Aging & Gerontology

Abstract

Age is the leading risk factor for prevalent diseases and death. However, the relation between age-related physiological changes and lifespan is poorly understood. We combine analytical and machine learning tools to investigate aging as a macroscopic manifestation of underlying dynamic instability of the organism state in large biomedical data. In mice, the leading aging signature (“dynamic frailty indicator”, dFI) increases exponentially and predicts the remaining lifespan. The dynamics of dFI is consistent with the late-life mortality deceleration. dFI changed along with hallmarks of aging, including frailty index, molecular markers of inflammation, senescent cell accumulation, and responded to life-shortening (high-fat diet) and life-extending (rapamycin) treatments. In human data, the analysis paints a more sophisticated picture. We analyzed aging signatures of DNA methylation and longitudinal electronic medical records from the UK Biobank datasets. We observed that aging is driven by a large number of independent and infrequent transitions between metastable states in a vast configuration space. The compound effect of configuration changes can be captured by a single stochastic variable, thermodynamic biological age (tBA), tracking entropy produced, and hence information lost during aging. We show that tBA increases with age, causes the linear and irreversible drift of physiological state variables, reduces resilience, and drives the exponential acceleration of chronic disease incidence and death risks. The reduction of resilience sets the maximum human lifespan limit, whereas the entropic character of aging drift sets severe constraints on the possibilities of age reversal. However, we highlight the universal features of configuration transitions, suggest practical ways of suppressing the rate of aging in humans, and speculate on the possibility of achieving negligible senescence. 

Biography

Ph.D. from the University of Amsterdam. Co-founder of Gero, a data-driven longevitybiotech company, that develops new drugs against aging and other complex diseases using AI-platform. An author of 75+ published papers in multiple domain areas, including publications in Science and Nature Communications.