Epigenetic Noise and Regulatory Entropy in Aging: A Quantitative Systems-Level Framework.

Aging is characterized by progressive functional decline and increased susceptibility to chronic disease. While directional epigenetic drift has been extensively documented, accumulating single-cell evidence indicates that aging is also associated with increased stochastic variability in chromatin states and gene expression. Here, we propose a quantitative systems-level framework in which epigenetic noise-defined as non-adaptive stochastic dispersion in regulatory states-contributes to aging by increasing regulatory entropy within gene regulatory networks. We formalize regulatory entropy using information-theoretic and network-based metrics, distinguish biological from technical variability, and outline experimentally testable predictions. Integrating single-cell atlases with methylation entropy, chromatin topology, and disease-associated datasets, we argue that rising regulatory entropy progressively destabilizes cellular identity and network coherence. This framework provides a complementary systems-level perspective on aging biology and suggests that preserving regulatory precision may represent a unifying strategy for extending healthspan.