Несбалансированность циркулирующих подсетей B-Cell была связана с повышенным риском возврата пациентов RRMS.

1. Introduction

In most patients diagnosed with multiple sclerosis (MS), the disease evolves via recurrent acute episodes of neurological impairment followed by total or partial clinical remission [ 1 ]. In this form, called relapsing–remitting MS (RRMS), relapses have been attributed to autoimmune attacks mainly coordinated by myelin‐specific Th17 cells [ 2 – 6 ]. Unfortunately, treatment of RRMS patients with disease‐modifying therapy (DMT), known to inhibit and/or block the access of T cells to the central nervous system (CNS), has little effect on the risk of disease progression to the secondary progressive form (SPMS). SPMS is characterized by progressive neurodegeneration with cortical atrophy even in the absence of clinical relapses [ 7 ]. Evidence suggests that this progression is associated with intense meningeal inflammation associated with the presence of local memory B‐cell clusters, forming an organized structure similar to lymphoid follicles (LFs) [ 8 ], probably involving recruitment of circulating CXCR5 + B cells induced by chemokine CXCL13 [ 9 , 10 ].

LFs are highly organized structures found in secondary lymphoid organs (SLOs) containing an elevated number of different B‐cell subsets, some CD4 + T cells, named follicular helper T cells ( T FH ), and follicular dendritic cells (FDCs) [ 11 , 12 ]. Lymphocyte recruitment into SLOs is thought to be driven by chemokines such as CXCL13 [ 9 ]. In this setting, following antigen exposure, interactions between T FH cells and different B‐cell subsets, along with FDCs, support the germinal center (GC) reaction that is pivotal for the expansion of high‐affinity B‐cell clones and their subsequent differentiation into plasmablasts, plasma cells, and memory B cells [ 11 , 12 ]. Although the GC reaction is vital for adequate response to different pathogens, it is also associated with pathological conditions. In autoimmunity, these ectopic LFs (eLFs) serve as a reservoir for autoreactive B‐ and T‐cell reactivation at chronic inflammation sites and are therefore a common feature of several B‐cell‐mediated autoimmune diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and Sjögren’s syndrome [ 11 ].

In many SPMS patients, structures similar to eFLs identified below the meninges have been associated with the number and size of cortical brain lesions [ 12 , 13 ]. Furthermore, the presence of eFLs also correlates with the expansion of circulating memory B cells and light‐chain neurofilament (NfL) levels in the cerebrospinal fluid (CSF) and plasma [ 14 – 16 ]. NfL is a neuron‐specific cytoskeletal protein that is released into the extracellular fluid following axonal injury [ 15 ]. Additionally, detection of high CXCL13 levels in the CSF of people with MS (pwMS) [ 16 ] reinforces the hypothesis of B‐cell involvement in tissue injury, neurodegeneration, and irreversible neurological impairment. Therefore, it is possible that a significant increase in different B‐cell subtypes in RRMS patients represents an early biomarker of secondary disease progression [ 17 ].

The role of B cells in MS outcomes may be related not only to antibody production but also to their ability to produce pro‐inflammatory cytokines and activate myelin‐specific CD4 + T cells. Indeed, high frequency of memory B cells expressing elevated surface levels of both HLA‐DR and the costimulatory molecules CD80 and CD86 [ 13 , 18 , 19 ], as well as IL‐6, GM‐CSF, TNF‐α, IFN‐γ and IL‐21 production have been observed in RRMS patients when compared with healthy individuals [ 20 – 25 ]. By contrast, circulating B cells capable of producing elevated IL‐10 levels are higher among pwMS with less disease activity than in patients with more aggressive forms of disease [ 26 ]. These data suggest that B cells play a dual role in MS.

Therefore, investigating the composition of different B‐cell subsets in RRMS patients might not only help to identify those at variable risk of disease progression but also help to develop new therapies. As such, given the expression of different biomarkers, we investigated the relationship between the frequencies of circulating transitional, naïve and memory B cells, as well as plasmablasts, and disease activity, evaluated here by occurrence of clinical relapses and severity of neurological impairment. We also correlated B‐cell subsets with plasma levels of CXCL13 and NfL.

2. Methods

2.1. Patients

For our study, 45 patients in clinical remission, with a definite diagnosis of relapsing–remitting MS, according to the McDonald 2010 criteria [ 27 ], were recruited from January 2022 to January 2024 from Gaffrée e Guinle University Hospital/UNIRIO (Rio de Janeiro, Brazil). Demographic data such as gender and age at disease onset were obtained from medical records (Table 1 ). Patients in clinical remission were recruited from Gaffrée e Guinle Hospital (HUGG/UNIRIO) (Table 1 ). Patients with additional autoimmune diseases, neoplasms, pregnant women, smokers, or users of illicit substances were excluded. Patients treated with corticosteroids within an interval of less than 3 months before the day of blood sampling were excluded. Patients using medications that deplete B cells (rituximab and ocrelizumab) were also excluded. The neurological disability status of patients was evaluated by one of the authors (CCV) and was scored according to the Expanded Disability Status Scale (EDSS) [ 28 ]. Information about the occurrence of clinical relapses subsequent to blood sampling for immunology over the 1‐year follow‐up was obtained from medical records. A clinical relapse is defined as a new or worsening neurological symptom lasting at least 24 h, in the absence of fever or infection, and separated by at least 30 days from the prior relapse. As control, 20 healthy individuals, matched by age and gender, were recruited to participate in the study. With regard to ancestry, we classified as Afrodescendant those with African descent until the third generation. After a complete description of the study to the participants, written informed consent was obtained from each individual. The study was approved by the Ethics Committee for Research on Human Subjects of the Federal University of the State of Rio de Janeiro (UNIRIO) (CAAE number: 43009015.6.0000.5258).

