Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

CXCR6 orchestrates brain CD8+ T cell residency and limits mouse Alzheimer’s disease pathology

Nature Immunology volume 24, pages 1735–1747 (2023)Cite this article

Subjects

Abstract

Neurodegenerative diseases, including Alzheimer’s disease (AD), are characterized by innate immune-mediated inflammation, but functional and mechanistic effects of the adaptive immune system remain unclear. Here we identify brain-resident CD8+ T cells that coexpress CXCR6 and PD-1 and are in proximity to plaque-associated microglia in human and mouse AD brains. We also establish that CD8+ T cells restrict AD pathologies, including β-amyloid deposition and cognitive decline. Ligand–receptor interaction analysis identifies CXCL16–CXCR6 intercellular communication between microglia and CD8+ T cells. Further, Cxcr6 deficiency impairs accumulation, tissue residency programming and clonal expansion of brain PD-1+CD8+ T cells. Ablation of Cxcr6 or CD8+ T cells ultimately increases proinflammatory cytokine production from microglia, with CXCR6 orchestrating brain CD8+ T cell–microglia colocalization. Collectively, our study reveals protective roles for brain CD8+ T cells and CXCR6 in mouse AD pathogenesis and highlights that microenvironment-specific, intercellular communication orchestrates tissue homeostasis and protection from neuroinflammation.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: CD8+ T cells accumulate in AD and protect mice from AD-associated pathologies.
Fig. 2: CXCL16–CXCR6 intercellular communication axis and CXCR6-dependent accumulation of CD8+ T cells in AD.
Fig. 3: Loss of CXCR6 exacerbates cognitive decline in 5xFAD mice.
Fig. 4: CXCR6 coordinates clonal expansion of brain CD8+ T cells.
Fig. 5: CXCR6 programs tissue residency of brain CD8+ T cells.
Fig. 6: CD8+ T cells colocalize with microglia in AD and restrain the proinflammatory activity of microglia in 5xFAD mice.
Fig. 7: Clonally expanded brain CD8+ T cells show regulatory gene expression and function on microglia in 5xFAD mice.

Similar content being viewed by others

Data availability

Data supporting the findings of this study are available within the paper. All scRNA-seq and scTCR-seq data described in the paper have been deposited in the NCBI Gene Expression Omnibus (GEO) database and are accessible through the GEO SuperSeries accession number GSE207702. Public data analyzed in this paper are also available under the GEO accession codes GSE73721 (ref. 24), GSE157827 (ref. 25), GSE98971 (ref. 10; for the DAM signature), GSE107395 (ref. 30; for the TRM cell signature) and GSE130975 (ref. 36; for the regulatory CD8+ T cell signature), downloaded from SRA accession number PRJNA529095 (ref. 11) or the PRIDE database (http://www.proteomexchange.org) with accession number PXD007985 (ref. 22). Publicly available databases used in this study are available at the indicated locations: MSigDB Collections (for Hallmark, CP: Reactome, and C5: GO:BP; http://www.gsea-msigdb.org/gsea/msigdb/collections.jsp) and the GLIPH2 database (http://50.255.35.37:8080/). Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Bettcher, B. M., Tansey, M. G., Dorothee, G. & Heneka, M. T. Peripheral and central immune system crosstalk in Alzheimer disease—a research prospectus. Nat. Rev. Neurol. 17, 689–701 (2021).

    PubMed  PubMed Central  Google Scholar 

  2. Leng, F. & Edison, P. Neuroinflammation and microglial activation in Alzheimer disease: where do we go from here? Nat. Rev. Neurol. 17, 157–172 (2021).

    PubMed  Google Scholar 

  3. Gate, D. et al. Clonally expanded CD8 T cells patrol the cerebrospinal fluid in Alzheimer’s disease. Nature 577, 399–404 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Phongpreecha, T. et al. Single-cell peripheral immunoprofiling of Alzheimer’s and Parkinson’s diseases. Sci. Adv. 6, eabd5575 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Marsh, S. E. et al. The adaptive immune system restrains Alzheimer’s disease pathogenesis by modulating microglial function. Proc. Natl Acad. Sci. USA 113, E1316–E1325 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Baruch, K. et al. Breaking immune tolerance by targeting Foxp3+ regulatory T cells mitigates Alzheimer’s disease pathology. Nat. Commun. 6, 7967 (2015).

    CAS  PubMed  Google Scholar 

  7. Kim, K. et al. Therapeutic B-cell depletion reverses progression of Alzheimer’s disease. Nat. Commun. 12, 2185 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Chen, X. et al. Microglia-mediated T cell infiltration drives neurodegeneration in tauopathy. Nature 615, 668–677 (2023).

    CAS  PubMed  Google Scholar 

  9. Olah, M. et al. Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease. Nat. Commun. 11, 6129 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Keren-Shaul, H. et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell 169, 1276–1290 (2017).

    CAS  PubMed  Google Scholar 

  11. Van Hove, H. et al. A single-cell atlas of mouse brain macrophages reveals unique transcriptional identities shaped by ontogeny and tissue environment. Nat. Neurosci. 22, 1021–1035 (2019).

    PubMed  Google Scholar 

  12. Da Mesquita, S. et al. Functional aspects of meningeal lymphatics in ageing and Alzheimer’s disease. Nature 560, 185–191 (2018).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Saito, T. et al. Single App knock-in mouse models of Alzheimer’s disease. Nat. Neurosci. 17, 661–663 (2014).

    CAS  PubMed  Google Scholar 

  15. Unger, M. S. et al. CD8+ T-cells infiltrate Alzheimer’s disease brains and regulate neuronal- and synapse-related gene expression in APP–PS1 transgenic mice. Brain Behav. Immun. 89, 67–86 (2020).

    CAS  PubMed  Google Scholar 

  16. Alves de Lima, K., Rustenhoven, J. & Kipnis, J. Meningeal immunity and its function in maintenance of the central nervous system in health and disease. Annu. Rev. Immunol. 38, 597–620 (2020).

