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Fibrin-targeting immunotherapy protects against neuroinflammation and neurodegeneration

Nature Immunology volume 19, pages 1212–1223 (2018)Cite this article

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Abstract

Activation of innate immunity and deposition of blood-derived fibrin in the central nervous system (CNS) occur in autoimmune and neurodegenerative diseases, including multiple sclerosis (MS) and Alzheimer’s disease (AD). However, the mechanisms that link disruption of the blood–brain barrier (BBB) to neurodegeneration are poorly understood, and exploration of fibrin as a therapeutic target has been limited by its beneficial clotting functions. Here we report the generation of monoclonal antibody 5B8, targeted against the cryptic fibrin epitope γ377–395, to selectively inhibit fibrin-induced inflammation and oxidative stress without interfering with clotting. 5B8 suppressed fibrin-induced nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activation and the expression of proinflammatory genes. In animal models of MS and AD, 5B8 entered the CNS and bound to parenchymal fibrin, and its therapeutic administration reduced the activation of innate immunity and neurodegeneration. Thus, fibrin-targeting immunotherapy inhibited autoimmunity- and amyloid-driven neurotoxicity and might have clinical benefit without globally suppressing innate immunity or interfering with coagulation in diverse neurological diseases.

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Fig. 1: Generation and characterization of monoclonal antibody 5B8, which targets the fibrin epitope γ377–395.
Fig. 2: Changes in gene expression induced by the treatment of fibrin-stimulated BMDMs with 5B8.
Fig. 3: 5B8 blocks fibrin-induced ROS production and axonal damage.
Fig. 4: 5B8 suppresses EAE and engages fibrin target.
Fig. 5: 5B8 inhibits microglial activation, monocyte recruitment and axonal damage in EAE.
Fig. 6: 5B8 target engagement in 5XFAD mice.
Fig. 7: 5B8 protects 5XFAD mice against neurodegeneration and inflammatory responses.
Fig. 8: 5B8 suppresses the complement–TYROBP microglial module in 5XFAD mice.

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Data availability

GEO data supporting the findings of this study have been deposited in the GEO depository under accession numbers GSE118920 and GSE118921. Networks are permanently referenced in two Wikipathways entries: TYROBP Causal Network (Mus musculus) (http://wikipathways.org/index.php?title=Pathway:WP3625&oldid=85694) and Microglia Pathogen Phagocytosis Pathway (Mus musculus) (http://wikipathways.org/index.php?title=Pathway:WP3626&oldid=85691). The authors declare that all other data supporting the findings of this study are available within the paper. Any additional data can be made available from the corresponding author upon request.

References

  1. Rivest, S. Regulation of innate immune responses in the brain. Nat. Rev. Immunol. 9, 429–439 (2009).

    Article  CAS  PubMed  Google Scholar 

  2. Ransohoff, R. M. & Brown, M. A. Innate immunity in the central nervous system. J. Clin. Invest. 122, 1164–1171 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Lassmann, H., van Horssen, J. & Mahad, D. Progressive multiple sclerosis: pathology and pathogenesis. Nat. Rev. Neurol. 8, 647–656 (2012).

    Article  CAS  PubMed  Google Scholar 

  4. Schuh, C. et al. Oxidative tissue injury in multiple sclerosis is only partly reflected in experimental disease models. Acta Neuropathol. 128, 247–266 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Heppner, F. L., Ransohoff, R. M. & Becher, B. Immune attack: the role of inflammation in Alzheimer disease. Nat. Rev. Neurosci. 16, 358–372 (2015).

    Article  CAS  PubMed  Google Scholar 

  6. Lassmann, H. Mechanisms of neurodegeneration shared between multiple sclerosis and Alzheimer’s disease. J. Neural Transm. (Vienna) 118, 747–752 (2011).

    Article  CAS  Google Scholar 

  7. Nikić, I. et al. A reversible form of axon damage in experimental autoimmune encephalomyelitis and multiple sclerosis. Nat. Med. 17, 495–499 (2011).