2.2. Plasma and Cell Cultures

Peripheral blood was collected from participants in heparin‐containing tubes, and both plasma and mononuclear cells (PBMC) were obtained by centrifugation on the Ficoll–Hypaque density gradient. For some experiments, whole B cells were isolated from PBMC using EasySep Human Pan‐B‐Cell Enrichment Kit (StemCell Technologies). After counting cells in trypan blue solution (10% v/v), viable PBMCs (1 × 10 6 /mL) or B cells (1 × 10 4 /mL) were suspended in RPMI‐1640 medium supplemented with 2 μM of L‐glutamine (GIBCO, Carlsbad, CA, USA), 10% fetal calf serum (FCS), 20 U/mL of penicillin, 20 μg/mL of streptomycin, and 20 mM of HEPES buffer. In order to analyze stimulation‐induced IL‐17 and IL‐10 response, PBMC or B‐cell cultures were stimulated for 4 h with phorbol 12‐myristate 13‐acetate (PMA, 20 ng/mL; Sigma–Aldrich) plus ionomycin (600 ng/mL; Sigma–Aldrich). For cytometry analysis of cytokine‐producing B‐cell subsets, brefeldin A (10 μg/mL; Sigma–Aldrich) was also added to PBMC cultures. The cell cultures were maintained at 37°C in a humidified 5% CO 2 incubator for incubation.

2.3. Flow Cytometry Analysis

To determine the frequency of different B lymphocyte subtypes, PBMCs were labeled with monoclonal antibodies (mAbs) directed against different markers [anti‐CD19‐Super Bright 600 (clone SJ25C1); anti‐IgD‐PerCP‐eFluor 710 (clone IA62); anti‐CD38‐PE (clone HIT2); anti‐CD27‐Super Bright 436 (clone 0353); anti‐HLA‐DR‐APC‐eFluor780 (clone LN3); anti‐IL‐10‐AlexaFluor 488 (clone JES39DT), anti‐IL‐17A‐APC (eBio64DEC17), anti‐CD138‐PECy‐7 (clone MI15)]. These mAb combinations allowed us to determine the following B cells: total (CD19 + ), naïve (CD38 + CD27 − CD19 + ), transitional (CD27 − CD38 ++ CD19 + ), memory subsets (CD27 − CD38 − CD19 + , CD27 + CD38 + CD19 + , CD27 + CD38 − CD19 + ), and total and CD138 + plasmablast (CD38 ++ CD27 ++ CD19 + ). These cells were also analyzed for HLA‐DR and IgD expression, as well as synthesis of IL‐17 and IL‐10. All monoclonals were purchased from BioLegend (San Diego, CA, USA), eBioscience (Waltham, Massachusetts, USA), and BD Bioscience (San Diego, CA, USA). Briefly, the PBMCs were incubated with different mAb combinations for surface markers (anti‐CD19, anti‐CD27, anti‐CD38, anti‐IgD, anti‐HLA‐DR, and anti‐CD138) at room temperature in the dark, according to manufacturer’s instructions. After 30 min, the cells were washed with PBS + 2%FBS at room temperature before cell permeabilization, which was performed by incubating cells at 4°C for 20 min with Cytofx/Cytoperm solution (BD Pharmigen, San Diego, CA). After washing, mAbs against IL‐17 and IL‐10 were added and incubated for a further 30 min at 4°C. The cells were acquired on Attune NxT flow cytometers (Thermo Fisher Corporation) and analyzed using FlowJo. Isotype control antibodies and single‐stained samples were used to periodically check the settings and gates on the flow cytometer. After acquisition of 100,000–200,000 events, lymphocytes were gated based on forward and side scatter properties after the exclusion of dead cells using propidium iodide [PI + cells mean: 2.13% (range 0.78%–3.1%)] and doublets (Supporting Information 1 : Figure S1 ).

2.4. ELISA Assay

CXCL13 levels in plasma were quantified using the ELISA technique with Thermo Scientific Human CXCL13 (BCL) kits following manufacturer’s instructions (Thermo Fischer–Waltham, Massachusetts, USA). The quantification of plasma NfL levels was performed using the ELISA technique (Enzyme‐Linked Immunosorbent Assay) with Elabscience Human NEFL ELISA kits (NfL, Light Polypeptide) following manufacturer’s instructions. Recombinant human CXCL13 (1.37–1000 pg/mL) and NfL (3.13–200 pg/mL) were employed to construct standard curves. IL‐17 and IL‐10 levels were determined using ELISA with Human IL‐17 (KHC0101) and IL‐10 (KAC1591) ELISA Kits (Thermo Fischer‐ Invitrogen) following manufacturer’s instructions. Recombinant human IL‐17 and IL‐10, at concentrations ranging from 15 to 1000 pg/mL (IL‐17) and 7.8 to 500 pg/mL (IL‐10), were used to construct standard curves. In those assays, the reaction was revealed with streptavidin‐horseradish peroxidase using 3.3′, 5.5′‐tetramethyl‐benzidine (TMB) as a substrate. The plates were read at 450 nm and 550 nm in an ELISA reader.

