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CNS fibroblasts form a fibrotic scar in response to immune cell infiltration

Abstract

Fibrosis is a common pathological response to inflammation in many peripheral tissues and can prevent tissue regeneration and repair. Here, we identified persistent fibrotic scarring in the CNS following immune cell infiltration in the experimental autoimmune encephalomyelitis (EAE) mouse model of multiple sclerosis. Using lineage tracing and single-cell sequencing in EAE, we determined that the majority of the fibrotic scar is derived from proliferative CNS fibroblasts, not pericytes or infiltrating bone marrow-derived cells. Ablating proliferating fibrotic cells using cell-specific expression of herpes thymidine kinase led to an increase in oligodendrocyte lineage cells within the inflammatory lesions and a reduction in motor disability. We further identified that interferon-gamma pathway genes are enriched in CNS fibrotic cells, and the fibrotic cell-specific deletion of Ifngr1 resulted in reduced fibrotic scarring in EAE. These data delineate a framework for understanding the CNS fibrotic response.

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Fig. 1: Fibrotic scar formation occurs in EAE lesions.
Fig. 2: Scar-forming cells arise from cells that produce collagen at rest and not from mural cells.
Fig. 3: Scar-forming cells have the transcriptional profile of fibroblasts at the single-cell level.
Fig. 4: Reducing fibrotic scar formation reduces disease severity in EAE.
Fig. 5: Fibrotic cells upregulate interferon-gamma pathway genes in EAE.
Fig. 6: Interferon-gamma signaling regulates scar formation following neuroinflammation.

Data availability

All RNA-seq and single-cell sequencing raw and processed data files have been uploaded to the Gene Expression Omnibus and can be accessed using the following accession codes: GSE135186 for single-cell transcriptional profile of Col1a1-GFP+ cells in healthy and EAE samples; GSE135044 for transcriptional profile of Col1a1-GFP+ CNS cells in healthy and EAE samples; and GSE135185 for single-cell transcriptional profile of a mouse spinal cord in EAE.

References

  1. Bataller, R. & Brenner, D. A. Liver fibrosis. J. Clin. Invest. 115, 209–218 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Lee, S. B. & Kalluri, R. Mechanistic connection between inflammation and fibrosis. Kidney Int. Suppl. https://doi.org/10.1038/ki.2010.418 (2010).

  3. Travers, J. G., Kamal, F. A., Robbins, J., Yutzey, K. E. & Blaxall, B. C. Cardiac fibrosis: the fibroblast awakens. Circ. Res. 118, 1021–1040 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Lederer, D. J. & Martinez, F. J. Idiopathic pulmonary fibrosis. N. Engl. J. Med. 378, 1811–1823 (2018).

    CAS  PubMed  Google Scholar 

  5. Mack, M. Inflammation and fibrosis. Matrix Biol. 68-69, 106–121 (2018).

    CAS  PubMed  Google Scholar 

  6. Wynn, T. A. Cellular and molecular mechanisms of fibrosis. J. Pathol. 214, 199–210 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Rockey, D. C., Bell, P. D. & Hill, J. A. Fibrosis—a common pathway to organ injury and failure. N. Engl. J. Med. 372, 1138–1149 (2015).

    CAS  PubMed  Google Scholar 

  8. Fernández-Klett, F. & Priller, J. The fibrotic scar in neurological disorders. Brain Pathol. 24, 404–413 (2014).

    PubMed  PubMed Central  Google Scholar 

  9. O’Shea, T. M., Burda, J. E. & Sofroniew, M. V. Cell biology of spinal cord injury and repair. J. Clin. Invest. 127, 3259–3270 (2017).

    PubMed  PubMed Central  Google Scholar 

  10. Kawano, H. et al. Role of the lesion scar in the response to damage and repair of the central nervous system. Cell Tissue Res. 349, 169–180 (2012).

