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Loss of fatty acid degradation by astrocytic mitochondria triggers neuroinflammation and neurodegeneration

Nature Metabolism volume 5, pages 445–465 (2023)Cite this article

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Abstract

Astrocytes provide key neuronal support, and their phenotypic transformation is implicated in neurodegenerative diseases. Metabolically, astrocytes possess low mitochondrial oxidative phosphorylation (OxPhos) activity, but its pathophysiological role in neurodegeneration remains unclear. Here, we show that the brain critically depends on astrocytic OxPhos to degrade fatty acids (FAs) and maintain lipid homeostasis. Aberrant astrocytic OxPhos induces lipid droplet (LD) accumulation followed by neurodegeneration that recapitulates key features of Alzheimer’s disease (AD), including synaptic loss, neuroinflammation, demyelination and cognitive impairment. Mechanistically, when FA load overwhelms astrocytic OxPhos capacity, elevated acetyl-CoA levels induce astrocyte reactivity by enhancing STAT3 acetylation and activation. Intercellularly, lipid-laden reactive astrocytes stimulate neuronal FA oxidation and oxidative stress, activate microglia through IL-3 signalling, and inhibit the biosynthesis of FAs and phospholipids required for myelin replenishment. Along with LD accumulation and impaired FA degradation manifested in an AD mouse model, we reveal a lipid-centric, AD-resembling mechanism by which astrocytic mitochondrial dysfunction progressively induces neuroinflammation and neurodegeneration.

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Fig. 1: Astrocyte-specific Tfam deletion induces cognitive impairment and neurodegeneration.
Fig. 2: Aberrant astrocytic OxPhos disrupts brain lipid homeostasis.
Fig. 3: Loss of astrocytic FA degradation leads to LD accumulation and reactive astrogliosis.
Fig. 4: Acetylation of STAT3 mediates FA- and TfamAKO-induced astrocyte reactivity.
Fig. 5: Impaired astrocytic FA degradation diminishes neurotrophic support and triggers neuronal FAO and oxidative stress.
Fig. 6: Astrocytes with OxPhos deficiency promote microglial activation and neuroinflammation through IL-3.
Fig. 7: Loss of astrocytic FA degradation suppresses lipid synthesis and induces demyelination.
Fig. 8: Impaired FA degradation, LD accumulation and TfamAKO-induced transcriptional signatures in a mouse model of AD.

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Data availability

The RNA-seq data for the TfamAKO mice have been deposited in Gene Expression Omnibus (GEO) repository under accession number GSE203234 and can be accessed at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE203234. Source data are provided with this paper.

References

  1. Cunnane, S. C. et al. Brain energy rescue: an emerging therapeutic concept for neurodegenerative disorders of ageing. Nat. Rev. Drug Discov. 19, 609–633 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Qi, G., Mi, Y. & Yin, F. Cellular specificity and inter-cellular coordination in the brain bioenergetic system: implications for aging and neurodegeneration. Front. Physiol. 10, 1531 (2019).

    Article  PubMed  Google Scholar 

  3. Wang, W., Zhao, F., Ma, X., Perry, G. & Zhu, X. Mitochondria dysfunction in the pathogenesis of Alzheimer’s disease: recent advances. Mol. Neurodegener. 15, 30 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Baik, S. H. et al. A breakdown in metabolic reprogramming causes microglia dysfunction in Alzheimer’s disease. Cell Metab. 30, 493–507 (2019).

    Article  CAS  PubMed  Google Scholar 

  5. March-Diaz, R. et al. Hypoxia compromises the mitochondrial metabolism of Alzheimer’s disease microglia via HIF1. Nat. Aging 1, 385–399 (2021).

    Article  Google Scholar 

  6. Sofroniew, M. V. & Vinters, H. V. Astrocytes: biology and pathology. Acta Neuropathol. 119, 7–35 (2010).

    Article  PubMed  Google Scholar 

  7. Linnerbauer, M., Wheeler, M. A. & Quintana, F. J. Astrocyte crosstalk in CNS inflammation. Neuron 108, 608–622 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Escartin, C. et al. Reactive astrocyte nomenclature, definitions, and future directions. Nat. Neurosci. 24, 312–325 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Almeida, A., Almeida, J., Bolanos, J. P. & Moncada, S. Different responses of astrocytes and neurons to nitric oxide: the role of glycolytically generated ATP in astrocyte protection. Proc. Natl Acad. Sci. USA 98, 15294–15299 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Wong-Riley, M. T. Cytochrome oxidase: an endogenous metabolic marker for neuronal activity. Trends Neurosci. 12, 94–101 (1989).