    Article  PubMed  Google Scholar 

  8. Chitnis, T. & Weiner, H. L. CNS inflammation and neurodegeneration. J. Clin. Invest. 127, 3577–3587 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Frischer, J. M. et al. The relation between inflammation and neurodegeneration in multiple sclerosis brains. Brain 132, 1175–1189 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Zhao, Z., Nelson, A. R., Betsholtz, C. & Zlokovic, B. V. Establishment and dysfunction of the blood-brain barrier. Cell 163, 1064–1078 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Petersen, M. A., Ryu, J. K. & Akassoglou, K. Fibrinogen in neurological diseases: mechanisms, imaging and therapeutics. Nat. Rev. Neurosci. 19, 283–301 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Davalos, D. & Akassoglou, K. Fibrinogen as a key regulator of inflammation in disease. Semin. Immunopathol. 34, 43–62 (2012).

    Article  CAS  PubMed  Google Scholar 

  13. Adams, R. A. et al. The fibrin-derived γ377-395 peptide inhibits microglia activation and suppresses relapsing paralysis in central nervous system autoimmune disease. J. Exp. Med. 204, 571–582 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ugarova, T. P. et al. Sequence γγ377-395(P2), but not γ190-202(P1), is the binding site for the alpha MI-domain of integrin αMβ2 in the γ C-domain of fibrinogen. Biochemistry 42, 9365–9373 (2003).

    Article  CAS  PubMed  Google Scholar 

  15. Davalos, D. et al. Fibrinogen-induced perivascular microglial clustering is required for the development of axonal damage in neuroinflammation. Nat. Commun. 3, 1227 (2012).

    Article  PubMed  Google Scholar 

  16. Ryu, J. K. et al. Blood coagulation protein fibrinogen promotes autoimmunity and demyelination via chemokine release and antigen presentation. Nat. Commun. 6, 8164 (2015).

    Article  PubMed  Google Scholar 

  17. Yates, R. L. et al. Fibrin(ogen) and neurodegeneration in the progressive multiple sclerosis cortex. Ann. Neurol. 82, 259–270 (2017).

    Article  CAS  PubMed  Google Scholar 

  18. Marik, C., Felts, P. A., Bauer, J., Lassmann, H. & Smith, K. J. Lesion genesis in a subset of patients with multiple sclerosis: a role for innate immunity? Brain 130, 2800–2815 (2007).

    Article  PubMed  Google Scholar 

  19. Lee, N. J. et al. Spatiotemporal distribution of fibrinogen in marmoset and human inflammatory demyelination. Brain 141, 1637–1649 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Strickland, S. Blood will out: vascular contributions to Alzheimer’s disease. J. Clin. Invest. 128, 556–563 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Nathan, C. & Cunningham-Bussel, A. Beyond oxidative stress: an immunologist’s guide to reactive oxygen species. Nat. Rev. Immunol. 13, 349–361 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fischer, M. T. et al. NADPH oxidase expression in active multiple sclerosis lesions in relation to oxidative tissue damage and mitochondrial injury. Brain 135, 886–899 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Shimohama, S. et al. Activation of NADPH oxidase in Alzheimer’s disease brains. Biochem. Biophys. Res. Commun. 273, 5–9 (2000).

    Article  CAS  PubMed  Google Scholar 

  24. Ma, M. W. et al. NADPH oxidase in brain injury and neurodegenerative disorders. Mol. Neurodegener. 12, 7 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Haslund-Vinding, J., McBean, G., Jaquet, V. & Vilhardt, F. NADPH oxidases in oxidant production by microglia: activating receptors, pharmacology and association with disease. Br. J. Pharmacol. 174, 1733–1749 (2017).

    Article  CAS  PubMed  Google Scholar 

  26. Han, M. H. et al. Proteomic analysis of active multiple sclerosis lesions reveals therapeutic targets. Nature 451, 1076–1081 (2008).

    Article  CAS  PubMed  Google Scholar 

  27. Davalos, D. et al. Early detection of thrombin activity in neuroinflammatory disease. Ann. Neurol. 75, 303–308 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Haider, L. et al. Oxidative damage in multiple sclerosis lesions. Brain 134, 1914–1924 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Cortes-Canteli, M., Mattei, L., Richards, A.T., Norris, E.H. & Strickland, S. Fibrin deposited in the Alzheimer’s disease brain promotes neuronal degeneration. Neurobiol. Aging. 36, 608–617 (2015).

    Article  CAS  PubMed  Google Scholar 

  30. DeKosky, S. T. & Scheff, S. W. Synapse loss in frontal cortex biopsies in Alzheimer’s disease: correlation with cognitive severity. Ann. Neurol. 27, 457–464 (1990).

