PHOENIX — Optometrists are set to play a key role in managing chronic conditions and monitoring systemic disease risk through the emerging field of oculomics, according to a speaker at Optometry’s Meeting. “Right now ... pretty much what we do is reactive care. We wait for something to happen before doing something about it,” Roya Attar, OD, MBA, DHA, associate professor and director of optometric services at University of Mississippi Medical Center, said during a presentation. “AI, oculomics and this whole new field is going to allow us to be more proactive.” The concept behind oculomics is to

Researchers have found non-invasive eye scans can pick up signs of atrial fibrillation (AF), a condition that heightens the risk of stroke

In this video, Vivienne S. Hau, MD, PhD, of Kaiser Permanente Bernard J. Tyson School of Medicine, discussed the emergence of oculomics, which was a topic at this year’s American Society of Retina Specialists annual meeting. Hau explained the use of oculomics, which combines current eye imaging techniques such as OCT angiography and fundus photos with AI. This may help retina specialists identify biomarkers earlier than before, possibly resulting in earlier treatment of retinal diseases. “At this meeting, there were a lot of talks looking at biomarkers that were recently found and are

A new commentary published in Eye has outlined the factors that will be important for the potential of oculomics to be fully realised within the NHS.

The molecular diagnostics developer hopes to find an edge among disease biomarker screening tests with a risk stratification approach using retinal scans.

Eye, Published online: 03 July 2026; doi:10.1038/s41433-026-04693-wOculomics and the NHS: A UK opportunity to translate eye-derived biomarkers into population health

June 17, 2026 11:00 am, Kresge Room, 269 Meliora Hall & Zoom

Aims To identify early oculomic biomarkers predictive of pathologic myopia (PM) in children with high myopia (HM) and to develop an artificial intelligence (AI)-based model for individualised risk stratification.Methods This prospective longitudinal study included 375 children with bilateral HM (spherical equivalent ≤ –6.00 dioptres (D)) from the Zhongshan High Myopia Cohort, followed for a median of 15.0 years (IQR, 14.9–15.4; range, 14.7–15.7). Deep learning-based automated retinal vascular phenotyping was applied to fundus photographs and integrated with longitudinal ocular biometry and swept-source optical coherence tomography metrics. Multivariable models identified independent predictors of PM onset and predictive performance was assessed using area under the receiver operating characteristic curve (AUROC). A web-based prediction tool was developed for clinical deployment.Results PM developed in 64 children (17.1%). Independent predictors included lower retinal vessel density (OR, 9.69; 95% CI 4.33 to 21.70), reduced fractal dimension (OR, 5.94; 95% CI 3.07 to 11.50), narrower arteriolar and venular calibres (central retinal arteriolar equivalent: OR, 3.44; 95% CI 1.86 to 6.34; central retinal venular equivalent: OR, 4.42; 95% CI 2.24 to 8.71), thinner subfoveal choroid (OR, 2.64; 95% CI 1.56 to 4.45), faster early axial elongation (OR, 1.72; 95% CI 1.17 to 2.50) and accelerated early choroidal thinning (OR, 2.33; 95% CI 1.41 to 3.84). The AI oculomic model achieved excellent discrimination (AUROC, 0.96; 95% CI 0.92 to 1.00), improving to 0.98 (95% CI 0.95 to 1.00) with biometric variables. These predictors were implemented in a publicly accessible risk prediction platform (System for Myopia AI-based Risk Tracking-PM).Conclusions PM risk in paediatric HM is detectable early through retinal microvascular architecture and ocular growth dynamics. AI-enabled oculomic profiling offers a scalable approach to early risk stratification, supporting targeted surveillance and timely prevention of sight-threatening pathology.

Oculomics, the study of eye biomarkers of systemic disease, is gaining traction as retinal imaging and AI advance. Tear testing could take the field in a new direction.

This Viewpoint explores the potential applications of the artificial intelligence (AI)–supported field of oculomics to identify and treat neurodegenerative and cerebrovascular diseases.