    PubMed  PubMed Central  Google Scholar 

  11. Cregg, J. M. et al. Functional regeneration beyond the glial scar. Exp. Neurol. 253, 197–207 (2014).

    PubMed  Google Scholar 

  12. Faulkner, J. R. et al. Reactive astrocytes protect tissue and preserve function after spinal cord injury. J. Neurosci. 24, 2143–2155 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Yiu, G. & He, Z. Glial inhibition of CNS axon regeneration. Nat. Rev. Neurosci. 7, 617–627 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Anderson, M. A. et al. Astrocyte scar formation aids central nervous system axon regeneration. Nature 532, 195–200 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Brazda, N. & Müller, H. W. Pharmacological modification of the extracellular matrix to promote regeneration of the injured brain and spinal cord. Prog. Brain Res. 175, 269–281 (2009).

    CAS  PubMed  Google Scholar 

  16. Göritz, C. et al. A pericyte origin of spinal cord scar tissue. Science 333, 238–242 (2011).

  17. Dias, D. O. & Göritz, C. Fibrotic scarring following lesions to the central nervous system. Matrix Biol. https://doi.org/10.1016/j.matbio.2018.02.009 (2018).

  18. Hellal, F. et al. Microtubule stabilization reduces scarring and causes axon regeneration after spinal cord injury. Science 331, 928–931 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Yoshioka, N., Hisanaga, S.-I. & Kawano, H. Suppression of fibrotic scar formation promotes axonal regeneration without disturbing blood–brain barrier repair and withdrawal of leukocytes after traumatic brain injury. J. Comp. Neurol. 518, 3867–3881 (2010).

    PubMed  Google Scholar 

  20. Zhu, Y. et al. Hematogenous macrophage depletion reduces the fibrotic scar and increases axonal growth after spinal cord injury. Neurobiol. Dis. 74, 114–125 (2015).

    CAS  PubMed  Google Scholar 

  21. Dias, D. O. et al. Reducing pericyte-derived scarring promotes recovery after spinal cord injury. Cell 173, 153–165 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Yahn, S. L. et al. Fibrotic scar after experimental autoimmune encephalomyelitis inhibits oligodendrocyte differentiation. Neurobiol. Dis. 134, 104674 (2020).

    CAS  PubMed  Google Scholar 

  23. van Horssen, J., Bö, L., Dijkstra, C. D. & de Vries, H. E. Extensive extracellular matrix depositions in active multiple sclerosis lesions. Neurobiol. Dis. 24, 484–491 (2006).

    PubMed  Google Scholar 

  24. van Horssen, J., Dijkstra, C. D. & de Vries, H. E. The extracellular matrix in multiple sclerosis pathology. J. Neurochem. 103, 1293–1301 (2007).

    PubMed  Google Scholar 

  25. Mohan, H. et al. Extracellular matrix in multiple sclerosis lesions: fibrillar collagens, biglycan and decorin are upregulated and associated with infiltrating immune cells. Brain Pathol. https://doi.org/10.1111/j.1750-3639.2010.00399.x (2010).

  26. Soderblom, C. et al. Perivascular fibroblasts form the fibrotic scar after contusive spinal cord injury. J. Neurosci. 33, 13882–13887 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Kelly, K. K. et al. Col1a1+ perivascular cells in the brain are a source of retinoic acid following stroke. BMC Neurosci. 17, 49–49 (2016).

    PubMed  PubMed Central  Google Scholar 

  28. Birbrair, A. et al. Type-1 pericytes accumulate after tissue injury and produce collagen in an organ-dependent manner. Stem Cell Res. Ther. 5, 122 (2014).

    PubMed  PubMed Central  Google Scholar 

  29. Guimarães-Camboa, N. et al. Pericytes of multiple organs do not behave as mesenchymal stem cells in vivo. Cell Stem Cell 20, 345–359 (2017).

    PubMed  PubMed Central  Google Scholar 

  30. Vanlandewijck, M. et al. A molecular atlas of cell types and zonation in the brain vasculature. Nature https://doi.org/10.1038/nature25739 (2018).

