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Microglia-mediated T cell infiltration drives neurodegeneration in tauopathy - Nature.com

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Abstract

Extracellular deposition of amyloid-β as neuritic plaques and intracellular accumulation of hyperphosphorylated, aggregated tau as neurofibrillary tangles are two of the characteristic hallmarks of Alzheimer’s disease1,2. The regional progression of brain atrophy in Alzheimer’s disease highly correlates with tau accumulation but not amyloid deposition3,4,5, and the mechanisms of tau-mediated neurodegeneration remain elusive. Innate immune responses represent a common pathway for the initiation and progression of some neurodegenerative diseases. So far, little is known about the extent or role of the adaptive immune response and its interaction with the innate immune response in the presence of amyloid-β or tau pathology6. Here we systematically compared the immunological milieux in the brain of mice with amyloid deposition or tau aggregation and neurodegeneration. We found that mice with tauopathy but not those with amyloid deposition developed a unique innate and adaptive immune response and that depletion of microglia or T cells blocked tau-mediated neurodegeneration. Numbers of T cells, especially those of cytotoxic T cells, were markedly increased in areas with tau pathology in mice with tauopathy and in the Alzheimer’s disease brain. T cell numbers correlated with the extent of neuronal loss, and the cells dynamically transformed their cellular characteristics from activated to exhausted states along with unique TCR clonal expansion. Inhibition of interferon-γ and PDCD1 signalling both significantly ameliorated brain atrophy. Our results thus reveal a tauopathy- and neurodegeneration-related immune hub involving activated microglia and T cell responses, which could serve as therapeutic targets for preventing neurodegeneration in Alzheimer’s disease and primary tauopathies.

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Fig. 1: Immune scRNA-seq reveals increased proportion of T cells in the context of tau-mediated neurodegeneration.
Fig. 2: T cell numbers are strongly elevated in the brain parenchyma of humans and mice with tauopathy and neuronal loss.
Fig. 3: T cells dynamically shift from activated to exhausted states with unique TCR clonal expansion in tauopathy.
Fig. 4: Microglia depletion prevents T cell infiltration in tauopathy.
Fig. 5: Depletion of T cells ameliorates inflammation, tauopathy and brain atrophy, and improves behaviour.

Data availability

Immune scRNA-seq sample information, information for samples from patients with Alzheimer’s disease, and immune cell numbers in each cluster in the brain are available in the Supplementary Information. All source data, including sequencing reads and single-cell expression matrices, are available from the Gene Expression Omnibus under accession code GSE221856.

Code availability

Code for preprocessing of immune scRNA-seq bioinformatic analysis is available at https://zenodo.org/record/7566414.

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Acknowledgements

We thank X. Zhang and S. Li for advice on scRNA-seq analysis; J. Rustenhoven, B. Korin and A. Rolls for advice on meninges isolation; D. Bender for assistance with multiplex immune monitoring; D. Gate for advice on T cell immunohistochemistry on human samples; N. Saligrama for advice on TCR and antigen analysis; and M. Gratuze for PLX3397 drug formulation. We thank the Department of Pathology and Immunology Flow Cytometry and Fluorescence Activated Cell Sorting Core for help with cell sorting. This work was supported by a Carol and Gene Ludwig Award for Neurodegeneration Research (D.M.H.), National Institute of Health grant NS090934 (D.M.H.), the JPB Foundation (D.M.H.), Cure Alzheimer’s Fund (D.M.H.) and Rainwater Charitable Foundation (D.M.H.). M.F. was supported by the Ministry of Science and Higher Education of the Russian Federation (agreement no. 075-15-2022-301). Single-nucleus sequencing was carried out at the McDonnell Genome Institute. Confocal microscopic analyses were carried out at the Washington University Center for Cellular Imaging supported by Washington University School of Medicine, The Children’s Discovery Institute of Washington University and St Louis Children’s Hospital (CDI-CORE-2015-505 and CDI-CORE-2019-813) and the Foundation for Barnes-Jewish Hospital (3770 and 4642). We thank E. Reiman, G. Serrano and T. Beach for human brain tissue. The schematic representations of the fear conditioning behavioural paradigms in Extended Data Fig. 9i were created with BioRender.com.

