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  • Systematic Review
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Association between FDG- and TSPO-PET signals across human and animal studies investigating neurodegenerative conditions: a systematic review

Molecular Psychiatry (2025)Cite this article

Abstract

Background

Fluorodeoxyglucose (FDG)-PET hypometabolism is considered a biomarker of neurodegeneration. However, recent evidence revealed that glial cells contribute to the FDG-PET signal. In this context, microglial changes have been evaluated with 18-kDa translocator protein (TSPO)-PET radiopharmaceuticals. While several studies have concomitantly conducted FDG- and TSPO-PET imaging, their associations remain controversial.

Objective

We systematically revised multi-tracer preclinical and clinical studies using FDG- and TSPO-PET to investigate neurodegenerative conditions.

Results

From 401 studies, 14 preclinical studies, 7 clinical studies and 1 study including both met the inclusion criteria. The preclinical studies included mouse models of amyloid, tau, and neurotoxins, whereas the clinical studies investigated Alzheimer’s disease, Parkinson’s disease and frontotemporal lobar degeneration. Most clinical studies found a negative association between FDG- and TSPO-PET signals, whereas animal studies showed mixed results being highly dependent on the radiotracer used.

Discussion

Our findings support the connection between glial and metabolic changes in the brain while highlighting glial heterogeneity between species and the specificities of TSPO-PET radiotracers. To better understand the dynamic associations between FDG- and TSPO-PET, it is essential to conduct longitudinal studies during the early stages of neurodegenerative disorders, along with the use of novel mouse models that more accurately represent these conditions.

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Fig. 1: TSPO-PET radiopharmaceuticals.
Fig. 2
Fig. 3: Summary of brain FDG- and TSPO-PET preclinical studies with animal models of neurodegenerative disorders.
Fig. 4: Summary of brain FDG- and TSPO-PET clinical studies with neurodegenerative disorders’ individuals.

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References

  1. Schöll M, Damián A, Engler H. Fluorodeoxyglucose PET in neurology and psychiatry. PET Clin. 2014;9:371–90. https://doi.org/10.1016/j.cpet.2014.07.005. v

    Article  PubMed  Google Scholar 

  2. Sambuceti G, Cossu V, Bauckneht M, Morbelli S, Orengo A, Carta S, et al. 18F-fluoro-2-deoxy-d-glucose (FDG) uptake. What are we looking at? Eur J Nucl Med Mol Imaging. 2021;48:1278–86. https://doi.org/10.1007/s00259-021-05368-2

    Article  PubMed  Google Scholar 

  3. Chételat G, Arbizu J, Barthel H, Garibotto V, Law I, Morbelli S, et al. Amyloid-PET and 18F-FDG-PET in the diagnostic investigation of Alzheimer’s disease and other dementias. Lancet Neurol. 2020;19:951–62. https://doi.org/10.1016/S1474-4422(20)30314-8

    Article  PubMed  Google Scholar 

  4. Tripathi M, Tripathi M, Damle N, Kushwaha S, Jaimini A, D’Souza MM, et al. Differential diagnosis of neurodegenerative dementias using metabolic phenotypes on F-18 FDG PET/CT. Neuroradiol J. 2014;27:13–21. https://doi.org/10.15274/NRJ-2014-10002

    Article  PubMed  PubMed Central  Google Scholar 

  5. Sestini S. The neural basis of functional neuroimaging signal with positron and single-photon emission tomography. Cell Mol Life Sci. 2007;64:1778–84. https://doi.org/10.1007/s00018-007-7056-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Zimmer ER, Parent MJ, Souza DG, Leuzy A, Lecrux C, Kim HI, et al. 18F]FDG PET signal is driven by astroglial glutamate transport. Nat Neurosci. 2017;20:393–5. https://doi.org/10.1038/nn.4492

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Xiang X, Wind K, Wiedemann T, Blume T, Shi Y, Briel N, et al. Microglial activation states drive glucose uptake and FDG-PET alterations in neurodegenerative diseases. Sci Transl Med. 2021;13:eabe5640. https://doi.org/10.1126/scitranslmed.abe5640

    Article  CAS  PubMed  Google Scholar 

  8. Rocha A, Bellaver B, Souza DG, Schu G, Fontana IC, Venturin GT, et al. Clozapine induces astrocyte-dependent FDG-PET hypometabolism. Eur J Nucl Med Mol Imaging. 2022;49:2251–64. https://doi.org/10.1007/s00259-022-05682-3

    Article  CAS  PubMed  Google Scholar 

  9. Braestrup C, Squires RF. Specific benzodiazepine receptors in rat brain characterized by high-affinity (3H)diazepam binding. Proc Natl Acad Sci USA. 1977;74:3805–9. https://doi.org/10.1073/pnas.74.9.3805

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Batarseh A, Papadopoulos V. Regulation of translocator protein 18 kDa (TSPO) expression in health and disease states. Mol Cell Endocrinol. 2010;327:1–12. https://doi.org/10.1016/j.mce.2010.06.013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Lavisse S, Guillermier M, Hérard AS, Petit F, Delahaye M, Van Camp N, et al. Reactive astrocytes overexpress TSPO and are detected by TSPO positron emission tomography imaging. J Neurosci. 2012;32:10809–18. https://doi.org/10.1523/JNEUROSCI.1487-12.2012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Guilarte TR, Rodichkin AN, McGlothan JL, Acanda De La Rocha AM, Azzam DJ. Imaging neuroinflammation with TSPO: a new perspective on the cellular sources and subcellular localization. Pharmacol Ther. 2022;234:108048. https://doi.org/10.1016/j.pharmthera.2021.108048

    Article  CAS  PubMed  Google Scholar 

  13. Yao R, Pan R, Shang C, Li X, Cheng J, Xu J, et al. Translocator protein 18 kDa (TSPO) deficiency inhibits microglial activation and impairs mitochondrial function. Front Pharmacol. 2020;11:986. https://doi.org/10.3389/fphar.2020.00986

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Papadopoulos V, Baraldi M, Guilarte TR, Knudsen TB, Lacapère JJ, Lindemann P, et al. Translocator protein (18kDa): new nomenclature for the peripheral-type benzodiazepine receptor based on its structure and molecular function. Trends Pharmacol Sci. 2006;27:402–9. https://doi.org/10.1016/j.tips.2006.06.005

    Article  CAS  PubMed  Google Scholar 

  15. Crawshaw AA, Robertson NP. The role of TSPO PET in assessing neuroinflammation. J Neurol. 2017;264:1825–7. https://doi.org/10.1007/s00415-017-8565-1

    Article  PubMed  PubMed Central  Google Scholar 

  16. Edison P, Donat CK, Sastre M. in vivo imaging of glial activation in Alzheimer’s disease. Front Neurol. 2018;9:625. https://doi.org/10.3389/fneur.2018.00625

    Article  PubMed  PubMed Central  Google Scholar 

  17. Stefaniak J, O’Brien J. Imaging of neuroinflammation in dementia: a review. J Neurol Neurosurg Psychiatry. 2016;87:21–8. https://doi.org/10.1136/jnnp-2015-311336

    Article  PubMed  Google Scholar 

  18. Setiawan E, Wilson AA, Mizrahi R, Rusjan PM, Miler L, Rajkowska G, et al. Role of translocator protein density, a marker of neuroinflammation, in the brain during major depressive episodes. JAMA Psychiatry. 2015;72:268–75. https://doi.org/10.1001/jamapsychiatry.2014.2427

    Article  PubMed  PubMed Central  Google Scholar 

  19. Vivash L, O’Brien TJ. Imaging microglial activation with TSPO PET: lighting up neurologic diseases? J Nucl Med. 2016;57:165–8. https://doi.org/10.2967/jnumed.114.141713

