A Breakdown in Metabolic Reprogramming Causes Microglia Dysfunction in Alzheimer's Disease
Open accessAbstract
Reactive microglia are a major pathological feature of Alzheimer's disease (AD). However, the exact role of microglia in AD pathogenesis is still unclear. Here, using metabolic profiling, we found that exposure to amyloid-β triggers acute microglial inflammation accompanied by metabolic reprogramming from oxidative phosphorylation to glycolysis. It was dependent on the mTOR-HIF-1α pathway. However, once activated, microglia reached a chronic tolerant phase as a result of broad defects in energy metabolisms and subsequently diminished immune responses, including cytokine secretion and phagocytosis. Using genome-wide RNA sequencing and multiphoton microscopy techniques, we further identified metabolically defective microglia in 5XFAD mice, an AD mouse model. Finally, we showed that metabolic boosting with recombinant interferon-γ treatment reversed the defective glycolytic metabolism and inflammatory functions of microglia, thereby mitigating the AD pathology of 5XFAD mice. Collectively, metabolic reprogramming is crucial for microglial functions in AD, and modulating metabolism might be a new therapeutic strategy for AD.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Acute exposure of primary microglia to Aβ increases inflammatory cytokine secretion and phagocytic performance, while chronic exposure reduces phagocytosis and induces immune tolerance, as well as a metabolic shift from oxidative phosphorylation to glycolysis.
“Acute exposure of primary microglia to Aβ increased their inflammatory cytokine secretion and phagocytic performance, while chronic exposure reduced phagocytosis and induced immune tolerance, as well as a metabolic shift from oxidative phosphorylation to glycolysis77.”
From Amyloid-β induces lipid droplet-mediated microglial dysfunction via the enzyme DGAT2 in Alzheimer’s disease (2025) · cites this paper as [77]
The efficiency of individual phagocytic processes can be dependent on experimental conditions.
“although it is important to note that the efficiency of individual phagocytic processes can be dependent on experimental conditions65–67.”
From Transcriptional signature in microglia associated with Aβ plaque phagocytosis (2021) · cites this paper as [66]
Cites
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864 · see citing works
A Unique Microglia Type Associated with Restricting Development of Alzheimer’s Disease
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., et al. (2017) · Cell · doi:10.1016/j.cell.2017.05.018 · Cited by 5,493 · see citing works
Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O'Keeffe, S., Phatnani, H. P., Guarnieri, P., Caneda, C., Ruderisch, N., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1860-14.2014 · Cited by 4,875 · see citing works
Querfurth, H. W., & LaFerla, F. M. (2010) · New England Journal of Medicine · doi:10.1056/nejmra0909142 · Cited by 4,569 · see citing works
Succinate is an inflammatory signal that induces IL-1β through HIF-1α
Tannahill, G. M., Curtis, A. M., Adamik, J., Palsson-McDermott, E. M., McGettrick, A. F., Goel, G., Frezza, C., Bernard, N. J., Kelly, B., Foley, N. H., et al. (2013) · Nature · doi:10.1038/nature11986 · Cited by 4,176 · see citing works
ATP mediates rapid microglial response to local brain injury in vivo
Davalos, D., Grutzendler, J., Yang, G., Kim, J. V., Zuo, Y., Jung, S., Littman, D. R., Dustin, M. L., & Gan, W.-B. (2005) · Nature Neuroscience · doi:10.1038/nn1472 · Cited by 3,913 · see citing works
Self-citationOakley, H., Cole, S. L., Logan, S., Maus, E., Shao, P., Craft, J., Guillozet-Bongaarts, A., Ohno, M., Disterhoft, J., Van Eldik, L., et al. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.1202-06.2006 · Cited by 3,530 · see citing works
Epigenetic programming of monocyte-to-macrophage differentiation and trained innate immunity
