Abstract

Purpose:A significant portion of patients with glaucoma exhibit normal intraocular pressure (IOP), suggesting additional risk factors other than elevated IOPs that are critical for the pathogenesis of glaucoma. This study aimed to identify blood biomarkers associated with glaucoma and construct a predictive model for glaucoma.Methods:Peripheral blood samples from patients with glaucoma and 175 age- and sex-matched healthy controls were analyzed using an automated hematology analyzer. Red blood cell membrane stability was analyzed by an osmotic fragility test. Red blood cell morphologies were analyzed using Giemsa staining. A least absolute shrinkage and selection operator (LASSO) regression model was constructed to predict glaucoma.Results:LASSO regression analysis of blood biomarkers identified important biomarkers for distinguishing patients with glaucoma from healthy controls, which also implied that red blood cells from patients with glaucoma were more prone to rupture. The erythrocyte osmotic fragility (EOF) test revealed significantly higher erythrocyte fragility in patients with glaucoma compared with healthy controls (P< 0.001). To improve the prediction accuracy, a new LASSO regression model for glaucoma prediction was constructed by integrating EOF. The probability of glaucoma (p) was calculated. The revised predictive model achieved an accuracy of 88.68% with a sensitivity of 92.59% and specificity of 84.62%. Validation using an independent dataset demonstrated the great predictive performance of the predictive model, with an area under the ROC (receiver operating characteristic) curve (AUC) value of 0.97.Conclusions:Increased EOF is a risk factor for glaucoma. EOF, along with several blood biomarkers, helps diagnose glaucoma.Translational Relevance:Measurement of EOF could facilitate clinical glaucoma diagnosis.