NeuroImmunology

Download PDF Subjects Bioinformatics Innate immunity Skull bone marrow (BM) has emerged as an important immune interface with the central nervous system (CNS). Park and colleagues identify germinal center-like lymphoid structures within skull BM that can generate adaptive immune responses to CNS-derived antigens and contribute to anti-tumor immunity in experimental glioma.The skull bone marrow (BM) is increasingly recognized as an immune interface with the central nervous system (CNS). Vascular channels and diploic veins connect skull BM with the dura mater, providing routes for the exchange of cells and soluble molecules between these compartments.1,2 Cerebrospinal fluid can access skull BM niches, while skull BM supplies myeloid cells and immature B cells to the meninges and, under some conditions, the CNS parenchyma.3,4,5 Organized lymphoid hubs containing germinal center (GC) B cells have also been identified around meningeal venous plexuses, where they support local humoral immune responses.6 More recently, neuron-derived proteins were shown to accumulate at skull-associated borders, where they are sampled by resident immune cells.7 Despite these anatomical and functional connections, whether skull BM can organize antigen-specific adaptive immune responses to CNS-derived antigens has remained unclear. Park and colleagues now identify GC-like lymphoid structures in skull BM and examine their contribution to CNS immunosurveillance.8Comparing BM from different bones, the authors identified an enrichment of IL-21+CXCR5+ follicular helper T (Tfh) cells in skull BM relative to the sternum and femur. These cells expressed Th1-associated markers and formed clusters with B cells in discrete regions of the skull. Skull BM also contained increased numbers of class-switched and GC-like B cells, IgG+ plasmablasts, and antibody-secreting cells. Further characterization revealed organized aggregates containing T cells, B cells, antigen-presenting cells (APCs), CXCL13, B cell activating factor, follicular dendritic cells, and activation-induced cytidine deaminase-expressing B cells. GC-like B cells and antibody-secreting cells underwent clonal expansion and somatic hypermutation and depended on CD4+ T cells, IL-21, and CD40-CD40L signaling. These findings identify a specialized lymphoid environment within skull BM capable of supporting a local humoral immune response.8What drives these responses? Gut microbiota and dietary antigens contributed to the generation of IgA-producing and GC-like B-cell populations but did not fully account for their presence. Park and colleagues therefore asked whether CNS-derived antigens could also reach and activate this compartment. Using neuronal expression of secreted ovalbumin (OVA), they detected antigen in skull BM and observed activation of antigen-specific CD4+ T and B cells.8 Recent work by Chayama and colleagues provides an interesting comparison. Using neuronal protein tracing, they found that brain-derived proteins reach skull-associated niches under physiological conditions.7 However, antigen-sampling skull B cells in that study expressed genes associated with antigen processing and presentation together with a predominantly tolerogenic transcriptional program. Earlier work also identified a CNS antigen-dependent tolerance checkpoint in the adjacent meninges, where developing B cells reactive to the CNS-specific antigen myelin oligodendrocyte glycoprotein were selectively eliminated.9 Access of CNS antigens to skull-associated immune niches, therefore, does not necessarily result in immune activation. The conditions and anatomical site in which antigen is encountered may determine the response that follows.Park and colleagues next examined whether these structures participate in immunity against brain tumors. Following intracranial implantation of CT2A glioma cells, T- and B-cell responses increased within skull BM. Using CT2A tumors expressing HEL-OVA together with antigen-specific lymphocytes, they detected early activation of tumor-reactive T and B cells in skull BM.8 These responses persisted in mice lacking conventional secondary lymphoid organs, although they were diminished and remained dependent on cells recruited from the periphery. The skull BM can therefore support local adaptive immune responses, but it does not appear to function independently of the peripheral immune system.The authors next asked whether these responses influence tumor control. Local blockade of CD40L disrupted skull GC-like structures, reduced intratumoral lymphocyte accumulation and CD8+ T-cell activation, and shortened survival. Conversely, combining a CD40 agonist with IL-21 and IFNγ enhanced skull B-cell responses, increased immune cell infiltration and cytotoxic activity within tumors, and prolonged survival.8 Under these experimental conditions, manipulating skull-associated immune responses can alter immunity within the brain and influence disease outcome (Fig. 1).How well these findings extend to naturally arising brain tumors remains uncertain. Glioblastoma (GBM) is generally considered an immunologically “cold” tumor, with an immune environment dominated by myeloid cells and relatively limited productive T-cell immunity. Evidence for skull-associated anti-tumor immunity has nevertheless been found in patients. Dobersalske and colleagues identified tumor-reactive CD8+ T cells in cranial BM from patients with GBM, including T-cell receptor clonotypes shared between cranial marrow and matched tumors.10 The extent to which these cells contribute to tumor control remains uncertain. Immune checkpoint blockade has also produced disappointing results in large clinical trials, with nivolumab failing to improve overall survival compared with bevacizumab in recurrent GBM.11 These clinical observations do not rule out a contribution from skull-associated immunity, but they show that tumor antigen recognition in GBM rarely translates into an effective anti-tumor response.The glioma models used in the study warrant some consideration. Tumors were established by intracranial transplantation, and some experiments employed cells engineered to express defined model antigens.8 These approaches are useful for resolving antigen-specific responses but may not fully reproduce tumors that arise spontaneously within the CNS. Whether skull-associated responses are similarly engaged by tumors with lower immunogenicity, and how their contribution compares with conventional lymphoid organs and other CNS border tissues, remain unresolved.An important question is how antigen encounter within skull BM is translated into an immune response. CNS-derived proteins reach skull-associated immune niches under physiological conditions,7 while studies of the skull and adjacent meninges have identified mechanisms that may favor B cell tolerance to CNS-derived antigens.7,9 What determines whether CNS antigen encounter promotes tolerance or productive adaptive immunity? Does inflammation or tissue injury alter this balance? Are similar skull-associated responses generated during infection, autoimmunity, or neurodegeneration? It will also be important to determine how much skull BM contributes to CNS immunity relative to the meninges and conventional secondary lymphoid organs, and whether comparable antigen-responsive lymphoid structures function in the human skull.Park and colleagues establish that skull BM contains organized lymphoid structures capable of responding to CNS-derived antigens and influencing immunity in experimental glioma. What remains less clear is when these responses become functionally important. Defining the signals that balance tolerance and immunity within this niche and determining its contribution relative to other CNS and peripheral immune compartments will be important for establishing the role of skull BM in CNS immunosurveillance. ReferencesMonaghan, K. L. et al. Nature 652, 1298–1307 (2026).Article PubMed Google Scholar Zanluqui, N. G. & McGavern, D. B. Trends Immunol. 45, 738–749 (2024).Article PubMed PubMed Central Google Scholar Brioschi, S. et al. Science 373, eabf9277 (2021).Article PubMed PubMed Central Google Scholar Cugurra, A. et al. Science 373, eabf7844 (2021).Article PubMed PubMed Central Google Scholar Mazzitelli, J. A. et al. Nat. Neurosci. 25, 555–560 (2022).Article PubMed PubMed Central Google Scholar Fitzpatrick, Z. et al. Nature 628, 612–619 (2024).Article PubMed PubMed Central Google Scholar Chayama, Y. et al. Cell 189, 4737–4755.e17 (2026).Article PubMed PubMed Central Google Scholar Park, J. H. et al. Nature 658, 196–204 (2026).Article PubMed PubMed Central Google Scholar Wang, Y. et al. Immunity 54, 2784–2794.e6 (2021).Article PubMed Google Scholar Dobersalske, C. et al. Nat. Med. 30, 2947–2956 (2024).Article PubMed PubMed Central Google Scholar Reardon, D. A. et al. JAMA Oncol. 6, 1003–1010 (2020).Article PubMed PubMed Central Google Scholar Download referencesAcknowledgementsThis work was supported by the intramural program at the National Institute of Neurological Disorders & Stroke (NINDS) within the National Institutes of Health (NIH). The contributions of the NIH author(s) are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.Author informationAuthors and AffiliationsViral Immunology and Intravital Imaging Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, USANagela G. Zanluqui, Yvonne L. Latour & Dorian B. McGavernAuthorsNagela G. ZanluquiView author publicationsSearch author on:PubMedGoogle ScholarYvonne L. LatourView author publicationsSearch author on:PubMedGoogle ScholarDorian B. McGavernView author publicationsSearch author on:PubMedGoogle ScholarCorresponding authorCorrespondence to Dorian B. McGavern.Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Rights and permissionsReprints and permissionsAbout this articleCite this articleZanluqui, N.G., Latour, Y.L. & McGavern, D.B. A neighborhood watch within the skull. Cell Res (2026). https://doi.org/10.1038/s41422-026-01310-zDownload citationPublished21 October 2026Version of record21 October 2026DOIhttps://doi.org/10.1038/s41422-026-01310-z

Highlights

Summary

For many many years we have been fed a diet of MS is an autoimmune disease of T cell reactivity to myelin basic protein.This has been lapped up by researchers and with any dissenting voices their …...

Abstract Objective To investigate whether anti-CD20 B-cell-depleting monoclonal antibodies (ɑCD20 mAbs) inhibit the formation or retention of meningeal ectopic lymphoid tissue (mELT) in a murine model of multiple sclerosis (MS). Methods We used a spontaneous chronic experimental autoimmune encephalomyelitis (EAE) model of mice with mutant T-cell and B-cell receptors specific for myelin oligodendrocyte glycoprotein (MOG), which develop meningeal inflammatory infiltrates resembling those described in MS. ɑCD20 mAbs were administered in either a preventive or a treatment regimen. The extent and cellular composition of mELT was assessed by histology and immunohistochemistry. Results ɑCD20 mAb, applied in a paradigm to either prevent or treat EAE, did not alter the disease course in either condition. However, ɑCD20 mAb depleted virtually all B cells from the meningeal compartment but failed to prevent the formation of mELT altogether. Because of the absence of B cells, mELT was less densely populated with immune cells and the cellular composition was changed, with increased neutrophil granulocytes. Conclusions These results demonstrate that, in CNS autoimmune disease, meningeal inflammatory infiltrates may form and persist in the absence of B cells. Together with the finding that ɑCD20 mAb does not ameliorate spontaneous chronic EAE with mELT, our data suggest that mELT may have yet unknown capacities that are independent of B cells and contribute to CNS autoimmunity. Glossary ɑCD20 mAb=anti-CD20 monoclonal antibody; BCR=B-cell receptor; EAE=experimental autoimmune encephalomyelitis; mELT=meningeal ectopic lymphoid tissue; MOG=myelin oligodendrocyte glycoprotein; MPO=myeloperoxidase; MS=multiple sclerosis; RRMS=relapsing-remitting multiple sclerosis; PMS=progressive MS; SLO=secondary lymphoid organ; LFB-PAS=Luxol fast blue and periodic acid-Schiff reaction; TCR=T-cell receptor B-cell-depleting strategies with anti-CD20 monoclonal antibodies (ɑCD20 mAbs), such as rituximab, ocrelizumab, or ofatumumab, are among the most potent therapies currently available in the treatment of relapsing-remitting multiple sclerosis (RRMS). Modest efficacy has also been shown in progressive MS (PMS), specifically active primary PMS, and early, relapse-independent progression in RRMS.1,-,4 Their success highlights the importance of B cells for MS pathogenesis. Among other factors, the therapeutic effect of B-cell depletion may be mediated by interrupting antigen presentation by B cells to T cells in the CNS.5,-,9 Leukocytic infiltrates, forming meningeal ectopic lymphoid tissue (mELT), are found in patients with PMS and to a lesser extent in RRMS. They correlate with an earlier disease onset, a more rapid disease progression, and subpial cortical damage.10,-,15 In general, ectopic lymphoid tissue (ELT) is formed by aggregates of B and T cells, which range from tight-cell clusters to highly organized structures and resemble secondary lymphoid organs (SLOs).16,-,20 In a model of MS, it was demonstrated that B-cell repertoire expansion occurs in mELT, suggesting germinal center activity in the CNS.21 Hereby, mELT may facilitate smoldering autoimmunity in the CNS parenchyma sequestered beyond the blood-brain barrier. Yet, it remains unclear whether and how mELT contributes to early or progressive MS. Because B cells are an integral part of mELT and ɑCD20 mAb that targets B cells not only in the periphery but also in the meninges,22 it seems possible that ɑCD20 mAb inhibits the formation or retention of mELT. Assuming that mELT plays a role in MS pathogenesis, preventing or suppressing mELT may contribute to the efficacy of B-cell depletion in MS. In this study, we investigated the effects of ɑCD20 mAb on mELT in a B-cell-dependent and T-cell-dependent experimental autoimmune encephalomyelitis (EAE) model of MS. Approximately, 50% of 2D2 (TCRMOG) × Th (IgHMOG) mice develop spontaneous chronic EAE and exhibit meningeal clusters of T and B cells in the spinal cord, reminiscent of those found in MS.23,-,25 In this model, we depleted B cells to investigate whether ɑCD20 mAb prevents mELT formation. Surprisingly, our results showed that, despite depleting virtually all B cells from the meninges, mELT still formed or persisted. Materials and Methods Mice 2D2xTh mice, developing spontaneous chronic EAE with mELT, were generated as previously described by crossing myelin oligodendrocyte glycoprotein (MOG)-specific T-cell receptor (TCR) transgenic 2D2 (TCRMOG) mice with MOG-B-cell receptor (BCR) knockin Th mice (IgHMOG).23,24 Mice were bred and maintained in-house at the Center of Preclinical Research (CPR) at Klinikum rechts der Isar (Technical University of Munich) under specific pathogen-free conditions, according to FELASA recommendations with free access to water and standard rodent chow. EAE and Clinical Assessment 2D2xTh mice develop spontaneous chronic EAE with an incidence of approximately 30–50% in our facility. Clinical scores of mice were evaluated on a daily basis and assessed as follows: 0 = no clinical signs, 1 = tail weakness, 1.5 = additional impaired tail erection, 2 = ataxia and hind limb weakness, 2.5 = hind limb paresis, 3 = high-grade hind limb paresis, 3.5 = additional minor weakness of the fore limbs, 4 = additional fore limb paresis, 4.5 = tetraplegia, and 5 = moribund. ɑCD20 mAb Treatment 100 µg of antimouse CD20 mAb (clone 18B12, provided by F. Hoffmann-La Roche, Switzerland) in a murine IgG2a Fc-format or antihen egg lysozyme isotype control (Crown bio, Cat: C0006) in 100 µL PBS was injected intraperitoneally (i.p.) at day 0, 7, 14, and 21 for a total of 4 doses. Mice were grouped for prevention or treatment of EAE. In an attempt to prevent EAE, mice received the first injection at the age of 26 ± 3 days (n = 18 in both groups). For the evaluation of the therapeutic potential, mice were treated when reaching a clinical score of ≥3 (n = 11 ɑCD20 mAb-treated, n = 14 isotype-treated). Mice were killed 28 days after the first injection. Reference mice at the onset of disease (figure 3C) were dissected immediately after reaching an EAE score of ≥3 without treatment. Cell Isolation and Flow Cytometric Analysis Blood was freshly obtained by terminal cardiac puncture and mixed with 500 µL 2 mM EDTA. Cervical lymph nodes were carefully dissected and passed through a 30-µm cell strainer. Samples were washed with RPMI medium, and erythrocytes were lysed using BD Pharm Lyse Buffer (BD Biosciences). Cells were washed again, and the number of living cells was determined using a hemocytometer (Cellometer Auto 2000, Nexcelom Bioscience). Single-cell suspensions were stained with antibodies in PBS containing 2% fetal calf serum for 20 minutes at 4°C in the dark. Fc-receptors were blocked to prevent nonspecific antibody binding. Dead cells were excluded using the LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Invitrogen). Cells were washed twice and acquired on a CytoFLEX flow cytometer (Beckman Coulter). The following antimouse antibodies were used: CD16/CD32 (2.4G2), CD45R/B220 (RA3-6B2, FITC), and CD3e (145-2C11, PE) (BD Bioscience). Data were analyzed using FlowJo version 10 (TreeStar). Histology, Immunohistochemistry, and Imaging Spinal cord, spleen, and inguinal lymph nodes were perfused before dissection, fixed with 4% paraformaldehyde, and paraffin embedded. The spinal cord was additionally decalcified with Osteosoft (Sigma-Aldrich) 72 hours before embedding. To determine the degree of meningeal infiltrates, the spinal cord was sectioned horizontally into 13–16 tissue blocks (thickness: 2 × 5 mm cervical, subsequently 2.5 mm) per mouse and stained with hematoxylin and eosin according to standard protocols. The stained tissues were digitized (Leica AT2 scanner) and examined using Image Scope (Pathology Slide Viewing Software, version 12.4.3, Leica Biosystems). Infiltrates with a size of ≥1 × 104 µm2 per section were considered as mELT. The cell density was analyzed using a nuclear algorithm (Nuclear v9, Image Scope; Leica). To characterize the cellular composition of mELT, immunohistochemistry was performed on representative sections with antimouse CD45R/B220 (BD, 550286, 1:50), CD3 (DCS, CI597R0, 1:50), and myeloperoxidase (MPO; Thermo Fisher, RB-373-A, 1:50). Mouse spleens served as positive controls. Numbers of B220+ and CD3+ positive cells were determined using a membrane algorithm (Membrane v9, Image Scope; Leica). In the CNS, MPO+ cells were counted manually. In the periphery, MPO+ cells were quantified by applying a nuclear algorithm (Membrane v9, Image Scope; Leica). Two cross-sections of the cervicothoracic, the thoracolumbar, and the lower lumbar part were stained with Luxol fast blue and periodic acid-Schiff reaction (LFB-PAS) according to standard protocols. LFB-PAS staining was analyzed semiquantitatively by dividing spinal cord sections into quadrants and counting quadrants with demyelination. All histologic evaluations were performed in a blinded manner. Detection of Anti-MOG Antibodies Antirecombinant mouse MOG (1–125) (Eurogentec, Cat: AS-55150-100) IgG was measured with a noncommercial ELISA in duplicates as described,26 using MOG at a final concentration of 10 µg/mL and horseradish peroxidase-labeled goat antimouse IgG (Thermo Fisher Scientific). The optical density was measured at a wavelength of 450 nm with 540 nm as a reference wavelength using the ELISA reader (infinite M200 PRO, TECAN). Statistical Analysis Data are shown as mean ± SEM or 95% CI. Statistical significance between groups was analyzed using the unpaired Student t test. For correlation analysis, simple linear regression was calculated for each group. A value of p ≤ 0.05 was considered significant with *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. Standard Protocol Approvals, Registrations, and Patient Consents All animal experiments were approved by the competent authority, Regierung von Oberbayern, Munich, Germany (ROB-55.2-2532.Vet_02-16-100). Data Availability Data not published within this article will be made available by request from any qualified investigator. Results ɑCD20 mAb Efficiently Depletes B Cells in the Periphery but Does Not Affect the Clinical Course of Spontaneous Chronic EAE To analyze the effects of ɑCD20 mAb on mELT in the context of EAE, we crossed MOG Ig-VH knock-in (IgHMOG, Th) mice, in which B cells express a MOG-specific BCR heavy chain, with MOG-specific TCR transgenic mice (TCRMOG, 2D2). As previously described, 2D2xTh mice develop spontaneous chronic EAE with B-cell-rich and T-cell-rich mELT along the spinal cord.23,24 2D2xTh mice were treated weekly for a total of 4 intraperitoneal (i.p.) doses with antimurine CD20 or isotype control mAb. Two treatment paradigms were pursued in parallel: (1) to prevent EAE and mELT formation, mice received the first dose as soon as they were weaned about 26 days after birth (figure 1A) and (2) to treat fully established EAE, ɑCD20 mAb was first administered after mice developed an EAE score of ≥3 (figure 3A). ɑCD20 mAb efficiently depleted B cells in the peripheral blood (figure 1B.a, upper panel) and lymph nodes (figure 1B.b, lower panel). However, its application neither attenuated the rather severe and chronic course of EAE compared with the control groups in either condition (figures 1C and 3B) nor changed the incidence of EAE. In total, 44% of preventatively treated mice developed spontaneous chronic EAE, which was similar to 39% of control treated mice (figure 1D). Figure 1 Spontaneous EAE Occurs in the Absence of Peripheral B Cells in Mice Preventatively Treated With ɑCD20 mAb (A) Experimental setup. Mice were treated with a weekly dose of 100 μg of ɑCD20 mAb (n = 18) or isotype control (n = 18) after weaning. (B) Flow cytometric analysis of B220+ and CD3+ cells in blood (B.a) and lymph nodes (B.b) after 4 weeks of treatment. The representative flow cytometry contour plot (left) and quantification (right). (C) Daily evaluated EAE scores over the experimental period. Data are shown as mean ± SEM. (D) Incidence of mice developing clinical signs of disease. When not stated differently, data shown as mean ±95% CI. *p < 0.05; ****p < 0.0001; statistical significance between groups was analyzed using the Student t test. ɑCD20 mAb = anti-CD20 monoclonal antibody; EAE = experimental autoimmune encephalomyelitis; i.p. = intraperitoneally; n/N = mice with EAE/all mice observed. mELT Formation and Retention Occurs in the Absence of B Cells in Preventatively Treated Mice To investigate whether mELT forms and persists under B-cell-depleting conditions, we analyzed cross-sections along the spinal cord of 2D2xTh mice, which developed clinical signs of EAE during the observation/treatment period. With a mean EAE duration of 19 days (range 13–24 days) in the ɑCD20 mAb-treated group and 16 days (range 3–21 days) in the isotype-treated group, all mice showed mELT in at least 5 of 12–16 segments with a maximum along the thoracolumbar part of the spinal cord (figure 2A). Infiltrates were considered as mELT when their size was ≥1 × 104 µm2 per section. Surprisingly, the mean area of mELT per section, including sections in which no mELT was detected, was similar in both groups with a mean of 81,152 µm2 per section in ɑCD20 mAb and 103,968 µm2 in isotype-treated controls (figure 2B, upper panel). Hence, despite the absence of B cells in circulation and cervical lymph nodes, structures of mELT formed. With B cells being a main component of mELT,21,23,24 we performed B220 immunohistochemistry on sections of the thoracolumbar part of the spinal cord. We found that, although mELT was present to a similar extend, mELT of ɑCD20 mAb-treated mice only exhibited 0.59% of B220+ B cells observed in controls (figure 2B, lower panel). Figure 2 mELT Formation Occurs in the Absence of B Cells in Mice Preventatively Treated With ɑCD20 mAb After weaning, 2D2xTh mice received a weekly dose of 100 µg ɑCD20 mAb (n = 18) or isotype control mAb (n = 18) and were observed for 28 days (A + B) 8 of 18 aCD20 mAb-treated mice and 7 of 18 isotype mAb-treated mice developed EAE. One aCD20 mAb-treated mouse died prematurely and had to be excluded from the histologic analysis. (A) Quantitative distribution of mELT along the spinal cord with 12–16 cross-sections per animal analyzed. (B) Representative HE-stained (upper left panel) and B220-stained (lower left panel) sections of the thoracolumbar part of the spinal cord and corresponding close-up views of mELT. Quantification of the mean area of mELT including all sections (upper right panel) and the number of B220+ cells in mELT, analyzed in 2 randomly selected sections per animal, for all mice (lower right panel). (C) Analysis of histologic signs of disease in mice without clinically manifest EAE (11 of 18 isotype mAb-treated mice and 10 of 18 aCD20 mAb-treated mice). Representative HE sections given in (a) and (b) for mice with no pathologies, in (c) and (d) for mice with minor cellular infiltrates in the meninges, and in (e) and (f) for mice with mELT. (D) Quantitative analysis of the size and distribution of mELT along the spine in mice without clinically manifest EAE. In total, 12–16 sections analyzed per animal. Scale bars: 250 µm (overviews) and 100 µm (close-ups). When not stated differently, data shown as mean ±95% CI. *p < 0.05; ****p < 0.0001; statistical significance between groups was analyzed using the Student t test. ɑCD20 mAb = anti-CD20 monoclonal antibody; EAE = experimental autoimmune encephalomyelitis; HE = hematoxylin & eosin; mELT = meningeal ectopic lymphoid tissue; n/N = mice showing mELT or noted feature/total number of mice analyzed; ns = not significant. Interestingly, in both groups, mice without clinically apparent EAE over the treatment period of 28 days also showed histologic signs of disease in approximately 60% of cases, ranging from scattered cellular infiltrates in the meninges in some cases to mELT in 30% of the ɑCD20 mAb-treated mice and 36% of the isotype controls (figure 2C). In these clinically unremarkable animals, mELT was also mainly found in the thoracolumbar part of the spinal cord and was comparable in size in both groups (figure 2D). Our data indicate that the absence of B cells in preventatively treated 2D2xTh mice is not sufficient to prevent mELT formation and that not only mELT formation but also its retention may be independent of B cells. Moreover, mELT formation in our model occurs before developing clinical signs of EAE. ɑCD20 mAb Treatment Does Not Influence the Size of mELT In a second experiment, more closely resembling a clinical scenario, mice were randomized into groups treated with ɑCD20 or control mAbs after disease onset, i.e., when having developed an EAE score of ≥3 (aged on average 47.6 days in the ɑCD20 mAb and 48.4 days in the isotype-treated group). As a baseline, we used mice which were euthanized without further treatment immediately after having developed a score of ≥3 (figure 3A). At that stage of disease (onset), all mice already exhibited extensive mELT with a distinct fraction of B220+ B cells (figure 3C), confirming that mELT was sufficiently present before we started our intervention. After 4 weeks of treatment, distribution of mELT throughout the spinal cord was almost identical in-between groups, with all mice exhibiting mELT in at least 1 of 14–16 cross-sections analyzed (figure 3D). Again, we did not observe a difference in the mean area of mELT in both groups (figure 3E). Similar to what was observed in autopsy cases of MS, the extent of mELT correlated with disease severity in control mice. However, this was not statistically significant in ɑCD20 mAb-treated animals (figure 3F). Figure 3 ɑCD20 mAb Applied After EAE Onset Does Not Change the Clinical Course of Spontaneous EAE or the Size of mELT (A) Experimental setup. As soon as 2D2xTh mice developed a score of ≥3, they received a weekly dose of 100 µg of ɑCD20 (n = 11) or isotype control mAb (n = 14) over a period of 28 days. Another 5 mice were euthanized and dissected directly after developing a clinical score of ≥3, without receiving treatment. They served as histologic reference at disease onset for the remainder of the mice for which treatment commenced at that stage. (B) Clinical course of EAE during application of ɑCD20 or isotype mAb. Data expressed as mean ± SEM. (C) Representative HE (upper left panel) and B220 (lower left panel) staining of the spinal cord mELT of mice at EAE onset and respective quantification in all mice (right panels). (D) Representative HE-stained cross-sections of the thoracolumbar part of the spinal cord of ɑCD20 mAb-treated and isotype-treated mice (left) and representation of the distribution of mELT along the spine with 14–16 sections analyzed per animal (right). (E) Quantification of the mean area of mELT per section. (F) Correlation of the mean area of mELT per section with the mean EAE score over the observation period. Simple linear regression was calculated for each group. Scale bars, 250 µm. When not indicated differently, data shown as mean ± 95% CI. Statistical significance between groups was analyzed using the Student t test. ɑCD20 mAb = anti-CD20 monoclonal antibody; EAE = experimental autoimmune encephalomyelitis; HE = hematoxylin & eosin; i.p. = intraperitoneally; mELT = meningeal ectopic lymphoid tissue; n/N = mice showing mELT/total number of mice analyzed; ns = not significant. Persisting High Titers of Anti-MOG Antibodies and Extensive Demyelination in B-Cell-Depleted Mice Reflects the Lasting Severe and Chronic Course of EAE Although B cells were effectively reduced not only in the periphery but also in the meningeal compartment, MOG-specific total IgG titers remained high even after 4 weeks of B-cell depletion (figure 4A). Correlating with the clinical disease course, the spinal cord was similarly affected by demyelination in ɑCD20 mAb-treated mice compared with controls (figure 4B). Together with persisting B-cell-free mELT, these observations may contribute to the lack of a clinical benefit of B-cell depletion in our model. Figure 4 B-Cell-Depleted Spontaneous Chronic EAE Mice Exhibit High Titers of Anti-MOG Antibodies and Extensive Demyelination, Reflecting Their Severe Disease Course 2D2xTh mice received 4 doses of ɑCD20 mAb (n = 11) or isotype control (n = 10) as soon as they reached an EAE score of ≥3. (A) Antimurine MOG IgG serum levels determined by ELISA (dilution 1:300). Data are shown as individual data points and mean ± 95% CI. (B) LFB-PAS staining of the spinal cord, showing representative thoracolumbar cross-sections and corresponding close-ups. For each mouse, 2 randomly chosen cross-sections per spinal cord segment—cervicothoracic (n = 5 for ɑCD20 mAb and n = 6 for isotype), thoracolumbar (n = 8 per group), and lumbar (n = 7 for ɑCD20 mAb and n = 6 for isotype)—were examined. Data are presented as minimum and maximum values and mean. Scale bars: 250 µm and 100 µm (close-ups). Statistical significance between groups was analyzed using the Student t test. ɑCD20 mAb = anti-CD20 monoclonal antibody; EAE = experimental autoimmune encephalomyelitis; LFB-PAS = Luxol fast blue and periodic acid-Schiff reaction; MOG = myelin oligodendrocyte glycoprotein; ns = not significant; OD = optical density. ɑCD20 mAb Treatment Changes the Density and Composition of the Cellular Content of mELT When we analyzed the cellular composition of mELT more closely, we found that, within the treatment paradigm, mELT in ɑCD20 mAb-treated mice was populated with 24.2% less cells (figure 5A). The count of B220+ B cells, which was the largest immune cell fraction in control mice, was drastically reduced on ɑCD20 mAb treatment, suggesting that the absence of B cells led to this reduced cellular density in mELT (figure 5B, upper panel). We did not notice a relevant change in CD3+ cells (figure 5B, middle panel), whereas the number of MPO positive neutrophil granulocytes was significantly increased under ɑCD20 mAb therapy (figure 5B, lower panel). Comparing these changes in mELT with SLOs, we observed that in the spleen and inguinal lymph nodes, B220+ B cells were also largely eliminated. MPO+ cells seemed to be increased, but this did not reach statistical significance. In contrast to mELT, however, the amount of CD3+ T cells was slightly increased in B-cell-depleted lymph nodes (figure 6). Figure 5 ɑCD20 mAb B-Cell Depletion in Spontaneous Chronic EAE Alters Cellular Density and Composition of mELT 2D2xTh mice received 4 doses of ɑCD20 mAb (n = 11) or isotype control (n = 10) as soon as they reached an EAE score of ≥3. (A) HE staining of representative spinal cord sections of (a) isotype-treated and (b) ɑCD20 mAb-treated mice visualizing the cellular density of mELT (c) and (d) show representative samples of the computer-aided quantification of nuclei in mELT with the corresponding graphs. (B) Quantification of B cells (B220), T cells (CD3), and neutrophil granulocytes (MPO) in spinal cord mELT. mELT of 1–4 randomly chosen cross-sections per mouse were analyzed. Scale bars: 50 µm (A) and 100 µm (B). Data are presented as individual data points and mean ± 95% CI. *p ≤ 0.05; **p < 0.01; ****p < 0.0001; statistical significance between groups was analyzed using the Student t test. ɑCD20 mAb = anti-CD20 monoclonal antibody; EAE = experimental autoimmune encephalomyelitis; HE = hematoxylin & eosin; mELT = meningeal ectopic lymphoid tissue; MPO = myeloperoxidase; ns = not significant. Figure 6 ɑCD20 mAb Efficiently Depletes B Cells in SLOs 2D2xTh mice received 4 doses of ɑCD20 mAb (n = 11) or isotype control (n = 10) as soon as they reached an EAE score of ≥3. Quantification of B cells (B220), T cells (CD3), and neutrophil granulocytes (MPO) in spleens and inguinal lymph nodes. One randomly chosen cross-section per organ (n = 5 mice per group) was evaluated. Scale bars: 250 µm. Data are presented as individual data points and mean ±95% CI. *p ≤ 0.05; ****p < 0.0001; statistical significance between groups was analyzed using the Student t test. ɑCD20 mAb = anti-CD20 monoclonal antibody; EAE = experimental autoimmune encephalomyelitis; LN = lymph node; MPO = myeloperoxidase; ns = not significant; SLO = secondary lymphoid organ; SPL = spleen. Together, our findings show that ɑCD20 mAb, to some degree, depletes B cells in mELT in mice with spontaneous chronic EAE, yet mELT persists. The role and function of mELT devoid of B cells remains unclear. Discussion Although its exact role in MS pathogenesis remains unclear, meningeal inflammation has gained widespread attention in recent years. Because B cells are a major component of mELT and B-cell-depleting mAbs are among the most successful MS therapeutics today, the question how B-cell-depleting therapies affect mELT is obvious. In this study, we systematically addressed this question in a murine model of MS. Not unexpectedly, B-cell depletion did not change the disease course in our spontaneous chronic EAE model. It has previously been reported that ɑCD20 mAb did not significantly change the course of EAE in the same model because high titers of MOG-binding antibodies in conjunction with MOGTCR 2D2 T cells could support clinical disease in the absence of B cells.26 Importantly, ɑCD20 mAb does not target antibody-producing plasma cells. It could be debated that spontaneous chronic EAE in 2D2xTh mice, because of the MOG specificity of both T and B cells, is not dynamic enough to allow being modified by pharmaceutical interventions. However, laquinimod ameliorated spontaneous chronic EAE and reduced meningeal B-cell aggregates and thereby demonstrated its plasticity.27 Thus, other factors are likely to contribute. Although clinical effects were neglectable, we found that ɑCD20 mAb depleted virtually all B cells not only from SLOs and blood but also from mELT. It has been shown before that B cells infiltrating the meninges in EAE could be efficiently depleted by ɑCD20 mAb administered either intraperitoneally or intrathecally.22 This study used a model, however, which does not feature large meningeal B-cell aggregates such as mELT. A case report of a patient with gastrointestinal mantle cell lymphoma, who developed progressive multifocal leukoencephalopathy after rituximab therapy, showed that 8 months after the last dose, no B cells were found in perivascular spaces.28 By contrast, a case report of a young man with aggressive MS treated with rituximab and with no detectable peripheral B cells found some B cells in the parenchyma and in perivascular cuffs on CNS autopsy.29 Regarding B-cell-depleting antibodies used to treat MS, it is an encouraging finding that ɑCD20 mAb could deplete B cells present in mELT and prospectively prevent colonization of the meningeal compartment by B cells. Yet, open questions remain. The most unexpected finding in our study was that mELT formed or remained in the absence of B cells when mice were B-cell-depleted after EAE was fully established and even when treated before EAE onset. The size and extent of mELT was even comparable whether they contained B cells or not. This shows that, in our model, B cells are not essential for the induction or maintenance of mELT development. Yet, in the absence of B cells, mELT was less densely packed with cells and the cellular composition was altered. ɑCD20 mAb-treated mice had drastically fewer B220+ B cells, comparable amounts of CD3+ T cells, and significantly more MPO+ neutrophil granulocytes in mELT. A recent study showed that neutrophil granulocytes pioneer mELT formation and precede B cells in the meningeal compartment.30 In addition, several other cell types have been proposed as candidates to induce ELT formation, including IL-22 or IL-17 secreting immune cells, dendritic cells, and CD3−CD4+CD45+ lymphoid tissue inducer cells.16,31,-,35 Our own data showed that shortly after EAE onset, B220+ B cells were already present in mELT, but after 4 weeks of isotype control treatment, their amount had roughly doubled. Thus, B cells seem to fully populate mELT at later stages. This raises the question, which role B cells play in (later stage) mELT and whether mELT without B cells still has a pathogenic role. Generally, our mice would be expected to benefit from B-cell depletion, like it has been shown in another B-cell-dependent model without mELT or in MS itself.1,-,3,36 If mELT lacking B cells still contribute to autoimmunity, this could explain why the EAE disease course is unchanged in ɑCD20 mAb-treated 2D2xTh mice. As discussed above, other inherent properties of the model could contribute, such as the presence of high titers of MOG-binding antibodies and MOGTCR T cells with a potentially altered activation status under ɑCD20 mAb therapy. However, the notion that mELT without B cells persist in EAE and its persistence correlates with sustained severe disease, may give rise to interesting considerations: B-cell-depleting therapies are disproportionately more effective in RRMS than PMS. It could be speculated that future therapeutic approaches targeting mELT directly, instead of B cells, may be more effective in treating PMS. We observed that approximately one-third of 2D2xTh mice without clinically manifest EAE develop a minor degree of mELT both in the presence or absence of B cells. What does this imply regarding the role of mELT? Naturally, it remains unknown whether for these mice disease was imminent and the occurrence of mELT only preceding clinical signs. Alternatively, it is possible that 2D2xTh mice live with mELT without developing a phenotype. The latter would suggest that mELT may be a rather irrelevant epiphenomenon of encephalitogenic B and T cells being present in this model or that mELT may even have a regulatory role. One limitation of our study is that we depleted B cells relatively soon, i.e., before the onset of EAE or at an early stage of disease, where B cells are already present in mELT but to a lesser extent. We believe that it is reasonable to conclude from our results that B cells already present in mELT were depleted by ɑCD20 mAb. However, we could not formally assess the respective contributions of preventing B-cell influx from the periphery or direct depletion in the CNS itself to our finding that mELT was devoid of B cells after several weeks of treatment with ɑCD20 mAb. It is very challenging to study meningeal pathologies in patients in vivo or even postmortem. Thus, animal models are instrumental, and yet, the transferability of any findings in such models to MS must be questioned continuously. Our model of spontaneous chronic EAE has several characteristics that make it a suitable tool. EAE develops without an external stimulus, such as immunization or an adjuvant, and mice form meningeal inflammatory aggregates. Furthermore, mELT is readily available in high quality and quantity. However, it is a highly artificial model which is genetically determined through B-cell-mediated and T-cell-mediated autoimmunity against MOG. MS, by contrast, is not known to have a single autoantigen and certainly does not feature such a highly polarized adaptive immune system. Therefore, studies in human subjects treated with ɑCD20 mAb are required to confirm our results. In conclusion, we provide evidence that systemically applied ɑCD20 mAbs efficiently deplete B cells in meningeal inflammatory aggregates, and yet, mELT still form and persist with an altered cellular composition. The unchanged severe course of EAE, despite near complete B-cell depletion, both in the periphery and the meningeal compartment, may point to a yet unknown function of mELT, which is independent of B cells. Future studies are required, which aim to better understand the role and pathogenic relevance of mELT with and without B cells. Study Funding This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) SFB TRR 130 TP17 to H. Radbruch. K. Lehmann-Horn received research support from the Deutsche Forschungsgemeinschaft (SFB-TR-128 and LE 3079/3-1), the Hertie Foundation (MyLab program), and the US National Multiple Sclerosis Society (NMSS) (G-1508-07064). Disclosure R.M. Brand, V. Friedrich, J. Diddens, M. Pfaller, F.R. de Franchis, H. Radbruch, and K. Steiger report no disclosures. B. Hemmer has served on scientific advisory boards for Novartis; he has served as DMSC member for AllergyCare, Polpharma, and TG therapeutics; he or his institution has received speaker honoraria from Desitin; his institution received research grants from Regeneron for MS research. He holds part of two patents: one for the detection of antibodies against KIR4.1 in a subpopulation of patients with MS and the other for genetic determinants of neutralizing antibodies to interferon. All conflicts are not relevant to the topic of this study. K. Lehmann-Horn has received research support (to TUM) from Novartis, honoraria, and compensation for travel expenses from Novartis, F. Hoffmann-La Roche, and Merck Serono. Go to Neurology.org/NN for full disclosures. Acknowledgment The authors would like to thank Melina Pekic Hajdarbasic, Beatrix Lunk, Olga Seelbach, Marion Mielke, Ulrike Mühlthaler (all TUM), and Vera Wolf and Sandra Meier (both Charité) for excellent technical assistance. The authors acknowledge support from F. Hoffmann-La Roche for providing the antimouse CD20 antibody 18B12. R.M. Brand is a fellow of the Hertie Foundation (medMS Doctoral Program). Appendix Authors Footnotes Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article. The Article Processing Charge was funded by the authors. Editorial, page e1000 Received January 25, 2021. Accepted in final form March 8, 2021. Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. References 1.↵Hauser SL, Waubant E, Arnold DL, et al. B-cell depletion with rituximab in relapsing-remitting multiple sclerosis. N Engl J Med. 2008;358(7):676-688.OpenUrlCrossRefPubMed 2.↵Hauser SL, Bar-Or A, Comi G, et al. Ocrelizumab versus interferon beta-1a in relapsing multiple sclerosis. N Engl J Med. 2017;376(3):221-234.OpenUrlCrossRefPubMed 3.↵Montalban X, Hauser SL, Kappos L, et al. Ocrelizumab versus placebo in primary progressive multiple sclerosis. N Engl J Med. 2017;376(3):209-220.OpenUrlCrossRefPubMed 4.↵Ancau M, Berthele A, Hemmer B. CD20 monoclonal antibodies for the treatment of multiple sclerosis: up-to-date. Expert Opin Biol Ther. 2019;19(8):829-843.OpenUrl 5.↵Molnarfi N, Schulze-Topphoff U, Weber MS, et al. MHC class II-dependent B cell APC function is required for induction of CNS autoimmunity independent of myelin-specific antibodies. J Exp Med. 2013;210(13):2921-2937. 6.↵Sabatino JJ Jr., Probstel AK, Zamvil SS. B cells in autoimmune and neurodegenerative central nervous system diseases. Nat Rev Neurosci. 2019;20(12):728-745.OpenUrl 7.↵von Budingen HC, Palanichamy A, Lehmann-Horn K, Michel BA, Zamvil SS. Update on the autoimmune pathology of multiple sclerosis: B-cells as disease-drivers and therapeutic targets. Eur Neurol. 2015;73(3-4):238-246.OpenUrlCrossRefPubMed 8.↵Weber MS, Hemmer B. Cooperation of B cells and T cells in the pathogenesis of multiple sclerosis. Results Probl Cell Differ. 2010;51:115-126.OpenUrlPubMed 9.↵Zamvil SS, Hauser SL. Antigen presentation by B cells in multiple sclerosis. N Engl J Med. 2021;384(4):378-381.OpenUrl 10.↵Serafini B, Rosicarelli B, Magliozzi R, Stigliano E, Aloisi F. Detection of ectopic B-cell follicles with germinal centers in the meninges of patients with secondary progressive multiple sclerosis. Brain Pathol. 2004;14(2):164-174.OpenUrlCrossRefPubMed 11.↵Magliozzi R, Howell O, Vora A, et al. Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology. Brain. 2007;130(pt 4):1089-1104.OpenUrlCrossRefPubMed 12.↵Howell OW, Reeves CA, Nicholas R, et al. Meningeal inflammation is widespread and linked to cortical pathology in multiple sclerosis. Brain. 2011;134(pt 9):2755-2771.OpenUrlCrossRefPubMed 13.↵Lucchinetti CF, Popescu BF, Bunyan RF, et al. Inflammatory cortical demyelination in early multiple sclerosis. N Engl J Med. 2011;365:2188-2197.OpenUrlCrossRefPubMed 14.↵Choi SR, Howell OW, Carassiti D, et al. Meningeal inflammation plays a role in the pathology of primary progressive multiple sclerosis. Brain. 2012;135(pt 10):2925-2937.OpenUrlCrossRefPubMed 15.↵Reali C, Magliozzi R, Roncaroli F, Nicholas R, Howell OW, Reynolds R. B cell rich meningeal inflammation associates with increased spinal cord pathology in multiple sclerosis. Brain Pathol. 2020;30(4):779-793.OpenUrl 16.↵Pitzalis C, Jones GW, Bombardieri M, Jones SA. Ectopic lymphoid-like structures in infection, cancer and autoimmunity. Nat Rev Immunol. 2014;14:447-462.OpenUrlCrossRefPubMed 17.↵Corsiero E, Nerviani A, Bombardieri M, Pitzalis C. Ectopic lymphoid structures: powerhouse of autoimmunity. Front Immunol. 2016;7:430.OpenUrlCrossRef 18.↵Pikor NB, Prat A, Bar-Or A, Gommerman JL. Meningeal tertiary lymphoid tissues and multiple sclerosis: a gathering place for diverse types of immune cells during CNS autoimmunity. Front Immunol. 2015;6:657.OpenUrlCrossRef 19.↵Jones GW, Jones SA. Ectopic lymphoid follicles: inducible centres for generating antigen-specific immune responses within tissues. Immunology. 2016;147(2):141-151.OpenUrlCrossRefPubMed 20.↵Bell L, Lenhart A, Rosenwald A, Monoranu CM, Berberich-Siebelt F. Lymphoid aggregates in the CNS of progressive multiple sclerosis patients lack regulatory T cells. Front Immunol. 2019;10:3090.OpenUrl 21.↵Lehmann-Horn K, Wang SZ, Sagan SA, Zamvil SS, von Budingen HC. B cell repertoire expansion occurs in meningeal ectopic lymphoid tissue. JCI Insight. 2016;1(20):e87234.OpenUrl 22.↵Lehmann-Horn K, Kinzel S, Feldmann L, et al. Intrathecal anti-CD20 efficiently depletes meningeal B cells in CNS autoimmunity. Ann Clin Transl Neurol. 2014;1(7):490-496.OpenUrl 23.↵Krishnamoorthy G, Lassmann H, Wekerle H, Holz A. Spontaneous opticospinal encephalomyelitis in a double-transgenic mouse model of autoimmune T cell/B cell cooperation. J Clin Invest. 2006;116(9):2385-2392.OpenUrlCrossRefPubMed 24.↵Bettelli E, Baeten D, Jager A, Sobel RA, Kuchroo VK. Myelin oligodendrocyte glycoprotein-specific T and B cells cooperate to induce a Devic-like disease in mice. J Clin Invest. 2006;116(9):2393-2402.OpenUrlCrossRefPubMed 25.↵Dang AK, Tesfagiorgis Y, Jain RW, Craig HC, Kerfoot SM. Meningeal infiltration of the spinal cord by non-classically activated B cells is associated with chronic disease course in a spontaneous B cell-dependent model of CNS autoimmune disease. Front Immunol. 2015;6:470.OpenUrl 26.↵Kinzel S, Lehmann-Horn K, Torke S, et al. Myelin-reactive antibodies initiate T cell-mediated CNS autoimmune disease by opsonization of endogenous antigen. Acta Neuropathol. 2016;132(1):43-58.OpenUrlCrossRefPubMed 27.↵Varrin-Doyer M, Pekarek KL, Spencer CM, et al. Treatment of spontaneous EAE by laquinimod reduces Tfh, B cell aggregates, and disease progression. Neurol Neuroimmunol Neuroinflamm. 2016;3(5):e272. 28.↵Martin MdP, Cravens PD, Winger R, et al. Depletion of B Lymphocytes from cerebral perivascular spaces by rituximab. Arch Neurol. 2009;66(8):1016-1020.OpenUrlCrossRefPubMed 29.↵esfandi S, Salimian S, Corboy J, Alvarez E. Persistent B lymphocytes in multiple sclerosis plaques after rituximab treatment (P5.341). Neurology. 2017;88(16 suppl):P5.341.OpenUrl 30.↵Parker Harp CR, Archambault AS, Cheung M, et al. Neutrophils promote VLA-4-dependent B cell antigen presentation and accumulation within the meninges during neuroinflammation. Proc Natl Acad Sci USA. 2019;116(48):24221-24230. 31.↵Pipi E, Nayar S, Gardner DH, Colafrancesco S, Smith C, Barone F. Tertiary lymphoid structures: autoimmunity goes local. Front Immunol. 2018;9:1952.OpenUrlCrossRefPubMed 32.↵Neyt K, Perros F, GeurtsvanKessel CH, Hammad H, Lambrecht BN. Tertiary lymphoid organs in infection and autoimmunity. Trends Immunol. 2012;33(6):297-305.OpenUrlCrossRefPubMed 33.↵Jones GW, Hill DG, Jones SA. Understanding immune cells in tertiary lymphoid organ development: it is all starting to come together. Front Immunol. 2016;7:401.OpenUrl 34.↵Gago da Graca C, van Baarsen LGM, Mebius RE. Tertiary lymphoid structures: diversity in their development, composition, and role. J Immunol. 2021;206(2):273-281. 35.↵Carragher DM, Rangel-Moreno J, Randall TD. Ectopic lymphoid tissues and local immunity. Semin Immunol. 2008;20(1):26-42.OpenUrlCrossRefPubMed 36.↵Weber MS, Prod'homme T, Patarroyo JC, et al. B-cell activation influences T-cell polarization and outcome of anti-CD20 B-cell depletion in central nervous system autoimmunity. Ann Neurol. 2010;68(3):369-383.OpenUrlCrossRefPubMed

