Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems

Nov 2, 2024Cell metabolism

Blood protein patterns reveal organ-specific aging and link diseases to faster aging of body systems

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Longevity & Aging on OpenScience ↗PubMed ↗DOI ↗

Abstract

Over 50,000 human subjects' plasma proteome data were analyzed to identify factors influencing organ-specific aging.

Models trained on chronological age and longitudinal proteome data predict disease specific to organs and systems.
Men may experience faster aging than women across most organs.
Accelerated aging of organs is associated with the onset of diseases in those organs.
Diets, lifestyles, professions, and medications could influence the rates of organ aging.
Proteins linked to organ-specific aging were identified, suggesting potential targets for interventions.

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Aging is a complex process manifesting at molecular, cellular, organ, and organismal levels. It leads to functional decline, disease, and ultimately death, but the relationship between these fundamental biomedical features remains elusive. By applying elastic net regularization to plasma proteome data of over 50,000 human subjects in the UK Biobank and other cohorts, we report interpretable organ-specific and conventional aging models trained on chronological age, mortality, and longitudinal proteome data. These models predict organ/system-specific disease and indicate that men age faster than women in most organs. Accelerated organ aging leads to diseases in these organs, and specific diets, lifestyles, professions, and medications influence organ aging rates. We then identify proteins driving these associations with organ-specific aging. Our analyses reveal that age-related chronic diseases epitomize accelerated organ- and system-specific aging, modifiable through environmental factors, advocating for both universal whole-organism and personalized organ/system-specific anti-aging interventions.

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Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems

Abstract

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