Author information

Authors and Affiliations

  1. Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA

    Xiaoying Chen, Melissa Manis, Chanung Wang, Xin Bao, Mary Beth Finn, Hao Hu, Carla M. Yuede, Jonathan Kipnis, Jason D. Ulrich & David M. Holtzman

  2. Almazov National Medical Research Centre, St Petersburg, Russia

    Maria Firulyova

  3. Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA

    Jasmin Herz, Igor Smirnov, Ekaterina Aladyeva, Irina Shchukina, Min Woo Kim, Jonathan Kipnis & Maxim N. Artyomov

  4. Center for Brain Immunology and Glia (BIG), Washington University School of Medicine, St Louis, MO, USA

    Jasmin Herz, Igor Smirnov, Min Woo Kim, Jonathan Kipnis & David M. Holtzman

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  1. Xiaoying Chen
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Contributions

X.C. and D.M.H. conceived the study. X.C. designed the study, carried out the experiments, analysed the data and wrote the draft of the manuscript. M.M., M.B.F., J.H., J.K., X.B., I. Smirnov. and C.W. were blinded to sample IDs for brain volume and neurofilament light chain measurement. M.F., E.A., X.C., M.N.A. and J.D.U. analysed scRNA-seq data. X.C., H.H. and M.W.K. carried out microglia in vitro antigen presentation assay. X.C., and I. Shchukina carried out anti-PDCD1 acute treatment flow cytometry assay. C.M.Y. was blinded to sample IDs, and carried out and analysed the memory behavioural assay. D.M.H. supervised the overall research. X.C. and D.M.H. wrote the manuscript with comments from all authors.

Corresponding author

Correspondence to David M. Holtzman.

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Competing interests

D.M.H. is an inventor on a patent licensed by Washington University to C2N Diagnostics on the therapeutic use of anti-tau antibodies. D.M.H. co-founded and is on the scientific advisory board of C2N Diagnostics. D.M.H. is on the scientific advisory board of Denali and Cajal Neuroscience and consults for Genentech and Alector. J.K. is a member of a scientific advisory group for PureTech. All other authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 ApoE4 exacerbates tau-mediated neurodegeneration.

(a) Representative image of 9.5-month A/PE4 mouse brain sections stained with an anti-amyloid-Aβ (Aβ) antibody and X-34. Scale bar = 500 μm. (b) Representative images of 6 and 9.5-month TE4 mouse brain sections stained with AT8 antibody. Scale bar = 500 μm. (c) Quantification of brain regional volumes of 9.5-month mice normalized to 6-month in b. TE4-6 months: n = 7, TE4-9.5 months: n = 13. ***p < 0.0001 for hippocampus (Hip) vs. cortex dorsal to the hippocampus (Ctx); amygdala (Amyg) vs. Ctx and entorhinal/piriform cortex (Ent) vs. Ctx. One-way ANOVA with Tukey’s post hoc test. (d) Quantification of the area covered by AT8 of 9.5-month TE4 mouse brain sections in b. TE4-6 months: n = 7, TE4-9.5months: n = 13. ***p < 0.0001 for Hip vs. Ctx; Amyg vs. Ctx and Ent vs. Ctx. One-way ANOVA with Tukey’s post hoc test. (e) Representative images of 6-month TE4, 9.5-month E4, and 9.5-month TE4 mouse brain sections stained with NeuN. Scale bar = 50 μm. (f) Thickness of granule cell layer of the DG in 9.5-month E3, TE3, E4, TE4 mice. (E3: n = 5, TE3: n = 6, E4: n = 15 and TE4: n = 13). *p = 0.0130 for TE3 vs. TE4. Two-way ANOVA with Tukey’s post hoc test. (g) Correlation between DG neuronal layer thickness and hippocampal volume. n = 39 biologically independent animals from f. Pearson correlation analysis. R2 = 0.8335, p < 0.0001. (h, i) Representative images of 9.5-month E4 and TE4 mouse brain sections stained with MBP. Scale bar = 500 μm in h. Scale bar = 100 μm in i. (j-l) Volumes of hippocampus, entorhinal/piriform cortex and posterior lateral ventricle in 9.5-month E3, TE3, E4, TE4 mice. (E3: n = 5, TE3: n = 6, E4: n = 15 and TE4 = 13). p = 0.0505 for TE3 vs. TE4 in comparing the volume of the hippocampus, *p = 0.0207 for TE3 vs. TE4 in comparing the volume of the posterior lateral ventricle. Two-way ANOVA with Tukey’s post hoc test. (m—o) Volumes of hippocampus, entorhinal/ piriform cortex and posterior lateral ventricle in 9.5-month TE3, TE4, A/PE4, 5xE4 male and female mice. (TE3-M: n = 6, TE3-F: n = 11, TE4-M: n = 13, TE4-F: n = 17, A/PE4-M: n = 7, A/PE4-F: n = 6, 5xE4-M: n = 6, 5xE4-F: n = 7). **p = 0.0087 for TE4 male vs. female entorhinal/piriform cortex volume. Two-way ANOVA with Tukey’s post hoc test. Data are mean ± s.e.m.

