AUTHOR=Shichkova Polina , Coggan Jay S. , Kanari Lida , Boci Elvis , Favreau Cyrille , Antonel Stefano Maximiliano , Keller Daniel , Markram Henry 

TITLE=Breakdown and repair of metabolism in the aging brain

JOURNAL=Frontiers in Science

VOLUME=Volume 3 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/science/articles/10.3389/fsci.2025.1441297

DOI=10.3389/fsci.2025.1441297

ISSN=2813-6330

ABSTRACT=Age-related neurodegenerative disorders, including dementia, are a major global health concern. This article describes the first comprehensive, data-driven molecular model of the neuro-glia-vascular system to explore the complex relationships between the aging brain, energy metabolism, blood flow, and neuronal activity. Comprising 16,800 interaction pathways, the model includes all key enzymes, transporters, metabolites, and circulatory factors vital for neuronal electrical activity. We found significant alterations in metabolite concentrations and differential effects on adenosine triphosphate (ATP) supply in neurons and astrocytes and within subcellular compartments in aged brains and identified reduced sodium/potassium adenosine triphosphatase (Na+/K+-ATPase) activity as the leading cause of impaired neuronal action potentials. The model predicts that the metabolic pathways cluster more closely in the aged brain, suggesting a loss of robustness and adaptability. Additionally, the aged metabolic system displays reduced flexibility, undermining its capacity to efficiently respond to stimuli and recover from damage. Through transcription factor analysis, the estrogen-related receptor alpha (ESRRA) emerged as a central target connected to these aging-related changes. An unguided optimization search pinpointed potential interventions capable of restoring the brain’s metabolic flexibility and action potential generation. These strategies include increasing the nicotinamide adenine dinucleotide (NADH) cytosol-mitochondria shuttle, NAD+ pool, the ketone β-hydroxybutyrate, lactate, and Na+/K+-ATPase, while reducing blood glucose levels. The model is open sourced to help guide further research into brain metabolism.