    Article  CAS  PubMed  Google Scholar 

  11. Bonvento, G. & Bolanos, J. P. Astrocyte-neuron metabolic cooperation shapes brain activity. Cell Metab. 33, 1546–1564 (2021).

    Article  CAS  PubMed  Google Scholar 

  12. Lopez-Fabuel, I. et al. Complex I assembly into supercomplexes determines differential mitochondrial ROS production in neurons and astrocytes. Proc. Natl Acad. Sci. USA 113, 13063–13068 (2016).

  13. Fecher, C. et al. Cell-type-specific profiling of brain mitochondria reveals functional and molecular diversity. Nat. Neurosci. 22, 1731–1742 (2019).

    Article  CAS  PubMed  Google Scholar 

  14. Yin, F. Lipid metabolism and Alzheimer’s disease: clinical evidence, mechanistic link and therapeutic promise. FEBS J. https://doi.org/10.1111/febs.16344 (2022).

  15. Karch, C. M. & Goate, A. M. Alzheimer’s disease risk genes and mechanisms of disease pathogenesis. Biol. Psychiatry 77, 43–51 (2015).

    Article  CAS  PubMed  Google Scholar 

  16. Qi, G. et al. ApoE4 impairs neuron–astrocyte coupling of fatty acid metabolism. Cell Rep. 34, 108572 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Gustafsson, C. M., Falkenberg, M. & Larsson, N. G. Maintenance and expression of mammalian mitochondrial DNA. Annu. Rev. Biochem. 85, 133–160 (2016).

    Article  CAS  PubMed  Google Scholar 

  18. Hamanaka, R. B. et al. Mitochondrial reactive oxygen species promote epidermal differentiation and hair follicle development. Sci. Signal. 6, ra8 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Gregorian, C. et al. Pten deletion in adult neural stem/progenitor cells enhances constitutive neurogenesis. J. Neurosci. 29, 1874–1886 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Endo, F. et al. Molecular basis of astrocyte diversity and morphology across the CNS in health and disease. Science 378, eadc9020 (2022).

    Article  CAS  PubMed  Google Scholar 

  21. Taft, J. R., Vertes, R. P. & Perry, G. Distribution of GFAP+ astrocytes in adult and neonatal rat brain. Int. J. Neurosci. 115, 1333–1343 (2005).

    Article  CAS  PubMed  Google Scholar 

  22. Rath, S. et al. MitoCarta3.0: an updated mitochondrial proteome now with sub-organelle localization and pathway annotations. Nucleic Acids Res. 49, D1541–D1547 (2021).

    Article  CAS  PubMed  Google Scholar 

  23. Olzmann, J. A. & Carvalho, P. Dynamics and functions of lipid droplets. Nat. Rev. Mol. Cell Biol. 20, 137–155 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Serrano-Pozo, A., Gomez-Isla, T., Growdon, J. H., Frosch, M. P. & Hyman, B. T. A phenotypic change but not proliferation underlies glial responses in Alzheimer disease. Am. J. Pathol. 182, 2332–2344 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Rambold, A. S., Cohen, S. & Lippincott-Schwartz, J. Fatty acid trafficking in starved cells: regulation by lipid droplet lipolysis, autophagy, and mitochondrial fusion dynamics. Dev. Cell 32, 678–692 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ceyzeriat, K., Abjean, L., Carrillo-de Sauvage, M. A., Ben Haim, L. & Escartin, C. The complex STATes of astrocyte reactivity: how are they controlled by the JAK–STAT3 pathway? Neuroscience 330, 205–218 (2016).

    Article  CAS  PubMed  Google Scholar 

  27. Allaman, I. et al. Amyloid-beta aggregates cause alterations of astrocytic metabolic phenotype: impact on neuronal viability. J. Neurosci. 30, 3326–3338 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Yuan, Z. L., Guan, Y. J., Chatterjee, D. & Chin, Y. E. Stat3 dimerization regulated by reversible acetylation of a single lysine residue. Science 307, 269–273 (2005).

