Exploration of ferroptosis-related genes and molecular mechanisms in psoriasis and atherosclerosis

AbstractObjective The purpose of this work is to look into the molecular mechanisms underlying the main ferroptosis-related genes in psoriasis (PsD) and atherosclerosis (AS). Methods Download the dataset between PsD patients and normal group (GSE30999) from the GEO database, while obtaining the dataset between AS patients and normal group (GSE100927). Using R software and the limma package in Bioconductor, differentially expressed genes (DE-FRG) were obtained. On the intersecting DE-FRG, enrichment analyses using GO and KEGG were conducted. The functional interactions between DE-FRG were then examined using a protein-protein interaction (PPI) network that was built using the STRING database. In order to analyze the relationship between infiltrating immune cells and Hub genes, the immune cell infiltration in PsD and AS tissues was assessed using CIBERSORT. The DGIdb database was utilized to choose potential Hub gene medication candidates. Finally, a network of lncRNA, miRNA, and mRNA associated to Hub gene was developed. Results 133 DE-FRGs in total, including 67 up-regulated genes and 66 down-regulated genes, were examined. As a total of the screening, 215 DEGs—including 171 up-regulated genes and 44 down-regulated genes—were obtained. DE-FRG was found to be strongly enriched for the FOXO signaling pathway, ferroptosis, fluid shear stress and atherosclerosis, mTOR signaling pathway, relaxin signaling pathway, and AMPK signaling pathway, according to functional enrichment analysis. It was considerably enriched for chemokines, signaling receptor activators, granulocyte chemotactic response, lipopolysaccharide metabolism, and mesovirus defense. Eight genes, including PTEN, STAT3, MAPK3, SIRT1, IL6, HRAS, EGFR, and PPARG, were subsequently included to the Cytoscape Hubba plug-in and the ROC diagnostic curve as Hub genes. Additionally, 222 medicines that target 8 marker genes in total were obtained. On the other hand, the ceRNA network, which was based on Hub genes, revealed intricate regulatory relationships. Additionally, CIBERSORT analysis demonstrated that PTEN, STAT3, MAPK3, SIRT1, IL6, HRAS, EGFR, and PPARG alterations in the immunological milieu of AS and PsD patients may be connected. Conclusion The results could lead to new understandings of the pathogenesis of PsD and AS as well as the discovery of new ferroptosis genes that could be used as potential therapeutic targets in clinical settings or as widely representative reference markers.