A Minimal Model Explains Aging Regimes and Guides Intervention Strategies

Aging varies widely across species yet exhibits universal statistical regularities, such as Gompertzian mortality and scaling laws, challenging efforts to link microscopic mechanisms with macroscopic outcomes. We present a minimal phenomenological model that captures these patterns by reducing complex physiology to three variables: a dynamic factor characterizing reversible physiological responses to stress, an entropic damage variable reflecting irreversible information loss, and a regulatory noise term. This framework reveals two fundamental aging regimes. In stable species, including humans, aging is driven by linear damage accumulation that gradually erodes resilience, producing a hyperbolic trajectory toward a maximum lifespan. In unstable species, such as mice and flies, intrinsic instability drives exponential divergence of biomarkers and mortality. Model predictions agree with DNA methylation dynamics, biomarker autocorrelation, and survival curves across taxa. Crucially, this regime-based view informs intervention strategies at three levels: (i) targeting dynamic hallmarks, (ii) reducing physiological noise, and (iii) slowing or reversing entropic damage—offering a roadmap from near-term healthspan gains to potential extension of human lifespan beyond current limits.