Single-cell combined transcriptional sequencing to explore key genes and regulatory mechanisms in diabetic retinopathy

Abstract Background Diabetic retinopathy (DR), a prevalent complication of diabetes with a poor prognosis, remains incompletely understood. Therefore, an in-depth study on the pathogenesis of DR at the molecular level is essential to identify key DR-related genes. The objective of this study was to employ bioinformatics approaches to explore key genes and potential molecular mechanisms underlying DR. Results The single-cell sequencing dataset (GSE209872) and transcriptome sequencing datasets (GSE94019 and GSE102485) from the GEO database were utilized to screen for differentially expressed genes. Through WGCNA analysis and GSEA enrichment analysis, key genes and potential mechanisms were identified. Six key genes associated with the development of DR, namely CD44, CPLX4, MMP14, PMEPA1, PMP22, and POSTN were screened, and the specific signaling mechanisms associated with the key genes causing DR were predicted. To assess the immune infiltration, the CIBERSORT method was employed. The immune profiling revealed significant heterogeneity in immune response between the control group and the DR group. Conclusions These six key genes have the potential to become biomarkers for the diagnosis of DR and provide new targets and research directions for the treatment of DR.