Abstract Objective The contemporary diagnosis of paraneoplastic neurologic syndromes (PNSs) requires an increasing understanding of their clinical, immunologic, and oncologic heterogeneity. The 2004 PNS criteria are partially outdated due to advances in PNS research in the last 16 years leading to the identification of new phenotypes and antibodies that have transformed the diagnostic approach to PNS. Here, we propose updated diagnostic criteria for PNS. Methods A panel of experts developed by consensus a modified set of diagnostic PNS criteria for clinical decision making and research purposes. The panel reappraised the 2004 criteria alongside new knowledge on PNS obtained from published and unpublished data generated by the different laboratories involved in the project. Results The panel proposed to substitute “classical syndromes” with the term “high-risk phenotypes” for cancer and introduce the concept of “intermediate-risk phenotypes.” The term “onconeural antibody” was replaced by “high risk” (>70% associated with cancer) and “intermediate risk” (30%–70% associated with cancer) antibodies. The panel classified 3 levels of evidence for PNS: definite, probable, and possible. Each level can be reached by using the PNS-Care Score, which combines clinical phenotype, antibody type, the presence or absence of cancer, and time of follow-up. With the exception of opsoclonus-myoclonus, the diagnosis of definite PNS requires the presence of high- or intermediate-risk antibodies. Specific recommendations for similar syndromes triggered by immune checkpoint inhibitors are also provided. Conclusions The proposed criteria and recommendations should be used to enhance the clinical care of patients with PNS and to encourage standardization of research initiatives addressing PNS. Glossary AMPAR=α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor; ANNA=antineuronal nuclear antibody; CASPR2=contactin-associated protein-like 2; CBA=cell-based assay; CRMP5=collapsin response-mediator protein 5; DNER=delta/notch-like epidermal growth factor-related receptor; EM=encephalomyelitis; GABABR=gamma-aminobutyric-acid B receptor; GAD65=glutamic acid decarboxylase 65; ICI=immune checkpoint inhibitor; IHC/IF=immunohistochemistry/immunofluorescence; irAE=immune-related adverse event; LE=limbic encephalitis; LEMS=Lambert-Eaton myasthenic syndrome; LGI1=leucine-rich glioma-inactivated 1; mGluR=metabotropic glutamate receptor; NSCLC=non-SCLC; OMS=opsoclonus-myoclonus syndrome; PCA=Purkinje cell antibody; PNS=paraneoplastic neurologic syndrome; SCLC=small-cell lung cancer; SNN=sensory neuronopathy; SPS=stiff-person syndrome; VGCC=voltage-gated calcium channel Paraneoplastic neurologic syndromes (PNSs) are remote effects of cancer with an immune-mediated pathogenesis.1,2 The diagnosis of PNS can be difficult and requires careful exclusion of direct involvement of the nervous system by cancer, such as brain metastasis or carcinomatous meningitis, and indirect involvement caused by coagulopathy, treatment-related neurotoxicity, metabolic problems, or infections.1,3 PNSs develop in approximately 1 of 300 patients with cancer.3 Few population-based epidemiologic studies have been performed in the field of PNS. Yet, stated incidence varies from 1.6 to 8.9 per million person-years, suggesting that underdiagnosis and underreporting are still relevant issues.3,4 It is likely that the expanding use of immune checkpoint inhibitors (ICIs) in oncologic practice will lead to an increased frequency of similar syndromes.5,6 In 2004, a set of recommended diagnostic criteria for PNS were defined by a panel of international experts and became the standard for clinical and research purposes.7 Since then, several advances in the field of PNS suggest that this is an opportune moment to update the 2004 criteria: first, the characterization of new intraneuronal proteins as targets of autoantibodies in PNS; second, the discovery of pathogenic antibodies against neuronal surface antigens in neurologic syndromes that can occur with or without cancer, a group which emphasizes the need for a new definition of an onconeural antibody; and third, some of the 2004 fundamental criteria needed to be redefined or modified. For example, the definition of definite PNS solely based on the presence of onconeural antibodies is no longer adequate. Similarly, in the elderly population, where the prevalence of some tumors is high (e.g., prostate cancer), the use of criteria that rely on generic tumor association may overestimate the real burden of PNS. In September 2019, a group of international experts (PNS-Care panel) was convened and charged with revising the diagnostic criteria of PNS to benefit clinical decision making, epidemiologic, and research purposes and to address the ancillary issues outlined above. The following report, which includes a newly developed clinical scoring system (PNS-Care Score), represents the panel's consensus recommendations. Methods The PNS-Care panel initially consisted of 14 investigators from 8 different countries; all members of the panel are neurologists with clinical and research expertise in PNS and related syndromes. The panel started with the premise that revised consensus diagnostic criteria for PNS were required to improve clinical care and support research. The group established 3 levels of certainty in the diagnosis of PNS (i.e., possible, probable, and definite PNS) according to the coherence between clinical phenotype, antibody, and cancer. In assessing the diagnostic process, the panel reviewed the experience and caveats with detection and interpretation of neuronal antibodies. In addition, new recommendations were considered for neurologic syndromes developing in the context of ICI treatment. It was agreed that several neurologic disorders that can occur in association with cancer are not included in the current diagnostic criteria, such as inflammatory myopathies (dermatomyositis, polymyositis, and necrotizing myopathies), myasthenia gravis, polyneuropathies associated with monoclonal gammopathies, and paraneoplastic retinopathy, optic neuritis, and cochlea-vestibulopathy. Well-designed diagnostic criteria already exist for most of these entities, which are historically not included within the spectrum of PNS. An initial draft of the guidelines was discussed during the inaugural meeting in Lyon (France) and subsequently underwent several iterations via electronic communication. The last version was then sent to all 14 members, in addition to 5 additional international experts, for final review and comment. All 19 PNS-Care panel members endorsed the final guidelines. Data Availability Data sharing is not applicable to this article as no new data were created or analyzed in this study. Results Definition of Paraneoplastic Neurologic Syndromes PNSs are defined as neurologic disorders that (1) can affect any part of the nervous system, often presenting with stereotyped clinical manifestations; (2) occur in association with cancer; and (3) have an immune-mediated pathogenesis that is supported by the frequent presence of specific neuronal antibodies. The 3 parts of this definition represent the main axes of discussion by the panel and constitute the structure of the present guidelines. High-Risk Neurologic Phenotypes There are no absolute pathognomonic neurologic presentations associated with PNS. However, the panel recognizes specific clinical presentations, here defined as “high-risk phenotypes” and previously known as “classical PNS,” frequently have a paraneoplastic etiology. In these phenotypes, cancer represents an important trigger, and therefore, their clinical recognition should lead to a search for an underlying cancer. The extent of cancer search may depend on the demographic characteristics of the patient (age, sex) and the type of neuronal antibody (see below). Despite numerous advances in the field of PNS in the last 16 years, including the discovery of new antibodies and novel clinical manifestations, the panel agrees that there are no new descriptions of high-risk phenotypes, and therefore, the list is as below: Encephalomyelitis Limbic encephalitis Rapidly progressive cerebellar syndrome Opsoclonus-myoclonus Sensory neuronopathy Gastrointestinal pseudo-obstruction (enteric neuropathy) Lambert-Eaton myasthenic syndrome Encephalomyelitis The term encephalomyelitis (EM) should be used only in patients with clinical dysfunction at multiple sites of the nervous system, including also peripheral involvement such as dorsal root ganglia, peripheral nerve or nerve roots, as recommended in the 2004 PNS criteria.7 These additional areas of involvement should be included in the description of the phenotype, for example, EM with dorsal root ganglionitis or sensory neuronopathy (SNN) or EM with peripheral neuropathy. EM almost always associates with small-cell lung cancer (SCLC) with Hu (also called antineuronal nuclear antibody 1, ANNA-1) or CV2/collapsin response-mediator protein 5 (CRMP5) antibodies.8,9 Limbic Encephalitis Limbic encephalitis (LE) usually presents with short-term memory loss, seizures, and psychiatric manifestations rapidly progressing in less than 3 months. The diagnostic criteria of LE were updated in 2016,10 and in this phenotype, the most advances have been made in terms of antibody discovery since 2004. At that time, paraneoplastic and autoimmune LEs were clearly underdiagnosed, and the frequency of reported cases was substantially lower compared with rapidly progressive cerebellar syndromes and sensory neuronopathies.11 Importantly, some of the most frequent cell surface antibodies associate with typically nonparaneoplastic forms of LE, such as leucine-rich glioma-inactivated 1 (LGI1) or contactin-associated protein-like 2 (CASPR2) antibodies.10 Therefore, the historical concept of LE as a phenotype predominantly associated with cancer has changed dramatically in the last 10 years. 12,13 However, because of multiple variants of LE, such as less common forms almost always associated with cancer, this disorder has been retained as a high-risk phenotype. This is important for 2 reasons: first, because the neurologic presentation of paraneoplastic and nonparaneoplastic cases can be undistinguishable, and second, because some of the associated antibodies (e.g., gamma-aminobutyric-acid B receptor [GABABR]14,15 and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor [AMPAR]16,17) can manifest as paraneoplastic LE in more than 50% of the cases. Although the presence of onconeural antibodies, such as anti-Hu and anti-Ma2, almost always occurs in adults and associate with an underlying cancer, the detection of Hu antibodies in children with LE is exceptionally rare and usually does not associate with cancer.18 Rapidly Progressive Cerebellar Syndrome This disorder, previously known as subacute cerebellar degeneration, is characterized by a rapidly progressive cerebellar syndrome, without substantial cerebellar atrophy at early stages of the disease. Cases with hyperacute onset, unilateral onset, or slowly progressive and insidious clinical course mimicking neurodegenerative diseases have also been reported,19,20 but in general, the patients rapidly develop a severe and bilateral cerebellar syndrome limiting activities of daily living in less than 3 months. The panel decided to avoid the term paraneoplastic cerebellar degeneration when referring to the clinical syndrome because the presentation of the cases with or without cancer can be indistinguishable. Although gait ataxia may be the main or sole initial feature, truncal and limb involvement later in the course of the disease are needed to define it as rapidly progressive cerebellar syndrome. Extracerebellar dysfunction, predominantly involving brainstem, may accompany the cerebellar features. Isolated cerebellar symptoms are typical of Yo (also known as PCA-1, Purkinje cell antibody 1)21 and Tr/delta/notch-like epidermal growth factor-related receptor (DNER) antibodies.22,23 Unlike LE, newly identified antibodies for paraneoplastic (and nonparaneoplastic autoimmune) rapidly progressive cerebellar syndrome have been reported only in isolated case reports or small series of patients (table e-1, links.lww.com/NXI/A491). Future research may help to clarify which aspects of cerebellar dysfunction correlate more with specific antibodies. Opsoclonus-Myoclonus Syndrome Opsoclonus-myoclonus syndrome (OMS) is characterized by involuntary, high-frequency, chaotic multidirectional saccadic movements without intersaccadic pauses, and nonrhythmic action myoclonus, often involving the trunk, limbs, and head. Additional features include cerebellar involvement (dysarthria and trunk ataxia) and encephalopathy (ranging from confusion to coma). Two main etiologies for OMS include paraneoplastic and idiopathic mechanisms, although there is increasing evidence suggesting that the latter is usually an immune-mediated, postinfectious process. Paraneoplastic OMS in children accounts for 50% of cases and is closely associated with neuroblastoma.24 Paraneoplastic OMS in adults frequently associates with SCLC or breast cancer. Patients with breast cancer and paraneoplastic OMS usually have Ri antibodies (also known as ANNA-2).20,25,26 Compared with adults with nonparaneoplastic OMS, those with paraneoplastic OMS are more likely to be older, develop encephalopathy, and have a poorer outcome.25 In young women, OMS may appear in association with ovarian teratomas without neuronal antibodies.27 Sensory Neuronopathy SNN refers to a phenotype caused by involvement of the sensory neurons of the dorsal root ganglia and manifesting with sensory deficits sometimes accompanied by motor symptoms due to additional involvement of motor nerve roots of peripheral nerves. SNN diagnosis (regardless of etiology) should follow previously reported criteria.28 The potential causes of SNN are diverse, including Sjögren syndrome or platinum-based chemotherapy, but a paraneoplastic origin should be especially considered if patients have inflammatory CSF or motor involvement.29 The terms sensorimotor/sensory neuropathy, polyradiculopathy, or polyradiculoneuropathy should be used when the clinical and electrophysiologic findings indicate additional involvement of the peripheral nerves or nerve roots. The most frequent antibody specificity for SNN is Hu, followed by CV2/CRMP5 and amphiphysin antibodies.8,30,31 Gastrointestinal Pseudo-obstruction This term applies to a clinical picture characterized by recurrent episodes of abdominal pain, distension, constipation, and/or vomiting, without evidence of mechanical obstruction.32 An abnormal gastric emptying or small bowel manometry confirms the diagnosis. Gastrointestinal pseudo-obstruction is due to a myenteric plexus dysfunction and may occur along with other features of autonomic involvement, SNN, or EM. The identification of Hu antibodies suggests a paraneoplastic origin,8,32 whereas antibodies against ganglionic acetylcholine receptor are more frequently seen in nonparaneoplastic cases.33 Lambert-Eaton Myasthenic Syndrome Lambert-Eaton myasthenic syndrome (LEMS) is characterized by the progressive development of proximal muscle weakness that usually starts in the lower limbs and follows with involvement of the upper limbs, distal muscles, and finally the ocular and bulbar muscles. About 90% of patients have symptoms of autonomic dysfunction, which is a hallmark of LEMS, including dry mouth, erectile dysfunction, and constipation. In addition to muscle weakness and dysautonomia, patients have decreased or absent muscle reflexes, which improve after repeat exercise or maximal voluntary contraction.34 Clinical suspicion must be confirmed with electrophysiologic studies.35 Antibodies against P/Q type voltage-gated calcium channels (VGCCs) are present in nearly 90% of the patients, although their detection is not needed for the diagnosis. These antibodies occur similarly in the paraneoplastic and nonparaneoplastic forms of the disease.34 Conversely, antiglial nuclear antibodies (or SOX1 antibodies) are strongly associated with SCLC or paraneoplastic syndromes associated with SCLC; therefore, their detection in patients with LEMS strongly suggests the presence of an underlying SCLC.36 In addition, the Dutch-English LEMS tumor association prediction score is based on clinical criteria and is useful in the discrimination between paraneoplastic and nonparaneoplastic LEMS.37 Intermediate-Risk Phenotypes Intermediate-risk phenotypes are neurologic disorders that can occur with or without cancer. The recognition of these phenotypes should prompt consideration of a PNS, particularly when no alternative explanation is found, and patients should be tested for neuronal specific antibodies. The Panel proposes to consider a possible intermediate-risk phenotype when the onset is rapidly progressive (<3 months) or there are inflammatory findings in the CSF or brain/spine MRI. The panel acknowledges that the list of possible intermediate-risk phenotypes is far from complete but listed below are some of the most suggestive ones: Encephalitis other than well-defined LE can be considered as intermediate risk phenotype if diagnostic criteria for possible autoimmune encephalitis are fulfilled and antibodies of high or intermediate risk are detected (see below and tables 1 and 2).10 This applies especially for those cases with multifocal or diffuse involvement not restricted to the limbic system, such as anti-mGluR5 (metabotropic glutamate receptor 5; associated with Hodgkin lymphoma),38 or anti-GABAAR encephalitis (gamma-aminobutyric-acid A receptor; associated with malignant thymoma in adult patients).39 View inline View popup Table 1 High-Risk Antibodies (>70% Associated With Cancer) View inline View popup Table 2 Intermediate-Risk Antibodies (30%–70% Associated With Cancer) A condition with well-defined diagnostic criteria but unusual oncologic associations is anti-NMDAR encephalitis.10 The panel considers this disease as an intermediate-risk phenotype because the presence of an associated tumor highly depends on age and sex.40 Children of both sexes and young adult men rarely have tumors but women aged between 18 and 35 years often have an ovarian teratoma, with frequencies ranging between 35% and 50%. In most cases, the teratoma is mature and therefore benign, yet pathologic studies show that they contain NMDAR-expressing neural tissue and often structures that may act as ectopic germinal centers, with tumor-resident NMDAR antibody–producing B cells, directly contributing to the PNS.41,42 Immature ovarian teratomas are less common but more frequent than in the general population,41 and other malignant tumors occur almost exclusively in elderly patients.43,44 Brainstem encephalitis usually presents with oculomotor abnormalities and bulbar symptoms (dysarthria, dysphagia), sometimes accompanied by abnormal movements or cerebellar dysfunction. Brainstem encephalitis may co-occur with LE and is strongly associated with Ma2 antibodies, usually with underlying testicular tumors or non-SCLC (NSCLC).45 Diencephalic involvement may accompany brainstem encephalitis in patients with Ma2 antibodies, characterized by excessive daytime sleepiness/narcolepsy, hyperphagia, hyperthermia, and endocrine abnormalities.45 The presence of bulbar dysfunction and central hypoventilation is characteristic of Hu antibodies,46 whereas OMS and jaw dystonia are common with Ri antibodies.20,47 Sensorineural deafness is frequent in brainstem encephalitis associated with KLHL11 antibodies and testicular cancer or teratomas.48,-,50 Morvan syndrome is defined by peripheral nerve hyperexcitability along with encephalopathy characterized by behavioral change, hallucinations, dysautonomia, and sleep disorders, especially agrypnia excitata. Importantly, the co-occurrence of LE and neuromyotonia should not be considered as a synonym of Morvan syndrome. Malignant thymoma is the tumor more commonly associated with Morvan syndrome, frequently accompanied by myasthenia gravis.51,52 Morvan syndrome is almost always associated with CASPR2 antibodies, sometimes with concurrent LGI1 and netrin 1 receptor antibodies.51,52 Isolated myelopathy as a paraneoplastic manifestation of cancer may have a variable clinical evolution and usually presents with longitudinally extensive, symmetric, tract or gray-matter specific abnormalities in MRI studies. It is mainly associated with breast and lung carcinomas, and with CV2/CRMP5 and amphiphysin antibodies.53 However, patients may not have neuronal antibodies, and in these cases, the possibility of a paraneoplastic origin should be considered when MRI is suggestive, and there are no alternative diagnoses. Stiff-person syndrome (SPS) is characterized by painful muscular spasms that can be spontaneous or triggered by activity or external sensory stimuli and occurs in association with stiffness due to coactivation of agonist and antagonist muscles. Paraneoplastic SPS is mostly associated with amphiphysin antibodies and breast cancer. Compared with the nonparaneoplastic SPS, usually associated with glutamic acid decarboxylase 65 (GAD65) antibodies, patients with amphiphysin-related paraneoplastic SPS are older and frequently have neck and upper limb involvement.54 Although some patients with anti–GAD65-associated SPS may have cancer, a paraneoplastic etiology should not be considered unless GAD65 is found expressed by the tumor cells. Besides focal variants of SPS (such as stiff-leg syndrome) that show the same antibody and tumor associations than classic SPS, another disorder lying within the SPS spectrum is progressive encephalomyelitis with rigidity and myoclonus, which usually presents with hyperekplexia, brainstem dysfunction, and dysautonomia, and is related mostly to glycine receptor antibodies in a nonparaneoplastic context.55,56 Paraneoplastic polyradiculoneuropathies have typically an axonal pattern and often present with concurrent CNS involvement. Pain, dysautonomia, and distribution (symmetric or asymmetric) are variable. The most frequent antibodies are CV2/CRMP5,30 amphiphysin,31 and PCA-2/microtubule-associated protein 1B,57 usually in the context of SCLC, or breast cancer also in association with amphiphysin antibodies. In patients with cancer, the development of neuropathies that fulfill the criteria of Guillain-Barré syndrome or chronic inflammatory demyelinating polyneuropathy should not be considered paraneoplastic unless a high-risk antibody is identified (table 1). Cancer Associated With PNS and Cancer Screening The panel agreed that the demonstration of a causal, not coincidental, association between the underlying tumor and the neurologic phenotype is crucial for the definite diagnosis of PNS. Although some progress has been made in the characterization of this pathogenic link, such as the identification of specific mutations or amplifications in the genes encoding for onconeural antigens in tumors of patients with PNS,58 in clinical practice, this link is suggested by: Epidemiologic Associations Clinical series indicate that distinct types of PNS preferentially associate with certain types of cancers, regardless of the presence or absence of antibodies, and type of antibody. For example, rapidly progressive cerebellar syndrome in postmenopausal women is frequently paraneoplastic, and the tumors more frequently involved are breast and ovarian cancer (in this case, patients usually have Yo antibodies). Another example is OMS in children with neuroblastoma (in this case, patients do not have a specific antibody). Antibody Associations Antibodies are important to guide the search for an underlying tumor. In the context of PNS, 3 groups of antibodies can be considered according to the frequency of cancer association regardless of their eventual pathogenic effect. The first group includes antibodies that occur very frequently (>70%) in patients with an underlying cancer (table 1). In the 2004 PNS criteria, these antibodies were defined as onconeural antibodies to emphasize the link between cancer and brain. However, it is now clear that some antibodies associate less frequently with cancer, for example, AMPAR and NMDAR, and the target antigens are expressed in both the neurons and the tumor. On the other hand, some of the antigens of classical onconeural antibodies (such as Tr/DNER) are not expressed in the associated tumor (Hodgkin lymphoma). For this reason, the panel proposes to substitute the term onconeural, which implies the obligatory expression of the antigen by the nervous system and cancer, for the term high risk. Most high-risk antibodies target intracellular antigens and are currently considered not to be directly pathogenic but only good biomarkers of PNS. The second group of antibodies occur in association with cancer in 30%–70% of cases (table 2). Finally, the third group of antibodies have a much lower (<30%), or absent, association with cancer (table 3). In cases of PNS without antibodies, the involvement of a tumor is more difficult to demonstrate as it may be coincidental and not pathogenically linked. The tumors more frequently associated with PNS irrespective of the antibody status are SCLC, breast cancer, ovarian cancer, NSCLC, and lymphomas.13,59,60,e1 View inline View popup Table 3 Lower-Risk Antibodies (<30% Associated With Cancer) In clinical practice, the indicated antibody associations with cancer have important clinical implications. For a specific phenotype, for example, LE, the presence of one antibody vs another suggests the likelihood of having a tumor or not and directs the tumor search. For example, patients with LE and LGI1 antibodies rarely have a tumor, whereas at least 50% of patients with GABABR antibodies have SCLC,14,15 more than 50% of patients with AMPAR antibodies have thymoma, lung, or breast cancer,16,17 and most (>85%) patients with Hu antibodies have SCLC.8 These antibody-tumor associations can show age and sex dependence; for example, NMDAR antibodies rarely associate with tumors in young children or young adult male patients.40 Very rarely, Hu18 or GABABRe2, e3 antibodies can be identified in children with epileptic encephalopathy, and these patients almost never have cancer. Expression of Neural Antigens by the Tumor In some clinical research settings (e.g., unexpected tumor and antibody concurrence), the demonstration that the tumor expresses the cognate antigen is critical to pathogenically associate it with the PNS (i.e., Yo antibodies in a man with gastric adenocarcinoma).e4 Similar studies are needed when there is limited experience with the PNS or associated antibody (i.e., mGluR2 antibodies and rapidly progressive cerebellar syndrome with sarcoma).e5 Cancer screening should be promptly undertaken when a PNS is suspected and should be guided by the type of phenotype or