Skip to main content
Advertisement
  • Neurology.org
  • Journals
    • Neurology
    • Clinical Practice
    • Education
    • Genetics
    • Neuroimmunology & Neuroinflammation
  • Online Sections
    • Neurology Video Journal Club
    • Neurology: Neuroimmunology & Neuroinflammation COVID-19 Article Hub
    • Diversity, Equity, & Inclusion (DEI)
    • Innovations in Care Delivery
    • Practice Buzz
    • Practice Current
    • Residents & Fellows
    • Without Borders
  • Collections
    • COVID-19
    • Disputes & Debates
    • Health Disparities
    • Infographics
    • Null Hypothesis
    • Patient Pages
    • Topics A-Z
    • Translations
  • Podcast
  • CME
  • About
    • About the Journals
    • Contact Us
    • Editorial Board
  • Authors
    • Submit New Manuscript
    • Submit Revised Manuscript
    • Author Center

Advanced Search

Main menu

  • Neurology.org
  • Journals
    • Neurology
    • Clinical Practice
    • Education
    • Genetics
    • Neuroimmunology & Neuroinflammation
  • Online Sections
    • Neurology Video Journal Club
    • Neurology: Neuroimmunology & Neuroinflammation COVID-19 Article Hub
    • Diversity, Equity, & Inclusion (DEI)
    • Innovations in Care Delivery
    • Practice Buzz
    • Practice Current
    • Residents & Fellows
    • Without Borders
  • Collections
    • COVID-19
    • Disputes & Debates
    • Health Disparities
    • Infographics
    • Null Hypothesis
    • Patient Pages
    • Topics A-Z
    • Translations
  • Podcast
  • CME
  • About
    • About the Journals
    • Contact Us
    • Editorial Board
  • Authors
    • Submit New Manuscript
    • Submit Revised Manuscript
    • Author Center
  • Home
  • Articles
  • Issues
  • COVID-19 Article Hub
  • Infographics & Video Summaries

User menu

  • My Alerts
  • Log in

Search

  • Advanced search
Neurology Neuroimmunology & Neuroinflammation
Home
A peer-reviewed clinical and translational neurology open access journal
  • My Alerts
  • Log in
Site Logo
  • Home
  • Articles
  • Issues
  • COVID-19 Article Hub
  • Infographics & Video Summaries

Share

March 2018; 5 (2) ArticleOpen Access

Proinflammatory B-cell profile in the early phases of MS predicts an active disease

Thomas Guerrier, Myriam Labalette, David Launay, Catalina Lee-Chang, Olivier Outteryck, Guillaume Lefèvre, Patrick Vermersch, Sylvain Dubucquoi, Hélène Zéphir
First published December 26, 2017, DOI: https://doi.org/10.1212/NXI.0000000000000431
Thomas Guerrier
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Myriam Labalette
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David Launay
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Catalina Lee-Chang
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Olivier Outteryck
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Guillaume Lefèvre
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Patrick Vermersch
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sylvain Dubucquoi
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hélène Zéphir
From the Université de Lille, CHU Lille, LIRIC-INSERM U 995, FHU Imminent, France.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Full PDF
Citation
Proinflammatory B-cell profile in the early phases of MS predicts an active disease
Thomas Guerrier, Myriam Labalette, David Launay, Catalina Lee-Chang, Olivier Outteryck, Guillaume Lefèvre, Patrick Vermersch, Sylvain Dubucquoi, Hélène Zéphir
Neurol Neuroimmunol Neuroinflamm Mar 2018, 5 (2) e431; DOI: 10.1212/NXI.0000000000000431

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Permissions

Make Comment

See Comments

Downloads
1026

Share

  • Article
  • Figures & Data
  • Info & Disclosures
Loading

Abstract

Objective: To assess whether any alteration of B-cell subset distribution and/or the cytokine production capacities of B cells could be associated with any stage of MS and could be predictive of MS evolution.

Methods: We prospectively enrolled radiologically isolated syndrome (RIS), clinically isolated syndrome (CIS), naive patients with relapsing remitting MS (RRMS) of any disease modifying drug, and healthy controls (HCs). Peripheral blood B-cell subset distributions and the interleukin (IL)-6/IL-10–producing B-cell ratio were assessed by flow cytometry to evaluate their proinflammatory and anti-inflammatory functional properties.