    Article  CAS  PubMed  Google Scholar 

  29. Wellen, K. E. et al. ATP-citrate lyase links cellular metabolism to histone acetylation. Science 324, 1076–1080 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Liu, L., MacKenzie, K. R., Putluri, N., Maletic-Savatic, M. & Bellen, H. J. The glia-neuron lactate shuttle and elevated ROS promote lipid synthesis in neurons and lipid droplet accumulation in glia via APOE/D. Cell Metab. 26, 719–737 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Schonfeld, P. & Reiser, G. Brain energy metabolism spurns fatty acids as fuel due to their inherent mitotoxicity and potential capacity to unleash neurodegeneration. Neurochem. Int. 109, 68–77 (2017).

    Article  PubMed  Google Scholar 

  32. Heneka, M. T. et al. Neuroinflammation in Alzheimer’s disease. Lancet Neurol. 14, 388–405 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. McAlpine, C. S. et al. Astrocytic interleukin-3 programs microglia and limits Alzheimer’s disease. Nature 595, 701–706 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Taylor, A. N. W. et al. Tract-specific white matter hyperintensities disrupt neural network function in Alzheimer’s disease. Alzheimers Dement. 13, 225–235 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Chen, J. F. et al. Enhancing myelin renewal reverses cognitive dysfunction in a murine model of Alzheimer’s disease. Neuron 109, 2292–2307 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Yeung, M. S. et al. Dynamics of oligodendrocyte generation and myelination in the human brain. Cell 159, 766–774 (2014).

    Article  CAS  PubMed  Google Scholar 

  37. Camargo, N. et al. Oligodendroglial myelination requires astrocyte-derived lipids. PLoS Biol. 15, e1002605 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Dimas, P. et al. CNS myelination and remyelination depend on fatty acid synthesis by oligodendrocytes. eLife 8, e44702 (2019).

  39. Oakley, H. et al. Intraneuronal beta-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s disease mutations: potential factors in amyloid plaque formation. J. Neurosci. 26, 10129–10140 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Forner, S. et al. Systematic phenotyping and characterization of the 5×FAD mouse model of Alzheimer’s disease. Sci. Data 8, 270 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Supek, F., Bosnjak, M., Skunca, N. & Smuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE 6, e21800 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. De Miguel, Z. et al. Exercise plasma boosts memory and dampens brain inflammation via clusterin. Nature 600, 494–499 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Halim, N. D. et al. Phosphorylation status of pyruvate dehydrogenase distinguishes metabolic phenotypes of cultured rat brain astrocytes and neurons. Glia 58, 1168–1176 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Vernochet, C. et al. Adipose-specific deletion of TFAM increases mitochondrial oxidation and protects mice against obesity and insulin resistance. Cell Metab. 16, 765–776 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Ignatenko, O. et al. Loss of mtDNA activates astrocytes and leads to spongiotic encephalopathy. Nat. Commun. 9, 70 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Conte, M. et al. Expression pattern of perilipins in human brain during aging and in Alzheimer’s disease. Neuropathol. Appl. Neurobiol. 48, e12756 (2021).

    PubMed  PubMed Central  Google Scholar 

  48. Sofroniew, M. V. Astrocyte reactivity: subtypes, states, and functions in CNS innate immunity. Trends Immunol. 41, 758–770 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Vicente-Gutierrez, C. et al. Astrocytic mitochondrial ROS modulate brain metabolism and mouse behaviour. Nat. Metab. 1, 201–211 (2019).

    Article  CAS  PubMed  Google Scholar 

  50. Liddelow, S. A. et al. Neurotoxic reactive astrocytes are induced by activated microglia. Nature 541, 481–487 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Guttenplan, K. A. et al. Neurotoxic reactive astrocytes induce cell death via saturated lipids. Nature 599, 102–107 (2021).

    Article  CAS  PubMed  Google Scholar 

  52. Pinkosky, S. L. et al. Long-chain fatty acyl-CoA esters regulate metabolism via allosteric control of AMPK beta1 isoforms. Nat. Metab. 2, 873–881 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Garcia, D. & Shaw, R. J. AMPK: mechanisms of cellular energy sensing and restoration of metabolic balance. Mol. Cell 66, 789–800 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. van Deijk, A. F. et al. Astrocyte lipid metabolism is critical for synapse development and function in vivo. Glia 65, 670–682 (2017).

    Article  PubMed  Google Scholar 

  55. Johnson, E. C. B. et al. Large-scale proteomic analysis of Alzheimer’s disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation. Nat. Med. 26, 769–780 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Williams, T. I., Lynn, B. C., Markesbery, W. R. & Lovell, M. A. Increased levels of 4-hydroxynonenal and acrolein, neurotoxic markers of lipid peroxidation, in the brain in mild cognitive impairment and early Alzheimer’s disease. Neurobiol. Aging 27, 1094–1099 (2006).

