Meta-analysis and de novo prediction of drug candidates in atopic dermatitis and psoriasis

Atopic dermatitis (AD) and psoriasis plaque (PP) are chronic inflammatory skin diseases that have a significant cutaneous and systemic disease impact and a poor health-related quality of life. Due to the lack of evidence related to severe AD in humans, this research attempted to identify potential new biomarkers associated with moderate AD. In addition, the interaction between identified genes with known medications was investigated. A meta-analysis was performed on several gene expression profile datasets to identify differentially expressed genes (DEGs) between AD and PP tissue samples and healthy tissue samples. Gene Set Enrichment Analysis (GSEA) was performed using clusterProfiler software. To investigate gene-drug interactions from different resources, the DGIdb online server was employed to construct the gene-drug networks. There were 5 and 91 DEGs between AD and PP compared to normal samples. Each condition yielded four overlapping genes, including GALNT6, IL37, BTC, and OGN. Mucin type O-glycan biosynthesis, other types of O-glycan biosynthesis, and growth factor activity in AD; Hepatitis C and NOD-like receptor, and defense response to symbiont in PP were demonstrated to be statistically significant. The interaction of STAT1, Pdcd1lg2, and CCNB1 genes with known medications was identified. Mild AD may have novel markers GALNT6, IL37, BTC, OGN, and CORIN. CLDN1, REG3A, GBP-1, IRF1, PLSCR1, and STAT1 might be novel markers of PP. AD and PP immune response might be regulated by miR-106b and miR-17.