系统性红斑狼疮基因表达差异分析及治疗中药预测

摘要/Abstract

摘要： 目的：基于生物信息学的方法分析系统性红斑狼疮（SLE）患者与正常人的差异表达基因(DEGs)，并预测潜在的治疗中药。方法：利用edgeR分析数据集GSE154851，获得DEGs，通过String构建蛋白互作（PPI）网络，使用Cytoscape的CytoHubba插件筛选关键基因，并进行GO功能及KEGG信号通路富集分析。将关键基因输入到Coremine Medical数据库筛选潜在治疗中药。结果：筛选出228个DEGs，其中有196个基因表达上调，32个基因表达下调。筛选到的关键基因有DDX58、ISG15、STAT1、TRIM25、IRF7、IFIH1、NOD2、UBE2L6、NOD1、FLT3，GO分析显示关键基因参与的主要生物过程包括调节IFN-I、TNF、IL-6的产生，对病毒的应答等；KEGG分析显示主要涉及的信号通路有RIG-I-样受体信号通路、甲型流感、EB病毒感染等。预测出治疗SLE的潜在中药有水牛角、赤芍、鳖甲、半夏、板蓝根、黄柏、独活、厚朴等。结论：本研究通过分析SLE的基因表达数据，获得DEGs，从而筛选了治疗SLE的关键基因以及潜在的治疗药物，为探索治疗SLE的药物选择提供了新思路。

关键词: font-size:medium, ">系统性红斑狼疮；生物信息学；差异表达基因；关键基因；中药预测

Abstract: Objective：To analyze the differentially expressed genes (DEGs) of patients with systemic lupus erythematosus (SLE) compared with healthy control based on bioinformatics method and to predict the potential therapeutic traditional Chinese medicine (TCM) for SLE. Methods： EdgeR package was used to analyze the dataset GSE154851 for obtaining DEGs. Protein-protein interaction (PPI) network of DEGs was constructed by String. Key genes were screened by using CytoHubba plugin of Cytoscape. GO function and KEGG signal pathway enrichment analysis were performed. Then key genes were input into the Coremine Medical platform to screen potential therapeutic TCM. Results: 228 DEGs were screened out， among which 196 genes were up-regulated and 32 genes were down-regulated. Key genes obtained were DDX58， ISG15， STAT1， TRIM25， IRF7， IFIH1， NOD2， UBE2L6， NOD1， and FLT3. GO analysis showed that key genes mainly participated in biological processes of regulating productions of IFN-I， TNF， and IL-6， and response to virus， etc. KEGG analysis showed that the main signaling pathways involved were RIG-I-like receptor signaling pathway， Influenza A， Epstein-Barr virus infection， etc. Potential therapeutic TCM for SLE included Bubali Cornu， Paeoniae Radix Rubra， Trionycis Carapax， Pinelliae Rhizoma， Isatidis Radix， Phellodendri Chinensis Cortex， Angelicae Pubescentis Radix， Magnoliae Officinalis and so on. Conclusion： In this study， DGEs were obtained by analyzing the gene expression data of SLE， and the key genes and potential therapeutic TCM for SLE were screened， which provide a new idea for exploring drugs for the treatment of SLE.

Key words: font-size:medium, ">SLE； Bioinformatics； DEGs； Key genes； Prediction of TCM

中图分类号:

刘瑞, 曹双, 张秋月, 阴志刚, 范长有, 田花丽, 黄冉涛. 系统性红斑狼疮基因表达差异分析及治疗中药预测[J]. 中国医药导刊, 2022, 24(8): 793-799.

LIU Rui , CAO Shuang, ZHANG Qiuyue, YIN Zhigang, FAN Changyou, TIAN Huali, HUANG Rantao. Analysis of Differentially Expressed Genes in Systemic Lupus Erythematosus and Prediction of Therapeutic Traditional Chinese Medicine[J]. CHINESE JOURNAL OF MEDICINAL GUIDE, 2022, 24(8): 793-799.

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