Extended Data Fig. 2 Immune cell composition in brain parenchyma and meninges.

(a) FACS sorting of CD45Total and /or CD45high cells from brain parenchyma and meninges from A/PE4 mice for single cell immune RNA-seq. (b) Analysis of the CD4 and CD8 positive T cells present in the brain of E4 and TE4 mice by flow cytometry. (E4: n = 8, TE4: n = 14) Data are mean ± s.e.m., ***p < 0.0001, Unpaired two-tailed Student’s t test. (c) Representative cell type specific makers in brain parenchyma (CD45Total) clusters. (d) CD45high immune cells from parenchyma assigned into 12 cell types as visualized by UMAP plot. (e) Representative cell type specific makers in meninges (CD45Total).

Extended Data Fig. 3 T cell infiltration in the brain parenchyma with significant tauopathy.

(a) Representative flow cytometry gating plot of splenic lymphocytes. (b) Quantification of the proportion of indicated lymphocytes and their subsets among 9.5-month E4, A/PE4, and TE4 mice. (E4: n = 4, A/PE4: n = 4, TE4: n = 8). p = 0.648, 0.492, 0.992 for E4 vs. A/PE4; E4 vs. TE4; A/PE4 vs. TE4 in T cells; p = 0.614, 0.518, 0.089 for E4 vs. A/PE4; E4 vs. TE4; A/PE4 vs. TE4 in CD4+ T cells; p = 0.665, 0.719, 0.196 for E4 vs. A/PE4; E4 vs. TE4; A/PE4 vs. TE4 in CD8+ T cells. Two-way ANOVA with Tukey’s post hoc test. p = 0.629, 0.472, 0.095 for E4 vs. A/PE4; E4 vs. TE4; A/PE4 vs. TE4 in Treg. One-way ANOVA with Tukey’s post hoc test. (c) Quantification of CD3+ T cell number per DG area with 0.3 mm2 in 9.5 month E3, TE3, E4, TE4 mice. (E3: n = 5, TE3: n = 6, E4: n = 15 and TE4: n = 13). Two-way ANOVA with Tukey’s post hoc test. p = 0.1342 for TE3 vs. TE4. (d) Representative images of 9.5-month old E4, TE4, A/PE4 and 5xE4 mouse brain sections stained with CD3, Iba1, Aβ and X-34. Scale bar = 20 μm. Images are representative of results from n = 4 in E4, A/PE4 and TE4 respectively. (e) TEM image demonstrating presence of a cell with T cell like features in brain parenchyma of 9.5 month of TE4 mouse. Scale bar = 2 μm. Images are representative of results from n = 3 in TE4 mice.

Extended Data Fig. 4 Characterization of T cell populations within the parenchyma and meninges of mice with amyloid or tau pathology.

(a) Heatmap showing identified marker genes in each of the categorized cell types in Total T cells, CD4+ and CD8+ T cells. (b) Total T cells from brain parenchyma and meninges with TCR assigned into 13 cell types as visualized by UMAP plot. (c) TRAV and TRBV enrichment in CD8+ and CD4+ T cells in TE4 and A/PE4 mice. (d) Representative TCR-TRBV projection in E4, A/PE4 and TE4 mice.

Extended Data Fig. 5 Expression of cytokines, chemokines, growth factors and soluble receptors in brain lysates.

Quantification of cytokines, chemokines, growth factors and soluble receptors in brain lysates in 9.5 month old E4, TE4, and TEKO mice. (E4: n = 10, TE4: n = 10 and TEKO: n = 10). One-way ANOVA with Tukey’s post hoc test. With Q=0.1% identify outlier function, n = 1 E4 and n = 1 TEKO samples for IFN-γ measurements were removed; n = 1 E4 sample for IL-1β measurements was removed. ***p = 0.0001, ***p < 0.0001, ***p < 0.0001, ***p < 0.0001, p = 0.1261, ***p < 0.0001, **p = 0.0038, ***p = 0.0005, ***p < 0.0001, *p = 0.0144, **p = 0.0022, ***p < 0.0001, *p = 0.0126, ***p = 0.0002, ***p = 0.0001, **p = 0.0074, **p = 0.0059, *p = 0.0434, ***p < 0.0001, **p = 0.007, *p = 0.038, ***p < 0.0001 for E4 vs. TE4 following the panel order. p = 0.2757, ***p < 0.0001, ***p < 0.0001, ***p < 0.0001, *p = 0.489, ***p < 0.0001, p = 0.2539, p = 0.9952, **p = 0.0011, p = 0.053, n = 0.625, ***p < 0.0001, n = 0.7867, p = 0.1013, p = 0.087, p = 0.9905, p = 0.1107, p = 0.7159, p = 0.9193, p = 0.8426, p = 0.83, **p = 0.0076 for TE4 vs. TEKO following the panel order. Data are mean ± s.e.m.; One-way ANOVA with Tukey’s post hoc test.

