Identification and functional analysis of novel biomarkers related to retinal neovascularization in proliferative diabetic retinopathy

Abstract

Background

Proliferative diabetes retinopathy (PDR) seriously affects the vision of patients. Exploring the key genes of retinal neovascularization is crucial for developing new biomarkers and therapeutic targets.

Objective

This study aimed to identify key genes associated with retinal neovascularization in Proliferative Diabetic Retinopathy (PDR), intending to develop new biomarkers and therapeutic targets. This would further our understanding of the progression of diabetic retinopathy and improve patient prognosis.

Methods

The gene data from 36 diabetic retinopathy patient samples and 45 samples from healthy volunteers or diabetic patients were selected from the GEO DataSets (Gene Expression Omnibus), specifically datasets GSE102485 and GSE160310. Utilizing the SVA algorithm to merge datasets and the limma package in R to identify differentially expressed genes (DEGs), we conducted a bioinformatic analysis of diabetic retinopathy. Functional insights were gained through DAVID database analyses, while STRING database-derived Protein-Protein Interaction (PPI) networks visualized in Cytoscape provided further context. Key genes were identified through LASSO regression and SVM analyses, with ROC curves assessing their diagnostic value. Single gene set enrichment analysis (GSEA) enhanced our understanding of the perturbed biological processes and pathways, advancing knowledge of diabetic retinopathy at the genomic level.

Results

A rigorous bioinformatic analysis yielded a comprehensive list of 1139 differentially expressed genes (DEGs), of which six pivotal genes—KDM5D, AC007040.11, AC015688.3, NLRP2, GYPC, and TMSB4Y—were identified as central to the study. These six genes consistently demonstrated a high diagnostic accuracy, with each exhibiting an area under the receiver operating characteristic (ROC) curve (AUC) exceeding 0.75. Gene Ontology (GO) enrichment analysis elucidated their primary roles in intricate biological processes, including inflammatory and immune responses, T-cell activation, cell apoptosis, and angiogenesis. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed their involvement in crucial signaling cascades such as cytokine-cytokine receptor interactions, cell adhesion molecule pathways, PI3K-Akt signaling, and hematopoietic cell lineage, further substantiating their significance in the pathogenesis of diabetic retinopathy.

Conclusions: In this research, we conducted a comprehensive gene expression analysis in patients with and without PDR, identifying differentially expressed genes, pivotal biomarkers, and critical pathways potentially involved in PDR progression. Our findings enhance understanding of PDR's molecular dynamics and offer potential avenues for improved prognostication and therapeutic intervention, despite limitations due to sample group heterogeneity.