Glial-neuron metabolic coupling in the central nervous system: Mechanisms, dysregulation in aging and injury, and implications for regeration

The central nervous system exhibits exceptionally high metabolic demands, yet neurons possess limited intrinsic metabolic reserves. As a result, neuronal function and survival depend on coordinated metabolic interactions with glial cells, a process collectively described as glial–neuron metabolic coupling. This review evaluates mechanistic and experimental evidence on glial–neuron metabolic interactions, identifies gaps and inconsistencies in current knowledge, and examines how these pathways are altered across aging, injury, and regeneration. A qualitative synthesis of mechanistic, experimental, and translational studies was conducted, focusing on astrocyte–neuron, oligodendrocyte–axon, and microglial–neuronal metabolic interactions. Evidence was integrated across aging, central nervous system injury, and regenerative contexts to identify conserved mechanisms and therapeutic opportunities. Evidence from experimental and translational studies indicates that astrocytes, oligodendrocytes, and microglia dynamically regulate neuronal energetics through lactate shuttling, lipid transfer, mitochondrial exchange, and immunometabolic signaling. Aging is associated with impaired glial glycolysis, reduced lactate availability, mitochondrial dysfunction, and chronic inflammatory metabolic states, contributing to neuronal vulnerability. Acute injury induces transient glycolytic reprogramming and metabolic compensation, which, when prolonged, promotes excitotoxicity and failed repair. In contrast, regenerative states engage adaptive glial metabolic responses, including enhanced lactate shuttling, mitochondrial donation, and redox remodeling, supporting neurogenesis, remyelination, and synaptic recovery. Glial–neuron metabolic coupling is a unifying framework linking energy metabolism to neural resilience, repair, and degeneration. While emerging pharmacological, dietary, and gene-based strategies targeting glial metabolism show promise, most evidence remains preclinical. Advancing clinical translation will require integrative multiomics approaches, improved metabolic imaging, and human-relevant models.