Results: Twelve RIS, 46 CIS, 31 RRMS patients, and 36 HCs were enrolled. We observed that a high IL-6/IL-10–producing B-cell ratio in patients with RIS/CIS was associated with the evolution of the disease in the short term (6 months). This imbalance in cytokine production was mainly explained by an alteration of the production of IL-10 by B cells, especially for the transitional B-cell subset. In addition, a significant increase in IgD−/CD27− B cells was detected in patients with CIS and RRMS compared with HCs (p = 0.01). Apart from this increase in exhausted B cells, no other variation in B-cell subsets was observed.

Conclusions: The association between a high IL-6/IL-10–producing B-cell ratio and the evolution of patients with RIS/CIS suggest a skew of B cells toward proinflammatory properties that might be implicated in the early phases of MS disease.

GLOSSARY

CIS=
clinically isolated syndrome;
EAE=
experimental autoimmune encephalomyelitis;
GM-CSF=
granulocyte-macrophage colony-stimulating factor;
HC=
healthy control;
IL=
interleukin;
LT=
lymphotoxin;
PBMC=
peripheral blood mononuclear cell;
RIS=
radiologically isolated syndrome;
ROC=
receiver operating characteristic;
RRMS=
relapsing remitting MS;
TNFα=
tumor necrosis factor–alpha

MS is a well-known T cell–dependent disease. Cumulative data revealed the involvement of B cells in the pathophysiology of the disease.1 Although the efficacy of B cell–targeting drugs2 implies a key role for B cells in MS, the exact molecular mechanisms of this role remain to be defined.1 The lack of impact of B-cell depletion on CSF oligoclonal bands suggests that the role of B cells in the lesional processes is not restricted to antibody-dependent mechanisms but could involve their cellular functions.1 Data from experimental autoimmune encephalomyelitis models showed that B cells can balance either a proinflammatory response by producing interleukin (IL)-63 or a regulatory response through IL-10 production.4 Some B-cell subsets have been associated with such pro- and anti-inflammatory profiles. Previous studies working on cytokine production by B cells in MS focused on anti-inflammatory cytokines (IL-10) and proinflammatory cytokines (IL-6, granulocyte-macrophage colony-stimulating factor [GM-CSF], lymphotoxin [LT], or tumor necrosis factor–alpha [TNF]α) in established MS disease including patients with disease modifying drugs. Most of those transversal studies showed a decrease of IL-10 and an increase of proinflammatory cytokines produced by B cells i.e., LT and TNFα,5 IL-6,3 or GM-CSF.6 However, Duddy et al.7 did not find any difference in LT and TNFα secretion by B cells. Michel et al.8 did not observe any alteration in IL-10 production by B cells in MS. Such discrepancy might be explained by the studied population, especially the treatment status of patients with MS, but also by heterogeneous methodological conditions mixing early and late MS, treated and naive patients, precluding any firm conclusion. We therefore conducted this prospective study focusing on the early phases of MS disease in patients naive of any disease modifying drug. We aimed to analyze whether from the initial phase of MS naive of any disease modifying drug, the evolution of the disease may be associated with any imbalance in cytokine production capacities by B cells.

METHODS

Patients and healthy volunteers.

Patients in the MS group were enrolled from the Department of Neurology in the University Hospital of Lille. In that group, patients with radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS) were included as well as those with relapsing remitting MS (RRMS) who were defined according to the 2010 McDonald criteria.9 RIS was defined according to Okuda criteria.10 Patients with CIS did not fulfill temporal and spatial dissemination for MS at baseline. Exclusion criteria were any history of taking disease modifying drugs; previous corticosteroid use for management of relapses was accepted. However, all blood samples had to be collected at least 1 month after the last steroid intake. Healthy subjects were enrolled as a control.

All biological procedures and statistical analyses are described in e-Methods at http://links.lww.com/NXI/A15, figures e-1 to e-9 at http://links.lww.com/NXI/A19. For all subjects, phenotypic and functional studies of B cells were performed at the time of the inclusion, i.e., at baseline, to assess (1) any differences between healthy controls (HCs) and the subgroups of patients with MS and (2) to define a potential prognosis biomarker associated with the evolution of the disease. Functional studies were focused on the analysis of intracellular IL-6 and IL-10 production by B cells.

All patients were routinely clinically visited at baseline before blood sampling and every 6 months. In our clinical practice, usually brain and spinal MRIs were performed at diagnosis time and 3 months afterward for patients with CIS.

Standard protocol approvals, registrations, and patients consents.

This study was approved by the local ethical committee (CPP Nord Ouest IV no. IDRCB: 2014 A00248 39). Informed written consent was obtained from all participants.

RESULTS

Eighty-nine patients with MS and 36 HCs were enrolled between 2013 and 2016 (table). There was no difference in age and sex between the different groups.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table

Demographic and clinical features of patients with MS and HCs

The frequency of IgD−/CD27− B cells is increased in CIS and RRMS.