Saeed, S., Quintin, J., Kerstens, H. H. D., Rao, N. A., Aghajanirefah, A., Matarese, F., Cheng, S.-C., Ratter, J., Berentsen, K., van der Ent, M. A., et al. (2014) · Science · doi:10.1126/science.1251086 · Cited by 1,761 · see citing works
TREM2 Maintains Microglial Metabolic Fitness in Alzheimer’s Disease
Ulland, T. K., Song, W. M., Huang, S. C.-C., Ulrich, J. D., Sergushichev, A., Beatty, W. L., Loboda, A. A., Zhou, Y., Cairns, N. J., Kambal, A., et al. (2017) · Cell · doi:10.1016/j.cell.2017.07.023 · Cited by 1,263 · see citing works
Innate immune memory in the brain shapes neurological disease hallmarks
Wendeln, A.-C., Degenhardt, K., Kaurani, L., Gertig, M., Ulas, T., Jain, G., Wagner, J., Häsler, L. M., Wild, K., Skodras, A., et al. (2018) · Nature · doi:10.1038/s41586-018-0023-4 · Cited by 956 · see citing works
Arts, R. J. W., Novakovic, B., ter Horst, R., Carvalho, A., Bekkering, S., Lachmandas, E., Rodrigues, F., Silvestre, R., Cheng, S.-C., Wang, S.-Y., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.10.008 · Cited by 930 · see citing works
Unexpected role of interferon-γ in regulating neuronal connectivity and social behaviour
Filiano, A. J., Xu, Y., Tustison, N. J., Marsh, R. L., Baker, W., Smirnov, I., Overall, C. C., Gadani, S. P., Turner, S. D., Weng, Z., et al. (2016) · Nature · doi:10.1038/nature18626 · Cited by 697 · see citing works
Bohlen, C. J., Bennett, F. C., Tucker, A. F., Collins, H. Y., Mulinyawe, S. B., & Barres, B. A. (2017) · Neuron · doi:10.1016/j.neuron.2017.04.043 · Cited by 676 · see citing works
Broad defects in the energy metabolism of leukocytes underlie immunoparalysis in sepsis
Cheng, S.-C., Scicluna, B. P., Arts, R. J. W., Gresnigt, M. S., Lachmandas, E., Giamarellos-Bourboulis, E. J., Kox, M., Manjeri, G. R., Wagenaars, J. A. L., Cremer, O. L., et al. (2016) · Nature Immunology · doi:10.1038/ni.3398 · Cited by 637 · see citing works
Krabbe, G., Halle, A., Matyash, V., Rinnenthal, J. L., Eom, G. D., Bernhardt, U., Miller, K. R., Prokop, S., Kettenmann, H., & Heppner, F. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060921 · Cited by 478 · see citing works
Autophagy in microglia degrades extracellular β-amyloid fibrils and regulates the NLRP3 inflammasome
Cho, M.-H., Cho, K., Kang, H.-J., Jeon, E.-Y., Kim, H.-S., Kwon, H.-J., Kim, H.-M., Kim, D.-H., & Yoon, S.-Y. (2014) · Autophagy · doi:10.4161/auto.29647 · Cited by 395 · see citing works
Il10 Deficiency Rebalances Innate Immunity to Mitigate Alzheimer-Like Pathology
Guillot-Sestier, M.-V., Doty, K. R., Gate, D., Rodriguez, J., Leung, B. P., Rezai-Zadeh, K., & Town, T. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.068 · Cited by 363 · see citing works
Baik, S. H., Kang, S., Son, S. M., & Mook-Jung, I. (2016) · Glia · doi:10.1002/glia.23074 · Cited by 234 · see citing works
Self-citationChakrabarty, P., Ceballos-Diaz, C., Beccard, A., Janus, C., Dickson, D., Golde, T. E., & Das, P. (2010) · The Journal of Immunology · doi:10.4049/jimmunol.0903382 · Cited by 206 · see citing works
Kroczynska, B., Rafidi, R. L., Majchrzak-Kita, B., Kosciuczuk, E. M., Blyth, G. T., Jemielity, J., Warminska, Z., Saleiro, D., Mehrotra, S., Arslan, A. D., et al. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.m115.664995 · Cited by 29 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Microglia in neurodegenerative diseases: mechanism and potential therapeutic targets
Gao, C., Jiang, J., Tan, Y., & Chen, S. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01588-0 · Cited by 1,616 · see citing works
Amyloid β-based therapy for Alzheimer’s disease: Challenges, successes and future
Zhang, Y., Chen, H., Li, R., Sterling, K., & Song, W. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01484-7 · Cited by 988 · see citing works
“One potential explanation for the activated glia cells in AD brain could be the response to Aβ produced largely by neurons.(157,158) Aβ shares structural similarities with antimicrobial peptides (AMPs) and viral fusion domains, which stimulates glia cells to secrete a mass of pro-inflammatory cytokines.”