    Article  CAS  PubMed  Google Scholar 

  20. Passamonti L, Rodríguez PV, Hong YT, Allinson KSJ, Bevan-Jones WR, Williamson D, et al. 11C]PK11195 binding in Alzheimer disease and progressive supranuclear palsy. Neurology. 2018;90:e1989–96. https://doi.org/10.1212/WNL.0000000000005610

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Lavisse S, Goutal S, Wimberley C, Tonietto M, Bottlaender M, Gervais P, et al. Increased microglial activation in patients with Parkinson disease using [18F]-DPA714 TSPO PET imaging. Parkinsonism Relat Disord. 2021;82:29–36. https://doi.org/10.1016/j.parkreldis.2020.11.011

    Article  CAS  PubMed  Google Scholar 

  22. Femminella GD, Ninan S, Atkinson R, Fan Z, Brooks DJ, Edison P. Does microglial activation influence hippocampal volume and neuronal function in Alzheimer’s disease and Parkinson’s disease dementia? J Alzheimers Dis. 2016;51:1275–89. https://doi.org/10.3233/JAD-150827

    Article  CAS  PubMed  Google Scholar 

  23. De Picker LJ, Morrens M, Branchi I, Haarman BCM, Terada T, Kang MS, et al. TSPO PET brain inflammation imaging: a transdiagnostic systematic review and meta-analysis of 156 case-control studies. Brain Behav Immun. 2023;113:415–31. https://doi.org/10.1016/j.bbi.2023.07.023

    Article  CAS  PubMed  Google Scholar 

  24. Kouli A, Spindler LRB, Fryer TD, Hong YT, Malpetti M, Aigbirhio FI, et al. Neuroinflammation is linked to dementia risk in Parkinson’s disease. Brain. 2023;147:923–35. https://doi.org/10.1093/brain/awad322

    Article  PubMed Central  Google Scholar 

  25. Malpetti M, Cope TE, Street D, Jones PS, Hezemans FH, Mak E, et al. Microglial activation in the frontal cortex predicts cognitive decline in frontotemporal dementia. Brain. 2023;146:3221–31. https://doi.org/10.1093/brain/awad078

    Article  PubMed  PubMed Central  Google Scholar 

  26. Malpetti M, Rittman T, Jones PS, Cope TE, Passamonti L, Bevan-Jones WR, et al. In vivo PET imaging of neuroinflammation in familial frontotemporal dementia. J Neurol Neurosurg Psychiatry. 2021;92:319–22. https://doi.org/10.1136/jnnp-2020-323698

    Article  PubMed  Google Scholar 

  27. Cosenza-Nashat M, Zhao ML, Suh HS, Morgan J, Natividad R, Morgello S, et al. Expression of the translocator protein of 18 kDa by microglia, macrophages and astrocytes based on immunohistochemical localization in abnormal human brain. Neuropathol Appl Neurobiol. 2009;35:306–28. https://doi.org/10.1111/j.1365-2990.2008.01006.x

    Article  CAS  PubMed  Google Scholar 

  28. Muñoz-Castro C, Noori A, Magdamo CG, Li Z, Marks JD, Frosch MP, et al. Cyclic multiplex fluorescent immunohistochemistry and machine learning reveal distinct states of astrocytes and microglia in normal aging and Alzheimer’s disease. J Neuroinflammation. 2022;19:30. https://doi.org/10.1186/s12974-022-02383-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Garland EF, Dennett O, Lau LC, Chatelet DS, Bottlaender M, Nicoll JAR, et al. The mitochondrial protein TSPO in Alzheimer’s disease: relation to the severity of AD pathology and the neuroinflammatory environment. J Neuroinflammation. 2023;20:186 https://doi.org/10.1186/s12974-023-02869-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Gui Y, Marks JD, Das S, Hyman BT, Serrano-Pozo A. Characterization of the 18 kDa translocator protein (TSPO) expression in post-mortem normal and Alzheimer’s disease brains. Brain Pathol. 2020;30:151–64. https://doi.org/10.1111/bpa.12763

    Article  CAS  PubMed  Google Scholar 

  31. Nutma E, Stephenson JA, Gorter RP, de Bruin J, Boucherie DM, Donat CK, et al. A quantitative neuropathological assessment of translocator protein expression in multiple sclerosis. Brain. 2019;142:3440–55. https://doi.org/10.1093/brain/awz287

    Article  PubMed  PubMed Central  Google Scholar 

  32. Nutma E, Gebro E, Marzin MC, van der Valk P, Matthews PM, Owen DR, et al. Activated microglia do not increase 18 kDa translocator protein (TSPO) expression in the multiple sclerosis brain. Glia. 2021;69:2447–58. https://doi.org/10.1002/glia.24052

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Nutma E, Fancy N, Weinert M, Tsartsalis S, Marzin MC, Muirhead RCJ, et al. Translocator protein is a marker of activated microglia in rodent models but not human neurodegenerative diseases. Nat Commun. 2023;14:5247. https://doi.org/10.1038/s41467-023-40937-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Owen DR, Narayan N, Wells L, Healy L, Smyth E, Rabiner EA, et al. Pro-inflammatory activation of primary microglia and macrophages increases 18 kDa translocator protein expression in rodents but not humans. J Cereb Blood Flow Metab. 2017;37:2679–90. https://doi.org/10.1177/0271678X17710182

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Ceyzériat K, Nicolaides A, Amossé Q, Fossey C, Cailly T, Fabis F, et al. Reactive astrocytes mediate TSPO overexpression in response to sustained CNTF exposure in the rat striatum. Mol Brain. 2023;16:57. https://doi.org/10.1186/s13041-023-01041-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Tournier BB, Tsartsalis S, Ceyzériat K, Fraser BH, Grégoire MC, Kövari E, et al. Astrocytic TSPO upregulation appears before microglial TSPO in Alzheimer’s disease. J Alzheimers Dis. 2020;77:1043–56. https://doi.org/10.3233/JAD-200136

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71 https://doi.org/10.1136/bmj.n71

    Article  PubMed  PubMed Central  Google Scholar 

  38. Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372:n160. https://doi.org/10.1136/bmj.n160

    Article  PubMed  PubMed Central  Google Scholar 

  39. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5:210. https://doi.org/10.1186/s13643-016-0384-4

    Article  PubMed  PubMed Central  Google Scholar 

  40. Macleod MR, O’Collins T, Howells DW, Donnan GA. Pooling of animal experimental data reveals influence of study design and publication bias. Stroke. 2004;35:1203–8. https://doi.org/10.1161/01.STR.0000125719.25853.20

    Article  PubMed  Google Scholar 

  41. Hooijmans CR, Rovers MM, de Vries RB, Leenaars M, Ritskes-Hoitinga M, Langendam MW. SYRCLE’s risk of bias tool for animal studies. BMC Med Res Methodol. 2014;14:43. https://doi.org/10.1186/1471-2288-14-43

    Article  PubMed  PubMed Central  Google Scholar 

  42. Critical Appraisal Tools | JBI. https://jbi.global/critical-appraisal-tools

  43. Brendel M, Probst F, Jaworska A, Overhoff F, Korzhova V, Albert NL, et al. Glial activation and glucose metabolism in a transgenic amyloid mouse model: a triple-tracer PET study. J Nucl Med. 2016;57:954–60. https://doi.org/10.2967/jnumed.115.167858