  31. Muhl, L. et al. Single-cell analysis uncovers fibroblast heterogeneity and criteria for fibroblast and mural cell identification and discrimination. Nat. Commun. 11, 3953 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Aktas, O., Küry, P., Kieseier, B. & Hartung, H. P. Fingolimod is a potential novel therapy for multiple sclerosis. Nat. Rev. Neurol. 6, 373–382 (2010).

    CAS  PubMed  Google Scholar 

  33. Chun, J. & Hartung, H.-P. Mechanism of action of oral fingolimod (FTY720) in multiple sclerosis. Clin. Neuropharmacol. 33, 91–101 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Aran, D. et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat. Immunol. 20, 163–172 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Xie, T. et al. Single-cell deconvolution of fibroblast heterogeneity in mouse pulmonary fibrosis. Cell Rep. 22, 3625–3640 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Ramachandran, A. et al. FosB regulates stretch-induced expression of extracellular matrix proteins in smooth muscle. Am. J. Pathol. 179, 2977–2989 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Chen, Y.-T., Levasseur, R., Vaishnav, S., Karsenty, G. & Bradley, A. Bigenic Cre/loxP, puΔtk conditional genetic ablation. Nucleic Acids Res. 32, e161 (2004).

    PubMed  PubMed Central  Google Scholar 

  38. Voskuhl, R. R. et al. Reactive astrocytes form scar-like perivascular barriers to leukocytes during adaptive immune inflammation of the CNS. J. Neurosci. 29, 11511–11522 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Tsai, H. H. et al. Oligodendrocyte precursors migrate along vasculature in the developing nervous system. Science 351, 379–384 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Schroder, K., Hertzog, P. J., Ravasi, T. & Hume, D. A. Interferon-gamma: an overview of signals, mechanisms and functions. J. Leukoc. Biol. 75, 163–189 (2004).

    CAS  PubMed  Google Scholar 

  41. Saha, B., Jyothi Prasanna, S., Chandrasekar, B. & Nandi, D. Gene modulation and immunoregulatory roles of IFN-γ. Cytokine 50, 1–14 (2010).

    CAS  PubMed  Google Scholar 

  42. Rawlings, J. S., Rosler, K. M. & Harrison, D. A. The JAK/STAT signaling pathway. J. Cell Sci. 117, 1281–1283 (2004).

    CAS  PubMed  Google Scholar 

  43. Oldroyd, S. D., Thomas, G. L., Gabbiani, G. & El Nahas, A. M. Interferon gamma inhibits experimental renal fibrosis. Kidney Int. 56, 2116–2127 (1999).

    CAS  PubMed  Google Scholar 

  44. Chen, E. S., Greenlee, B. M., Wills-Karp, M. & Moller, D. R. Attenuation of lung inflammation and fibrosis in interferon-gamma-deficient mice after intratracheal bleomycin. Am. J. Respir. Cell Mol. Biol. 24, 545–555 (2001).

    CAS  PubMed  Google Scholar 

  45. Kim, J. H. et al. Natural killer T cells attenuate bleomycin-induced pulmonary fibrosis by producing interferon-gamma. Am. J. Pathol. 167, 1231–1241 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. King, T. E. et al. Effect of interferon gamma-1b on survival in patients with idiopathic pulmonary fibrosis (INSPIRE): a multicentre, randomised, placebo-controlled trial. Lancet 374, 222–228 (2009).

    CAS  PubMed  Google Scholar 

  47. Wang, L., Li, J. & Li, D. Losartan reduces myocardial interstitial fibrosis in diabetic cardiomyopathy rats by inhibiting JAK/STAT signaling pathway. Int J. Clin. Exp. Pathol. 8, 466–473 (2015).

    PubMed  PubMed Central  Google Scholar 

  48. Lin, W. et al. Interferon gamma inhibits central nervous system remyelination through a process modulated by endoplasmic reticulum stress. Brain 129, 1306–1318 (2006).