    Article  CAS  PubMed  Google Scholar 

  57. Konttinen, H. et al. PPARβ/δ-agonist GW0742 ameliorates dysfunction in fatty acid oxidation in PSEN1∆E9 astrocytes. Glia 67, 146–159 (2019).

  58. Karran, E., Mercken, M. & De Strooper, B. The amyloid cascade hypothesis for Alzheimer’s disease: an appraisal for the development of therapeutics. Nat. Rev. Drug Discov. 10, 698–712 (2011).

    Article  CAS  PubMed  Google Scholar 

  59. Swerdlow, R. H., Burns, J. M. & Khan, S. M. The Alzheimer’s disease mitochondrial cascade hypothesis: progress and perspectives. Biochim. Biophys. Acta 1842, 1219–1231 (2014).

    Article  CAS  PubMed  Google Scholar 

  60. Martens, Y. A. et al. ApoE cascade hypothesis in the pathogenesis of Alzheimer’s disease and related dementias. Neuron 110, 1304–1317 (2022).

    Article  CAS  PubMed  Google Scholar 

  61. Fanning, S. et al. Lipidomic analysis of α-synuclein neurotoxicity identifies stearoyl CoA desaturase as a target for Parkinson treatment. Mol. Cell 73, 1001–1014 (2019).

    Article  CAS  PubMed  Google Scholar 

  62. Lee, H. et al. Multi-omic analysis of selectively vulnerable motor neuron subtypes implicates altered lipid metabolism in ALS. Nat. Neurosci. 24, 1673–1685 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Polyzos, A. A. et al. Metabolic reprogramming in astrocytes distinguishes region-specific neuronal susceptibility in Huntington mice. Cell Metab. 29, 1258–1273 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Dong, Y. et al. Oxidized phosphatidylcholines found in multiple sclerosis lesions mediate neurodegeneration and are neutralized by microglia. Nat. Neurosci. 24, 489–503 (2021).

    Article  CAS  PubMed  Google Scholar 

  65. Qi, G., Mi, Y. & Yin, F. Characterizing brain metabolic function ex vivo with acute mouse slice punches. STAR Protoc. 2, 100559 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Yin, F. et al. The perimenopausal aging transition in the female rat brain: decline in bioenergetic systems and synaptic plasticity. Neurobiol. Aging 36, 2282–2295 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Eghlimi, R., Shi, X., Hrovat, J., Xi, B. & Gu, H. Triple negative breast cancer detection using LC–MS/MS lipidomic profiling. J. Proteome Res. 19, 2367–2378 (2020).

    Article  CAS  PubMed  Google Scholar 

  68. Shi, X. et al. Comprehensive isotopic targeted mass spectrometry: reliable metabolic flux analysis with broad coverage. Anal. Chem. 92, 11728–11738 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M. & Nichols, T. E. Permutation inference for the general linear model. Neuroimage 92, 381–397 (2014).

    Article  PubMed  Google Scholar 

  70. Tournier, J. D. et al. MRtrix3: a fast, flexible and open software framework for medical image processing and visualisation. Neuroimage 202, 116137 (2019).

    Article  PubMed  Google Scholar 

  71. Chang, L. C., Jones, D. K. & Pierpaoli, C. RESTORE: robust estimation of tensors by outlier rejection. Magn. Reson. Med. 53, 1088–1095 (2005).

    Article  PubMed  Google Scholar 

  72. Smith, S. M. et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23, S208–S219 (2004).

    Article  PubMed  Google Scholar 

  73. Yeh, F.-C. et al. Automatic removal of false connections in diffusion MRI tractography using topology-informed pruning (TIP). Neurotherapeutics 16, 52–58 (2019).

    Article  PubMed  Google Scholar 

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Acknowledgements

This work has been supported by the National Institute on Aging (NIA) grants RF1AG068175 to F.Y., P01AG026572 (Project 1 and Analytic Core to F.Y.), University of Arizona Center for Innovation in Brain Science Startup Fund to F.Y., Arizona Alzheimer’s Consortium Pilot Project grants to F.Y. and the Packer-Wenz research endowment to F.Y. H.G. is supported by R21AG072561. We thank A. Bhattrai and the University of Arizona Translational Bioimaging Resource for their assistance in small animal MRI scans. The 5×FAD mouse transcriptomics data were obtained from the AD Knowledge Portal (https://adknowledgeportal.synapse.org/), and these data were generated by IU/JAX/UCI MODEL-AD Center with funding from NIA (U54 AG054345-01, U54 AG054349 and P30 AG0380770).

