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:

β2-Microglobulin coaggregates with Aβ and contributes to amyloid pathology and cognitive deficits in Alzheimer’s disease model mice

Nature Neuroscience volume 26, pages 1170–1184 (2023)Cite this article

Subjects

Abstract

Extensive studies indicate that β-amyloid (Aβ) aggregation is pivotal for Alzheimer’s disease (AD) progression; however, cumulative evidence suggests that Aβ itself is not sufficient to trigger AD-associated degeneration, and whether other additional pathological factors drive AD pathogenesis remains unclear. Here, we characterize pathogenic aggregates composed of β2-microglobulin (β2M) and Aβ that trigger neurodegeneration in AD. β2M, a component of major histocompatibility complex class I (MHC class I), is upregulated in the brains of individuals with AD and constitutes the amyloid plaque core. Elevation of β2M aggravates amyloid pathology independent of MHC class I, and coaggregation with β2M is essential for Aβ neurotoxicity. B2m genetic ablation abrogates amyloid spreading and cognitive deficits in AD mice. Antisense oligonucleotide- or monoclonal antibody-mediated β2M depletion mitigates AD-associated neuropathology, and inhibition of β2M–Aβ coaggregation with a β2M-based blocking peptide ameliorates amyloid pathology and cognitive deficits in AD mice. Our findings identify β2M as an essential factor for Aβ neurotoxicity and a potential target for treating AD.

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: β2M co-sediments with Aβ and accelerates amyloid deposition in an MHC class I-independent manner.
Fig. 2: B2m deficiency ameliorates cognitive deficits and prevents spreading of amyloid pathology in 5×FAD mice.
Fig. 3: B2m deficiency abrogates oAβ-induced neurotoxicity in vivo.
Fig. 4: B2M ASO or anti-β2M antibody reduces amyloid pathology in 5×FAD mice.
Fig. 5: Peripheral clearance of β2M ameliorates amyloid pathology in 5×FAD mice.
Fig. 6: Systemic injection of anti-β2M antibody ameliorates neuropathology in 5×FAD mice.
Fig. 7: Coaggregation with β2M promotes Aβ aggregation.
Fig. 8: Blocking β2M–Aβ coaggregation abrogates Aβ aggregation and neurotoxicity.

Similar content being viewed by others

Data availability

The datasets generated and/or analyzed in the current study are within the manuscript or the Supplementary Information. The bulk RNA-sequencing data were deposited in the CNGB Sequence Archive of the China National GeneBank Database with the accession number CNP0003897. Source data are provided with this paper.

Code availability

No custom software code was used.

References

  1. Long, J. M. & Holtzman, D. M. Alzheimer disease: an update on pathobiology and treatment strategies. Cell 179, 312–339 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Duyckaerts, C., Delatour, B. & Potier, M. C. Classification and basic pathology of Alzheimer disease. Acta Neuropathol. 118, 5–36 (2009).

    Article  CAS  PubMed  Google Scholar 

  3. Bertram, L., Lill, C. M. & Tanzi, R. E. The genetics of Alzheimer disease: back to the future. Neuron 68, 270–281 (2010).

    Article  CAS  PubMed  Google Scholar 

  4. Uhlmann, R. E. et al. Acute targeting of pre-amyloid seeds in transgenic mice reduces Alzheimer-like pathology later in life. Nat. Neurosci. 23, 1580–1588 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Walker, L. C. & Jucker, M. Neurodegenerative diseases: expanding the prion concept. Annu. Rev. Neurosci. 38, 87–103 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Sowade, R. F. & Jahn, T. R. Seed-induced acceleration of amyloid-β mediated neurotoxicity in vivo. Nat. Commun. 8, 512 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Jucker, M. & Walker, L. C. Self-propagation of pathogenic protein aggregates in neurodegenerative diseases. Nature 501, 45–51 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  9. Hardy, J. & Selkoe, D. J. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297, 353–356 (2002).

    Article  CAS  PubMed  Google Scholar 

  10. Wang, J., Gu, B. J., Masters, C. L. & Wang, Y. J. A systemic view of Alzheimer disease—insights from amyloid-β metabolism beyond the brain. Nat. Rev. Neurol. 13, 612–623 (2017).

    Article  CAS  PubMed  Google Scholar 

  11. Webers, A., Heneka, M. T. & Gleeson, P. A. The role of innate immune responses and neuroinflammation in amyloid accumulation and progression of Alzheimer’s disease. Immunol. Cell Biol. 98, 28–41 (2020).

    Article  PubMed  Google Scholar 

  12. Gjoneska, E. et al. Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease. Nature 518, 365–369 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Pimenova, A. A., Raj, T. & Goate, A. M. Untangling genetic risk for Alzheimer’s disease. Biol. Psychiatry 83, 300–310 (2018).