    Article  CAS  PubMed  Google Scholar 

  44. Vogler L, Ballweg A, Bohr B, Briel N, Wind K, Antons M, et al. Assessment of synaptic loss in mouse models of β-amyloid and tau pathology using [18F]UCB-H PET imaging. Neuroimage Clin. 2023;39:103484. https://doi.org/10.1016/j.nicl.2023.103484

    Article  PubMed  PubMed Central  Google Scholar 

  45. Takkinen JS, López-Picón FR, Al Majidi R, Eskola O, Krzyczmonik A, Keller TR, et al. Brain energy metabolism and neuroinflammation in ageing APP/PS1-21 mice using longitudinal 18F-FDG and 18F-DPA-714 PET imaging. J Cereb Blood Flow Metab. 2017;37:2870–82. https://doi.org/10.1177/0271678X16677990

    Article  CAS  PubMed  Google Scholar 

  46. Rapic S, Backes H, Viel T, Kummer MP, Monfared P, Neumaier B, et al. Imaging microglial activation and glucose consumption in a mouse model of Alzheimer’s disease. Neurobiol Aging. 2013;34:351–4. https://doi.org/10.1016/j.neurobiolaging.2012.04.016

    Article  CAS  PubMed  Google Scholar 

  47. Kong Y, Maschio CA, Shi X, Xie F, Zuo C, Konietzko U, et al. Relationship between reactive astrocytes, by [18F]SMBT-1 imaging, with Amyloid-beta, tau, glucose metabolism, and TSPO in mouse models of Alzheimer’s disease. Mol Neurobiol. 2024;61:8387–401. https://doi.org/10.1007/s12035-024-04106-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Xia D, Lianoglou S, Sandmann T, Calvert M, Suh JH, Thomsen E, et al. Novel App knock-in mouse model shows key features of amyloid pathology and reveals profound metabolic dysregulation of microglia. Mol Neurodegener. 2022;17:41 https://doi.org/10.1186/s13024-022-00547-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Liu Y, Xu Y, Li M, Pan D, Li Y, Wang Y, et al. Multi-target PET evaluation in APP/PS1/tau mouse model of Alzheimer’s disease. Neurosci Lett. 2020;728:134938. https://doi.org/10.1016/j.neulet.2020.134938

    Article  CAS  PubMed  Google Scholar 

  50. Kong Y, Cao L, Wang J, Zhuang J, Xie F, Zuo C, et al. In vivo reactive astrocyte imaging using [18F]SMBT-1 in tauopathy and familial Alzheimer’s disease mouse models: a multi-tracer study. J Neurol Sci. 2024;462:123079. https://doi.org/10.1016/j.jns.2024.123079

    Article  CAS  PubMed  Google Scholar 

  51. Poxleitner M, Hoffmann SHL, Berezhnoy G, Ionescu TM, Gonzalez-Menendez I, Maier FC, et al. Western diet increases brain metabolism and adaptive immune responses in a mouse model of amyloidosis. J Neuroinflammation. 2024;21:129. https://doi.org/10.1186/s12974-024-03080-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Endepols H, Anglada-Huguet M, Mandelkow E, Schmidt Y, Krapf P, Zlatopolskiy BD, et al. Assessment of the in vivo relationship between cerebral hypometabolism, tau deposition, TSPO expression, and synaptic density in a tauopathy mouse model: a multi-tracer PET study. Mol Neurobiol. 2022;59:3402–13. https://doi.org/10.1007/s12035-022-02793-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Eckenweber F, Medina-Luque J, Blume T, Sacher C, Biechele G, Wind K, et al. Longitudinal TSPO expression in tau transgenic P301S mice predicts increased tau accumulation and deteriorated spatial learning. J Neuroinflammation. 2020;17:208. https://doi.org/10.1186/s12974-020-01883-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Kleinberger G, Brendel M, Mracsko E, Wefers B, Groeneweg L, Xiang X, et al. The FTD-like syndrome causing TREM2 T66M mutation impairs microglia function, brain perfusion, and glucose metabolism. EMBO J. 2017;36:1837–53. https://doi.org/10.15252/embj.201796516

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Barron AM, Tokunaga M, Zhang MR, Ji B, Suhara T, Higuchi M. Assessment of neuroinflammation in a mouse model of obesity and β-amyloidosis using PET. J Neuroinflammation. 2016;13:221. https://doi.org/10.1186/s12974-016-0700-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ye P, Bi L, Yang M, Qiu Y, Huang G, Liu Y, et al. Activated microglia in the early stage of a rat model of Parkinson’s disease: revealed by PET-MRI imaging by [18F]DPA-714 targeting TSPO. ACS Chem Neurosci. 2023;14:2183–92. https://doi.org/10.1021/acschemneuro.3c00202

    Article  CAS  PubMed  Google Scholar 

  57. Fan Z, Okello AA, Brooks DJ, Edison P. Longitudinal influence of microglial activation and amyloid on neuronal function in Alzheimer’s disease. Brain. 2015;138:3685–98. https://doi.org/10.1093/brain/awv288

    Article  PubMed  Google Scholar 

  58. Fan Z, Aman Y, Ahmed I, Chetelat G, Landeau B, Ray Chaudhuri K, et al. Influence of microglial activation on neuronal function in Alzheimer’s and Parkinson’s disease dementia. Alzheimers Dement. 2015;11:608–21.e7. https://doi.org/10.1016/j.jalz.2014.06.016

    Article  PubMed  Google Scholar 

  59. Yokokura M, Mori N, Yagi S, Yoshikawa E, Kikuchi M, Yoshihara Y, et al. In vivo changes in microglial activation and amyloid deposits in brain regions with hypometabolism in Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2011;38:343–51. https://doi.org/10.1007/s00259-010-1612-0

    Article  CAS  PubMed  Google Scholar 

  60. Tondo G, Iaccarino L, Caminiti SP, Presotto L, Santangelo R, Iannaccone S, et al. The combined effects of microglia activation and brain glucose hypometabolism in early-onset Alzheimer’s disease. Alzheimers Res Ther. 2020;12:50. https://doi.org/10.1186/s13195-020-00619-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Edison P, Ahmed I, Fan Z, Hinz R, Gelosa G, Ray Chaudhuri K, et al. Microglia, amyloid, and glucose metabolism in Parkinson’s disease with and without dementia. Neuropsychopharmacology. 2013;38:938–49. https://doi.org/10.1038/npp.2012.255

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Kim MJ, McGwier M, Jenko KJ, Snow J, Morse C, Zoghbi SS, et al. Neuroinflammation in frontotemporal lobar degeneration revealed by 11 C-PBR28 PET. Ann Clin Transl Neurol. 2019;6:1327–31. https://doi.org/10.1002/acn3.50802

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Tan YL, Yuan Y, Tian L. Microglial regional heterogeneity and its role in the brain. Mol Psychiatry. 2020;25:351–67. https://doi.org/10.1038/s41380-019-0609-8

    Article  PubMed  Google Scholar 

  64. Boche D, Gordon MN. Diversity of transcriptomic microglial phenotypes in aging and Alzheimer’s disease. Alzheimers Dement. 2022;18:360–76. https://doi.org/10.1002/alz.12389

    Article  PubMed  Google Scholar 

  65. Olah M, Menon V, Habib N, Taga MF, Ma Y, Yung CJ, et al. Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease. Nat Commun. 2020;11:6129. https://doi.org/10.1038/s41467-020-19737-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Hasel P, Aisenberg WH, Bennett FC, Liddelow SA. Molecular and metabolic heterogeneity of astrocytes and microglia. Cell Metab. 2023;35:555–70. https://doi.org/10.1016/j.cmet.2023.03.006

