ArticleBiochemistry and biophysics reports2025
Integrated transcriptomics of multiple sclerosis peripheral blood mononuclear cells explored potential biomarkers for the disease.
Article in Biochemistry and biophysics reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Background: Despite their importance, blood RNAs have not been comprehensively studied as potential diagnostic markers for multiple sclerosis (MS). Herein, by the integration of GSE21942 and GSE203241 microarray profiles of peripheral blood mononuclear cells, this study explored potential biomarkers for the disease. Methods: After identification of differentially expressed genes (DEGs), functional enrichment analyses were performed, and PPI and miRNA-mRNA regulatory networks were constructed. After implementing weighted gene co-expression network analysis (WGCNA) and discovering MS-specific modules, the converging results of differential expression analysis and WGCNA were subjected to machine learning methods. Lastly, the diagnostic performance of the prominent genes was evaluated by receiver operating characteristic (ROC) analysis. Results: Conclusions: This study could not unveil promising blood biomarkers for MS, possibly due to a small sample size and unaccounted confounding factors. Considering PBMCs and blood specimens as valuable sources for the identification of biomarkers, further transcriptomic analyses are needed to discover potential biomarkers for the disease.
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