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Severe reactive astrocytes precipitate pathological hallmarks of Alzheimer’s disease via H2O2− production

Nature Neuroscience volume 23, pages 1555–1566 (2020)Cite this article

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Abstract

Although the pathological contributions of reactive astrocytes have been implicated in Alzheimer’s disease (AD), their in vivo functions remain elusive due to the lack of appropriate experimental models and precise molecular mechanisms. Here, we show the importance of astrocytic reactivity on the pathogenesis of AD using GiD, a newly developed animal model of reactive astrocytes, where the reactivity of astrocytes can be manipulated as mild (GiDm) or severe (GiDs). Mechanistically, excessive hydrogen peroxide (H2O2) originated from monoamine oxidase B in severe reactive astrocytes causes glial activation, tauopathy, neuronal death, brain atrophy, cognitive impairment and eventual death, which are significantly prevented by AAD-2004, a potent H2O2 scavenger. These H2O2−-induced pathological features of AD in GiDs are consistently recapitulated in a three-dimensional culture AD model, virus-infected APP/PS1 mice and the brains of patients with AD. Our study identifies H2O2 from severe but not mild reactive astrocytes as a key determinant of neurodegeneration in AD.

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Fig. 1: Astrocyte hypertrophy and dose-modulated reactivity in an astrocyte-specific toxin receptor model (GiD).
Fig. 2: H2O2-mediated microglial activation, nitrosative stress, tauopathy and neurodegeneration in GiDs astrocytes.
Fig. 3: H2O2-mediated permanent cognitive deficits, brain atrophy and decreased survival in GiDs mice.
Fig. 4: H2O2-mediated reactive astrocytes, tau phosphorylation and neurodegeneration in a microfluidic human AD brain model.
Fig. 5: DTR-mediated increase of astrocyte reactivity and its effects on neurodegeneration, spike probability and memory ability in APP/PS1 mice.
Fig. 6: Astrocytic hypertrophy, nitrosative stress, brain inflammation and tauopathy in the brain of patients with AD.

Data availability

The datasets generated and/or analyzed during the current study are available in the Mendeley data repository (https://data.mendeley.com/) with DOI https://doi.org/10.17632/8mf35ntz9z.1. The datasets generated for the supplementary figures are available from the corresponding author upon reasonable request. Source data are provided with this paper.

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Acknowledgements

This research was supported by the Creative Research Initiative Program, Korean National Research Foundation (NRF) (grant no. 2015R1A3A2066619), Brain Research Program through the NRF funded by the Ministry of Science and ICT (grant nos. 2018M3C7A1056682 and 2018M3C7A1056897), a National Research Council of Science & Technology grant by the Korean government (MSIP) (no. CRC-15-04-KIST), grant no. 2E28411 from the Korean Institute of Science and Technology (KIST) and grant no. IBS-R001-D2 from the Institute for Basic Science from the Ministry of Science (to C.J.L.). This study was also supported by a National Institutes of Health grant no. AG054156, grant no. NRF-2016M3C7A1904233 and grant no. 2E26663 from KIST (to H.R.). This work was supported by the Pioneering Funding Award funded by the Cure Alzheimer’s Fund and the NIH (grant no. AG059236-01A1 to H.C.), by the National Honor Scientist Program (grant no. NRF-2012R1A3A1050385 to B.K.K.) and by The Bio & Medical Technology Development Program (grant no. NRF‐2019M3E5D2A01066259 to D.K.).

Author information

Authors and Affiliations

  1. Center for Cognition and Sociality, Institute for Basic Science, Daejeon, Republic of Korea

    Heejung Chun, Woojin Won, Jiwoon Lim, Yeonha Ju, Yongmin Mason Park, Sunpil Kim & C. Justin Lee

  2. Center for Glia-Neuron Interaction, Brain Science Institute, Korea Institute of Science and Technology, Seoul, Republic of Korea

    Heejung Chun, Jaekwang Lee, Junsung Woo, Seonmi Jo & C. Justin Lee

  3. Center for Neuroscience, Brain Science Institute, Korea Institute of Science and Technology, Seoul, Republic of Korea

    Heejung Chun, Hyeonjoo Im, Yunha Kim, Yujin Hwang, Hyesun Cho & Hoon Ryu

  4. Department of Mechanical Engineering and Engineering Science, Center for Biomedical Engineering and Science, Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA

    You Jung Kang & Hansang Cho

  5. GNT Pharma Co. Ltd., Yongin, Republic of Korea

    Jin Hee Shin & Byoung Joo Gwag

  6. Korea Uivresity-Korea Institute of Science and Technology, Graduate School of Convergence Technology, Korea University, Seoul, Republic of Korea

