痛风和动脉粥样硬化共同差异基因的生物信息学分析

摘要/Abstract

摘要： 目的：比较分析痛风（gout）和动脉粥样硬化（AS）的共同差异基因、共同通路和关键基因，为Gout和AS共同发病机制研究提供参考。方法：通过GEO数据库获取编号为GSE160170和GSE97210的基因表达数据集。利用Perl和R语言等工具对基因表达数据集进行重注释。利用R语言中的“limma”包筛选gout和AS的差异表达基因并取交集。利用STRING数据库和Cytoscape软件对交集差异基因进行蛋白互作网络构建与模块构建，筛选出关键基因（HubGene）。通过TRRUST数据库获得调控HubGene的转录因子(TF)。最后利用R软件中“cluster Profiler”包对HubGene进行GO和KEGG富集分析。结果：筛选得到gout和AS的交集差异基因231个。通过MCODE插件获得了2个紧密连接的基因模块，包含20个基因。通过cytoHubba插件的Degree算法，获得了前10个基因。两者交集后，筛选出10个重要的HubGene，包含CCL3、PTGS2、FOS、NLRP3、CXCL1、IL-10、IL-1B、IL-1A、CXCL8与CXCL2。基于TRRUST数据库，本研究发现有30个转录因子可能调控这些HubGene的表达，其中FOS既可作为转录因子，也可作为HubGene关键基因。GO富集显示，其主要涉及细胞对生物刺激的反应、白细胞游出、发热、脂多糖反应等。KEGG富集显示，其主要参与类风湿性关节炎、NOD-样受体信号通路、酒精性肝疾病、脂质和动脉粥样硬化、IL-17信号通路、百日咳、阿米巴病、耶尔森氏菌感染、Toll-样受体信号通路、C型凝集素受体信号通路、趋化因子信号通路、NF-kB信号通路、破骨细胞分化、多种细菌病毒感染、TNF信号通路等。结论：本研究确定了Gout和AS的10个共同关键基因（CCL3、PTGS2、FOS、NLRP3、CXCL1、IL-10、IL-1B、IL-1A、CXCL8与CXCL2），强调了趋化因子和细胞因子、炎症和免疫途径在这两种疾病中的重要作用。这些关键基因和共同的途径可能为进一步探索Gout合并AS靶向治疗的新方法开拓思路。

关键词: 痛风, 动脉粥样硬化, 生物信息学, 差异表达基因, 关键基因

Abstract: Objective： To compare and analyze the common differential genes (DEGs)， common pathways and key genes of gout and atherosclerosis (AS)， so as to provide reference for the study of the common pathogenesis of gout and AS. Methods： Obtain gene expression datasets numbered GSE160170 and GSE97210 from the GEO database. Use tools such as Perl and R language to reannotate gene expression datasets. Use the “limma” package in R language to screen for differentially expressed genes in gout and AS， and obtain intersections. Using the STRING database and Cytoscape software， protein protein interaction networks (PPI) and module construction were performed on intersecting differentially expressed genes (CODEGs) to screen out key genes (HubGene). Obtain the transcription factor (TF) that regulates HubGene through the TRRUST database. Finally， HubGene was analyzed for GO and KEGG enrichment using the “cluster Profiler” package in R software. Results： 231 intersection differentially expressed genes were screened for gout and AS. Two tightly connected gene modules containing 20 genes were obtained through the MCODE plugin. The top 10 genes were obtained through the degree correlation algorithm of the cytoHubba plugin. After the intersection of the two， 10 important HubGenes were selected， including CCL3， PTGS2， FOS， NLRP3， CXCL1， IL-10， IL-1B， IL-1A， CXCL8， and CXCL2. Based on the TRRUST database， we found that 30 transcription factors may regulate the expression of these HubGenes， with FOS serving as both a transcription factor and Key genes. GO enrichment shows that it mainly involves cell responses to biological stimuli， leukocyte migration， fever， and lipopolysaccharide reactions. KEGG enrichment shows that it is mainly involved in rheumatoid arthritis， NOD like receptor signaling pathway， alcoholic liver disease， lipid and atherosclerosis， IL-17 signaling pathway， pertussis， amebiasis， Yersinia infection， Toll- like receptor signaling pathway， C-agglutinin receptor signaling pathway， chemokine signaling pathway， NF-kB signaling pathway， osteoclast differentiation， multiple bacterial and viral infections， TNF signaling pathway， etc. Conclusion： The study identified 10 common key genes for gout and atherosclerosis (CCL3， PTGS2， FOS， NLRP3， CXCL1， IL-10， IL-1B， IL-1A， CXCL8 and CXCL2)， emphasized the important roles of chemokines and cytokines， inflammation， and immune pathways in these two diseases. These key genes and common pathways may open up new ideas for further exploration of new targeted therapies for gout combined with atherosclerosis.

Key words: font-size:medium, ">Gout； Atherosclerosis； Bioinformatics； Differentially expressed genes； Hub genes

中图分类号:

邵子晨, 汪士裕, 邓琴琴, 程凌, 孙伟康, 万刚平, 黄鑫. 痛风和动脉粥样硬化共同差异基因的生物信息学分析[J]. 中国医药导刊, 2023, 25(8): 818-825.

SHAO Zichen, WANG Shiyu, DENG Qinqin, CHENG Ling, SUN Weikang, WAN Gangping, HUANG Xin. Bioinformatics Analysis of Common Differential Genes Between Gout and Atherosclerosis[J]. CHINESE JOURNAL OF MEDICINAL GUIDE, 2023, 25(8): 818-825.

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