The phenotypical analysis of peripheral blood lymphocytes showed both similar counts of lymphocytes and distribution of CD4+, CD8+ and total T cells, NK cells, and total B cells between HCs and patients with RIS, CIS, and RRMS (figure e-3).

We observed a similar distribution of the different B-cell subsets (transitional, mature naive, marginal zone, switched memory B cells, IgM-only, IgD-only B cells, and plasmablasts) (figures e-1 and 1A). Double-negative IgD−/CD27− B cells were the only subset that was significantly increased in patients with CIS and RRMS when compared with HCs (p = 0.01).

Figure 1
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1 Phenotype and functional properties of B cells in MS and HCs at baseline

(A) Comparison of B-cell subset distribution in MS patient groups and HCs. Comparison of percentages of transitional, mature naive, marginal zone, switched memory, IgM-only, IgD-only B cells, exhausted B cells, and plasmablasts. (B) Comparison of functional properties of B cells in MS patient groups and HCs. Comparison of percentages of IL-6– and IL-10–producing B cells and IL-6/IL-10–producing B-cell ratio. CIS = clinically isolated syndrome; HC = healthy control; IL = interleukin; RIS = radiologically isolated syndrome; RRMS = relapsing remitting MS.

No difference in IL-10 and IL-6 production by B cells in patients with MS compared with controls.

Stimulating B cells with CD40 and CpG reliably induced IL-6 and IL-10 production. After 48 hours of polyclonal stimulation, no differences in IL-6 or IL-10–expressing B cells or in IL-6/IL-10–producing B-cell ratio were observed between the different groups of patients and HCs (figure 1B). Total B cells did not present any alteration in IL-10 and IL-6 production at any phase of MS disease (RIS, CIS, or RRMS stage) compared with HCs.

Comparison of B-cell subset distribution according to the MS evolution over time.

Among cytometric and functional B-cell characteristics obtained at baseline after 48-hour polyclonal stimulation, we searched for parameters with a predictive value of the disease evolution at the maximum follow-up of 11.2 months (±6.7). In the following 2 groups, RIS/CIS and RRMS, we distinguished patients who evolved and patients who did not, at 6 months (short term) and after 6 months (long term). Evolution was defined as (1) conversion from RIS to CIS, (2) conversion from CIS to MS according to 2010 MacDonald criteria, and (3) another relapse for RRMS (table).

We did not find any association between the different lymphocytes including B cells populations, at baseline, and the evolution at short term and long term in patients with RIS/CIS and in patients with RRMS at short term (figures e-4 and e-5). No statistical analysis was performed for patients with RRMS for the long-term evolution (n = 2).

An increased IL-6/IL-10–producing B-cell ratio is associated with the evolution of MS.

To assess the predictive value for MS outcome of IL-6 and IL-10 production by B cells at baseline, we compared IL-6/IL-10–producing B-cell ratio at baseline between evolving and not-evolving patients with MS. We observed that the IL-6/IL-10–producing B-cell ratio was significantly increased in patients with RIS/CIS who evolved at 6 months (p = 0.021, figure 2A). Next, we compared the IL-6– and IL-10–producing B cells separately and did not observe any variation in IL-6–producing B cells according to the outcome of patients with RIS/CIS. Conversely, we observed a significant decrease of IL-10–producing B cells (p = 0.0016) at baseline in patients with RIS/CIS who evolved at 6 months (figure 2, B and C). We did not observe any association between the IL-6/IL-10 ratio and the evolution of the RIS/CIS group in the long term and of the patients with RRMS in the short term (figure e-6, A–F).

Figure 2
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2 Functional properties of B cells according to disease evolution in patients with RIS/CIS

(A–C) Comparison of IL-6/IL-10–producing B-cell ratios (A), percentages of IL-6–producing B cells (B), and percentages of IL-10–producing B cells (C) between patients who had evolved and patients who had not at 6 months. (D and E) Correlation between IL-6/IL-10–producing B-cell ratio and percentages of IL-10 (D) or IL-6–producing B cells (E) in evolving patients with RIS/CIS MS at 6 months. CIS = clinically isolated syndrome; IL = interleukin; RIS = radiologically isolated syndrome.