    Article  CAS  PubMed  Google Scholar 

  67. Fontana IC, Ferreira PCL, Miron D, Santos LE, Ferreira ST, Souza DO, et al. Rapid size-exclusion high performance liquid chromatography method for the quality control of amyloid-β oligomers. J Chromatogr A. 2021;1643:462024. https://doi.org/10.1016/j.chroma.2021.462024

  68. Ghosh S, Castillo E, Frias ES, Swanson RA. Bioenergetic regulation of microglia. Glia. 2018;66:1200–12. https://doi.org/10.1002/glia.23271

    Article  PubMed  Google Scholar 

  69. Wang L, Pavlou S, Du X, Bhuckory M, Xu H, Chen M. Glucose transporter 1 critically controls microglial activation through facilitating glycolysis. Mol Neurodegener. 2019;14:2. https://doi.org/10.1186/s13024-019-0305-9

    Article  PubMed  PubMed Central  Google Scholar 

  70. Gerrits E, Brouwer N, Kooistra SM, Woodbury ME, Vermeiren Y, Lambourne M, et al. Distinct amyloid-β and tau-associated microglia profiles in Alzheimer’s disease. Acta Neuropathol. 2021;141:681–96. https://doi.org/10.1007/s00401-021-02263-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Swanson MEV, Scotter EL, Smyth LCD, Murray HC, Ryan B, Turner C, et al. Identification of a dysfunctional microglial population in human Alzheimer’s disease cortex using novel single-cell histology image analysis. Acta Neuropathol Commun. 2020;8:170. https://doi.org/10.1186/s40478-020-01047-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Santacruz K, Lewis J, Spires T, Paulson J, Kotilinek L, Ingelsson M, et al. Tau suppression in a neurodegenerative mouse model improves memory function. Science. 2005;309:476–81. https://doi.org/10.1126/science.1113694

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Sasaguri H, Nilsson P, Hashimoto S, Nagata K, Saito T, De Strooper B, et al. APP mouse models for Alzheimer’s disease preclinical studies. EMBO J. 2017;36:2473–87. https://doi.org/10.15252/embj.201797397

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Fung CW, Guo J, Fu H, Figueroa HY, Konofagou EE, Duff KE. Atrophy associated with tau pathology precedes overt cell death in a mouse model of progressive tauopathy. Sci Adv. 2020;6:eabc8098. https://doi.org/10.1126/sciadv.abc8098

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Saito T, Matsuba Y, Mihira N, Takano J, Nilsson P, Itohara S, et al. Single App knock-in mouse models of Alzheimer’s disease. Nat Neurosci. 2014;17:661–3. https://doi.org/10.1038/nn.3697

    Article  CAS  PubMed  Google Scholar 

  76. Radde R, Bolmont T, Kaeser SA, Coomaraswamy J, Lindau D, Stoltze L, et al. Abeta42-driven cerebral amyloidosis in transgenic mice reveals early and robust pathology. EMBO Rep. 2006;7:940–6. https://doi.org/10.1038/sj.embor.7400784

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Ozmen L, Albientz A, Czech C, Jacobsen H. Expression of transgenic APP mRNA is the key determinant for beta-amyloid deposition in PS2APP transgenic mice. Neurodegener Dis. 2009;6:29–36. https://doi.org/10.1159/000170884

    Article  CAS  PubMed  Google Scholar 

  78. Weidensteiner C, Metzger F, Bruns A, Bohrmann B, Kuennecke B, von Kienlin M. Cortical hypoperfusion in the B6.PS2APP mouse model for Alzheimer’s disease: comprehensive phenotyping of vascular and tissular parameters by MRI. Magn Reson Med. 2009;62:35–45. https://doi.org/10.1002/mrm.21985

    Article  PubMed  Google Scholar 

  79. Oddo S, Caccamo A, Shepherd JD, Murphy MP, Golde TE, Kayed R, et al. Triple-transgenic model of Alzheimer’s disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron. 2003;39:409–21. https://doi.org/10.1016/s0896-6273(03)00434-3

    Article  CAS  PubMed  Google Scholar 

  80. Ramsden M, Kotilinek L, Forster C, Paulson J, McGowan E, SantaCruz K, et al. Age-dependent neurofibrillary tangle formation, neuron loss, and memory impairment in a mouse model of human tauopathy (P301L). J Neurosci. 2005;25:10637–47. https://doi.org/10.1523/JNEUROSCI.3279-05.2005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Wenger K, Viode A, Schlaffner CN, van Zalm P, Cheng L, Dellovade T, et al. Common mouse models of tauopathy reflect early but not late human disease. Mol Neurodegener. 2023;18:10. https://doi.org/10.1186/s13024-023-00601-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Yoshiyama Y, Higuchi M, Zhang B, Huang SM, Iwata N, Saido TC, et al. Synapse loss and microglial activation precede tangles in a P301S tauopathy mouse model. Neuron. 2007;53:337–51. https://doi.org/10.1016/j.neuron.2007.01.010. [published correction appears in Neuron. 2007 Apr 19;54(2):343-4]

    Article  CAS  PubMed  Google Scholar 

  83. Holmes BB, Furman JL, Mahan TE, Yamasaki TR, Mirbaha H, Eades WC, et al. Proteopathic tau seeding predicts tauopathy in vivo. Proc Natl Acad Sci USA. 2014;111:E4376–85. https://doi.org/10.1073/pnas.1411649111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Jaremko L, Jaremko M, Giller K, Becker S, Zweckstetter M. Structure of the mitochondrial translocator protein in complex with a diagnostic ligand. Science. 2014;343:1363–6. https://doi.org/10.1126/science.1248725

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Guo Y, Kalathur RC, Liu Q, Kloss B, Bruni R, Ginter C, et al. Protein structure. Structure and activity of tryptophan-rich TSPO proteins. Science. 2015;347:551–5. https://doi.org/10.1126/science.aaa1534

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Jaremko Ł, Jaremko M, Giller K, Becker S, Zweckstetter M. Conformational flexibility in the transmembrane protein TSPO. Chemistry. 2015;21:16555–63. https://doi.org/10.1002/chem.201502314

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Liu J, Hiser C, Li F, Hall R, Garavito RM, Ferguson-Miller S. New TSPO crystal structures of mutant and heme-bound forms with altered flexibility, ligand binding, and porphyrin degradation activity. Biochemistry. 2023;62:1262–73. https://doi.org/10.1021/acs.biochem.2c00612. [published correction appears in Biochemistry. 2023 Jun 6;62(11):1832]

    Article  CAS  PubMed  Google Scholar 

  88. Owen DR, Yeo AJ, Gunn RN, Song K, Wadsworth G, Lewis A, et al. An 18-kDa translocator protein (TSPO) polymorphism explains differences in binding affinity of the PET radioligand PBR28. J Cereb Blood Flow Metab. 2012;32:1–5. https://doi.org/10.1038/jcbfm.2011.147

    Article  CAS  PubMed  Google Scholar 

  89. Wilson DM 3rd, Cookson MR, Van Den Bosch L, Zetterberg H, Holtzman DM, Dewachter I. Hallmarks of neurodegenerative diseases. Cell. 2023;186:693–714. https://doi.org/10.1016/j.cell.2022.12.032

    Article  CAS  PubMed  Google Scholar 

  90. Fu H, Hardy J, Duff KE. Selective vulnerability in neurodegenerative diseases. Nat Neurosci. 2018;21:1350–8. https://doi.org/10.1038/s41593-018-0221-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Zott B, Simon MM, Hong W, Unger F, Chen-Engerer HJ, Frosch MP, et al. A vicious cycle of β amyloid-dependent neuronal hyperactivation. Science. 2019;365:559–65. https://doi.org/10.1126/science.aay0198