    Article  CAS  PubMed  Google Scholar 

  31. Zhang, B. et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer’s disease. Cell 153, 707–720 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Shoeb, M. & Fang, M. C. Assessing bleeding risk in patients taking anticoagulants. J. Thromb. Thrombolysis 35, 312–319 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Mócsai, A. et al. Integrin signaling in neutrophils and macrophages uses adaptors containing immunoreceptor tyrosine-based activation motifs. Nat. Immunol. 7, 1326–1333 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Bedard, K. & Krause, K. H. The NOX family of ROS-generating NADPH oxidases: physiology and pathophysiology. Physiol. Rev. 87, 245–313 (2007).

    Article  CAS  PubMed  Google Scholar 

  35. Turnbull, I. R. & Colonna, M. Activating and inhibitory functions of DAP12. Nat. Rev. Immunol. 7, 155–161 (2007).

    Article  CAS  PubMed  Google Scholar 

  36. Park, L. et al. Scavenger receptor CD36 is essential for the cerebrovascular oxidative stress and neurovascular dysfunction induced by amyloid-β. Proc. Natl. Acad. Sci. USA 108, 5063–5068 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Cummings, J. Lessons learned from Alzheimer disease: clinical trials with negative outcomes. Clin. Transl. Sci. 11, 147–152 (2018).

    Article  PubMed  Google Scholar 

  38. Vemuri, P. et al. Vascular and amyloid pathologies are independent predictors of cognitive decline in normal elderly. Brain 138, 761–771 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Rabin, J. S. et al. Interactive associations of vascular risk and β-amyloid burden with cognitive decline in clinically normal elderly individuals: findings from the Harvard aging brain study. JAMA Neurol. 75, 1124–1131 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Miron, V. E. et al. M2 microglia and macrophages drive oligodendrocyte differentiation during CNS remyelination. Nat. Neurosci. 16, 1211–1218 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Petersen, M. A. et al. Fibrinogen activates BMP Signaling in oligodendrocyte progenitor cells and inhibits remyelination after vascular damage. Neuron 96, 1003–1012 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Oka, A., Belliveau, M. J., Rosenberg, P. A. & Volpe, J. J. Vulnerability of oligodendroglia to glutamate: pharmacology, mechanisms, and prevention. J. Neurosci. 13, 1441–1453 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Butovsky, O. et al. Identification of a unique TGF-β-dependent molecular and functional signature in microglia. Nat. Neurosci. 17, 131–143 (2014).

    Article  CAS  PubMed  Google Scholar 

  44. Ajami, B. et al. Single-cell mass cytometry reveals distinct populations of brain myeloid cells in mouse neuroinflammation and neurodegeneration models. Nat. Neurosci. 21, 541–551 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Keren-Shaul, H. et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell 169, 1276–1290.e17 (2017).

    Article  CAS  PubMed  Google Scholar 

  46. Mrdjen, D. et al. High-dimensional single-cell mapping of central nervous system immune cells reveals distinct myeloid subsets in health, aging, and disease. Immunity 48, 380–395 (2018).

    Article  CAS  PubMed  Google Scholar 

  47. Suh, T. T. et al. Resolution of spontaneous bleeding events but failure of pregnancy in fibrinogen-deficient mice. Genes Dev. 9, 2020–2033 (1995).

    Article  CAS  PubMed  Google Scholar 

  48. Flick, M. J. et al. Leukocyte engagement of fibrin(ogen) via the integrin receptor αMββ2/Mac-1 is critical for host inflammatory response in vivo. J. Clin. Invest. 113, 1596–1606 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Lak, M., Keihani, M., Elahi, F., Peyvandi, F. & Mannucci, P. M. Bleeding and thrombosis in 55 patients with inherited afibrinogenaemia. Br. J. Haematol. 107, 204–206 (1999).

    Article  CAS  PubMed  Google Scholar 

  50. Bugge, T. H. et al. Loss of fibrinogen rescues mice from the pleiotropic effects of plasminogen deficiency. Cell 87, 709–719 (1996).

    Article  CAS  PubMed  Google Scholar 

  51. Akassoglou, K., Yu, W.-M., Akpinar, P. & Strickland, S. Fibrin inhibits peripheral nerve remyelination by regulating Schwann cell differentiation. Neuron 33, 861–875 (2002).

