Identification of Biomarkers for Oxidative Stress in Age-Related Macular Degeneration: Combining Transcriptomics and...

Oxidative stress has long been recognized as a significant influence in the pathophysiology of age-related macular degeneration (AMD). Therefore there is a need to explore the relationship between oxidative stress-related biomarkers and AMD.

Based on Gene Expression Omnibus database-Gene Expression Omnibus Series (GSE)29801 and GSE135092 datasets, three machine learning methods were used to screen biomarkers. The Wilcoxon test was used to compare the percentage of immune cells in control and AMD samples. The causal relationship between biomarkers and AMD was explored in a series of Mendelian randomization (MR) analyses. Ultimately, the expression levels of biomarkers were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in the simulated AMD cell model.

A total of 16 differentially expressed oxidative stress-related genes (DE-OSRGs) were screened. Functional enrichment analysis indicated that DE-OSRGs participated in cellular senescence, cell cycle regulation, and PPAR signaling pathways. Machine learning methods were used to screen for five biomarkers (GFAP, Stearoyl-CoA desaturase [SCD], BCKDHB, GPX8, and MSRB2). The qRT-PCR results showed that the expression levels of five biomarkers were significantly different between the simulated AMD cell model and control groups. Spearman correlation analysis showed that GPX8 had the highest positive correlation with M2 macrophages (correlation coefficient [cor] = 0.36, P < 0.01), and SCD had a strong negative correlation with eosinophils (cor = -0.28, P < 0.05). MR results revealed that BCKDHB played a crucial role as a risk factor for AMD (odds ratio > 1, P < 0.05).

This study screened the biomarkers related to oxidative stress in AMD, providing a certain theoretical basis for the prevention and clinical diagnosis of AMD.

Identifying biomarkers with diagnostic value for AMD could provide new understanding of its pathogenesis, and open up potential targets for clinical intervention.