    PubMed  Google Scholar 

  49. Zhou, T. et al. Microvascular endothelial cells engulf myelin debris and promote macrophage recruitment and fibrosis after neural injury. Nat. Neurosci. https://doi.org/10.1038/s41593-018-0324-9 (2019).

  50. Burgy, O. & Königshoff, M. The WNT signaling pathways in wound healing and fibrosis. Matrix Biol. 68-69, 67–80 (2018).

    CAS  PubMed  Google Scholar 

  51. Wendling, O., Bornert, J. M., Chambon, P. & Metzger, D. Efficient temporally controlled targeted mutagenesis in smooth muscle cells of the adult mouse. Genesis 47, 14–18 (2009).

    CAS  PubMed  Google Scholar 

  52. Niu, J. et al. Aberrant oligodendroglial-vascular interactions disrupt the blood–brain barrier, triggering CNS inflammation. Nat. Neurosci. 22, 709–718 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol. 20, 296 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Heng, T. S. P. et al. The Immunological Genome Project: networks of gene expression in immune cells. Nat. Immunol. 9, 1091–1094 (2008).

    CAS  PubMed  Google Scholar 

  56. Mei, F. et al. Micropillar arrays as a high-throughput screening platform for therapeutics in multiple sclerosis. Nat. Med. 20, 954–960 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank K. Jepsen and the UCSD Institute of Genomic Medicine Genomics center, T. Lambardo and the UCSD Veterans Hospital Flow Cytometry Core, Y. Jones and the CMM UCSD Electron Microscopy Core and J. Santini and M. Erb at the UCSD Microscopy Core. We thank D. Brenner (UCSD Health Sciences) for kindly supplying the Col1a1-GFP mice. R.D. is funded by National Institutes of Health (NIH)/National Institute of Neurological Disorders and Stroke (NINDS) awards (R01 NS091281, R01 NS103844), a National Multiple Sclerosis Society grant and the UCSF Program for Breakthrough Biomedical Science. C.E.D. is funded by the UCSD Graduate Training Program in Cellular and Molecular Pharmacology through an institutional training grant from the National Institute of General Medical Sciences (T32 GM007752) and an NIH/NINDS award (F31 NS108651). R.D. and T.A. are funded by NIH/NINDS R01 NS119615. T.A. is funded by NIH/NINDS grant no. 5K08NS096192. B.P. is funded by NIH/NINDS grant no. R01 NS034939. The UCSD Microscopy Core is funded by NINDS grant no. NS047101.

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Authors and Affiliations

Authors

Contributions

C.E.D., T.A. and R.D. designed experiments and wrote the manuscript. C.E.D. performed and analyzed lineage tracing, single-cell and bulk RNA-seq, fibrosis reduction and IFN-γ experiments, and performed immunostaining and microscopy on EAE spinal cords. D.A. analyzed single-cell sequencing data. E.A.H. quantified the location of Col1a1-GFP+ cells in healthy and disease samples. R.N.S. analyzed fibrosis reduction experiments. K.K.H. performed and analyzed OPC in vitro experiments. L.P quantified the number of pericytes and immune cells in lesions over time. Y.C. and B.P. performed cuprizone experiments. T.A., C.O.L. and K.M.C. performed and analyzed bone marrow transplant and lineage tracing experiments. G.A.W. analyzed RNA-seq experiments, and S.P.J.F performed LPC surgeries.

Corresponding authors

Correspondence to Thomas D. Arnold or Richard Daneman.

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The authors declare no competing interests.

