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Traumatic Brain Injury: Multi-Omics Insights into Brain Aging, Neurodegeneration, and Precision Therapeutics
Alaa Shafie1, Amal Adnan Ashour2, Muhanad Musaad Alhujaily3
1Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, P.O Box 11099, Taif 21944, Saudi Arabia; King Salman Center for Disability Research, Riyadh, 11614, Saudi Arabia.
Abstract:
Traumatic brain injury (TBI) is a major cause of mortality and persistent neurological disability and is increasingly recognized as a potential contributor to accelerated brain aging and long-term neurodegenerative processes. Beyond the immediate mechanical insult, TBI initiates dynamic secondary injury cascades involving chronic neuroinflammation, oxidative stress, mitochondrial dysfunction, synaptic and axonal degeneration, metabolic disturbances, and blood-brain barrier disruption. The persistence and temporal evolution of these molecular alterations may interact with intrinsic aging mechanisms, contributing to progressive neuronal dysfunction and increased vulnerability to age-associated neurodegenerative disorders. The marked biological and temporal heterogeneity of TBI therefore presents major challenges for conventional diagnostic, prognostic, and therapeutic approaches. Recent advances in multi-omics technologies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and single-cell and spatial approaches offer unprecedented opportunities to characterize the molecular trajectories linking TBI, brain aging, and neurodegeneration. Integrative multi-omics frameworks, coupled with network biology, artificial intelligence, machine learning, and causal inference, enable the identification of molecular signatures, age-related regulatory networks, clinically relevant biomarkers, and therapeutically actionable targets. This review synthesizes emerging multi-omics insights into the molecular mechanisms through which TBI may influence brain aging and neurodegenerative progression, with particular emphasis on phase-specific molecular signatures, biomarker discovery, patient stratification, therapeutic target prioritization, and precision neurotherapeutics. We further discuss longitudinal profiling, single-cell and spatial approaches, and AI-assisted modeling for patient stratification and therapeutic optimization. Integrating multi-omics with systems biology may provide a framework for studying TBI-associated brain aging and developing personalized interventions, although prospective clinical validation remains essential.
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