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Jack CR Jr, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s Association Workgroup. Alzheimers Dement. 2024;20:5143–69. https://doi.org/10.1002/alz.13859

    Article  PubMed  PubMed Central  Google Scholar 

  93. Jack CR Jr, Wiste HJ, Schwarz CG, Lowe VJ, Senjem ML, Vemuri P, et al. Longitudinal tau PET in ageing and Alzheimer’s disease. Brain. 2018;141:1517–28. https://doi.org/10.1093/brain/awy059

    Article  PubMed  PubMed Central  Google Scholar 

  94. Bollack A, Pemberton HG, Collij LE, Markiewicz P, Cash DM, Farrar G, et al. Longitudinal amyloid and tau PET imaging in Alzheimer’s disease: A systematic review of methodologies and factors affecting quantification. Alzheimers Dement. 2023;19:5232–52. https://doi.org/10.1002/alz.13158

    Article  PubMed  Google Scholar 

  95. Villain N, Chételat G, Grassiot B, Bourgeat P, Jones G, Ellis KA, et al. Regional dynamics of amyloid-β deposition in healthy elderly, mild cognitive impairment and Alzheimer’s disease: a voxelwise PiB-PET longitudinal study. Brain. 2012;135:2126–39. https://doi.org/10.1093/brain/aws125

    Article  PubMed  Google Scholar 

  96. Minhas PS, Jones JR, Latif-Hernandez A, Sugiura Y, Durairaj AS, Wang Q, et al. Restoring hippocampal glucose metabolism rescues cognition across Alzheimer’s disease pathologies. Science. 2024;385:eabm6131. https://doi.org/10.1126/science.abm6131

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Dos Santos SE, Medeiros M, Porfirio J, Tavares W, Pessôa L, Grinberg L, et al. Similar microglial cell densities across brain structures and mammalian species: implications for brain tissue function. J Neurosci. 2020;40:4622–43. https://doi.org/10.1523/JNEUROSCI.2339-19.2020

    Article  PubMed  PubMed Central  Google Scholar 

  98. Azevedo FA, Carvalho LR, Grinberg LT, Farfel JM, Ferretti RE, Leite RE, et al. Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J Comp Neurol. 2009;513:532–41. https://doi.org/10.1002/cne.21974

    Article  PubMed  Google Scholar 

  99. Herculano-Houzel S. The human brain in numbers: a linearly scaled-up primate brain. Front Hum Neurosci. 2009;3:31. https://doi.org/10.3389/neuro.09.031.2009

    Article  PubMed  PubMed Central  Google Scholar 

  100. Herculano-Houzel S. The glia/neuron ratio: how it varies uniformly across brain structures and species and what that means for brain physiology and evolution. Glia. 2014;62:1377–91. https://doi.org/10.1002/glia.22683

    Article  PubMed  Google Scholar 

  101. Liddelow SA, Guttenplan KA, Clarke LE, Bennett FC, Bohlen CJ, Schirmer L, et al. Neurotoxic reactive astrocytes are induced by activated microglia. Nature. 2017;541:481–7. https://doi.org/10.1038/nature21029

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Wood LB, Winslow AR, Proctor EA, McGuone D, Mordes DA, Frosch MP, et al. Identification of neurotoxic cytokines by profiling Alzheimer’s disease tissues and neuron culture viability screening. Sci Rep. 2015;5:16622. https://doi.org/10.1038/srep16622

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Meyer-Arndt L, Kerkering J, Kuehl T, Infante AG, Paul F, Rosiewicz KS, et al. Inflammatory cytokines associated with multiple sclerosis directly induce alterations of neuronal cytoarchitecture in human neurons. J Neuroimmune Pharmacol. 2023;18:145–59. https://doi.org/10.1007/s11481-023-10059-w

    Article  PubMed  PubMed Central  Google Scholar 

  104. Gavillet M, Allaman I, Magistretti PJ. Modulation of astrocytic metabolic phenotype by proinflammatory cytokines. Glia. 2008;56:975–89. https://doi.org/10.1002/glia.20671

    Article  PubMed  Google Scholar 

  105. Wang WY, Tan MS, Yu JT, Tan L. Role of pro-inflammatory cytokines released from microglia in Alzheimer’s disease. Ann Transl Med. 2015;3:136. https://doi.org/10.3978/j.issn.2305-5839.2015.03.49

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Edison P. Neuroinflammation, microglial activation, and glucose metabolism in neurodegenerative diseases. Int Rev Neurobiol. 2020;154:325–44. https://doi.org/10.1016/bs.irn.2020.03.017

    Article  CAS  PubMed  Google Scholar 

  107. Bieger A, Rocha A, Bellaver B, Machado L, Da Ros L, Borelli WV, et al. Neuroinflammation biomarkers in the AT(N) framework across the Alzheimer’s disease continuum. J Prev Alzheimers Dis. 2023;10:401–17. https://doi.org/10.14283/jpad.2023.54

    Article  CAS  PubMed  Google Scholar 

  108. Tay TL, Mai D, Dautzenberg J, Fernández-Klett F, Lin G, Sagar, et al. A new fate mapping system reveals context-dependent random or clonal expansion of microglia. Nat Neurosci. 2017;20:793–803. https://doi.org/10.1038/nn.4547

    Article  CAS  PubMed  Google Scholar 

  109. Keren-Shaul H, Spinrad A, Weiner A, Matcovitch-Natan O, Dvir-Szternfeld R, Ulland TK, et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell. 2017;169:1276–90.e17. https://doi.org/10.1016/j.cell.2017.05.018

    Article  CAS  PubMed  Google Scholar 

  110. Paolicelli RC, Sierra A, Stevens B, Tremblay ME, Aguzzi A, Ajami B, et al. Microglia states and nomenclature: a field at its crossroads. Neuron. 2022;110:3458–83. https://doi.org/10.1016/j.neuron.2022.10.020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Leng F, Edison P. Neuroinflammation and microglial activation in Alzheimer disease: where do we go from here? Nat Rev Neurol. 2021;17:157–72. https://doi.org/10.1038/s41582-020-00435-y

    Article  PubMed  Google Scholar 

  112. Pereira JB, Janelidze S, Strandberg O, Whelan CD, Zetterberg H, Blennow K, et al. Microglial activation protects against accumulation of tau aggregates in nondemented individuals with underlying Alzheimer’s disease pathology. Nat Aging. 2022;2:1138–44. https://doi.org/10.1038/s43587-022-00310-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Ferrari-Souza JP, Lussier FZ, Leffa DT, Therriault J, Tissot C, Bellaver B, et al. APOEε4 associates with microglial activation independently of Aβ plaques and tau tangles. Sci Adv. 2023;9:eade1474. https://doi.org/10.1126/sciadv.ade1474

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Choi H, Choi Y, Lee EJ, Kim H, Lee Y, Kwon S, et al. Hippocampal glucose uptake as a surrogate of metabolic change of microglia in Alzheimer’s disease. J Neuroinflammation. 2021;18:190. https://doi.org/10.1186/s12974-021-02244-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Crook H, Wahdan M, Edison P. The dynamic functional role of triggering receptor expressed on myeloid cells 2 (TREM2) assessed with cerebrospinal fluid and positron emission tomography measures. Alzheimer’s Dement. 2023;19:e067792. https://doi.org/10.1002/alz.067792

    Article  Google Scholar 

  116. Bonomi CG, Chiaravalloti A, Camedda R, Ricci F, Mercuri NB, Schillaci O, et al. Functional correlates of microglial and astrocytic activity in symptomatic sporadic Alzheimer’s disease: a CSF/18F-FDG-PET study. Biomedicines. 2023;11:725. https://doi.org/10.3390/biomedicines11030725