IL-6/IL-10 ratio was significantly correlated with IL-10 but not with IL-6 B-cell production (figure 2, D and E). The IL-6/IL-10–producing B-cell ratio was also inversely correlated with the delay of evolution of the disease (rspearman = −0.42; p = 2.10−2). Even not significant, the IL-6/IL-10–producing B-cell ratio is higher in patients with early evolution of disease (figure 3A). In addition, the percentage of IL-10–producing B cells was also correlated with the delay of evolution of the disease (rspearman = 0.54; p = 2.10−3). Even not significant, the percentage of IL-10–producing B-cell ratio is lower in patients with early evolution of disease (figure 3B).

Figure 3
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 3 Analysis of the prognostic value of IL-10–producing B cells or IL-6/IL-10–B-cell ratio measurements in patients with RIS/CIS MS

(A) Comparison of baseline IL-6/IL-10–producing B-cell ratios between patients with RIS/CIS in whom disease has evolved at 3, 6, 12, and 24 months. (B) Comparison of baseline percentages of IL-10–producing B cells between patients with RIS/CIS in whom disease has evolved at 3, 6, 12, and 24 months. (C) ROC curve representation of IL-10–producing B-cell percentage and IL-6/IL-10–producing B-cell ratio according to the capacity to predict the evolution of the disease. (D) Representative graph of the posttest probability values according to pretest probability values, positive and negative likelihood ratios of IL-6/IL-10–producing B-cell ratio. CIS = clinically isolated syndrome; IL = interleukin; LR+ = positive likelihood ratio; LR− = negative likelihood ratio; RIS = radiologically isolated syndrome; ROC = receiver operating characteristic.

We then performed receiver operating characteristic (ROC) curve analysis to find a cutoff value for the IL-6/IL-10 ratio defining a higher risk of evolution. Areas under the curve were at 0.7 for the IL-6/IL-10–producing B-cell ratio and for the percentage of IL-10–producing B cells (figure 3C). Seven of 8 patients with RIS/CIS (87.5%) having a value above a ratio cutoff of 6.3 defined by an ROC curve analysis evolved at 6 months, with a good specificity of 97%. With a ratio below 6.3, 19 of 50 patients with RIS/CIS (38%) evolved giving a sensitivity of 31%. The ROC curve analyses performed for the percentage of IL-10–producing B cells show the same performances with a cutoff at 4.5% (figure 3D). For the IL-10–producing B-cell test, the graph representing its performance is similar (data not shown).

Even if no specific lymphocyte distributions at baseline seem to predict any disease evolution, an alteration of IL-10–expressing B cells and the IL-6/IL-10–producing B-cell ratio, at the very early phase of the disease, is significantly associated with an evolution in the short term.

Potential B-cell subsets and mechanisms involved in the alteration of IL-10 production in early-phase MS.

Using short 5-hour stimulation instead of long 48-hour stimulation in patients in the RIS/CIS group, we did not observe any further difference in IL-10–producing B cells in evolving patients compared with nonevolving patients (figure e-7). We hypothesized that according to different stimulation methods, different B-cell subsets were involved in IL-10 production. We tested both stimulation methods in the different B-cell subsets from HCs. We observed that IL-10 was mainly produced by memory B cells with the short 5-hour stimulation, whereas IL-10 was mainly produced by marginal zone and transitional B cells with the long 48-hour one (figure e-8).

To decipher the mechanisms of IL-10 production by B cells after long stimulation, we explored the type I interferon pathway. Using peripheral blood mononuclear cells (PBMC) from HCs, we analyzed IL-10 production by B cells after long stimulation with or without interferon-blocking antibodies (figure e-9). Blocking Ab had no effect on the IL-10 production by B cells.

DISCUSSION

The main results of this study are as follows: (1) an increase of the IL-6/lL-10 ratio in patients with RIS/CIS at baseline is significantly associated with an activity of the disease at 6 months; (2) this proinflammatory imbalance is linked to a decrease of the IL-10–producing B cells, without alteration of the IL-6–producing B cells; (3) this alteration of IL-10 production in patients with RIS/CIS who evolved concerns mainly transitional B cells and is independent of type I interferon secretion; (4) this feature was not observed when considering baseline samples from patients with RRMS, suggesting that impaired regulatory functions of B cells affect the early phase of MS disease.