BackgroundPan, R.-Y., He, L., Zhang, J., Liu, X., Liao, Y., Gao, J., Liao, Y., Yan, Y., Li, Q., Zhou, X., et al. (2022) · Cell Metabolism · doi:10.1016/j.cmet.2022.02.013 · Cited by 862 · see citing works
Kim, M.-S., Kim, Y., Choi, H., Kim, W., Park, S., Lee, D., Kim, D. K., Kim, H. J., Choi, H., Hyun, D.-W., et al. (2020) · Gut · doi:10.1136/gutjnl-2018-317431 · Cited by 614 · see citing works
Self-citationErny, D., Dokalis, N., Mezö, C., Castoldi, A., Mossad, O., Staszewski, O., Frosch, M., Villa, M., Fuchs, V., Mayer, A., et al. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.10.010 · Cited by 478 · see citing works
Microglia: Agents of the CNS Pro-Inflammatory Response
Rodríguez-Gómez, J. A., Kavanagh, E., Engskog-Vlachos, P., Engskog, M. K. R., Herrera, A. J., Espinosa-Oliva, A. M., Joseph, B., Hajji, N., Venero, J. L., & Burguillos, M. A. (2020) · Cells · doi:10.3390/cells9071717 · Cited by 365 · see citing works
Transcriptional signature in microglia associated with Aβ plaque phagocytosis
Grubman, A., Choo, X. Y., Chew, G., Ouyang, J. F., Sun, G., Croft, N. P., Rossello, F. J., Simmons, R., Buckberry, S., Landin, D. V., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23111-1 · Cited by 357 · see citing works
Cai, Y., Liu, J., Wang, B., Sun, M., & Yang, H. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.856376 · Cited by 351 · see citing works
Lipid accumulation induced by APOE4 impairs microglial surveillance of neuronal-network activity
Victor, M. B., Leary, N., Luna, X., Meharena, H. S., Scannail, A. N., Bozzelli, P. L., Samaan, G., Murdock, M. H., von Maydell, D., Effenberger, A. H., et al. (2022) · Cell Stem Cell · doi:10.1016/j.stem.2022.07.005 · Cited by 316 · see citing works
Lonnemann, N., Hosseini, S., Marchetti, C., Skouras, D. B., Stefanoni, D., D’Alessandro, A., Dinarello, C. A., & Korte, M. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2009680117 · Cited by 298 · see citing works
Microglia and the aging brain: are senescent microglia the key to neurodegeneration?
