Disease Network-Based Approaches to Study Comorbidity in Heart Failure: Current State and Future Perspectives.

IF 3.8 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS Current Heart Failure Reports Pub Date : 2024-12-27 DOI:10.1007/s11897-024-00693-7
Sergio Alejandro Gomez-Ochoa, Jan D Lanzer, Rebecca T Levinson
{"title":"Disease Network-Based Approaches to Study Comorbidity in Heart Failure: Current State and Future Perspectives.","authors":"Sergio Alejandro Gomez-Ochoa, Jan D Lanzer, Rebecca T Levinson","doi":"10.1007/s11897-024-00693-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>Heart failure (HF) is often accompanied by a constellation of comorbidities, leading to diverse patient presentations and clinical trajectories. While traditional methods have provided valuable insights into our understanding of HF, network medicine approaches seek to leverage these complex relationships by analyzing disease at a systems level. This review introduces the concepts of network medicine and explores the use of comorbidity networks to study HF and heart disease.</p><p><strong>Recent findings: </strong>Comorbidity networks are used to understand disease trajectories, predict outcomes, and uncover potential molecular mechanisms through identification of genes and pathways relevant to comorbidity. These networks have shown the importance of non-cardiovascular comorbidities to the clinical journey of patients with HF. However, the community should be aware of important limitations in developing and implementing these methods. Network approaches hold promise for unraveling the impact of comorbidities in the complex presentation and genetics of HF. Methods that consider comorbidity presence and timing have the potential to help optimize management strategies and identify pathophysiological mechanisms.</p>","PeriodicalId":10830,"journal":{"name":"Current Heart Failure Reports","volume":"22 1","pages":"6"},"PeriodicalIF":3.8000,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11671564/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Heart Failure Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s11897-024-00693-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose of review: Heart failure (HF) is often accompanied by a constellation of comorbidities, leading to diverse patient presentations and clinical trajectories. While traditional methods have provided valuable insights into our understanding of HF, network medicine approaches seek to leverage these complex relationships by analyzing disease at a systems level. This review introduces the concepts of network medicine and explores the use of comorbidity networks to study HF and heart disease.

Recent findings: Comorbidity networks are used to understand disease trajectories, predict outcomes, and uncover potential molecular mechanisms through identification of genes and pathways relevant to comorbidity. These networks have shown the importance of non-cardiovascular comorbidities to the clinical journey of patients with HF. However, the community should be aware of important limitations in developing and implementing these methods. Network approaches hold promise for unraveling the impact of comorbidities in the complex presentation and genetics of HF. Methods that consider comorbidity presence and timing have the potential to help optimize management strategies and identify pathophysiological mechanisms.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于疾病网络的方法研究心力衰竭共病:现状和未来展望。
综述目的:心力衰竭(HF)通常伴有一系列合并症,导致不同的患者表现和临床轨迹。虽然传统方法为我们对心衰的理解提供了有价值的见解,但网络医学方法试图通过在系统层面分析疾病来利用这些复杂的关系。本文介绍了网络医学的概念,并探讨了合并症网络在心衰和心脏病研究中的应用。最新发现:共病网络用于了解疾病轨迹,预测结果,并通过鉴定与共病相关的基因和途径揭示潜在的分子机制。这些网络显示了非心血管合并症对心衰患者临床旅程的重要性。然而,社区应该意识到开发和实施这些方法的重要局限性。网络方法有望揭示HF复杂表现和遗传学中合并症的影响。考虑合并症存在和时间的方法有可能帮助优化管理策略和确定病理生理机制。
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 去求助
来源期刊
Current Heart Failure Reports
Current Heart Failure Reports Medicine-Emergency Medicine
CiteScore
5.30
自引率
0.00%
发文量
44
期刊介绍: This journal intends to provide clear, insightful, balanced contributions by international experts that review the most important, recently published clinical findings related to the diagnosis, treatment, management, and prevention of heart failure. We accomplish this aim by appointing international authorities to serve as Section Editors in key subject areas, such as investigative, pharmacologic, and nonpharmacologic therapies, pathophysiology, and prevention. Section Editors, in turn, select topics for which leading experts contribute comprehensive review articles that emphasize new developments and recently published papers of major importance, highlighted by annotated reference lists. An international Editorial Board reviews the annual table of contents, suggests articles of special interest to their country/region, and ensures that topics are current and include emerging research. Commentaries from well-known figures in the field are also provided.
期刊最新文献
Biomarkers in Subclinical Transthyretin Cardiac Amyloidosis. Insights and Opportunities from Multimarker Evaluation of Heart Failure: Lessons from BIOSTAT-HF. Disease Network-Based Approaches to Study Comorbidity in Heart Failure: Current State and Future Perspectives. Artificial Intelligence Advancements in Cardiomyopathies: Implications for Diagnosis and Management of Arrhythmogenic Cardiomyopathy. Gamification and its Potential for Better Engagement in the Management of Heart Failure or Quality of Care Registries: A Viewpoint.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1