    Article  CAS  PubMed  Google Scholar 

  14. Kunkle, B. W. et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat. Genet. 51, 414–430 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Venegas, C. et al. Microglia-derived ASC specks cross-seed amyloid-β in Alzheimer’s disease. Nature 552, 355–361 (2017).

    Article  CAS  PubMed  Google Scholar 

  16. Hur, J. Y. et al. The innate immunity protein IFITM3 modulates γ-secretase in Alzheimer’s disease. Nature 586, 735–740 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Barnes, L. L. et al. Cytomegalovirus infection and risk of Alzheimer disease in older black and white individuals. J. Infect. Dis. 211, 230–237 (2015).

    Article  CAS  PubMed  Google Scholar 

  18. Abbott, A. Are infections seeding some cases of Alzheimer’s disease? Nature 587, 22–25 (2020).

    Article  CAS  PubMed  Google Scholar 

  19. Muzambi, R. et al. Assessment of common infections and incident dementia using UK primary and secondary care data: a historical cohort study. Lancet Healthy Longev. 2, e426–e435 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Cresswell, P., Ackerman, A. L., Giodini, A., Peaper, D. R. & Wearsch, P. A. Mechanisms of MHC class I-restricted antigen processing and cross-presentation. Immunol. Rev. 207, 145–157 (2005).

    Article  CAS  PubMed  Google Scholar 

  21. Goddard, C. A., Butts, D. A. & Shatz, C. J. Regulation of CNS synapses by neuronal MHC class I. Proc. Natl Acad. Sci. USA 104, 6828–6833 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Corriveau, R. A., Huh, G. S. & Shatz, C. J. Regulation of class I MHC gene expression in the developing and mature CNS by neural activity. Neuron 21, 505–520 (1998).

    Article  CAS  PubMed  Google Scholar 

  23. Huh, G. S. et al. Functional requirement for class I MHC in CNS development and plasticity. Science 290, 2155–2159 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Becker, J. W. & Reeke, G. N. Jr. Three-dimensional structure of β2-microglobulin. Proc. Natl Acad. Sci. USA 82, 4225–4229 (1985).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Eichner, T. & Radford, S. E. Understanding the complex mechanisms of β2-microglobulin amyloid assembly. FEBS J. 278, 3868–3883 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Leri, M. et al. Molecular insights into cell toxicity of a novel familial amyloidogenic variant of β2-microglobulin. J. Cell. Mol. Med. 20, 1443–1456 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Eichner, T. et al. Conformational conversion during amyloid formation at atomic resolution. Mol. Cell 41, 161–172 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Smith, L. K. et al. β2-Microglobulin is a systemic pro-aging factor that impairs cognitive function and neurogenesis. Nat. Med. 21, 932–937 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Gao, Y. et al. β2-Microglobulin functions as an endogenous NMDAR antagonist to impair synaptic function. Cell 186, 1026–1038 (2023).

    Article  CAS  PubMed  Google Scholar 

  30. Zalocusky, K. A. et al. Neuronal ApoE upregulates MHC-I expression to drive selective neurodegeneration in Alzheimer’s disease. Nat. Neurosci. 24, 786–798 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Carrette, O. et al. A panel of cerebrospinal fluid potential biomarkers for the diagnosis of Alzheimer’s disease. Proteomics 3, 1486–1494 (2003).

    Article  CAS  PubMed  Google Scholar 

  32. Kim, Y. et al. Plasma protein biomarker model for screening Alzheimer disease using multiple reaction monitoring-mass spectrometry. Sci. Rep. 12, 1282 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. McArthur, J. C. et al. The diagnostic utility of elevation in cerebrospinal fluid β2‐microglobulin in HIV‐1 dementia. Neurology 42, 1707–1712 (1992).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  35. Zeisel A, M.-M. A. B. et al. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347, 1138–1142 (2015).

    Article  PubMed  Google Scholar 

  36. Gowrishankar, S. et al. Massive accumulation of luminal protease-deficient axonal lysosomes at Alzheimer’s disease amyloid plaques. Proc. Natl Acad. Sci. USA 112, E3699–E3708 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Van Kaer, L., Ashton-Rickardt, P. G., Ploegh, H. L. & Tonegawa, S. TAP1 mutant mice are deficient in antigen presentation, surface class I molecules, and CD4-8+ T cells. Cell 71, 1205–1214 (1992).

    Article  PubMed  Google Scholar 

  38. Eggensperger, S. & Tampe, R. The transporter associated with antigen processing: a key player in adaptive immunity. J. Biol. Chem. 396, 1059–1072 (2015).

    Article  CAS  Google Scholar 

  39. Lewis, P. A. et al. Expression of BRI-amyloid β peptide fusion proteins: a novel method for specific high-level expression of amyloid β peptides. Biochem. Biophys. Acta 1537, 58–62 (2001).

    CAS  PubMed  Google Scholar 

  40. Meyer-Luehmann, M. et al. Exogenous induction of cerebral β-amyloidogenesis is governed by agent and host. Science 313, 1781–1784 (2006).

