Identification of hub biomarkers and immune cell infiltration in polymyositis and dermatomyositis

Si Chen, Haolong Li, H. Zhan, Xiaoli Zeng, Hui Yuan, Yongzhe Li
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引用次数: 4

Abstract

Objective: Polymyositis (PM) and dermatomyositis (DM) are heterogeneous disorders. However, the etiology of PM/DM development has not been thoroughly clarified. Methods: Gene expression data of PM/DM were obtained from Gene Expression Omnibus. We used robust rank aggregation (RRA) to identify differentially expressed genes (DEGs). Gene Ontology functional enrichment and pathway analyses were used to investigate potential functions of the DEGs. Weighted gene co-expression network analysis (WGCNA) was used to establish a gene co-expression network. CIBERSORT was utilized to analyze the pattern of immune cell infiltration in PM/DM. Protein–protein interaction (PPI) network, Venn, and association analyses between core genes and muscle injury were performed to identify hub genes. Receiver operating characteristic analyses were executed to investigate the value of hub genes in the diagnosis of PM/DM, and the results were verified using the microarray dataset GSE48280. Results: Five datasets were included. The RRA integrated analysis identified 82 significant DEGs. Functional enrichment analysis revealed that immune function and the interferon signaling pathway were enriched in PM/DM. WGCNA outcomes identified MEblue and MEturquoise as key target modules in PM/DM. Immune cell infiltration analysis revealed greater macrophage infiltration and lower regulatory T-cell infiltration in PM/DM patients than in healthy controls. PPI network, Venn, and association analyses of muscle injury identified five putative hub genes: TRIM22, IFI6, IFITM1, IFI35, and IRF9. Conclusions: Our bioinformatics analysis identified new genetic biomarkers of the pathogenesis of PM/DM. We demonstrated that immune cell infiltration plays a pivotal part in the occurrence of PM/DM.
多发性肌炎和皮肌炎中心生物标志物和免疫细胞浸润的鉴定
目的:多发性肌炎(PM)和皮肌炎(DM)是一种异质性疾病。然而,PM/DM发展的病因尚未完全澄清。方法:从Gene expression Omnibus获取PM/DM的基因表达数据。我们使用鲁棒秩聚集(RRA)来识别差异表达基因(DEGs)。通过基因本体功能富集和通路分析,研究了deg的潜在功能。采用加权基因共表达网络分析法(Weighted gene co-expression network analysis, WGCNA)建立基因共表达网络。采用CIBERSORT分析PM/DM免疫细胞浸润模式。通过蛋白质-蛋白质相互作用(PPI)网络、Venn和核心基因与肌肉损伤之间的关联分析来确定枢纽基因。进行受试者工作特征分析,探讨hub基因在PM/DM诊断中的价值,并使用微阵列数据集GSE48280对结果进行验证。结果:共纳入5个数据集。RRA综合分析鉴定出82个显著的deg。功能富集分析显示PM/DM的免疫功能和干扰素信号通路富集。WGCNA结果确定MEblue和MEturquoise是PM/DM的关键靶模块。免疫细胞浸润分析显示PM/DM患者的巨噬细胞浸润高于健康对照组,而调节性t细胞浸润低于健康对照组。肌肉损伤的PPI网络、Venn和关联分析确定了五个假定的中枢基因:TRIM22、IFI6、IFITM1、IFI35和IRF9。结论:我们的生物信息学分析发现了PM/DM发病机制的新的遗传生物标志物。我们证明免疫细胞浸润在PM/DM的发生中起关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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