    Woojin Won, Sunpil Kim & C. Justin Lee

  7. IBS School, University of Science and Technology, Daejeon, Republic of Korea

    Yeonha Ju, Yongmin Mason Park & C. Justin Lee

  8. Neuroscience Program, University of Science and Technology, Daejeon, Republic of Korea

    Yeonha Ju, Yongmin Mason Park & Ki Duk Park

  9. Virus Facility, Research Animal Resource Center, Korea Institute of Science and Technology, Seoul, Republic of Korea

    Seung Eun Lee

  10. Precision Medicine Center, Seoul National University Bundang Hospital, Seongnam, Republic of Korea

    Hyesun Cho & Jeong-Sun Seo

  11. Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

    Seonmi Jo & Daesoo Kim

  12. Convergence Research Center for Diagnosis, Treatment and Care System of Dementia, Korea Institute of Science and Technology, Seoul, Republic of Korea

    Jong-Hyun Park & Ki Duk Park

  13. Genetics and Aging Research Unit, Mass General Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA

    Doo Yeon Kim

  14. Genomic Institute, Macrogen Inc., Seoul, Republic of Korea

    Jeong-Sun Seo

  15. Integrated Science and Engineering Division, Department of Pharmacy, and Yonsei Institute of Pharmaceutical Sciences, Yonsei University, Incheon, Republic of Korea

    Young Soo Kim

  16. Division of Bio-Med Science & Technology, KIST School, Korea University of Science and Technology, Seoul, Republic of Korea

    Ki Duk Park

  17. School of Biological Sciences, Seoul National University, Seoul, Republic of Korea

    Bong-Kiun Kaang

  18. The Nanoscale Science Program, University of North Carolina at Charlotte, Charlotte, NC, USA

    Hansang Cho

  19. Department of Biophysics, Institute of Quantum Biophysics, Sungkyunkwan University, Suwon, Republic of Korea

    Hansang Cho

  20. Boston University Alzheimer’s Disease Center and Department of Neurology, Boston University School of Medicine, Boston, MA, USA

    Hoon Ryu

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  1. Heejung Chun
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Contributions

H.J.C., H.R. and C.J.L. designed the study, analyzed the data and wrote the manuscript. H.J.C., J.W.L. and Y.M.P. performed and analyzed the IHC in GiD, fGiD and APP/PS1 mice. Y.H.K. performed and analyzed the western blot and MTT assay. Y.J.K. performed and analyzed the experiments in the 3D neurocyte AD model. H.J.C. and J.W.L. performed the microdialysis and in vivo H2O2 assay. W.J.W. performed the IHC and in vitro H2O2 assay. Y.M.P. validated the GFAP-CreERT2 mice. J.W.L., J.H.S., Y.H.J. and S.K. performed the behavioral tests. H.J.C., W.J.W., Y.H.J., J.K.L. and J.S.W. performed the electrophysiological experiments. S.E.L. generated the adenovirus and AAV virus. H.J.I. and Y.J.H. performed the immunostaining and quantitative RT–PCR analysis in the human samples. D.Y.K. and H.C. provided the 3D neurocyte AD model. J.H.S. and B.J.G. provided the AAD-2004 scavenger. S.M.J. and D.K. provided the transgenic animal models. Y.S.K. provided the Aβ. J.H.P. and K.D.P. provided the KDS2010 MAO-B inhibitor. H.S.C. and J.S.S. performed the gene expression analysis. B.K.K. designed the experiments and wrote the manuscript. All authors contributed to the analysis and discussion of the results and reviewed the manuscript.

Corresponding authors

Correspondence to Hoon Ryu or C. Justin Lee.

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Extended data

Extended Data Fig. 1 Validation and characterization of GiD system.

a, (left) RT-PCR analysis of diphtheria toxin receptor(DTR) in hippocampus of Gcon and GiDm. (right) RT-PCR analysis of DTR in cultured astrocytes from Gcon and GiD (GiDc). GAPDH, internal control. Experiments were repeated more than twice. b, Measuring passive conductance in astrocytes of Gcon and GiDs. c, Experimental procedures of GiD mice, which GFAP-CreERT2 crossed with iDTR mice. Tam, tamoxifen, 100 mg/kg/day, 5 days; DT, 50 µg/kg/day, 2 days. d, GFAP immunostaining in brain regions of frontal lobe containing cortex, hippocampus, striatum and amygdala of Gcon and GiD mice. Ctx, cortex; Hipp, hippocampus; Str, striatum; Amyg, amygdala. e, Experimental procedures for PI staining in GiDm, CiD mice and KA-injected seizure model mice. DT, 50 µg/kg/day, 2 days; KA, kainic acid, 25 mg/kg. f, PI staining in GiDm, CiD and seizure model mice. g, h, MTT assay in DT-treated GiD astrocyte. DT, 1 ug/ml, 5 days; 3-MA, 3-Methyladenine, 0.5 mM (g), Baf A1, bafilomycin A1, 4 µM (h). Data are presented as mean ± SEM. *P < 0.05; NS: not significant. Additional statistical details are provided in Supplementary Table 1.

