In partnership with
🔬TODAY’S BREAKTHROUGH
A pilot study shows how integrating epigenetic, proteomic, metabolomic, and clinical aging clocks into digital twins can track biological aging and predict health risks in real time.
The Discovery:
In the IAM Frontier cohort (30 adults, 45–59 years, followed for 13 months), researchers tested 34 biological age predictors across multiple omics layers (omics refers to large-scale biological data such as genomics, epigenomics, proteomics, and metabolomics).
They found that epigenetic clocks were the most stable within individuals, while proteomic and clinical clocks captured short-term health fluctuations. Integrating these predictors into digital twins could enable personalized, adaptive healthcare models.
The Science:
Study design: Monthly sampling of blood, urine, stool, plus continuous wearables and questionnaires; omics data analyzed included DNA methylation, proteomics, metabolomics, and clinical biomarkers.
Clocks tested: 34 predictors, including GrimAge, PhenoAge, Skin & Blood, Hannum, MethylDetectR, DunedinPACE, mPoA, plus proteomic and metabolomic clocks.
Accuracy: MethylDetectR and Skin & Blood clocks correlated most strongly with chronological age (r=0.90 and r=0.87). GrimAge also tracked lifespan and healthspan.
Stability: Epigenetic clocks produced the most consistent within-person predictions; proteomic and clinical clocks were more sensitive to short-term lifestyle or health changes.
Case examples: Individual deviations flagged risks such as premature telomere shortening, abnormal lipid profiles, and immune abnormalities, detectable before overt disease.
Implication: Digital twins anchored to multi-omics clocks can simulate personalized health trajectories, detect accelerated aging early, and guide targeted prevention.
Your Action:
Aging clocks and digital twins are not yet clinical tools, but you can act on the principle: track health regularly, combine biomarkers with wearables, and support resilience through exercise, diet, and sleep. Consistent monitoring is key.
Bottom Line:
Multi-omics aging clocks linked with digital twins could redefine precision health by turning biological age into a dynamic, personal biomarker.
Source:
From ageing clocks to human digital twins in personalising healthcare through biological age analysis. npj Digital Medicine. Pusparum M, Thas O, Beck S, Ecker S, Ertaylan G.
https://doi.org/10.1038/s41746-025-01911-9
How was today’s newsletter?
A Quick Favor:
We kindly ask you to check out the sponsor(s) that made this newsletter possible. Your support helps us continue sharing valuable insights and empowering your wellness journey.
Join 400,000+ executives and professionals who trust The AI Report for daily, practical AI updates.
Built for business—not engineers—this newsletter delivers expert prompts, real-world use cases, and decision-ready insights.
No hype. No jargon. Just results.
LEARN MORE ABOUT OUR WORK
— Capilli Eternal
Disclaimer:
This newsletter is for informational purposes only and does not substitute professional medical advice. Always consult with a healthcare provider before making any changes to your health regimen.