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Peer review information Nature Neuroscience thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Col1a1-GFP cell localization in health and following EAE.

a, Analysis of the number of Col1a1-GFP+ cells per total vascular length and smooth muscle actin (SMA) + vascular length in different CNS regions in healthy adult mice. CP = choroid plexus, SC = spinal cord white or grey matter, ± s.e.m., n = 4, Col1a1-GFP mice. b-d, Spinal cord sections from wild type mice in health or with EAE at 2, 5 or 10 days PSO were stained with Col1 (red), DAPI (blue) and CD11b (b, green), GFAP (c, green), or CD4 (d, green) Scale bars = 100 µm. e, Light sheet microscopy image of a Col1a1-GFP mouse in health (left) and one with EAE (right) 10 days PSO perfused with tomato lectin and optically cleared, scale bars = 200 µm. f, Confocal microscopy images of Col1a1-GFP spinal cords from health (left) and EAE (right) stained for CD31 in red, scale bars = 10 µm.

Extended Data Fig. 2 Fibrotic scarring is present in the LPC, but not cuprizone, model of demyelination.

a, Spinal cord sections from mice either 5, 7, or 14 days post LPC injection into the spinal cord were stained for either Col1 (green) and FluoroMyelin (red) or myelin basic protein (MBP) (green) and Cd11b (red). b, Brain sections in the area of the corpus callosum from GFAP/tTA;TRE/IFN-γ mice following cuprizone administration. GFAP/tTA;TRE/IFN-γ mice received doxycycline starting from birth, and half of the mice were taken off of doxycycline at 6 weeks of age (-dox) to induce the expression of IFN-γ in the CNS. Both the +dox and -dox groups were divided into two groups. The first group (3 wk) was given cuprizone for 3 weeks and then analyzed at the end of the 3 week period. The second group (8 wk) was given cuprizone for 5 weeks and then analyzed 3 weeks after completion of the cuprizone administration. All brains were stained for either Col1 (green) and FluoroMyelin (red) or myelin basic protein (MBP) (green) and Cd11b (red). Scale bar = 100 µM. c, Quantification of the proportion of the demyelinated area that is Col1+ from mice 7 days post LPC injection (n = 4) or mice 3 weeks post cuprizone administration with and without doxycycline (n = 3 each), ± s.e.m.

Extended Data Fig. 3 Col1a2CreERT and NG2CreERTM reporter expression.

Spinal cords of Col1a2CreERT;Rosa-tdTomato (a) or NG2CreERTM;Rosa-tdTomato (b) mice in health or EAE 10 d PSO were stained with CD31 in green and DAPI in blue. Scale bars = 100 µm. c, Spinal cords of Col1a2CreERT;Rosa-tdTomato;Col1a1-GFP mice in health or 10 days EAE PSO were imaged for both reporters. The percentage of GFP+ cells that were also positive for the tomato reporter in health and EAE is quantified in (d), ± s.e.m., n = 5 health, 4 EAE. e, Col1a2CreERT;Rosa-tdTomato mice were stained with NG2 in red, and the proportion of Col1a2CreERT+ cells that were NG2+ and NG2 were quantified in (f), ± s.e.m., n = 4. Scale bars = 100 µm.

Extended Data Fig. 4 Single-cell sequencing: cell purification and cluster expression.

a, Sample FACS plots of the purificaiton of Col1a1-GFP+ cells used for the single-cell sequencing analysis of Col1a1-GFP+ cells in health and EAE. b, UMAP plot of the single-cell RNA-seq dataset of Col1a1GFP+ cells in health and EAE with the individual sample identity labeled for each cell. c, Heat map depicting the expression of the 10 most differentially expressed genes in each cluster based on the logFC of the dataset. d, Heat map depicting the expression levels of genes specific to the labeled cell types, Olig = oligodendrocyte.

