edition , ICD-10)代码I50确定。该信息是从UKB中首次出现的健康结果中提取,主要基于相关的住院、死亡登记、初级保健记录和小部分自我报告的数据。随访时间自招募之日开始计算,直至首次发生心衰事件、死亡、失访、删失或随访结束,以最早发生的事件时间作为随访终止时间。
本研究包括以下潜在混杂因素:年龄、性别、种族、教育程度、Townsend贫困指数(TDI)、饮食评分、体重指数(Body mass index, BMI)、吸烟状况、饮酒状况、高血压和糖尿病。其中,年龄、TDI、饮食评分和BMI为连续变量,其他为分类变量。
在参与者的基本特征描述中,对于连续性变量用标准差表示,对于分类变量用频数(百分比)表示。
在分析之前,所有代谢物都进行了基于秩的逆正态转换和标准化处理[15]。使用多元线性回归模型来研究衰弱和每个代谢物之间的关系。采用Cox比例风险模型分析代谢标志物和HF发病的关系以及评估衰弱和HF发病的风险比(Hazard Ratio, HR)及其95%置信区间(Confidence Interval,CI)。对于在上述两步分析中筛选出的共同代谢标志物,使用基于回归的因果中介模型进行中介分析[16],以探讨代谢物在衰弱与HF之间关系中的介导作用。在涉及代谢组学标志物的分析中,经过Bonferroni校正后,检验水准α=0.05。所有研究分析均使用R软件4.3.1版进行。
研究人群的基线特征分布见表1。本研究共有255 160名参与者,其中女性占54.0%,男性占46.0%,平均年龄为56.5岁。在13.1年的中位随访期内,共有7 932例心衰患者。与未发生心衰的人相比,心衰患者年龄较大,收入和受教育程度较低,更有可能吸烟和摄入不健康的饮食,高血压和糖尿病患病者更多,衰弱程度更高。
衰弱与心衰发病关联的Cox比例风险模型结果如表2所示。在多变量调整后的模型2中,衰弱状态会增加心力衰竭发生风险。与非衰弱组相比,衰弱前期的心衰风险为非衰弱者的1.441倍( HR=1.441, 95% CI: 1.374~1.511),衰弱者的心衰风险为非衰弱者的2.544倍( HR=2.544, 95% CI: 2.323~2.785)。
对168个代谢组学标志物分别与衰弱和心衰发病进行关联分析,其结果如图1所示。经Bonferroni校正后,衰弱和心衰分别与148个和144个代谢标志物存在统计学关联。最终,筛选出131个共同相关代谢物,包括总胆固醇(Total_C)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)、亚油酸(LA)等。
对筛选出的131种共同代谢物进行中介分析,结果如图2。分析显示,其中120个代谢物具有统计学意义。研究重点展示了中介效应比例排名前30的代谢物,其中多种脂蛋白亚类及其组分显示出中介作用。值得注意的是,小的高密度脂蛋白相关代谢物(如S_HDL_P、S_HDL_C和S_HDL_CE等)和低密度脂蛋白组分(如LDL_C、LDL_CE、LDL_FC等)在衰弱与心衰风险关联中的中介效应尤为突出(中介比例3.8%~5.5%)。此外,进行多代谢物联合中介分析,结果显示这些脂蛋白代谢物共同解释了衰弱与心衰关联的13.6%(95% CI:12.1%~15.0%)。
研究利用代谢组学数据,探讨了衰弱状态与心衰发病的关联以及介导二者关联的主要代谢标志物。结果显示,与非衰弱人群相比,衰弱前期和衰弱的参与者发生心衰的风险更高。此外,小的高密度脂蛋白相关代谢物和低密度脂蛋白组分介导了衰弱对心衰风险增加的影响。这些发现提示脂质代谢异常可能是衰弱状态下促进心衰发生的重要机制之一。
衰弱是老年人群中常见的临床综合征,表现为多系统功能储备下降。越来越多的研究表明,衰弱状态与心力衰竭的发生和发展关系密切相关[17-18]。本研究结果显示,与非衰弱人群相比,衰弱前期和衰弱状态均与更高的心衰风险相关,其风险比分别为1.441(95% CI: 1.374~1.511)和2.544(95% CI: 2.323~2.785)。这一结果与既往研究一致[19],进一步支持了衰弱作为心衰重要危险因素的观点。然而,关于衰弱通过何种代谢途径影响心衰风险的证据仍较为有限。
为进一步探索潜在机制,本研究基于血浆代谢组学数据进行了中介分析。结果显示,脂蛋白在二者关系中发挥重要中介作用。其潜在机制可能在于:衰弱常伴随慢性低度炎症、氧化应激及内分泌紊乱,这些全身性改变可扰动肝脏脂蛋白的合成、转运与清除,进而导致脂蛋白谱的功能和组成异常。具体而言,HDL在逆向胆固醇转运、抗氧化和抗炎反应中发挥重要作用[20-21],其中小HDL颗粒尤为关键,其减少可能削弱胆固醇清除能力、加剧动脉壁炎症,间接影响心肌能量代谢和线粒体功能[22–24]。同时,这些病理改变还可促进小而密LDL的形成,使其更易沉积于血管壁并诱发内皮损伤和炎症反应[25-26]。上述环节可共同导致冠脉微循环受损与心肌能量失衡,从而在衰弱基础上加速心衰的发生与发展。
综上所述,本研究结合代谢组学,定量揭示了脂蛋白在衰弱与心衰关系中的中介作用。研究不仅补充了衰弱影响心衰的分子机制证据,还提示脂蛋白异常可能成为衰弱人群心衰风险评估与干预的重要靶点。本研究具有多方面优势。首先,基于英国生物银行大规模前瞻性队列,样本量大、随访时间长,结果具有较高的代表性和稳健性。其次,创新性地结合衰弱表型与血浆代谢组学数据,通过中介分析,识别出以小HDL和LDL为代表的脂质代谢物作为重要中介。然而,本研究也存在局限性。研究对象主要为中老年白人个体,结果的外部推广性有限。代谢组学数据仅来源于基线单次测量,无法反映代谢状态的动态变化及其对衰弱与心衰关系的影响。此外,作为观察性研究,无法建立明确的因果关系。
  • 国家自然科学基金(82073667)
  • 四川省自然科学基金项目(2025ZNSFSC1784)
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2025年第52卷第24期
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doi: 10.20043/j.cnki.MPM.202506272
  • 接收时间:2025-06-17
  • 首发时间:2026-11-02
  • 出版时间:2025-12-25
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  • 收稿日期:2025-06-17
基金
国家自然科学基金(82073667)
四川省自然科学基金项目(2025ZNSFSC1784)
作者信息
    四川大学华西公共卫生学院/华西第四医院流行病与卫生统计学系,四川 成都 610041

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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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