Extended Data Fig. 6 Changes in microglia and T cells with Tau-meditated neurodegeneration require ApoE.

(a) MHCII, CD206, Iba1 and GFAP staining in 9.5-month TE4 mice. Scale bar = 100 μm. Images are representative of results from n = 13 in TE4 mice. (b) Iba1, MHCII and Aβ staining in 9.5 month E4, A/PE4, TE4 and TEKO mice in Cortex dorsal to Hippocampus, Hippocampus and Ent/Piri cortex. Scale bar = 50 μm. (c) Quantification of the area covered by MHCII in Ctx, Hip and Ent in 9.5-month TE4 and TEKO mice. (TE4: n = 13 and TEKO: n = 15). ***p < 0.0001 for TE4-Hip vs. TEKO-Hip. One-way ANOVA with Tukey’s post hoc test. (d) Iba1, CD11c and Aβ staining in 9.5-month E4, A/PE4, TE4 and TEKO mice in Prefrontal cortex, Hippocampus and Ent/Piri cortex. Scale bar = 50 μm. (e) Quantification of the area covered by CD11c in Ctx, Hip and Ent in 9.5-month TE4 and TEKO mice. (TE4: n = 13 and TEKO: n = 15). ***p < 0.0001 for TE4-Hip vs. TEKO-Hip. One-way ANOVA with Tukey’s post hoc test. (f) Volume of hippocampus in 9.5-month TE4 and TEKO mice. (TE4: n = 13 and TEKO: n = 15). ***p < 0.0001. Unpaired two-tailed Student’s t test. (g) Quantification of numbers of CD3+ T cells in DG per 0.3 mm2. (TE4: n = 13 and TEKO: n = 15). ***p < 0.0001. Data are mean ± s.e.m.; Unpaired two-tailed Student’s t test.

Extended Data Fig. 7 IFN-γ in the T cell population and microglia can directly present antigen to CD8+ T cells in vitro.

(a) Ligand-receptor analysis in T cells and microglia. (b) IFN-γ expression in brain parenchyma (CD45Total) 12 cell types and T cells from brain parenchyma 15 clusters of T cells as visualized by UMAP plot. (c) The gating strategy for sorting naïve OT-1 CD8+ T cells, dendritic cells (DCs), and microglia. (d) Representative flow cytometry plot to assess the proliferation of OT-1 T cells by cell tracer violet (CTV) dilution after 3 days of co-culture with APCs in the presence of OVA. (e) Representative flow cytometry plot showing dose dependent OVA antigen presentation by DCs, microglia, or microglia in the presence of IFNγ assayed by OT-1 proliferation. (f) Percent of proliferating OT-1 T cells under the indicated conditions. Data are from one representative experiment. Two independent experiments were done showing similar results.

Extended Data Fig. 8 Blocking IFNγ signaling reduces tau-mediated neurodegeneration and tau pathology.

(a) Representative images of 9.5-month TE3-IgG and TE3-αIFN-γ treated mouse brain sections stained with Sudan black. Scale bar = 1 mm. (b–d) Volumes of hippocampus, entorhinal/piriform cortex and posterior lateral ventricle in 9.5-month TE3-IgG and TE3-αIFNγ treated mice. (TE3-IgG: n = 12 and TE3-αIFNγ: n = 12). p = 0.0479, 0.0398, 0.265 for TE3-IgG vs. TE3-αIFNγ in comparing the volumes of hippocampus, entorhinal/piriform cortex and posterior lateral ventricle, respectively. Unpaired two-tailed Student’s t test. (e) CD11c, CD8, Iba1 staining in 9.5-month TE3-IgG and TE3-αIFNγ treated mice. Scale bar = 50 μm. (f) Quantification of area covered by CD11c in 9.5-month TE3-IgG and TE3-αIFNγ mice. (TE3-IgG: n = 12 and TE3-αIFNγ: n = 12). *p = 0.0344. Unpaired two-tailed Student’s t test. (g) Representative images of 9.5-month TE3-IgG and TE3-αIFNγ treated mouse brain sections stained with AT8 antibody. Scale bar = 250 μm. (h) p-Tau (AT8) covered area in 9.5-month TE3-IgG and TE3-αIFNγ treated mice. (TE3-IgG: n = 12 and TE3-αIFNγ: n = 12). *p = 0.0122. Unpaired two-tailed Student’s t test. (i) Schematic representation of the timeline of PLX3397 treatment for microglia depletion. (j) Schematic representation of the timeline of anti-CD4 and anti-CD8 antibody treatment for T cell depletion.

