基于生物信息学分析类风湿关节炎与急性心肌梗死共同差异基因及相关机制

Analysis of Common Differential Genes and Related Mechanisms of Rheumatoid Arthritis and Acute Myocardial Infarction Based on Bioinformatics

摘要: 目的：基于生物信息学分析类风湿关节炎(RA)与急性心肌梗死(AMI)共同差异基因、共同通路、免疫机制及潜在药物。方法：通过GEO数据库下载RA数据集(GSE77298)及AMI数据集(GSE66360)，应用R语言分别筛选RA及AMI数据集的差异表达基因(DEGs)。对DEGs进行GO和KEGG富集分析。利用韦恩图对RA和AMI差异表达基因取交集筛选共同DEGs，利用CytoScape软件构建共同DEGs的PPI网络识别参与疾病发生发展的关键基因(HubGene)。HubGene在外部数据集验证。对HubGene进行KEGG、GSEA富集分析并导入TRRUST数据库预测出转录调控因子，对HubGene行ssGSEA评估与免疫细胞关系。将关键基因导入DGIdb数据库寻找潜在治疗药物。结果：RA数据集共鉴定出250个DEGs，富集分析主要集中在免疫、趋化因子活性、细胞分泌等。AMI数据集共鉴定出438个DEGs，富集分析主要集中在免疫、炎症、感染等相关生物学改变。通过CytoScape筛选出关键基因IL1RN，对IL1RN进行单基因KEGG、GSEA富集分析，均富集到NF-κB信号通路，在TRRUST数据库预测出转录调控因子NFκB1，ssGSEA结果提示IL1RN与多种免疫细胞相关，DGIdb数据库得到甲氨蝶呤、双醋瑞因、低分子肝素、氟哌啶醇四种药物。结论：IL1RN可能是AS发生AMI的预测指标，而IL1RN与NFκB1存在负相关，进而影响NF-κB信号通路表达。并且IL1RN的表达与免疫细胞呈相关性，甲氨蝶呤、双醋瑞因、低分子肝素、氟哌啶醇可能是AS合并AMI的潜在药物。

Abstract: Objective: To analyze the common differential genes, common pathways, immune mechanisms and potential drugs between rheumatoid arthritis and acute myocardial infarction based on bioinformatics. Methods: RA dataset (GSE77298) and AMI dataset (GSE66360) were downloaded from the GEO database, and R language was used to screen differentially expressed genes (DEGs) in RA and AMI datasets. GO and KEGG enrichment analyses were performed for DEGs. Venn diagram was used to screen common DEGs between RA and AMI differentially expressed genes, and CytoScape software was used to construct PPI network of common DEGs to identify the HubGene involved in the occurrence and development of the disease. HubGene was validated on an external dataset. KEGG and GSEA enrichment analysis were performed on HubGene and imported into TRRUST database to predict transcription regulators. ssGSEA was used to evaluate the relationship between HubGene and immune cells. Key genes were imported into DGIdb database to find potential therapeutic drugs. Results: A total of 250 DEGs were identified in the RA dataset, and enrichment analysis mainly focused on immunity, chemokine activity, and cell secretion. A total of 438 DEGs were identified in the AMI dataset, and enrichment analysis mainly focused on immune, inflammation, infection and other related biological changes. The key gene IL1RN was screened out by CytoScape, and the KEGG and GSEA enrichment analysis of IL1RN showed that all of them were enriched in the NF-κB signaling pathway. The transcription regulator NFκB1 was predicted in TRRUST database. Four drugs were obtained from the drug-drug-gene interaction database (DGIdb): methotrexate, diacerein, tinzaparin sodium and haloperidol decanoate. Conclusion: IL1RN may be a predictor of AMI in AS patients, and IL1RN is negatively correlated with NFκB1, thereby affecting the expression of NF-κB signaling pathway. The expression of IL1RN is correlated with immune cells. Methotrexate, diacerein, tinzaparin sodium and haloperidol decanoate may be potential drugs for AS complicated with AMI.