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Author notes

  1. These authors contributed equally: Yashi Mi, Guoyuan Qi.

Authors and Affiliations

  1. Center for Innovation in Brain Science, University of Arizona Health Sciences, Tucson, AZ, USA

    Yashi Mi, Guoyuan Qi, Francesca Vitali, Yuan Shang, Adam C. Raikes, Tian Wang, Roberta D. Brinton & Fei Yin

  2. Department of Neurology, College of Medicine Tucson, University of Arizona, Tucson, AZ, USA

    Francesca Vitali, Tian Wang & Roberta D. Brinton

  3. Center of Translational Science, Florida International University, Port St. Lucie, FL, USA

    Yan Jin & Haiwei Gu

  4. Department of Pharmacology, College of Medicine Tucson, University of Arizona, Tucson, AZ, USA

    Roberta D. Brinton & Fei Yin

  5. Graduate Interdisciplinary Program in Neuroscience, University of Arizona, Tucson, AZ, USA

    Roberta D. Brinton & Fei Yin

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Contributions

Conceptualization, F.Y.; methodology, F.Y., Y.M., G.Q., T.W. and H.G.; investigation, Y.M., G.Q. and Y.J.; formal analysis, Y.M., G.Q., F.Y., F.V., Y.S. and A.C.R.; writing—original draft, F.Y., Y.M. and G.Q.; writing—review and editing, F.Y., T.W., F.V., Y.S., A.C.R., R.D.B. and H.G.; funding acquisition, F.Y.

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Correspondence to Fei Yin.

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Nature Metabolism thanks Maria Ioannou, Robert C. Cumming and Frida Loria for their contribution to the peer review of this work. Primary Handling Editor: Alfredo Gimenez-Cassina, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 Astrocytic Tfam deletion-induced neurodegeneration in 6- but not 1.5-month-old mice.

a, Schematic diagram of the generating of astrocyte specific Tfam knockout allele. b, Western blots and quantification showing protein levels of Tfam in 3-month and 1.5-month WT and TfamAKO mouse hippocampi. c, Tfam mRNA levels in neurons, astrocytes, and microglia acutely isolated from 6-month WT and TfamAKO mouse brains. d-e, Representative mitochondrial stress test performed with primary astrocytes isolated from 6-month WT or TfamAKO mouse brains with sequential injections of mitochondrial inhibitors including oligomycin A, FCCP and rotenone + antimycin A (d); basal, maximal, and uncoupling-linked respiration were shown in (e). f, Brain weight of 6-month WT and TfamAKO mice. g, The ratio between distance travelled in the center area and total distance travelled for 6-month mice. h, Discrimination index of 1.5-month WT and TfamAKO mice in NOR test. i-j, Representative tracks (i) and time spent in the center area (marked by orange squares) and the ratio between distance travelled in the center and total distance travelled (j) for 1.5-month WT and TfamAKO mice. k, Speed, LF swing, and LF step cycle of 6-month WT and TfamAKO mice in CatWalk tests. l, Tfam mRNA levels in the cerebellum and brainstem of 6-month mice. n = 5 (3-mon) or 4 (1.5-mon) mice (b); n = 5 (astrocyte and neuron) or 6 (microglia) mice (c); n = 14 (WT) or 16 (AKO) wells (d,e); n = 5 mice (f, j, l); n = 13 (WT) or 9 (AKO) mice (g); n = 5 (WT) or 4 (AKO) mice (h); n = 14 (WT) or 17 (AKO) mice (k). Bar graphs are presented as mean ± SEM. Two-sided unpaired t-test was used for all comparisons.

Source data

Extended Data Fig. 2 TfamAKO has no effect on neurogenesis or neuronal death, and synaptic deficits occur after 3-month-of-age.

a, Densitometric analyses of MAP-2, PSD95, and SNAP25 protein expression in the hippocampus of 6-month mice (Fig. 1i). b, Representative images and quantification of MAP-2-positive area in hippocampal sections of 3-month mice. c, Western blots and quantifications showing protein expression of MAP-2 and PSD95 in 3-month mouse hippocampi. d, Heatmap showing DEGs (FDR-corrected p < 0.05) related to synaptic function from RNAseq data of 6-month mouse hippocampi. e, Representative images showing the hippocampal area of brain sections of 6-month mice co-stained for NeuN and Doublecortin. f, Representative images and quantification for NeuN+ areas of the hippocampus and cortex of 6-month mouse brains. g, Representative images and quantification of BrdU+NeuN+ cells in dentate gyrus of 6-month mouse brains. n = 5 (a, c), 4 (b, f), or 3 (g) mice. Bar graphs are presented as mean ± SEM. Two-sided unpaired t-test was used for all comparisons. Scale bars, 100 μm (b,e-h).