Angelova, D. M., & Brown, D. R. (2019) · Journal of Neurochemistry · doi:10.1111/jnc.14860 · Cited by 262 · see citing works
Lipid and Lipoprotein Metabolism in Microglia
Loving, B. A., & Bruce, K. D. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.00393 · Cited by 255 · see citing works
The Role of Microglia and the Nlrp3 Inflammasome in Alzheimer's Disease
Hanslik, K. L., & Ulland, T. K. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.570711 · Cited by 236 · see citing works
Microglia reprogram metabolic profiles for phenotype and function changes in central nervous system
Yang, S., Qin, C., Hu, Z.-W., Zhou, L.-Q., Yu, H.-H., Chen, M., Bosco, D. B., Wang, W., Wu, L.-J., & Tian, D.-S. (2021) · Neurobiology of Disease · doi:10.1016/j.nbd.2021.105290 · Cited by 232 · see citing works
Lee, S., Devanney, N. A., Golden, L. R., Smith, C. T., Schwartz, J. L., Walsh, A. E., Clarke, H. A., Goulding, D. S., Allenger, E. J., Morillo-Segovia, G., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112196 · Cited by 203 · see citing works
Liu, C.-C., Wang, N., Chen, Y., Inoue, Y., Shue, F., Ren, Y., Wang, M., Qiao, W., Ikezu, T. C., Li, Z., et al. (2023) · Nature Immunology · doi:10.1038/s41590-023-01640-9 · Cited by 146 · see citing works
Hypoxia compromises the mitochondrial metabolism of Alzheimer’s disease microglia via HIF1
March-Diaz, R., Lara-Ureña, N., Romero-Molina, C., Heras-Garvin, A., Ortega-de San Luis, C., Alvarez-Vergara, M. I., Sanchez-Garcia, M. A., Sanchez-Mejias, E., Davila, J. C., Rosales-Nieves, A. E., et al. (2021) · Nature Aging · doi:10.1038/s43587-021-00054-2 · Cited by 125 · see citing works
Microglia in Aging and Alzheimer’s Disease: A Comparative Species Review
Edler, M. K., Mhatre-Winters, I., & Richardson, J. R. (2021) · Cells · doi:10.3390/cells10051138 · Cited by 126 · see citing works
TRPV1 sustains microglial metabolic reprogramming in Alzheimer's disease
Lu, J., Zhou, W., Dou, F., Wang, C., & Yu, Z. (2021) · The EMBO Reports · doi:10.15252/embr.202052013 · Cited by 121 · see citing works
Prakash, P., Manchanda, P., Paouri, E., Bisht, K., Sharma, K., Rajpoot, J., Wendt, V., Hossain, A., Wijewardhane, P. R., Randolph, C. E., et al. (2025) · Immunity · doi:10.1016/j.immuni.2025.04.029 · Cited by 104 · see citing works
Chung, S., Jeong, J.-H., Park, J.-C., Han, J. W., Lee, Y., Kim, J.-I., & Mook-Jung, I. (2024) · Experimental & Molecular Medicine · doi:10.1038/s12276-024-01295-y · Cited by 103 · see citing works
“Identifying the causes and key drivers of microglial phenotypic changes is crucial for understanding and modulating the pathophysiology of neurodegenerative diseases 3 .”
