基于数据挖掘及网络药理学探讨运脾法治疗儿童便秘的用药规律及机制  

Analysis of Medication Rules and Mechanism in Treatment of Children with Functional Constipation by Activating the Spleen Based on Data Mining and Network Pharmacology

作　　者：吴嘉宝 赵霞[1,2] 汪受传[1,2] 张艺斐 潘青云 WU Jiabao;ZHAO Xia;WANG Shouchuan(Affiliated Hospital of Nanjing University of Chinese Medicine,Nanjing,210029,China;Jiangsu Key Laboratory of Children's Health and Chinese Medicine(Nanjing University of Chinese Medicine))

机构地区：[1]南京中医药大学附属医院,南京210029 [2]儿童健康与中医药省高校重点实验室(南京中医药大学)

出　　处：《浙江中医药大学学报》2024年第8期1033-1049,共17页Journal of Zhejiang Chinese Medical University

基　　金：江苏省中医药领军人才项目(SLJ0224);江苏高校优势学科建设工程资助项目(035062005001);江苏省中医院第三批高峰学术人才培养对象(Y2021RC21);江苏省研究生科研与实践创新计划项目(SJCX21_0722)。

摘　　要：[目的]结合数据挖掘及网络药理学,探讨运脾法治疗儿童功能性便秘的用药规律及作用机制。[方法]收集562例功能性便秘患儿病案,采用SPSS Statistic 24.0软件进行聚类分析,SPSS Modeler 18.0软件进行关联规则分析,Liquorice软件进行复杂网络分析,得出核心方药。运用中药系统药理学数据库与分析平台(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform,TCMSP)、中药分子机制生物信息学分析工具(Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine,BATMAN-TCM)数据库筛选核心方活性成分及靶点,通过基因组注释数据平台(Genome Annotation Database Platform,GeneCards)数据库筛选功能性便秘相关靶点,取交集后获得预测靶标。基于蛋白质基因相互作用分析(Search Tool for the Retrieval of Interacting Genes/Proteins,STRING)数据库构建靶基因蛋白互作网络(protein-protein interaction,PPI),利用Cytoscape 3.8.0软件建立核心方成分-便秘-靶点网络图,借助Network Analyzer工具进行拓扑分析,确定核心靶点。基于STRING数据库,使用R语言4.2.2进行基因本体(gene ontology,GO)功能富集与京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路富集分析。[结果]所纳病案包含1121诊次方药记录,各疗程的症状改善率在86%~97%,便秘三大主症的改善率均在90%左右。涉及中药119味,药性以寒、平为主,药味以苦、甘居多,归经多属胃、脾。通过药物关联、聚类和复杂网络分析得到9味药物构成的核心组方。核心组方调治便秘的主要活性成分为槲皮素、甲基庚烯酮、胆汁三烯、烟酸、木犀草素、山柰酚、汉黄芩素。关键靶点包括前列腺素内过氧化物合酶2(prostaglandin-endoperoxide synthase 2,PTGS2)、V-Jun肉瘤病毒17癌基因同源物(V-Jun sarcoma virus 17 oncogene homolog,JUN)、蛋白激酶B1(protein kinase B1,AKT1)、磷酸肌醇-3-激酶调节亚�[Objective]To analyze the medication rules and mechanism in treatment of children with functional constipation(FC)by activating the spleen.[Methods]Collecting 562 cases of children with functional constipation,cluster analysis was conducted using SPSS Statistics 24.0 software,association rule analysis was performed using SPSS Modeler 18.0 software,and complex network analysis was carried out using Liquorice software to derive the core formula.The active ingredients and targets of the core formula were screened using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine(BATMAN-TCM),the targets related to FC were screened by Genome Annotation Database Platform(GeneCards),and the predicted targets were obtained after taking the intersection.Based on the Search Tool for the Retrieval of Interacting Genes/Proteins(STRING)database,the target gene protein-protein interaction(PPI)network was constructed,Cytoscape 3.8.0 software was used to build the core formula component-constipation-target network map,and topology analysis was performed with the help of Network Analyzer tool to identify the core targets.Based on the STRING database,gene ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were performed by using R language4.2.2.[Results]The cases contained 1121 prescriptions.The improvement rate of symptoms in each course was 86%to 97%,and the improvement rate of the three main symptoms of constipation was around 90%.Drug properties were mainly cold and flat,mostly were bitter and sweet.The drugs commonly belonged to the stomach and spleen.The core formula was obtained by drug association,clustering and complex network analysis,and was composed of nine drugs.The main active ingredients of the core formula were quercetin,methylheptenone,bile triene,niacin,lignan,kaempferol and baicalin.The key targets included prostaglandin-endoperoxide syntha

关 键 词：数据挖掘 网络药理学 运脾法 儿童 功能性便秘 中医药 

分 类 号：R720[医药卫生—儿科]