    CAS  PubMed  Google Scholar 

  17. Da Mesquita, S. et al. Meningeal lymphatics affect microglia responses and anti-Aβ immunotherapy. Nature 593, 255–260 (2021).

    PubMed  PubMed Central  Google Scholar 

  18. Scheltens, P. et al. Alzheimer’s disease. Lancet 397, 1577–1590 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Miedel, C. J., Patton, J. M., Miedel, A. N., Miedel, E. S. & Levenson, J. M. Assessment of spontaneous alternation, novel object recognition and limb clasping in transgenic mouse models of amyloid-β and tau neuropathology. J. Vis. Exp. 123, 55523 (2017).

    Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Zhang, L. et al. Single-cell analyses inform mechanisms of myeloid-targeted therapies in colon cancer. Cell 181, 442–459 (2020).

    CAS  PubMed  Google Scholar 

  22. Bai, B. et al. Deep multilayer brain proteomics identifies molecular networks in Alzheimer’s disease progression. Neuron 105, 975–991 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Bai, B. et al. Proteomic landscape of Alzheimer’s disease: novel insights into pathogenesis and biomarker discovery. Mol. Neurodegener. 16, 55 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Zhang, Y. et al. Purification and characterization of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse. Neuron 89, 37–53 (2016).

    CAS  PubMed  Google Scholar 

  25. Lau, S. F., Cao, H., Fu, A. K. Y. & Ip, N. Y. Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer’s disease. Proc. Natl Acad. Sci. USA 117, 25800–25809 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Yuan, P. et al. TREM2 haplodeficiency in mice and humans impairs the microglia barrier function leading to decreased amyloid compaction and severe axonal dystrophy. Neuron 90, 724–739 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Glanville, J. et al. Identifying specificity groups in the T cell receptor repertoire. Nature 547, 94–98 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Chronister, W. D. et al. TCRMatch: predicting T-cell receptor specificity based on sequence similarity to previously characterized receptors. Front. Immunol. 12, 640725 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Milner, J. J. et al. Runx3 programs CD8+ T cell residency in non-lymphoid tissues and tumours. Nature 552, 253–257 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Kok, L., Masopust, D. & Schumacher, T. N. The precursors of CD8+ tissue resident memory T cells: from lymphoid organs to infected tissues. Nat. Rev. Immunol. 22, 283–293 (2021).

    PubMed  PubMed Central  Google Scholar 

  32. Pasciuto, E. et al. Microglia require CD4 T cells to complete the fetal-to-adult transition. Cell 182, 625–640 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Piehl, N. et al. Cerebrospinal fluid immune dysregulation during healthy brain aging and cognitive impairment. Cell 185, 5028–5039 (2022).

    CAS  PubMed  Google Scholar 

  34. Liu, X. et al. Unbiased and robust analysis of co-localization in super-resolution images. Stat. Methods Med. Res. 31, 1484–1499 (2022).

    PubMed  PubMed Central  Google Scholar 

  35. Jin, S. et al. Inference and analysis of cell–cell communication using CellChat. Nat. Commun. 12, 1088 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Saligrama, N. et al. Opposing T cell responses in experimental autoimmune encephalomyelitis. Nature 572, 481–487 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Dudek, M. et al. Auto-aggressive CXCR6+ CD8 T cells cause liver immune pathology in NASH. Nature 592, 444–449 (2021).

    CAS  PubMed  Google Scholar 

  38. Di Pilato, M. et al. CXCR6 positions cytotoxic T cells to receive critical survival signals in the tumor microenvironment. Cell 184, 4512–4530 (2021).

    PubMed  PubMed Central  Google Scholar 

  39. Hemonnot, A. L., Hua, J., Ulmann, L. & Hirbec, H. Microglia in Alzheimer disease: well-known targets and new opportunities. Front. Aging Neurosci. 11, 233 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Heckmann, B. L. et al. LC3-associated endocytosis facilitates β-amyloid clearance and mitigates neurodegeneration in murine Alzheimer’s disease. Cell 178, 536–551 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Hansen, D. V., Hanson, J. E. & Sheng, M. Microglia in Alzheimer’s disease. J. Cell Biol. 217, 459–472 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Sarlus, H. & Heneka, M. T. Microglia in Alzheimer’s disease. J. Clin. Invest 127, 3240–3249 (2017).

    PubMed  PubMed Central  Google Scholar 

  43. Wendeln, A. C. et al. Innate immune memory in the brain shapes neurological disease hallmarks. Nature 556, 332–338 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Heneka, M. T. et al. NLRP3 is activated in Alzheimer’s disease and contributes to pathology in APP/PS1 mice. Nature 493, 674–678 (2013).

    CAS  PubMed  Google Scholar 

  45. Chapman, N. M. & Chi, H. Metabolic adaptation of lymphocytes in immunity and disease. Immunity 55, 14–30 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Altendorfer, B. et al. Transcriptomic profiling identifies CD8+ T cells in the brain of aged and Alzheimer’s disease transgenic mice as tissue-resident memory T cells. J. Immunol. 209, 1272–1285 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Smolders, J. et al. Tissue-resident memory T cells populate the human brain. Nat. Commun. 9, 4593 (2018).

    PubMed  PubMed Central  Google Scholar 

  48. Alves de Lima, K. et al. Meningeal γδ T cells regulate anxiety-like behavior via IL-17a signaling in neurons. Nat. Immunol. 21, 1421–1429 (2020).

    CAS  PubMed  Google Scholar 

  49. Baruch, K. et al. PD-1 immune checkpoint blockade reduces pathology and improves memory in mouse models of Alzheimer’s disease. Nat. Med. 22, 135–137 (2016).

    CAS  PubMed  Google Scholar 

  50. Li, J. et al. KIR+CD8+ T cells suppress pathogenic T cells and are active in autoimmune diseases and COVID-19. Science 376, eabi9591 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Beach, T. G. et al. Arizona Study of Aging and Neurodegenerative Disorders and Brain and Body Donation Program. Neuropathology 35, 354–389 (2015).