    Article  CAS  PubMed  Google Scholar 

  41. Southwell, A. L., Skotte, N. H., Bennett, C. F. & Hayden, M. R. Antisense oligonucleotide therapeutics for inherited neurodegenerative diseases. Trends Mol. Med. 18, 634–643 (2012).

    Article  CAS  PubMed  Google Scholar 

  42. Salazar-Gonzalez, J. F. et al. Relationship of plasma HIV-RNA levels and levels of TNF-α and immune activation products in HIV infection. Clin. Immunol. Immunopathol. 84, 36–45 (1997).

  43. Prentice, R. L., et al. Proteomic risk markers for coronary heart disease and stroke: Validation and mediation of randomized trial hormone therapy effects on these diseases. Genome Med. 5, 112 (2012).

  44. Honig, L. et al. Stroke and the risk of Alzheimer disease. Arch. Neurol. 60, 1707–1712 (2003).

    Article  PubMed  Google Scholar 

  45. Ohashi, K. Pathogenesis of β2-microglobulin amyloidosis. Pathol. Int. 51, 1–10 (2001).

    Article  CAS  PubMed  Google Scholar 

  46. Murray, A. M. Cognitive impairment in the aging dialysis and chronic kidney disease populations an occult burden. Adv. Chronic Kidney Dis. 15, 123–132 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Ren, B. et al. Fundamentals of cross-seeding of amyloid proteins: an introduction. J. Mater. Chem. B 7, 7267–7282 (2019).

    Article  CAS  PubMed  Google Scholar 

  48. Ardeniz, O. et al. β2-Microglobulin deficiency causes a complex immunodeficiency of the innate and adaptive immune system. J. Allergy Clin. Immunol. 136, 392–401 (2015).

    Article  CAS  PubMed  Google Scholar 

  49. Togo, T. et al. Occurrence of T cells in the brain of Alzheimer’s disease and other neurological diseases. J. Neuroimmunol. 124, 83–92 (2002).

    Article  CAS  PubMed  Google Scholar 

  50. 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).

    Article  CAS  PubMed  Google Scholar 

  51. Koller, B. H., Marrack, P., Kappler, J. W. & Smithies, O. Normal development of mice deficient in β2M, MHC class I proteins, and CD8+ T cells. Science 248, 1227–1230 (1990).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  53. Monsonego, A. et al. Aβ-induced meningoencephalitis is IFN-γ-dependent and is associated with T cell-dependent clearance of Aβ in a mouse model of Alzheimer’s disease. Proc. Natl Acad. Sci. USA 103, 5048–5053 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Floege, J. & Ketteler, M. β2-Microglobulin-derived amyloidosis: an update. Kidney Int. Suppl. 78, S164–S171 (2001).

    Article  CAS  PubMed  Google Scholar 

  55. Assem, M. et al. The impact of uremic toxins on cerebrovascular and cognitive disorders. Toxins 10, 303 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Messele, T. et al. Plasma levels of viro-immunological markers in HIV-infected and non-infected Ethiopians: correlation with cell surface activation markers. Clin. Immunol. 98, 212–219 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. Doecke, J. D. et al. Blood-based protein biomarkers for diagnosis of Alzheimer disease. Arch. Neurol. 69, 1318–1325 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Yu, Y. J. & Watts, R. J. Developing therapeutic antibodies for neurodegenerative disease. Neurotherapeutics 10, 459–472 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Fuller, J. P., Stavenhagen, J. B. & Teeling, J. L. New roles for Fc receptors in neurodegeneration—the impact on immunotherapy for Alzheimer’s disease. Front. Neurosci. 8, 235 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Xu, H. et al. Estrogen reduces neuronal generation of Alzheimer β-amyloid peptides. Nat. Med. 4, 447–451 (1998).

    Article  CAS  PubMed  Google Scholar 

  61. Zheng, Q. et al. Trisomy 21-induced dysregulation of microglial homeostasis in Alzheimer’s brains is mediated by USP25. Sci. Adv. 7, eabe1340 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Pan, L. et al. Tau accelerates α-synuclein aggregation and spreading in Parkinson’s disease. Brain 145, 3454–3471 (2022).

    Article  PubMed  Google Scholar 

  63. Zhang, S. et al. Mechanistic basis for receptor-mediated pathological α-synuclein fibril cell-to-cell transmission in Parkinson’s disease. Proc. Natl Acad. Sci. USA 118, e2011196118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Youmans, K. L. et al. Amyloid-β42 alters apolipoprotein E solubility in brains of mice with five familial AD mutations. J. Neurosci. Methods 196, 51–59 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. DeVos, S. L. & Miller, T. M. Antisense oligonucleotides: treating neurodegeneration at the level of RNA. Neurotherapeutics 10, 486–497 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Bennett, C. F. & Swayze, E. E. RNA targeting therapeutics: molecular mechanisms of antisense oligonucleotides as a therapeutic platform. Annu. Rev. Pharmacol. Toxicol. 50, 259–293 (2010).