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Biel D, Suárez-Calvet M, Hager P, Rubinski A, Dewenter A, Steward A, et al. sTREM2 is associated with amyloid-related p-tau increases and glucose hypermetabolism in Alzheimer’s disease. EMBO Mol Med. 2023;15:e16987. https://doi.org/10.15252/emmm.202216987

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Carter SF, Schöll M, Almkvist O, Wall A, Engler H, Långström B, et al. Evidence for astrocytosis in prodromal Alzheimer disease provided by 11C-deuterium-L-deprenyl: a multitracer PET paradigm combining 11C-Pittsburgh compound B and 18F-FDG. J Nucl Med. 2012;53:37–46. https://doi.org/10.2967/jnumed.110.087031

    Article  CAS  PubMed  Google Scholar 

  119. Schöll M, Carter SF, Westman E, Rodriguez-Vieitez E, Almkvist O, Thordardottir S, et al. Early astrocytosis in autosomal dominant Alzheimer’s disease measured in vivo by multi-tracer positron emission tomography. Sci Rep. 2015;5:16404. https://doi.org/10.1038/srep16404

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Carter SF, Chiotis K, Nordberg A, Rodriguez-Vieitez E. Longitudinal association between astrocyte function and glucose metabolism in autosomal dominant Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2019;46:348–56. https://doi.org/10.1007/s00259-018-4217-7

    Article  CAS  PubMed  Google Scholar 

  121. Mancuso R, Van Den Daele J, Fattorelli N, Wolfs L, Balusu S, Burton O, et al. Stem-cell-derived human microglia transplanted in mouse brain to study human disease. Nat Neurosci. 2019;22:2111–6. https://doi.org/10.1038/s41593-019-0525-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Sharma K, Bisht K, Eyo UB. A comparative biology of microglia across species. Front Cell Dev Biol. 2021;9:652748. https://doi.org/10.3389/fcell.2021.652748

    Article  PubMed  PubMed Central  Google Scholar 

  123. Gosselin D, Skola D, Coufal NG, Holtman IR, Schlachetzki JCM, Sajti E, et al. An environment-dependent transcriptional network specifies human microglia identity. Science. 2017;356:eaal3222. https://doi.org/10.1126/science.aal3222

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Zhou Y, Song WM, Andhey PS, Swain A, Levy T, Miller KR, et al. Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease. Nat Med. 2020;26:131–42. https://doi.org/10.1038/s41591-019-0695-9. [published correction appears in Nat Med. 2020 Jun;26(6):981]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Zhu XC, Tan L, Wang HF, Jiang T, Cao L, Wang C, et al. Rate of early onset Alzheimer’s disease: a systematic review and meta-analysis. Ann Transl Med. 2015;3:38. https://doi.org/10.3978/j.issn.2305-5839.2015.01.19. [published correction appears in Ann Transl Med. 2016 May;4(9):E4]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Commins S, Kirby BP. The complexities of behavioural assessment in neurodegenerative disorders: a focus on Alzheimer’s disease. Pharmacol Res. 2019;147:104363. https://doi.org/10.1016/j.phrs.2019.104363

    Article  PubMed  Google Scholar 

  127. Cozachenco D, Zimmer ER, Lourenco MV. Emerging concepts towards a translational framework in Alzheimer’s disease. Neurosci Biobehav Rev. 2023;152:105246. https://doi.org/10.1016/j.neubiorev.2023.105246

    Article  CAS  PubMed  Google Scholar 

  128. Hamelin L, Lagarde J, Dorothée G, Leroy C, Labit M, Comley RA, et al. Early and protective microglial activation in Alzheimer’s disease: a prospective study using 18F-DPA-714 PET imaging. Brain. 2016;139:1252–64. https://doi.org/10.1093/brain/aww017

    Article  PubMed  Google Scholar 

  129. Vanhoutte M, Semah F, Rollin Sillaire A, Jaillard A, Petyt G, Kuchcinski G, et al. 18F-FDG PET hypometabolism patterns reflect clinical heterogeneity in sporadic forms of early-onset Alzheimer’s disease. Neurobiol Aging. 2017;59:184–96. https://doi.org/10.1016/j.neurobiolaging.2017.08.009

    Article  CAS  PubMed  Google Scholar 

  130. Shah F, Hume SP, Pike VW, Ashworth S, McDermott J. Synthesis of the enantiomers of [N-methyl-11C]PK 11195 and comparison of their behaviours as radioligands for PK binding sites in rats. Nucl Med Biol. 1994;21:573–81. https://doi.org/10.1016/0969-8051(94)90022-1

    Article  CAS  PubMed  Google Scholar 

  131. Jučaite A, Cselényi Z, Arvidsson A, Ahlberg G, Julin P, Varnäs K, et al. Kinetic analysis and test-retest variability of the radioligand [11C](R)-PK11195 binding to TSPO in the human brain - a PET study in control subjects. EJNMMI Res. 2012;2:15. https://doi.org/10.1186/2191-219X-2-15

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Chauveau F, Becker G, Boutin H. Have (R)-[11C]PK11195 challengers fulfilled the promise? A scoping review of clinical TSPO PET studies. Eur J Nucl Med Mol Imaging. 2021;49:201–20. https://doi.org/10.1007/s00259-021-05425-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Vettermann FJ, Harris S, Schmitt J, Unterrainer M, Lindner S, Rauchmann BS, et al. Impact of TSPO receptor polymorphism on [18F]GE-180 binding in healthy brain and pseudo-reference regions of neurooncological and neurodegenerative disorders. Life (Basel). 2021;11:484. https://doi.org/10.3390/life11060484

    Article  CAS  PubMed  Google Scholar 

  134. Albert NL, Unterrainer M, Kaiser L, Brendel M, Vettermann FJ, Holzgreve A, et al. In response to: anatomy of 18F-GE180, a failed radioligand for the TSPO protein. Eur J Nucl Med Mol Imaging. 2020;47:2237–41. https://doi.org/10.1007/s00259-020-04885-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Zanotti-Fregonara P, Veronese M, Pascual B, Rostomily RC, Turkheimer F, Masdeu JC. The validity of 18F-GE180 as a TSPO imaging agent. Eur J Nucl Med Mol Imaging. 2019;46:1205–7. https://doi.org/10.1007/s00259-019-4268-4

    Article  PubMed  Google Scholar 

  136. Zanotti-Fregonara P, Pascual B, Rostomily RC, Rizzo G, Veronese M, Masdeu JC, et al. Anatomy of 18F-GE180, a failed radioligand for the TSPO protein. Eur J Nucl Med Mol Imaging. 2020;47:2233–6. https://doi.org/10.1007/s00259-020-04732-y

    Article  CAS  PubMed  Google Scholar 

  137. Albert NL, Unterrainer M, Brendel M, Kaiser L, Zweckstetter M, Cumming P, et al. In response to: The validity of 18F-GE180 as a TSPO imaging agent. Eur J Nucl Med Mol Imaging. 2019;46:1208–11. https://doi.org/10.1007/s00259-019-04294-8

    Article  PubMed  Google Scholar 

  138. Zimmer ER, Pascoal TA, Rosa-Neto P, Nordberg A, Pellerin L. Comment on “Microglial activation states drive glucose uptake and FDG-PET alterations in neurodegenerative diseases”. Sci Transl Med. 2022;14:eabm8302 https://doi.org/10.1126/scitranslmed.abm8302

