The epidermal infiltration of neutrophils is a hallmark of psoriasis (PSO) and its activation leads to the release of neutrophil extracellular traps (NETs). However, the molecular mechanism of NETsrelated genes (NETRGs) has not been extensively studied in PSO. To define NETs-related-biomarkers for PSO. The GSE13355 and GSE78097 datasets, and NETRGs gene set were included in this study. The datasets used in this study were all microarray data. The weighted gene co-expression network analysis (WGCNA) and machine learning algorithms were used to mine key genes. Later on, singlegene gene set enrichment analysis (GSEA) and immune infiltration analysis were implemented. Finally, the expression of key genes was verified using quantitative real-time fluorescence PCR (qRT-PCR). A total of 3 key genes (S100A9, CLEC7A, and CXCR4) were derived, and they all had excellent diagnostic performance. The single-gene GSEA enrichment results indicated that the key genes were mainly enriched in the chemokine signaling pathway and humoral immune response in the high-expression group, while focal adhesion was enriched in the low-expression group. The correlation analysis indicated that all key genes were strongly negatively correlated with resting mast cells and TGF-β family member receptor, while they were strongly positively correlated with activated CD4 memory T cells and antigen processing and presentation. Lastly, the experimental results showed that the expression trends of key genes were consistent with public database. In this study, we successfully screened three potential PSO diagnostic genes (S100A9, CLEC7A and CXCR4) that were closely related to NETs, and these findings not only provided new molecular marker candidates for the precise diagnosis of PSO patients, but also revealed possible future therapeutic targets. However, further indepth research and validation were necessary.
