Systems Age: a single blood methylation test to quantify aging heterogeneity across 11 physiological systems

Area of Science:

• Biogerontology
• Epigenetics
• Systems Biology

Background:

• Aging varies significantly between individuals and physiological systems.
• Existing epigenetic clocks typically provide a single age estimate, neglecting within-person variability.
• A more granular assessment of aging across different bodily systems is needed.

Purpose of the Study:

• To develop novel DNA methylation clocks capable of measuring aging across 11 distinct physiological systems.
• To integrate machine learning with clinical data for improved aging assessment.
• To identify distinct biological aging subtypes and their associated health risks.

Main Methods:

• Development of systems-based DNA methylation clocks for 11 physiological systems (Heart, Lung, Kidney, Liver, Brain, Immune, Inflammatory, Blood, Musculoskeletal, Hormone, Metabolic).
• Utilized data from a single blood draw.
• Integrated supervised and unsupervised machine learning with clinical biomarkers, functional assessments, and mortality risk data.

Main Results:

• System-specific aging scores were derived, outperforming global clocks in predicting diseases and aging phenotypes.
• A composite Systems Age score was created to reflect overall multisystem aging.
• Clustering revealed distinct biological aging subtypes associated with unique health decline and disease risk patterns.

Conclusions:

• The developed framework provides a more granular and clinically relevant assessment of biological aging.
• This approach enables personalized monitoring and targeted interventions for system-specific aging processes.
• Systems-based epigenetic clocks offer a comprehensive view of aging, accounting for individual variability across physiological systems.