Source data

Extended Data Fig. 3 Lipid dyshomeostasis in TfamAKO mouse brains.

a, Glast-1 positive rate of isolated brain cells by flow cytometry (left) and cell viability of primary astrocytes from 6-month WT and TfamAKO mice. b-f, Heatmaps of DEGs (FDR-corrected p < 0.05) of mitochondrial complexes I (b), II (c), III (d), IV (e) and V (f) that are encoded by either mtDNA or nuclear DNA (nDNA) in 6-month mouse hippocampi. g, Densitometric analyses of PPARα protein in 6-month WT and TfamAKO hippocampus (Fig. 2e). h-i, TLC assay showing altered levels of major classes of lipid species in 6-month mouse cortices (h), which are quantified by normalizing to protein concentrations (i). Std., standard mix. j-k, Total TAG (j) and FFA (k) levels in 6-month mouse cortices measured by fluorometric assays. l-n, Cortical levels of total cholesterol (l), cholesteryl ester (m), and free cholesterol (n) of 6-month mice. o-p, Total TAG (o) and FFA (p) levels in 3-month mouse cortices measured by fluorometric assays. q, Heatmap of all 153 lipid species detected by the targeted lipidomic panel in 6-month mouse cortices. n = 3 (a-left, i), 5 (g), or 7 (l-n) mice; n = 11 (WT) or 14 (AKO) independent samples (a-right); n = 5 (WT) or 4 (AKO) mice (j); n = 5 (WT) or 6 (AKO) mice (k); n = 7 (WT) or 4 (AKO) mice (o); n = 6 (WT) or 4 (AKO) mice (p). Bar graphs are presented as mean ± SEM. Two-sided unpaired t-test was used for all analyses.

Source data

Extended Data Fig. 4 Lipid accumulation and metabolic shift in astrocytic FA degradation-deficient brains.

a, Western blots and quantification showing Plin2 expression in 6-month WT and TfamAKO mouse hippocampi. b, Representative Montage images of Plin2 staining of coronal brain sections of 6-month mice. c, Representative images of hippocampal sections of 3-month mice stained for LD and GFAP. d, Representative images of hippocampal sections of 1.5-month mice stained for LD and GFAP. e, Representative images of hippocampal sections of 6-month mice stained for LD and IBA-1 (left) or LD and NeuN (right). f, Sholl analysis, including ending radius, sum of intersects, and ramification index, of astrocytes (GFAP stained) in the hippocampus of 6-month mouse brains. g, Representative GFAP staining images of cultured astrocytes from 6-month WT or TfamAKO mice. h, Representative images of LD staining of 6-month primary astrocytes. (i-j) Quantification (i) and fluorescent TLC image (j) of esterified and free BODIPY-C12 from pulse-chase assay with 6-month primary astrocytes. Std., BODIPY-C12 standard. k, PCA plot of cortical acylcarnitine profiles of 6-month WT and TfamAKO mice. l, Heatmap of significantly changed acylcarnitines in 6-month WT vs. TfamAKO cortices. m, Representative images and quantification of S100β immunostaining of vehicle- or oleate-treated 6-month WT astrocytes. n, Relative CellROX intensity in oleate treated WT astrocytes. o, Lactate levels in 6-month mouse cortices. p, Heatmap of DEGs involved in glycolysis in 6-month mouse hippocampi. q, Western blots and quantification of HK2 and PFKFB3 expression in 6-month mouse hippocampi. r, mRNA levels of Hk2 and Glut1 in astrocytes acutely isolated from 6-month mice. s, Lactate levels in cultured astrocytes from 6-month WT and TfamAKO mice. n = 5 (a, m, o, q), 3 (f, i), or 4 (s) mice; n = 12 independent samples (n); n = 7 (Hk2), 4 (Glut1-WT), or 3 (Glut1-AKO) mice (r). Bar graphs are presented as mean ± SEM. Two-sided unpaired t-test was used for all comparisons. Scale bars, 1000 μm (b), 500 μm (g, m); 100 μm (d, e); 20 μm (c); 15 μm (h).