2.5. Statistical Analysis

The statistical analysis was carried out using Prism 8.0 software (GraphPad Software). Comparisons between immune assays from the two patient subgroups were performed by using Kruskal–Wallis followed by Dunn’s test. Additionally, the results were corrected by Bonferroni. The nonparametric Mann–Whitney U test and Student’s t ‐test were applied to determine whether the two groups were statistically different for nonparametric and parametric variables, respectively. Multivariate Firth logistic regression models were applied to evaluate the relationship between B‐cell subsets and CXCL13 levels with a binary outcome variable (relapse/no relapse) taking into account multiple confounding variables simultaneously (age, EDSS, gender, therapy). ROC analysis of Firth logistic regression models was performed. To evaluate the robustness of the predictive linear models, leave‐one‐out cross‐validation (LOOCV) was performed. In each iteration, one participant was excluded from the dataset, and the Firth logistic regression model was refitted using the remaining participants. The fitted model was used to estimate the predicted probability for the excluded participant. This process was repeated until every participant had served as the test observation once. The validated predicted probabilities were then combined to construct ROC curves. The optimal cutoff value was determined using Youden’s index, and the corresponding sensitivity, specificity, and accuracy were calculated. Correlations between nonparametric variables were investigated using Spearman’s correlations. Aiming to evaluate the strength and direction of association between two ranked or ordinal variables, Spearman’s rank correlation coefficient with 95% confidence intervals was estimated using the percentile bootstrap method with 2000 resamples. Significance for all experiments was p < 0.05.

3. Results

3.1. Circulating B‐Cell Subsets are Correlated With Severity of Neurological Impairment in MS

For the present study, different B‐cell subsets in the peripheral blood from healthy individuals (control, n = 20) and pwMS in remission phase ( n = 45) were collected (Table 1 ). According to data regarding the occurrence of relapses over the 1‐year follow‐up period, pwMS were grouped in Table 1 as either clinically stable (stable, n = 30) or relapsed (unstable, n = 15). For ethnicity, the majority is Afrodescendant, mainly among unstable group (73%). Neurological impairment, determined by EDSS scale, was evaluated just before (t0) and 1 year after (t1) blood sampling. For DMT, stable pwMS were undergoing treatment with fingolimod (FGL, n = 7), dimethyl fumarate (DMF, n = 6), natalizumab (NATz, n = 7), interferon (IFN, n = 5), and glatiramer acetate (AG, n = 5). During the 1‐year follow‐up period, 15 pwMS undergoing DMT [FGL ( n = 3), DMF ( n = 4), NATz ( n = 3), IFN ( n = 3), and AG ( n = 2)] showed one or more clinical relapses (Table 1 ). With regard to plasma CXCL13, higher levels of this chemokine were observed in pwMS samples, mainly among unstable patients (Table 1 ). Furthermore, the plasma NfL concentration was also significantly higher in relapsed group as compared with the control one. Regarding treatment, no significant difference was observed between DMT regimes and B‐cell subsets in either patient subgroup (Supporting Information 2 : Figure S2 ). Moreover, since our experiment was performed with MS patients with an unbalanced DMT regimen, analysis by using a multivariate logistic regression demonstrated that B‐cell subsets by treatment are not different. These variables presented wide confidence intervals and high standard errors, likely reflecting the limited sample size and sparse observations within treatment subgroups.

Taking into account the different B‐cell subsets shown in Supporting Information 1 : Figure S1 , pwMS ( n = 45) presented higher frequency of total and CD138 + and HLA‐DR + IgD − plasmablasts, HLA‐DR + IgD + and HLA‐DR + IgD − transitional cells, and different memory B‐cell subsets (HLA‐DR + IgD + CD27 + CD38 + , HLA‐DR + IgD − CD27 + CD38 + and HLA‐DR + IgD + CD27 + CD38 − ) when compared with healthy individuals (Table 2 ). Also, elevated percentages of HLA‐DR − IgD + memory B cells were observed in the MS group. By contrast, the frequency of HLA‐DR − IgD + cells among transitional and plasmablasts was lower in patients than in the control (Table 2 ).

Cytokines such as IL‐17 and IL‐10 have been classically associated with the promotion and suppression of inflammation in MS [ 29 ]. Taking into account the strategy of IL‐17 + and/or IL‐10 + B‐cell identification in Supporting Information 1 : Figure S1 , Table 2 shows that a higher proportion of IL‐17 + IL‐10 − in total, naïve, plasmablast, and all memory B‐cell subsets was observed in the control group than in MS samples. Moreover, an elevated percentage of IL‐17 + IL‐10 + plasmablasts and naïve cells was also seen in the healthy group (Table 2 ).

Regarding the severity of neurological impairment and RRMS‐derived B cells, different plasmablast subsets (CD138 + , HLA‐DR + IgD − , and IL‐17 + IL‐10 − ) correlated with EDSS score. HLA‐DR + IgD − and IL‐17 + IL‐10 − memory CD27 + CD38 + B cells also positively correlated with severity of neurological impairment (Table 3 ). By contrast, the proportion of HLA‐DR − IgD + and IL‐17 − IL‐10 + among transitional and IL‐17 − IL‐10 + plasmablasts was observed in patients with lower neurological impairment (Table 3 ).