    PubMed  PubMed Central  Google Scholar 

  52. Derecki, N. C. et al. Regulation of learning and memory by meningeal immunity: a key role for IL-4. J. Exp. Med. 207, 1067–1080 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Bhat, S. A., Sood, A., Shukla, R. & Hanif, K. AT2R activation prevents microglia pro-inflammatory activation in a NOX-dependent manner: inhibition of PKC activation and p47phox phosphorylation by PP2A. Mol. Neurobiol. 56, 3005–3023 (2019).

    CAS  PubMed  Google Scholar 

  54. Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33, 495–502 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Borcherding, N., Bormann, N. L. & Kraus, G. scRepertoire: an R-based toolkit for single-cell immune receptor analysis. F1000Res 9, 47 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Huang, H., Wang, C., Rubelt, F., Scriba, T. J. & Davis, M. M. Analyzing the Mycobacterium tuberculosis immune response by T-cell receptor clustering with GLIPH2 and genome-wide antigen screening. Nat. Biotechnol. 38, 1194–1202 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Ramilowski, J. A. et al. A draft network of ligand–receptor-mediated multicellular signalling in human. Nat. Commun. 6, 7866 (2015).

    CAS  PubMed  Google Scholar 

  60. Vento-Tormo, R. et al. Single-cell reconstruction of the early maternal–fetal interface in humans. Nature 563, 347–353 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Reimand, J. et al. Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap. Nat. Protoc. 14, 482–517 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Dong, X. et al. NetBID2 provides comprehensive hidden driver analysis. Nat. Commun. 14, 2581 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We acknowledge M. Hendren and R. Walton for animal colony management and animal behavior, P. Zhou and L. Long for performing tail vein injections, S. Yuan for tissue processing, J. Raynor and X. Sun for scientific insights, B. Heckmann for discussion of animal behavior experiments, T. C. Saido (RIKEN Center for Brain Science) for providing APPNL-G-F mice and the St. Jude Immunology Flow Cytometry Core Facility for cell sorting. This work was supported by ALSAC, the Arizona Department of Health Services, the Arizona Research Commission, the Michael J. Fox Foundation for Parkinson’s Research and US National Institutes of Health grants AG072980, NS072026 and AG19610 (to T.G.B.), AG068581 (to J.P.) and AI131703 (to H.C.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author information

Author notes

  1. These authors contributed equally: Wei Su, Jordy Saravia.

Authors and Affiliations

  1. Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Wei Su, Jordy Saravia, Isabel Risch, Sherri Rankin, Cliff Guy, Nicole M. Chapman, Hao Shi, Yu Sun, Anil KC, Wei Li, Hongling Huang, Seon Ah Lim, Haoran Hu, Yan Wang & Hongbo Chi

  2. Department of Structural Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Danting Liu, Yun Jiao, Ping-Chung Chen, Hadeer Soliman & Junmin Peng

  3. Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Danting Liu, Yun Jiao, Ping-Chung Chen, Hadeer Soliman & Junmin Peng

  4. Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Koon-Kiu Yan, Jonathan Zhang & Jiyang Yu

  5. Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Peter Vogel

  6. Department of Mathematics, University of New Orleans, New Orleans, LA, USA

    Xueyan Liu

  7. Banner Sun Health Research Institute, Sun City, AZ, USA

    Geidy E. Serrano & Thomas G. Beach

  8. Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Junmin Peng

Authors
  1. Wei Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jordy Saravia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Isabel Risch
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sherri Rankin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cliff Guy
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Nicole M. Chapman
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hao Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yu Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Anil KC
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Wei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Hongling Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Seon Ah Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Haoran Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Yan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Danting Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Yun Jiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Ping-Chung Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Hadeer Soliman
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Koon-Kiu Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Jonathan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Peter Vogel
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Xueyan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Geidy E. Serrano
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Thomas G. Beach
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Jiyang Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Junmin Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Hongbo Chi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

W.S. and J.S. conceived the project, designed and performed in vitro and in vivo experiments, analyzed data and wrote the paper. I.R., H. Shi, Y.S. and H. Hu performed scRNA-seq data analysis. S.R. and C.G. performed immunofluorescence stainings. N.M.C. helped to conceive and design experiments and co-wrote the paper. W.L. performed scRNA-seq experiments of 5xFAD and 5xFAD; Cxcr6–/– mice. H. Huang performed scRNA-seq experiments of Non-Tg and 5xFAD mice. A.K., S.A.L. and Y.W. assisted with cellular experiments. D.L., Y.J., P.-C.C. and H. Soliman helped with the analysis of APPNL-G-F mice, collected tissue samples from 5xFAD mice and helped with postmortem brain tissue sections from individuals with AD. H. Shi, K.-K.Y. and J.Z. developed cell–cell communication network inferences. P.V. performed immunohistochemistry stainings. X.L. performed spatial colocalization analyses. G.E.S. and T.G.B. provided postmortem brain tissue from individuals with AD. J.P. provided 5xFAD mice and scientific insights. J.Y. provided oversight of bioinformatics and scientific insights. H.C. helped to conceive and design experiments, co-wrote the paper and provided overall direction.

Corresponding author

Correspondence to Hongbo Chi.

Ethics declarations

Competing interests

H.C. is a consultant for Kumquat Biosciences. The other authors declare no competing interests.