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Extended Data Fig. 5 LD accumulation is insufficient to induce astrocyte reactivity.

a, Representative images and qualification of LD volumes in 6-month WT astrocytes treated with 10 μM atglistatin for 24 h. b, Representative GFAP staining images and intensity (normalized to cell counts) of 6-month WT astrocytes treated with 10 μM atglistatin for 24 h. c, Representative western blots and quantification of p-STAT3Tyr705 in 6-month WT astrocytes treated with 10 μM atglistatin for 24 h. d, PGE2 levels in the cortex of 6-month WT and TfamAKO mice. e, Representative images of hippocampal section of 6-month TfamAKO mouse showing that STAT3 is predominantly localized to GFAP+ astrocytes. n = 4 mice (a, b, c); n = 6 (WT) or 5 (AKO) mice (d). Bar graphs are presented as mean ± SEM. Two-sided unpaired t-test was used for all comparisons. Scale bars, 1000 μm (b); 100 μm (e); 15 μm (a).

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Extended Data Fig. 6 Loss of OxPhos diminishes astrocytic support to neurons and induces neuronal oxidative stress.

a, Neurite volume of WT neurons cultured alone or with 6-month astrocytes. b, Basal OCR of WT neurons cultured with 6-month astrocytes. c, ECAR of WT neurons cocultured with 6-month astrocytes. d, Increases in LD volume for WT or TfamAKO astrocytes cocultured with WT neurons relative to these astrocytes cultured alone. e, Design for data in (f). WT neurons pretreated with vehicle, MCTi (AR-C155858) or ACCi (ND630) were cultured with WT or TfamAKO astrocytes. Astrocytes were stained for LD (image created with BioRender.com). f, Reductions in LD volume in WT or TfamAKO astrocytes induced by neuronal MCTi (left) or neuronal ACCi (right). Presented values were calculated as: LD volume in astrocytes cocultured with vehicle-pretreated neurons – LD volume in genotype-matched astrocytes cocultured with ACCi- or MCTi-pretreated neurons. g, mRNA levels of Acaca and Fasn in WT neurons cocultured with 6-month astrocytes. h-i, OCR of WT neurons cocultured with 6-month oleate-BSA-treated WT astrocytes. j, mRNA levels of genes involved in FA transport and β-oxidation in acute 6-month astrocytes. k, Protein levels of PPARα in WT neurons cultured with 6-month astrocytes. l-m, Representative images of hippocampal sections of 6-month mice co-stained for 4-HNE and GFAP (l) or 8-OHdG and GFAP (m). n, Relative CellROX intensity in cultured 6-month astrocytes. o, CellROX positive rate of Glast1+ astrocytes in 6-month brains by flow cytometry analysis. p-q, Representative images of hippocampal sections of 3-month mice stained for 4-HNE (p) or 8-OHdG (q). n = 3 (no-astrocyte) or 5 (+WT and +AKO) independent samples (a); n = 6 (WT) or 5 (AKO) independent samples (b, c); n = 4 (d, f), 5 (g), 6 (j), 3 (k, o), or 4 (n) independent samples; n = 5 (+WT) or 4 (+Oleate) independent samples (h, i). Bars are presented as mean ± SEM. Two-sided unpaired t-test was used except for a, where one-way ANOVA with post-hoc Tukey test was used. Scale bars, 100 μm (m, p, q); 25 μm (l).

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Extended Data Fig. 7 Microglial activation and neuroinflammation are induced by astrocytes with OxPhos deficiency via IL-3 signaling.

a, Top 10 GO Biological Processes enriched in 6-month TfamAKO hippocampi compared to WT mice. b, IBA-1 positive area in cortical sections of 6-month WT and TfamAKO mouse brains. c, Representative images of hippocampal sections of 3-month WT and TfamAKO mice stained for CD-74 and IBA-1. d, Representative images of hippocampal and cortical sections of 1.5-month mice stained for IBA-1. e, Densitometric analysis of NFκB protein levels in 6-month mouse hippocampi (Fig. 6g). f, Heatmap showing DEGs (FDR-corrected p < 0.05) encoding cytokines in 6-month mouse hippocampi. g, Representative images of IBA-1 staining of WT primary microglia (on coverslips in 6-well plates) cocultured with WT or TfamAKO astrocytes (in 6-well inserts) for 24 h. h-i, Quantification (h) and representative images (i) of IBA-1 intensity (normalized to cell count) in WT primary microglia cultured with WT or TfamAKO astrocytes for 48 h. j, Representative images of cortical sections of 6-month WT and TfamAKO mice stained for IL-3 and GFAP. k-l, Representative images of hippocampal (k) and cortical (l) sections of 3-month WT and TfamAKO mice stained for IL-3 and GFAP. m, Representative images of WT primary microglia (on coverslips in 6-well plates) pretreated with vehicle or IL-3Rα neutralizing antibody, cocultured with TfamAKO astrocytes (in 6-well inserts) for 24 h and then stained for IBA-1. n = 4 (b, h) or 5 (e) mice or independent samples. Bar graphs are presented as mean ± SEM. Two-sided unpaired t-test was used for all comparisons. Scale bars, 1000 μm (g, i, m); 100 μm (c, d, j, k, l).