3.2. B‐Cell Subset Imbalance Was Associated With Clinical Activity of MS

Given that RRMS is characterized by unpredictable relapses followed by remission periods, our next objective was to determine if the frequency of different RRMS‐derived B‐cell subsets during remission could be associated with the occurrence of clinical relapses during the 1‐year follow‐up even when undergoing DMT.

Assuming the gating strategy shown in Figure 1 A, the frequency of transitional cells was higher in stable patients throughout the 1‐year follow‐up period by comparison with the relapsed (unstable) groups (Figure 1 C). On the other hand, the percentage of plasmablasts was higher among unstable pwMS (Figure 1 E), with no difference for the other B‐cell subsets.

Regarding HLA‐DR and IgD expression, and assuming the gating strategy shown in Figure 2 A, the percentage of HLA‐DR + IgD + and HLA‐DR + IgD − transitional (Figure 2 C) and HLA‐DR + IgD + memory B‐cell subsets [CD27 + CD38 + (Figure 2 G) and CD27 + CD38 − (Figure 2 H)] was significantly higher in both MS subgroups by comparison with the control, with no difference observed between stable and unstable patients. The occurrence of relapses was mainly observed in pwMS who showed higher frequency of total (Figure 2 B), plasmablast (Figure 2 E), and all memory B‐cell subsets (Figure 2 F–H) with HLA‐DR + IgD − phenotype at baseline. Furthermore, increased percentages of CD138 + plasmablasts at t0 were associated with clinical relapse during follow‐up (Figure 2 E). By contrast, the presence of HLA‐DR − IgD + among naïve (Figure 2 D) and all memory B cells (Figure 2 F–H) was higher in stable pwMS than in either control or relapsed patients. Moreover, total (Figure 2 B), transitional (Figure 2 C), and plasmablasts negative for HLA‐DR but positive for IgD were higher in stable patients by comparison with unstable ones.

Regarding mean fluorescence intensity (MFI), as shown in Figure 3 A, lower intensity of HLA‐DR per total (Figure 3 B), transitional (Figure 3 C), plasmablast (Figure 3 E), and all memory B‐cell subsets (Figure 3 F–H) was observed in samples from clinically stable patients, by comparison with control and unstable groups. Interestingly, total (Figure 3 B), transitional (Figure 3 C), naïve (Figure 3 D), and plasmablast (Figure 3 E) cells expressing high IgD levels were mainly observed in patients without relapse during the 1‐year follow‐up.

Regarding cytokines, and assuming the gating strategy shown in Figure 4 A, the frequency of IL‐17 + IL‐10 − phenotype among total (Figure 4 B), naïve (Figure 4 D), and memory B‐cell subsets [CD27 − CD38 − (Figure 4 F) and CD27 + CD38 − (Figure 4 H) was significantly higher in the control group than pwMS. Also, a lower percentage of memory IL‐17 + IL‐10 − CD27 + CD38 + B cells was observed in stable patients as compared with the control group (Figure 4 G). At baseline, a higher proportion of IL‐17 + IL‐10 − phenotype in the transitional (Figure 4 C), naïve (Figure 4 D), plasmablast (Figure 4 E), and memory B‐cell subsets [CD27 − CD38 − (Figure 4 F) and CD27 + CD38 + (Figure 4 G)] was associated with occurrence of relapses over time. By contrast, a higher percentage of total (Figure 4 B), transitional (Figure 4 C) and plasmablasts (Figure 4 E) with IL‐17 − IL‐10 + phenotype was seen in stable patients than in relapsed ones. The proportion of IL‐17 + IL‐10 + plasmablasts (Figure 4 E) and IL‐17 + IL‐10 + memory B‐cell subsets [CD27 − CD38 − (Figure 4 F) and CD27 + CD38 + (Figure 4 G)] was elevated in the control group. In B‐cell cultures, the levels of IL‐17 released in the control samples were significantly higher than for stable and relapsed MS patients, with no difference for IL‐10 release (Supporting Information 3 : Figure S3 ). On the other hand, among pwMS, while IL‐17 release was greater, the release of IL‐10 was lower in unstable B‐cell cultures (Supporting Information 3 : Figure S3 ). Like IL‐10 + and IL‐17 + ‐secreting B cells, the levels of those cytokines released by total B cells were not correlated with disease activity (data not shown).

Comparison between different cytokine‐producing B‐cell subsets and clinical activity of MS. PBMC cultures (1 × 10 6 /mL) from healthy control (Control, n = 20) and stable ( n = 30) and unstable ( n = 15) RRMS were stimulated with PMA and ionomycin for 4 h, and the frequency of (B) total, (C) transitional, (D) naïve, (E) plasmablasts, and different memory B‐cell subsets [(F) (CD27 − CD38 − ), (G) (CD27 + CD38 + ), and (H) (CD27 + CD38 − )] capable of producing IL‐17 and/or IL‐10 was determined adopting the gating strategy shown in (A). Data are shown as mean ± SD of nine independent experiments with three to six samples per experiment. Significance was calculated by comparing control and MS patient subgroups using Kruskal–Wallis followed by Dunn’s test. Multivariate Firth logistic regression models and ROC analysis of Firth logistic regression models were also applied. The p ‐values are indicated in the figure.

