Abstract
BACKGROUND: Pyroptosis and hypoxia play pivotal roles in the onset and progression of psoriasis, though their interactions remain poorly understood. This study aims to clarify the involvement of pyroptosis-related genes (PRGs) and hypoxia-related genes (HRGs) in psoriasis pathogenesis. METHODS: Psoriasis-related datasets were analyzed alongside PRGs and HRGs. Differentially expressed genes (DEGs) between psoriasis and control samples were first identified. Expression levels of PRGs and HRGs were used to compute respective scores, which facilitated the identification of key module genes. Candidate genes were then derived by intersecting DEGs with key module genes. Biomarkers were selected using machine learning algorithms, gene expression analysis, and receiver operating characteristic (ROC) curves. A nomogram was constructed and subsequently validated. Additional analyses were conducted to investigate the underlying mechanisms. Finally, biomarker expression was assessed via real-time reverse transcriptase-polymerase chain reaction (RT-qPCR). RESULTS: PI3 and LCE3D, exhibiting significantly elevated expression and an area under the curve (AUC) greater than 0.9, were identified as biomarkers. The nomogram constructed with these biomarkers accurately predicted the risk of psoriasis. Enrichment analyses revealed that the cytosolic DNA-sensing pathway, focal adhesion, and oxidative phosphorylation were significantly associated with these biomarkers. Immune infiltration analysis highlighted 20 distinct cell types with significant expression differences between psoriasis and control samples. Furthermore, 18 potential therapeutic drugs were predicted based on the biomarkers. RT-qPCR validation confirmed elevated biomarker expression in psoriasis. CONCLUSION: This study identified two biomarkers, PI3 and LCE3D, linked to pyroptosis and hypoxia in psoriasis. These findings provide valuable insights that could guide future therapeutic strategies for psoriasis.