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Extended Data Fig. 8 Loss of myelin integrity and suppressed lipid synthesis in TfamAKO brains.

a, Voxel-wise analyses of fractional anisotropy, mean-, axial-, and radial diffusivity of coronal slices on the study specific template. Blue voxels identify statistically significant TfamAKO < WT voxels (family-wise error corrected p < 0.05) for each index. b, Total brain volume of 6-month WT and TfamAKO mice. c-d, Representative Montage images of 6-month WT and TfamAKO mouse coronal sections stained for FluoroMyelin and MBP. e, Representative images and quantification of FluoroMyelin staining of the corpus callosum area of 3-month brain sections. f, Representative images and quantification of 3-month cortical sections stained for MBP. g-h, Representative images of the hippocampus (g) or white matter (h) areas of 6-month brain sections stained for CC1 and Olig2. i-j, Representative images of corpus callosum (CC) of 6-month brain sections stained for TUNEL and Olig2 and dMBP. k, Heatmap showing DEGs (FDR-corrected p < 0.05) that are positive (Mag, Myrf, Sox10, Nkx6-2, Ckap5) and negative (Omg, Chrm1, and Id4) regulators of myelination in 6-month mouse hippocampi. l-m, Densitometric analysis of FAS and p-ACC/ACC levels in 6-month mouse hippocampi (Fig. 7e). n-o, Western blots and quantification showing protein expression of FAS, p-ACC, and ACC in 3-month mouse hippocampi. p, Densitometric analysis of p-AMPK/AMPK ratio in 6-month mouse hippocampi (Fig. 7e). n = 4 (b, f), 3 (e), or 5 (l, m, o, p) mice. Bar graphs are presented as mean ± SEM. Two-sided unpaired t-test was used for all comparisons. Scale bars, 1000 μm (c and d); 100 μm (e, f, g, h, i, j).

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Extended Data Fig. 9 Impaired FA degradation, LD accumulation, and TfamAKO-induced transcriptional signatures are resembled in a mouse model of AD.

a-b, Heatmaps showing AD-related (a) and DAM (b) DEGs (FDR-corrected p < 0.05) in 6-month mouse hippocampi. c, Western blot and quantification showing protein levels of Plin2 in 4-month WT and 5xFAD mouse cortices. d-e, Representative images showing the subiculum area of 6-month WT or 5xFAD mouse brain sections stained for LD and IBA-1 (d) or LD and NeuN (e) suggest no localization of LD to neuron or microglia. f, Representative images of LDs in primary astrocytes isolated from 4-month WT or 5xFAD mouse brains (quantified in Fig. 8f). g, The ratio of fission to fusion products in cultured astrocytes from 4-month WT or 5xFAD mice by subtype analysis of mitochondria reticulum images. h-i, Quantification and representative images of BODIPY-C12 localized to mitochondria (MitoTracker+) in primary astrocytes from 6-month WT or 5xFAD mice. n = 4 (c, g) or 3 (h) mice. Bar graphs are presented as mean ± SEM. Two-sided unpaired t-test was used for all comparisons. Scale bars, 100 μm (d, e); 20 μm (f, i).

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Supplementary information

Supplementary Information

Supplementary Fig. 1 and Supplementary Table 1.

Reporting Summary

Supplementary Data

Complete lipidomics and acylcarnitine data of WT and TfamAKO mouse cortices.

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Mi, Y., Qi, G., Vitali, F. et al. Loss of fatty acid degradation by astrocytic mitochondria triggers neuroinflammation and neurodegeneration. Nat Metab 5, 445–465 (2023). https://doi.org/10.1038/s42255-023-00756-4

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