Applying Multivariate logistic regression adjusted for the same control variables (age, EDSS, and gender) (Supporting Information 4 : Table S1 ), the plasma levels of CXCL13, the percentage of CD138 + plasmablasts, and the frequency of HLA‐DR + IgD − cells among naïve, plasmablasts, transitional, and memory B cells (CD27 − CD38 − and CD27 + CD38 − ) remained significantly higher among unstable patients. Moreover, the intensity of HLA‐DR expression per plasmablast and memory B‐cell subsets and MFI of CD138 on plasmablasts remained higher among B cells from unstable patients, even after adjusting for the same control variables. On other hand, the intensity of IgD expression persisted significantly higher among naïve, plasmablast, and CD27 + CD38 + memory B cells from stable MS patients. Concerning the cytokine profile, even after adjusting for age, EDSS, and gender, the percentage of transitional and memory B‐cell subsets (CD27 − CD38 − and CD27 + CD38 − ) with IL‐17 + IL‐10 − phenotype remained significantly higher in relapsed group, while IL‐17 − IL‐10 + plasmablast frequency remained higher in stable patients.

Finally, by applying both ROC analysis of Firth Logistic Regression Models (Supporting Information 5 : Table S2 ) and internal validation using LOOCV (Supporting Information 6 : Table S3 ), the following parameters showed an excellent discriminatory performance for predicting disease stability or clinical relapses in 1‐year follow‐up: percentages of HLA‐DR − IgD + naïve, plasmablast, and memory B cells, IL‐17 − IL‐10 + transitional cells, IL‐17 + IL‐10 − plasmablasts and memory B cells, as well as the intensity of expression of IgD per transitional cell and of CD138 per plasmablast. The LOOCV‐AUC, sensitivity, specificity, and overall accuracy were above 90% (Supporting Information 7 : Table S4 ).

3.3. Plasma Levels of CXCL13 and NfL Were Correlated With Different B‐Cell Subsets in MS Patients

It is known that the migration of B cells expressing CXCR5 to LFs is mediated by the chemokine CXCL13 [ 9 ]. As demonstrated in Supporting Information 8 : Figure S4 , most circulating B cells express CXCR5, with no difference between the three different subgroups. When compared with the control group, the plasma levels of CXCL13 were higher in pwMS samples, mainly among unstable patients (Table 1 ). Furthermore, the plasma NfL concentration, a biomarker of MS activity [ 14 ], presented a tendency to increase in relapsed pwMS (Table 1 , p = 0.079). The mean NfL levels in the control group were very low (most of them below the detection limit). Among stable and relapsed pwMS, CXCL13 levels directly correlated with the frequency of total and CD138 + plasmablasts and memory B cells with phenotype HLA‐DR + IgD − (Table 4 ). Regarding NfL, plasma levels of this protein, in both MS subgroups, positively correlated with CD138 + and HLA‐DR + IgD − plasmablasts but negatively correlated with HLA‐DR − IgD + cell phenotypes among transitional and naïve cells (Table 4 ). No correlation was observed between the percentage of cytokine‐producing B‐cell subsets with either CXCL13 or NfL levels in either patient group (Supporting Information 7 : Table S4 ).

4. Discussion

Although RRMS patients evolve through acute episodes of neurological impairment followed by total or partial remission, unfortunately most patients progress to the secondary neurodegenerative form (SPMS) despite DMT. This form is characterized by progressive neuroimage worsening and accumulation of irreversible physical and cognitive impairments due to neurodegeneration. The recent identification of B‐cell‐rich eFLs in the meninges underlying SPMS lesions suggests B‐cell involvement in the neurodegenerative process [ 11 – 14 , 29 ]. Interestingly, our findings suggest that differential expression of HLA‐DR and IgD, as well as IL‐10 and IL‐17, on RRMS‐derived B‐cell subsets may indicate risk of disease progression.

It is known that most DMTs targeting effector/memory T‐cell lymphocytes [ 30 ] are considered the primary immune cells involved in demyelination in RRMS [ 31 ]. Nonetheless, therapies targeting B‐cell depletion produce significant clinical benefits, which have been associated with decreased pro‐inflammatory CD4 + and CD8 + T‐cell subtypes [ 32 , 32 ]. Furthermore, some DMTs that modulate T‐cell functions also appear to target B‐cell subsets. Ramgolam et al. [ 33 ] demonstrated that treatment of RRMS patients with IFN‐β‐1β diminished the immunogenicity of B cells, identified by lower CD40 and CD80 expression and reduced production of GM‐CSF, IL‐1β and IL‐23 cytokines, while elevating IL‐10 + B‐cell frequency. Hâusler et al. [ 34 ] also found an increase in IL‐10 + B‐cell frequency, associated with decreased transitional cells and plasmablast frequency in RRMS patients treated with AG. Indeed, treatment of RRMS with DMF has been reported to reduce memory B cells [ 35 , 36 ] and plasmablasts [ 34 ] but elevate transitional and IL‐10 + B‐cell frequency. RRMS patients undergoing FGL therapy showed elevated percentages of circulating plasmablasts, IL‐10 + B cells, and particularly transitional cells [ 37 ]. Finally, NATz has been shown to increase the percentage of different memory B‐cell subsets (CD27 + CD38 + , CD27 + CD38 − and CD27 − CD38 − ) but reduce plasmablasts and IgG titers in RRMS patients [ 38 ]. Also, NATz failure was associated with diminished circulating memory B‐cell subsets but elevated transitional and plasmablast cells [ 38 ]. Altogether, the studies above showed that these drugs preferentially target memory B cells, plasmablast, transitional, and IL‐10 + B cells. In our cohort, no consistent pattern across MS therapies for any of the B‐cell populations analyzed was found to be significant, probably due to our small sample size and/or the longer treatment time our patients underwent when compared with those recruited in the other studies.

