Integrated transcriptomics of multiple sclerosis peripheral blood mononuclear cells identified COPG1, RPN1, and KDM3B as potential biomarkers

Abstract

Among diagnostic techniques, RNA biomarkers have been poorly investigated for multiple sclerosis (MS). In this study, by the integration of GSE21942 and GSE203241 microarray profiles of peripheral blood mononuclear cells, potential biomarkers were explored. A comparison between 28 MS patients and 23 healthy controls led to the identification of 71 upregulated and 35 downregulated genes. Immune-related functional terms, particularly pathways linked to lymphocyte activation, were enriched with the differentially expressed genes (DEGs). Subsequently, key mRNAs and miRNAs were detected regarding their number of interactions in the miRNA-mRNA regulatory network. Weighted gene co-expression network analysis (WGCNA) detected a gene module highly enriched for neurodegenerative disorders. Central genes in the protein-protein interaction (PPI) network of this module were genes encoding various subunits of the respiratory chain complexes. 59 genes selected from converging results of differential expression analysis and WGCNA underwent machine learning methods and receiver operating characteristic (ROC) analysis. COPG1, RPN1, and KDM3B were subsequently identified as potential biomarkers based on their acceptable diagnostic efficacy in the integrated data, as well as in both GSE141804 and GSE146383 datasets as validation sets.