Identification of key biomarkers in Diabetic retinopathy and age-related macular degeneration by integrated bioinformatics analysis

Abstract

Abstract Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are the main causes of visual impairment in individuals aged 50 and above globally. Interestingly, there is a complex relationship between DR and AMD, although the specific mechanisms connecting them are not yet fully understood. This study aims to identify common gene signatures and uncover potential molecular mechanisms involved in the development of both DR and AMD. The gene expression profiles of GSE160306 and GSE29801 were obtained from the Gene Expression Omnibus (GEO) database to analyze the differences in gene expression between AMD, DR, and healthy samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the clusterProfiler package in R. The protein-protein interaction (PPI) network was constructed using the STRING database and Cytoscape software. Additionally, meaningful hub genes were identified through machine-learning algorithms. Receiver operating characteristic (ROC) analyses were conducted to assess the diagnostic value of the differentially expressed genes (DEGs) for DR and AMD. Overall, a total of 5 DEGs (C5, KRAS, FSTL1, KCNV2, and PILRB) were identified, and further analysis revealed key pathways, gene modules, and co-expression networks associated with DR and AMD.