Peer review

Peer review information

Nature Immunology thanks Vijay Kuchroo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: L. A. Dempsey, in collaboration with the Nature Immunology team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 T cells accumulate in mouse models of AD.

a, Schematic workflow of scRNA-seq and scTCR-seq experiments, showing tissue collection sites, cell sorting strategies and computational analyses of Non-Tg and 5xFAD mice. b, Gating strategy for sorting microglia and non-microglia immune cells used for scRNA-seq and scTCR-seq analysis. Sorting gates for Non-Tg and 5xFAD samples were set according to the following parameters (in order): 1) cell size (to exclude debris); 2) singlet; 3) viable cells; 4) CD45int/+CD11b+ (for microglia) and CD45+CD11b– (for non-microglia immune cells). c, Violin plots showing expression of cell type-defining genes in clusters from Fig. 1b. d, e, CD45+ immune cell clusters colored by genotype (d) or cell types (e) from a public dataset of indicated mice11. f, Frequencies of cells described in d and e. g, Brain T cells (CD3+TCRβ+) from 10-month-old Non-Tg (n = 11) and 5xFAD (n = 13) mice. h, CD4+ and CD8+ T cells in the brains of female and male 10-month-old Non-Tg (n = 12 for female and 9 for male) and 5xFAD (n = 14 for female and 11 for male) mice. i, j, CD3+ (i, 3 months: Non-Tg (n = 4) and 5xFAD (n = 4); 6 months: Non-Tg (n = 8) and 5xFAD (n = 9); 9 months: Non-Tg (n = 8) and 5xFAD (n = 13); 12 months: Non-Tg (n = 11) and 5xFAD (n = 13)) or CD4+ (j, 3 months: Non-Tg (n = 6) and 5xFAD (n = 6); 6 months: Non-Tg (n = 13) and 5xFAD (n = 16); 9 months: Non-Tg (n = 8) and 5xFAD (n = 9); 12 months: Non-Tg (n = 14) and 5xFAD (n = 17)) T cells in the brains of Non-Tg and 5xFAD mice at indicated time points. k, Immunohistochemical analysis of CD3+ T cells in the brains of 10-month-old Non-Tg (n = 7) and 5xFAD (n = 6) mice. Scale bar, 200 μm. Arrows indicate positive staining for CD3+ T cells. l, m, CD3+ (l) or CD8+ (m) T cells in the brains of Non-Tg and APPNL-G-F mice (3 months: Non-Tg (n = 5) and APPNL-G-F (n = 5); 6 months: Non-Tg (n = 5) and APPNL-G-F (n = 4); 9 months: Non-Tg (n = 5) and APPNL-G-F (n = 4)). Data were analyzed by two-tailed unpaired Student’s t-test (g, h, k–m) or two-way ANOVA (i, j). Data are shown as mean ± s.e.m. in g–m; NS, not significant. Data were pooled from at least three (g–j) or two (k–m) independent experiments.

Source data

Extended Data Fig. 2 Single-cell immune profiling of meninges and functional characterization of T cells by multiple genetic models.

a, b, scRNA-seq profiling of CD45+ immune cells from the meninges of male Non-Tg or 5xFAD mice (n = 2 biological replicates for each genotype) at 8 months of age. CD45+ immune cell clusters colored by genotype (a) or cell type (b). c, Frequencies (normalized to total cells from each genotype) of annotated clusters described in b. d, CD4+ and CD8+ T cells in the meninges of 10-month-old Non-Tg (n = 13) and 5xFAD (n = 13) mice. e, CD4+ and CD8+ T cells in the indicated tissues of 10-month-old Non-Tg and 5xFAD mice (spleen: Non-Tg (n = 11), 5xFAD (n = 16); liver: Non-Tg (n = 7), 5xFAD (n = 8); lung: Non-Tg (n = 5), 5xFAD (n = 6)). f, Representative flow cytometry plots demonstrating a lack of CD8+TCRβ+ or CD4+TCRβ+ T cells in the brains of 5xFAD;Tcra–/– mice. g, Immunofluorescence analysis of the number and burden of Aβ plaques in 10-month-old female 5xFAD;Tcra+/+ (n = 8 sections for plaque number; n = 15 sections for plaque burden) and 5xFAD;Tcra–/– (n = 9 sections for plaque number; n = 15 sections for plaque burden) mice. Scale bar, 250 μm. h, Representative flow cytometry plots demonstrating a lack of CD8+ T cells (CD8+TCRβ+) but not CD4+ T cells (CD4+TCRβ+) in the brains of 5xFAD;B2m–/– mice. i, Immunofluorescence analysis of number and burden of Aβ plaques in 10-month-old male and female 5xFAD;B2m+/+ (n = 9 sections for female and 8 for male for plaque number; n = 10 sections for female and 4 for male for plaque burden) and 5xFAD;B2m–/– (n = 10 sections for female and 12 for male for plaque number; n = 10 sections for female and 6 for male for plaque burden) mice. Scale bar, 250 μm. j, k, Illustrations of Y maze (j) and novel objection recognition (k) behavioral tests. l, Total arm entries from spontaneous Y maze alternation testing in 4-month-old 5xFAD;B2m+/+ (n = 9 for female and 8 for male) and 5xFAD;B2m–/– (n = 15 for female and 8 for male) mice. m, n, Spontaneous alternation (m) and total arm entries (n) from spontaneous Y maze alternation testing in 4-month-old female 5xFAD;Tcra+/+ (n = 15) and 5xFAD;Tcra–/– (n = 15) mice. Data were analyzed by two-tailed unpaired Student’s t-test (d, e, g, i for plaque burden and l–n) or two-tailed unpaired t-test with Welch’s correction for plaque number (g, i). Data are shown as mean ± s.e.m. in d, e, g, i and l–n; NS, not significant. Data were pooled from at least three (d, e, m, n) or two (g, i, l) independent experiments or are representative of at least two (f, h) independent experiments.

Source data

Extended Data Fig. 3 CXCL16–CXCR6 intercellular communication axis between microglia and T cells.