Here, compared with healthy individuals, pwMS showed a higher proportion of total plasmablasts, with no difference in the other B‐cell subsets. Nonetheless, the analysis of the expression of other biological markers showed that an imbalance of different B‐cell subsets correlated with disease severity, regardless of DMT.

Higher frequency of HLA‐DR + , either IgD + or IgD − , and most memory CD27 + and CD27 − B‐cell subsets were observed in pwMS by comparison with the control group. Regarding memory B cells, Negron et al. [ 8 ] found that the massive presence of eFLs in meningeal areas adjacent to neurodegenerative lesions in SPMS patients correlated with an abnormally expanded memory IgD − CD27 − B‐cell subset. Interestingly, a similar B‐cell phenotype, HLA‐DR + IgD − CD27 − CD38 − was associated with higher risk for new relapses during the 1‐year follow‐up. For human memory B cells, loss of CD27 expression indicates differentiation and maturation [ 39 , 40 ]. Therefore, circulating CD27 + B cells possibly become CD27 − cells when they are reactivated following a new relapse. Since studies have shown that the frequency of relapses elevates the risk of MS progression [ 41 , 42 ], the correlation between HLA‐DR + IgD − CD27 + CD38 + memory B‐cell frequency and severity of neurological impairment, determined by EDSS score, may be associated, at least in part, with the ability of CD27 + IgD − cells to become CD27 − ones. Interestingly, in the present study, plasma CXCL13 levels not only positively correlated with HLA‐DR + IgD + memory B‐cell frequency but were also associated with occurrences of new relapses.

Beyond HLA‐DR + memory B cells, disease activity positively correlated with total and CD138 + plasmablasts. The frequency of plasmablast with HLA‐DR + IgD − or CD138 + phenotypes was associated with both EDSS score and clinical activity. Plasmablasts, either CD138 + or HLA‐DR + IgD − subsets, are a precursor to plasma cells that migrate to bone marrow and LFs from different secondary lymphoid organs [ 43 , 44 ]. In lupus, CD138 expression and high HLA‐DR levels on plasmablasts correlate with disease activity and anti‐dsDNA antibody titers [ 45 ]. Moreover, in the present study, plasma CXCL13 levels positively correlated with CD138 + plasmablast.

Through CXCR5 expression, B cells can migrate to different tissues in response to chemokines, such as CXCL13 [ 46 ]. CXCL13, found to be elevated in the CSF and plasma of RRMS patients, correlated with the presence of B cells and plasmablasts [ 47 ]. Disano et al. [ 48 ] demonstrated that the chemokine CXCL13, by favoring eFL formation, can be an excellent biomarker of MS activity. Moreover, we observed a positive correlation between CD138 + and HLA‐DR + IgD − plasmablasts and plasma NfL levels, a neuro‐specific marker of disease activity and neuroaxonal damage in MS [ 13 ].

In contrast to HLA‐DR + IgD − cells, the presence of HLA‐DR − IgD + cells was associated with less severe disease. Here, higher frequency of HLA‐DR − IgD + memory B cells at baseline correlated with clinically stable MS. Although a lower proportion of HLA‐DR − IgD + transitional cells was observed in pwMS than the control group, these cells were negatively associated with both neurological disabilities and occurrence of new relapses during follow‐up. Additionally, a higher percentage of HLA‐DR − IgD + naïve cells was also observed among nonrelapsed patients. Also, plasma NfL levels negatively correlated with the presence of transitional and naïve B cells with HLA‐DR − IgD + phenotype.

Given that HLA‐DR signaling amplifies B‐cell activation [ 49 ], we believe that the expansion of anergic HLA‐DR − IgD + B‐cell subsets is associated with better MS prognosis. Moreover, unlike IgA, IgE, IgG, and IgM, which are widely studied, the role of IgD is still not well understood [ 50 , 51 ]. Some authors have found that high IgD levels on the B‐cell surface, associated with lower IgM expression, could be indicative of anergic lymphocytes in peripheral blood and secondary lymphoid tissues, most of them self‐reactive cells, leading to a dysfunctional response to self‐antigens [ 50 , 51 ]. Although we did not evaluate IgM expression, more intense IgD expression according to B‐cell subset was observed in clinically stable RRMS patients.

The absence of HLA‐DR on MS‐related IgD + B‐cell subsets, if confirmed in a larger patient cohort, may indicate that this immune regulation does not depend on their role as antigen‐presenting cells to CD4 + T cells but rather on their ability to produce anti‐inflammatory cytokines, such as IL‐10 [ 52 ].

