A Multimodal Framework for Organ- and Cell-Resolved Biological Aging and Longevity Intervention Discovery

Area of Science:

• Biogerontology
• Biomarkers
• Personalized Medicine

Background:

• Aging is a primary driver of chronic disease and mortality.
• Comprehensive frameworks are needed to quantify aging and identify longevity interventions.

Purpose of the Study:

• To develop a multimodal biological aging framework (mAge) integrating plasma proteomics and wearable data.
• To predict biological age, intrinsic capacity, and mortality risk.
• To identify potential longevity interventions.

Main Methods:

• Integrated plasma proteomics, wearable data, and mortality hazard data from UK Biobank.
• Developed organ- and cell type-specific biological clocks for 49 subsystems.
• Mapped data to FDA-approved drug targets to identify interventions.

Main Results:

• mAge achieved a test R² of 0.87 for age prediction and reduced mortality prediction error by 21%.
• Wearable integration significantly improved cardiac, immune, and intracellular protein signatures.
• Identified interventions like GLP-1 receptor agonists associated with lower aging markers and mortality risk.

Conclusions:

• mAge provides a scalable framework for nominating and validating personalized longevity interventions.
• The framework bridges digital monitoring with molecular aging diagnostics.
• mAge enhances the prediction of biological age and mortality risk.