Screening and validation of differentially expressed genes in polymyositis

Abstract

Background: Polymyositis (PM), a prevalent inflammatory myopathy, currently lacks defined pathogenic mechanism. To illuminate its pathogenesis, we integrated bioinformatics and clinical specimens to examine potential aberrant gene expression patterns and their localization. Methods: We obtained GSE128470 and GSE3112 dataset from the Gene Expression Omnibus, performed Gene Set Enrichment Analysis (GSEA) and immune infiltration analysis using CiberSort, identified differentially expressed genes with Limma, conducted functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, constructed a Protein-Protein Interaction network, and identified hub genes using Cytoscape. ROC analysis evaluated hub gene diagnostic accuracy for PM, validated their expression levels with clinical specimens. Results: DEG analysis revealed 51 upregulated and 779 downregulated genes. Gene Ontology (GO) analysis implicated Type I interferon (IFN-Ⅰ) signaling, while KEGG pointed to cell adhesion molecule activation and oxidative phosphorylation inhibition. Protein-Protein Interaction (PPI) analysis identified 8 diagnosffftic hub genes. Clinical samples confirmed their upregulation in PM, especially IRF1 and IRF9 between muscle fibers. Different immune cell infiltrations were observed in PM patients versus controls. Conclusions: Our study explores potential pathogenic factors, diagnostic markers, and immune cells in PM, with a focus on verifying IRF1 and IRF9 upregulation in the IFN-I signaling pathway. These findings bear significance for PM diagnosis and treatment.

Keywords

• Polymyositis
• IFN-I
• DEGs
• HLA
• Bioinformatics