Evidence mapPaperPMID 41735452Full record

ArticleScientific reports2026

Retinal BioAge is associated with indicators of cardiovascular-kidney-metabolic syndrome in UK and US populations.

David Squirrell, Christopher Nielsen, Ehsan Vaghefi, Songyang An, Shima Moghadam, Song Yang, Li Xie, Atefeh Rahimi, Mary K Durbin, Huiyuan Hou and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Observational
  2. 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

12 authors.

David SquirrellToku, Inc., La Jolla, CA, USA.
Christopher NielsenToku, Inc., La Jolla, CA, USA.
Ehsan VaghefiToku, Inc., La Jolla, CA, USA.
Songyang AnToku, Inc., La Jolla, CA, USA.
Shima MoghadamToku, Inc., La Jolla, CA, USA.
Song YangToku, Inc., La Jolla, CA, USA.
Li XieToku, Inc., La Jolla, CA, USA.
Atefeh RahimiToku, Inc., La Jolla, CA, USA.
Mary K DurbinTopcon Healthcare, Oakland, NJ, USA.
Huiyuan HouTopcon Healthcare, Oakland, NJ, USA.
Robert N WeinrebViterbi Family Department of Ophthalmology, Hamilton Glaucoma Center, Shiley Eye Institute, University of California, San Diego, CA, USA.
Michael V McConnellToku, Inc., La Jolla, CA, USA. michael.mcconnell@tokueyes.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accelerated biological aging, as well as cardiovascular, kidney, and metabolic (CKM) diseases, contribute to shortened healthspan. We studied a deep-learning model, retinal BioAge, and multiple indicators of CKM syndrome in participants from UK Biobank and the US-based EyePACS dataset. Retinal BioAge was trained on 77,887 retinal images and then used to analyze separate retinal images from UK Biobank (10,976) and EyePACS (19,856). In both datasets, CKM biomarker profiles were significantly worse for the top vs. bottom quartiles of BioAgeGap (retinal BioAge-chronological age), including measures of blood pressure, kidney function, adiposity, and glycemia. The top BioAgeGap quartile also had a significantly higher prevalence of clinical CKM indicators, including hypertension, kidney disease, and diabetes (UK Biobank) or suboptimally controlled diabetes (EyePACS). Thus, analysis of retinal images for accelerated biological aging may provide opportunistic screening to help identify individuals who could benefit from formal CKM assessment, potentially contributing to earlier detection and management of CKM syndrome.

Indexed as

Cardiovascular DiseasesKidney DiseasesMetabolic SyndromeRetinaAgedAgingBiomarkersFemaleHumansMaleUK BiobankUnited KingdomUnited StatesBiomarkers

Identifiers

PMID41735452
PMCPMC13031334

What Socratic holds

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Registered trials

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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.