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中国医药导刊 ›› 2025, Vol. 27 ›› Issue (5): 442-447.

• 研究进展 • 上一篇    下一篇

基于精准医学的急性冠脉综合征症状网络研究进展

魏萍12, 张娜13, 徐百超4, 赵振宇1, 赵亚娟1, 张华1*   

  1. 1.海南医科大学,海南 海口 571199;
    2.重庆大学附属三峡医院,重庆 404000;
    3.海南医科大学急救与创伤研究教育部重点实验室,海南 海口 571199;
    4.海南医科大学海南省运动与健康促进重点实验室,海南 海口 571199
  • 收稿日期:2025-01-09 修回日期:2025-02-13 接受日期:2025-03-14 出版日期:2025-05-28 发布日期:2025-07-23
  • 基金资助:
    海南省自然科学基金项目(822MS071);海南省重点研发项目(ZDYF2022SHFZ306);海南省高等学校教育教学改革研究项目(HnjgS2022-8);海南医科大学2024年研究生创新科研课题(HYYB2024-S013)

Research Progress on Symptom Network of Acute Coronary Syndrome Based on Precision Medicine

WEI Ping12, ZHANG Na13, XU Baichao4, ZHAO Zhenyu1, ZHAO Yajuan1, ZHANG Hua1*   

  1. 1.Hainan Medical University Hainan Haikou 571199, China
    2.Chongqing University Three Gorges Hospital Chongqing 404000, China
    3.Key Laboratory of Emergency and Trauma Research of Ministry of Education
    Hainan Medical University Hainan Haikou 571199, China
    4.Hainan Provincial Key Laboratory of Sports and Health Promotion Hainan Medical University
    Hainan Haikou 571199, China
  • Received:2025-01-09 Revised:2025-02-13 Accepted:2025-03-14 Online:2025-05-28 Published:2025-07-23
  • Contact: ZHANG, Hua

摘要:

急性冠脉综合征(acute coronary syndromeACS)是全球主要致死疾病之一,其症状复杂且受多种因素影响,快速识别对预后至关重要。传统ACS症状研究多聚焦单一症状或症状群,易忽略症状表型相同但发生机制及生理、心理等因素的差异,不利于精准干预策略的制定。症状网络是基于精准医学视角提出的一种新研究范式,通过整合ACS的复杂症状、生物标志物等多维度数据,揭示疾病的病理机制及其内在关联,为该病的精准预防和治疗提供新思路。本研究系统回顾了症状网络的概念、原理及其在ACS精准诊治中的应用优势与挑战。症状网络通过节点和边缘构建的网络结构及特异性指标,直观呈现症状间的复杂关联,有效识别核心症状和桥梁症状。研究表明,症状网络不仅能准确反映复杂症状的动态变化,还能结合生物标志物实现ACS的早期识别与精准干预。然而,该研究范式仍面临数据安全、多组学技术局限性及结果应用等挑战。未来需通过更多实证研究,进一步完善症状网络模型,推动精准医学在ACS症状管理中的应用。

 

关键词:  , 急性冠脉综合征;症状网络;精准医学;组学

Abstract:

Acute coronary syndrome ACS is one of the leading causes of death globally with complex symptoms influenced by multiple factors. Rapid identification of ACS is crucial for determining its prognosis. The traditional symptom research of ACS focuses on a single symptom or symptom cluster easily ignoring the differences in symptom phenotypes mechanisms physiological and psychological factors which may not be conducive to developing precise intervention strategies. Symptom network is a novel research paradigm based on the perspective of precision medicine which reveals pathological mechanisms and intrinsic associations by integrating multi-dimensional data such as complex symptoms and biomarkers of ACS. It provides new ideas for precision prevention and treatment of the disease. This study systematically reviews the concepts and principles of symptom network and their application advantages and challenges in the precise diagnosis and treatment of ACS. Symptom networks visualize the complex associations among symptoms through the network structure and specificity indicators constructed by nodes and edges and effectively identify core and bridge symptoms. Studies have shown that symptom networks can not only accurately reflect the dynamic changes of complex ACS symptoms but also combine with biomarkers to realize early identification and precise intervention. However this research paradigm still faces challenges such as data safety limitations of multi-omics technology and application of results. More empirical studies are needed to improve the model of symptom network and promote the application of precision medicine in ACS symptom management in the future.


Key words:  , Acute coronary syndromes , Symptom network , Precision medicine , Omics

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