Department of Education and Training, CHA Bundang Medical Center, Seongnam, Republic of Korea.
Department of Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Clin Rheumatol. 2023 Oct;42(10):2799-2809. doi: 10.1007/s10067-023-06597-6. Epub 2023 Jun 27.
INTRODUCTION/OBJECTIVES: This study aimed to identify differentially expressed genes (DEGs) of systemic lupus erythematosus (SLE) using gene expression-based computational methodologies to analyze disease-immune interactions, which affect the development and progression of SLE.
Twenty-six patients with SLE and 46 healthy controls were selected from the Gene Expression Omnibus (GEO) database. The significantly enriched immune and virus-related gene lists were computed and visualized by using the DEGs from the gene set enrichment analysis (GSEA). Quantification of 38 immune cells was performed in determining the impact of immune cells on the virus mediated immunity in SLE by using ImmQuant algorithm.
Thirty-nine upregulated and 57 downregulated were identified in SLE patient compared to the healthy controls. Upregulated genes were significantly implicated in Gene Ontology gene sets as cytokine mediated signaling, secretion, and exocytosis in immune response pathways in 26 female SLE patients. In addition, these genes were enriched in hepatitis C, influenza A, measles, Epstein-Barr virus, and herpes simplex virus 1 infection in Kyoto Encyclopedia of Genes and Genomes pathways. Especially, FCGR1A, IRF7, OAS2, CAMP, MX1, OAS3, OAS1, DEFA3, ISG15, and RSAD2 were involved in virus mediated SLE mechanism, and the expression for OAS1, OAS2, and IRF7 was closely associated with the quantities of colony forming unit-monocyte and colony forming unit-granulocyte.
Identifying virus-mediated SLE genes and quantifies of immune cells were used to understand the pathological process and perform early diagnosis of female SLE, and will lead to clinical tools for treating SLE in patients. Key Points • Using gene expression-based computational methodologies, the 57 immune and viral genes were significantly upregulated in 26 SLE patients. • The identified three key viral genes such as OAS1, OAS2, and IF7 were closely associated with colony-forming unit-monocytes and colony-forming unit-granulocytes, which affect the virus mediated immunity in SLE. • The viral genes and quantifies of immune cells are useful in understanding pathogenesis of SLE, and this will provide clinical strategies of potential treatment choices in SLE patients.
简介/目的:本研究旨在通过基于基因表达的计算方法识别系统性红斑狼疮(SLE)的差异表达基因(DEGs),以分析影响 SLE 发生和发展的疾病免疫相互作用。
从基因表达综合数据库(GEO)中选择 26 例 SLE 患者和 46 例健康对照者。通过基因集富集分析(GSEA)中的 DEGs 计算和可视化显著富集的免疫和病毒相关基因列表。使用 ImmQuant 算法,对 38 种免疫细胞进行定量,以确定免疫细胞对 SLE 中病毒介导免疫的影响。
与健康对照组相比,SLE 患者中发现 39 个上调和 57 个下调基因。上调基因在 26 名女性 SLE 患者的免疫反应途径中的细胞因子介导信号转导、分泌和胞吐等基因本体论基因集中具有显著意义。此外,这些基因在京都基因与基因组百科全书通路中富集了丙型肝炎、甲型流感、麻疹、Epstein-Barr 病毒和单纯疱疹病毒 1 感染。特别是,FCGR1A、IRF7、OAS2、CAMP、MX1、OAS3、OAS1、DEFA3、ISG15 和 RSAD2 参与了病毒介导的 SLE 机制,OAS1、OAS2 和 IRF7 的表达与集落形成单位单核细胞和集落形成单位粒细胞的数量密切相关。
鉴定病毒介导的 SLE 基因并定量免疫细胞有助于了解女性 SLE 的病理过程并进行早期诊断,并将为患者的 SLE 治疗提供临床工具。关键点:· 使用基于基因表达的计算方法,在 26 例 SLE 患者中发现了 57 个显著上调的免疫和病毒基因。· 鉴定的三个关键病毒基因,如 OAS1、OAS2 和 IF7,与影响 SLE 中病毒介导免疫的集落形成单位单核细胞和集落形成单位粒细胞密切相关。· 病毒基因和免疫细胞的定量有助于了解 SLE 的发病机制,并为 SLE 患者提供潜在治疗选择的临床策略。