The concept of oculomics has emerged from the recognition that the retina is a uniquely accessible and data-rich interface between ocular and systemic health. Recent advances in retinal imaging—such as ultra-widefield (UWF) fundus photography and optical coherence tomography angiography (OCT-A)—enable detailed visualization of the retinal microvasculature, which reflects systemic vascular alterations. An increasing body of evidence demonstrates that retinal features such as vessel caliber, tortuosity, and OCT-based parameters like vessel density and perfusion density are strongly correlated with systemic conditions including cardiovascular disease and Alzheimer’s disease. The combination of retinal imaging and machine learning allows for the identification of subtle changes that may serve as early indicators of disease. This approach could revolutionize diagnostics by providing rapid and non-invasive assessments of systemic health. This Research Topic aims to consolidate current knowledge and stimulate new interdisciplinary investigations that explore the retina as a non-invasive diagnostic gateway to systemic disease.

This Research Topic aims to explore how oculomics — the extraction of systemic health information from the eye — can transform retinal imaging into a powerful, non-invasive diagnostic gateway. The central problem we address is the current gap in early, accessible, and cost-effective detection of systemic diseases, particularly those affecting the cardiovascular and neurological systems. With the advent of AI-powered image analysis and increasingly refined imaging techniques, we are now capable of detecting subtle retinal changes that correlate with systemic pathology long before clinical symptoms emerge. The goal is to encourage research that pushes the boundaries of retinal imaging in identifying new biomarkers, supports early disease detection, and enhances risk prediction models. Ultimately, this Research Topic aims to foster the development of standardized, clinically applicable retinal biomarkers that can accelerate their translation into real-world healthcare. The long-term vision is to support population-level screening, enable earlier intervention, and guide personalized treatment strategies through a simple eye exam.

This Research Topic seeks submissions that investigate the intersection between retinal imaging and systemic disease, with a focus on biomarker discovery, machine learning applications, and clinical translation. We welcome contributions in the form of original research, technical reports, reviews, perspectives and opinions addressing:

   •  Identification of novel retinal biomarkers for systemic diseases
   •  Application of AI and deep learning to ophthalmic data
   •  Multimodal imaging techniques (e.g., OCT, OCT-A, UWF imaging) and their diagnostic implications on systemic disease
   •  Integration of retinal and systemic data in predictive models
   •  Clinical feasibility and real-world implementation of oculomics

Papers should emphasize translational impact and innovation in non-invasive diagnostics.

Are you interested in contributing a manuscript to this Research Topic?

Beyond the Eye: How Oculomics is Transforming Retinal Imaging Into a Gateway to Systemic Biomarkers