目的 通过数据挖掘和网络药理学方法分析中药治疗肺结核的用药规律和作用机制。方法 采用Excel 2010、SPSS Modeler 18.0和SPSS Statistics 24.0软件对昆明市第三人民医院2019年1月-2020年8月肺结核患者的中药处方进行频数分析和关联规则分析;运用中药系统药理学数据库与分析平台(TCMSP)筛选核心药团的活性成分,整合GeneCards数据库中肺结核的作用靶点,并获得交集靶点。利用STRING数据库构建靶点蛋白相互作用(PPI)网络;通过DAVID 6.8数据库将共同靶点进行基因本体(GO)分析和京都基因和基因组百科全书(KEGG)通路富集分析。结果 共纳入处方数2648份,中药164种。从排名前10位的高频中药中进行关联规则分析得出置信度最高的核心药团为"百部-党参-茯苓"。核心药团共筛选出59个活性成分和153个潜在靶点,并确定24个治疗肺结核的核心靶点。GO富集得出141条结果,KEGG分析得出94条通路。结论 百部-党参-茯苓可能是通过干预炎症反应、细胞凋亡从而起到治疗肺结核的作用。

Objective Data mining and network pharmacology methods were used to analyze the medication rule of Chinese medicine in treatment of pulmonary tuberculosis. Methods Excel 2010, SPSS Modeler 18.0, and SPSS Statistics 24.0 software were used to conduct frequency analysis and association rule analysis on the prescriptions of traditional Chinese medicine for pulmonary tuberculosis patients in The Third People's Hospital of Kunming from January 2019 to August 2020. The active components of core drug group were screened by TCMSP, and the action targets of tuberculosis in GeneCards database were integrated, and the intersection targets were obtained. PPI network was constructed using STRING database. Action targets were analyzed using the DAVID 6.8 database for gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Results A total of 2 648 prescriptions including 164 kinds of Traditional Chinese medicine were included. The core drug group with the highest confidence was “Stemonae Radix–Codonopsis Radix–Poria” by association rule analysis among the top 10 high-frequency Chinese medicines. A total of 59 active ingredients and 153 potential targets were screened out from the core drug group, and 24 core targets for the treatment of tuberculosis were identified. 141 results were obtained by GO enrichment and 94 pathways were obtained by KEGG analysis. Conclusion “Stemonae Radix–Codonopsis Radix–Poria” may play a role in the treatment of pulmonary tuberculosis by interfering inflammatory reaction and apoptosis.

R978.3

昆明市卫生科技项目（2020-0201-011，2021-16-01-0010）；昆明市卫生科技人才培养项目“千”工程（2020-SW[后备]-60）