antibody (tables 1 and 2). Patients can have more than 1 tumor; thus, if the identified tumor is atypical for the type of suspected phenotype or antibody, additional studies for a second tumor should be considered.e6 Recommendations according to the type of suspected tumor are shown in table e-2 (links.lww.com/NXI/A491).21,e6-e16 When initial tumor screening is negative, it should be repeated every 4–6 months for 2 years in patients with high-risk phenotypes along with high-risk antibodies (table 1). The panel decided to establish this time frame based on the members' clinical experience and the evidence from the literature showing that a vast majority of the tumors are diagnosed within 2 years after PNS onset8,21,-,23,26,30,31,45,48,e15-e18; however, this is a general recommendation that should be adapted to every individual case according to risk factors, clinical evolution, and medical resources. The same applies to patients with high-risk phenotypes along with intermediate risk antibodies (table 2) who show particular demographic characteristics (older age and smoking) or have concurrent antibodies with strong cancer association (e.g., P/Q VGCC and SOX1 antibodies in LEMS). For patients who do not fulfill these criteria, and those with lower risk antibodies (table 3), a comprehensive screening for cancer by the time of initial diagnostic assessment is sufficient. Tumor rescreening could be considered in some clinical settings, such as patients refractory to treatment or with relapsing neurologic diseases (e.g., anti-NMDAR encephalitis). Neuronal Antibodies as Biomarkers in PNS Although PNS can be diagnosed without neuronal antibody testing (e.g., pediatric OMS and neuroblastoma; LEMS and SCLC), the demonstration of neuronal antibodies is of extraordinary help in the diagnosis of PNS, and these antibodies have become very important biomarkers of PNS. Gold standard detection methods include rodent brain tissue immunohistochemistry/immunofluorescence (IHC/IF) accompanied by confirmatory studies using immunoblot with recombinant proteins (for most antibodies directed to intracellular antigens) or cell-based assays (CBAs, for antibodies against cell surface or synaptic proteins).e19,e20 Brain immunohistochemistry is not useful for 2 antibodies (P/Q type VGCC, glycine receptor antibodies), and the utility of tissue immunohistochemistry is unclear (pending to be better defined) for SOX1 antibody. Recommendations for antibody testing are shown in table 4. View inline View popup Table 4 Recommendations for Antibody Testing in PNS Sensitivity and specificity for serum or CSF analysis vary among different antibodies; it is therefore recommended to perform antibody testing in both samples. Laboratory studies using CBA with serum only have similar problems of false-positive and -negative results. For all suspected autoimmune or paraneoplastic encephalitis associated with antibodies against neuronal surface antigens, screening of CSF should be obligatory to avoid mistakes. Patients with neuronal surface antibodies detected in serum only (CSF negative) should be re-examined in a research laboratories or with confirmatory tissue IHC/IF before considering a definite diagnosis. On the other hand, some antibodies (e.g., against LGI1) are best detected in serum, with CSF showing lower sensitivity. Despite the indicated gold standard techniques mentioned above (brain IHC/IF and CBA), very few laboratories use both techniques. Commercial kits that test multiple antibodies may be helpful. However, often, the kits detect antibodies of limited clinical value for diagnosis of PNS along with antibodies with well-known clinical and cancer associations that have been validated across different specialized centers. Although commercial line blot kits for antibody detection are useful for the initial screening of patients, the number of false-positive and -negative results is particularly high for line blots assessing Yo, Ma2, CV2/CRMP5, and SOX1 antibodies.e21-e25 Unexpected antibody results based on the type of neurologic phenotype, tumor, or patient's age and sex should raise concern for false-positive results and be reassessed with additional studies, preferably in research laboratories. Similarly, reference laboratories should perform the antibody testing in patients with high suspicion for PNS but negative routine screening of antibodies in clinical or commercial laboratories.e21,e22 Several antibodies, mostly related to rapidly progressive cerebellar syndrome, are not well characterized yet, because they have been described recently, in small series or isolated case reports, or there is limited experience across different research laboratories (table e-1, links.lww.com/NXI/A491). Further studies involving larger series are needed to confirm the clinical and oncologic associations of these new antibodies and require input of research laboratories to forward the accuracy of patient diagnoses. Diagnostic Criteria for PNS The diagnosis of PNS requires the reasonable exclusion of alternative causes that sometimes are much more prevalent. The differential diagnosis of PNS is wide, as it includes infections, autoimmune nonparaneoplastic diseases, tumors, neurodegenerative disorders, and toxic/metabolic disturbances. Most of these alternative diagnoses are epidemiologically more frequent than PNS, and some of them are treatable; therefore, there is an important need to readily identify them. The differential diagnosis should be based on the clinical presentation and patient's demographic features (table e-3, links.lww.com/NXI/A491). After that, 3 levels of diagnostic certainty are proposed (possible, probable, and definite PNS) based on a scoring system (PNS-Care Score) that considers the type of clinical phenotype, presence or absence of neuronal antibodies, and presence or absence of cancer (table 5). View inline View popup Table 5 PNS-Care Score The panel recognizes that the proposed criteria may underestimate the occurrence of cases of PNS without neuronal antibodies, but the use of these biomarkers provides unambiguous diagnostic certainty and enables to homogenize samples for research purposes. According to these criteria, the diagnosis of definite PNS (score ≥8) includes the presence of a high- or intermediate-risk phenotype (as previously described) along with a high- or intermediate-risk antibody, and the presence of cancer. The presence of cancer is mandatory to define definite PNS. If the cancer is unusual for the type of antibody found, the diagnosis of definite PNS requires the demonstration of antigen expression by the tumor. The panel proposed as exception the OMS associated with neuroblastoma or SCLC in which there is no specific antibody association. Therefore, although this syndrome provides a score of 7, it should be considered definite PNS when associated with these tumors. The panel also acknowledges that the present criteria do not identify as definite PNS neurologic syndromes associated with cancer and low-risk antibodies even if tumor cells express the neuronal antigen recognized by the antibody (e.g, neuromyelitis optica with aquaporin 4 antibodies and concurrent lung adenocarcinoma that expresses aquaporin 4). Note that the diagnostic level of probable or possible PNS (table 5) may change over time according to the length of follow-up, greater or less than 2 years. For example, a patient with LEMS, VGCC antibodies but no cancer at diagnosis has a score of 6 (probable). If an SCLC is found 18 months later, the diagnosis will be upgraded to definite (score 9), but if no cancer is found after >2 years, the diagnosis will be downgraded to possible (score 5). The Era of Immune Checkpoint Inhibitors ICIs enhance antitumor immunity by blocking immune checkpoint molecules expressed in T lymphocytes and tumor cells including programmed cell death protein 1, its ligand, and cytotoxic T-lymphocyte–associated antigen 4.e26 The adoption of ICI treatment in oncologic practice has led to increased survival and long-term remissions, even in patients with extensive metastatic cancer.e26 The major downside of ICIs is the possibility of developing immune-related adverse events (irAEs),e27 including severe (grade 3 or higher) neurologic syndromes (1%–3% of the cases).5,e28 These include the worsening of preexisting and de novo development of autoimmune neurologic diseases. The panel recommends that the first step in approaching these disorders is to determine whether the syndrome fulfills the above-mentioned criteria for PNS, after having excluded other alternative etiologies (e.g., carcinomatous meningitis).e29 Both peripheral and CNS complications have been described.e30,e31 There is already evidence that specific neurologic syndromes (e.g., those associated with Ma2 and Hu antibodies) can be triggered by cancer immunotherapy.6,e32 Nevertheless, a substantial proportion of cases remain seronegative despite comprehensive screening, and the detection of antibodies is not required for the diagnosis of irAEs. Although classical PNSs are known to precede the discovery of cancer, neurologic syndromes triggered by ICIs by definition develop when the cancer is already diagnosed, in general shortly after the initiation of ICIs. Of interest, for the few patients who developed antibody-associated irAEs and samples taken before ICI introduction were available, the retrospective analysis revealed the presence of Ma2 or Hu antibodies before the onset of PNS in 4 cases,6,e33-e35 similarly to what it was observed in 3 cases of ICI-triggered myasthenia gravis.e36-e38 The optimal management of ICI-induced neurologic autoimmunity has not been established and is beyond the scope of this diagnostic guidelines, but the panel recommended the following considerations: (1) neuronal antibody testing needs to be routinely performed in all patients developing neurologic irAEs resembling high or intermediate risk PNS; (2) patients with current or previous PNS are at a higher risk of developing neurologic worsening if treated with ICIs, and therefore, the risk/benefit ratio of ICI should be carefully weighted in this setting. For example, 50% of cases with preexistent PNS worsened during ICI treatment in a recent studye39; (3) future studies should address the potential value of assessing neuronal antibodies before starting ICIs, particularly in patients harboring cancers with tendency to associate with PNS (e.g., lung, breast, and ovary cancer); (4) close neurologic follow-up of antibody-positive cases is recommended. Final Comments The evaluation of suspected PNS and their management requires detailed (and evolving) knowledge, so as to permit timely and accurate diagnosis of these uncommon disorders. Unambiguous diagnostic criteria facilitate both timely diagnosis (which may affect the neurologic and oncologic outcome) and avoidance of overdiagnosis and unnecessary treatments. In addition, these criteria represent an important research tool for epidemiologic studies and to analyze the value of new antibodies for the diagnosis of PNS. For the reasons stated in the introduction, modification of the 2004 criteria was necessary to accommodate the new knowledge generated in the last 16 years. The update criteria presented here (1) include novel phenotypes and immune-mediated pathogenic mechanisms identified since 2004; (2) emphasize a causal (and not merely chronological) association with cancer; and (3) require the demonstration of neuronal antibodies using gold standard techniques. These 3 elements represent the core of the present criteria of PNS that we hope will be of help to clinicians and researchers. Study Funding This study is supported by FRM (Fondation pour la recherche médicale, DQ20170336751) and has been developed within the BETPSY project, which is supported by a public grant overseen by the French National Research Agency (ANR), as part of the second “Investissements d'Avenir” program (reference ANR-18-RHUS-0012). This research was funded in whole, or in part, by the Wellcome Trust (Grant number 104079/Z/14/Z). One of the authors (M.J.T.) of this publication is a member of the European Reference Network for Rare Immunodeficiency, Autoinflammatory and Autoimmune Diseases—Project ID No 739543. S.R. Irani is supported by the Wellcome Trust (104079/Z/14/Z), the UCB-Oxford University Alliance, BMA Research Grants—Vera Down grant (2013) and Margaret Temple (2017), Epilepsy Research UK (P1201), the Fulbright UK-US commission (MS-Society research award), and by the NIHR Oxford Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. Disclosure F. Graus receives royalties from licensing fees to Euroimmun for the use of IgLON5 as a diagnostic test. A. Vogrig reported receiving a fellowship grant from the European Academy of Neurology (EAN). S. Muñiz-Castrillo, J.-C.G. Antoine, V. Desestret, D. Dubey, and B. Giometto report no disclosures relevant to the manuscript. S.R. Irani is a coapplicant and receives royalties on patent application WO/210/046716 (U.K. patent no., PCT/GB2009/051441) entitled “Neurological Autoimmune Disorders.” The patent has been licensed for the development of assays for LGI1 and other VGKC-complex antibodies. S.R. Irani has filed a patent on a Diagnostic Strategy to improve specificity of antibody detection. S.R. Irani has received honoraria from UCB, MedImmune, ADC Therapeutics, Immunovant, Brain, Medlink Neurology and research support from CSL Behring, UCB, and ONO Pharma. B. Joubert, F. Leypoldt, A. McKeon, H. Prüss, D. Psimaras, L. Thomas, M.J. Titulaer, C.A. Vedeler, and J. Verschuuren report no disclosures relevant to the manuscript. J. Dalmau receives royalties from licensing fees to Athena Diagnostics for a patent for the use of Ma2 as an autoantibody test; licensing fees to Euroimmun for patents for the use of NMDA receptor and GABAB receptor as autoantibody tests; licensing fees for the use of DPPX, GABAA receptor, and IgLON5 antibodies as diagnostic tests; and has received a research grant from Euroimmun. J. Honnorat receives royalties from licensing fees to Athena Diagnostics, Euroimmun, and Ravo Diagnostika for a patent for the use of CV2/CRMP5 as diagnostic tests. None of the funding sources had any influence in the preparation of this Position Paper. Go to Neurology.org/NN for full disclosures. Appendix Authors Footnotes Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article. ↵* These authors contributed equally to this work. The Article Processing Charge was funded by Wellcome Trust. Editorial, page e1015 Received November 18, 2020. Accepted in final form February 22, 2021. Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. References 1.↵Honnorat J, Antoine JC. Paraneoplastic neurological syndromes. Orphanet J Rare Dis. 2007;2(1):22.OpenUrlCrossRefPubMed 2.↵Darnell RB, Posner JB. Paraneoplastic syndromes involving the nervous system. N Engl J Med. 2003;349(3):1543-1554.OpenUrlCrossRefPubMed 3.↵Vogrig A, Gigli GL, Segatti S, et al. Epidemiology of paraneoplastic neurological syndromes: a population-based study. J Neurol. 2019;267(1):26-35.OpenUrl 4.↵Hébert J, Riche B, Vogrig A, et al. Epidemiology of paraneoplastic neurologic syndromes and autoimmune encephalitides in France. Neurol Neuroimmunol Neuroinflamm. 2020;7(6):e883. 5.↵Graus F, Dalmau J. Paraneoplastic neurological syndromes in the era of immune-checkpoint inhibitors. Nat Rev Clin Oncol. 2019;16(9):535-548.OpenUrlPubMed 6.↵Vogrig A, Fouret M, Joubert B, et al. Increased frequency of anti-Ma2 encephalitis associated with immune checkpoint inhibitors. Neurol Neuroimmunol Neuroinflamm. 2019;6(6):e604. 7.↵Graus F, Delattre JY, Antoine JC, et al. Recommended diagnostic criteria for paraneoplastic neurological syndromes. J Neurol Neurosurg Psychiatry. 2004;75(8):1135-1140. 8.↵Graus F. Anti-Hu-associated paraneoplastic encephalomyelitis: analysis of 200 patients. Brain. 2001;124(pt 6):1138-1148.OpenUrlCrossRefPubMed 9.↵Yu Z, Kryzer TJ, Griesmann GE, Kim K, Benarroch EE, Lennon VA. CRMP-5 neuronal autoantibody: marker of lung cancer and thymoma-related autoimmunity. Ann Neurol. 2001;49(2):146-154.OpenUrlCrossRefPubMed 10.↵Graus F, Titulaer MJ, Balu R, et al. A clinical approach to diagnosis of autoimmune encephalitis. Lancet Neurol. 2016;15(4):391-404.OpenUrlCrossRefPubMed 11.↵Giometto B, Grisold W, Vitaliani R, et al. Paraneoplastic neurologic syndrome in the PNS Euronetwork database: a European study from 20 centers. Arch Neurol. 2010;67(3):330-335.OpenUrlCrossRefPubMed 12.↵Dubey D, Pittock SJ, Kelly CR, et al. Autoimmune encephalitis epidemiology and a comparison to infectious encephalitis: autoimmune Encephalitis. Ann Neurol. 2018;83(1):166-177.OpenUrlCrossRefPubMed 13.↵Graus F, Escudero D, Oleaga L, et al. Syndrome and outcome of antibody-negative limbic encephalitis. Eur J Neurol. 2018;25(8):1011-1016.OpenUrlCrossRef 14.↵Hoftberger R, Titulaer MJ, Sabater L, et al. Encephalitis and GABAB receptor antibodies: novel findings in a new case series of 20 patients. Neurology. 2013;81(17):1500-1506.OpenUrlCrossRefPubMed 15.↵Jeffery OJ, Lennon VA, Pittock SJ, Gregory JK, Britton JW, McKeon A. GABAB receptor autoantibody frequency in service serologic evaluation. Neurology. 2013;81:(10)882-887.OpenUrlCrossRefPubMed 16.↵Hoftberger R, van Sonderen A, Leypoldt F, et al. Encephalitis and AMPA receptor antibodies: novel findings in a case series of 22 patients. Neurology. 2015;84(24):2403-2412.OpenUrlPubMed 17.↵Joubert B, Kerschen P, Zekeridou A, et al. Clinical spectrum of encephalitis associated with antibodies against the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor: case series and review of the literature. JAMA Neurol. 2015;72(10):1163.OpenUrl 18.↵Honnorat J, Didelot A, Karantoni E, et al. Autoimmune limbic encephalopathy and anti-Hu antibodies in children without cancer. Neurology. 2013;80(24):2226-2232.OpenUrlCrossRefPubMed 19.↵Vogrig A, Bernardini A, Gigli GL, et al. Stroke-like presentation of paraneoplastic cerebellar degeneration: a single-center experience and review of the literature. Cerebellum. 2019;18(5):976-982.OpenUrl 20.↵Simard C, Vogrig A, Joubert B, et al. Clinical spectrum and diagnostic pitfalls of neurologic syndromes with Ri antibodies. Neurol Neuroimmunol Neuroinflamm. 2020;7(3):e699. 21.↵McKeon A. Purkinje cell cytoplasmic autoantibody type 1 accompaniments: the cerebellum and beyond. Arch Neurol. 2011;68(10):1282.OpenUrlCrossRefPubMed 22.↵Bernal F, Shams'ili S, Rojas I, et al. Anti-Tr antibodies as markers of paraneoplastic cerebellar degeneration and Hodgkin's disease. Neurology. 2003;60(2):230-234.OpenUrlCrossRefPubMed 23.↵de Graaff E, Maat P, Hulsenboom E, et al. Identification of delta/notch-like epidermal growth factor-related receptor as the Tr antigen in paraneoplastic cerebellar degeneration. Ann Neurol. 2012;71(6):815-824.OpenUrlCrossRefPubMed 24.↵Pranzatelli MR, Tate ED, McGee NR. Demographic, clinical, and immunologic features of 389 children with opsoclonus-myoclonus syndrome: a cross-sectional study. Front Neurol. 2017;8:468.OpenUrl 25.↵Armangué T, Sabater L, Torres-Vega E, et al. Clinical and immunological features of opsoclonus-myoclonus syndrome in the era of neuronal cell surface antibodies. JAMA Neurol. 2016;73(4):417.OpenUrl 26.↵Pittock SJ, Lucchinetti CF, Lennon VA. Anti-neuronal nuclear autoantibody type 2: paraneoplastic accompaniments. Ann Neurol. 2003;53(5):580-587.OpenUrlCrossRefPubMed 27.↵Armangue T, Titulaer MJ, Sabater L, et al. A novel treatment-responsive encephalitis with frequent opsoclonus and teratoma. Ann Neurol. 2014;75(3):435-441.OpenUrl 28.↵Camdessanché JP, Jousserand G, Ferraud K, et al. The pattern and diagnostic criteria of sensory neuronopathy: a case-control study. Brain. 2009;132(pt 7):1723-1733.OpenUrlCrossRefPubMed 29.↵Camdessanché JP, Jousserand G, Franques J, et al. A clinical pattern-based etiological diagnostic strategy for sensory neuronopathies: a French collaborative study. J Peripher Nerv Syst JPNS. 2012;17(3):331-340.OpenUrl 30.↵Dubey D, Lennon VA, Gadoth A, et al. Autoimmune CRMP5 neuropathy phenotype and outcome defined from 105 cases. Neurology. 2018;90(2):e103-e110.OpenUrl 31.↵Dubey D, Jitprapaikulsan J, Bi H, et al. Amphiphysin-IgG autoimmune neuropathy: a recognizable clinicopathologic syndrome. Neurology. 2019;93(20):e1873-e1880.OpenUrl 32.↵Lee HR, Prather CM. Paraneoplastic gastrointestinal motor dysfunction: clinical and laboratory characteristics. Am J Gastroenterol. 2001;96(2):7.OpenUrl 33.↵Li Y, Jammoul A, Mente K, et al. Clinical experience of seropositive ganglionic acetylcholine receptor antibody in a tertiary neurology referral center. Muscle Nerve. 2015;52(3):386-391.OpenUrlPubMed 34.↵Titulaer MJ, Lang B, Verschuuren JJ. Lambert-Eaton myasthenic syndrome: from clinical characteristics to therapeutic strategies. Lancet Neurol. 2011;10(12):1098-1107.OpenUrlCrossRefPubMed 35.↵Oh SJ, Kurokawa K, Claussen GC, Ryan HF. Electrophysiological diagnostic criteria of Lambert-Eaton myasthenic syndrome. Muscle Nerve. 2005;32(4):515-520.OpenUrlCrossRefPubMed 36.↵Graus F, Vincent A, Pozo-Rosich P, et al. Anti-glial nuclear antibody: marker of lung cancer-related paraneoplastic neurological syndromes. J Neuroimmunol. 2005;165(1-2):166-171.OpenUrlCrossRefPubMed 37.↵Titulaer MJ, Maddison P, Sont JK, et al. Clinical Dutch-English Lambert-Eaton Myasthenic syndrome (LEMS) tumor association prediction score accurately predicts small-cell lung cancer in the LEMS. J Clin Oncol. 2011;29(7):902-908. 38.↵Spatola M, Sabater L, Planagumà J, et al. Encephalitis with mGluR5 antibodies: symptoms and antibody effects. Neurology. 2018;90(22):e1964-e1972.OpenUrl 39.↵Spatola M, Petit-Pedrol M, Simabukuro MM, et al. Investigations in GABA A receptor antibody-associated encephalitis. Neurology. 2017;88(11):1012-1020.OpenUrlPubMed 40.↵Titulaer MJ, McCracken L, Gabilondo I, et al. Treatment and prognostic factors for long-term outcome in patients with anti-NMDA receptor encephalitis: an observational cohort study. Lancet Neurol. 2013;12(2):157-165.OpenUrlCrossRefPubMed 41.↵Chefdeville A, Treilleux I, Mayeur ME, et al. Immunopathological characterization of ovarian teratomas associated with anti-N-methyl-D-aspartate receptor encephalitis. Acta Neuropathol Commun. 2019;7:38.OpenUrl 42.↵Makuch M, Wilson R, Al-Diwani A, et al. N-methyl-D-aspartate receptor antibody production from germinal center reactions: therapeutic implications. Ann Neurol. 2018;83(3):553-561.OpenUrlPubMed 43.↵Titulaer MJ, McCracken L, Gabilondo I, et al. Late-onset anti-NMDA receptor encephalitis. Neurology. 2013;81(12):1058-1063.OpenUrlCrossRefPubMed 44.↵Bost C, Chanson E, Picard G, et al. Malignant tumors in autoimmune encephalitis with anti-NMDA receptor antibodies. J Neurol. 2018;265(10):2190-2200.OpenUrl 45.↵Dalmau J, Graus F, Villarejo A, et al. Clinical analysis of anti-Ma2-associated encephalitis. Brain. 2004;127(pt 8):1831-1844.OpenUrlCrossRefPubMed 46.↵Saiz A, Bruna J, Stourac P, et al. Anti-Hu-associated brainstem encephalitis. J Neurol Neurosurg Psychiatry. 2008;80(4):404-407.OpenUrl 47.↵Pittock SJ, Parisi JE, McKeon A, et al. Paraneoplastic jaw dystonia and laryngospasm with antineuronal nuclear autoantibody type 2 (anti-Ri). Arch Neurol. 2010;67(9):1109-1115.OpenUrlCrossRefPubMed 48.↵Mandel-Brehm C, Dubey D, Kryzer TJ, et al. Kelch-like protein 11 antibodies in seminoma-associated paraneoplastic encephalitis. N Engl J Med. 2019;381:47-54.OpenUrlCrossRefPubMed 49.↵Maudes E, Landa J, Muñoz-Lopetegi A, et al. Clinical significance of Kelch-like protein 11 antibodies. Neurol Neuroimmunol Neuroinflamm. 2020;7(3):e666. 50.↵Dubey D, Wilson MR, Clarkson B, et al. Expanded clinical phenotype, oncological associations, and immunopathologic insights of paraneoplastic Kelch-like protein-11 encephalitis. JAMA Neurol. 2020;77(11):1-10.OpenUrl 51.↵Irani SR, Pettingill P, Kleopa KA, et al. Morvan syndrome: clinical and serological observations in 29 cases. Ann Neurol. 2012;72(2):241-255.OpenUrlCrossRefPubMed 52.↵Muñiz-Castrillo S, Joubert B, Elsensohn MH, et al. Anti-CASPR2 clinical phenotypes correlate with HLA and immunological features. J Neurol Neurosurg Psychiatry. 2020;91(10):1076-1084. 53.↵Flanagan EP, McKeon A, Lennon VA, et al. Paraneoplastic isolated myelopathy: clinical course and neuroimaging clues. Neurology. 2011;76(24):2089-2095.OpenUrlCrossRefPubMed 54.↵Murinson BB, Guarnaccia JB. Stiff-person syndrome with amphiphysin antibodies. Neurology. 2008;71(24):1955-1958.OpenUrlCrossRef 55.↵Carvajal-González A, Leite MI, Waters P, et al. Glycine receptor antibodies in PERM and related syndromes: characteristics, clinical features and outcomes. Brain. 2014;137(pt 8):2178-2192.OpenUrlCrossRefPubMed 56.↵Hinson SR, Lopez-Chiriboga AS, Bower JH, et al. Glycine receptor modulating antibody predicting treatable stiff-person spectrum disorders. Neurol Neuroimmunol Neuroinflamm. 2018;5(2):e438. 57.↵Jitprapaikulsan J, Klein CJ, Pittock SJ, et al. Phenotypic presentations of paraneoplastic neuropathies associated with MAP1B-IgG. J Neurol Neurosurg Psychiatry. 2020;91(3):328-330.OpenUrlFREE Full Text 58.↵Small M, Treilleux I, Couillault C, et al. Genetic alterations and tumor immune attack in Yo paraneoplastic cerebellar degeneration. Acta Neuropathol (Berl). 2018;135(4):569-579.OpenUrl 59.↵Ducray F, Demarquay G, Graus F, et al. Seronegative paraneoplastic cerebellar degeneration: the PNS Euronetwork experience. Eur J Neurol. 2014;21(5):731-735.OpenUrl 60.↵Gultekin SH, Rosenfeld MR, Voltz R, et al. Paraneoplastic limbic encephalitis: neurological symptoms, immunological findings and tumour association in 50 patients. Brain. 2000;123(pt 7):1481-1494.OpenUrlCrossRefPubMed

T cells that react to alpha-synuclein are most abundant in the early stages of Parkinson's disease but tend to disappear as the disease progresses. Signs of autoimmunity can appear in Parkinson's patients up to ten years before a diagnosis of the neurodegenerative disease.

