TO IDENTIFY IMMUNE-RELATED BIOMARKERS OF DIABETIC RETINOPATHY BASED ON BIOINFORMATICS

Abstract

Background: Bioinformatics analysis of gene microarray data from retinal tissues of diabetic retinopathy (DR) patients and healthy controls to identify DR signature genes. Methods: The Gene Expression Omnibus (GEO) database was queried to retrieve DR-related datasets, which were then normalized to identify differentially expressed genes (DEGs), and intersected with immune-related genes to obtain immune-related DEGs. Then, an analysis of gene ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), interaction network and immune cell infiltration. Constructing diagnostic models based on screened core genes while predicting potential immunotherapeutic agents. Results: 23 immune-related DEGs have been identified, the functions of which were primarily associated with the extrinsic apoptotic signaling pathway, the external side of the plasma membrane, and interleukin-1 receptor binding, etc. Closely connected to the NF-kappa B signaling pathway, the TNF signaling pathway and other pathways. We screened for the F2R, PDIA3, ICAM1 and B2M total 4 key genes. T cells CD4 memory activated and T cells gamma delta were abundant in the DR, while T cells regulatory and resting Mast cells were in reduced abundance. Conclusion: Our research provided a solid scientific foundation for later DR studies by identifying a total of four putative critical genes and pathways in F2R, PDIA3, ICAM1, and B2M.