Extended Data Fig. 9 T cell depletion in tauopathy mice.

(a) Representative flow cytometry gating plot and quantification of CD4+, CD8+ T cells in brain parenchyma, meninges and blood in IgG control or α-CD4 and α-CD8 (αT) treated mice. (b) Bar plot showing the number of CD8+ T and CD4+ T cells in IgG and αT treated mice. (IgG: n = 2 and αT: n = 4). Data are mean ± s.e.m. (c) Microglia from brain parenchyma of TE4-IgG and TE4-αT treated mice assigned into 3 categories as visualized by UMAP plot. (d) Bar plot showing the percentage of the 3 categories of microglia in TE4-IgG and TE4-αT mice. (e) Heat map showing representative functional genes specifically expressed in active microglia clusters in TE4-IgG and TE4-αT mice. (f) Quantification of nest-building behavior at 9.5 months age. (TE4-IgG: n = 15 and TE4-αT: n = 21). *p = 0.02 for IgG vs. αT. Fisher’s exact test. (g) Quantification of total rearing at baseline levels of general exploratory behavior in 1 h. (TE4-IgG: n = 10 and TE4-αT: n = 15). p = 0.4363 for TE4-IgG vs. TE4-αT. Unpaired two-tailed Student’s t test. (h) Quantification of total ambulations at baseline levels of locomotor activity levels in 1 h. (TE4-IgG: n = 10 and TE4-αT: n = 15). p = 0.0709. Two-tailed Mann-Whitney test. (i) Schematic representation of fear conditioning behavioral paradigms. Schematics in i were created with BioRender.com.

Extended Data Fig. 10 Blocking PD-1 immune checkpoint increases Foxp3+CD4+ Tregs and reduces tau-mediated neurodegeneration.

(a) The gating strategy for sorting Foxp3+ CD4+ Treg, Pd1+ Foxp3+ CD4+ Treg, Klrg1+ effector CD8+ T cells, PD-1+ Tox1+ CD8+ exhausted T cells in the brain parenchyma. (b–e) Quantification of T cell populations in the brain parenchyma of mice acutely treated with IgG control and αPD-1 antibodies. (TE4-IgG: n = 12 and TE4-αPD-1: n = 13 for b, d, e; TE4-IgG: n = 10 and TE4-αPD-1: n = 11 for c). *p = 0.041, **p = 0.0075, p = 0.52, p = 0.945 for Foxp3+CD4+ Treg, Pd1+ Foxp3+ CD4+ Treg, Klrg1+ effector CD8+ T cells, PD-1+ Tox1+ CD8+ exhausted T cells. Unpaired two-tailed Student’s t test. (f) Representative images of 9.5-month TE4-IgG and TE4-αPD-1 treated mouse brain sections stained with Sudan black. Scale bar = 1 mm. (g-h) Volumes of hippocampus, entorhinal/piriform cortex in 9.5-month TE4-IgG and TE4-αPD-1 treated mice. (TE4-IgG: n = 14 and TE4-αPD-1: n = 14). *p = 0.018 and 0.015 for TE4-IgG vs. TE4-αPD-1 in comparing the volumes of hippocampus, entorhinal/piriform cortex, respectively. Unpaired two-tailed Student’s t test. (i) Quantification of the area covered by AT8 in DG per slice in 9.5-month TE4-IgG vs. TE4-αPD-1 mice (TE4-IgG: n = 14 and TE4-αPD: n = 14). **p = 0.0009. Unpaired two-tailed Student’s t test.

Supplementary information

Supplementary Information

Reporting Summary

Supplementary Video 1

CD3 and IBA1 staining in hippocampus of TE4 mice. IBA1 (red) and CD3 (green) staining in 9.5-month-old TE4 mice with tau pathology in DG. Scale bar, 10 μm.

Supplementary Video 2

CD11c, CD8 and IBA1 staining in hippocampus of TE4 mice. IBA1 (blue), CD11c (red) and CD8 (green) staining in 9.5-month-old TE4 mice with tau pathology in DG. Scale bar, 15 μm.

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Chen, X., Firulyova, M., Manis, M. et al. Microglia-mediated T cell infiltration drives neurodegeneration in tauopathy. Nature (2023). https://ift.tt/iMRKw0J

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