Understanding the impact of the B-cell role in MS pathophysiology involves the analysis of peripheral blood B-cell subset distribution in patients, trying to associate any phenotypic characteristics with functional properties. Conflicting results are found in the literature. Immature B-cell phenotype (such as transitional B cells) has been associated with an anti-inflammatory profile,11 whereas memory B-cell phenotype has been associated with a more proinflammatory profile.7

Studies usually focused on the distribution of the following subsets: transitional, mature naive, and memory B cells. Although Haas et al.12 described an increase of transitional B cells in CIS and RRMS patients with active disease, Lee-Chang et al.13 found a decrease of those same cells in the same patient groups. Memory B-cell decrease have also been described in RRMS,12,14 whereas Michel et al.8 did not find any modification in the distribution of B-cell subsets in MS compared with HCs. In our study, we did not find any alteration in the distribution of those B-cell subsets at any phase of the disease. The only exception was that the double-negative (IgD−/CD27−) B-cell subset is overrepresented in CIS and RRMS groups compared with HCs. Such double-negative B cells have been reported as increased in other autoimmune conditions (systemic lupus and Sjögren syndrome)15,16 but have not been explored in MS except by Haas et al.12 who also described their overrepresentation in CIS and RRMS. These cells are described as exhausted B cells in a chronic activation status, but their functional properties remain elusive.17,18 We observed that the distribution of some B-cell subsets like transitional B cells was more heterogeneous in patients with MS.12,13 This could mean that, despite an apparent homogeneity through the clinical clustering of patients in defined groups (RIS, CIS, and RRMS), every individual patient presents a peculiar heterogeneous disease history. Indeed Carr et al.19 recently reported how peripheral blood immune cell distribution could be heterogeneous and how that distribution was shaped by environmental conditions. Besides the lack of association between B-cell subsets and the stage of MS at baseline in our study, we did not find any association with MS evolution either. These data suggest that the phenotypic analysis of peripheral blood B cells could be insufficiently informative. We therefore assessed a more functional analysis of B cells through their cytokine production capacities.

We hypothesized that initial phases of the disease could reflect a more homogenous pathologic process before any additional modifications brought by treatments and cumulative damage occurrence. In addition to patients with RRMS, we did select early MS disease (RIS and CIS) patients who are naive of any immunomodulating or immunosuppressive drugs. We did not see any difference in IL-6 and IL-10 production by B cells between HCs and RIS, CIS, or RRMS nor between the different subgroups of patients. Such discrepant results with literature might be linked to the different methodological approaches: cells studied and stimulation methods used. We chose to use stimulated fresh PBMCs to analyze specific cytokine production by B cells using a cytometric approach. Iwata et al.20 demonstrated that this technique using PBMC is as convenient as purified B cells for the specific cytokine production analysis. Moreover, the stimulation pathway we used in our study has been demonstrated as optimal for the analysis of cytokine production by B cells.21

In the longitudinal phase of our study, we concluded that, in the very early phases of MS (for RIS and CIS), the higher the IL-6/IL-10 B-cell ratio, the poorer the prognosis at 6 months.

The increase of this ratio was mainly explained by a decrease of IL-10 production. Indeed, although IL-6 production did not significantly vary, the decrease of the capacity of B cells to produce IL-10 could confer a higher proinflammatory property on those B cells. Moreover, in the group of patients who evolved at 6 months, we observed an inverse correlation between time to progression and IL-6/IL-10 ratio. A lower ratio was associated with a longer time to evolution.

Using an ROC curve approach, we delineated a cutoff to define a test with a high specificity. More than 87% of patients with RIS/CIS who presented less than 4.5% of B-cell–producing IL-10 have evolved at 6 months, corresponding to a specificity of 97%, but a low sensitivity of 31%. This approach points out that, under this percentage of IL-10–producing B cells, the patients with RIS/CIS are at substantial risk of developing an active disease.

Those results were obtained with a long stimulation while they were not observed after short stimulation of B cells. We could hypothesize that the decrease in the level of IL-10 B-cell production may be restricted to transitional B cells. Moreover, previous studies have shown that IL-10 production by transitional B cells after long TLR9 stimulation could depend on type I interferon produced by PBMC.19 However, we did show that IL-10 B-cell production was independent of type I interferon synthesis in our population.

In the RRMS group, we did not observe that IL-6/IL-10 ratios and IL-10 B cells were associated with any further disease activity during the follow-up. These data suggest that at the RRMS stage, peripheral blood no longer reflected the initial pathologic processes but, perhaps, a more heterogeneous process linked to accumulation, in a single patient, of lesions at various stages.

In conclusion, we suggested that B cells had a reduced capacity for producing the immunoregulatory cytokine IL-10 that may confer a proinflammatory profile to those cells. This phenomenon is objectively shown only at the early initial phases of the disease and could help at that step to identify patients who will need active treatment. A replication cohort would be helpful to substantiate that this test IL-6/IL-10 ratio in B cells is predictive of early disease activity in patients with RIS/CIS.

