Diagnosis of Primary Open-Angle Glaucoma Using Spectral Profiling of Aqueous Humor-Derived Exosomes
Clinical Snapshot
PICO Framework
| P — Population | Patients with suspected primary open-angle glaucoma and healthy controls undergoing aqueous humor sampling |
| I — Intervention | Spectral profiling of aqueous humor-derived exosomes using gold nanoparticle-enhanced Raman spectroscopy with CNN analysis |
| C — Comparator | Conventional diagnostic methods (intraocular pressure measurement and optical coherence tomography) |
| O — Outcomes | Diagnostic accuracy metrics including sensitivity, specificity, AUC, and prediction accuracy for POAG detection |
Bottom Line
This diagnostic accuracy study presents a novel approach using spectral profiling of aqueous humor-derived exosomes for POAG diagnosis, achieving promising results with 96% AUC and 91% accuracy. However, the study suffers from incomplete reporting of essential diagnostic accuracy metrics including sensitivity, specificity, confidence intervals, and likelihood ratios. The invasive nature of aqueous humor sampling limits clinical applicability compared to current non-invasive methods. While the technology shows potential for molecular-level diagnosis, significant gaps in methodology reporting, unclear patient selection criteria, and absence of blinding procedures raise concerns about bias. The clinical utility remains uncertain without comparison to existing diagnostic pathways and cost-effectiveness analysis. Further validation studies with complete STARD-compliant reporting are needed before clinical implementation.
Key Findings
P Value: Not reported
Effect Size: AUC 0.96
Primary Outcome: Diagnostic accuracy for primary open-angle glaucoma detection
Nnt Or Sensitivity: Prediction accuracy 91% (sensitivity and specificity not separately reported)
Confidence Interval: Not reported
Clinical Application
Limited by need for invasive aqueous humor collection and specialized equipment Would require TGA approval for diagnostic use; cost-effectiveness assessment needed for PBS consideration; integration with existing ophthalmology services challenging Patients with suspected POAG requiring aqueous humor sampling
Abstract
Primary open-angle glaucoma (POAG) is one of the most common neurodegenerative diseases that cause irreversible optic nerve damage. POAG diagnosis requires multimodal assessments; however, current methods like intraocular pressure (IOP) and optical coherence tomography (OCT) imaging suffer from low sensitivity and inter-patient variability, respectively. Liquid biopsy provides objective molecular signatures, offering a robust alternative to overcome limitations of conventional clinical hallmarks. Here, we present an efficient and highly sensitive diagnostic platform operating on spectral profiles from aqueous humor (AH)-derived exosomes. Following morphological and compositional validation of exosome presence in AH samples, antibody-functionalized substrates were fabricated for selective capture. Immobilized AH-derived exosomes are then coated with gold nanoparticles to generate molecular fingerprint Raman signals. A total of 7600 spectra are acquired and used to train and evaluate the convolutional neural network (CNN) model for binary classification between healthy controls and glaucoma patients. The trained CNN model achieved an AUC of 0.96 and a prediction accuracy of 91%. The system enables rapid, individualized diagnosis, overcoming sample volume limitations via integrated immunoassay-based isolation and artificial intelligence (AI)-driven classification, highlighting the potential of ocular fluid-derived EVs in the diagnosis of neurodegenerative diseases.
References
- 1.Sun, H., Lee, S. H., Kim, S., Moon, C. E., Kim, J. W., Yoon, H. B., Ji, Y. W., & Choi, Y. (2026). Diagnosis of Primary Open-Angle Glaucoma Using Spectral Profiling of Aqueous Humor-Derived Exosomes. ACS Sensors. https://doi.org/10.1021/acssensors.5c04461
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