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基于基因表达谱的生物信息学分析鉴定出参与皮肤红斑狼疮的关键基因和功能途径。

Bioinformatics analyses of gene expression profile identify key genes and functional pathways involved in cutaneous lupus erythematosus.

机构信息

Department of Rheumatology and Immunology, The Affiliated Hospital of Hubei Minzu University, Enshi, Hubei Province, China.

Hubei Provincial Key Laboratory of Occurrence and Intervention of Rheumatic Disease, The Affiliated Hospital of Hubei Minzu University, Enshi, Hubei Province, China.

出版信息

Clin Rheumatol. 2022 Feb;41(2):437-452. doi: 10.1007/s10067-021-05913-2. Epub 2021 Sep 23.

Abstract

BACKGROUND

Lupus erythematosus is an autoimmune disease that causes damage to multiple organs ranging from skin lesions to systemic manifestations. Cutaneous lupus erythematosus (CLE) is a common type of lupus erythematosus (LE), but its molecular mechanisms are currently unknown. The study aimed to explore changes in the gene expression profiles and identify key genes involved in CLE, hoping to uncover its molecular mechanism and identify new targets for CLE.

METHOD

We analyzed the microarray dataset (GSE109248) derived from the Gene Expression Omnibus (GEO) database, which was a transcriptome profiling of CLE cutaneous lesions. The differentially expressed genes (DEGs) were identified, and the functional annotation of DEGs was performed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) network was also constructed to identify hub genes involved in CLE.

RESULT

A total of 755 up-regulated DEGs and 405 down-regulated DEGs were identified. GO enrichment analysis showed that defense response to virus, immune response, and type I interferon signaling pathway were the most significant enrichment items in DEGs. The KEGG pathway analysis identified 51 significant enrichment pathways, which mainly included systemic lupus erythematosus, osteoclast differentiation, cytokine-cytokine receptor interaction, and primary immunodeficiency. Based on the PPI network, the study identified the top 10 hub genes involved in CLE, which were CXCL10, CCR7, FPR3, PPARGC1A, MMP9, IRF7, IL2RG, SOCS1, ISG15, and GSTM3. By comparison between subtypes, the results showed that ACLE had the least DEGs, while CCLE showed the most gene and functional changes.

CONCLUSION

The identified hub genes and functional pathways found in this study may expand our understanding on the underlying pathogenesis of CLE and provide new insights into potential biomarkers or targets for the diagnosis and treatment of CLE. Key Points • The bioinformatics analysis based on CLE patients and healthy controls was performed and 1160 DEGs were identified • The 1160 DEGs were mainly enriched in biological processes related to immune responses, including innate immune response, type I interferon signaling pathway, interferon-γ-mediated signaling pathway, positive regulation of T cell proliferation, regulation of immune response, antigen processing, and presentation via MHC class Ib and so on • KEGG pathway enrichment analysis indicated that DEGs were mainly enriched in several immune-related diseases and virus infection, including systemic lupus erythematosus, primary immunodeficiency, herpes simplex infection, measles, influenza A, and so on • The hub genes such as CXCL10, IRF7, MMP9, CCR7, and SOCS1 may become new markers or targets for the diagnosis and treatment of CLE.

摘要

背景

红斑狼疮是一种自身免疫性疾病,可导致皮肤损伤到全身表现等多种器官受损。盘状红斑狼疮(CLE)是红斑狼疮(LE)的常见类型,但目前其分子机制尚不清楚。本研究旨在探讨 CLE 中基因表达谱的变化,并鉴定关键基因,希望揭示其分子机制,并为 CLE 鉴定新的靶点。

方法

我们分析了来自基因表达综合数据库(GEO)的微阵列数据集(GSE109248),这是一个 CLE 皮肤损伤的转录组图谱。鉴定差异表达基因(DEGs),并使用基因本体论(GO)和京都基因与基因组百科全书(KEGG)途径富集分析对 DEGs 进行功能注释。还构建了蛋白质-蛋白质相互作用(PPI)网络,以鉴定 CLE 中涉及的枢纽基因。

结果

共鉴定出 755 个上调 DEGs 和 405 个下调 DEGs。GO 富集分析表明,防御病毒反应、免疫反应和 I 型干扰素信号通路是 DEGs 中最显著的富集项。KEGG 途径分析确定了 51 个显著富集途径,主要包括系统性红斑狼疮、破骨细胞分化、细胞因子-细胞因子受体相互作用和原发性免疫缺陷。基于 PPI 网络,研究鉴定了 CLE 中涉及的前 10 个枢纽基因,它们是 CXCL10、CCR7、FPR3、PPARGC1A、MMP9、IRF7、IL2RG、SOCS1、ISG15 和 GSTM3。通过亚型间的比较,结果表明 ACLE 的 DEGs 最少,而 CCLE 的基因和功能变化最多。

结论

本研究中发现的枢纽基因和功能途径可能扩展了我们对 CLE 潜在发病机制的理解,并为 CLE 的诊断和治疗提供了新的潜在生物标志物或靶点。关键点• 对来自 CLE 患者和健康对照者的基于生物信息学的分析进行了研究,并鉴定了 1160 个差异表达基因• 1160 个差异表达基因主要富集于与免疫反应相关的生物学过程,包括先天免疫反应、I 型干扰素信号通路、干扰素-γ介导的信号通路、T 细胞增殖的正调控、免疫反应的调节、抗原加工和呈递通过 MHC 类 Ib 等• KEGG 途径富集分析表明,差异表达基因主要富集于几种免疫相关疾病和病毒感染,包括系统性红斑狼疮、原发性免疫缺陷、单纯疱疹感染、麻疹、流感 A 等• CXCL10、IRF7、MMP9、CCR7 和 SOCS1 等枢纽基因可能成为 CLE 诊断和治疗的新标志物或靶点。

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