    Article  CAS  PubMed  Google Scholar 

  67. DeVos, S. L. et al. Antisense reduction of tau in adult mice protects against seizures. J. Neurosci. 33, 12887–12897 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. McKay, R. A. et al. Characterization of a potent and specific class of antisense oligonucleotide inhibitor of human protein kinase C-α expression. J. Biol. Chem. 274, 1715–1722 (1999).

    Article  CAS  PubMed  Google Scholar 

  69. Cheruvallath, Z. S., Kumar, R. K., Rentel, C., Cole, D. L. & Ravikumar, V. T. Solid phase synthesis of phosphorothioate oligonucleotides utilizing diethyldithiocarbonate disulfide (DDD) as an efficient sulfur transfer reagent. Nucleosides Nucleotides Nucleic Acids 22, 461–468 (2003).

    Article  CAS  PubMed  Google Scholar 

  70. Palovics, R. et al. Molecular hallmarks of heterochronic parabiosis at single-cell resolution. Nature 603, 309–314 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Yang, C. et al. Parabiosis modeling: protocol, application and perspectives. Zool. Res. 42, 253–261 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank G. Fu, Y. Shen, C. Xiao and N. Xiao for sharing experimental resources. We thank Y. Zhao, L. Zhong, L. Yao, C. Wu, Q. Liu, X. You, J. Huang, B. Xie, Q. Deng, T. Guo, H. Zhang, S. Zhang and X. Sheng for technical assistance. This work was supported by National Natural Science Foundation of China (U21A20358, 81822014 and 31871077 to X.W.), the National Key R&D Program of China (2021YFA1101401 and STI2030-Major Projects-2021ZD0202400 to X.W.), National Natural Science Foundation of China (82271451 and 81701130 to Q.Z.; 81701349 to H.Z.; 81802823 to Y. Zhou), Natural Science Foundation of Fujian Province of China (2021J02004 and 2017J06021 to X.W.; 2018J01054 to Y. Zhou), Guangdong Basic and Applied Basic Research Foundation (2021B1515120081 to X.W.), Science Innovation 2030-Brain Science and Brain-Inspired Intelligence Technology Major Projects (2021ZD0201103 and 2021ZD0201803 to X.-X.Y.) and Fundamental Research Funds for the Chinese Central Universities (20720220052 to Q.Z.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, China

    Yini Zhao, Qiuyang Zheng, Yujuan Hong, Yue Gao, Maoju Lang, Hongfeng Zhang, Hong Luo, Xian Zhang, Hao Sun & Xin Wang

  2. Shenzhen Research Institute of Xiamen University, Shenzhen, China

    Yini Zhao, Qiuyang Zheng, Hongfeng Zhang & Xin Wang

  3. Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China

    Jiaojiao Hu & Cong Liu

  4. National Institute for Data Science in Health and Medicine, School of Medicine, Xiamen University, Xiamen, China

    Ying Zhou

  5. Department of Anatomy and Neurobiology, Central South University Xiangya Medical School, Changsha, China

    Xiao-Xin Yan

  6. Degenerative Diseases Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA

    Timothy Y. Huang

  7. Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China

    Yan-Jiang Wang

  8. Center for Brain Sciences, the First Affiliated Hospital of Xiamen University, Institute of Neuroscience, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Xiamen University, Xiamen, China

    Huaxi Xu

  9. Institute for Brain Science and Disease, Chongqing Medical University, Chongqing, China

    Huaxi Xu

Authors
  1. Yini Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qiuyang Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yujuan Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yue Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jiaojiao Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Maoju Lang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hongfeng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ying Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Hong Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Xian Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Hao Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Xiao-Xin Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Timothy Y. Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Yan-Jiang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Huaxi Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Cong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Xin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

X.W. conceived the study and designed the experiments. Y. Zhao performed most studies and data analyses. Y.H. performed two-photon microscopy and analyzed the data. J.H. and C.L. performed the BLI assay and analyzed the data. M.L. performed the ASO screening experiment. Q.Z., Y.G., H.Z., Y. Zhou, X.Z., H.L. and H.S. analyzed the data and contributed reagents, materials and analysis tools. Y.-J.W. and X.-X.Y. provided human brain or plasma samples. X.W. and Y. Zhao wrote the manuscript. T.Y.H., H.X. and C.L. edited the manuscript. X.W. supervised the project. All authors reviewed the manuscript.

Corresponding author

Correspondence to Xin Wang.

