A Statistical Physics Framework for Loss of Network Resilience in Aging

The interplay between mutations and epigenetic alterations represents a fundamental yet unresolved aspect of aging. Both forms of molecular damage accumulate nearly linearly with time, while aging phenotypes exhibit nonlinear behavior. To address this, we develop a statistical physics framework describing how the joint accumulation of mutations and epimutations reduces the system’s ability to maintain function, leading to a loss of resilience in gene regulatory networks. Mutations perturb network structure, while epimutations alter network dynamics, jointly weakening resilience. As damage accumulates, the system remains resilient up to a novel critical mutation–epigenetic threshold, beyond which resilience declines sharply, analogous to a phase transition. Using statistical mechanics concepts, we quantify cellular susceptibility to molecular damage, apply the fluctuation–dissipation theorem to link it to transcriptional noise, identify critical slowing down as a hallmark of declining resilience with age, and use Kramers’ formula to predict cellular lifespan across tissues. This statistical physics framework provides a quantitative explanation of how gradual molecular damage produces emergent nonlinear dynamics in aging, offering a new perspective on the aging process.