Microglial Metabolic Reprogramming: The Missing Link in Chronic Neurodegeneration
DOI:
https://doi.org/10.63501/azz6za12Keywords:
microglia; immunometabolism; glycolysis; oxidative phosphorylation; mitochondrial dysfunction; inflammasome; neurodegenerationAbstract
Background:
Microglial activation and sustained neuroinflammation are central features of chronic neurodegenerative diseases. Emerging evidence indicates that microglial function is tightly linked to intracellular metabolic state, with shifts between oxidative phosphorylation (OXPHOS) and glycolysis shaping inflammatory output, phagocytosis, and neurotoxicity.
Objective:
To synthesize mechanistic, translational, and disease-specific evidence that positions microglial metabolic reprogramming as a key driver and potential therapeutic target in chronic neurodegeneration.
Methods:
Narrative synthesis of preclinical and clinical studies addressing microglial metabolism, mitochondrial dysfunction, inflammasome activation, and immunometabolic interventions.
Findings:
Pro-inflammatory stimuli (LPS, amyloid-β, α-synuclein) induce glycolytic reprogramming in microglia, accompanied by mitochondrial dysfunction, ROS generation, and NLRP3 inflammasome activation (3,6,9). Disease-specific evidence links these metabolic shifts to impaired debris clearance and sustained cytokine release in Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and ALS (8,10–13). Aging-associated metabolic drift primes microglia toward inflammatory phenotypes (14). Interventions targeting glycolysis, AMPK activation, or NLRP3 show preclinical promise (3,6,16).
Conclusion:
Microglial immunometabolism provides a mechanistic bridge between chronic inflammation and neurodegeneration. Precision metabolic modulation of microglia — recalibrating rather than suppressing activity — is a promising translational strategy warranting biomarker-guided clinical evaluation.
References
1. Cherry, J. D., Olschowka, J. A., & O’Banion, M. K. (2014). Neuroinflammation and M2 microglia: The good, the bad, and the inflamed. Journal of Neuroinflammation, 11(1), 98. https://doi.org/10.1186/1742-2094-11-98
2. Ransohoff, R. M. (2016). A polarizing question: Do M1 and M2 microglia exist? Nature Neuroscience, 19(8), 987–991. https://doi.org/10.1038/nn.4338
3. Orihuela, R., McPherson, C. A., & Harry, G. J. (2016). Microglial M1/M2 polarization and metabolic states. British Journal of Pharmacology, 173(4), 649–665. https://doi.org/10.1111/bph.13139
4. Palsson-McDermott, E. M., & O’Neill, L. A. J. (2013). The Warburg effect then and now: From cancer to inflammatory diseases. BioEssays, 35(11), 965–973. https://doi.org/10.1002/bies.201300084
5. Tannahill, G. Á., Curtis, A. M., Adamik, J., Palsson-McDermott, E. M., McGettrick, A. F., Goel, G., Frezza, C., Bernard, N. J., Kelly, B., Foley, N. H., Zheng, L., & O’Neill, L. A. J. (2013). Succinate is an inflammatory signal that induces IL-1β through HIF-1α. Nature, 496(7444), 238–242. https://doi.org/10.1038/nature11986
6. Zhou, R., Yazdi, A. S., Menu, P., & Tschopp, J. (2011). A role for mitochondria in NLRP3 inflammasome activation. Nature, 469(7329), 221–225. https://doi.org/10.1038/nature09663
7. West, A. P., & Shadel, G. S. (2017). Mitochondrial DNA in innate immune responses and inflammatory pathology. Nature Reviews Immunology, 17(6), 363–375. https://doi.org/10.1038/nri.2017.21
8. Li, Y., Xia, X., Wang, Y., & Zheng, J. C. (2022). Mitochondrial dysfunction in microglia: A novel perspective for pathogenesis of Alzheimer’s disease. Journal of Neuroinflammation, 19(1), 248. https://doi.org/10.1186/s12974-022-02613-9
9. Keren-Shaul, H., Spinrad, A., Weiner, A., Matcovitch-Natan, O., Dvir-Szternfeld, R., Ulland, T. K., David, E., Baruch, K., Lara-Astaiso, D., Toth, B., Itzkovitz, S., Colonna, M., Schwartz, M., & Amit, I. (2017). A unique microglia type associated with restricting development of Alzheimer’s disease. Cell, 169(7), 1276–1290.e17. https://doi.org/10.1016/j.cell.2017.05.018
10. Elliott, T. R., Valencia, X., Chen, S., & Matta, A. (2025). Brain fog in Parkinson’s disease: Unraveling mechanisms and measuring impact. Frontiers in Neurology, 16, 1571079. https://doi.org/10.3389/fneur.2025.1571079
11. Gimeno-Bayón, J., López-López, A., Rodríguez, M. J., & Mahy, N. (2014). Glucose pathways adaptation supports acquisition of activated microglia phenotype. Journal of Neuroscience Research, 92(6), 723–731. https://doi.org/10.1002/jnr.23356
12. Abboud, G., Choi, S. C., Kanda, N., Zeumer-Spataro, L., Roopenian, D. C., & Morel, L. (2018). Inhibition of glycolysis reduces disease severity in an autoimmune model of rheumatoid arthritis. Frontiers in Immunology, 9, 1973. https://doi.org/10.3389/fimmu.2018.01973
13. Geloso, M. C., Corvino, V., Marchese, E., Serrano, A., Michetti, F., & D’Ambrosi, N. (2017). The dual role of microglia in ALS: Mechanisms and therapeutic approaches. Frontiers in Aging Neuroscience, 9, 242. https://doi.org/10.3389/fnagi.2017.00242
14. Spittau, B. (2017). Aging microglia—Phenotypes, functions, and implications for age-related neurodegenerative diseases. Frontiers in Aging Neuroscience, 9, 194. https://doi.org/10.3389/fnagi.2017.00194
15. Gauthier, T., & Chen, W. (2022). Modulation of macrophage immunometabolism: A new approach to fight infections. Frontiers in Immunology, 13, 780839. https://doi.org/10.3389/fimmu.2022.780839
16. Sag, D., Carling, D., Stout, R. D., & Suttles, J. (2008). Adenosine 5′-monophosphate-activated protein kinase promotes macrophage polarization to an anti-inflammatory functional phenotype. Journal of Immunology, 181(12), 8633–8641. https://doi.org/10.4049/jimmunol.181.12.8633
17. Ulland, T. K., Song, W. M., Huang, S. C., Ulrich, J. D., Sergushichev, A., Beatty, W. L., Loboda, A. A., Zhou, Y., Cairns, N. J., Kambal, A., Loginicheva, E., Gilfillan, S., Cella, M., Virgin, H. W., Unanue, E. R., Wang, Y., Artyomov, M. N., Holtzman, D. M., & Colonna, M. (2017). TREM2 maintains microglial metabolic fitness in Alzheimer’s disease. Cell, 170(4), 649–663.e13. https://doi.org/10.1016/j.cell.2017.07.023
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