Abstract
Background
Primary open-angle glaucoma (POAG) is a chronic, progressive and irreversible eye disease. Currently, there is no effective way to prevent optic nerve damage.
Objective
This study explored POAG gene markers to identify high-risk groups at an early stage and to find new effective therapeutic targets.
Methods
The mRNA and clinical information of POAG patients and normal samples were downloaded from the Gene Expression Omnibus (GEO) database. Through Weighted correlation network analysis (WGCNA) and generalized linear models (GLM), random forests (RF), support vector machines (SVM), and extreme gradient boosting (xGB) models, key risk genes were identified and an early diagnosis model was established. Functional enrichment analysis and CIBERSORT algorithm were used to further reveal the changes in the POAG immune environment and find emerging therapeutic targets.
Results
HERPUD1, IQCK, MRPL40, SRSF7 and TMEM243 were identified as risk genes, and the prediction model and nomogram constructed based on them had good early prediction efficiency. At the mechanistic level, the heterogeneity of T cell subsets seems to be a key factor affecting the progression of POAG and has potential therapeutic value.
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