Characterization of Ferroptosis-Associated Subtypes in Psoriasis and the Potential of CHAC1 as a Diagnostic Biomarker Based on Machine Learning.

Purpose: Ferroptosis, a form of iron-dependent lipid peroxidation cell death. However, the mechanism of ferroptosis in psoriasis remains to be further investigated. Therefore, our research focuses on uncovering the role of ferroptosis in the pathogenesis of psoriasis and providing accurate biomarkers as therapeutic targets. Patients and Methods: We merged differentially expressed genes (DEGs) from the gene expression omnibus (GEO) with ferroptosis-related genes from FerrDb database. Key genes were further identified using weighted gene co-expression network analysis (WGCNA) and machine learning. Additionally, we used non-negative matrix factorization (NMF) clustering to identify two ferroptosis molecular subgroups. Results: CHAC1, PARP9 and LCN2 are identified as key ferroptosis-related genes in psoriasis. The psoriatic skin samples were divided into cluster 1 and cluster 2, with cluster 1 being the more severe subtype of psoriatic lesions. The expression of CHAC1 had the highest correlation with activated CD4 T cells, neutrophil, regulatory T cell (Tregs) and type 2 T helper cell (Th2), which were significantly enriched in cluster1. Conclusion: In conclusion, the ferroptosis associated diagnostic gene CHAC1 exacerbates psoriasis by regulating activated CD4 T cells, neutrophil, Tregs and Th2, serving as a reliable biomarker to predict patient survival.