AUTHOR CONTRIBUTIONS

Thomas Guerrier: study concept and design and acquisition, analysis, and interpretation of data. Myriam Labalette: study concept and critical revision of the manuscript for intellectual content. Caty Lee Chang: critical revision of the manuscript for intellectual content. Olivier Outteryck: acquisition of data and critical revision of the manuscript for intellectual content. Guillaume Lefèvre and David Launay: critical revision of the manuscript for intellectual content. Patrick Vermersch: acquisition of data and critical revision of the manuscript for intellectual content. Dubucquoi Sylvain: study concept and design, study supervision, analysis and interpretation of data, and critical revision of the manuscript for intellectual content. Hélène Zéphir: study concept and design, study supervision, acquisition of data, analysis and interpretation of data, and critical revision of the manuscript for intellectual content.

STUDY FUNDING

This study was funded by Université de Lille 2 and the Fondation pour l'aide à la recherche sur la sclérose en plaques (ARSEP).

DISCLOSURE

T. Guerrier received research fellowships from Fondation pour la Recherche, Université Lille 2, and ARSEP; received research grants from Université Lille 2 and ARSEP; and received research support from GENZYME. M. Labalette reports no disclosures. D. Launany received travel funding and/or speaker honoraria from Shire, GSK, CSL Behring, and Pfizer and is an associate editor of La Revue de Medecine Interne. C. Lee-Chang received lecture fees from Merck and research grants from Novartis Pharma AG. O. Outteryck received consulting fees and invitations for national and international congresses from Biogen, Merck, Teva, Sanofi Genzyme, Novartis, Bayer, Sanofi-Aventis, and Roche; received research support from Biogen, Bayer, and Novartis; and received academic research grants from the VISIO Foundation. G. Lefèvre received consulting fees and invitations for national and international congresses from LFB, Octapharma, and Shire, as well as received research supports from LFB, CSL Behring, Air Liquide, Octapharma, GRIFOLS, and GSK. P. Vermersch received honoraria and consulting fees from Biogen Idec, Sanofi Genzyme, Bayer, Novartis, Teva, Merck, Roche, Almirall, and Celgene; received research support from Biogen, Bayer, Novartis, Sanofi Genzyme, Roche, and Novartis-Merck; and served on the scientific advisory board of Sanofi, Biogen, Merck, Teva, Novartis, Roche, Serrvier, and Celgene. S. Dubucquoi: received consulting fees and invitations for national and international congresses from Biogen and Teva; received research support from Genzyme, Octapharma, Roche, CSL Behring, and Novartis; and received academic research grants from Lille University and the ARSEP Foundation. H. Zéphir received fees for consulting or lectures and invitations for national and international congresses from Biogen, Merck, Teva, Sanofi Genzyme, Novartis, and Bayer; received research support from Teva and Roche; and received academic research grants from Académie de Médecine, LFSEP, and ARSEP Foundation. Go to Neurology.org/nn for full disclosure forms.

ACKNOWLEDGMENT

The authors acknowledge the University of Lille 2 and the Fondation pour l'aide à la recherche sur la sclérose en plaques (ARSEP), which funded the study and Carine Hauspie for technical support.

Footnotes

  • ↵* These authors contributed equally to the manuscript.

  • Funding information and disclosures are provided at the end of the article. Go to Neurology.org/nn for full disclosure forms. The Article Processing Charge was funded by the authors.

