Abstract：
BACKGROUND: Systemic Lupus Erythematosus (SLE) is a multifactorial and complex immune disease; however, the relevance of COVID-19 infection in SLE patients remains uncertain.
OBJECTIVE: This study aims to explore the key candidate genes and pathways in patients with SLE. It also seeks to employ bioinformatics analysis to unravel the molecular signatures inherent in both SLE and COVID-19 patients. The ultimate aim is to identify potential targets and markers specifically relevant to SLE patients who contract SARS-CoV-2.
METHODS: Datasets (GSE12374, GSE20864, GSE61635, GSE81622, and GSE144390) from the Gene Expression Omnibus (GEO) database were analyzed using Robust Rank Aggregation (RRA) method to identify differential expression genes (DEGs) in SLE patients compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, tissue-specific gene analysis, and Protein-protein interaction (PPI) network were performed. Finally, the Venn diagram was employed to identify the intersections of COVID-19 genes, serving as potential targets for SLE patients with COVID-19 infection.
RESULTS: A total of 154 DEGs were discovered, with GO enrichment indicating a predominant involvement in the defense response against the virus (P<0.001). KEGG pathway analysis showed enrichment in the NOD-like receptor signaling pathway and coronavirus disease, specifically COVID-19 (P<0.001). Tissue-specific genes related to the hematological and immune systems were emphasized (74%). The PPI network highlighted 22 genes, and 5 key genes, namely, IFIT1, IFIT3, MX1, MX2, and OAS3, which were identified after intersecting with COVID-19 patients\' data.
CONCLUSIONS: IFIT1, IFIT3, MX1, MX2, and OAS3 exhibiting differential expression, as well as the pathways associated with COVID-19, could potentially function as biomarkers and therapeutic targets for individuals with SLE infected with COVID-19.
OBJECTIVE: This study aims to explore the key candidate genes and pathways in patients with SLE. It also seeks to employ bioinformatics analysis to unravel the molecular signatures inherent in both SLE and COVID-19 patients. The ultimate aim is to identify potential targets and markers specifically relevant to SLE patients who contract SARS-CoV-2.
METHODS: Datasets (GSE12374, GSE20864, GSE61635, GSE81622, and GSE144390) from the Gene Expression Omnibus (GEO) database were analyzed using Robust Rank Aggregation (RRA) method to identify differential expression genes (DEGs) in SLE patients compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, tissue-specific gene analysis, and Protein-protein interaction (PPI) network were performed. Finally, the Venn diagram was employed to identify the intersections of COVID-19 genes, serving as potential targets for SLE patients with COVID-19 infection.
RESULTS: A total of 154 DEGs were discovered, with GO enrichment indicating a predominant involvement in the defense response against the virus (P<0.001). KEGG pathway analysis showed enrichment in the NOD-like receptor signaling pathway and coronavirus disease, specifically COVID-19 (P<0.001). Tissue-specific genes related to the hematological and immune systems were emphasized (74%). The PPI network highlighted 22 genes, and 5 key genes, namely, IFIT1, IFIT3, MX1, MX2, and OAS3, which were identified after intersecting with COVID-19 patients\' data.
CONCLUSIONS: IFIT1, IFIT3, MX1, MX2, and OAS3 exhibiting differential expression, as well as the pathways associated with COVID-19, could potentially function as biomarkers and therapeutic targets for individuals with SLE infected with COVID-19.
摘要：
背景：系统性红斑狼疮（SLE）是一种多因素复杂的免疫疾病；SLE患者中COVID-19感染的相关性仍不确定。
目的：本研究旨在探索SLE患者的关键候选基因和通路。它还寻求利用生物信息学分析来揭示SLE和COVID-19患者固有的分子特征。最终目的是确定与感染SARS-CoV-2的SLE患者特别相关的潜在靶标和标志物。
方法：使用稳健秩汇总（RRA）方法分析了来自基因表达综合（GEO）数据库的数据集（GSE12374，GSE20864，GSE61635，GSE81622和GSE144390），以鉴定SLE患者与健康个体的差异表达基因（DEG）。基因本体论（GO）和京都基因和基因组百科全书（KEGG）途径分析，组织特异性基因分析，进行蛋白质-蛋白质相互作用(PPI)网络。最后,维恩图用于确定COVID-19基因的交叉点，作为患有COVID-19感染的SLE患者的潜在目标。
结果：共发现154个DEG，GO富集表明主要参与针对病毒的防御反应(P<0.001)。KEGG通路分析显示NOD样受体信号通路和冠状病毒疾病的富集，特别是COVID-19（P<0.001）。强调了与血液学和免疫系统相关的组织特异性基因（74％）。PPI网络突出了22个基因，和5个关键基因，即,IFIT1、IFIT3、MX1、MX2和OAS3，与COVID-19患者数据相交后鉴定。
结论：IFIT1、IFIT3、MX1、MX2和OAS3表现出差异表达，以及与COVID-19相关的通路，可能作为感染COVID-19的SLE患者的生物标志物和治疗靶标。
目的：本研究旨在探索SLE患者的关键候选基因和通路。它还寻求利用生物信息学分析来揭示SLE和COVID-19患者固有的分子特征。最终目的是确定与感染SARS-CoV-2的SLE患者特别相关的潜在靶标和标志物。
方法：使用稳健秩汇总（RRA）方法分析了来自基因表达综合（GEO）数据库的数据集（GSE12374，GSE20864，GSE61635，GSE81622和GSE144390），以鉴定SLE患者与健康个体的差异表达基因（DEG）。基因本体论（GO）和京都基因和基因组百科全书（KEGG）途径分析，组织特异性基因分析，进行蛋白质-蛋白质相互作用(PPI)网络。最后,维恩图用于确定COVID-19基因的交叉点，作为患有COVID-19感染的SLE患者的潜在目标。
结果：共发现154个DEG，GO富集表明主要参与针对病毒的防御反应(P<0.001)。KEGG通路分析显示NOD样受体信号通路和冠状病毒疾病的富集，特别是COVID-19（P<0.001）。强调了与血液学和免疫系统相关的组织特异性基因（74％）。PPI网络突出了22个基因，和5个关键基因，即,IFIT1、IFIT3、MX1、MX2和OAS3，与COVID-19患者数据相交后鉴定。
结论：IFIT1、IFIT3、MX1、MX2和OAS3表现出差异表达，以及与COVID-19相关的通路，可能作为感染COVID-19的SLE患者的生物标志物和治疗靶标。