Ethics declarations

Competing interests

Y. Zhao, Q.Z., Y.G., M.L. and X.W. have filed a patent application based on this work. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Neuroscience thanks Adriano Aguzzi, Li Gan, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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 NF-κB pathway-mediated B2M overproduction in activated microglia.

a, Quantification of Aβ42 levels in human cortex by ELISA (AD, n = 27; control, n = 8; two-sided unpaired Mann Whitney test). b, c, Immunoblot (b) and quantification of B2M, APP and β-actin (as loading control) in the hippocampus from 3- to 15-month-old 5×FAD mice and WT mice (n = 3 mice per group; B2M: two-sided two-way ANOVA followed by Bonferroni’s multiple comparisons test; comparing each month with the 3-month-old WT). d, Strategy of humanized B2M knock-in (B2MKI/KI) mouse generation. e, Quantification of body weights of 2-month-old WT and B2MKI/KI mice (WT, n = 7 mice; B2MKI/KI, n = 8 mice; two-sided unpaired t-test). f, Representative immunostaining for microglia (Iba1), astrocytes (GFAP), neurons (TUJ1) and B2M (HA) in hippocampal CA1 region of 2-month-old B2MKI/KI mice (expressing human B2M with a C-terminal HA tag). g, Quantification of the percentages of double-positive cells in each cell type (microglia, n = 458 cells; astrocyte, n = 550 cells; neuron, n = 370 cells). h, Experimental schematic of B2m mRNA expression analysis in primary microglial cultures. i, Relative B2m mRNA expression levels in primary microglia under differing treatment conditions are shown in (h) (Control and oAβ, n = 3 biologically independent samples; LPS, n = 4 biologically independent samples; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test). j, Immunohistochemical analysis of B2M (anti-B2M antibody) and Aβ (thioflavin S) colocalization in 5×FAD mouse hippocampal sections. Similar results were observed in three independent experiments. The data represent means in (f) and mean ± s.e.m. in (a, c, g and i). The P values are indicated on the graphs. For detailed statistical information, see Source Data.

Source data

Extended Data Fig. 2 Overexpression of B2M accelerates amyloid deposition in the hippocampus of 5×FAD mice.

a, Schematic of the AAV viral vector expressing human B2M. b, Confocal imaging of AAV-injected hippocampus labeled with mCherry. Similar results were observed in two independent experiments. c, d, Immunoblot analysis of B2M-HA, APP and β-actin (as a loading control) in the hippocampus of AAV-injected WT and 5×FAD mice (n = 5 mice per group; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test). e-g, Representative immunostaining images (e) and quantification of total Aβ immunostained area (AAV-Ctrl, n = 5 mice; AAV-B2M, n = 6 mice; two-sided unpaired Mann Whitney test) (f) and amyloid plaque number (AAV-Ctrl, n = 5 mice; AAV-B2M, n = 6 mice; 0–20 μm, 20–40 μm and total: two-sided unpaired t-test; >40 μm: two-sided unpaired Mann Whitney test) (g) in hippocampal DG region of AAV-injected 5×FAD mice. h, Quantification of total Aβ immunostained area (AAV-Ctrl, n = 5 mice; AAV-B2M, n = 6 mice; two-sided unpaired t-test) and amyloid plaque number (AAV-Ctrl, n = 5 mice; AAV-B2M, n = 6 mice; 0–15 μm and 15–30 μm: two-sided unpaired t-test; >30 μm and total: two-sided unpaired Mann Whitney test) in hippocampal CA1 region of AAV-injected 5×FAD mice. i, Quantification of Aβ42 levels in the hippocampus of AAV-injected 5×FAD mice by ELISA (AAV-Ctrl, n = 5 mice; AAV-B2M, n = 6 mice; two-sided unpaired t-test). j, k, Representative immunostaining images (j) and quantification of Lamp1-positive dystrophic neurites in hippocampal DG region of AAV-injected 5×FAD mice (AAV-Ctrl, n = 5 mice; AAV-B2M, n = 6 mice; two-sided unpaired t-test) (k). The P values are indicated on the graphs: mean ± s.e.m. For detailed statistical information, see Source Data.

Source data

Extended Data Fig. 3 Elevation of B2M promotes spreading of amyloid pathology.

a, Schematic of B2M injection experiments. Bilateral guide cannulas were implanted into hippocampal DG region of 4-month-old 5×FAD mice. Mice were injected with purified B2M (2 μl, 1 μg/μl) or PBS (2 μl, vehicle) every 7 days (four times in total within 28 days). b, Schematic of amyloid spreading analysis. The site of hippocampal injection at bilateral sites is shown; images from sections were sequentially quantified at 120 μ m distance intervals relative to the injection site. c, Quantification of rostro-caudal spreading of amyloid pathology. Number of amyloid deposits in the hippocampus of B2M-injected 5×FAD mice displayed for each section (n = 5 mice; two-sided paired t-test). d, e, Representative immunostaining (d) and quantification of Lamp1-positive dystrophic neurites in the hippocampus of B2M-injected 5×FAD mice (n = 5 mice; two-sided paired t-test) (e). f, Schematic of the AAV viral vector expressing BRI-Aβ42 fusion protein. BRI can be cleaved by furin to release human Aβ42 peptides in the mouse brain. g, Immunohistochemical analysis of amyloid plaques in 5×FAD mouse cortex using B2M, MHC-I and Aβ (6E10) antibodies. A liver section from a WT mouse was used as a positive control for MHC-I staining. Similar results were observed in three independent experiments. The P values are indicated on the graphs: mean ± s.e.m. For detailed statistical information, see Source Data.

