生理网络映射可以揭示对新出现的疾病的病理生理学的见解吗? 从COVID-19中吸取的经验教训
Cindy Xinyu Ji1, Majid Sorouri2, Mohammad Abdollahi3
1Network Physiology Lab, Division of Medicine, UCL, London, United Kingdom.
PloS one
|November 21, 2025
概括
网络生理学映射揭示了COVID-19非幸存者的独特器官系统连接,确定了意识和肝酶以及功能标志物之间的独特相关性. 这种方法有助于理解复杂的疾病病理生理学.
科学领域:
- 网络生理学 网络生理学
- 系统生物学 系统生物学
- 计算医学是一种计算医学.
背景情况:
- 网络生理学提供了对人体相互作用的整体观点.
- 器官系统的连接对于理解健康和疾病至关重要.
- 新出现的疾病需要新的方法来获得病理生理学的见解.
研究的目的:
- 评估用于预测COVID-19患者结果的生理网络映射.
- 确定非幸存者与COVID-19幸存者的不同网络模式.
- 在新型传染病的背景下探索器官之间的连接.
主要方法:
- 从202名COVID-19患者的临床和实验室数据的回顾性分析.
- 使用21个生理变量通过相关性分析构建器官网络连接.
- 应用亲临床网络分析来评估与幸存者参考相互作用的偏差.
主要成果:
- 在非幸存者和幸存者之间观察到明显的相关性网络图.
- 不幸存者显示了意识和肝酶之间的显著相关性,幸存者缺席.
- 在非幸存者中,强烈的BUN-轴相关性表明功能障碍和改变的平衡.
结论:
- 生理网络映射是发现新出现的疾病中复杂的器官间相互作用的宝贵工具.
- 非幸存者的独特网络特征为疾病严重程度提供了潜在的生物标志物.
- 网络生理学可以在未来的流行病中支持临床医生,研究人员和政策制定者.
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