    Article  CAS  PubMed  Google Scholar 

  52. Koseki-Kuno, S., Yamakawa, M., Dickneite, G. & Ichinose, A. Factor XIII A subunit-deficient mice developed severe uterine bleeding events and subsequent spontaneous miscarriages. Blood 102, 4410–4412 (2003).

    Article  CAS  PubMed  Google Scholar 

  53. Chen, R. & Doolittle, R. F. γ-γ cross-linking sites in human and bovine fibrin. Biochemistry 10, 4487–4491 (1971).

    CAS  PubMed  Google Scholar 

  54. Aleman, M. M. et al. Factor XIII activity mediates red blood cell retention in venous thrombi. J. Clin. Invest. 124, 3590–3600 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Jung, S. et al. Analysis of fractalkine receptor CX(3)CR1 function by targeted deletion and green fluorescent protein reporter gene insertion. Mol. Cell. Biol. 20, 4106–4114 (2000). Medline.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Feng, G. et al. Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron 28, 41–51 (2000).

    Article  CAS  PubMed  Google Scholar 

  57. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Jackson, S. H., Gallin, J. I. & Holland, S. M. The p47phox mouse knock-out model of chronic granulomatous disease. J. Exp. Med. 182, 751–758 (1995).

    Article  CAS  PubMed  Google Scholar 

  59. Saederup, N. et al. Selective chemokine receptor usage by central nervous system myeloid cells in CCR2-red fluorescent protein knock-in mice. PLoS One 5, e13693 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Jensen, M. R. et al. Structural basis for simvastatin competitive antagonism of complement receptor 3. J. Biol. Chem. 291, 16963–16976 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Abid, M. R., Spokes, K. C., Shih, S. C. & Aird, W. C. NADPH oxidase activity selectively modulates vascular endothelial growth factor signaling pathways. J. Biol. Chem. 282, 35373–35385 (2007).

    Article  CAS  PubMed  Google Scholar 

  62. Klunk, W. E. et al. Imaging Abeta plaques in living transgenic mice with multiphoton microscopy and methoxy-X04, a systemically administered Congo red derivative. J. Neuropathol. Exp. Neurol. 61, 797–805 (2002).

    Article  CAS  PubMed  Google Scholar 

  63. Kutmon, M. et al. WikiPathways: capturing the full diversity of pathway knowledge. Nucleic Acids Res. 44, D488–494 (2016).

    Article  CAS  PubMed  Google Scholar 

  64. Warde-Farley, D. et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 38, W214–220 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Gentleman, R. C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank I.F. Charo (Gladstone Institutes) for Ccr2RFP/RFP mice on a C57BL/6 background; J.L. Degen for advice and critical reading of the manuscript; S. Pintchovski, I. Kadiu, J. Palop and J. Egebjerg for discussions; B. Cabriga, R. Meza Acevedo, L. Ta and A. Williams for technical assistance; G. Maki for graphics; and G. Howard and K. Claiborne for editorial assistance. The Gladstone Center for In vivo Imaging Research was supported in part by grants from H. Lundbeck A/S, the S.D. Bechtel, Jr. Foundation, and the Conrad N. Hilton Foundation (17348 to K.A.). The microscopy studies were carried out in part at facilities adapted for this project at the National Center for Microscopy and Imaging Research, which is supported by grant P41 GM10341 (awarded to M.H.E.). Gladstone Institutes was supported by NIH/NCRR grant RR18928. The Mouse Pathology Core of the UCSF Helen Diller Family Comprehensive Cancer Center was supported by CA082103. J.K.R., D.D. and A.S.M. were supported by National Multiple Sclerosis Society (NMSS) Postdoctoral Fellowships; J.K.R. and D.D. were supported by Race to Erase MS Young Investigator Awards and American Heart Association (AHA) Scientist Development Grants; V.A.R. was supported by postdoctoral fellowships from AHA and NIH/NINDS F32 NS096920; A.S.M. was supported by NIAID T32AI733429 and NMSS FG-1708-28925; K.K.H. was supported by NSF pre-doctoral fellowship DGE-0648991/1144247; M.A.P. was supported by a NIH/NICHD K12-HD072222; L.M. was supported by a gift from the Dolby Family; S.S.Z. was supported by NIH R01 NS092835; R21 NS108159, NMSS RG1701-26628, RG 5179A10/2, the Weill Institute and the Maisin Foundation; and R.A.S was supported by NIH R01 NS081149. This work was also supported by grants to K.A. from NMSS (RG3782), H. Lundbeck A/S, the Conrad N. Hilton Foundation (17348), a gift from the Levine Family, and NIH/NINDS (R01 NS052189, R21 NS082976 and R35 NS097976).