Source data

Extended Data Fig. 4 B2m deficiency ameliorates amyloid pathology in 5×FAD mice.

a, Quantification of 6E10-positive amyloid plaques in hippocampal CA1 region (n = 5 mice per group; 0–20 μm and 20–40 μm: two-sided unpaired t-test; >40 μm: 5×FAD versus 5×FAD; B2m+/−, two-sided unpaired t-test; 5×FAD versus 5×FAD; B2m−/− and 5×FAD; B2m+/− versus 5×FAD; B2m−/−, two-sided unpaired Mann Whitney test; Aβ plaque number: two-sided unpaired t-test; Aβ plaque area: two-sided unpaired t-test). b, Representative immunostaining of 6E10-positive amyloid plaques in the cortex of 6-month-old 5×FAD, 5×FAD; B2m+/− and 5×FAD; B2m−/− mice. c, d, Quantification of total Aβ immunostained area (n = 5 mice per group; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test) (c) and amyloid plaque number (n = 5 mice per group; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test) (d) in (b). e, Representative immunostaining of amyloid plaques in the hippocampus and cortex of 12-month-old 5×FAD and 5×FAD; B2m−/− mice. f-h, Quantification of amyloid plaques in hippocampal DG (5×FAD, n = 4 mice; 5×FAD; B2m−/−, n = 3 mice; two-sided unpaired t-test) (f) and CA1 (5×FAD, n = 4 mice; 5×FAD; B2m−/−, n = 3 mice; two-sided unpaired t-test) (g) region and the cortex (5×FAD, n = 4 mice; 5×FAD; B2m−/−, n = 3 mice; two-sided unpaired t-test) (h). i, Quantification of Aβ42 in the hippocampus from 12-month-old 5×FAD and 5×FAD; B2m−/− mice by ELISA (5×FAD, n = 4 mice; 5×FAD; B2m−/−, n = 3 mice; two-sided unpaired t-test). The P values are indicated on the graphs: mean ± s.e.m. For detailed statistical information, see Source Data.

Source data

Extended Data Fig. 5 B2m deficiency ameliorates the loss of dendritic spines and spreading of amyloid pathology in 5×FAD mice.

a, Immunoblot analysis of APP, APP-CTFs, APP processing- and Aβ degrading-enzymes in the cortex of 6- to 7-month-old B2m+/+, B2m+/−, 5×FAD and 5×FAD; B2m+/− mice. b, Quantification of APP, B2M, PS-NTF, BACE1, APP-CTF, ADAM17, IDE, NEP (n = 5 mice per genotype; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test for B2M, APP-CTF, ADAM17, BACE1, PS1-NTF and IDE; two-sided Kruskal–Wallis test followed by Dunn’s multiple comparisons test for APP and NEP) and β-actin (as loading control). c, Golgi staining and quantification of dendritic spines in hippocampal CA1 region of 6- to 7-month-old mice (the number of counted dendrites is indicated on the graphs, n = 4 mice per group; two-sided Kruskal–Wallis test followed by Dunn’s multiple comparisons test). d, Golgi staining and quantification of dendritic spines in hippocampal DG region of 6- to 7-month-old mice (the number of counted dendrites is indicated on the graphs, n = 4 mice per group; two-sided Kruskal–Wallis test followed by Dunn’s multiple comparisons test). e, f, Quantification of the rostro-caudal spreading of Aβ pathology. Number of amyloid deposits displayed for each section (n = 6 mice; two different lysates: two-sided paired t-test; lysate + IgG: for -3, -1, 2 and 3: two-sided paired t-test; for -2 and 1: two-sided Wilcoxon matched-pairs signed rank test). The P values are indicated on the graphs: mean ± s.e.m. For detailed statistical information, see Source Data.

Source data

Extended Data Fig. 6 B2m deficiency alters learning and memory-related transcriptional profiles in oAβ-injected mice.

a, Schematic of oAβ injection and RNAseq analysis. Two- to three-month-old WT and B2m−/− mice were ICV injected with oligomeric Aβ42 (oAβ) or PBS (Vehicle). Hippocampal tissues were dissected, and total RNA was isolated, purified and sequenced. n = 3 mice per group. b, Volcano plots with genes that were significantly downregulated (blue) or upregulated (red) in the hippocampus of oAβ-injected 2- to 3-month-old B2m−/− versus WT mice (fold change > 1.5, P value < 0.05) (two-tailed Wald test). c, GO analysis of upregulated genes in the oAβ-injected B2m−/− mouse hippocampus (hypergeometric test, qvalueCutoff = 0.05). d, GO analysis of downregulated genes in the oAβ-injected B2m−/− mouse hippocampus (hypergeometric test, qvalueCutoff = 0.05). e, Heatmap depicting upregulated genes in the oAβ-injected B2m−/− mouse hippocampus.

