Diabetic retinopathy (DR) causes irreversible visual impairment in diabetes mellitus (DM) patients. Immunity played a crucial role in DR. Nevertheless, the triggering mechanism of DR was not yet thorough enough. Herein, we aim to identify the immune-associated genes as biomarkers associated with immune scores that can distinguish early DR from DM without DR.
In this study, total RNA of peripheral blood mononuclear cell (PBMC) samples from 15 non-proliferative DR patients and 15 DM patients without DR were collected and the transcriptome sequencing data were extracted. Firstly, the target genes were obtained by intersecting the differentially expressed genes (DEGs), which were screened by “limma”, and the module genes (related to immune scores), which were screened by “WGCNA”. In order to screen for the crucial genes, three machine learning algorithms were implemented, and a receiver operating characteristic (ROC) curve was used to obtain the diagnostic genes. Moreover, the gene set enrichment analysis (GSEA) was performed to understand the function of diagnostic genes, and analysis of the proportions of immune cells and their association with diagnostic genes was performed to analyze the pathogenesis of DR. Furthermore, the regulatory network of TF–mRNA–miRNA was built to reveal the possible regulation of diagnostic genes. Finally, the quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the mRNA level of diagnostic genes.
A total of three immune-associated diagnostic genes, namely,
This study identified three immune-associated diagnostic genes,