DISCO metric from proteomics predicts mortality and frailty in older adults

Aging involves diminished homeostatic control and changes in individual biomarker levels/states. However, it is unknown whether these alterations reflect a rise in entropy during the aging process, and whether entropy disrupts broad systemic interrelationships. The entropy of human aging has not been well characterized, but measures of systemic entropy could reveal aging dynamics that may not be apparent even by integration of state-based aging metrics. Here, we leverage the Distance of Covariance (DISCO), which quantifies entropy in large ensembles of biological information, to demonstrate that organs and systems exhibit interconnected increased entropy with age. We validate DISCO on multiple data substrates (clinical biomarkers, proteomics, metabolomics, and microbiomes) in five cohort datasets: UK BioBank, National Health and Nutrition Examination Survey, and three Chinese cohorts of older adults. DISCO consistently outperforms mortality prediction of existing metrics of dysregulation and is comparable to the best-in-class epigenetic clocks. It also strongly predicts frailty and incidence of age-related chronic conditions. Crucially, organ- and system-specific DISCO scores derived from circulating proteomics demonstrate broad predictive power with little to no specificity of a given organ predicting its own diseases and mortality. Network analysis of organ- and system-specific DISCO shows that more central, connected organ DISCOs predict health outcomes more strongly. For example, for each mortality cause, brain entropy is one of the strongest predictors. These findings challenge current notions of independent organ-specific aging signatures, suggesting instead that while pathology may be organ-specific, entropy spills readily across systems, and thus conversely that health during aging requires integrated homeostatic coordination across multiple systems.