目的:研究多发性肌炎(PM)相关基因表达谱的变异性,探索PM潜在的分子机制,并预测新的干预目标。
方法:描述性研究。研究的地点和持续时间:风湿病科,台州市立医院,台州,中国,2023年8月至11月。
方法:从基因表达综合(GEO)中提取三个微阵列数据集(GSE3112、GSE39454和GSE128470)。这项研究的分析涉及与正常样品相比,在PM中鉴定差异表达基因(DEG)。富集分析,基因-microRNA,基因转录因子(TF),和蛋白质-蛋白质相互作用(PPI)网络研究,以确定枢纽基因和相关途径。此外,药物-基因相互作用数据库(DGIdb)用于预测治疗药物.
结果:确定了88个DEG。富集分析结果强调了下调的DEGs在抗原加工和呈递中的显著参与。基于PPI网络,选择了七个具有高连接度的hub基因,包括一个分化簇74(CD74),人类白细胞抗原(HLA)-DPA1,HLA-B,鸟苷酸结合蛋白1(GBP1),重组2',5'-寡腺苷酸合成酶1(OAS1),HLA-C,HLA-E
结论:这项研究筛选出核心基因,预计的前瞻性治疗药物,在PM和正常样本之间发现DEG,并为进一步研究PM的可能机制和治疗靶点提供了新的视角。
背景:多发性肌炎,DEGs,Hub基因,生物信息学,潜在的治疗剂。
OBJECTIVE: To investigate the variability in the expression profile of genes associated with
polymyositis (PM), explore the potential molecular mechanisms underlying PM, and predict novel targets for intervention.
METHODS: Descriptive study. Place and Duration of the Study: Department of Rheumatology, Taizhou Municipal Hospital, Taizhou, China, from August to November 2023.
METHODS: Three microarray datasets (GSE3112, GSE39454, and GSE128470) were extracted from the gene expression omnibus (GEO). The analysis of this research involved identifying the differentially expressed genes (DEGs) in PM compared to normal samples. Enrichment analysis, gene-microRNA, gene-transcription factor (TF), and protein-protein interaction (PPI) network studies were conducted to identify hub genes and relevant pathways. Additionally, the drug-gene interaction database (DGIdb) was used to predict therapeutic medications.
RESULTS: Eighty-eight DEGs were identified. The enrichment analysis results highlighted the significant involvement of downregulated DEGs in antigen processing and presentation. Based on the PPI networks, seven hub genes with high connectivity degrees were selected including a cluster of differentiation 74 (CD74), human leukocyte antigen (HLA)-DPA1, HLA-B, guanylate-binding protein 1 (GBP1), recombinant 2\', 5\'-oligoadenylate synthetase 1 (OAS1), HLA-C, and HLA-E.
CONCLUSIONS: This research screened-out core genes, projected prospective therapeutic medications, discovered DEGs between PM and normal samples, and offered fresh perspectives for additional research into the possible mechanism and therapeutic targets of PM.
BACKGROUND: Polymyositis, DEGs, Hub genes, Bioinformatics, Potential therapeutic agents.