Abstract At steady state, the CNS parenchyma has few to no lymphocytes and less potent Ag-presentation capability compared with other organs. However, the meninges surrounding the CNS host diverse populations of immune cells that influence how CNS-related immune responses develop. Interstitial and cerebrospinal fluid produced in the CNS is continuously drained, and recent advances have emphasized that this process is largely taking place through the lymphatic system. To what extent this fluid process mobilizes CNS-derived Ags toward meningeal immune cells and subsequently the peripheral immune system through the lymphatic vessel network is a question of significant clinical importance for autoimmunity, tumor immunology, and infectious disease. Recent advances in understanding the role of meningeal lymphatics as a communicator between the brain and peripheral immunity are discussed in this review. Footnotes This work was supported by grants from the National Institutes of Health (AG034113, AG057496, and NS096967) to J.K. Abbreviations used in this article: AQP4 aquaporin-4 water channel DC dendritic cell EAE experimental autoimmune encephalomyelitis ISF interstitial fluid. Received July 17, 2019. Accepted November 15, 2019. Copyright © 2020 by The American Association of Immunologists, Inc.

Research ArticleImmunologyNeuroscience Free access | 10.1172/JCI128475 Early adaptive immune activation detected in monozygotic twins with prodromal multiple sclerosis Eduardo Beltrán,1 Lisa Ann Gerdes,1 Julia Hansen,1 Andrea Flierl-Hecht,1 Stefan Krebs,2 Helmut Blum,2 Birgit Ertl-Wagner,3,4 Frederik Barkhof,5,6 Tania Kümpfel,1 Reinhard Hohlfeld,1,7 and Klaus Dornmair1,7 First published September 30, 2019 - More info Abstract Multiple sclerosis (MS) is a disabling disease of the CNS. Inflammatory features of MS include lymphocyte accumulations in the CNS and cerebrospinal fluid (CSF). The preclinical events leading to established MS are still enigmatic. Here we compared gene expression patterns of CSF cells from MS-discordant monozygotic twin pairs. Six “healthy” co-twins, who carry a maximal familial risk for developing MS, showed subclinical neuroinflammation (SCNI) with small MRI lesions. Four of these subjects had oligoclonal bands (OCBs). By single-cell RNA sequencing of 2752 CSF cells, we identified clonally expanded CD8+ T cells, plasmablasts, and, to a lesser extent, CD4+ T cells not only from MS patients but also from subjects with SCNI. In contrast to nonexpanded T cells, clonally expanded T cells showed characteristics of activated tissue-resident memory T (TRM) cells. The TRM-like phenotype was detectable already in cells from SCNI subjects but more pronounced in cells from patients with definite MS. Expanded plasmablast clones were detected only in MS and SCNI subjects with OCBs. Our data provide evidence for very early concomitant activation of 3 components of the adaptive immune system in MS, with a notable contribution of clonally expanded TRM-like CD8+ cells. Graphical Abstract Introduction Multiple sclerosis (MS) is the most frequent inflammatory disease of the central nervous system (CNS). A variety of lymphocyte subtypes invade the brain parenchyma, where they sustain chronic inflammation and contribute to characteristic lesion formation. The current concepts of MS pathogenesis and treatment have been mainly shaped by autoimmune animal models, with a strong emphasis on autoreactive CD4+ T effector lymphocytes (1–4). In contrast to animal models, it has been difficult to investigate the early phase of the disease process in humans, because the diagnosis of MS requires the occurrence of a first clinical episode, which is known to be preceded by an undetermined period of subclinical neuroinflammation. It has therefore been very difficult to distinguish between early, potentially primary, and later, potentially secondary, immunological mechanisms. Here we took a 2-pronged approach to investigate the earliest identifiable stages of MS, which we refer to as subclinical neuroinflammation (SCNI), in familially predisposed subjects. First, we identified a small cohort of monozygotic twins in whom one sibling has clinically definite MS and the other is clinically “healthy” but has MRI and/or immunological evidence for SCNI. Second, we applied single-cell whole transcriptome sequencing (scRNA-Seq) to analyze cerebrospinal fluid (CSF) samples from MS-discordant twin pairs and controls. In contrast to traditional flow cytometry, which is restricted to very limited panels of antibodies against preselected markers, this technology gives an unbiased overview of expression patterns of thousands of genes expressed in each single cell at the time of lumbar puncture. This technology offers novel insights into the complexities of the human immune system and of disease-relevant cell populations (5, 6). We found that clonal expansions of CD8+ T cells, B cells, and CD4+ T cells are conspicuous even in the prodromal stage of MS in familially predisposed subjects. Strikingly, the majority of clonal expansions occur in the CD8+ T cell compartment. In direct comparison with nonexpanded CD8+ T cells, the clonally expanded CD8+ T cells show distinct signs of acute activation, express an array of cytotoxic effector molecules, and phenotypically resemble tissue-resident memory T (TRM) cells (7, 8). This pattern was most pronounced in subjects with definite MS, less pronounced but detectable in subjects with SCNI, and absent in healthy controls and nonexpanded cells from all subjects. In the CD4+ compartment, a few clonal expansions are present, which also display an activated phenotype. Furthermore, the presence of clonally expanded B cells in the plasmablast cluster is strictly correlated with the presence of oligoclonal immunoglobulin bands (OCBs). Viewed together, our findings demonstrate that even the earliest experimentally approachable stage of MS is characterized by a synergistic activation of the main components of the adaptive immune system, with a striking contribution of recently activated, clonally expanded CD8+ T cells with a TRM phenotype. Results Landscape of lymphocytes analyzed by scRNA-Seq. To obtain an overview of the different lymphocyte populations, we isolated single lymphocytes by flow cytometry, determined their transcriptomes by scRNA-Seq, and applied dimensional reduction analysis (t-distributed stochastic neighbor embedding [t-SNE]) to the gene expression data (see Figure 1A for workflow). Altogether, we analyzed 3084 single lymphocyte cells from 16 subjects (Figure 1B and Table 1). We spiked 2752 CSF cells with 332 cells from peripheral blood, since blood cells are well characterized; these cells served as “guideposts” to initially match the unbiased clustering to known immune cell types. In all subsequent analyses, blood cells were excluded from the data set. Throughout, we used conditions that allowed us to identify distinct T and B cell clones according to their matching T and B cell antigen receptor (TCR, BCR) chains (Figure 1A). After combining the gene markers for each individual cluster identified through unbiased clustering with the flow cytometry data, we grouped the cells into several clusters designated T cell cluster I, T cell cluster II, plasmablasts, B cells, plasmacytoid dendritic cells (pDCs), all other subfamilies of dendritic cells (DCs), monocytes, and natural killer (NK) cells (Figure 1B and Supplemental Table 1). Further, CD4+ and CD8+ T cells were identified by the presence of at least one TCR chain as identified by scRNA-Seq. It should be noted that the absolute numbers of CD4+ cells do not reflect the relative proportion of sorted (analyzed) cells present in the original CSF samples (see legend to Figure 1A). Figure 1 Cellular composition of lymphocytes upon analysis by scRNA-Seq. (A) Flowchart of the analysis of human CSF by scRNA-Seq. Because CD4+ cells make up the majority of CSF cells, they were collected by magnetic beads and single CD4+ cells were isolated by flow cytometry. The remaining non-CD4+ cells were separately isolated by single-cell index sorting using different markers. Thus, the ratio of CD4+ and non-CD4+ cell numbers does not reflect the ratio of absolute cell numbers in the CSF samples. Nevertheless, ratios and cell numbers within the non-CD4+ populations are comparable. Whole transcriptomes of each single cell were determined by next-generation sequencing (NGS) with a read length of 2 × 150 bp that allows identification of the hypervariable regions of TCRs and BCRs together with their corresponding V families. Thus, not only transcriptome profiles of each single cell are determined, but also matching α:β TCR and H:L BCR chains. This allows tracking of distinct clones. (B) t-SNE projection of transcriptome data from 2752 single CSF cells and 332 PBMCs from 16 patients, profiled in 9 main clusters. For better visualization, background areas were shaded manually to indicate major cell populations, although some cells will appear in “foreign” areas. Each dot corresponds to one single cell, colored according to the respective cell cluster. DCs, pDCs, and monocytes were not specifically labeled during flow cytometry analyses; therefore up to 6 transcripts were used as discriminators and are listed next to each cluster. (C) Heatmap showing normalized mean expression levels of discriminative gene sets for T cell cluster I CD4+ (lane 1) and CD8+ cells (lane 2), and cluster II CD4+ (lane 3) and CD8+ cells (lane 4). (D) t-SNE projection of all index-sorted CD8+ T cells. (E) t-SNE projection of all index-sorted CD4+ T cells. Table 1 Clinical characteristics of all subjects We then compared the expression profiles of genes that discriminate T cell clusters I and II (Figure 1C). The heatmap and corresponding t-SNE projections (Figure 1, D and E) show that T cell cluster I mainly (but not exclusively) contains CD4+ T cells, whereas T cell cluster II mainly contains CD8+ T cells. In each cluster, the dominant population expresses a characteristic panel of lead transcripts (e.g., IL-7 receptor in CD4+ T cells or cytotoxic molecules [granzymes] in CD8+ T cells). Further, each cluster contains a subpopulation of the nondominant phenotype (CD8+ cells in cluster I, CD4+ cells in cluster II). High levels of the chemokine receptor CCR7 and the cell adhesion molecule SELL confirm that cells profiled in T cell cluster I (mostly CD4+) have a central memory (TCM) phenotype (9). In contrast, the mRNA profiles of discriminative genes of T cell cluster II (mostly CD8+) suggest an effector/cytotoxic phenotype. In Figure 1, D and E, TCR+ cells are displayed in accordance with their flow cytometry information as CD8+ or CD4+ T cells. Composition of CSF cell populations from SCNI, MS, and control subjects. Based on the overall cellular landscape determined by scRNA-Seq (Figure 1B), we compared the cellular distribution of CSF samples from 4 different groups of subjects: SCNI (n = 6), clinically definite MS (MS; n = 4), noninflammatory controls (NIC; n = 4), and autoimmune encephalitis (Enc; n = 2) (Figure 2, A–D, and Table 1). Our study cohort included 8 pairs of MS-discordant monozygotic twins. We were able to obtain CSF samples from all 8 clinically “healthy” co-twins, and from 4 of the MS-affected co-twins (Table 1). Among the 8 clinically healthy co-twins (who have a maximally high familial risk of developing MS), 6 subjects showed MRI evidence for SCNI. In addition, 4 of the 6 had OCBs (Table 1). None of the healthy co-twins had ever been treated with an immunosuppressive or immunomodulatory drug. Figure 2 Cellular composition of CSF samples in different disease stages of MS and controls. t-SNE projections of CSF samples from subjects with NIC (A), SCNI (B), MS (C), and Enc (D). Clusters were defined as in Figure 1B but blood cells were removed. CD4+ and CD8+ T cells are colored according to the index-sorting information obtained by flow cytometry. As seen in Figure 2, A–D, all groups show considerable similarities in the overall cellular distribution. In all groups, T cells contribute the majority of cells, and the distribution between T cell clusters I and II is preserved. B cells were also detectable in all groups, and plasmablasts were only missing in the NIC group. Notably, plasmablasts were already present in SCNI. When analyzing individual SCNI patients (Table 1), we found that plasmablasts were detected only in subjects who had OCBs. Further, we found increased numbers of DCs and pDCs not only in MS but also in SCNI. These results show that t-SNE projections do not distinguish different stages of disease, except for the presence of plasmablasts, which are strictly correlated with OCBs and are already a distinct feature of subjects with SCNI. Clonal expansions of T cells and plasmablasts. In addition to clustering CSF cells according to their genome-wide expression profiles, our approach provides information about the antigen-specific, paired α:β TCR and H:L BCR chains expressed by individual lymphocytes. This enabled us to detect clonal B and T cell expansions in clusters containing B or T cells in the t-SNE projections (Figure 3, A and B). Strong clonal expansions were detectable in the plasmablast cluster of MS, where 90% of all clones were expanded, but also in SCNI, where 20% were expanded. Expanded CD4+ and CD8+ clones were found predominantly in T cell cluster II. The numbers of identified nonexpanded and expanded T cell clones are listed in Table 2. Strong clonal expansions were also found in the CD8+ T cell population of all inflammatory cases (SCNI, MS, Enc), whereas lower percentages of expansions were observed in the CD4+ population. For example, 29% of all CD8+ but only 9% of all CD4+ T cells from MS patients belonged to expanded clones, and a similar preponderance of expanded CD8+ cells was seen in SCNI and Enc (Table 2). Note that the ratios of expanded versus nonexpanded cells are given in percent independently for CD4+ and CD8+ cells. They are therefore not related to the absolute cell numbers or to CD4/CD8 ratios. Regarding the distribution of expanded T cells between clusters I and II, most CD8+ clones from SCNI subjects tended to group in the upper right region of cluster II, whereas clones from MS patients were found predominantly in the lower right and central right region (Figure 4, A and B). A similarly uneven distribution is seen for CD4+ clones. Comparison of TCR sequences of CSF-resident CD8+ T cells with sequences of corresponding memory and naive CD8+ T cells from peripheral blood revealed clonal overlaps of expanded clones preferentially in SCNI and healthy subjects, whereas fewer overlaps were observed in MS patients (Supplemental Figure 1; supplemental material available online with this article; https://doi.org/10.1172/JCI128475DS1). Whether these differences represent statistical fluctuations or systematic differences of phenotypic properties remains to be determined in future investigations with larger numbers of patients and cells. Taken together, clonal expansions occur in all cellular compartments of adaptive immunity, namely B cells, CD8+ T cells, and, to a lesser extent, CD4+ T cells. In particular, such clonal expansions are a consistent and conspicuous feature observed in subjects with SCNI. Figure 3 Analysis of clonally expanded lymphocyte cells. t-SNE projection of all CSF cells where either CD4+ (A) or CD8+ (B) cells were removed. Cells of the adaptive immune system with at least 1 detectable TCR or BCR chain are shown in light reddish color. Cells of the innate immune system are shown in gray. Expanded clones, i.e., T and B cells that express identical α:β TCR or H:L BCR chains, are highlighted in dark red for CD8+ T cells, blue for CD4+ T cells, and green for B cells. Dot sizes correlate with clonal frequencies: normal-sized dots indicate that the clone was found 2 times; larger dots indicate that it was found 3 or more times. Figure 4 Analysis of clonally expanded T cells in SCNI and MS. t-SNE projection of all CD8+ and CD4+ T cells from subjects with SCNI (A) and MS (B). Expanded T cell clones that express identical α:β TCR are highlighted in dark red for CD8+ T cells and blue for CD4+ T cells. Dot sizes correlate with clonal frequencies: normal-sized dots indicate that the clone was found 2 times; larger dots indicate that it was found 3 or more times. Table 2 Numbers of identified nonexpanded and expanded T cell clones Differentially regulated transcripts in expanded versus nonexpanded T cell clones. Clonal expansion is usually interpreted as evidence for pathogenic relevance of the expanded lymphocyte clones. Therefore, we compared normalized expression levels of differentially expressed genes related to T cell egress, tissue retention, inhibition, transcription factors, cytokines, and migration and activation of expanded and nonexpanded CD8+ T cell clones (Figure 5). The top panel of this heatmap shows expression of homing receptors and molecules involved in T cell egress, including CCR7, SELL (CD62L), TCF7 (TCF-1), and S1PR1. These markers are gradually downregulated from NIC, via nonexpanded cells from SCNI and MS subjects, to expanded clones from SCNI and MS subjects. In the latter case, all markers are downregulated, indicating a fully established TRM phenotype (10–12). Figure 5 Heatmap of gene expression levels of selected function-associated genes in CD8+ T cells. CD8+ T cells were selected based on flow cytometry staining for CD8 and presence of at least one TCR chain as determined by next-generation sequencing. Gene expression of 25 marker genes for homing, migration, and activation is shown for nonexpanded CD8+ T cells and expanded CD8+ T cell clones from SCNI, MS, and Enc subjects. No distinction is made for NIC, as the number of expanded clones is too low. Color scheme is based on Z score distribution from –2.5 (blue) to 2.5 (red). In addition, CD69 (second panel), which has been postulated as a marker of TRM as well as being an early activation marker (13, 14), is upregulated in the MS expanded CD8+ T cell clones but not in SCNI. Consistently, other tissue retention molecules, i.e., ITGAE (CD103), ITGA1 (CD49a), and CRTAM, which play an important role in TRM development (14), are upregulated in MS as compared with SCNI, but no significant differences are seen between expanded and nonexpanded clones. Typical TRM gene signatures also include upregulation of inhibitors of T cell activation, including PDCD1 (PD-1), CD101, CTLA4 (third panel), and increased expression of CXCR6 (bottom panel), a recently identified key marker of TRM cells (14). Strikingly, our data again show upregulation of these molecules in the expanded CD8+ T cell population in MS but not in SCNI subjects. Further, this expression profile is consistent with upregulation of the key regulator of the universal TRM transcriptional program ZNF683 (Hobit), which causes downregulation of KLF2 (fourth panel) (15, 16), and finally downregulation of the egress-related transcripts. Such a pattern is not seen explicitly in SCNI. The cytokine expression panel (fifth panel) resembles TRM characteristics in expanded CD8+ clones from MS patients and additional signs of T cell activation as indicated by GZMH, high levels of CXCR6 and CCR5, and proinflammatory cytokines including IFNG and IL-2 (10, 14, 17). Other activation and migration markers, such as SLAMF7, FCRL6, ADGRE5 (CD97) (bottom panel), and HLA class II, were also upregulated in CD8+ T cells from MS patients. In SCNI, no increases or only minor increases of these markers were seen. Similar, though not as concise, patterns are detected by comparison of expanded and nonexpanded CD4+ T cell clones (Supplemental Figure 2). As seen for CD8+ T cells, the bias toward TRM increases from NIC via SCNI to expanded clones in MS. Together, these findings indicate that expanded and nonexpanded T cell clones display different expression profiles. Markers for T cell egress, tissue retention, and inhibition together with the cytokine pattern suggest a TRM phenotype in expanded T cell clones from MS patients, particularly in the CD8 compartment. In MS, the expanded CD8+ T cells express markers of cellular activation and cytotoxic activity. Conspicuous clonal expansions are also present in SCNI, but — compared with MS — they show a less distinct phenotype and activation profile. Recruitment of expanded TRM CD8+ cells into the CSF of MS patients. Because heatmaps only show average values of all cells, we next analyzed the strong downregulation of S1PR1 and upregulation of CXCR6 in single expanded TRM CD8+ cells from different subject groups by violin plots (Figure 6, A and B). S1PR1 is significantly downregulated only in expanded CD8+ cells from MS patients, and CXCR6 is upregulated only in expanded cells from MS and Enc patients. CXCR6 is the sole receptor for CXCL16, which can mediate lymphocyte recruitment, in particular of CD8+ T cells, and is induced by the proinflammatory cytokine IFNG (18). Here we found significant upregulation of CXCL16 in DCs and monocytes (Figure 6C) from all subject groups (Figure 6D). Notably, IFNG is also strongly upregulated in expanded CD8+ T cells of MS (Figure 5), whereas it is not upregulated in all other subject groups, including SCNI. Taken together, these findings indicate that the CXCR6-CXCL16 axis may be involved in the recruitment and maintenance of clonally expanded CD8+ T cells in the CSF of MS patients. Figure 6 Violin plots show gene expression of CD8+ T cells on the single-cell level. Each dot represents a single cell. Statistically significant gene expression is observed only if a violin-shaped fitting area can be calculated. (A) The homing marker S1PR1 is expressed on all T cells but is downregulated when a cell adopts a TRM phenotype. This is only the case for expanded CD8+ T cells from MS patients. (B) The TRM marker CXCR6 is upregulated only in expanded CD8+ T cells from MS and Enc patients. (C) The marker CXCL16 is the sole ligand of CXCR6. It is upregulated only in DCs and monocytes. (D) CXCL16 is expressed in DCs (left panel) and monocytes (right panel) from all patient groups. Comparison of clonal expansions within monozygotic, MS-discordant twin pairs. We were able to obtain CSF from 4 MS-discordant twin pairs (Table 1). This allowed us to compare different disease conditions on a genetically identical background. Thus, in contrast to Figure 5, where data from all subjects were analyzed together, we now compared distinct twin pairs. In 2 twin pairs, the clinically unaffected twin had SCNI (Figure 7 and Supplemental Figure 3), whereas in the 2 other pairs, the clinically unaffected twin had no evidence of subclinical inflammation (NIC; Supplemental Figures 4 and 5). Thus, we compared the gene expression pattern of CD8+ T cells individually for each pair: AR-MS versus AR-H, who later developed radiologically isolated syndrome, i.e., MRI-based evidence for dissemination in space (Figure 7); AU-MS versus AU-H (Supplemental Figure 3); AV-MS versus AV-H (healthy) (Supplemental Figure 4); and BJ-MS versus BJ-H (Supplemental Figure 5). The individual gene expression patterns fit to the average patterns shown in Figure 5 with signatures of TRM cells, expression of a panel of cytotoxic molecules, higher proinflammatory marker cytokines, and markers of activation including MHC class II. These patterns are particularly pronounced in expanded CD8+ T cells from MS patients as compared with nonexpanded cells, and with SCNI or healthy twins. This is remarkable since all MS patients received different medication (Table 1). The only exception is pair BJ-MS, BJ-H (Supplemental Figure 5), in whom the pattern of the teriflunomide-treated MS patient BJ-MS differs from those of all other probands. Together, these findings in genetically identical, yet disease-discordant twins support the notion that clonal activation and expansion, particularly of CD8+ T cells, is a distinct, very early event in the chain of pathogenic events leading from prodromal SCNI to clinically manifest MS. Figure 7 Heatmap of gene expression levels of nonexpanded and expanded CD8+ T cells from 1 monozygotic twin pair. Expression levels of the same genes as in Figure 5 are shown for the twin pair AR-H and AR-MS. Discussion Here we investigated early cellular CSF profiles in the prodromal stage of MS in subjects with a maximally high familial risk of developing clinically manifest MS. We identified 8 subjects who were clinically unaffected but had an identical twin sibling who had clinically definite MS. Only 2 of them did not show any evidence of latent neuroinflammation, whereas 6 showed MRI signs of SCNI and 4 additionally showed OCBs. This allowed us to investigate SCNI using freshly isolated CSF cells for index sorting and subsequent scRNA-Seq, including identification of clonally distributed B and T cell antigen receptor chains at the single-cell level. Compared with traditional approaches that often focus on particular, predefined subsets and lineages of lymphocytes, scRNA-Seq provides an unbiased overview and therefore offers novel insights into the complexity of human (auto)immune reactions. SCNI as defined here is not identical with conventional radiologically isolated syndrome (RIS). The concept of RIS is based on radiological criteria that have changed over time. According to the most recent criteria, the diagnosis of RIS requires at least 1 MRI lesion in at least 2 predefined areas (19, 20). As RIS is usually discovered by chance, strict radiological criteria are required in order to distinguish neuroinflammatory MRI changes from those commonly observed in other conditions like migraine or ischemia. Rather than relying on chance detection, in our study we searched for SCNI in a cohort of subjects who had a maximal familial risk of developing MS. In this way we identified 6 clinically “healthy” co-twins who showed small MRI lesions (Table 1). It is noteworthy that these subjects represent a spectrum of SCNI changes (Table 1): two (AR-H and BF-H; Table 1) fulfilled the current RIS criteria of dissemination in space, whereas the other 4 SCNI subjects, 2 of whom had positive OCBs, did not fulfill the current RIS criteria and thus may be considered “pre-RIS.” Indeed, one of the SCNI subjects (AR-H) meanwhile showed MRI evidence for dissemination in time (Table 1). Like conventional RIS, SCNI may be regarded as an early stage in the pathogenesis of MS, although it is impossible to know exactly when lesion initiation started. One of the most conspicuous features we observed in our t-SNE projections of CSF cells from subjects with SCNI was the early and consistent presence of clonally expanded, activated CD8+ T cells. CD8+ cells have long been implicated in the pathogenesis of human MS because they predominate in MS brain lesions and show signs of clonal expansion, persistence, and pervasiveness, all of which support their pathogenic relevance (3, 21–28). However, CD8+ T cells have not been extensively studied in animal models, and therefore, they do not play a prominent role in the CD4+ T cell–centered scenario derived from classical experimental autoimmune encephalomyelitis models (29). Indeed, it has been argued that the CD8+ predominance in MS lesions might reflect the recruitment of bystander cells, and therefore a secondary event in the pathogenesis. Our findings strongly support the notion that clonal