  • Received August 21, 2017.
  • Accepted in final form October 30, 2017.
  • Copyright © 2017 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. 1.↵
    1. Cross AH,
    2. Stark JL,
    3. Lauber J, et al
    . Rituximab reduces B cells and T cells in cerebrospinal fluid of multiple sclerosis patients. J Neuroimmunol 2006;180:63–70.
    OpenUrlCrossRefPubMed
  2. 2.↵
    1. Kappos L,
    2. Li D,
    3. Calabresi PA, et al
    . Ocrelizumab in relapsing-remitting multiple sclerosis: a phase 2, randomised, placebo-controlled, multicentre trial. Lancet 2011;378:1779–1787.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Barr TA,
    2. Shen P,
    3. Brown S, et al
    . B cell depletion therapy ameliorates autoimmune disease through ablation of IL-6–producing B cells. J Exp Med 2012;209:1001–1010.
    OpenUrlAbstract/FREE Full Text
  4. 4.↵
    1. Fillatreau S,
    2. Sweenie CH,
    3. McGeachy MJ,
    4. Gray D,
    5. Anderton SM
    . B cells regulate autoimmunity by provision of IL-10. Nat Immunol 2002;3:944–950.
    OpenUrlCrossRefPubMed
  5. 5.↵
    1. Bar-Or A,
    2. Fawaz L,
    3. Fan B, et al
    . Abnormal B-cell cytokine responses a trigger of T-cell-mediated disease in MS? Ann Neurol 2010;67:452–461.
    OpenUrlCrossRefPubMed
  6. 6.↵
    1. Li R,
    2. Rezk A,
    3. Miyazaki Y, et al
    . Proinflammatory GM-CSF–producing B cells in multiple sclerosis and B cell depletion therapy. Sci Transl Med 2015;7:310ra166.
    OpenUrlAbstract/FREE Full Text
  7. 7.↵
    1. Duddy M,
    2. Niino M,
    3. Adatia F, et al
    . Distinct effector cytokine profiles of memory and naive human B cell subsets and implication in multiple sclerosis. J Immunol 2007;178:6092–6099.
    OpenUrlAbstract/FREE Full Text
  8. 8.↵
    1. Michel L,
    2. Chesneau M,
    3. Manceau P, et al
    . Unaltered regulatory B-cell frequency and function in patients with multiple sclerosis. Clin Immunol 2014;155:198–208.
    OpenUrl
  9. 9.↵
    1. Polman CH,
    2. Reingold SC,
    3. Banwell B, et al
    . Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 2011;69:292–302.
    OpenUrlCrossRefPubMed
  10. 10.↵
    1. Okuda DT,
    2. Siva A,
    3. Kantarci O, et al
    ; Radiologically Isolated Syndrome Consortium (RISC); Club Francophone de la Sclérose en Plaques (CFSEP). Radiologically isolated syndrome: 5-year risk for an initial clinical event. PLoS One 2014;9:e90509.
    OpenUrlCrossRefPubMed
  11. 11.↵
    1. Blair PA,
    2. Noreña LY,
    3. Flores-Borja F, et al
    . CD19(+)CD24(hi)CD38(hi) B cells exhibit regulatory capacity in healthy individuals but are functionally impaired in systemic Lupus Erythematosus patients. Immunity 2010;32:129–140.
    OpenUrlCrossRefPubMed
  12. 12.↵
    1. Haas J,
    2. Bekeredjian-Ding I,
    3. Milkova M, et al
    . B cells undergo unique compartmentalized redistribution in multiple sclerosis. J Autoimmun 2011;37:289–299.
    OpenUrlCrossRefPubMed
  13. 13.↵
    1. Lee-Chang C,
    2. Top I,
    3. Zéphir H, et al
    . Primed status of transitional B cells associated with their presence in the cerebrospinal fluid in early phases of multiple sclerosis. Clin Immunol 2011;139:12–20.
    OpenUrlPubMed
  14. 14.↵
    1. Niino M,
    2. Hirotani M,
    3. Miyazaki Y,
    4. Sasaki H
    . Memory and naive B-cell subsets in patients with multiple sclerosis. Neurosci Lett 2009;464:74–78.
    OpenUrlCrossRefPubMed
  15. 15.↵
    1. Wei C,
    2. Anolik J,
    3. Cappione A, et al
    . A new population of cells lacking expression of CD27 represents a notable component of the B cell memory compartment in systemic lupus erythematosus. J Immunol 2007;178:6624–6633.
    OpenUrlAbstract/FREE Full Text
  16. 16.↵
    1. Saadoun D,
    2. Terrier B,
    3. Bannock J, et al
    . Expansion of autoreactive unresponsive CD21(-/low) B cells in Sjögren's syndrome associated lymphoproliferation. Arthritis Rheum 2013;65:1085–1096.
    OpenUrlPubMed
  17. 17.↵
    1. Seifert M,
    2. Küppers R
    . Human memory B cells. Leukemia 2016;30:2283–2292.
    OpenUrl
  18. 18.↵
    1. Wu YCB,
    2. Kipling D,
    3. Dunn-Walters DK
    . The relationship between CD27 negative and positive B cell populations in human peripheral blood. Front Immunol 2011;2:81.
    OpenUrlCrossRefPubMed
  19. 19.↵
    1. Carr EJ,
    2. Dooley J,
    3. Garcia-Perez JE, et al
    . The cellular composition of the human immune system is shaped by age and cohabitation. Nat Immunol 2016;17:461–468.
    OpenUrlCrossRefPubMed
  20. 20.↵
    1. Iwata Y,
    2. Matsushita T,
    3. Horikawa M, et al
    . Characterization of a rare IL-10-competent B-cell subset in humans that parallels mouse regulatory B10 cells. Blood 2011;117:530–541.
    OpenUrlAbstract/FREE Full Text
  21. 21.↵
    1. Menon M,
    2. Blair PA,
    3. Isenberg DA,
    4. Mauri C
    . A regulatory feedback between plasmacytoid dendritic cells and regulatory B cells is aberrant in systemic lupus erythematosus. Immunity 2016;44:683–697.
    OpenUrlCrossRefPubMed

Letters: Rapid online correspondence

No comments have been published for this article.
Comment

REQUIREMENTS

If you are uploading a letter concerning an article:
You must have updated your disclosures within six months: http://submit.neurology.org

Your co-authors must send a completed Publishing Agreement Form to Neurology Staff (not necessary for the lead/corresponding author as the form below will suffice) before you upload your comment.