a, Circle plot of predicted cell type interactions based on ligand–receptor pairs in brain immune cells in 5xFAD mice. Line thickness indicates number of ligand–receptor interactions; red color indicates CD8+ T cells and microglia as the cell-type pair with the highest number of interactions; purple color indicates comparatively weaker interactions present between CD4+ T or NK cells and microglia. b, GSEA enrichment plots showing upregulation of chemokine-associated signatures in microglia from 5xFAD mice compared to Non-Tg mice. c, Circle plot of predicted cell–cell interactions based on CXCL16 and CXCR6 pairing in brain immune cells of 5xFAD mice (red arrow indicates strongest interaction). d, Violin plot of Cxcl16 expression in microglia from Non-Tg (n = 1,782 cells) and 5xFAD (n = 2,870 cells) mice. e, Violin plot of Cxcl16 expression in immune cell clusters (n = 4,105 cells for M0 and 547 cells for DAM) in 5xFAD mice. f, GSEA enrichment plots showing upregulation of chemokine-associated signatures in DAM compared to M0. g, Bubble plot showing stronger predicted CXCL16–CXCR6 interaction between DAM and CD8+ T cells than M0 and CD8+ T cells in 5xFAD mice. h, Circle plot of predicted cell–cell interactions based on CXCL16 and CXCR6 pairing in brain immune cells of APP/PS1 mice (red arrow indicates the strongest interaction); BAM/DCs, border-associated macrophages/dendritic cells. i, Bubble plot showing stronger predicted CXCL16–CXCR6 interaction between DAM and CD8+ T cells than M0 and CD8+ T cells in APP/PS1 mice. j, Bubble plot of CXCL16 expression in brain cell types from a public human single-nuclear RNA-seq dataset25. k, CXCR6+CD8+ T cells in the meninges (Non-Tg (n = 13) and 5xFAD (n = 13)), spleen (Non-Tg (n = 5) and 5xFAD (n = 7)), liver (Non-Tg (n = 5) and 5xFAD (n = 7)), and lung (Non-Tg (n = 5) and 5xFAD (n = 7)) of 10-month-old Non-Tg and 5xFAD mice. l, CXCR6+CD4+ T cells from the spleens and brains of 10-month-old Non-Tg (n = 6) and 5xFAD (n = 9) mice. Data were analyzed by two-tailed normalized weighted Kolmogorov–Smirnov test (NES for b and f), two-tailed Benjamini–Hochberg adjusted P value (FDR for b and f), two-tailed Bonferroni correction (d), two-tailed Wilcoxon rank-sum test (e), or two-tailed unpaired Student’s t-test (k, l). Data are shown as mean ± s.e.m. in k and l; NS, not significant. Data were pooled from at least three (k, l) independent experiments.

Source data

Extended Data Fig. 4 CXCR6 promotes brain CD8+ T cell accumulation.

a, Widefield immunofluorescence images of CD3+ T cells, Aβ and Iba1+ microglia in brains of indicated 10-month-old mice. Scale bar, 200 μm. White arrows indicate positive staining for CD3+ T cells. Boxed areas show CD3 staining insets. b, CD4+ and CD8+ T cells in the meninges (upper left, 5xFAD;Cxcr6+/+ (n = 13) and 5xFAD;Cxcr6–/– (n = 9)), spleen (upper right, 5xFAD;Cxcr6+/+ (n = 16) and 5xFAD;Cxcr6–/– (n = 17)), liver (lower left, 5xFAD;Cxcr6+/+ (n = 8) and 5xFAD;Cxcr6–/– (n = 10)), or lung (lower right, 5xFAD;Cxcr6+/+ (n = 7) and 5xFAD;Cxcr6–/– (n = 10)) of indicated 10-month-old mice. c–f, Indicated immune cell populations in the brains of 10-month-old female and male 5xFAD;Cxcr6+/+ (c, d; n = 10, 10, 6, 6, 10, and 6 for CD8+ T cells, CD4+ T cells, NK1.1 cells, NKT cells, γδ T cells, and eTreg cells in female mice, respectively; and 12, 12, 9, 9, 9, and 7 for CD8+ T cells, CD4+ T cells, NK1.1 cells, NKT cells, γδ T cells, and eTreg cells in male mice, respectively) and 5xFAD;Cxcr6–/– mice (c, d; n = 14, 14, 7, 7, 13 and 7 for CD8+ T cells, CD4+ T cells, NK1.1 cells, NKT cells, γδ T cells, and eTreg cells in female mice, respectively; and 13, 13, 11, 11, 11, and 7 for CD8+ T cells, CD4+ T cells, NK1.1 cells, NKT cells, γδ T cells, and eTreg in male mice, respectively), or in 4-month-old APPNL-G-F;Cxcr6+/+ (e, f; n = 5, 5, 5, 5, 4 and 5 for CD8+ T cells, CD4+ T cells, NK1.1 cells, NKT cells, γδ T cells, and eTreg cells in female mice, respectively; and 5, 5, 5, 5, 5, and 5 for CD8+ T cells, CD4+ T cells, NK1.1 cells, NKT cells, γδ T cells, and eTreg cells in male mice, respectively) and APPNL-G-F;Cxcr6–/– (e, f; n = 5, 5, 5, 5, 4 and 5 for CD8+ T cells, CD4+ T cells, NK1.1 cells, NKT cells, γδ T cells, and eTreg cells in female mice, respectively; and 6, 6, 6, 6, 6, and 6 for CD8+ T cells, CD4+ T cells, NK1.1 cells, NKT cells, γδ T cells, and eTreg cells in male mice, respectively) mice. g, Non-viable (Zombie Aqua+) CD8+ T cells in indicated tissues of 10-month-old 5xFAD;Cxcr6+/+ (n = 13, 9, 9, 4 for meninges, spleen, liver, lung, respectively) and 5xFAD;Cxcr6–/– (n = 9, 12, 12, 7 for meninges, spleen, liver, lung, respectively) mice. h, Ki67+ cells among brain CD8+ T cells from 10-month-old 5xFAD;Cxcr6+/+ (n = 8) and 5xFAD;Cxcr6–/– (n = 9) mice. Data were analyzed by two-tailed unpaired Student’s t-test (b–h). Data are shown as mean ± s.e.m. in b–h; NS, not significant. Data were pooled from at least two (b–h) independent experiments or are representative of two (a) independent experiments.