Source data

Extended Data Fig. 2 Autophagy activation in astrocytes of GiDs and GiDc.

a, Schematic diagram for possible mechanism of DT intoxification in GiD. b, Immunostaining for LC3 and GFAP in cortex of Gcon and GiDs. c, d, Immunostaining for LC3 (c) and SQSTM1 (d) in hippocampus of Gcon and GiDs. e, Experimental timeline for DT treatment in cultured astrocytes from Gcon and GiD (GiDc). f, g, Western blot analysis showing that levels of endogenous SQSTM1 and LC3-II are time-dependently increased in DT-treated GiDc astrocyte. h-s, Autophagic flux assay and densitometry analysis in DT-treated GiDc astrocytes. DT, 1 µg/ml, 8 hrs; E64d+Pep.A, 10 µg/ml E64d plus 10 µg/ml Pep.A, 6 hrs (h-m); CQ, 20 µM, 6 hrs (n-s). Data are presented as mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; NS: not significant. Additional statistical details are provided in Supplementary Table 1.

Source data

Extended Data Fig. 3 MAO-B-mediated astrocytic hypertrophy and lack of neurodegeneration in GiDm brain.

a, Experimental procedures for AAD-2004 and selegiline treatment in GiDm. b,c, Immunostaining and quantification for GFAP in Gcon, GiDm, selegline-treated GiDm and AAD-2004-treated GiDm. d,e, Immunostaining and quantification for NeuN in Gcon and GiDm. Data are presented as mean ± SEM. ***P < 0.001, ****P < 0.0001; NS: not significant. Additional statistical details are provided in Supplementary Table 1.

Extended Data Fig. 4 Astrocytic hypertrophy and neurodegeneration in cortex, striatum and amygdala of GiDs brain.

a, Representative image of immunostaining for GFAP and NeuN in the brain of Gcon and GiDs. b-d, Quantification for the number of cells positive for NeuN in cortex, striatum and amygdala of Gcon and GiDs. Data are presented as mean ± SEM. *P < 0.05, ***P < 0.001, ****P < 0.0001. Additional statistical details are provided in Supplementary Table 1.

Extended Data Fig. 5 Development of focal GiD (fGiD).

a, b, Schematic diagram and experimental procedure for making mild and severe focal GiD, fGiDm and fGiDs, respectively. c, Immunostaining for GFAP and mCherry in CTL, fGiDm and fGiDs. d, Quantification for GFAP intensity in CTL, fGiDm and fGiDs. e, DAPI image in CTL, fGiDm and fGiDs. f, Counting the number of DAPI signals in stratum radiatum of CTL, fGiDm and fGiDs. g, Measuring the size of CA1 region in CTL, fGiDm and fGiDs. h, Comparison of glial activation in hippocampus between fGiDs and GiDs. Data are presented as mean ± SEM. **P < 0.01, ***P < 0.001, ****P < 0.0001; NS: not significant. Additional statistical details are provided in Supplementary Table 1.

Extended Data Fig. 6 Virus-mediated increase of astrocyte’s reactivity and its effects on neurodegeneration and tauopathy in APP/PS1 mice.

a, Schematic diagram and experimental timeline for increasing the reactivity of astrocytes in APP/PS1 mice using Adeno-GFAP-GFP virus. b-d, Immunostaining for GFAP, NeuN and quantification of the mean intensity in uninjected- or virus injected- WT and APP/PS1 mice. Magenta, Adeno-GFAP-GFP virus. e-g, DAB staining and quantification for p-Tau(S199) and p-Tau(S396) in virus injected- WT and APP/PS1 mice. Data are presented as mean ± SEM. *P < 0.05, **P < 0.01, ****P < 0.0001; NS: not significant. Additional statistical details are provided in Supplementary Table 1.

Supplementary information

Supplementary Information

Supplementary Figs. 1–11 and Supplementary Tables 1 and 2.

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Chun, H., Im, H., Kang, Y.J. et al. Severe reactive astrocytes precipitate pathological hallmarks of Alzheimer’s disease via H2O2− production. Nat Neurosci 23, 1555–1566 (2020). https://doi.org/10.1038/s41593-020-00735-y

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