activation and expansion of CD8+ T cells represent crucial, early steps in the disease process. We identified striking differences between expanded and nonexpanded CD8+ T cell clones. Regarding nonexpanded T cell clones, we did not observe much variation between NIC, SCNI, MS, and Enc subjects in the t-SNE projections. Slight differences were seen when we analyzed specific homing, migration, and activation markers. In striking contrast, we observed major alterations in t-SNE projections and markers when we analyzed clonally expanded T cells, which were detected in all subjects with neuroinflammation, although to a different extent. Thus, the percentages of expanded clones as compared with nonexpanded clones were about 2-fold higher in MS and Enc than in SCNI, and higher in SCNI than in NIC. In all conditions, CD8+ T cell expansions were more frequent than CD4+ expansions. In both populations, however, there were subtle differences between SCNI and MS in the t-SNE projections of the expanded clones, indicating altered cellular phenotypes. Because dimensional reductions were calculated on thousands of highly diverse genes, the resulting clusters may not reflect the classical lineages that are defined by a few selected markers. Gene expression analysis of markers related to migration, homing, and activation of CD8+ T cells revealed that expression of egress markers (S1PR1, CCR7, SELL, TCF7) was normal in NIC but strongly downregulated in expanded CD8+ TRM cell clones from MS patients. In nonexpanded MS cells, they were weakly downregulated, suggesting that this population is sensing the inflammatory milieu and is possibly “on the road” to adopting a TRM phenotype. The expression levels of egress markers in SCNI reveal that nonexpanded CD8+ T cells are indistinguishable from NIC cells. Strikingly, expanded CD8+ T cells from SCNI, though fewer in number than expanded CD8+ T cells from MS, downregulated CCR7 and SELL and upregulated proinflammatory cytokines, indicating that they are in transition to an effector phenotype. This is also reflected by different positions in the t-SNE projections (Figure 4, A and B). Comparison of egress markers and t-SNE projections therefore illustrates the gradual transition from a TCM to an effector phenotype, moving from NIC and nonexpanded SCNI to expanded T cell SCNI and nonexpanded MS, to a fully established TRM phenotype of CD8+ T cells in definite MS. This interpretation is supported by the gradual upregulation of inhibition and retention markers (such as PDCD1 or CD69), cytokines, and activation markers (such as IFNG or CXCR6), moving from NIC and nonexpanded SCNI, to expanded SCNI and nonexpanded MS, and finally to definite MS. This pattern is compatible with a phenotype change of CD8+ T cells from TCM to TRM during the course of the disease. Four of the six SCNI subjects had positive CSF OCBs. This is in agreement with numerous previous reports that OCBs represent an early immunological marker of neuroinflammation and indeed serve as a prognostic marker in subjects with RIS (30). The presence of OCBs was strictly correlated with the presence and expansion of plasmablasts in our t-SNE projection. This is consistent with previous observations that plasmablasts are characteristic components of the B cell compartment in MS CSF (31, 32), and supports our previous observation that intrathecal B cells are a cellular source of OCBs (33), which at least in some cases were shown to be involved in removal of debris from cells that died by prior events (34). Together, our data suggest that deleterious inflammatory events may already be ongoing at a cryptic stage of the disease, possibly even earlier than the SCNI stage investigated here. Extensive analyses of intrathecal B cell clonal pedigrees suggested an ongoing intrathecal antigen-driven B cell maturation process in MS, including immunoglobulin class switching and somatic hypermutation (35–37). These processes likely depend on help by CD4+ T cells. However, our scRNA-Seq analyses of CSF CD4+ T cells did not reveal any distinct signatures of known CD4+ T cell lineages such as T follicular helper cells, regulatory T cells, Th1, Th2, or Th17 effector cells, which are usually defined by flow cytometry. This by no means implies that CD4+ T cells are not crucially involved. However, with the introduction of scRNA-Seq, the borders between traditional cell lineages are beginning to blur, and an unexpected complexity and dynamic nature of the cellular immune system are beginning to emerge (38, 39). A still unanswered key question in MS pathogenesis is how putatively autoreactive lymphocytes are recruited to the CNS and which target cells they communicate with. It has long been known that T cells survey the brain parenchyma also in noninflammatory conditions (40), and recently it has been shown that many of them are TRM cells (41). Here we found that expanded CD8+ T cells from MS and Enc patients strongly upregulated CXCR6. CXCR6 has been implicated in various human diseases (17, 42–44), and notably, it has a significant role in recruiting activated CD8+, but not CD4+, T cells, under pathological conditions (42, 43). Its only ligand is CXCL16. Strikingly, we detected highly elevated levels of CXCL16 transcription in monocytes and DCs in the CSF. For CD4+ T cells, we also observed upregulation of CXCR6 predominantly in expanded clones of SCNI and MS subjects. This might also be triggered by mononuclear phagocytes and/or DCs serving as antigen-presenting cells. Consistent with earlier reports (45, 46), we observed DCs and pDCs already in the CSF of NIC with a marked predominance of myeloid DCs over pDCs, but cell numbers were significantly increased in the CSF of patients with neuroinflammatory diseases, such as MS. This is not yet an ultimate proof of a functional interaction of CD8+ T cells with mononuclear phagocytes and/or DCs, but it may trigger further investigations. An obvious limitation of our study is the small sample size. For example, we did not include subjects with clinically isolated syndrome because they are usually sampled in close relation to clinical activity. In our study, all subjects were sampled outside clinical activity, as this could turn out to be a significant confounding factor that hampers comparability of data and needs to be addressed in future studies with larger cohorts. The same applies to the potential confounding effects of various MS treatments. In contrast to the subjects with SCNI, who had never been exposed to any immunomodulatory therapy, the group of MS patients was heterogeneous with regard to treatment. Surprisingly, however, there were no significant differences in the overall CSF cell populations, clonal expansions, and gene expression levels of the MS patients irrespective of their diverse treatments. The only significant deviation from the reasonably conserved overall expression pattern was seen in MS patient BJ-MS, who was under teriflunomide treatment, which inhibits lymphocyte proliferation and therefore changes gene expression patterns and phenotypes. Obviously, these treatment-related initial findings need validation in larger cohorts. Our results provide a first glimpse into the complexity of CSF cells at a very early stage of neuroinflammation as it occurs in clinically healthy subjects who are at a maximally high familial risk because they have a monozygotic co-twin affected by MS. In these subjects, we observed evidence for early involvement of the major components of the adaptive immune system, B cells, CD4+ T cells, and CD8+ T cells. Both in SCNI and in MS, conspicuous changes were observed in clonally expanded CD8+ T cells, though these changes were more pronounced in MS than in SCNI. The observed alterations in gene expression levels suggest that activation and clonal expansion of CD8+ T cells are not just a late epiphenomenon but rather reflect early mechanisms of MS pathogenesis. Expanded CD8+ T cell clones show a TRM phenotype and may be assumed to relate directly to disease progression as seen in tumors and infections (7, 8, 10). It is tempting to speculate that expanded CD8+ clones might also play a major role in CNS lesions, where they are the dominant lymphocyte population, persist, and are shared between CNS and CSF (22–27). Although our cohort is small and should be enlarged for drawing final conclusions, our results underline the need to study antigens and communication partners of intrathecally expanded CD8+ T cell clones in much greater detail. These results have implications not only for the pathogenesis but also for the therapy of MS. Methods Study subjects and procedures. Twins were recruited in Germany. Inclusion criteria for study participation were met for monozygotic twins with an MS diagnosis according to the revised McDonald criteria (20). Monozygotic twin pairs with clinical discordance for MS visited the outpatient department at the Institute of Clinical Neuroimmunology, Munich, for a detailed interview, neurological examination, MRI investigations, and optional CSF sampling. Twins either volunteered for CSF sampling or were specifically offered CSF sampling if suspicious lesions were detected on MRI. For inclusion in the present analysis, CSF samples had to be available of either both co-twins or the clinically healthy co-twin only, resulting in 4 monozygotic twin pairs and 4 additional clinically healthy co-twins with signs of SCNI in MRI and/or CSF. Zygosity was confirmed by genotyping of 17 highly polymorphic microsatellite markers and by next-generation sequencing of 33 SNPs. CSF samples from control subjects with encephalitis (Enc) and noninflammatory controls (NIC) were provided during routine diagnostic testing or serial CSF collection to treat idiopathic intracranial hypertension. All twins underwent MR imaging on a 3 Tesla MR scanner (Magnetom Skyra, Siemens Healthineers) using a 20-channel phased-array head and neck coil. The sequence protocol included a 3D-FLAIR (TI 1800 ms, TR 5000 ms, TE 388 ms, flip angle 90°; 1.0 mm3 isotropic voxels) and a 3D T1-weighted sequence using a 3D magnetization-prepared rapid-acquisition gradient-echo (MP-RAGE) sequence (TR 1600 ms, TE 2.15 ms, flip angle 9°; 1.0 mm3 isotropic voxels). Flow cytometry single-cell index sorting. Fresh CSF and blood samples were processed within 1 hour after collection. CSF samples (3–6 mL) were centrifuged at 300 g for 10 minutes and CD4+ cells isolated using the EasySep human CD4 Positive Selection Kit II (STEMCELL Technologies) according to the manufacturer’s instructions. In parallel, non-CD4+ cells were stained for the following lymphocyte cell surface markers: CD3 (eBioscience, clone OKT3; diluted 1:50), CD8 (BioLegend, clone SK1; diluted at 1:50), CD56 (BioLegend, clone HCD56; diluted 1:40), CD19 (BioLegend, clone HIB19; diluted at 1:40), CD27 (BioLegend, clone O323; diluted 1:40), CD38 (eBioscience, clone HB7; diluted 1:40), and Fc receptor blocking (Miltenyi Biotec) in a total volume of 100 μL PBS with 2% FBS. After incubation for 30 minutes at 4°C, both CD4+ and non-CD4+ cells were washed twice, resuspended in 300 μL of the above buffer, and single-cell-sorted using a FACSAria Fusion (BD Biosciences) sorter. Single cells were sorted only according to their forward and side scatter properties, and no further gates were used to keep the ratios between all non-CD4+ cells unchanged. Cells were sorted into lysis buffer in 96-well plates using index sorting. Index sorting enabled us to sort all single cells while retaining the complete phenotype of every single cell sorted into the plate. For profiling of blood lymphocytes, PBMCs were isolated using Ficoll-Paque density gradient centrifugation. Single-cell suspensions were stained using the same markers as described above for CD8+ cells plus anti-CD4 (BioLegend, clone SK3; diluted 1:25). Then, single CD4+ T cells (CD3+CD4+), CD8+ T cells (CD3+CD8+), B cells (CD3–CD19+), and CD3–CD19– cells were sorted into 96-well plates. scRNA-Seq. The Smart-Seq2 protocol was performed on sorted single cells as described previously (47), with minor modifications. Briefly, PCR preamplification products were purified using Ampure XP beads in a 0.6:1 ratio. For the tagmentation reaction (48), 0.8 ng DNA was used as input. Then, PCR purification was carried out using Ampure XP beads in a 0.75:1 ratio. Multiplex sequencing of 96 single-cell libraries was performed on a Hiseq 1500 lane in 150-bp paired-end mode, giving an average sequence depth of 2 million reads per cell. A total of 3362 CSF cells and 384 PMBCs were sequenced, and 2752 and 332 passed quality control. scRNA-Seq raw data were deposited in the NCBI’s Sequence Read Archive database (SRA), and processed gene expression data can be accessed from the Gene Expression Omnibus (GEO) database under accession numbers SRP180896 and GSE127969. scRNA-Seq data analyses. Short sequencing reads were aligned to the UCSC hg38 transcriptome using HISAT2. These alignments were used as input in featureCounts to count mapped reads in all samples. As quality control steps, we removed transcripts detected in fewer than 3 cells and kept only cells with 200 to 6000 detected transcripts. Further, we disregarded cells in which the proportion of mitochondrial transcripts was higher than 5%. Following visual inspection, we further discarded cells located in a cluster characterized by mitochondrial and ribosomal gene expression. Transcripts per million (TPM) data were log-transformed [log(TPM+1)] for all downstream analyses. Detection of highly variable genes, unbiased graph-based clustering of single-cell data, and identification of markers for each cluster were performed with Seurat (49). See Supplemental Methods (online) for more details, including the Seurat R script used to analyze the single-cell data. In addition, scRNA-Seq data were aligned to the TCR and Ig genes. The sorted reads were subjected to MiGEC-CdrBlast (https://migec.readthedocs.io) for extraction of TCR and Ig chains, leading to the identification of CDR3 sequences of TCR and BCR chains. To compare single–T cell repertoires from CSF with T cells from peripheral blood, we analyzed the TCR repertoire of T cells present in 14 mL blood collected into EDTA containing tubes as described previously (50). Statistics. The χ2 test was used to assess the differences in size of both nonexpanded and expanded T cells in each of the study groups. A P value less than 0.05 was considered statistically significant. Study approval. The study was approved by the local ethics committee of the Ludwig Maximilian University of Munich, and all participants gave written informed consent, according to the principles of the Declaration of Helsinki. Author contributions EB, LAG, and JH share first authorship. EB and LAG both contributed to study design and, as EB also performed bioinformatics analysis, analyzed data and contributed to writing, he is listed first. See below for more detailed contributions. EB, LAG, RH, and KD designed the study and experiments. EB and JH performed flow cytometry experiments, PCR, and sample preparation for next-generation sequencing analysis. SK and HB performed Illumina next-generation sequencing. EB performed bioinformatics analysis. LAG, AFH, FB, TK, and RH characterized and contributed patients’ samples. BEW performed MRI examinations and analyzed data. KD, RH, and EB analyzed data and wrote the manuscript with contributions of all other authors. All authors reviewed and approved the manuscript. Supplemental material View Supplemental data Acknowledgments We are grateful to all subjects who participated in this study. We thank Edgar Meinl and Naoto Kawakami for comments on the manuscript, Nicolaus König for valuable support, and Katja Anslinger for zygosity determination, and acknowledge the Core Facility Flow Cytometry unit at the Biomedical Center, Ludwig Maximilian University of Munich, for providing equipment. The study was supported by the German Research Council through CRC128-A5, DO 420/3-1 DACH, the Munich Cluster for Systems Neurology (SyNergy), the Dr. Leopold and Carmen Ellinger Foundation, the Gemeinnützige Hertie Stiftung, the national division of the German MS Society (DMSG), the Bavarian Association of the German MS society (DMSG-Landesverband Bayern), the Federal Ministry of Education and Research (BMBF) organization Krankheitsbezogenes Kompetenznetz Multiple Sklerose, and the association Verein zur Therapieforschung für MS Kranke e.V. FB is supported by the National Institute for Health Research Biomedical Research Centre at University of College London Hospitals. Footnotes Conflict of interest: The authors have declared that no conflict of interest exists. Copyright: © 2019, American Society for Clinical Investigation. Reference information: J Clin Invest. https://doi.org/10.1172/JCI128475. References Dendrou CA, Fugger L. Immunomodulation in multiple sclerosis: promises and pitfalls. Curr Opin Immunol. 2017;49:37–43. View this article via: PubMed CrossRef Google Scholar Hohlfeld R, Dornmair K, Meinl E, Wekerle H. The search for the target antigens of multiple sclerosis, part 1: autoreactive CD4+ T lymphocytes as pathogenic effectors and therapeutic targets. Lancet Neurol. 2016;15(2):198–209. View this article via: PubMed CrossRef Google Scholar Hohlfeld R, Dornmair K, Meinl E, Wekerle H. The search for the target antigens of multiple sclerosis, part 2: CD8+ T cells, B cells, and antibodies in the focus of reverse-translational research. Lancet Neurol. 2016;15(3):317–331. View this article via: PubMed CrossRef Google Scholar Reich DS, Lucchinetti CF, Calabresi PA. Multiple sclerosis. N Engl J Med. 2018;378(2):169–180. View this article via: PubMed CrossRef Google Scholar Papalexi E, Satija R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immunol. 2018;18(1):35–45. View this article via: PubMed CrossRef Google Scholar Stubbington MJT, Rozenblatt-Rosen O, Regev A, Teichmann SA. Single-cell transcriptomics to explore the immune system in health and disease. Science. 2017;358(6359):58–63. View this article via: PubMed CrossRef Google Scholar Molodtsov A, Turk MJ. Tissue resident CD8 memory T cell responses in cancer and autoimmunity. Front Immunol. 2018;9:2810. View this article via: PubMed Google Scholar Park CO, Kupper TS. The emerging role of resident memory T cells in protective immunity and inflammatory disease. Nat Med. 2015;21(7):688–697. View this article via: PubMed CrossRef Google Scholar Kivisäkk P, et al. Human cerebrospinal fluid central memory CD4+ T cells: evidence for trafficking through choroid plexus and meninges via P-selectin. Proc Natl Acad Sci U S A. 2003;100(14):8389–8394. View this article via: PubMed CrossRef Google Scholar Amsen D, van Gisbergen KPJM, Hombrink P, van Lier RAW. Tissue-resident memory T cells at the center of immunity to solid tumors. Nat Immunol. 2018;19(6):538–546. View this article via: PubMed CrossRef Google Scholar Mackay LK, Kallies A. Transcriptional regulation of tissue-resident lymphocytes. Trends Immunol. 2017;38(2):94–103. View this article via: PubMed CrossRef Google Scholar Matloubian M, et al. Lymphocyte egress from thymus and peripheral lymphoid organs is dependent on S1P receptor 1. Nature. 2004;427(6972):355–360. View this article via: PubMed CrossRef Google Scholar Cibrián D, Sánchez-Madrid F. CD69: from activation marker to metabolic gatekeeper. Eur J Immunol. 2017;47(6):946–953. View this article via: PubMed CrossRef Google Scholar Kumar BV, et al. Human tissue-resident memory T cells are defined by core transcriptional and functional signatures in lymphoid and mucosal sites. Cell Rep. 2017;20(12):2921–2934. View this article via: PubMed CrossRef Google Scholar Mackay LK, et al. Hobit and Blimp1 instruct a universal transcriptional program of tissue residency in lymphocytes. Science. 2016;352(6284):459–463. View this article via: PubMed CrossRef Google Scholar Skon CN, Lee JY, Anderson KG, Masopust D, Hogquist KA, Jameson SC. Transcriptional downregulation of S1pr1 is required for the establishment of resident memory CD8+ T cells. Nat Immunol. 2013;14(12):1285–1293. View this article via: PubMed CrossRef Google Scholar Zaid A, et al. Chemokine receptor-dependent control of skin tissue-resident memory T cell formation. J Immunol. 2017;199(7):2451–2459. View this article via: PubMed CrossRef Google Scholar van Lieshout AW, et al. Regulation of CXCL16 expression and secretion by myeloid cells is not altered in rheumatoid arthritis. Ann Rheum Dis. 2009;68(6):1036–1043. View this article via: PubMed CrossRef Google Scholar De Stefano N, et al. Radiologically isolated syndrome or subclinical multiple sclerosis: MAGNIMS consensus recommendations. Mult Scler. 2018;24(2):214–221. View this article via: PubMed CrossRef Google Scholar Thompson AJ, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018;17(2):162–173. View this article via: PubMed CrossRef Google Scholar Friese MA, Fugger L. Autoreactive CD8+ T cells in multiple sclerosis: a new target for therapy? Brain. 2005;128(pt 8):1747–1763. View this article via: PubMed Google Scholar Machado-Santos J, et al. The compartmentalized inflammatory response in the multiple sclerosis brain is composed of tissue-resident CD8+ T lymphocytes and B cells. Brain. 2018;141(7):2066–2082. View this article via: PubMed CrossRef Google Scholar Skulina C, et al. Multiple sclerosis: brain-infiltrating CD8+ T cells persist as clonal expansions in the cerebrospinal fluid and blood. Proc Natl Acad Sci U S A. 2004;101(8):2428–2433. View this article via: PubMed CrossRef Google Scholar van Nierop GP, et al. Phenotypic and functional characterization of T cells in white matter lesions of multiple sclerosis patients. Acta Neuropathol. 2017;134(3):383–401. View this article via: PubMed CrossRef Google Scholar Held K, et al. αβ T-cell receptors from multiple sclerosis brain lesions show MAIT cell-related features. Neurol Neuroimmunol Neuroinflamm. 2015;2(4):e107. View this article via: PubMed CrossRef Google Scholar Junker A, et al. Multiple sclerosis: T-cell receptor expression in distinct brain regions. Brain. 2007;130(pt 11):2789–2799. View this article via: PubMed Google Scholar Salou M, et al. Expanded CD8 T-cell sharing between periphery and CNS in multiple sclerosis. Ann Clin Transl Neurol. 2015;2(6):609–622. View this article via: PubMed CrossRef Google Scholar Babbe H, et al. Clonal expansions of CD8(+) T cells dominate the T cell infiltrate in active multiple sclerosis lesions as shown by micromanipulation and single cell polymerase chain reaction. J Exp Med. 2000;192(3):393–404. View this article via: PubMed CrossRef Google Scholar Lassmann H. Pathogenic mechanisms associated with different clinical courses of multiple sclerosis. Front Immunol. 2018;9:3116. View this article via: PubMed Google Scholar Lebrun C, Kantarci OH, Siva A, Pelletier D, Okuda DT, , RIS Consortium. Anomalies characteristic of central nervous system demyelination: radiologically isolated syndrome. Neurol Clin. 2018;36(1):59–68. View this article via: PubMed CrossRef Google Scholar Cepok S, et al. Short-lived plasma blasts are the main B cell effector subset during the course of multiple sclerosis. Brain. 2005;128(pt 7):1667–1676. View this article via: PubMed Google Scholar Michel L, Touil H, Pikor NB, Gommerman JL, Prat A, Bar-Or A. B cells in the multiple sclerosis central nervous system: trafficking and contribution to CNS-compartmentalized inflammation. Front Immunol. 2015;6:636. View this article via: PubMed Google Scholar Obermeier B, et al. Matching of oligoclonal immunoglobulin transcriptomes and proteomes of cerebrospinal fluid in multiple sclerosis. Nat Med. 2008;14(6):688–693. View this article via: PubMed CrossRef Google Scholar Brändle SM, et al. Distinct oligoclonal band antibodies in multiple sclerosis recognize ubiquitous self-proteins. Proc Natl Acad Sci U S A. 2016;113(28):7864–7869. View this article via: PubMed CrossRef Google Scholar Beltrán E, et al. Intrathecal somatic hypermutation of IgM in multiple sclerosis and neuroinflammation. Brain. 2014;137(pt 10):2703–2714. View this article via: PubMed Google Scholar Palanichamy A, et al. Immunoglobulin class-switched B cells form an active immune axis between CNS and periphery in multiple sclerosis. Sci Transl Med. 2014;6(248):248ra106. View this article via: PubMed CrossRef Google Scholar Stern JN. B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes. Sci Transl Med. 2014;6(248):248ra107. View this article via: PubMed CrossRef Google Scholar Neu KE, Tang Q, Wilson PC, Khan AA. Single-cell genomics: approaches and utility in immunology. Trends Immunol. 2017;38(2):140–149. View this article via: PubMed CrossRef Google Scholar Nguyen A, Khoo WH, Moran I, Croucher PI, Phan TG. Single cell RNA sequencing of rare immune cell populations. Front Immunol. 2018;9:1553. View this article via: PubMed Google Scholar Ransohoff RM, Engelhardt B. The anatomical and cellular basis of immune surveillance in the central nervous system. Nat Rev Immunol. 2012;12(9):623–635. View this article via: PubMed CrossRef Google Scholar Smolders J, et al. Tissue-resident memory T cells populate the human brain. Nat Commun. 2018;9(1):4593. View this article via: PubMed CrossRef Google Scholar Günther C, Carballido-Perrig N, Kaesler S, Carballido JM, Biedermann T. CXCL16 and CXCR6 are upregulated in psoriasis and mediate cutaneous recruitment of human CD8+ T cells. J Invest Dermatol. 2012;132(3 pt 1):626–634. View this article via: PubMed Google Scholar Sato T, et al. Role for CXCR6 in recruitment of activated CD8+ lymphocytes to inflamed liver. J Immunol. 2005;174(1):277–283. View this article via: PubMed CrossRef Google Scholar van der Voort R, et al. Elevated CXCL16 expression by synovial macrophages recruits memory T cells into rheumatoid joints. Arthritis Rheum. 2005;52(5):1381–1391. View this article via: PubMed CrossRef Google Scholar de Graaf MT, et al. Central memory CD4+ T cells dominate the normal cerebrospinal fluid. Cytometry B Clin Cytom. 2011;80(1):43–50. View this article via: PubMed Google Scholar Pashenkov M, Huang YM, Kostulas V, Haglund M, Söderström M, Link H. Two subsets of dendritic cells are present in human cerebrospinal fluid. Brain. 2001;124(pt 3):480–492. View this article via: PubMed Google Scholar Picelli S, Faridani OR, Björklund AK, Winberg G, Sagasser S, Sandberg R. Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc. 2014;9(1):171–181. View this article via: PubMed CrossRef Google Scholar Baym M, Kryazhimskiy S, Lieberman TD, Chung H, Desai MM, Kishony R. Inexpensive multiplexed library preparation for megabase-sized genomes. PLoS One. 2015;10(5):e0128036. View this article via: PubMed CrossRef Google Scholar Butler A, Hoffman P, Smibert P, Papalexi E, Satija R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol. 2018;36(5):411–420. View this article via: PubMed CrossRef Google Scholar Beltrán E, et al. Shared T cell receptor chains in blood memory CD4+ T cells of narcolepsy type 1 patients. J Autoimmun. 2019;100:1–6. View this article via: PubMed CrossRef Google Scholar Version history Version 1 (September 30, 2019): Electronic publication

Growing evidence links COVID-19 with acute and long-term neurological dysfunction. However, the pathophysiological mechanisms resulting in central nervous system involvement remain unclear, posing both diagnostic and therapeutic challenges.