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Author notes

  1. Dimitrios Davalos

    Present address: Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA

  2. These authors contributed equally: Victoria A. Rafalski, Anke Meyer-Franke.

Authors and Affiliations

  1. Gladstone Institutes, San Francisco, CA, USA

    Jae Kyu Ryu, Victoria A. Rafalski, Anke Meyer-Franke, Pamela E. Rios Coronado, Kim M. Baeten, Catherine Bedard, Kristina Hanspers, Sophia Bardehle, Andrew S. Mendiola, Dimitrios Davalos, Michael R. Machado, Justin P. Chan, Ioanna Plastira, Mark A. Petersen, Catriona Syme, Alexander R. Pico, Lennart Mucke, Stephen B. Freedman & Katerina Akassoglou

  2. Department of Pharmacology, University of California, San Diego, La Jolla, CA, USA

    Ryan A. Adams, Shoana L. Sikorski & Katerina Akassoglou

  3. Lundbeck Research USA, Paramus, NJ, USA

    Suresh B. Poda, Veena Menon, Stevin H. Zorn & Robert B. Nelson

  4. H. Lundbeck A/S, Copenhagen, Denmark

    Lars Østergaard Pedersen & Jeffrey B. Stavenhagen

  5. Institute of Molecular Biology and Biochemistry, Medical University Graz, Graz, Austria

    Ioanna Plastira

  6. Division of Neonatology, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA

    Mark A. Petersen

  7. Small Molecule Discovery Center, Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA

    Samuel J. Pfaff, Kenny K. Ang, Kenneth K. Hallenbeck & Michelle R. Arkin

  8. National Center for Microscopy and Imaging Research, University of California, San Diego, La Jolla, CA, USA

    Hiroyuki Hakozaki & Mark H. Ellisman

  9. Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA

    Mark H. Ellisman

  10. Neurology Service, San Francisco Veteran Affairs Medical Center, San Francisco, CA, USA

    Raymond A. Swanson

  11. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA

    Raymond A. Swanson, Scott S. Zamvil, Lennart Mucke & Katerina Akassoglou

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Contributions

J.K.R. performed and designed experiments and analyzed data; V.A.R. did two-photon imaging and AD studies; A.M.-F. and K.K.A. did microglia inhibition experiments; R.A.A., S.L.S. and C.B. did EAE experiments.; R.A.A., J.B.S. and R.B.N. produced antibodies; A.M.-F., S.B.P., L.O.P., V.M. and C.B. did antibody-binding ELISA; P.E.R.C. and M.R.M. did histology; K.M.B. did immunohistochemistry and coagulation assays; K.H. and A.R.P. performed the bioinformatics analysis; P.E.R.C., S.B., M.R.M., J.P.C. and M.A.P. did image analysis; A.S.M. performed qPCR array and flow cytometry; D.D. performed EAE studies; I.P. performed immunoblot analysis; S.J.P. and K.K.H. produced recombinant CD11b I domain; C.S., H.H., M.H.E., M.R.A. and R.B.N. analyzed data; R.A.S., S.S.Z., S.H.Z., L.M., and S.B.F. designed experiments; J.B.S. and R.B.N. designed experiments and analyzed data; K.A. conceived of the project, designed the study and analyzed data; and J.K.R. and K.A. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Katerina Akassoglou.

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Competing interests

H. Lundbeck A/S sponsored research in K.A.’s laboratory at the Gladstone Institutes. K.A. is a co-founder and scientific advisor of MedaRed and is an inventor on patents US7807645, US8569242, US8877195 and US8980836, covering fibrin antibodies, issued by the University of California. K.A. and J.K.R are co-inventors on patent US9669112 covering fibrin in vivo models, issued by Gladstone Institutes, and the Gladstone Institutes’ pending patent application US20160320370, covering in vitro fibrin assays. K.A., A.M.-F., M.R.A. and K.K.A. are co-inventors on the Gladstone Institutes’ and University of California’s pending patent application US20170003280, covering assays for inhibition of microglia activation. Their interests are managed by the Gladstone Institutes in accordance with its conflict-of-interest policy. J.B.S., R.B.N., S.B.P, L.O.P, V.M., S.H.Z. were employees of Lundbeck during the time the work was performed.