    Article  CAS  PubMed  Google Scholar 

  139. Augusto-Oliveira M, Arrifano GP, Delage CI, Tremblay MÈ, Crespo-Lopez ME, Verkhratsky A. Plasticity of microglia. Biol Rev Camb Philos Soc. 2022;97:217–50. https://doi.org/10.1111/brv.12797

    Article  PubMed  Google Scholar 

  140. Klunk WE, Koeppe RA, Price JC, Benzinger TL, Devous MD Sr, Jagust WJ, et al. The Centiloid Project: standardizing quantitative amyloid plaque estimation by PET. Alzheimers Dement. 2015;11:1–15.e154. https://doi.org/10.1016/j.jalz.2014.07.003

    Article  PubMed  Google Scholar 

  141. Villemagne VL, Leuzy A, Bohorquez SS, Bullich S, Shimada H, Rowe CC, et al. CenTauR: toward a universal scale and masks for standardizing tau imaging studies. Alzheimers Dement (Amst). 2023;15:e12454 https://doi.org/10.1002/dad2.12454

    Article  PubMed  Google Scholar 

  142. Coughlin JM, Du Y, Lesniak WG, Harrington CK, Brosnan MK, O’Toole R, et al. First-in-human use of 11C-CPPC with positron emission tomography for imaging the macrophage colony-stimulating factor 1 receptor. EJNMMI Res. 2022;12:64. https://doi.org/10.1186/s13550-022-00929-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Harada R, Hayakawa Y, Ezura M, Lerdsirisuk P, Du Y, Ishikawa Y, et al. 18F-SMBT-1: a selective and reversible PET tracer for monoamine Oxidase-B imaging. J Nucl Med. 2021;62:253–8. https://doi.org/10.2967/jnumed.120.244400

    Article  CAS  PubMed  Google Scholar 

  144. Rodriguez-Vieitez E, Carter SF, Chiotis K, Saint-Aubert L, Leuzy A, Schöll M, et al. Comparison of Early-Phase 11C-Deuterium-l-Deprenyl and 11C-Pittsburgh compound B PET for assessing brain perfusion in Alzheimer disease. J Nucl Med. 2016;57:1071–7. https://doi.org/10.2967/jnumed.115.168732

    Article  CAS  PubMed  Google Scholar 

  145. Kumar A, Koistinen NA, Malarte ML, Nennesmo I, Ingelsson M, Ghetti B, et al. Astroglial tracer BU99008 detects multiple binding sites in Alzheimer’s disease brain. Mol Psychiatry. 2021;26:5833–47. https://doi.org/10.1038/s41380-021-01101-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Mosconi L Glucose metabolism in normal aging and Alzheimer’s disease: Methodological and physiological considerations for PET studies. Clin Transl Imaging 2013; 1:https://doi.org/10.1007/s40336-013-0026-y

  147. Arbizu J, Festari C, Altomare D, Walker Z, Bouwman F, Rivolta J, et al. Clinical utility of FDG-PET for the clinical diagnosis in MCI. Eur J Nucl Med Mol Imaging. 2018;45:1497–508. https://doi.org/10.1007/s00259-018-4039-7

    Article  CAS  PubMed  Google Scholar 

  148. Shimohama S, Tezuka T, Takahata K, Bun S, Tabuchi H, Seki M, et al. Impact of amyloid and tau PET on changes in diagnosis and patient management. Neurology. 2023;100:e264–4. https://doi.org/10.1212/WNL.0000000000201389

    Article  PubMed  Google Scholar 

  149. Jack CR, Wiste HJ, Algeciras-Schimnich A, Figdore DJ, Schwarz CG, Lowe VJ, et al. Predicting amyloid PET and tau PET stages with plasma biomarkers. Brain. 2023;146:2029–44. https://doi.org/10.1093/brain/awad042

    Article  PubMed  PubMed Central  Google Scholar 

  150. Ossenkoppele R, Pichet Binette A, Groot C, Smith R, Strandberg O, Palmqvist S, et al. Amyloid and tau PET-positive cognitively unimpaired individuals are at high risk for future cognitive decline. Nat Med. 2022;28:2381–7. https://doi.org/10.1038/s41591-022-02049-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Ridler C. Neuroimmunology: Microglia-induced reactive astrocytes - toxic players in neurological disease? Nat Rev Neurol. 2017;13:127 https://doi.org/10.1038/nrneurol.2017.17

    Article  PubMed  Google Scholar 

  152. Gao C, Jiang J, Tan Y, Chen S. Microglia in neurodegenerative diseases: mechanism and potential therapeutic targets. Signal Transduct Target Ther. 2023;8:359 https://doi.org/10.1038/s41392-023-01588-0

    Article  PubMed  PubMed Central  Google Scholar 

  153. Liddelow SA, Marsh SE, Stevens B. Microglia and astrocytes in disease: dynamic duo or partners in crime? Trends Immunol. 2020;41:820–35. https://doi.org/10.1016/j.it.2020.07.006

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

LSM is supported by Anna-Lisa och Bror Björnsons Stiftelse. MM is funded by Race Against Dementia Alzheimer’s Research UK (ARUK-RADF2021A-010), and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (NIHR203312: the views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care). HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2023-00356; #2022-01018 and #2019-02397), the European Union’s Horizon Europe research and innovation programme under grant agreement No 101053962, Swedish State Support for Clinical Research (#ALFGBG-71320), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C, and #ADSF-24-1284328-C), the Bluefield Project, Cure Alzheimer’s Fund, the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), the European Union Joint Programme – Neurodegenerative Disease Research (JPND2021-00694), the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, and the UK Dementia Research Institute at UCL (UKDRI-1003). AS-P is funded by the Harrison Gardner Jr. Innovation Award, the Karen Toffler Charitable Trust, and the Massachusetts Center for Alzheimer Therapeutics Science (MassCATS). PRN is supported by the Weston Brain Institute, Canadian Institutes of Health Research (CIHR) [MOP-11-51-31; RFN 152985, 159815, 162303], Canadian Consortium of Neurodegeneration and Aging (CCNA; MOP-11-51-31 -team 1), Brain Canada Foundation (CFI Project 34874; 33397), the Fonds de Recherche du Québec – Santé (FRQS; Chercheur Boursier, 2020-VICO-279314). ERZ is supported by CAPES (#88881.996985/2024-01), CNPq (#12410/2018-2, #435642/2018-9, #312306/2021-0, #409066/2022-2, #447074/2023-7, #409595/2023-3, and #444880/2024-0), Instituto Nacional Saúde em Excitotoxicidade Neuroproteção (#465671/2014-4), Instituto Nacional Saúde Cerebral (#406020/2022-1), Instituto Serrapilheira (#Serra-1912-31365; and #R-2401-47242), FAPERGS (#21/2551-0000673-0 and #85053.824.30451.24062024), Alzheimer’s Association (#21-850670; #22-928689; #23-1148735; and #BFECAA2024), National Academy of Neuropsychology and Alzheimer’s Association (#22-92838), Michael J. Fox Foundation (#MJFF-023158), and the Ministério da Saúde (#00030420240118-003490).