The study was supported by an unrestricted research grant from Merck-Serono.

Abstract Objective To investigate the involvement of interleukin (IL)-26 in neuroinflammatory processes in multiple sclerosis (MS), in particular in blood-brain barrier (BBB) integrity. Methods Expression of IL-26 was measured in serum, CSF, in vitro differentiated T helper (TH) cell subsets, and postmortem brain tissue of patients with MS and controls by ELISA, quantitative PCR, and immunohistochemistry. Primary human and mouse BBB endothelial cells (ECs) were treated with IL-26 in vitro and assessed for BBB integrity. RNA sequencing was performed on IL-26–treated human BBB ECs. Myelin oligodendrocyte glycoprotein35–55 experimental autoimmune encephalomyelitis (EAE) mice were injected IP with IL-26. BBB leakage and immune cell infiltration were assessed in the CNS of these mice using immunohistochemistry and flow cytometry. Results IL-26 expression was induced in TH lymphocytes by TH17-inducing cytokines and was upregulated in the blood and CSF of patients with MS. CD4+IL-26+ T lymphocytes were found in perivascular infiltrates in MS brain lesions, and both receptor chains for IL-26 (IL-10R2 and IL-20R1) were detected on BBB ECs in vitro and in situ. In contrast to IL-17 and IL-22, IL-26 promoted integrity and reduced permeability of BBB ECs in vitro and in vivo. In EAE, IL-26 reduced disease severity and proinflammatory lymphocyte infiltration into the CNS, while increasing infiltration of Tregs. Conclusions Our study demonstrates that although IL-26 is preferentially expressed by TH17 lymphocytes, it promotes BBB integrity in vitro and in vivo and is protective in chronic EAE, highlighting the functional diversity of cytokines produced by TH17 lymphocytes. Glossary BBB=blood-brain barrier; CLDN=claudins; DEG=differentially expressed gene; EAE=experimental autoimmune encephalomyelitis; EC=endothelial cell; GM-CSF=granulocyte macrophage colony-stimulating factor; GSEA=gene set enrichment analysis; HDs=healthy donors; IL=interleukin; JAM=junctional adhesion molecule; MOG=myelin oligodendrocyte glycoprotein; mRNA=messenger RNA; OCLN=occludin; OND=other neurologic disease controls; rh=recombinant human; TEER=transendothelial electrical resistance; TH=T helper; TJ=tight junction; ZO=zonula occludens The abundance of immune cells and their products in CNS lesions and in the CSF of patients with multiple sclerosis (MS), together with the genetic risk conferred by immune gene variants, supports the concept that MS is an autoimmune disorder.1,–,5 It is strongly believed that myelin-reactive CD4+ T helper (TH) lymphocytes are activated by an environmental trigger, after which they cross the blood-brain barrier (BBB), invade the CNS, and initiate a chronic, relapsing inflammatory cascade leading to tissue damage.3,6,–,8 These TH lymphocytes produce cytokines such as interleukin (IL)-17, IL-22, and granulocyte macrophage colony-stimulating factor (GM-CSF); the former 2 being involved in BBB breakdown8 and the latter stimulating CCR2+ monocytes, which promote tissue damage.9 IL-26 was first discovered as an inducible gene in Herpesvirus saimiri–transformed human T lymphocytes,10 but has since been described as a TH17-associated cytokine that is regulated by IL-1β, IL-23, and RORγt.5,11,12 IL-26 is part of the IL-10 cytokine family and binds to a heterodimeric receptor composed of the IL-10R2 and IL-20R1 chains, which results in activation of STAT1 and STAT3.13,14 Although the IL26 gene is absent in rodents, Ohnuma et al15 have recently demonstrated that recombinant human (rh) IL-26 can bind to and function through the murine receptor complex. In recent years, studies regarding the role of IL-26 in various immunologic diseases have started to emerge.15,–,20 In chronic inflammatory diseases including Crohn disease, rheumatoid arthritis, chronic hepatitis C infection, and chronic graft-versus-host disease, IL-26 appears to play a proinflammatory role, acting on epithelial cells, monocytes, natural killer cells, and fibroblasts, respectively.15,–,17,19 It was also recently found to be involved in antibacterial host defense.18,20,–,22 However, the role of IL-26 in MS, where TH17 lymphocytes are believed to play a major role, has not yet been investigated. In the current study, we hypothesized that IL-26 has a proinflammatory role and is involved in BBB disruption. We report that the concentration of IL-26 is elevated in the serum and CSF of untreated patients with MS compared with healthy individuals and controls, respectively. We further demonstrate that IL-26–expressing TH lymphocytes are found within perivascular infiltrates in the brain of patients with MS. In contrast to our hypothesis, we demonstrate that the administration of IL-26 in mice with experimental autoimmune encephalomyelitis (EAE) reduces disease severity compared with control-treated mice. This is associated with a barrier-promoting effect of IL-26 through upregulation of tight junction molecules. Overall, our results demonstrate that IL-26, preferentially produced by TH17 lymphocytes, has a beneficial effect on barrier function during neuroinflammation and reduces clinical and pathologic disease burden in sterile autoimmune CNS inflammation. Methods Ethics Blood was obtained from patients with MS and healthy donors (HDs) after written informed consent and ethical approval (Centre Hospitalier de l'Université de Montréal research ethic committee approval number BH07.001). Patients were classified according to the 2010 McDonald's revised criteria for MS diagnosis (Polman et al., 2011), as previously described (Larochelle et al., 2012). Other neurologic disease controls (OND) consisted of migraine, glioblastoma, and subjective neurologic symptoms with normal neurologic examination, normal MRI, and normal CSF analysis. With informed consent and ethical approval (Centre Hospitalier de l'Université de Montréal research ethic committee approval number BH07.001), human temporal lobe material was obtained from patients who underwent surgical treatment for intractable temporal lobe epilepsy and used for isolation of primary BBB endothelial cells (ECs). Human fetal brain tissue was obtained with ethical approval (Centre Hospitalier de l'Université de Montréal research ethic committee approval number HD07.002) for isolation of astrocytes. All animal procedures were approved by the CHUM Animal Care Committee in accordance with the guidelines of the Canadian Council on Animal Care (approval number N15035APs). Data availability Data not provided in the article because of space limitations can be shared at the request of other investigators for purposes of replicating procedures and results. Results IL-26 is preferentially expressed by TH17 lymphocytes To address the phenotype of TH lymphocytes expressing IL-26, we cultured human naive (CD45RA+) TH lymphocytes from HDs in TH1, TH2, or TH17 differentiating conditions. We found that TH17 lymphocytes expressed the highest level of IL26 messenger RNA (mRNA) after 3 days in culture, which correlated with expression of IL17 (figure e-1, A and B, links.lww.com/NXI/A295). TH1 lymphocytes also expressed IL26 mRNA, but only after 6 days in culture. To identify the cytokine (or combination of cytokines) that induces expression of IL26 mRNA in naive TH lymphocytes, we treated naive TH lymphocytes from HDs with TH17-inducing cytokines daily for 6 days. We found that the combination of IL-1β, IL-23, and transforming growth factor (TGF)-β1 induced the highest level of IL26 mRNA expression in these lymphocytes (figure e-1C) and that IL-6, alone or in combination with other cytokines, did not significantly affect IL26 gene expression. To address whether IL26 is also expressed in memory TH lymphocytes, we cultured CD45RO+ TH lymphocytes from HDs in TH1- or TH17-polarizing conditions. IL-26 mRNA (figure e-1D) and protein (figure e-1E) expression was highest in TH17 lymphocytes, generated from memory CD4+ lymphocytes after 6 days in culture, when compared with TH1 lymphocytes or ex vivo memory TH lymphocytes. Because intracellular flow cytometry with commercially available antibodies does not work in our hands, we used immunocytofluorescent microscopy to analyze coexpression of IL-26 with IL-17 and RORγt in TH17 differentiated lymphocytes of HDs (figure e-1F). Quantification revealed a greater enrichment of IL-26+ cells in IL-17–expressing TH lymphocytes compared with interferon (IFN)-γ–expressing TH lymphocytes (figure e-1G). In addition, levels of IL26 mRNA significantly correlated with mRNA levels of TH17 markers IL17, IL22, RORC, and MCAM, but not with Csf2 (figure e-1H). To investigate whether IL-26 is primarily associated with TH17 lymphocytes and not with other immune cells, we measured its levels via qPCR in different ex vivo or activated/differentiated immune cell subsets collected from HDs. The highest IL26 mRNA levels were detected in TH17 lymphocytes polarized from memory TH lymphocytes (figure e-2A), whereas lower IL26 mRNA levels were detected in CD8+ T cytotoxic 17 (TC17) lymphocytes and TCR-stimulated memory TH lymphocytes without addition of polarizing cytokines. B lymphocytes, monocytes, M1 and M2 macrophages, and immature and mature dendritic cells (DCs) did not have detectable IL26 mRNA levels. IL-26 is elevated in the serum and CSF of untreated patients with MS To determine whether IL-26 is augmented in relevant biological compartments during MS disease, we measured the concentration of IL-26 in the serum and CSF of controls and untreated patients with MS. IL-26 was significantly elevated in the serum of untreated patients with relapsing-remitting MS compared with HDs (figure 1A). In addition, IL-26 was approximately twofold higher in the CSF of untreated patients with MS compared with OND (figure 1B). Using MS patient–derived TH17 differentiated lymphocytes, we also found that IL26 mRNA significantly correlated with expression of IL17, IL22, RORC, and MCAM (figure 1C), as previously demonstrated using the blood of HDs. In addition, expression of IL26 mRNA also correlated with expression of Csf2 mRNA in TH17 lymphocytes of patients with MS (figure 1C). Finally, immunohistofluorescence imaging of active MS brain lesions (18 lesions, 6 distinct patients) revealed innumerable CD4+ T lymphocytes expressing IL-26 in perivascular infiltrates (figure 1D). Figure 1 IL-26 is increased in the serum and CSF of untreated patients with MS and is expressed by CNS-infiltrating lymphocytes (A) IL-26 protein levels in the serum of HDs (n = 6) and untreated patients with RRMS (MS, n = 9). (B) IL-26 protein levels in the CSF of persons with OND (n = 8) and untreated patients with MS (n = 10). (C) Relative expression of IL26 mRNA plotted against the relative expression of other T helper (TH)17-associated genes (IL17, IL22, Csf2, RORC, and MCAM) in ex vivo CD4+CD45RO+ T lymphocytes, TH1- and TH17-polarized lymphocytes (after 6 days in culture) from 5 to 18 patients with MS. mRNA expression is relative to 18S mRNA and was assessed by qPCR. (D) Autopsy-derived MS CNS material was stained with Luxol Fast Blue/H&E (LHE, left panel) to identify lesions (dashed line). Colocalization of IL-26 (red) with CD4+ cells (green) and TOPRO-3 (blue, nuclei) in MS lesions is shown (left panel). As a control, CNS material was stained with an isotype control and secondary antibody (red) or secondary antibody alone (green, right panel). Images shown are representative of immunostainings on CNS samples from 6 patients with MS (3 tissue blocks per patient). Scale bars: 25 μm. Data are presented as mean ± SEM (A and B). *p < 0.05; **p < 0.01. Statistical tests: Student 2-tailed t test (A and B) and Pearson correlation (C). HDs = healthy donors; IL = interleukin; mRNA = messenger RNA; OND = other neurologic disease controls; RRMS = relapsing-remitting MS. IL-26 increases BBB tightness through upregulation of tight junction molecules Our group previously demonstrated that the TH17-associated cytokines, IL-17A and IL-22, increase BBB permeability and facilitate TH lymphocyte migration across the BBB.8 Because IL-26 is preferentially expressed by TH17 lymphocytes, we hypothesized that it has a similar effect on the BBB. To investigate whether BBB ECs can respond to IL-26 stimulation, we first assessed expression of the IL-10R2 and IL-20R1 chains. Indeed, we detected both IL-26 receptor chains on primary cultures of human BBB ECs in vitro (figure 2A) as well as on CNS-ECs in situ (figure 2, B and C). Inflammatory conditions did not significantly affect the expression of either chain (figure 2A). Further investigation of the 2 receptor chains demonstrated their spatial colocalization on ECs in situ both in normal-appearing white matter and in MS lesions (figure 2, B and C), suggesting that these cells can respond to IL-26. Figure 2 Presence of IL-10R2 and IL-20R1 on BBB ECs (A) IL-26 receptor expression on resting (CTL) and inflamed (IFNγ and TNFα, I/T) human BBB ECs by Western blot. Representative image of n = 4 experiments is shown. (B) Autopsy-derived MS CNS material stained for IL-10R1 (red) and IL-20R2 (green) and with TOPRO-3 (blue, nuclei). Representative plots of IL-20R1 and IL-10R2 signal intensity and colocalization of both receptor chain (upper graphs) in areas 1 and 2 are shown for NAWM (left) or MS lesions (right). (C) Semiquantitative analysis of the signal intensity from 10 µm z-stack reconstructions along the line markers in the images shown in (B), for IL-20R1 and IL-10R2, in NAWM and MS lesion. Mean fluorescence intensity was averaged from 3 distinct measurements on each vessel (n = 33 blood vessels). Images shown are representative of immunostainings on brain lesions of 6 patients with MS (1–2 tissue blocks per patient). Scale bars: 50 μm for lesion and 30 μm for NAWM. Data are represented as mean ± SEM (C). Statistical tests: Student 2-tailed t test (C). BBB ECs = blood-brain barrier endothelial cells; CTL = control; IL = interleukin; NAWM = normal-appearing white matter. To assess the effect of IL-26 on human BBB ECs, we investigated the transcriptome of resting (control [CTL]) vs rhIL-26 treated BBB ECs. In total, 459 differentially expressed genes (DEGs; false discovery rate < 0.1 & |logFC| > 0.25) were identified, all in the 100 ng/mL condition (figure e-3, A and B, links.lww.com/NXI/A295). To understand what functional pathways might be associated with these transcriptional changes, a ranked gene-set enrichment analysis (GSEA) approach was used to alleviate the limitations of setting predefined numerical thresholds of significance to form discrete gene sets (See Methods section). Our data demonstrate that rhIL-26 treatment resulted mostly in a general downregulation of pathways, notably those involved in the signaling of proinflammatory cytokines tumor necrosis factor-α, IFN-γ, IFN-α, and IL-6, as well as in apoptosis and adipogenesis (figure 3A, figure e-3C). The most significant enrichment was associated with a downregulation of oxidative phosphorylation and was consistent in both conditions (figure e-3C). This suggests that IL-26 could mediate cellular metabolism through decrease in energy production. Of interest, using the ranked approach for GSEA shows that although there are no DEGs in the 10 ng/mL condition according to predefined criteria, the pathways associated with the transcriptomic variation is consistent with the 100 ng/mL condition, indicating that the response in both conditions is correlated. We indeed observe correlation between the fold changes calculated in each condition (R = 0.62, p < 2.2 × 10−16). Because BBB integrity is highly dependent on the expression of tight junction (TJ) molecules (e.g., junctional adhesion molecules [JAM], claudins [CLDN], occludin [OCLN], and zonula occludens [ZO]),23 we hypothesized that some of these molecules would also be downregulated on IL-26 stimulation. Therefore, we decided to focus on the expression profiles of specific BBB-associated TJ molecules within the same transcriptome data. This allowed us to observe that stimulation with IL-26 upregulates the mRNA levels of TJP1 (ZO-1), OCLN, and CLDN18, while also downregulating F11R (JAM-1) levels (figure 3B). CLDN5 mRNA was below the detection limit. Collectively, these data indicate that unlike IL-17, IL-26 has a unique effect on BBB ECs where it downregulates proinflammatory pathways and upregulates TJ molecules. Figure 3 IL-26 enhances BBB function in vitro (A and B) Human BBB ECs derived from 1 donor were treated with 0, 10, or 100 ng/mL recombinant human (rh)IL-26 in triplicate for 24 hours. RNA sequencing was performed on messenger RNA (mRNA) isolated from these samples. (A) A heatmap of the enrichment scores for pathways found in the hallmark curated database is shown. Only the pathways that are significant in at least 1 condition are shown (adjusted p value < 0.25). Gray tiles are nonsignificant, and the enrichment is not shown for clarity purposes. (B) The boxplots show the distributions of the voom-normalized expression of claudin 18 (CLDN18), ZO-1 (TJP1), JAM-1 (F11R), and occludin (OCLN) mRNA levels using the same samples as for (A). Normalization was performed with limma/voom. (C) JAM-1 protein expression by human BBB ECs pretreated with or without 5 μg/mL anti–IL-10R2 or 5 μg/mL anti–IL-20R1. After 1 hour, 100 ng/mL rhIL-26 or control was added for 24 hours. Samples were analyzed by Western blot (n = 3). Protein expression, relative to beta-actin, was calculated and normalized to the respective controls (upper panels, white dotted line). (D) In vitro permeability was investigated using a modified Boyden chamber assay. The permeability coefficients of 3-kDa, 10-kDa, and 70-kDa fluorescently labeled dextran through untreated (CTL), 100 ng/mL IL-26, or 40% ACM (positive control) treated monolayer of human BBB ECs (n = 4 experiments). Each condition was performed in triplicate. (E) Transendothelial electrical resistance of human BBB EC monolayers was measured continuously for 92 hours. ACM (positive control) or rhIL-26 was added 24 hours after BBB EC plating (dotted line, left panel and arrow right panel). The right panel is an enlarged representation of the insert box in the left panel. Representative graph of n = 4 experiments is shown. All conditions were performed in triplicate. Data are represented as mean ± SEM (C and D). *p < 0.05; ***p < 0.001. Statistical tests: Student 2-tailed t test (C), a 1-way analysis of variance (ANOVA) (D), and repeated-measures 1-way ANOVA followed by the Dunnett multiple comparison test (E). ACM = astrocyte-conditioned medium; BBB ECs = blood-brain barrier endothelial cells; CTL = control; IL = interleukin; SEM = standard error of the mean. To confirm our observations at the protein level, we performed Western blot analysis on IL-26–treated BBB ECs and observed an increase in JAM-1 protein levels compared with CTL BBB ECs (figure 3C and figure e-4A, links.lww.com/NXI/A295, p = 0.053). The ZO-1 protein level did not change (figure e-4B, p = 0.431). To confirm that JAM-1 upregulation is due to IL-26 signaling via its heterodimeric receptor, we pretreated BBB ECs with blocking antibodies against IL-10R2 or IL-20R1 before rhIL-26 was added. The IL-26–induced upregulation in the JAM-1 level in BBB ECs was prevented by pretreatments with anti–IL-10R2 or anti–IL-20R1 (figure 3C and figure e-4A). To investigate whether IL-26 has a functional effect on BBB integrity, we performed an in vitro permeability assay using modified Boyden chambers. Briefly, we treated primary human BBB ECs, grown to confluency on inserts, with rhIL-26, and measured their permeability to 3-, 10- and 70-kDa dextrans via spectroscopy. Of interest, rhIL-26–treated human BBB ECs acquired a significantly lower permeability coefficient to each of the dextrans compared with untreated BBB ECs (figure 3D), suggesting that IL-26 indeed has a positive effect on BBB integrity compared with IL-17 and IL-22. Consistent with these observations, the transendothelial electrical resistance (TEER) of human BBB ECs monolayers was also significantly and sustainably increased by rhIL-26 treatment to the same extent as the positive control (astrocyte-conditioned medium; figure 3E). IL-26 therapy reduces BBB permeability during neuroinflammation Although mice do not express IL-26, they do express a functional receptor, which responds to rhIL-26.15 Previous studies on IL-26 have shown that results obtained from mouse models using rhIL-26 provide information, which is supportive of human in vitro or in situ studies.15,24,25 Before investigating the contribution of IL-26 on BBB permeability in vivo, we first sought to confirm whether rhIL-26 affects mouse BBB ECs in vitro. Mouse brain ECs were isolated and treated with 100 ng/mL rhIL-26, and subsequent expression of TJ molecules JAM-1, ZO-1, and CLDN5 was assessed. In line with our aforementioned observations, we found that rhIL-26–treated mouse BBB ECs significantly upregulated the expression of both JAM-1 and CLDN5 (figure 4A), whereas it had no effect on ZO-1 (not shown). In addition, rhIL-26 enhanced the organizational structure of the