The SELP, CD93, IL2RG, and VAV1 Genes Associated with Atherosclerosis May Be Potential Diagnostic Biomarkers for Psoriasis - Liu S; Liu F; Zhang Z; Zhuang Z; Yuan X; Chen Y (Dove Medical Press, 2023)
Shougang Liu,1,* Fanghua Liu,1,2,* Zeqiao Zhang,1 Zhe Zhuang,1,2 Xiuqing Yuan,1 Yongfeng Chen1,2 1Department of Dermatology, Dermatology Hospital of Southern Medical University, Guangzhou, People's Republic of China; 2Department of Dermatology, Guangdong Medical University, Zhanjiang, People's Republic of China*These authors contributed equally to this workCorrespondence: Yongfeng Chen, Dermatology Hospital of Southern Medical University, No. 2, LuJing Road, Guangzhou, Guangdong Province, 510091, People's Republic of China, Tel +86 13802920269, Email gdcyf@163.comPurpose: Psoriasis and atherosclerosis are immunometabolic diseases. This study aimed to integrate bioinformatics and updated public resources to find potential biological markers associated with atherosclerosis that can cause psoriasis.Patients and Methods: Microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened, and functional enrichment analysis was performed. We identified psoriasis and atherosclerosis common immune-related genes (PA-IRGs) by overlapping immune-related genes (IRGs) with genes in the module most associated with psoriasis and atherosclerosis obtained by weighted gene co-expression network analysis (WGCNAs). Receiver operating characteristic (ROC) was conducted to evaluate the predictive ability. The skin expression levels of diagnostic biomarkers were further verified by immunohistochemical staining. CIBERSORT, single-sample gene set enrichment analysis (ssGSEA), and Pearson's correlation analysis were applied to evaluate immune and lipid metabolism relationships in psoriatic tissues. In addition, a lincRNA-miRNA-mRNA network was constructed to find the pathogenesis in which diagnostic markers may be involved.Results: Four PA-IRGs (SELP, CD93, IL2RG, and VAV1) demonstrated the optimal diagnostic value, with an AUC above 0.8. The immune cell infiltration analysis showed that dendritic resting cells, NK cell activation, neutrophils, macrophages M2, macrophages M0, and B-cell memory were highly abundant in psoriasis. Immune response analysis showed that TNF family members, chemokine receptors, interferons, natural killer cells, and TGF-β family members might be involved in psoriasis. Diagnostic biomarkers are strongly associated with various infiltrating immune cells, immune responses, and lipid metabolism. A lincRNA-miRNA-mRNA regulatory network consisting of 31 lincRNAs and 23 miRNAs was constructed. LINC00662 is involved in modulating four diagnostic biomarkers.Conclusion: This study identified atherosclerosis-related genes SELP, CD93, VAV1, and IL2RG as potential psoriasis diagnostic markers. Provide novel insights into the possible regulatory mechanisms involved in psoriasis.Keywords: psoriasis, atherosclerosis, biomarker, immune, lipid metabolism, ceRNA network