Abstract

As a common neurodegenerative condition, glaucoma is manifested by increased intraocular pressure and gradual retinal ganglion cell degeneration, to ultimately result in irreversible blindness. Investigating crucial genes involved in mitophagy holds promise as potential diagnostic biomarkers for the condition and provides valuable insights for clinical decision-making and novel therapeutics for patients. Researchers utilized datasets from the gene expression omnibus to identify genes differentially expressed in relation to mitophagy. They employed least absolute shrinkage and selection operator regression to sift through these genes and pinpoint potential diagnostic markers. A glaucoma prediction model (nomogram) was then generated using multivariable logistic regression analyses, and then evaluated. To gain a deeper molecular understanding of glaucoma, molecular subtyping and enrichment, interaction network, and immune infiltration analyses were performed. We identified 15 mitophagy, from which Bcl-2 interacting protein 3, X-C motif chemokine ligand 12, fucosyltransferase 8, microtubule associated scaffold protein 1, phospho fructokinase, platelet, and reticulon 1 were selected and used to construct a glaucoma prediction model. The evaluation of the model involved calibration curves, receiver operating characteristic curves, and decision curve analysis analysis to ensure precision and stability. Based on this, a diagnostic diagram was constructed. The study revealed potential involvement of immune cells in glaucoma, with cathepsin K identified as a crucial immune regulatory factor. Significant differences in immune cell populations between glaucoma and normal groups were observed, and strong correlations were found between specific immune cell types and key genes. Our findings and predictive model provide valuable insights for future clinical investigations and research underpinning the molecular mechanisms in glaucoma.