intercellular TJ strands between mouse BBB ECs (figure 4A). To study the impact of IL-26 on the BBB in vivo, we analyzed its effect on BBB permeability in EAE mice immunized with myelin oligodendrocyte glycoprotein (MOG)35–55 and treated with 200 ng rhIL-26 daily IP from day 5–24 postimmunization. In situ analysis of endogenous serum proteins extravasation into the CNS revealed that rhIL-26 treatment significantly reduced extravasation of both IgG (figure 4B) and fibrinogen (figure 4C) in spinal cords of EAE animals compared with Hanks balanced salt solution (control)-treated mice. Figure 4 IL-26 treatment reduces fibrinogen and IgG leakage in EAE mice (A) Monolayers of mouse BBB ECs immunostained for tight junction molecules JAM-A (red) and claudin-5 (green) and nuclei (blue) after treatment with IFN-γ and TNF-α (I/T), 100 ng/mL IL-26, or left untreated (24 hours treatment). Representative images of n = 4 experiments are shown. JAM-A and Claudin-5 mean fluorescent intensity across the mouse BBB EC membrane was quantified at 30 different places per image. Three fields of view were randomly analyzed and quantified for each condition and for each experiment (n = 240 measurements per condition). Scale bars: 100 μm. (B and C) MOG35–55 immunized C57BL/6 mice were injected IP with either HBSS or 200 ng recombinant human IL-26 in HBSS daily from day 5 to day 24. Immunohistofluorescence of IgG (green, B, central panel), fibrinogen (green, C, central panel), and PECAM-1 (red, left panel) was performed on spinal cords of EAE mice at day 27 postinduction. Fluorescence of IgG (B, right panel) and fibrinogen (C, right panel) extravasation was quantified (n = 3 animals per group and 3 sections per mouse). Scale bars: 25 μm. Data are represented as mean ± SEM (A–C). *p < 0.05; **p < 0.01; ***p < 0.001. Statistical tests: 1-way analysis of variance followed by the Dunnett multiple comparison test (A) and Student 2-tailed t test (B and C). BBB ECs = blood-brain barrier endothelial cells; EAE = experimental autoimmune encephalomyelitis; HBSS = Hanks balanced salt solution; IL = interleukin; MOG = myelin oligodendrocyte glycoprotein; SEM = standard error of the mean. IL-26 therapy reduces EAE severity and limits infiltration of pathogenic T lymphocytes To evaluate whether the protective effects of IL-26 on the BBB in EAE translate into a clinically detectable benefit, we monitored the symptoms of EAE mice treated with IL-26 daily for 45 days. We found that rhIL-26–treated EAE mice experienced a less severe clinical disease course compared with control-treated mice, particularly during the chronic phase of the disease (figure 5, A and B), but also at the peak of the disease. Surprisingly, this beneficial outcome was associated with an increased number of CNS-infiltrating TH lymphocytes at peak of disease, and a decreased number during the chronic phase, compared with control-treated mice (figure 5C). A deeper analysis of these lymphocytes revealed that the administration of IL-26 resulted in an infiltration of both conventional and regulatory (CD4+Foxp3+CD25+) T lymphocytes (Treg) at peak of disease (figure e-5A, links.lww.com/NXI/A295 and figure 5C). When analyzing cytokine production by different TH subsets, we found that the proportion and number of IL-17–expressing TH lymphocytes were significantly reduced in the CNS of rhIL-26–treated animals, whereas the number and proportion of IL-10–expressing TH lymphocytes were increased compared with control animals (figure 5D). No clear effect was observed for IFN-γ+IL-17+ TH lymphocytes, but a tendency toward a lower proportion of GM-CSF+IL-17+ TH lymphocytes was observed (figure 5D). In the myeloid compartment within the CNS at peak of disease, no significant differences were found for the number of inflammatory (Ly6C+) or patrolling (Ly6C−) monocytes between IL-26–treated and control animals (figure e-5, B and C). In addition, no differences were observed for the numbers of Ly6Cint neutrophils (figure e-5D). Of interest, the number of microglia was decreased in the chronic phase of IL-26–treated mice compared with control mice (figure e-5E). Figure 5 IL-26 treatment ameliorates clinical symptoms of EAE (A) MOG35–55 immunized C57BL/6 mice injected IP with either 200 μL HBSS (black squares) or 200 μL containing 200 ng recombinant human IL-26 in HBSS (gray open circles) were scored (left panel) and weighed (normalized to day 0; right panel) daily. IL-26 treatment was started at day 5 after disease induction and was given daily until day 24. (B) Distribution and sum of the clinical scores for the 2 different treatment groups. Each dot is 1 animal. (C) The CNS of perfused mice was collected, and infiltrating immune cells were isolated, counted, and analyzed by flow cytometry at onset (day 7), peak (day 15), and chronic (day 27) phases of disease. (D) The CNS, spleen, and LN of perfused mice were collected, and immune cells were isolated, counted, and analyzed by flow cytometry for intracellular cytokine staining at peak (day 15) of disease. Bars to the left of the dotted line represent cell percentages (left y-axis), and bars to the right of the dotted line represents total number of cells (right y-axis). Data are represented as mean ± SEM (A–D). *p < 0.05. Statistical analyses performed: Student 2-tailed t test of the area under the curve (A); Student 2-tailed t test (B–D). Data shown are representative of 6 independent EAE experiments with 9–30 animals per group (A and B). n = 3 animals per group (C and D). EAE = experimental autoimmune encephalomyelitis; GM-CSF = granulocyte macrophage colony-stimulating factor; HBSS = Hanks balanced salt solution; IL = interleukin; LN = lymph nodes; MOG = myelin oligodendrocyte glycoprotein; SEM = standard error of the mean. Discussion Although IL-26 is suspected to be proinflammatory and antimicrobial,15,–,17,19,20 the exact role of this cytokine in the context of neuroinflammatory disorders has not been identified. Here, we demonstrated that IL-26, in contrast to IL-17 and IL-22, produced by TH17 lymphocytes, reduced BBB permeability through upregulation of TJ molecules, thereby reducing clinical severity in EAE mice treated with rhIL-26 in vivo. Our data demonstrate that IL26 mRNA expression was induced in naive TH lymphocytes by a combination of the TH17-polarizing cytokines IL-1β, IL-23, and TGF-β1, whereas IL-6, a nonredundant cytokine for TH17 differentiation, seems to have barely an effect on IL-26 levels. In addition, IL26 transcript expression correlated strongly with TH17 markers. Overall, these data support its preferential association with the TH17 lineage, although broader regulation across TH lineages cannot be ruled out, especially because our postmortem MS brain analyses show that the majority of TH lymphocytes in perivascular cuffs express IL-26. Together with our data showing nondetectable mRNA levels in B cells, monocytes, macrophages, and DCs, this suggests that TH lymphocytes (especially TH17 lymphocytes) are the most relevant source of IL-26 in MS. Because both IL-17 and IL-22 have been shown to be involved in BBB disruption,8 we wanted to determine whether the same held true for IL-26. Surprisingly, IL-26 enhanced BBB integrity by reducing permeability of BBB ECs both in vitro and in vivo. This seemed to be a direct effect because both IL-26 receptor chains were found to be expressed on BBB ECs. We further demonstrated that this reduction in leakage was due to an increased expression of TJ molecules, especially JAM-1 and CLDN5. Although our pathway analysis indicated an increase in TJP1, this was not seen on the protein level. A possible explanation could be that the effect on protein levels might take longer than 24 hours. Of interest, F11R levels seemed to be decreased, whereas protein levels were increased after 24 hours of IL-26 treatment. This could also be related to the time point of protein detection. However, it is also possible that the translation rate is increased on IL-26 treatment. Protein levels are, however, the most important readout for TJ molecules and hold the most biological relevance for BBB integrity. These results in combination with the observed increase in IL-26 levels in MS suggest a compensatory mechanism to restore BBB integrity and reduce BBB leakage. A barrier-promoting effect was already shown for IL-10,26–28 which shares one of the receptor chains of the IL-26 receptor, suggesting that the barrier-promoting effect of IL-26 is established through signaling via the IL-10R2 subunit. We have confirmed that both receptor units, IL-10R2 and IL-20R1, are critically involved in this barrier-enhancing effect. Because it has been shown that activation of both receptor units signals via the STAT1/STAT3 pathway,14 the barrier-strengthening effect of IL-26 seems to also be mediated via this pathway. Recently, Itoh et al.29 showed a possible opposite effect of IL-26 on vasculature in a psoriasis model. This difference might either be due to a secondary inflammatory effect via the epidermal keratinocytes and dermal fibroblast or a direct effect. To study this, they used human umbilical vein ECs, which were able to respond to IL-26 stimulation. However, these cells did not express the IL-20R1, which was confirmed by the lack of p-STAT3 upregulation. Our data show that human primary BBB ECs do express the IL-20R1 and that IL-26 signals via this receptor. The fact that both cell types react differently to IL-26 might not be very surprising because numerous studies have already reported differences with regard to permeability, TEER, migration, and chemokine production.30,31 A previous study has shown that IL-26 is not expressed in mice, although they do express a functional IL-26 receptor.15 Therefore, murine cell lines or mouse models have been used to further unravel the mechanisms of IL-26 and to study the effect of IL-26 in vivo.15,24,25 Moreover, the results of these studies were in line with findings obtained in human in vitro experiments. To assess the role of IL-26 in vivo in the context of neuroinflammation, we administered rhIL-26 to EAE mice immunized with MOG35–55. Mice treated with IL-26 displayed a milder disease course and a reduced BBB permeability. Most surprisingly, there were a higher number of IL-10–producing CNS-infiltrating TH lymphocytes in the IL-26–treated group. In parallel, we also observed a reduction in CNS-infiltrating pathogenic TH lymphocytes in IL-26–treated mice (IL-17+IFN-γ+). Whether these findings are the result of (1) suppression of pathogenic TH lymphocytes by infiltrating Tregs, (2) skewing of pathogenic TH lymphocytes toward Tregs by modification in the cytokine environment induced by IL-26, (3) a direct effect of IL-26 on polarization of TH lymphocytes, or finally (4) an effect of IL-26 on the expression of CAMs by BBB ECs, has yet to be investigated. However, it is unlikely that IL-26 directly skews TH lymphocytes toward a regulatory phenotype because these cells do not express the IL-20R1. This is supported by our data showing that rhIL-26 does not influence TH17 lymphocyte polarization (figure e-6A, links.lww.com/NXI/A295). In addition, a study by Oral et al.32 also shows that IL-26 did not affect naive TH lymphocyte differentiation, proliferation, or viability. An indirect effect on TH lymphocytes, via antigen-presenting cells, can not be excluded. Recent studies show that IL-26 can bind to genomic and mitochondrial self-DNA and bacterial DNA and activate the Toll-like receptor 9 or directly activate stimulator of interferon genes in myeloid cells.20,33 Nevertheless, this effect of IL-26 induces IFN-α, IL-6, and IL-1β, which trigger a proinflammatory, rather than an anti-inflammatory, response. Alternatively, IL-26 could also act on other immune or CNS cells, which would, in turn, skew TH lymphocytes toward an IL-10–producing phenotype. Finally, as Tregs have been reported to migrate faster across BBB ECs than non-Tregs,34 we therefore speculate that IL-26, produced by CNS-infiltrating TH lymphocytes in the context of neuroinflammation, could affect the recruitment of IL-10–producing TH lymphocytes across the CNS barriers by a yet unknown mechanism. In conclusion, our data reveal that IL-26 is a protective cytokine, which is preferentially produced by TH17 lymphocytes on inflammation. During neuroinflammation, the administration of IL-26 promotes BBB functions through upregulation of TJ molecules, increases the number of IL-10–producing CNS-infiltrating TH lymphocytes, and reduces the number of CNS-infiltrating pathogenic TH lymphocytes. These findings might have important therapeutic implications for patients with MS, which will be validated in future studies. Study funding This work was funded by a grant from the Canadian Institutes of Health Research (MOP136980). A. Prat holds a senior Canada Research Chair in Multiple Sclerosis. M. Charabati held a postdoctoral studentship from the Fonds de recherche du Québec–Santé (FRQS) and is now supported by a doctoral scholarship from the Multiple Sclerosis Society of Canada (MSSC). E. Peelen and S. Zandee held a postdoctoral studentship from the FRQS/MSSC Partnership Award. B. Broux held a postdoctoral studentship from Fonds Wetenschappelijk Onderzoek–Vlaanderen. L. Hachehouche held PhD studentships from the MSSC, FRQS, and Neuroinflammation Training Program. Disclosure The authors report no disclosures relevant to the manuscript. Go to Neurology.org/NN for full disclosures. Acknowledgment The authors are grateful to Dr. D. Gauchat (Flow Cytometry Core Facility, CRCHUM, Montreal, QC, Canada) for her technical support with flow cytometry and Dr. A. Cleret-Buhot (Cell Imaging Core Facility, CRCHUM, Montreal, QC, Canada) for her technical support with confocal microscopy. They thank Dr. E. Haddad (Pediatric Immunologist, CHU Sainte-Justine Research Center) for providing human fetal CNS material. Appendix Authors Footnotes Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article. ↵* These authors contributed equally to the manuscript. ↵‡ These authors should be considered co–last authors. The Article Processing Charge was funded by the authors. Received April 18, 2020. Accepted in final form July 13, 2020. Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. References 1.↵Weiner HL. Multiple sclerosis is an inflammatory T-cell-mediated autoimmune disease. Arch Neurol 2004;61:1613–1615.OpenUrlCrossRefPubMed 2.↵Nylander A, Hafler DA. Multiple sclerosis. J Clin Invest 2012;122:1180–1188.OpenUrlCrossRefPubMed 3.↵Broux B, Stinissen P, Hellings N. Which immune cells matter? The immunopathogenesis of multiple sclerosis. Crit Rev Immunol 2013;33:283–306.OpenUrlCrossRefPubMed 4.↵Beecham AH, Patsopoulos NA, Xifara DK, et alInternational Multiple Sclerosis Genetics Consortium, Beecham AH, Patsopoulos NA, Xifara DK, et al. Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis. Nat Genet 2013;45:1353–1360.OpenUrlCrossRefPubMed 5.↵Manel N, Unutmaz D, Littman DR. The differentiation of human T(H)-17 cells requires transforming growth factor-beta and induction of the nuclear receptor RORgammat. Nat Immunol 2008;9:641–649.OpenUrlCrossRefPubMed 6.↵Hafler DA. Multiple sclerosis. J Clin Invest 2004;113:788–794.OpenUrlCrossRefPubMed 7.↵Codarri L, Greter M, Becher B. Communication between pathogenic T cells and myeloid cells in neuroinflammatory disease. Trends Immunol 2013;34:114–119.OpenUrlCrossRefPubMed 8.↵Kebir H, Kreymborg K, Ifergan I, et al. Human TH17 lymphocytes promote blood-brain barrier disruption and central nervous system inflammation. Nat Med 2007;13:11731175.OpenUrl 9.↵Croxford AL, Lanzinger M, Hartmann FJ, et al. The cytokine GM-CSF drives the inflammatory signature of CCR2 monocytes and licenses autoimmunity. Immunity 2015;43:502–514.OpenUrlCrossRefPubMed 10.↵Knappe A, Hor S, Wittmann S, Fickenscher H. Induction of a novel cellular homolog of interleukin-10, AK155, by transformation of T lymphocytes with herpesvirus saimiri. J Virol 2000;74:3881–3887. 11.↵Wilson NJ, Boniface K, Chan JR, et al. Development, cytokine profile and function of human interleukin 17-producing helper T cells. Nat Immunol 2007;8:950–957.OpenUrlCrossRefPubMed 12.↵Donnelly RP, Sheikh F, Dickensheets H, Savan R, Young HA, Walter MR. Interleukin-26: an IL-10-related cytokine produced by Th17 cells. Cytokine Growth Factor Rev 2010;21:393–401.OpenUrlCrossRefPubMed 13.↵Sheikh F, Baurin VV, Lewis-Antes A, et al. Cutting edge: IL-26 signals through a novel receptor complex composed of IL-20 receptor 1 and IL-10 receptor 2. J Immunol 2004;172:2006–2010. 14.↵Hor S, Pirzer H, Dumoutier L, et al. The T-cell lymphokine interleukin-26 targets epithelial cells through the interleukin-20 receptor 1 and interleukin-10 receptor 2 chains. J Biol Chem 2004;279:33343–33351. 15.↵Ohnuma K, Hatano R, Aune TM, et al. Regulation of pulmonary graft-versus-host disease by IL-26+CD26+CD4 T lymphocytes. J Immunol 2015;194:3697–3712. 16.↵Dambacher J, Beigel F, Zitzmann K, et al. The role of the novel Th17 cytokine IL-26 in intestinal inflammation. Gut 2009;58:1207–1217. 17.↵Corvaisier M, Delneste Y, Jeanvoine H, et al. IL-26 is overexpressed in rheumatoid arthritis and induces proinflammatory cytokine production and Th17 cell generation. PLoS Biol 2012;10:e1001395.OpenUrlCrossRefPubMed 18.↵Che KF, Tengvall S, Levanen B, et al. Interleukin-26 in antibacterial host defense of human lungs. Effects on neutrophil mobilization. Am J Respir Crit Care Med 2014;190:10221031.OpenUrl 19.↵Miot C, Beaumont E, Duluc D, et al. IL-26 is overexpressed in chronically HCV-infected patients and enhances TRAIL-mediated cytotoxicity and interferon production by human NK cells. Gut 2015;64:1466–1475. 20.↵Meller S, Di Domizio J, Voo KS, et al. TH17 cells promote microbial killing and innate immune sensing of DNA via interleukin 26. Nat Immunol 2015;16:970–979.OpenUrlCrossRefPubMed 21.↵Scala E, Di Caprio R, Cacciapuoti S, et al. A new T helper 17 cytokine in hidradenitis suppurativa: antimicrobial and proinflammatory role of interleukin-26. Br J Dermatol 2019;181:1038–1045.OpenUrl 22.↵Woetmann A, Alhede M, Dabelsteen S, et al. Interleukin-26 (IL-26) is a novel antimicrobial peptide produced by T cells in response to staphylococcal enterotoxin. Oncotarget 2018;9:19481–19489.OpenUrlCrossRef 23.↵Luissint AC, Artus C, Glacial F, Ganeshamoorthy K, Couraud PO. Tight junctions at the blood brain barrier: physiological architecture and disease-associated dysregulation. Fluids Barriers CNS 2012;9:23.OpenUrlCrossRefPubMed 24.↵Bao A, Che KF, Bozinovski S, et al. Recombinant human IL-26 facilitates the innate immune response to endotoxin in the bronchoalveolar space of mice in vivo. PLoS One 2017;12:e0188909.OpenUrlCrossRefPubMed 25.↵Peng YJ, Wang CY, Lin YH, et al. Interleukin 26 suppresses receptor activator of nuclear factor kappaB ligand induced osteoclastogenesis via down-regulation of nuclear factor of activated T-cells, cytoplasmic 1 and nuclear factor kappaB activity. Rheumatology (Oxford) 2016;55:2074–2083.OpenUrlCrossRefPubMed 26.↵Chen X, Duan XS, Xu LJ, et al. Interleukin-10 mediates the neuroprotection of hyperbaric oxygen therapy against traumatic brain injury in mice. Neuroscience 2014;266:235–243.OpenUrl 27.Liu Z, Zhang P, Ma Y, et al. Lactobacillus plantarum prevents the development of colitis in IL-10-deficient mouse by reducing the intestinal permeability. Mol Biol Rep 2011;38:1353–1361.OpenUrlCrossRefPubMed 28.↵Mazzon E, Puzzolo D, Caputi AP, Cuzzocrea S. Role of IL-10 in hepatocyte tight junction alteration in mouse model of experimental colitis. Mol Med 2002;8:353–366.OpenUrlPubMed 29.↵Itoh T, Hatano R, Komiya E, et al. Biological effects of IL-26 on T cell-mediated skin inflammation, including psoriasis. J Invest Dermatol 2019;139:878–889.OpenUrl 30.↵Man S, Ubogu EE, Williams KA, Tucky B, Callahan MK, Ransohoff RM. Human brain microvascular endothelial cells and umbilical vein endothelial cells differentially facilitate leukocyte recruitment and utilize chemokines for T cell migration. Clin Dev Immunol 2008;2008:384982.OpenUrlCrossRefPubMed 31.↵Shukaliak JA, Dorovini-Zis K. Expression of the beta-chemokines RANTES and MIP-1 beta by human brain microvessel endothelial cells in primary culture. J Neuropathol Exp Neurol 2000;59:339–352.OpenUrlPubMed 32.↵Oral HB, Kotenko SV, Yilmaz M, et al. Regulation of T cells and cytokines by the interleukin-10 (IL-10)-family cytokines IL-19, IL-20, IL-22, IL-24 and IL-26. Eur J Immunol 2006;36:380–388.OpenUrlCrossRefPubMed 33.↵Poli C, Augusto JF, Dauve J, et al. IL-26 confers proinflammatory properties to extracellular DNA. J Immunol 2017;198:3650–3661. 34.↵Schneider-Hohendorf T, Stenner MP, Weidenfeller C, et al. Regulatory T cells exhibit enhanced migratory characteristics, a feature impaired in patients with multiple sclerosis. Eur J Immunol 2010;40:3581–3590.OpenUrlCrossRefPubMed

The aim of this study was to test whether autoantibodies against neurologic surface Ags are found in nonneurologic autoimmune diseases, indicating a broader loss of tolerance. Patient and matched healthy donor (HD) sera were derived from four large cohorts: 1) rheumatoid arthritis (RA) ( n = 194,...