Department of Orthopedics, 900th Hospital of Joint Logistics Support Force, Fuzhou, China.
Arthritis Clinical and Research Center, Peking University People's Hospital, Beijing, China.
Front Immunol. 2022 Sep 15;13:1013322. doi: 10.3389/fimmu.2022.1013322. eCollection 2022.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of severe coronavirus disease 2019 (COVID-19). is one of the most common pathogenic bacteria in humans, rheumatoid arthritis (RA) is among the most prevalent autoimmune conditions. RA is a significant risk factor for SARS-CoV-2 and infections, although the mechanism of RA and SARS-CoV-2 infection in conjunction with infection has not been elucidated. The purpose of this study is to investigate the biomarkers and disease targets between RA and SARS-CoV-2 and infections using bioinformatics analysis, to search for the molecular mechanisms of SARS-CoV-2 and immune escape and potential drug targets in the RA population, and to provide new directions for further analysis and targeted development of clinical treatments.
The RA dataset (GSE93272) and the bacteremia (SAB) dataset (GSE33341) were used to obtain differentially expressed gene sets, respectively, and the common differentially expressed genes (DEGs) were determined through the intersection. Functional enrichment analysis utilizing GO, KEGG, and ClueGO methods. The PPI network was created utilizing the STRING database, and the top 10 hub genes were identified and further examined for functional enrichment using Metascape and GeneMANIA. The top 10 hub genes were intersected with the SARS-CoV-2 gene pool to identify five hub genes shared by RA, COVID-19, and SAB, and functional enrichment analysis was conducted using Metascape and GeneMANIA. Using the NetworkAnalyst platform, TF-hub gene and miRNA-hub gene networks were built for these five hub genes. The hub gene was verified utilizing GSE17755, GSE55235, and GSE13670, and its effectiveness was assessed utilizing ROC curves. CIBERSORT was applied to examine immune cell infiltration and the link between the hub gene and immune cells.
A total of 199 DEGs were extracted from the GSE93272 and GSE33341 datasets. KEGG analysis of enrichment pathways were NLR signaling pathway, cell membrane DNA sensing pathway, oxidative phosphorylation, and viral infection. Positive/negative regulation of the immune system, regulation of the interferon-I (IFN-I; IFN-α/β) pathway, and associated pathways of the immunological response to viruses were enriched in GO and ClueGO analyses. PPI network and Cytoscape platform identified the top 10 hub genes: RSAD2, IFIT3, GBP1, RTP4, IFI44, OAS1, IFI44L, ISG15, HERC5, and IFIT5. The pathways are mainly enriched in response to viral and bacterial infection, IFN signaling, and 1,25-dihydroxy vitamin D3. IFI44, OAS1, IFI44L, ISG15, and HERC5 are the five hub genes shared by RA, COVID-19, and SAB. The pathways are primarily enriched for response to viral and bacterial infections. The TF-hub gene network and miRNA-hub gene network identified YY1 as a key TF and hsa-mir-1-3p and hsa-mir-146a-5p as two important miRNAs related to IFI44. IFI44 was identified as a hub gene by validating GSE17755, GSE55235, and GSE13670. Immune cell infiltration analysis showed a strong positive correlation between activated dendritic cells and IFI44 expression.
IFI144 was discovered as a shared biomarker and disease target for RA, COVID-19, and SAB by this study. IFI44 negatively regulates the IFN signaling pathway to promote viral replication and bacterial proliferation and is an important molecular target for SARS-CoV-2 and immune escape in RA. Dendritic cells play an important role in this process. 1,25-Dihydroxy vitamin D3 may be an important therapeutic agent in treating RA with SARS-CoV-2 and infections.
严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引发了全球严重冠状病毒病 2019(COVID-19)大流行。金黄色葡萄球菌(S. aureus)是人类最常见的致病细菌之一,类风湿关节炎(RA)是最常见的自身免疫性疾病之一。RA 是 SARS-CoV-2 和 感染的重要危险因素,尽管 RA 和 SARS-CoV-2 感染与 感染相结合的机制尚未阐明。本研究的目的是利用生物信息学分析探讨 RA 和 SARS-CoV-2 和 感染之间的生物标志物和疾病靶点,寻找 SARS-CoV-2 在 RA 人群中免疫逃逸和潜在药物靶点的分子机制,为进一步分析和靶向开发临床治疗提供新的方向。
使用 RA 数据集(GSE93272)和 菌血症(SAB)数据集(GSE33341)分别获得差异表达基因集,并通过交集确定共同差异表达基因(DEGs)。利用 GO、KEGG 和 ClueGO 方法进行功能富集分析。利用 STRING 数据库构建 PPI 网络,利用 Metascape 和 GeneMANIA 确定并进一步研究前 10 个枢纽基因的功能富集。将前 10 个枢纽基因与 SARS-CoV-2 基因库进行交叉,确定 RA、COVID-19 和 SAB 共有的 5 个枢纽基因,并利用 Metascape 和 GeneMANIA 进行功能富集分析。利用 NetworkAnalyst 平台构建这 5 个枢纽基因的 TF-hub 基因和 miRNA-hub 基因网络。利用 GSE17755、GSE55235 和 GSE13670 验证枢纽基因,并利用 ROC 曲线评估其有效性。利用 CIBERSORT 分析枢纽基因与免疫细胞的关系。
从 GSE93272 和 GSE33341 数据集共提取 199 个 DEGs。KEGG 分析富集通路为 NLR 信号通路、细胞膜 DNA 感应通路、氧化磷酸化和病毒感染。GO 和 ClueGO 分析富集了正/负免疫调节、IFN-I(IFN-α/β)途径调节和免疫反应相关途径。PPI 网络和 Cytoscape 平台确定了前 10 个枢纽基因:RSAD2、IFIT3、GBP1、RTP4、IFI44、OAS1、IFI44L、ISG15、HERC5 和 IFIT5。这些通路主要富集在对病毒和细菌感染的反应、IFN 信号和 1,25-二羟维生素 D3 中。IFI44、OAS1、IFI44L、ISG15 和 HERC5 是 RA、COVID-19 和 SAB 共有的 5 个枢纽基因。这些通路主要富集在对病毒和细菌感染的反应中。TF-hub 基因网络和 miRNA-hub 基因网络确定 YY1 为关键 TF,hsa-mir-1-3p 和 hsa-mir-146a-5p 为与 IFI44 相关的两个重要 miRNA。IFI44 通过验证 GSE17755、GSE55235 和 GSE13670 被确定为枢纽基因。免疫细胞浸润分析显示,激活的树突状细胞与 IFI44 表达之间存在强烈的正相关关系。
本研究发现 IFI144 是 RA、COVID-19 和 SAB 的共同生物标志物和疾病靶点。IFI44 通过负向调节 IFN 信号通路促进病毒复制和细菌增殖,是 SARS-CoV-2 和 RA 中 免疫逃逸的重要分子靶点。树突状细胞在这个过程中起着重要作用。1,25-二羟维生素 D3 可能是治疗 SARS-CoV-2 和 感染 RA 的重要治疗药物。