If you are responding to a comment that was written about an article you originally authored:
You (and co-authors) do not need to fill out forms or check disclosures as author forms are still valid
and apply to letter.

Submission specifications:

  • Submissions must be < 200 words with < 5 references. Reference 1 must be the article on which you are commenting.
  • Submissions should not have more than 5 authors. (Exception: original author replies can include all original authors of the article)
  • Submit only on articles published within 6 months of issue date.
  • Do not be redundant. Read any comments already posted on the article prior to submission.
  • Submitted comments are subject to editing and editor review prior to posting.

More guidelines and information on Disputes & Debates

Compose Comment

More information about text formats

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Author Information
NOTE: The first author must also be the corresponding author of the comment.
First or given name, e.g. 'Peter'.
Your last, or family, name, e.g. 'MacMoody'.
Your email address, e.g. higgs-boson@gmail.com
Your role and/or occupation, e.g. 'Orthopedic Surgeon'.
Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.
Publishing Agreement
NOTE: All authors, besides the first/corresponding author, must complete a separate Publishing Agreement Form and provide via email to the editorial office before comments can be posted.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

Vertical Tabs

You May Also be Interested in

Back to top
  • Article
    • Abstract
    • GLOSSARY
    • METHODS
    • RESULTS
    • DISCUSSION
    • AUTHOR CONTRIBUTIONS
    • STUDY FUNDING
    • DISCLOSURE
    • ACKNOWLEDGMENT
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Info & Disclosures
Advertisement

SARS-CoV-2 Vaccination Safety in Guillain-Barré Syndrome, Chronic Inflammatory Demyelinating Polyneuropathy, and Multifocal Motor Neuropathy

Dr. Jeffrey Allen and Dr. Nicholas Purcell

► Watch

Topics Discussed

  • All Immunology
  • Multiple sclerosis

Alert Me

  • Alert me when eletters are published

Recommended articles

  • What's Happening
    What's happening in Neurology® Neuroimmunology & Neuroinflammation
    et al.
    Neurology, July 02, 2018
  • Article
    B-Cell Compartmental Features and Molecular Basis for Therapy in Autoimmune Disease
    Chao Zhang, Tian-Xiang Zhang, Ye Liu et al.
    Neurology: Neuroimmunology & Neuroinflammation, August 31, 2021
  • Article
    Effect of Ocrelizumab in Blood Leukocytes of Patients With Primary Progressive MS
    José I. Fernández-Velasco, Jens Kuhle, Enric Monreal et al.
    Neurology: Neuroimmunology & Neuroinflammation, January 06, 2021
  • Article
    Dimethyl fumarate treatment of relapsing-remitting multiple sclerosis influences B-cell subsets
    Steven K. Lundy, Qi Wu, Qin Wang et al.
    Neurology - Neuroimmunology Neuroinflammation, March 03, 2016
Neurology - Neuroimmunology Neuroinflammation: 10 (3)

Articles

  • Articles
  • Issues
  • Popular Articles

About

  • About the Journals
  • Ethics Policies
  • Editors & Editorial Board
  • Contact Us
  • Advertise

Submit

  • Author Center
  • Submit a Manuscript
  • Information for Reviewers
  • AAN Guidelines
  • Permissions

Subscribers

  • Subscribe
  • Sign up for eAlerts
  • RSS Feed
Site Logo
  • Visit neurology Template on Facebook
  • Follow neurology Template on Twitter
  • Visit Neurology on YouTube
  • Neurology
  • Neurology: Clinical Practice
  • Neurology: Education
  • Neurology: Genetics
  • Neurology: Neuroimmunology & Neuroinflammation
  • AAN.com
  • AANnews
  • Continuum
  • Brain & Life
  • Neurology Today

Wolters Kluwer Logo

Neurology: Neuroimmunology & Neuroinflammation
Online ISSN: 2332-7812

© 2023 American Academy of Neurology

  • Privacy Policy
  • Feedback
  • Advertise