Histological aging signatures for monitoring tissue-specific aging and disease

GTEx Consortium investigators

1. 01

   25,712 whole-slide histopathology images, 40 tissue types, 983 GTEx donors

2. 02

   Mean tissue-clock prediction error approximately 4.9 years

3. 03

   Age gaps associated with telomere attrition, subclinical pathologies and comorbidity burden

4. 04

   Organ-specific age acceleration linked to modifiable demographic and lifestyle factors

5. 05

   Blood-based inference of tissue-specific age gaps validated across eight diseases including Alzheimer's, stroke and Crohn's

6. 06

   Positions tissue architecture as an aging substrate orthogonal to methylation and proteomics

Study Design

Cohort Study

Sample Size

983 subjects

Study Duration

Cross-sectional (GTEx donor cohort) with external disease-cohort validation

Methodology

Deep-learning (vision model) analysis of whole-slide histopathological images from the GTEx cohort to derive per-tissue biological-age predictors; association testing against telomere length, subclinical pathology, comorbidity and lifestyle factors; integration with paired transcriptomic data to enable blood-based prediction of tissue-specific age gaps; external validation across independent disease cohorts.

Limitations

GTEx is a post-mortem donor cohort, which limits generalisability to living-patient tissue and to longitudinal change; the blood-based tissue-age predictions are a derived inference layer rather than a direct tissue measurement; cross-sectional design cannot establish that tissue age gaps are modifiable; no intervention was tested.