基于数据挖掘及网络药理学探究中医药治疗脓毒症的用药规律及其作用机制  

Analysis of Medication Laws and Mechanisms of Traditional Chinese Medicine in Treatment of Sepsis Based on Data Mining and Network Pharmacology

作　　者：陈美娟 尹江涛 金颂峰 CHEN Meijuan;YIN Jiangtao;JIN Songfeng(Liaoning University of Traditional Chinese Medicine,Shenyang 110847,Liaoning,China;Liaoning Province Chinese Medicine Research Institute,Shenyang 110034,Liaoning,China)

机构地区：[1]辽宁中医药大学,辽宁沈阳110847 [2]辽宁省中医药研究院,辽宁沈阳110034

出　　处：《实用中医内科杂志》2025年第1期84-88,I0023-I0027,共10页Journal of Practical Traditional Chinese Internal Medicine

基　　金：国家中医药管理局国际合作专项(0730-236132ZC0052/01-04);辽宁省科技厅博士启动基金项目(2022-BS-068)。

摘　　要：目的基于数据挖掘及网络药理学探究中医药治疗脓毒症的用药规律及其作用机制。方法检索中国知网、维普及万方数据库自建库以来治疗脓毒症的处方,依据纳排标准筛选,采用中医传承计算平台V3.0、IBM SPSS Statistics 29软件分析处方的药物频次、四气五味、功效归经、药物组合规律、关联规则,归纳中药治疗脓毒症的用药规律及配伍规律;再通过TCMSP数据库获取核心药物活性成分及其相关靶点,GeneCards数据库获取脓毒症的潜在作用靶点,将脓毒症与核心药物的交集靶点导入String 11.5数据库与Cytoscape 3.9.1获取核心靶点,对二者的交集靶点进行GO及KEGG富集分析,取前20条通路,利用Cytoscape 3.9.1构建“核心药物-靶点-通路”网络。结果通过检索文献,依据纳排标准筛选,最终获得治疗脓毒症的处方78首,涉及中药132味,药物使用频次前8的依次为大黄、甘草、黄芪、生地黄、黄芩、枳实、当归、金银花;四气频次靠前的为寒、温、平;五味频次靠前的为苦、甘、辛;归经频次靠前的为脾、肺、胃;功效频次靠前的为清热类、补虚类、活血化瘀类;关联规则分析显示枳实、厚朴→大黄支持度与置信度最高,聚类分析将药物分为3类。对“当归-黄芪-大黄-枳实-厚朴-桃仁”进行网络药理学分析,获取脓毒症与核心药物交集靶点113个,核心靶点10个:AKT1、JUN、TNF、RELA等,涉及通路246条,主要包括癌症通路、NF-κB信号通路、JAK-STAT信号通路、TNF信号通路等。结论核心药物“当归-黄芪-大黄-枳实-厚朴-桃仁”的主要活性成分可能通过AKT1、IL-6、TNF等靶点,参与NF-κB信号通路、TNF信号通路、JAK-STAT信号通路等以抑制炎症因子的产生及细胞凋亡的发生,改善脓毒症患者症状,为中医药治疗脓毒症,延缓疾病发展提供数据支持及理论依据。Objective Based on data mining and network pharmacology,to explore the medication laws and mechanisms of traditional Chinese medicine in treating sepsis.Method The prescriptions for treating sepsis since the establishment of CNKI,Weipu database and Wanfang database were retrieved.After selection according to the inclusion and exclusion criteria,the drug frequency,four properties and five flavors,efficacy and meridian entry,drug combination regularities and association rules of the prescriptions were analysed by the TCM inheritance computing platform V3.0 and IBM SPSS Statistics 29 software,as well as the laws of medication and compatibility of traditional Chinese medicine in the treatment of sepsis were summarized;Then,the vigorous components of core drugs and their related targets were acquired through TCMSP database,as well as the potential targets of sepsis were acquired through GeneCards database.The intersection targets of sepsis and core drugs were imported into String 11.5 database as well as Cytoscape 3.9.1 to gain the core targets.GO and KEGG enrichment analysis were carried out on the intersecting targets,then the top 20 pathways were selected to construct a"core drug-target-pathway"network through Cytoscape 3.9.1.Results 78 prescriptions for treating sepsis were finally obtained by searching the literature and selecting according to the standard of the inclusion and exclusion,involving 132 herbs.The top 8 drugs used were rhubarb,licorice,astragalus,fresh radix rehmanniae,scutellaria baicalensis,fructus aurantii immaturus,angelica and honeysuckle;the highest frequency of four properties is cold,warm and neutral;The top five flavors are bitter,sweet and pungent;the highest frequency of meridian entry is spleen,lung and stomach;the highest frequency of efficacy is heat-clearing,deficiency-tonifying,blood-activating and blood-stasis-removing.Association rule analysis shows that fructus aurantii immaturus,cortex magnolia officinalis and rhubarb have the highest support and confidence,and cluster analysis di

关 键 词：中医药 脓毒症 数据挖掘 网络药理学 机制 

分 类 号：R25[医药卫生—中医内科学]