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Integrated supplementary information

Supplementary Figure 1 Identification and characterization of anti-γ377-395 antibodies.

Workflow diagram depicting the screening decision tree for the identification of fibrin-specific anti-inflammatory antibodies without adverse effects on blood coagulation. (b) Binding affinities to the γ377-395 peptide of antibodies 4E11 and 4F1 (generated against γ377-395) and 1E3 (generated against γ190-202) measured by chemiluminescence ELISA. Data are mean ± s.e.m. from n = 3 independent experiments for 4E11 and n = 4 independent experiments for 4F1 and 1E3. (c) ELISA binding of recombinant CD11b I-domain to immobilized fibrinogen or fibrin. Data are mean ± s.e.m. Data are representative from n = 2 independent experiments performed in duplicates with CD11b I-domain concentrations ranged from 0.03 to 55 µM with similar results. (d) Binding of 4E11, 4F1, and 1E3 to fibrin or fibrinogen measured by ELISA. Data are mean ± s.e.m. from n = 3 independent experiments. (e) Domain and species specificity of 5B8 revealed by competition binding assay. 5B8 was pre-incubated with human γ377-395, γ190-202 or mouse γ377-395, γ190-202 peptides. Human γ377-395 peptide was used for substrate binding in the ELISA. Data are mean ± s.e.m. from n = 4 independent experiments.

Supplementary Figure 2 Functional comparison of the anti-γ377-395 antibodies in blocking fibrin-stimulated activation of microglia.

(a) Inhibition of fibrin-induced microglia activation by the anti-γ377-395 antibodies 4E11, 4F1, and 5B8 and the anti-γ190-202 antibody 1E3. Microglia activation was quantified after fibrin stimulation in the presence of the indicated antibodies or IgG2b (endotoxin levels < 0.002 EU/µg) isotype control. Data are from one experiment (mean ± s.e.m. of triplicate wells). (b) Inhibition of fibrin-induced microglia activation by the F(ab) fragment of 5B8. Data are from one experiment representative of two independent experiments with similar results (mean ± s.e.m. of triplicate wells). (c) Inhibition of coated fibrin-induced microglia activation by 5B8. Data are from n = 7 independent experiments performed in octuplicates (mean ± s.e.m. of n = 7). ****P < 0.0001 by one-way ANOVA Tukey’s multiple comparisons. (d) Multiplex qPCR assay of 5B8- vs. IgG2b-treated primary rat microglia 4 h after fibrin D-dimer stimulation. Relative expression of differentially expressed pro-inflammatory genes Cxcl10, Cxcl11, Il1b, Il23a, Tlr1, and Tlr2 in fibrin D-dimer-stimulated microglia treated with 5B8 or IgG2b, measured by multiplex qPCR. Differentially expressed genes were defined as fold change ≥ 2,  P < 0.05 by two-tailed student t-test comparing unstimulated to D-dimer groups and then data were further analyzed by one-way ANOVA with Tukey’s multiple comparisons test. Data are mean ± s.e.m. from n = 3 independent experiments. **** P < 0.0001 (Cxcl10), * P = 0.0327 (Il1b), ** P = 0.0077 (Il23a, unstimulated vs. fibrin), ** P = 0.0089 (Il23a, unstimulated vs fibrin+IgG2b), ** P = 0.0015 (Tlr1, unstimulated vs. fibrin), * P = 0.0267 (Tlr1, unstimulated vs fibrin+IgG2b), ** P = 0.0042 (Tlr1, fibrin vs. fibrin+5B8), * P = 0.0109 (Tlr2, unstimulated vs fibrin), * P = 0.0162 (Tlr2, fibrin vs. fibrin+5B8). (e) Comparison of two anti-mouse IgG2b antibodies with different endotoxin levels (< 0.002 EU/μg and < 0.01 EU/μg) on morphologic microglia activation. Data are mean ± s.e.m from n = 2 independent experiments performed in duplicates for unstimulated control and fibrin or from one experiment performed in triplicates for IgG2b endotoxin < 0.002 EU/μg and duplicates for IgG2b endotoxin < 0.01 EU/μg. (f) Pharmacokinetic study of 5B8 in mouse plasma. Data are mean ± s.e.m. from n = 3 mice.

Supplementary Figure 3 Inhibition of fibrin interaction with CD11b-CD18 blocks fibrinogen-induced microglial activation and pro-inflammatory gene expression.