Extended Data Fig. 5 Effects of reducing fibrotic scar formation on immune cell infiltration, oligodendrocyte lineage cell populations and axon numbers.

a, Spinal cord sections from fHTK mice and controls were stained for DAPI (blue) and periostin (green), ER-TR7 (green), Col3 (green) and CD11b (red), or GFAP (green) and Cd11b (red). b, Spinal cord sections from fHTK mice and controls were stained for CD4 (red, left) and DAPI (blue) and the number of CD4+ cells per lesion area was compared between groups (right), p = 0.38 by Student’s two-tailed t-test, ± s.e.m., n = 21 control and 19 fHTK. c, Spinal cord sections from fHTK mice and controls were stained for CD8 (red, left) and DAPI (blue) and the number of CD8+ cells per lesion area was compared between groups (right), ± s.e.m., p = 0.22 by Student’s two-tailed t-test, n = 21 control and 19 fHTK. d, Spinal cord sections from fHTK mice and controls were stained for OLIG2 in green and CC1 in red, and the percent of OLIG2+ cells that were also CC1+ was quantified, ± s.e.m., p = 0.26 by Student’s two-tailed t-test e, Spinal cord sections from fHTK mice and controls were stained for neurofilament heavy polypeptide (NF) in green and CD11b in red, and the number of healthy, blebbed and total axons was quantified, ± s.e.m.. Scale bars = 100 µm.

Extended Data Fig. 6 Col1 reduces OPC migration, but not proliferation or differentiation, in vitro.

a, Representative images of OLIG2 (green) and PDGFRa (red) staining with EdU labeling (cyan) in rat OPC cultures on PLL, laminin, fibronectin, or collagen I after a 2 hour incubation in 10 uM EdU. b, Quantification of the percentage of EdU+ OPCs (OLIG2+PDGFRa+) for cultures represented in a., ± s.e.m., n = 9 replicates. c, Representative images of MBP (red) staining in rat OPC cultures on PLL, laminin, fibronectin, or collagen I three days after removal of PDGF-AA. Cell nuclei detected with DAPI (blue). d, Quantification of MBP+ cells over total cells (DAPI+) for cultures represented in c., ± s.e.m., n = 9 replicates. e, Representative images of PDGFRa (green) staining with DAPI in rat OPC cultures that had migrated through transwells coated with PLL, laminin, fibronectin, or collagen I following a 24 hour incubation. f, Quantification of PDGFRa+ cells on the underside of each transwell for the cultures represented in e., ± s.e.m., n = 9 replicates. Data displayed represent 3 replicates of 3 samples, each containing cells from three pooled postnatal day-7 rats. Comparisons were performed using one-way ANOVA with Sidak’s post hoc tests, ****p < 0.0001, ***p < 0.001, *p < 0.05. Scale bars = 100 µm.

Extended Data Fig. 7 RNA sequencing analysis of Col1a1-GFP+ cells from the spinal cord in health and EAE.

a-c, MA plots comparing the transcriptome of CNS fibroblasts in health with whole spinal cord tissue (a), CNS fibroblasts in health with CNS fibroblasts EAE D5 (b) or D10 (c) PSO with red dots signifying genes with FDR < 0.1. d, Pathway analysis using DAVID Bioinformatics Resources 6.8, NIAID/NIH, GOTERM_BP_DIRECT for genes with a log2 fold change greater than 2 for CNS fibroblasts EAE D5 PSO compared to CNS fibroblasts in health. e, CPM of collagen genes from the bulk sequencing of whole spinal cord tissue (Whole SC, n = 2), CNS fibroblasts from health (CNS Fibro Health, n = 3) CNS fibroblasts 5 days PSO (CNS Fibro EAE D5, n = 3) and 10 days PSO (CNS Fibro EAE D10, n = 3), ± s.e.m., *FDR < 0.05, **FDR < 0.01 to Whole SC, #FDR < 0.05, ##FDR < 0.01 to CNS Fibro Health. f, Heat map of the expression levels of the top genes differentially expressed in CNS Fibro Health (each expressed at least 1 CPM in each control sample) compared to the whole spinal cord by FDR.

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Dorrier, C.E., Aran, D., Haenelt, E.A. et al. CNS fibroblasts form a fibrotic scar in response to immune cell infiltration. Nat Neurosci 24, 234–244 (2021). https://doi.org/10.1038/s41593-020-00770-9

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