Cardiovascular diseases and depression: A meta-analysis and Mendelian randomization analysis

IF 9.6 1区 医学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Jun Zeng, Yuting Qiu, Chengying Yang, Xinrong Fan, Xiangyu Zhou, Chunxiang Zhang, Sui Zhu, Yang Long, Yan Wei, Kenji Hashimoto, Lijia Chang
{"title":"Cardiovascular diseases and depression: A meta-analysis and Mendelian randomization analysis","authors":"Jun Zeng, Yuting Qiu, Chengying Yang, Xinrong Fan, Xiangyu Zhou, Chunxiang Zhang, Sui Zhu, Yang Long, Yan Wei, Kenji Hashimoto, Lijia Chang","doi":"10.1038/s41380-025-03003-2","DOIUrl":null,"url":null,"abstract":"<p>Depression is a common psychiatric symptom among patients with cardiovascular disease (CVD), adversely affecting their health. Despite the identification of various contributing factors, the precise mechanisms linking CVD and depression remain elusive. This study conducted a meta-analysis to investigate the association between CVD and depression. Furthermore, a bidirectional Mendelian randomization (MR) analysis was undertaken to clarify the causal relationship between the two conditions. The meta-analysis included 39 studies, encompassing 63,444 patients with CVD, 12,308 of whom were diagnosed with depression. The results revealed a significant association between CVD and depression or anxiety, with an estimated overall prevalence of depression in CVD patients of 20.8%. Subgroup analyses showed that the prevalence of depression in patients with coronary artery disease and heart failure was 19.8 and 24.7%, respectively. According to a random-effects model, depressive symptoms were linked to an increase in unadjusted all-cause mortality compared with non-depressed patients. The MR analysis, employing the inverse-variance weighted method as the primary tool for causality assessment, identified significant associations between various CVD types and depression or anxiety phenotypes. These findings underscore the significant relationship between CVD and depression or anxiety, leading to an elevated risk of all-cause mortality. Moreover, the MR analysis provides the first genetically-informed evidence suggesting that depression plays a critical role in the development and progression of certain CVD subtypes. This emphasizes the need for addressing depressive symptoms in CVD patients to prevent or reduce adverse cardiovascular outcomes.</p>","PeriodicalId":19008,"journal":{"name":"Molecular Psychiatry","volume":"88 1","pages":""},"PeriodicalIF":9.6000,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Psychiatry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41380-025-03003-2","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Depression is a common psychiatric symptom among patients with cardiovascular disease (CVD), adversely affecting their health. Despite the identification of various contributing factors, the precise mechanisms linking CVD and depression remain elusive. This study conducted a meta-analysis to investigate the association between CVD and depression. Furthermore, a bidirectional Mendelian randomization (MR) analysis was undertaken to clarify the causal relationship between the two conditions. The meta-analysis included 39 studies, encompassing 63,444 patients with CVD, 12,308 of whom were diagnosed with depression. The results revealed a significant association between CVD and depression or anxiety, with an estimated overall prevalence of depression in CVD patients of 20.8%. Subgroup analyses showed that the prevalence of depression in patients with coronary artery disease and heart failure was 19.8 and 24.7%, respectively. According to a random-effects model, depressive symptoms were linked to an increase in unadjusted all-cause mortality compared with non-depressed patients. The MR analysis, employing the inverse-variance weighted method as the primary tool for causality assessment, identified significant associations between various CVD types and depression or anxiety phenotypes. These findings underscore the significant relationship between CVD and depression or anxiety, leading to an elevated risk of all-cause mortality. Moreover, the MR analysis provides the first genetically-informed evidence suggesting that depression plays a critical role in the development and progression of certain CVD subtypes. This emphasizes the need for addressing depressive symptoms in CVD patients to prevent or reduce adverse cardiovascular outcomes.

Abstract Image

心血管疾病与抑郁症:一项荟萃分析和孟德尔随机化分析
抑郁症是心血管疾病(CVD)患者常见的精神症状,严重影响其健康。尽管确定了各种促成因素,但将心血管疾病和抑郁症联系起来的确切机制仍然难以捉摸。本研究进行了一项荟萃分析,以调查心血管疾病与抑郁症之间的关系。此外,进行了双向孟德尔随机化(MR)分析,以澄清两种情况之间的因果关系。荟萃分析包括39项研究,涉及63,444名心血管疾病患者,其中12,308名被诊断为抑郁症。结果显示CVD与抑郁或焦虑之间存在显著关联,CVD患者中抑郁症的总体患病率估计为20.8%。亚组分析显示,冠状动脉疾病和心力衰竭患者的抑郁患病率分别为19.8%和24.7%。根据随机效应模型,与非抑郁患者相比,抑郁症状与未调整的全因死亡率增加有关。MR分析采用反方差加权法作为因果关系评估的主要工具,确定了各种CVD类型与抑郁或焦虑表型之间的显著关联。这些发现强调了心血管疾病与抑郁或焦虑之间的重要关系,导致全因死亡率的风险升高。此外,MR分析提供了第一个遗传学证据,表明抑郁在某些CVD亚型的发展和进展中起着关键作用。这强调了解决CVD患者抑郁症状以预防或减少不良心血管结局的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Molecular Psychiatry
Molecular Psychiatry 医学-精神病学
CiteScore
20.50
自引率
4.50%
发文量
459
审稿时长
4-8 weeks
期刊介绍: Molecular Psychiatry focuses on publishing research that aims to uncover the biological mechanisms behind psychiatric disorders and their treatment. The journal emphasizes studies that bridge pre-clinical and clinical research, covering cellular, molecular, integrative, clinical, imaging, and psychopharmacology levels.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信