Classically, cytokines like IL‐17 and IL‐10, mainly produced by effector (IL‐17) and regulatory (IL‐10) lymphocytes, have been associated with MS disease activity and control, respectively [ 53 ]. In the present study, although the effect of DMTs in inhibiting pro‐inflammatory cytokine production [ 32 – 38 ] may explain the lower frequency of IL‐17 + B‐cell subsets in pwMS as compared with healthy individuals, the frequency of IL‐17 + IL‐10 − B‐cell subsets was associated with clinical relapses. Also, the presence of IL‐17 + IL‐10 − plasmablasts and IL‐17 + memory CD27 + CD28 + B cells correlated positively with EDSS score. On the other hand, the presence of an elevated percentage of IL‐17 − IL‐10 + transitional B cells was associated with both less neurological damage (a lower EDSS score) and absence of new relapses.

In humans, transitional cells are closely related to IL‐10‐producing regulatory B cells (Bregs) in terms of phenotypical and functional similarities [ 2 ]. As reported by Zhou et al. [ 54 ], the main functions of transitional B cells are able to suppress both proliferation of autoreactive CD4 + T cells and inhibit Th1 and Th17 cell differentiation, thus limiting excessive production of pro‐inflammatory cytokines, such as IL‐17. Moreover, transitional cells promote the conversion of effector CD4 + T cells into regulatory T cells (Tregs). Many of these regulatory immune functions have been associated with IL‐10 production by transitional cells that are able to inhibit CD8 + T‐cell responses [ 55 ]. However, damage to transitional cells has been observed in autoimmune diseases, including MS [ 56 , 57 ], neuromyelitis optica spectrum disorders (NMOSDs) [ 58 ], and lupus [ 59 ]. In MS, fewer transitional cells were detected in patients with clinically isolated syndrome (CIS) than in healthy individuals, and the frequency of transitional cells was increased after related treatments, such as FGL [ 60 – 62 ]. Transitional cells in the peripheral blood of pwMS undergoing treatment with FGL produced more IL‐10 and less TNF‐α than memory and mature naïve B cells and expressed low CD80 levels [ 60 ]. Clinical control of relapses by therapy with IFN‐β, DMF, and FGL correlates with increased frequency of circulating IL‐10 + transitional and IL‐10 + naïve B cells and reduced proportion of memory IgD − B cells [ 63 – 66 ]. Moreover, a study by Grutzke et al. [ 62 ] found that IL‐10‐producing B cells, induced by FGL treatment, were able to migrate into the CNS and reduce disease severity. Currently, our group is dedicated to analyzing the frequency of different RRMS‐derived B‐cell subtypes just before and 1 year after initiating DMT.

In addition to transitional cells, IL‐17 − IL‐10 + plasmablasts were inversely correlated with neurological impairment in the present study. In an experimental MS model, named Experimental Autoimmune Encephalomyelitis (EAE), expansion of IL‐10 + plasmablasts attenuated disease severity, which was associated with decreased infiltration of pathogenic T cells into the CNS of the animals [ 67 ]. Therefore, the ability of DMT to expand tolerogenic B‐cell phenotypes, such as HLA‐DR − IgD + and IL‐17 − IL‐10 + , mainly among transitional and plasmablast cells, may contribute to achieving a more stable clinical evolution of the disease, known as “no evidence of disease activity ( NEDA )” [ 68 ].

Although these findings are interesting, in the present study, the B cells were stimulated by a nonphysiological, receptor‐independent B‐cell activator, which does not allow to determine the fraction of dysregulated B cells directed against myelin antigens. Additionally, independent external validation in larger, multicenter cohorts will be required to confirm the reproducibility and generalizability of these findings.

In addition, it is possible that the difference in B‐cell subsets between stable and unstable MS patients is related to the ethnicity. As demonstrated in Table 1 , the majority of relapsed patients were Afrodescendent. As compared with Caucasian individuals, MS is more severe and less responsive to DMT treatment in Afrodescendent, including among Brazilian patients [ 69 – 72 ].

By using similar surface markers (CD27, CD38, IgD, and CD138), Telesford et al. [ 73 ] demonstrated significant difference in circulating B‐cell subsets in natalizumab‐treated MS patient according to self‐reported ethnicity. As compared with Caucasians, Afrodescent showed an increased baseline frequency of memory B cells, CD138 + plasmablasts, and elevated systemic and CSF antineuron IgG [ 73 ]. Unfortunately, those authors did not evaluate the percentage of IgD + HLA‐DR − B cells. Therefore, it is probably that elevated prevalence of Afrodescent in unstable patients contribute to perfect, or near‐perfect, predictive performance between B‐cell subsets and clinical activity of MS observed in our cohort.

5. Conclusions

Despite our small sample size, the data presented here are original and indicate, for the first time, that accumulation of B‐cell subsets differently expressing HLA‐DR, IgD, IL‐17, and IL‐10, associated with the expression of CD138 on plasmablasts, could be effective biomarkers for differentiating DMT‐treated RRMS patients at low‐ or high‐risk of therapy failure and disease evolution. Notably, MS severity was associated with the presence of CD138 + plasmablast and IL‐17 + IL‐10 − , HLA‐DR + IgD − cell phenotypes among plasmablast, transitional, and memory CD27 + CD38 + B‐cell subsets. On the other hand, stable DMT‐treated patients showed higher frequency of circulating transitional and plasmablasts with HLA‐DR − IgD + and IL‐17 − IL‐10 + phenotypes.

Funding

This work was supported by Fundação de Amparo à Pesquisa Carlos Chagas Filho (FAPERJ (Grants E‐26/202.940/2017 and E‐26/202.726/2019) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Grant 301.780/2017‐0).

