BiomarkersHumans71,343 participantsCohort study

Retinal imaging model predicts age and reveals sex differences in human aging

The retinal age gap correlates with mortality, disease risks, and sex-specific genetic pathways in more than 71,000 UK Biobank participants.

Two retinal fundus scans above two hearts, one paired with a cluster of fat cells and the other with a branching vascular network.

Nature Communications2 Oct 2026, 23:17 BST

Researchers analyzed retinal fundus images from 71,343 human participants in the UK Biobank. They fine-tuned the deep learning foundation model RETFound to predict chronological age, reaching a mean absolute error of 2.85 years. The retinal age gap, defined as the difference between predicted and actual age, tracked with inflammation, cardiometabolic traits, cognitive performance, all-cause mortality, dementia, cancer, and incident cardiovascular disease. Genome-wide analyses linked this gap to genes involved in longevity, metabolism, neurodegeneration, and eye diseases. Sex-stratified analyses revealed distinct biological features. Retinal aging in males showed stronger ties to metabolic syndrome. In females, retinal aging involved vascular pathways and shifted across menopause, with postmenopausal women displaying higher age gaps and clinical profiles resembling those in males.

Why it matters

The findings indicate that non-invasive retinal imaging captures systemic aging processes and age-related disease risks. They also show that aging trajectories differ biologically between men and women.

Caveats

The study relied on observational data from a single cohort, the UK Biobank. It evaluated associations without directly demonstrating causal biological mechanisms.