Heterogeneous aging across multiple organ systems and prediction of chronic disease and mortality

Biological aging of human organ systems reflects the interplay of age, chronic disease, lifestyle and genetic risk. Using longitudinal brain imaging and physiological phenotypes from the UK Biobank, we establish normative models of biological age for three brain and seven body systems. Here we find that an organ's biological age selectively influences the aging of other organ systems, revealing a multiorgan aging network. We report organ age profiles for 16 chronic diseases, where advanced biological aging extends from the organ of primary disease to multiple systems. Advanced body age associates with several lifestyle and environmental factors, leukocyte telomere lengths and mortality risk, and predicts survival time (area under the curve of 0.77) and premature death (area under the curve of 0.86). Our work reveals the multisystem nature of human aging in health and chronic disease. It may enable early identification of individuals at increased risk of aging-related morbidity and inform new strategies to potentially limit organ-specific aging in such individuals. Organ-specific aging clocks for multiple brain and body systems show that the biological age of one organ system selectively influences the aging of multiple other systems via characteristic aging pathways.

Automated summary

Using brain imaging and physiological data from the UK Biobank, researchers establish normative models of biological age for various organ systems and find that biological aging of one organ selectively influences the aging of others, revealing a multiorgan aging network. They also report organ age profiles for chronic diseases, showing that advanced biological aging extends from the primary organ to multiple systems. Advanced body age is associated with lifestyle factors, telomere lengths, mortality risk, and predicts survival time and premature death. This research sheds light on the multisystem nature of human aging and the potential for early identification of individuals at risk.