Bioinformatics analysis of genes related to uveitis and differential gene expression in a model of experimental autoimmune uveitis

Uveitis is a sight-threatening disease in which autoimmune and inflammatory reactions play a central role. This study aimed to identify key genes involved in the pathogenesis of uveitis using bioinformatics approaches and to validate their expression in a rat model of experimental autoimmune uveitis (EAU). The GSE66936 microarray dataset, comprising transcriptomes of CD14 and CD16 monocytes from five patients with uveitis and four healthy donors, was downloaded from the Gene Expression Omnibus, and known uveitis-related targets were retrieved from six disease-gene databases. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A protein-protein interaction network was constructed using STRING, and hub genes were screened with Cytoscape and evaluated by receiver operating characteristic (ROC) curve analysis. EAU was induced in Sprague-Dawley rats by immunization with interphotoreceptor retinoid-binding protein (IRBP), and ocular inflammation was assessed by slit-lamp examination and histopathology. The expression of the hub genes was validated in ocular, liver, and spleen tissues by reverse transcription-quantitative polymerase chain reaction and enzyme-linked immunosorbent assay. A total of 139 uveitis-related genes were identified; these were enriched in inflammatory response, immune response, viral defense response, and the TNF and NF-κB signaling pathways. Ten hub genes ( IL17A, IL18, TLR2, IL2, TLR4, IL10, IL1B, IL6, TNF , and CCL2 ) were identified, each with an area under the ROC curve greater than 0.6. The EAU model was successfully established, with significantly greater anterior segment inflammation than in controls, and the mRNA and protein levels of the hub genes were significantly elevated in the ocular and peripheral tissues of EAU rats (p < 0.05). These findings reveal key genes and pathways involved in the pathogenesis of uveitis and provide candidate targets for its diagnosis and treatment.