Metabolic reprogramming-driven neuroimmunoregulation: Key mechanisms and therapeutic opportunities and challenges in...

Central nervous system (CNS) disorders are fundamentally linked to metabolic dysregulation within immune and glial cells. This review provides a systematic synthesis of immunometabolic reprogramming-encompassing glucose, lipid, and amino acid metabolism, and oxidative phosphorylation-in CNS-resident microglia, immunomodulatory astrocytes, and peripherally infiltrating immune cells (T cells, B cells, and neutrophils) across Alzheimer's disease, Parkinson's disease, multiple sclerosis, and ischemic stroke. Critically, rather than presenting all reported metabolic alterations as equivalently established, we introduce an evidence-transparency framework that systematically distinguishes the nature of supporting data-ranging from direct metabolic flux measurements (Seahorse, isotope tracing, lipidomics) and molecular correlates, to genetic/pharmacological perturbations, human tissue validation, and model-specific observations-enabling readers to independently assess the strength of each major conclusion. We further delineate aging as an active analytical dimension, demonstrating how age-related changes in mitochondrial quality control, lipid handling, redox buffering, and glial-immune crosstalk establish a permissive baseline that modifies disease-specific reprogramming trajectories. By integrating analyses of intercellular crosstalk, neuroinflammation, blood-brain barrier integrity, and oxidative stress, we illustrate both convergent and divergent metabolic mechanisms across diseases. Finally, we critically assess therapeutic strategies targeting immunometabolism, emphasizing shared translational obstacles including target selectivity, blood-brain barrier penetration, stage-dependent efficacy, and the inherent challenge of pathway pleiotropy. This review provides a conceptually grounded framework for interpreting immunometabolic evidence, navigating the gap between correlative findings and causal mechanisms, and guiding future hypothesis-driven therapeutic design for CNS disorders.