Evidence map›Paper›PMID 41310556›Full record

ArticleBMC medicine2025

Retinomics: a window to multidisease prediction using retinal biomarkers from routine eye imaging.

Mayinuer Yusufu, Matthew J Burton, Shanshan Jin, Xianwen Shang, Lei Zhang, Danli Shi, Mingguang He

Abstract read
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mayinuer YusufuCentre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.
Matthew J BurtonInternational Centre for Eye Health, London, School of Hygiene & Tropical Medicine , London, UK.
Shanshan JinBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing, China.
Xianwen ShangGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China. xianwen.shang@polyu.edu.hk.
Lei ZhangCentre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.
Danli ShiSchool of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong, SAR, China. danli.shi@polyu.edu.hk.
Mingguang HeSchool of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong, SAR, China. mingguang.he@polyu.edu.hk.

Funding

Global STEM Professorship Scheme P0046113
6 · The paper itself

Abstract

backgroundThe aim of this study is to investigate the potential of retinal biomarkers (retinomics) derived from color fundus photography and optical coherence tomography for predicting multiple diseases.

methodsUsing UK Biobank cohort data, we applied least absolute shrinkage and selection operator regression to address multicollinearity and identify key biomarkers. Cox proportional hazards models, with and without retinomic features. Detection rates (DR) across false positive rates (FPR: 5-40%) were assessed to ensure improved sensitivity without disproportionate false positives.

resultsThree retinomic features emerged as top predictors: ganglion cell-inner plexiform layer (37 diseases), retinal pigment epithelium (33 diseases), and central subfield of inner segment/outer segment-RPE (32 diseases). Adding retinomics improved mean C-index from 0.653 to 0.693 (+ 6.4%) in baseline models (age and sex) and from 0.697 to 0.721 (+ 3.5%) in clinical models (traditional common risk factors). A simplified retinal model (retinomics + age/sex) achieved C-index ≥ 0.75 for 13 diseases. Retinomics enhanced prediction by > 5% for 24 diseases in baseline models and 12 diseases in clinical models. DR improvements across FPR ranges confirmed robust performance without excessive false positives.

conclusionsRetinomics universally enhanced disease prediction, with marked gains for conditions like cardiovascular and metabolic disorders. The onset of presbyopia (~ 50 years)-a common trigger for eye exams-aligns with escalating chronic disease risks, suggesting an opportunity to leverage routine eye care for broader health assessment. While requiring further validation, this approach demonstrates the potential to enhance health screening efficiency using existing ophthalmic infrastructure, offering particular value for resource-limited settings.

Indexed as

RetinaRetinal DiseasesTomography, Optical CoherenceAdultAgedBiomarkersFemaleHumansMaleMiddle AgedUnited KingdomBiomarkersChronic diseases predictionCohort studyNeurovascular biomarkersPreventive careRetina-based microvascular health assessment systemRetinal neural layersRetinal vascular measurements

Identifiers

PMID41310556
PMCPMC12661837

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.