Source data

Extended Data Fig. 5 CXCR6 deletion increases Aβ plaques in 5xFAD mice.

a, Representative immunofluorescence images (upper) and quantification of number (lower left) and burden (% of area) (lower right) of Aβ plaques in 10-month-old female 5xFAD;Cxcr6+/+ (n = 6 sections for plaque number; n = 4 sections for plaque burden) and 5xFAD;Cxcr6–/– (n = 8 sections for plaque number; n = 16 sections for plaque burden) mice. Scale bar, 250 μm. b, Representative Aβ immunostaining in composite wide-field brain sections from indicated 10-month-old female mice. c, Immunofluorescence analysis of number and burden of Aβ plaques in 4-month-old male 5xFAD;Cxcr6+/+ (n = 10 sections for plaque number; n = 8 sections for plaque burden) and 5xFAD;Cxcr6–/– (n = 12 sections for plaque number; n = 8 sections for plaque burden) mice. Scale bar, 250 μm. d, Immunofluorescence analysis of number and burden of Aβ plaques in 10-month-old male 5xFAD;Cxcr6+/+ (n = 6 sections for plaque number; n = 6 sections for plaque burden) and 5xFAD;Cxcr6–/– (n = 6 sections for plaque number; n = 6 sections for plaque burden). Scale bar, 250 μm. e, f, Soluble and insoluble fractions of Aβ1-40 and Aβ1-42 protein levels in the hippocampus or cortex of 4-month-old female (e) and male (f) 5xFAD;Cxcr6+/+ (n = 4 for female and 4 for male) and 5xFAD;Cxcr6–/– (n = 4 for female and 4 for male) mice. g, Total arm entries from spontaneous Y maze alternation testing of 5xFAD;Cxcr6+/+ (n = 10 for female and 9 for male) and 5xFAD;Cxcr6–/– (n = 9 for female and 10 for male) mice. h, Filamentous, compact, and inert Aβ plaque phenotypes in brain sections from 10-month-old female 5xFAD;Cxcr6+/+ (n = 6 sections) and 5xFAD;Cxcr6–/– (n = 8 sections) mice. Data were analyzed by two-tailed unpaired Student’s t-test (a, c, d for plaque burden and e–h) or two-tailed unpaired t-test with Welch’s correction for plaque number (a, c, d). Data are shown as mean ± s.e.m. in a and c–h; NS, not significant. Data were pooled from at least two (a, c, d, g) or one (b, e, f, h) independent experiments.

Source data

Extended Data Fig. 6 Clonal expansion of Pdcd1-expressing brain CD8+ T cells in 5xFAD mice.

a, Frequencies of clonally expanded (clonotype size > 1) versus non-expanded (clonotype size = 1) αβ+ T cells in brain and meninges from indicated mice. b, Subclustered brain and meninges αβ+ T cells colored by clonotype sizes and genotypes. c, Identification of CD4+ T cell, CD8+ T cell and NKT cell clusters among αβ+ T cells combined from both tissues and genotypes. d, TCR clones detected among CD8+ T cells, CD4+ T cells and NKT cells, grouped by their clonotype sizes. e, Top 5 GLIPH patterns with TRBV sequence and number of cells in clonally expanded CD8+ T cells in the brains of 5xFAD mice from scTCR-seq analysis. f, TCRMatch analysis for predicted antigen epitopes that are recognized by clonally expanded brain CD8+ T cells from 5xFAD mice. g, Bar plot showing Pearson correlation of gene expression with clonotype sizes, with Pdcd1 identified as the top-ranked gene. h, Heatmap depicting relative expression values of the top 10 differentially expressed genes in each brain CD8+ T cell subcluster shown in Fig. 4c, with selected genes labeled. i, Frequencies of clonotype sizes for brain CD8+ T cells from Fig. 4c cluster 2 (representing the highest expression of Pdcd1) in Non-Tg versus 5xFAD mice. j, Fold change (FC)/FC plot analysis of transcriptomes from clonally expanded versus non-expanded CD8+ T cells compared with Pdcd1+ versus Pdcd1– CD8+ T cells. Red and blue dots indicate shared upregulated and downregulated genes, respectively. Data were analyzed by Pearson correlation coefficient (for r in j) and two-tailed F-test (for P value in j).

Extended Data Fig. 7 Clonal expansion and heterogeneity of CD8+ T cells in the brain and meninges.

a, b, GSEA enrichment plots showing increased core TRM cell signature30 in clonally expanded versus non-expanded (a) or Pdcd1+ versus Pdcd1– (b) brain CD8+ T cells. c, d, Heatmap of TRM cell signature genes30 in clonally expanded versus non-expanded (c) or Pdcd1+ versus Pdcd1– (d) brain CD8+ T cells. e, CD69+ (lower left), CD103+ (lower middle), and CD69+ CD103+ (lower right) among brain CD4+ T cells from 10-month-old Non-Tg (n = 4) and 5xFAD (n = 5) mice. f, Two separate imaging fields depicting brain CD8+ T cells (yellow) in proximity to Aβ (green) and CD31+ intravascular structures (red) in 10-month-old 5xFAD mice. Scale bar, 200 μm. Boxed areas show CD8 staining insets. g, PD-1 expression on PE+ and PE– CD8+ T cells from 10-month-old Non-Tg (n = 3) and 5xFAD (n = 3) mice. PE+ and PE– populations were identified after 5 min of labeling by intravenous injection of PE-conjugated anti-CD45 antibody; MFI, mean fluorescence intensity. h, Alluvial plots showing the top 20 CD8+ T cell clones (shared TCRα and TCRβ sequences) between brain and meninges from Non-Tg and 5xFAD mice. i, Pie chart summarizing the percentages (normalized to total cells in each compartment) of CD8+ T cell clonotype sizes in brain and meninges. j, Subclustered CD8+ T cells colored by CNS compartments or subclusters. k, Bar plot showing the frequencies (normalized to total cells from each compartment) of cells derived from the brain and meninges in subclusters as shown in j. l, Violin plots of Pdcd1 expression in CD8+ T cell subclusters as shown in j. The asterisk (*) labels significance in indicated subcluster (n = 1,274 cells) compared to all other subclusters (n = 3,900 cells). m, Clonotypes of CD8+ T cells and bar plot showing the distribution of clonotype sizes for CD8+ T cell subclusters shown in j. The encircled region indicates subcluster 3. Clonotype size: Large ( >20); Medium (6–20); Small (2–5); and Single (1). n, UMAP and violin plots showing Pdcd1 expression from the brain (n = 4,641 cells) and meninges (n = 533 cells). o, Bubble plot showing relative Cd69 and Itgae expression in CD8+ T cells in the brain and meninges of 5xFAD mice. p, CD69+, CD103+, and CD69+CD103+ cells among CD8+ T cells in the meninges (n = 11) and brains (n = 12) of 10-month-old 5xFAD mice. Data were analyzed by two-tailed normalized weighted Kolmogorov–Smirnov test (NES for a and b), two-tailed Benjamini–Hochberg adjusted P value (FDR for a and b), two-tailed unpaired Student’s t-test (e, g, p), or two-tailed Wilcoxon rank-sum test (l, n). Data are shown as mean ± s.e.m. in e, g and p; NS, not significant. Data were pooled from at least three (p), two (g) or one (e) independent experiments.