Source data

Extended Data Fig. 7 Hippocampal injection of an anti-B2M monoclonal antibody ameliorates neuropathology in 5×FAD and APP/PS1 mice.

a, Body weights of B2M/Control ASO-injected and non-injected 5×FAD; B2MKI/KI mice (n = 3 mice per group; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test). b, Quantification of 6E10-positive amyloid plaques in hippocampal CA1 region of antibody-injected 5×FAD mice (5×FAD + Iso-IgG, n = 5 mice; 5×FAD + Anti-B2M-IgG, n = 7 mice; two-sided unpaired t-test). c, d, Representative immunostaining images (c) and quantification of Lamp1-labeled dystrophic neurites in hippocampal DG region of 5×FAD mice injected with antibodies as indicated (5×FAD + Iso-IgG, n = 5 mice; 5×FAD + Anti-B2M-IgG, n = 7 mice; two-sided unpaired t-test) (d). e, Immunoblot and quantification of B2M, APP and β-actin (as a loading control) in the hippocampus of 9-month-old APP/PS1 and WT mice (n = 4 mice per group; two-sided unpaired t-test). f, Immunohistochemical analysis of B2M-Aβ coaggregation in the hippocampus of 12-month-old APP/PS1 mice using B2M (anti-B2M) and Aβ (6E10) antibodies. Similar results were observed in two independent experiments. g, Bilateral guide cannulas were implanted into hippocampal DG region of 7-month-old APP/PS1 mice. The mice received anti-B2M IgG (2 μl, 1 μg/μl) or iso-type IgG (2 μl, vehicle) injections every 7 days (six times in total within 42 days). h, i, Representative immunostaining images (h) and quantification of 6E10-positive amyloid plaques in the hippocampus of antibody-injected APP/PS1 mice (n = 5 mice; two-sided paired t-test) (i). j, k, Representative immunostaining (j) and quantification of Lamp1-positive dystrophic neurites in the hippocampus of antibody-injected APP/PS1 mice (n = 5 mice; two-sided paired t-test) (k). l, Quantification of anti-B2M antibody levels in the plasma of parabiotic or non-parabiotic B2m−/− mice (n = 4 mice per group; two-sided unpaired t-test). The P values are indicated on the graphs: mean ± s.e.m. For detailed statistical information, see Source Data.

Source data

Extended Data Fig. 8 B2M interacts with and promotes Aβ neurotoxicity.

a, Co-IP of endogenous Aβ42 and B2M in 12-month-old WT and 5×FAD mouse cortex. Similar results were observed in two independent experiments. b, c, Co-IP between synthetic Aβ42 and purified B2M. Similar results were observed in two independent experiments. d, e, Binding profiles of monomeric or oligomeric Aβ42 to different concentrations of B2M were determined by the BLI assay. The association and dissociation profiles are divided by the vertical dashed line. BLI was independently repeated three times. f, ThT fluorescence assay of purified B2M at various concentrations indicates that B2M does not self-aggregate. ThT assays were independently repeated three times for each condition, and the data represent mean values. g, CCK8 assay testing the cell viability of WT primary neurons exposed to B2M (0.2 μM), oAβ (2 μM) or oAβ + B2M (2 μM Aβ together with 0.2 μM B2M) for 24 hours (control and B2M n = 5 biologically independent samples, oAβ and Aβ + B2M n = 10 biologically independent samples; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test). h, Representative immunostaining of MAP2 in WT primary neurons treated with B2M (0.2 μM), oAβ (2 μM) or oAβ + B2M (2 μM Aβ together with 0.2 μM B2M) for 24 hours. i, j, Quantification of total neurite length (control, n = 22 cells; B2M, n = 23 cells; oAβ, n = 23 cells; Aβ + B2M, n = 22 cells; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test) (i) and branching (control, n = 29 cells; B2M, n = 23 cells; oAβ, n = 23 cells; Aβ + B2M, n = 23 cells; two-sided two-way ANOVA followed by Tukey’s multiple comparisons test; oAβ versus oAβ + B2M) (j) of the WT primary neurons with different treatments in (h). k, Experimental schematic of Il1b and Il6 mRNA expression analysis and microsphere uptake analysis in primary microglia. l, Representative immunostaining images showing microsphere uptake in primary microglia. m, Quantification of microsphere uptake in primary microglia under different treatment conditions (DMSO, n = 159 cells; oAβ, n = 153 cells; oAβ + B2M, n = 185 cells; two-sided Kruskal–Wallis test followed by Dunn’s multiple comparisons test), as shown in (k). n, Relative Il1b and Il6 mRNA expression levels in primary microglia under different treatment conditions (n = 4 biologically independent samples; two-sided one-way ANOVA followed by Tukey’s multiple comparisons test), as shown in (k). With the exception of those in (f) and (m), the data represent mean ± s.e.m. The P values are indicated on the graphs. For detailed statistical information, see Source Data.

