Identification of Polyamine Metabolism-Related Biomarkers in Psoriasis: A Study Based on Transcriptomics and Single-Cell Sequencing

Abstract

Psoriasis (PS) is linked to altered polyamine metabolism, which may drive chronic inflammation and abnormal keratinocyte proliferation. We integrated transcriptomics and single-cell RNA sequencing (scRNA-seq) to identify polyamine metabolism-related genes (PMRGs) as biomarkers for PS and elucidate their mechanisms. Through the application of differential expression analysis, three machine learning algorithms, combined with receiver operating characteristic (ROC) analysis and expression quantification, biomarkers related to polyamine metabolism in PS were identified. Furthermore, the expression of these biomarkers was verified through western blotting. These biomarkers were subsequently incorporated into a diagnostic nomogram. Further investigations of these biomarkers included enrichment analysis and immune infiltration analysis. Additionally, scRNA-seq analysis was conducted to annotate the cell types in PS, providing insights into the cellular mechanisms underlying the progression of PS. In PS samples, biomarkers PSME2, PSMB5, PSMC4, PSMB10 and SMOX were significantly upregulated, achieving an area under the ROC curve (AUC) > 0.9 in GSE13355. Western blotting confirmed their upregulation, aligning with bioinformatics results. These biomarkers were closely associated with inflammation, cell proliferation, energy metabolism and signalling pathways. scRNA-seq identified 11 cell types, with mature dendritic cell (mDC) showing notable proportional differences between PS patients and controls, marking them as key cells. mDC exhibited distinct developmental trajectories with branching heterogeneity, featuring a reduction in early stages and an increase in later stages. Biomarker expression levels were higher in the later stages of mDC differentiation. The five PMRGs—PSME2, PSMB5, PSMC4, PSMB10 and SMOX—identified through comprehensive analyses, emerged as significant biomarkers for PS, providing promising diagnostic targets and mechanistic insights for the early detection and targeted treatment of PS.