Source data

Extended Data Fig. 8 CXCR6-dependent clonal expansion and tissue residency programs in brain CD8+ T cells from 5xFAD mice.

a, UMAP and violin plots showing Cxcr6 expression in brain CD8+ T cells. b, UMAP of Pdcd1 expression (also shown in Fig. 4e) or Cxcr6 and Pdcd1 coexpression (purple color) in brain CD8+ T cell subclusters shown in a. c, UMAP of CD8+ T cells from a public dataset of Non-Tg and APP/PS1 mice11 colored by genotypes. d, Expression of Cxcr6, Pdcd1 or their overlap (purple color) on subclusters shown in c. e, CXCR6+PD-1+CD8+ T cells (3 months: Non-Tg (n = 3) and 5xFAD (n = 3); 6 months: Non-Tg (n = 4) and 5xFAD (n = 4); 9 months: Non-Tg (n = 4) and 5xFAD (n = 4); 12 months: Non-Tg (n = 5) and 5xFAD (n = 10)) in the brains of Non-Tg and 5xFAD mice at indicated time points. f, g, Subclustered brain CD8+ T cells from indicated mice colored by genotype (f) or subclusters (g). h, UMAP and violin plot of Pdcd1 expression in brain CD8+ T cell subclusters in g. i, PD-1+CD8+ T cells in the brains of APPNL-G-F;Cxcr6+/+ (n = 10) and APPNL-G-F;Cxcr6–/– (n = 11) mice. j, CD69+CXCR6+CD8+ T cells from 10-month-old Non-Tg (n = 5) and 5xFAD (n = 8) mice. k, l, GSEA enrichment plots showing downregulated core TRM cell signature in clonally expanded (k) or Pdcd1+ brain CD8+ T cells (l) from 5xFAD;Cxcr6–/– versus 5xFAD;Cxcr6+/+ mice. m, CD69+, CD103+, and CD69+CD103+ among brain CD8+ T cells from 4-month-old APPNL-G-F;Cxcr6+/+ (n = 10) and APPNL-G-F;Cxcr6–/– (n = 11) mice. Data were analyzed by two-way ANOVA (e), two-tailed unpaired Student’s t-test (i, j, m), two-tailed normalized weighted Kolmogorov–Smirnov test (NES for k and l), or two-tailed Benjamini–Hochberg adjusted P value (FDR for k and l). Data are shown as mean ± s.e.m. in e, i, j and m; NS, not significant. Data were pooled from at least three (12 months in e, i and j), two (6 and 9 months in e and m) or one (3-month-old mice in e) independent experiments.

Source data

Extended Data Fig. 9 Brain T cells colocalize with microglia and Aβ plaques in 5xFAD mice and inhibit microglia proinflammatory activity.

a, GSEA enrichment plot showing upregulation of inflammatory response signatures in microglia from 5xFAD mice versus Non-Tg mice. b, Violin plots showing expression of Tnf, Il1b and Tgfb1 in microglia from Non-Tg (n = 1,782 cells) and 5xFAD (n = 2,870 cells) mice. c, Relative percentages (normalized to Non-Tg mice) of TNF-α+ and pro-IL-1β+ microglia from 10-month-old Non-Tg (n = 15) and 5xFAD (n = 21) mice. d, Immunofluorescence images of brain CD3+ T cells in proximity to Aβ or Iba1+ microglia in 10-month-old 5xFAD mice. Scale bar, 20 μm. e, Immunofluorescence image of brain CD8+ T cells (red), Aβ (white) and Iba1+ microglia (green) in 10-month-old 5xFAD;Cxcr6–/– mice. Scale bar, 20 μm. f, g, Spatial colocalization index between CD8+ T cells (CD8) and activated microglia (Iba1) (f) or CD8 and Aβ plaques (g) within the brains of 5xFAD;Cxcr6+/+ (n = 105 scored interactions) and 5xFAD;Cxcr6–/– (n = 71 scored interactions) mice. The index values for each target–pair were compared by genotype (P values shown in black color) and against simulated random distribution (P values shown in red or green color) (see Methods). h, Immunofluorescence images of PD-1 (green) and CD8 (red) coexpressing T cells in proximity to Iba1+ microglia (white) in 10-month-old 5xFAD mice. Scale bar, 5 μm. i, Heatmap showing the differential interaction strength, predicted by CellChat, between T cell subsets and microglia in indicated mice. Row z score indicates the differential interaction strengths. j, k, Relative percentages (normalized to sex-matched controls) of pro-IL-1β+ microglia (j, k) and geometric mean fluorescence intensity (gMFI; j, k) from 10-month-old 5xFAD;B2m+/+ (percentage, n = 19 for female and 11 for male; gMFI, n = 19 for female and 9 for male) and 5xFAD;B2m–/– (percentage, n = 19 for female and 16 for male; gMFI, n = 19 for female and 13 for male) mice (j), or 5xFAD;Cxcr6+/+ (n = 10 for female and 16 for male) and 5xFAD;Cxcr6–/– (n = 14 for female and 24 for male) mice (k). l, m Frequencies of M0 and DAM subclusters from scRNA-seq analysis of microglia from indicated mice. n, Functional enrichment analysis of upregulated genes in M0 and DAM from 5xFAD;Cxcr6–/– versus 5xFAD;Cxcr6+/+ mice. Data were analyzed by two-tailed normalized weighted Kolmogorov–Smirnov test (NES for a), two-tailed Benjamini–Hochberg adjusted P value (FDR for a), two-tailed unpaired Student’s t-test (b, c, f, g, j, k), or two-tailed Fisher’s exact test (n). Data are shown as mean ± s.e.m. (c, j, k) or medians with quartiles (f, g); NS, not significant. Data were pooled from at least three (c, j, k) independent experiments or are representative of three (d, e) or two (f–h) independent experiments.

