Organ-specific proteomic aging clocks predict disease and longevity across diverse populations

Area of Science:

• Proteomics
• Machine Learning
• Gerontology
• Biomarkers

Background:

• Aging and age-related diseases share common molecular pathways.
• Plasma proteome analysis offers a window into organismal and organ health.

Purpose of the Study:

• To develop and validate accurate proteomic clocks for organismal and organ-specific aging.
• To assess the predictive power of these clocks for disease onset, progression, and mortality.
• To explore the genetic and environmental determinants of organ aging and associated disease pathways.

Main Methods:

• Utilized plasma proteomics and machine learning algorithms.
• Developed organismal and ten organ-specific aging clocks using the UK Biobank cohort.
• Validated clock accuracy in independent cohorts from China and the USA.
• Analyzed associations between organ aging, lifestyle, genetics, and disease outcomes.

Main Results:

• High accuracy of proteomic aging clocks was achieved and validated across cohorts (cross-cohort r = 0.98).
• Accelerated organ aging significantly predicted disease onset, progression, and mortality, outperforming clinical and genetic factors.
• Brain aging showed the strongest association with mortality and was linked to lifestyle, specific genes (GABBR1, ECM1), and brain structure.
• Identified distinct organ-specific pathways, with brain and artery aging linked to cognitive decline and dementia via synaptic loss, vascular dysfunction, and glial activation.
• The brain aging clock stratified Alzheimer's disease risk and identified resilience conferred by a youthful brain against APOE4.

Conclusions:

• Proteomic organ aging clocks provide a robust, biologically interpretable framework for tracking aging and disease risk.
• These clocks can enhance personalized risk assessment and stratify individuals for targeted interventions.
• Understanding organ-specific aging pathways is crucial for developing strategies against age-related diseases.