(a) Microglial activation 3 days after injection of artificial cerebrospinal fluid (ACSF) or fibrinogen in the corpus callosum of Cx3cr1GFP/+ mice treated with stereotactic i.c.v. injection of IgG2b or 5B8. ctx, cortex; cc, corpus callosum; dotted lines indicate corpus callosum. Scale bar, 250 μm. Quantification of GFP intensity. Date are mean ± s.e.m.; ACSF+IgG2b, n = 7 mice. Fibrinogen+IgG2b, n = 5 mice. Fibrinogen+5B8, n = 5 mice. * P = 0.0178 by one-way ANOVA with Bonferroni multiple comparisons test. (b) Gene expression analysis of Cxcl10 and Il12b in the corpus callosum of mice treated with IgG2b or 5B8 at 12 h after injection of ACSF or fibrinogen. Data are mean ± s.e.m.; n = 7 mice per group for Cxcl10 and n = 4 mice per group for Il-12b expression analysis. * P = 0.0221 (Cxcl10), * P = 0.0287 (Il12b) by one-way ANOVA with Bonferroni multiple comparisons test. (c) Quantification of microglial activation in the corpus callosum 7 days after injection of fibrinogen in the corpus callosum of Cx3cr1GFP/+ mice treated with stereotactic i.c.v. injection of the F(ab) fragment of 5B8 or vehicle (PBS) (left). Date are mean ± s.e.m.; ACSF+PBS, n = 6 mice. Fibrinogen+PBS, n = 5 mice. Fibrinogen+F(ab), n = 6 mice. * P = 0.0272 by one-way ANOVA with Bonferroni multiple comparisons test. Cxcl10 RNA levels in the corpus callosum of mice treated with the F(ab) fragment of 5B8 or PBS 12 h after the injection of ACSF or fibrinogen. Date are mean ± s.e.m.; ACSF+PBS, n = 8 mice. Fibrinogen+PBS, n = 9 mice. Fibrinogen+F(ab), n = 6 mice. * P = 0.0423 by one-way ANOVA with Bonferroni multiple comparisons test.

Supplementary Figure 4 Fibrin-induced ROS release in macrophages is mediated by CD11b-CD18.

(a) ROS production in fibrin-stimulated BMDMs determined by DHE assay. The anti-CD11b neutralizing antibody M1/70 reduced ROS production in fibrin-stimulated BMDMs. Rat IgG2b was used as an isotype control. A.U., arbitrary units. Data are mean ± s.e.m. from n = 4 independent experiments. * P = 0.0319 by one-way ANOVA with Bonferroni multiple comparisons test. (b) Cell density analysis of fibrin-treated BMDMs. Untreated control and fibrin-treated BMDMs analyzed for cell density. Number of DAPI+ cell nuclei per 40x field after 24 h of fibrin treatment in the presence of 5B8 or IgG2b. Data are mean ± s.e.m. from n = 3 independent experiments.

Supplementary Figure 5 5B8 inhibits accumulation of immune cells, microglial activation, and demyelination in EAE.

(a) Hematoxylin-eosin staining and immunostaining for myelin basic protein (MBP) in spinal cord sections of PLP139-151 EAE mice treated with 5B8 or IgG2b. Scale bars, 200 μm. Data are mean ± s.e.m.; ** P = 0.0019 (top, n = 8 per group), *** P = 0.0003 (bottom; n = 8 IgG2b and n = 7 5B8) by two-tailed Mann-Whitney test (b) Iba-1 immunostaining of spinal cord sections from mice with TH1 cell-induced EAE treated with 5B8 or IgG2b. Scale bar, 150 μm. Data are mean ± s.e.m.; n = 8 (IgG2b) and 15 mice (5B8). * P = 0.0194 two-tailed Mann-Whitney test (c) Correlated histology using SMI-32, a marker of axonal damage, performed in the same spinal cord area in EAE-challenged mice after 2 daily i.v. injections of the superoxide indicator dihydroethidium (DHE) at the peak of EAE. (n = 12, R2 = 0.4612, P = 0.0170; association was determined by Pearson correlation). Scale bar, 100 μm.

Supplementary Figure 6 Flow cytometry analysis on splenocytes from PLP139-151-EAE mice treated with IgG2b or 5B8 antibody.