Source data

Extended Data Fig. 10 Brain CD8+ T cells mitigate proinflammatory features of microglia and limit microgliosis in 5xFAD mice.

a, PD-1+CD8+ T cells among freshly isolated splenic CD44hiCD8+ T cells from C57BL/6 mice (Fresh (n = 13)) and splenic CD44hiCD8+ T cells after cytokine culture (Cultured (n = 13)) (see Methods). b, Indicated marker expression on PD-1+ versus PD-1– CD44hiCD8+ T cells from 5xFAD mice (n = 20) after cytokine culture. c, TNF-α+ cells in microglia after in vitro coculture with indicated in vitro-expanded, spleen-derived CD8+ T cell populations (see Methods for details). Stimulated condition indicates treatment with PMA and ionomycin plus 1 μM Aβ (Unstimulated (n = 6); Stimulated (n = 5); Stimulated + cultured CXCR6+CD8+ T cells (n = 12); Stimulated + cultured CXCR6–CD8+ T cells (n = 12)). d, TNF-α+ cells in microglia after in vitro coculture with brain CD8+ T cells from the indicated mice (Unstimulated (n = 28); Stimulated (n = 28); Stimulated + brain-derived 5xFAD;Nt5e+/+ CD8+ T cells (n = 9); Stimulated + brain-derived 5xFAD;Nt5e–/– CD8+ T cells (n = 4)). e–g, Immunohistochemical images of Iba1+ microglia in brains of indicated mice. Scale bar, 200 μm (e) or 100 μm (f, g). h, i, Immunofluorescence analysis of Iba1+ microglia or Aβ-plaque-associated Iba1+ microglia from 10-month-old male 5xFAD;B2m+/+ (n = 4 sections from 3 mice) and 5xFAD;B2m–/– (n = 6 sections from 3 mice) mice (h) or male 5xFAD;Cxcr6+/+ (n = 6 sections from 3 mice) and 5xFAD;Cxcr6–/– (n = 6 sections from 3 mice) mice (i). Scale bar, 100 μm. j, k, Immunofluorescence analysis of Iba1+ microglia associated with individual Aβ plaques in 4-month-old (j) or 10-month-old (k) female and male 5xFAD;B2m+/+ (n = 22 sections for 4-month-old female, 10 sections for 4-month-old male, 10 sections for 10-month-old female, 4 sections for 10-month-old male) and 5xFAD;B2m–/– (n = 25 sections for 4-month-old female, 8 sections for 4-month-old male, 10 sections for 10-month-old female, 6 sections for 10-month-old male) mice. l, Model for CD8+ T cell-dependent suppression of proinflammatory microglia. CXCR6+CD8+ T cells accumulate in the brains but not meninges of 5xFAD mice, where they colocalize with proinflammatory microglia near Aβ plaques. CXCL16-expressing microglia are present in the brains of individuals with AD and mouse models, and CXCR6 is required for CD8+ T cells to undergo enhanced tissue residency programing and clonal expansion (as marked by PD-1 expression) in the brain. These PD-1+CD8+ T cells limit proinflammatory microglia that contribute to Aβ plaque accumulation and cognitive impairments. Data were analyzed by two-tailed unpaired Student’s t-test (a, b, h–k) or one-way ANOVA (c, d). Data are shown as mean ± s.e.m. in a–d and h–k; NS, not significant. Data were pooled from at least four (d), three (b), two (a, c), or one (j, k) independent experiments or are representative of two (e–i) independent experiments.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2.

Reporting Summary

Source data

Source Data Fig. 1

Excel file containing source data for graphs depicted in Fig. 1.

Source Data Fig. 2

Excel file containing source data for graphs depicted in Fig. 2.

Source Data Fig. 3

Excel file containing source data for graphs depicted in Fig. 3.

Source Data Fig. 4

Excel file containing source data for graphs depicted in Fig. 4.

Source Data Fig. 5

Excel file containing source data for graphs depicted in Fig. 5.

Source Data Fig. 6

Excel file containing source data for graphs depicted in Fig. 6.

Source Data Fig. 7

Excel file containing source data for graphs depicted in Fig. 7.

Source Data Extended Data Fig. 1

Excel file containing source data for graphs depicted in Extended Data Fig. 1.

Source Data Extended Data Fig. 2

Excel file containing source data for graphs depicted in Extended Data Fig. 2.

Source Data Extended Data Fig. 3

Excel file containing source data for graphs depicted in Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Excel file containing source data for graphs depicted in Extended Data Fig. 4.

Source Data Extended Data Fig. 5

Excel file containing source data for graphs depicted in Extended Data Fig. 5.

Source Data Extended Data Fig. 7

Excel file containing source data for graphs depicted in Extended Data Fig. 7.

Source Data Extended Data Fig. 8

Excel file containing source data for graphs depicted in Extended Data Fig. 8.

Source Data Extended Data Fig. 9

Excel file containing source data for graphs depicted in Extended Data Fig. 9.

Source Data Extended Data Fig. 10

Excel file containing source data for graphs depicted in Extended Data Fig. 10.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Su, W., Saravia, J., Risch, I. et al. CXCR6 orchestrates brain CD8+ T cell residency and limits mouse Alzheimer’s disease pathology. Nat Immunol 24, 1735–1747 (2023). https://doi.org/10.1038/s41590-023-01604-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41590-023-01604-z

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing