Background: Psoriasis is a common chronic skin inflammatory disease. Understanding the pathogenesis of psoriasis and identifying novel therapeutic targets are under investigation.
Methods: Gene expression profiles were obtained from GSE13355, GSE30999 and GSE54456 datasets to identify differentially expressed genes (DEGs) between psoriasis and normal controls. Enrichment analysis was used to identify the biological functions and pathways of common genes from three groups of DEGs. Protein-protein interaction (PPI) network was then constructed to identify key genes according to degree of connectivity. Expression of genes was detected by the method of qRT-PCR and immunohistochemistry. The infiltration of immune cells of psoriasis were quantified and detected by flow cytometry.
Results: A total of 146 common genes were identified between psoriasis and normal controls. They were significantly enriched in IL-17, chemokine, and NOD-like receptor (NLR) signaling pathway. Ten key genes were selected with bigger degree of connectivity through PPI network, and ARG1 and CXCL2 had better predictive ability based on ROC curves. Increased expression of ARG1 and CXCL2 in psoriasis patients were verified by qRT-PCR and immunohistochemistry method. In addition, a lot of immune cells were upregulated in psoriasis compared to healthy controls through ssGSEA and flow cytometry.
Conclusion: ARG1 and CXCL2 may serve as biomarkers and potential therapy for psoriasis. This may be related to the immune response and NLR pathway.
Keywords: ARG1; CXCL2; NOD-like receptor; bioinformatics; psoriasis.