Source data

Extended Data Fig. 9 The P3 peptide blocks B2M-Aβ coaggregation and neurotoxicity.

a, Immunoblot analysis of Aβ42 oligomer formation. The P3 peptide blocks B2M-induced Aβ42 oligomer formation (This assay was independently repeated seven times; two-sided unpaired Mann Whitney test). b, Co-IP between synthetic Aβ42 and P3 peptides. Similar results were observed in two independent experiments. c, Schematic of the truncated P3 peptides. Three P3-derived subfragments were designed and synthesized based on the P3 β-sheet structure: P3-1 (aa 51–60), P3-2 (aa 61–75) and P3-3 (aa 61–69). d, ThT fluorescence assay for protein aggregation. Truncated P3 peptides were incubated with Aβ42 in the presence of full-length B2M. ThT assays were independently repeated three times, and the data represent the mean values. e, Cell viability of primary neurons treated with the P3 peptide was determined by CCK8 assay. Cultured primary neurons from C57BL/6 mice were incubated with increasing concentrations of P3 or scrambled peptide for 24 hours (n = 5 biologically independent samples per group; two-sided unpaired t-test; Ctrl versus Scrambled peptide or P3 peptide). f, Schematic for the aggregates and peptide injection and Golgi staining assay. g, Schematic for peptide injection and behavioral analysis. h, MWM probe test results (n = 8 mice per group; Platform cross number: two-sided unpaired t-test; Time in quadrant: two-sided unpaired Mann Whitney test). i, Schematic for peptide injection and immunostaining analysis. j, Immunoblot analysis of B2M in the hippocampus of peptide-injected 5×FAD; B2MKI/KI mice (n = 5 mice per group; two-sided unpaired t-test). With the exception of the ThT fluorescence data in (d), the data represent mean ± s.e.m. The P values are indicated on the graphs. For detailed statistical information, see Source Data.

Source data

Extended Data Fig. 10 B2M is an essential factor for Aβ neurotoxicity and a novel target for therapeutic intervention in AD.

Elevation of B2M aggravates amyloid pathology independent of MHC-I, and coaggregation with B2M is essential for Aβ neurotoxicity. Importantly, both peripheral and brain B2M contribute to AD pathogenesis. Therapeutically, ASO or monoclonal antibody-mediated B2M depletion mitigates AD-associated neuropathology, and inhibiting B2M-Aβ coaggregation with a B2M-based blocking peptide ameliorates amyloid pathology and cognitive deficits in AD mice.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 and Tables 2 and 4–6 and titles for Supplementary Tables 1, 3 and 7 and Videos 1 and 2.

Reporting Summary

Supplementary Table 1

Mouse information for each experiment.

Supplementary Table 3

Information on the postmortem human brain samples.

Supplementary Table 7

Antibodies used in experiments.

Supplementary Data 1

Source data for Supplementary Fig. 1.

Supplementary Data 2

Source data for Supplementary Fig. 2.

Supplementary Video 1

Two-photo imaging for the characterization of β2M.

Supplementary Video 2

Two-photo imaging for the characterization of anti-β2M antibody.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 7

Statistical source data.

Source Data Fig. 8

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 4

Statistical source data.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 8

Statistical source data.

Source Data Extended Data Fig. 9

Statistical source data.

Unprocessed blots Fig. 1

Unprocessed western blots.

Unprocessed blots Fig. 4

Unprocessed western blots.

Unprocessed blots Fig. 5

Unprocessed western blots.

Unprocessed blots Fig. 6

Unprocessed western blots.

Unprocessed blots Fig. 7

Unprocessed western blots.

Unprocessed blots Extended Data Fig. 1

Unprocessed western blots.

Unprocessed blots Extended Data Fig. 2

Unprocessed western blots.

Unprocessed blots Extended Data Fig. 5

Unprocessed western blots.

Unprocessed blots Extended Data Fig. 7

Unprocessed western blots.

Unprocessed blots Extended Data Fig. 8

Unprocessed western blots.

Unprocessed blots Extended Data Fig. 9

Unprocessed western blots.

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

Zhao, Y., Zheng, Q., Hong, Y. et al. β2-Microglobulin coaggregates with Aβ and contributes to amyloid pathology and cognitive deficits in Alzheimer’s disease model mice. Nat Neurosci 26, 1170–1184 (2023). https://doi.org/10.1038/s41593-023-01352-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-023-01352-1

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