(a) Splenocytes from mice treated with IgG2b or 5B8 mice were stained for CD4+, CD8+, B220+ (Gated on CD45+), Ly6G+, CD11c+ (Gated on CD45+CD11b+), and CD45+CD11b+ (Gated on CD11c-Ly6G-) cells. Data are mean ± s.e.m. from n = 5 mice per group; CD4+ T cells P = 0.8413, CD8+ T cells P = 0.4048, B220+ B cells P = 0.0556, Ly6G+ cells * P = 0.0317, CD11c+ cells P = 0.6905, and CD45+CD11b+ cells P = 0.3095 (two-tailed Mann Whitney test). (b) Splenocytes were stimulated with cell stimulation cocktail for 4 h and analyzed for IL-17A– and IFN-γ–expressing CD4+ T cells by flow cytometry. The data shown were gated on CD4+ splenocytes. Data are mean ± s.e.m. from n = 5 mice per group; CD4+IL-17+ T cells (%) P = 0.6905, CD4+IL-17+ T cells (#) P = 0.8413, CD4+IFN-γ+ T cells (%) P = 0.0952, and CD4+IFN-γ+ T cells (#) P = 0.0556 (two-tailed Mann Whitney test).

Supplementary Figure 7 Fibrin(ogen) deposition and 5B8 in vivo target engagement in 5XFAD mice.

(a) Fibrin(ogen) deposits (red) and activation of CD11b+ microglia (green) near fluorescent Aβ probe methoxy-X04-positive Aβ plaques (blue) in cortical brain sections of 5-month-old 5XFAD mice were detected by immunostaining with antibodies against CD11b and fibrinogen. Non-transgenic littermates were used as controls. Scale bars, 50 μm. n = 4 mice 3–5 months old. Representative images are shown. (b) 5B8 in vivo target engagement in the brain of 5XFAD mice. Brain sections of 5XFAD or wild-type (WT) i.p.-injected with biotinylated 5B8 and methoxy-X04-detecting Aβ plaques (blue) were stained with Cy3-streptavidin (red) and anti-fibrin(ogen) (green). Scale bars, 50 μm. n = 3 mice. Representative images are shown.

Supplementary Figure 8 Analysis of cortical amyloid load, macrophage infiltration, and cellular network of 5B8-downregulated genes in 5XFAD mice.

(a) Immunostaining for Aβ (green) of brain sections of 5XFAD mice injected with methoxy-04 (blue) treated with 5B8 or IgG2b for 2 months from 3.5 months of age to 5.5 months of age. Quantification of co-labeled amyloid plaques in the neocortex. Scale bar, 70 μm. Data are mean ± s.e.m.; n = 7 IgG2b-treated and n = 9 5B8-treated 5XFAD mice. P = 0.1142 by two-tailed Mann-Whitney test n.s., not significant. (b) Mac-2+ macrophages around Methoxy-X04+ plaques in the cortices of 5XFAD mice treated with IgG2b or 5B8 at 5.5 months of age. Data are presented as mean ± s.e.m.; n = 7 IgG2b-treated and n = 9 5B8-treated 5XFAD mice. P = 0.5169 by two-tailed Mann-Whitney test. n.s., not significant. (c) A mouse model of microglia phagocytosis pathway was constructed based on Zhang et al31. Complement C1q or immunoglobulin (IgG) binds to microglia complement receptors (for example, ITGAM/ITGB2) or Fc-receptors (for example, FCGR1) that signal via the immunoreceptor tyrosine-based activation motif (ITAM)-containing adaptor molecules TYROBP or FCER1G, respectively. Alternatively, classical innate immune receptors (for example, TREM2) require the interaction with TYROBP for further signaling. This pathway was converted from the original human pathway to mouse. This pathway was annotated to indicate cortical gene expression regulation by 5B8 administration in 5XFAD mice compared to IgG2b control. Gene nodes are colored with yellow-blue gradient to indicate degree of log2 fold change in gene expression between 5B8 and IgG2b control. Red border intensity and border width indicate statistical significance of P <= 0.05 (two-tailed moderated t-test).

Supplementary Figure 9 Uncropped western blots for Fig. 3b.

Black dotted lines indicate regions that were cropped for the figures.

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Ryu, J.K., Rafalski, V.A., Meyer-Franke, A. et al. Fibrin-targeting immunotherapy protects against neuroinflammation and neurodegeneration. Nat Immunol 19, 1212–1223 (2018). https://doi.org/10.1038/s41590-018-0232-x

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