| 引用本文: |
邓文欣, 董斐, 刘流, 赵屹.基于复杂网络探究肺系疫病各阶段核心“症-药”关联及作用机制[J].湖南中医药大学学报,2024,44(8):1459-1467[点击复制] |
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| 基于复杂网络探究肺系疫病各阶段核心“症-药”关联及作用机制 |
| 邓文欣,董斐,刘流,赵屹 |
| (北京中医药大学中医学院, 北京 102488;北京中医药大学中医疫病研究院, 北京 102488) |
| 摘要: |
| 目的 通过整合肺系疫病的各阶段临床表现与中药复方，利用现代生命科学的组学大数据资源，挖掘肺系疫病各阶段症状与中药的内在联系，为阐明中医药在治疗肺系疫病中的作用机制提供数据支持。方法 明确界定肺系疫病非特异性症状特征，系统梳理古代疫病文献资料、中成药目录，以及针对新型冠状病毒肺炎的中医药诊疗方案，构建包含肺系疫病各阶段症状与方药的大数据集；运用网页排名算法提炼出肺系疫病在急性期（轻症、重症）和恢复期3个不同阶段的“核心症状群”和“核心中药群”，并通过随机游走算法深入剖析核心“症-药”间的相互关系。结果 在纳入的822条数据中（轻症287条，重症403条，恢复期132条），所识别的核心症状群与各阶段肺系疫病的实际临床表现高度吻合。轻症阶段的核心中药以解表药和清热药为主，重症阶段则在此基础上增加了祛湿化痰药，而恢复期以补气养阴药为核心。进一步的富集分析揭示，急性期核心中药主要涉及调控Janus激酶/信号转导与转录激活子和核转录因子κB信号通路，恢复期核心中药主要影响成纤维细胞增殖相关通路。结论 核心症状群对应的核心中药群可能通过调节关键转录因子来治疗肺系疫病。 |
| 关键词: 核心症状群 肺系疫病 核心中药群 复杂网路 随机游走算法 |
| DOI：10.3969/j.issn.1674-070X.2024.08.015 |
| 投稿时间：2024-04-10 |
| 基金项目:科技基础资源调查专项资助（2022FY102000，2022FY102005）；国家中医药管理局高水平中医药重点学科建设项目（zyyzdxk-2023264）；国家中医药管理局中医药创新团队及人才支持计划项目（ZYYCXTD-C-202006）。 |
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| Core "symptom-Chinese medicines" associations and their mechanisms of action at different stages of pulmonary epidemic diseases based on complex network analysis |
| DENG Wenxin, DONG Fei, LIU Liu, ZHAO Yi |
| (School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China;Institute of Chinese Medicine Epidemic Disease, Beijing University of Chinese Medicine, Beijing 102488, China) |
| Abstract: |
| Objective To explore the inherent connections between symptoms and Chinese medicines at different stages of pulmonary epidemic diseases (PED) by integrating the clinical manifestations of PED at various stages with compound formulas of Chinese medicines and utilizing omics big data resources of modern life science, aiming to provide a data basis for elucidating the mechanisms of action of TCM in treating PED. Methods The nonspecific symptom characteristics of PED were defined clearly, and the ancient epidemic literature, catalogues of Chinese patent medicines, and TCM diagnostic and therapeutic protocols for corona virus disease 2019 (COVID-19) were systematically sorted out, through which, a large dataset containing symptoms, Chinese medicines, and formulas for different stages of PED was constructed. The PageRank algorithm was used to identify the "core symptom clusters" and "core clusters of Chinese medicines" in three different stages of PED: acute stages (mild and severe) and recovery stage. The random walk algorithm was then employed to further explore the interrelationships between the core "symptom-Chinese medicines" pairs. Results Among the 822 formulas included (287 for mild stage, 403 for severe stage, and 132 for recovery stage), the identified core symptom clusters were highly consistent with the actual clinical manifestations of PED at each stage. The core clusters of Chinese medicines for mild stage focused mainly on relieving exterior pattern and clearing heat, while for severe stage, dampness-eliminating and phlegm-transforming medicines were added to this basis. During the recovery stage, the core clusters of Chinese medicines were focused on tonifying qi and nourishing yin. The enrichment analysis further revealed that the core Chinese medicines for the acute stage mainly involved the regulation of the Janus kinase/signal transducer and activator of transcription (JAK-STAT) and nuclear factor-κB (NF-κB) signaling pathways, while those for the recovery stage primarily affected the fibroblast proliferation-related pathways. Conclusion The core clusters of Chinese medicines corresponding to the core symptom clusters may intervene and treat PED by regulating key transcription factors. |
| Key words: core symptom clusters pulmonary epidemic diseases core clusters of Chinese medicines complex network random walk algorithm |
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