摘要
目的:通过生物信息学技术探寻类风湿性关节炎(rheumatoid arthritis,RA)的发病机制,预测治疗RA的潜在中药。方法:从基因表达数据库(gene expression omnibus,GEO)提取数据集GSE1919、GSE55235、GSE55457基因片段原始数据,使用GEO2R在线分析工具筛选每个数据集的差异表达基因(differentialy expressed genes,DEGs),取交集得到RA的DEGs。利用DAVID数据库对DEGs进行基因本体(gene ontology,GO)功能富集分析和京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes,KEGG)信号通路富集分析。利用STRING数据库构建DEGs的蛋白质-蛋白质相互作用(protein-protein interaction network,PPI)网络,使用Cytoscape3.7.0软件进行拓扑分析筛选重点基因,采用GSE77298数据集进行验证筛选关键基因。将关键基因与在线中药预测工具Coremine Medical进行映射,筛选治疗RA的靶向中药。结果:基于GSE1919、GSE55235、GSE55457数据集筛选RA共同DEGs 33个。GO分析发现,分子功能主要涉及趋化因子活性、免疫球蛋白受体结合、抗原结合、肽聚糖结合等;细胞组分主要集中在质膜外侧、细胞外间隙、细胞外组分、质膜、IgM免疫球蛋白复合物等;生物过程主要集中在免疫应答、B细胞受体信号转导过程、适应性免疫反应、趋化因子介导的信号通路、免疫反应调节、细胞信号转导、细胞增殖调节等。KEGG信号通路分析结果表明,DEGs主要富集在细胞因子间受体相互作用、趋化因子信号通路、原发性免疫缺陷、Toll样受体信号通路等。PPI网络拓扑分析发现CD27、CD79A、CXCL9、CXCL10、CXCL13、CCL5、CD3D、LCK、TNFRSF17、CCL8是与RA发生发展相关的重点基因。通过GSE77298原始数据集验证发现:CXCL9、CXCL10、CXCL13、CCL5、CCL8和CD79A、CD3D、TNFRSF17为关键基因。关键基因与Coremine Medical数据库映射后筛选出治疗RA的中药52种,包括清热凉血药(白药子、苦参、苦瓜等)、祛风散寒药(青风藤、姜皮等)和活血祛瘀药(丹参、没药等)。结论:通关藤、青风藤、苦参、干姜、花椒、茶树根、连翘等中药可能为治疗RA的潜在靶向中药。
Objective:To explore the pathogenesis of rheumatoid arthritis(RA)by bioinformatics and to predict the potential traditional Chinese medicine for the treatment of RA.Methods:The original data of gene fragments of GSE1919,GSE55235 and GSE55457 were extracted from the gene expression omnibus(GEO),and the differentialy expressed genes(DEGs)of each dataset were screened by GEO2R online analysis tool,and the DEGs of RA were obtained by intersection.The DAVID database was used to perform gene ontology(GO)functional enrichment analysis and KEGG signal pathway enrichment analysis of DEGs.The protein-protein interaction network(PPI)network of DEGs was constructed using the STRING database,the key genes were screened out by topological analysis using Cytoscape3.7.0 software,and the GSE77298 dataset was used to verify and screen out the key genes.Key genes were mapped to Coremine Medical,an online TCM prediction tool,to screen targeted TCM for the treatment of RA.Results:33 RA common DEGs were screened based on GSE1919,GSE55235 and GSE55457 datasets.GO analysis found that molecular functions mainly involve chemokine activity,immunoglobulin receptor binding,antigen binding,peptidoglycan binding,etc.The cell components are mainly concentrated on the outside of the plasma membrane,extracellular space,extracellular components,plasma membrane,IgM immunoglobulin complex,etc.Biological processes mainly focus on immune response,B-cell receptor signal transduction process,adaptive immune response,chemokine-mediated signaling pathway,immune response regulation,cell signal transduction,cell proliferation regulation,etc.The results of KEGG signaling pathway analysis showed that DEGs were mainly enriched in cytokine-receptor interaction,chemokine signaling pathway,primary immune deficiency,and toll-like receptor signaling pathway.The PPI network topology analysis showed that CD27,CD79A,CXCL9,CXCL10,CXCL13,CCL5,CD3D,L CK,TNFRSF17 and CCL8 were key genes related to the occurrence and development of RA.Through the verification of the GSE77298 original dataset,it was found that CXCL9,CXCL10,CXCL13,CCL5,CCL8,CD79A,CD3D and TNFRSF17 were screened as key genes.After mapping the key genes with the Coremine Medical database,52 kinds of traditional Chinese medicines that may treat RA were screened,including heat and cold blood medicine(Baiyaozi/Trichosanthes palmata,Kushen/Radix sophorae flavescentis,Kugua/Bitter gourd,etc.),wind and cold dispelling medicine(Qingfengteng/Sabia japonica,Jiangpi/Ginger peel,etc.)and blood stasis relieving medicine(Danshen/Red-rooted salvia,Moyao/Myrrh,etc.).Conclusion:Traditional Chinese medicines such as Tongguanteng(Marsdenia tenacissima),Qingfengteng(Sabia japonica),Kushen(Radix sophorae flavescentis),Ganjiang(Dried jinger),Huajiao(Petter),Chashugen(Root of tea tree),and Lianqiao(Fructus forsythiae)may be potential target medicines in RA treatment.
作者
姚承佼
李奕霖
熊钦
罗利红
谢凤娇
李廷林
谢文光
周京国
冯培民
YAO Chengling;LI Yilin;XIONG Qin;LUO Lihong;XIE Fengjiao;LI Tinglin;XIE Wenguang;ZHOU Jingguo;FENG Peimin(The Affiliated Hospital of Chengdu University of Traditional Chinese Medicine,Chengdu Sichuan China 610072;The Affiliated Hospital of North Sichuan Medical College,Nanchong Sichuan China 637007;The First Affiliated Hospital of Chengdu Medical College,Chengdu Sichuan China 610500)
出处
《中医学报》
CAS
2023年第1期152-160,共9页
Acta Chinese Medicine
基金
国家自然科学基金项目(81673854)
四川省医学青年创新课题项目(Q20001)。
关键词
类风湿性关节炎
差异表达基因
发病机制
中药预测
生物信息学
rheumatoid arthritis
differentially expressed genes
pathogenesis
Chinese medicine forecast
bioinformatics
