Brain Age Acceleration on MRI Due to Poor Sleep: Associations, Mechanisms, and Clinical Implications

Sleep disturbances, affecting nearly half of middle-aged adults, have emerged as modifiable determinants of brain health and dementia risk. Recent advances in machine learning applied to MRI enable the estimation of "brain age," a biomarker that quantifies deviation from normative neural aging. This review synthesizes and critically evaluates converging evidence that poor sleep accelerates biological brain aging, identifies mechanistic pathways, and delineates translational barriers to clinical application. Across large-scale cohorts comprising more than 25,000 participants, suboptimal sleep independently predicts 1-3 years of MRI-derived brain age acceleration, even after adjusting for vascular and metabolic confounders. Objective sleep fragmentation and altered sleep-stage architecture exhibit sleep-specific neuroanatomical signatures, independent of amyloid and tau pathology, while inflammatory, vascular, and glymphatic mechanisms mediate a small fraction of the effect. Experimental sleep deprivation studies demonstrate reversibility of accelerated brain aging, highlighting opportunities for early intervention. Translation to clinical practice is constrained by methodological heterogeneity, reliance on self-reported sleep metrics, limited population diversity, and the absence of randomized intervention trials demonstrating causal reversibility. Addressing these gaps through standardized MRI-based biomarkers, longitudinal mechanistic studies, and interventional trials could establish sleep optimization as a viable neuroprotective strategy for dementia prevention.