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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  1. Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos 2500, 90035-003, Porto Alegre, Rio Grande do Sul, Brazil

    Luiza S. Machado, Pedro Vidor, Lavínia Perquim, Christian Limberger, Wagner S. Brum, Diogo O. Souza & Eduardo R. Zimmer

  2. Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Göteborgsvägen 31, 431 8, Mölndal, Västergötland, Sweden

    Luiza S. Machado, Wagner S. Brum, Kaj Blennow, Henrik Zetterberg, Nicholas J. Ashton & Andrea L. Benedet

  3. Graduate Program in Biological Sciences: Pharmacology and Therapeutics, UFRGS, Rua Ramiro Barcelos 2600, 90035-003, Porto Alegre, Rio Grande do Sul, Brazil

    Leonardo Machado, Wyllians V. Borelli & Eduardo R. Zimmer

  4. Department of Psychiatry, University of Pittsburgh, 4200 Fifth Avenue, 15213, Pittsburgh, PA, USA

    Andréia Rocha, Carolina Soares, Bruna Bellaver, Pamela C. L. Ferreira & Tharick A. Pascoal

  5. Graduate Program in Neuroscience, McGill University, 845 Sherbrooke Street West, H3A 2T5, Montreal, Quebec, Canada

    Nesrine Rahmouni & Pedro Rosa-Neto

  6. Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, McGill University, 845 Sherbrooke Street West, H3A 2T5, Montreal, Quebec, Canada

    Nesrine Rahmouni, Tharick A. Pascoal, Pedro Rosa-Neto & Eduardo R. Zimmer

  7. Hospital Moinhos de Vento, Rua Ramiro Barcelos 910, 90035-000, Porto Alegre, Rio Grande do Sul, Brazil

    Wyllians V. Borelli & Eduardo R. Zimmer

  8. Brain Institute of Rio Grande do Sul - Pontifícia Universidade Católica do Rio Grande do Sul, Avenida Ipiranga 6690, 90610-000, Porto Alegre, Rio Grande do Sul, Brazil

    Jaderson C. da Costa & Eduardo R. Zimmer

  9. Department of Clinical Neurosciences, University of Cambridge, The Old Schools, Trinity Ln, CB2 1TN, Cambridge, Cambridgeshire, UK

    Maura Malpetti

  10. Department of Neurology, University of Pittsburgh, 4200 Fifth Avenue, 15213, Pittsburgh, PA, USA

    Tharick A. Pascoal

  11. Department of Biochemistry, Rua Ramiro Barcelos 2500, 90035-003, Porto Alegre, Rio Grande do Sul, Brazil

    Diogo O. Souza

  12. Department of Brain Sciences, Faculty of Medicine, Imperial College London, Exhibition Rd, South Kensington, SW7 2DD, London, Greater London, UK

    Paul Edison

  13. Cardiff University, Cardiff CF10 3AT, Cardiff, Wales, UK

    Paul Edison

  14. Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Blå stråket 5, 413 45, Gothenburg, Västergötland, Sweden

    Kaj Blennow & Henrik Zetterberg

  15. Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, 96 JinZhai Road Baohe District, 230026, Hefei, Anhui, P.R. China

    Kaj Blennow

  16. Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, 47 bd de l’Hôpital, 75013, Paris, France

    Kaj Blennow

  17. Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, WC1N 3BG, London, UK

    Henrik Zetterberg

  18. UK Dementia Research Institute at UCL, Queen Square, WC1N 3BG, London, UK

    Henrik Zetterberg

  19. Hong Kong Center for Neurodegenerative Diseases, Units 1501-1502, 1512-1518, 15/F Building 17W, 17 Science Park W Ave, Science Park, Hong Kong, China

    Henrik Zetterberg

  20. Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, 600 Highland Ave J5/1 Mezzanine, 53792, Madison, WI, USA

    Henrik Zetterberg

  21. Banner Alzheimerʼs Institute, 901 E Willetta St, AZ 85006, Phoenix, USA

    Nicholas J. Ashton

  22. Banner Sun Health Research Institute, 10515 W Santa Fe Drive, AZ 85351, Sun City, USA

    Nicholas J. Ashton

  23. Department of Neurology, Massachusetts General Hospital, 55 Fruit Street, 02114, Boston, MA, USA

    Alberto Serrano-Pozo

  24. Massachusetts Alzheimer’s Disease Research Center, 114 16th St 2011, 02129, Charlestown, MA, USA

    Alberto Serrano-Pozo

  25. Harvard Medical School, Shattuck Street, 02115, Boston, MA, USA

    Alberto Serrano-Pozo

  26. Douglas Research Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux de l’Ouest-de-l’Île-de-Montréal, McGill University, 6875 LaSalle Boulevard, H4A 1R3, Montreal, Quebec, Canada

    Pedro Rosa-Neto

  27. Department of Neurology and Neurosurgery, McGill University, 845 Sherbrooke Street West, H3A 2T5, Montreal, Quebec, Canada

    Pedro Rosa-Neto

  28. Department of Psychiatry, McGill University, 845 Sherbrooke Street West, H3A 2T5, Montreal, Quebec, Canada

    Pedro Rosa-Neto

  29. Peter OʼDonnell Jr. Brain Institute, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., 75390, Dallas, TX, USA

    Pedro Rosa-Neto

  30. Department of Pharmacology, UFRGS, Rua Ramiro Barcelos 2600, 90035-003, Porto Alegre, Rio Grande do Sul, Brazil

    Eduardo R. Zimmer

Authors
  1. Luiza S. Machado
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  2. Pedro Vidor
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  3. Lavínia Perquim
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  4. Christian Limberger
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  5. Leonardo Machado
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  6. Andréia Rocha
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  7. Carolina Soares
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  8. Nesrine Rahmouni
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  9. Wagner S. Brum
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  10. Bruna Bellaver
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  11. Pamela C. L. Ferreira
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  12. Wyllians V. Borelli
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  13. Jaderson C. da Costa
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  14. Maura Malpetti
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  15. Tharick A. Pascoal
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  16. Diogo O. Souza
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  17. Paul Edison
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  18. Kaj Blennow
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  19. Henrik Zetterberg
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  20. Nicholas J. Ashton
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  21. Andrea L. Benedet
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  22. Alberto Serrano-Pozo
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  23. Pedro Rosa-Neto
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  24. Eduardo R. Zimmer
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Contributions

Study conception and design: LSM and ERZ. Article screening and data extraction: LSM, PV, CL, LM, AR, and LP. Risk of bias assessment: LSM and PV. Data preparation: LSM. Data interpretation: LSM, AS-P, PR-N and ERZ. Manuscript preparation and figure elaboration: LSM. Intellectual content: all authors. All authors revised and approved the final version of the manuscript.

Corresponding author

Correspondence to Eduardo R. Zimmer.

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Competing interests

HZ has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZPath, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Red Abbey Labs, reMYND, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Alzecure, Biogen, Cellectricon, Fujirebio, Lilly, and Roche, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). KB has served as a consultant and at advisory boards for Acumen, ALZPath, AriBio, BioArctic, Biogen, Eisai, Lilly, Moleac Pte. Ltd, Novartis, Ono Pharma, Prothena, Roche Diagnostics, and Siemens Healthineers; has served at data monitoring committees for Julius Clinical and Novartis; has given lectures, produced educational materials and participated in educational programs for AC Immune, Biogen, Celdara Medical, Eisai, and Roche Diagnostics; and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, outside the work presented in this paper. AS-P reports on a material transfer agreement with Ionis Pharmaceuticals, Inc. PRN has served on the scientific advisory board of Novonordisk, Eisai, and Ely Lilly. He has also served as a consultant to Eisai, and Cerveau radiopharmaceuticals. ERZ has served on the scientific advisory board, as a consultant or speaker for Nintx, Novo Nordisk, Biogen, Lilly and Magdalena Biosciences. He is also a co-founder and a minority shareholder at masima. Other authors declare no conflict of interest.

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Machado, L.S., Vidor, P., Perquim, L. et al. Association between FDG- and TSPO-PET signals across human and animal studies investigating neurodegenerative conditions: a systematic review. Mol Psychiatry (2025). https://doi.org/10.1038/s41380-025-03160-4

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  • DOI: https://doi.org/10.1038/s41380-025-03160-4