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Review
. 2025 May:106:101350.
doi: 10.1016/j.preteyeres.2025.101350. Epub 2025 Mar 4.

Oculomics: Current concepts and evidence

Affiliations
Free article
Review

Oculomics: Current concepts and evidence

Zhuoting Zhu et al. Prog Retin Eye Res. 2025 May.
Free article

Abstract

The eye provides novel insights into general health, as well as pathogenesis and development of systemic diseases. In the past decade, growing evidence has demonstrated that the eye's structure and function mirror multiple systemic health conditions, especially in cardiovascular diseases, neurodegenerative disorders, and kidney impairments. This has given rise to the field of oculomics-the application of ophthalmic biomarkers to understand mechanisms, detect and predict disease. The development of this field has been accelerated by three major advances: 1) the availability and widespread clinical adoption of high-resolution and non-invasive ophthalmic imaging ("hardware"); 2) the availability of large studies to interrogate associations ("big data"); 3) the development of novel analytical methods, including artificial intelligence (AI) ("software"). Oculomics offers an opportunity to enhance our understanding of the interplay between the eye and the body, while supporting development of innovative diagnostic, prognostic, and therapeutic tools. These advances have been further accelerated by developments in AI, coupled with large-scale linkage datasets linking ocular imaging data with systemic health data. Oculomics also enables the detection, screening, diagnosis, and monitoring of many systemic health conditions. Furthermore, oculomics with AI allows prediction of the risk of systemic diseases, enabling risk stratification, opening up new avenues for prevention or individualized risk prediction and prevention, facilitating personalized medicine. In this review, we summarise current concepts and evidence in the field of oculomics, highlighting the progress that has been made, remaining challenges, and the opportunities for future research.

Keywords: Artificial intelligence; Big data; Disease detection; Disease prediction; Oculomics; Retinal imaging; Systemic diseases.

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Conflict of interest statement

Conflict of interest statement Dr. Y Liu is an employee of Google and owns Alphabet stock. Dr. AG Lee works as a consultant for NASA but the views expressed here are his own and do not necessarily represent those of NASA or the United States government; he has the following disclosures which are not relevant to the contents of this manuscript: Amgen (speaker), Alexion (speaker), Viridian, Catalys, Ethyreal, Astrazeneca, Bristol Myers Squibb, Stoke. Dr. PA Keane has acted as a consultant for Retina Consultants of America, Topcon, Roche, Boehringer-Ingleheim, and Bitfount and is an equity owner in Big Picture Medical; he has received speaker fees from Zeiss, Novartis, Gyroscope, Boehringer-Ingleheim, Apellis, Roche, Abbvie, Topcon, and Hakim Group; he has received travel support from Bayer, Topcon, and Roche, he has attended advisory boards for Topcon, Bayer, Boehringer-Ingleheim, RetinAI, and Novartis. Dr. CY Cheng is a consultant for Medi-Whale. Dr. TY Wong is a consultant for Bayer, Boehringer-Ingelheim, Genentech, Opthea Limited, Roche; he is an inventor, holds patents and is a co-founder of start-up companies EyRiS and Visre, which have interests in, and develop digital solutions for eye diseases.