Self-citationSingh, N., Das, B., Zhou, J., Hu, X., & Yan, R. (2022) · Science Advances · doi:10.1126/sciadv.abo3610 · Cited by 95 · see citing works
Lee, H., Cho, S., Kim, M.-J., Park, Y. J., Cho, E., Jo, Y. S., Kim, Y.-S., Lee, J. Y., Thoudam, T., Woo, S.-H., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113183 · Cited by 93 · see citing works
Glucose metabolism, neural cell senescence and Alzheimer's disease
Wang, Q., Duan, L., Li, X., Wang, Y., Guo, W., Guan, F., & Ma, S. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23084351 · Cited by 90 · see citing works
Zhang, B., Chen, T., Cao, M., Yuan, C., Reiter, R. J., Zhao, Z., Zhao, Y., Chen, L., Fan, W., Wang, X., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.900132 · Cited by 80 · see citing works
Microglia gone awry: linking immunometabolism to neurodegeneration
Afridi, R., Lee, W.-H., & Suk, K. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2020.00246 · Cited by 64 · see citing works
Self-citationHuang, Q., Wang, Y., Chen, S., & Liang, F. (2023) · Aging and disease · doi:10.14336/ad.2023.0807 · Cited by 62 · see citing works
Shan, C., Zhang, D., Ma, D.-N., Hou, Y.-F., Zhuang, Q.-Q., Gong, Y.-L., Sun, L.-H., Zhao, H.-Y., Tao, B., Yang, Y.-Y., et al. (2023) · Cell Death Discovery · doi:10.1038/s41420-023-01343-y · Cited by 53 · see citing works
Poles, M. Z., Nászai, A., Gulácsi, L., Czakó, B. L., Gál, K. G., Glenz, R. J., Dookhun, D., Rutai, A., Tallósy, S. P., Szabó, A., et al. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.717157 · Cited by 49 · see citing works
Regulation of microglial physiology by the microbiota
Cook, J., & Prinz, M. (2022) · Gut Microbes · doi:10.1080/19490976.2022.2125739 · Cited by 49 · see citing works
Erythropoietin signaling in peripheral macrophages is required for systemic β‐amyloid clearance
Xu, L., Li, L., Pan, C., Song, J., Zhang, C., Wu, X., Hu, F., Liu, X., Zhang, Z., & Zhang, Z. (2022) · The EMBO Journal · doi:10.15252/embj.2022111038 · Cited by 29 · see citing works
Versatile nanomaterials for Alzheimer’s disease: Pathogenesis inspired disease-modifying therapy
Xi, Y., Chen, Y., Jin, Y., Han, G., Song, M., Song, T., Shi, Y., Tao, L., Huang, Z., Zhou, J., et al. (2022) · Journal of Controlled Release · doi:10.1016/j.jconrel.2022.02.034 · Cited by 27 · see citing works
Scott-Solache, J., Pei, J., Drew, J., López-Doménech, G., Jolivet, R. B., Nieto-Rostro, M., Davenport, E. C., Arancibia-Cárcamo, I. L., Attwell, D., & Kittler, J. T. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2532488123 · Cited by 2 · see citing works
“CYFIP1 has been associated with regulating the function of mTOR complex 1 (mTORC1) in neurons (37, 38). mTORC1 is crucial for controlling many aspects of microglial activity including inflammation (52), metabolism (53), and phagocytosis (54, 55).”
- Authors
- Baik, S. H., Kang, S., Lee, W., Choi, H., Chung, S., Kim, J.-I., & Mook-Jung, I.
- Affiliations
- Seoul National University (KR)
- Venue
- Cell Metabolism
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 30
- Issue
- 3
- Pages
- 493-507.e6
- ISSN
- 1550-4131 (ISSN-L)
- OpenAlex
- W2954390789
- Cited by
- 843
- References
- 20
- Citations by year
- 2026: 150 · 2025: 144 · 2024: 171 · 2023: 113 · 2022: 123 · 2021: 82 · 2020: 50 · 2019: 9
- FWCI
- 29.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell Metabolism (publishedVersion)
- PubMed (publishedVersion)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Funders
- National Research Foundation of Korea
- Topics
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neurological Disease Mechanisms and Treatments
- Keywords
- Alzheimer's disease, microglia, metabolic reprogramming, amyloid-beta, microglial inflammation, oxidative phosphorylation, glycolysis, mTOR, HIF-1α, energy metabolism, phagocytosis, cytokine production, interferon-gamma, 5xFAD mice, treatment options
- MeSH terms
- Alzheimer Disease, Animals, Cell Line, Disease Models, Animal, Female, Gene Expression Regulation, Glycolysis, Inflammation, Interferon-gamma, Male, Mice, Inbred ICR, Mice, Transgenic, Oxidative Phosphorylation, Phagocytosis, Recombinant Proteins, Cytokines, Amyloid beta-Peptides, Microglia, Mice, Hypoxia-Inducible Factor 1, alpha Subunit, TOR Serine-Threonine Kinases
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