Disclosure

The authors declare that no generative AI was used in the creation of this manuscript.

Ethics Statement

The study was approved by the Ethics Committee for Research on Human Subjects of the Federal University of the State of Rio de Janeiro (UNIRIO) (CAAE number: 43009015.6.0000.5258). All samples were collected only after written informed consent was obtained from each individual.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting Information

Additional supporting information can be found online in the Supporting Information section.

Supporting information

Supporting Information 1 Figure S1: Flow cytometry supporting information and representative dot‐plots of different B cell (CD19 + ) subsets in healthy and RRMS patients.

Supporting Information 2 Figure S2: Analysis of the different RRMS‐derived B cell subsets according to treatment. In DMT‐treated RRMS patients.

Supporting Information 3 Figure S3: The stimulation‐induced IL‐17 and IL‐10 response by B cells in healthy and RRMS patients.

Supporting Information 4 Table S1: Multivariate firth logistic regression.

Supporting Information 5 Table S2: ROC analysis of firth logistic regression models.

Supporting Information 6 Table S3: LOOCV validation of firth logistic regression models.

Supporting Information 7 Table S4: Correlation between CXCL13, NfL and cytokine‐producing B cell subsets from MS patients.

Supporting Information 8 Figure S4: The frequency of total CXCR5 + B cells in healthy and stable and relapsed RRMS patients.

Data Availability Statement

The datasets generated during and/or analyzed in the current study are available from the corresponding author upon reasonable request.

References

1. Milo R. and Miller A., Revised Diagnostic Criteria of Multiple Sclerosis, Autoimmunity Reviews. (2014) 13, no. 4-5, 518–524, 10.1016/j.autrev.2014.01.012.

2. Wing A. C., Hygino J., and Ferreira T. B., et al.Interleukin-17- and Interleukin-22-Secreting Myelin-Specific CD4(+) T Cells Resistant to Corticoids are Related With Active Brain Lesions in Multiple Sclerosis Patients, Immunology. (2016) 147, no. 2, 212–220, 10.1111/imm.12552.

3. Ferreira T. B., Hygino J., and Wing A. C., et al.Different Interleukin-17-Secreting Toll-Like Receptor + T-Cell Subsets are Associated With Disease Activity in Multiple Sclerosis, Immunology. (2018) 154, no. 2, 239–252, 10.1111/imm.12872.

4. Kebir H., Ifergan I., and Alvarez J. I., et al.Preferential Recruitment of Interferon-Gamma-Expressing TH17 Cells in Multiple Sclerosis, Annals of Neurology. (2009) 66, no. 3, 390–402, 10.1002/ana.21748.

5. Lovett-Racke A. E., Yang Y., and Racke M. K., Th1 Versus Th17: are T Cell Cytokines Relevant in Multiple Sclerosis?, Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease. (2011) 1812, no. 2, 246–251, 10.1016/j.bbadis.2010.05.012.

6. Restorick S. M., Durant L., and Kalra S., et al.CCR6 + Th Cells in the Cerebrospinal Fluid of Persons With Multiple Sclerosis are Dominated by Pathogenic Non-Classic Th1 Cells and GM-CSF-Only-Secreting Th Cells, Brain, Behavior, and Immunity. (2017) 64, 71–79, 10.1016/j.bbi.2017.03.008.

7. Mahad D. H., Trapp B. D., and Lassmann H., Pathological Mechanisms in Progressive Multiple Sclerosis, The Lancet Neurology. (2015) 14, no. 2, 183–193, 10.1016/S1474-4422(14)70256-X.

8. Negron A., Stüve O., and Forsthuber T. G., Ectopic Lymphoid Follicles in Multiple Sclerosis: Centers for Disease Control?, Frontiers in Neurology. (2020) 8, no. 11, 607–766, 10.3389/fneur.2020.607766.

9. Harrer C., Otto F., and Radlberger R. F., et al.The CXCL13/CXCR5 Immune Axis in Health and Disease-Implications for Intrathecal B Cell Activities in Neuroinflammation, Cells. (2022) 11, no. 17, 26–49, 10.3390/cells11172649.

10. Havenar-Daughton C., Lindqvist M., and Heit A., et al.CXCL13 is a Plasma Biomarker of Germinal Center Activity, Proceedings of the National Academy of Sciences. (2016) 113, no. 10, 2–7, 10.1073/pnas.1520112113.

11. Rao D. A., T Cells That Help B Cells in Chronically Inflamed Tissues, Frontiers in Immunology. (2018) 23, no. 9, 19–24, 10.3389/fimmu.2018.01924.

12. Serafini B., Rosicarelli B., Magliozzi R., Stigliano E., and Aloisi F., Detection of Ectopic B-Cell Follicles With Germinal Centers in the Meninges of Patients With Secondary Progressive Multiple Sclerosis, Brain Pathology. (2004) 14, no. 2, 164–174, 10.1111/j.1750-3639.2004.tb00049.x.

13. Comabella M., Cantó E., and Nurtdinov R., et al.MRI Phenotypes With High Neurodegeneration are Associated With Peripheral Blood B-Cell Changes, Human Molecular Genetics. (2016) 25, no. 3, 8–16, 10.1093/hmg/ddv473.

14. Magliozzi R., Howell O. W., and Nicholas R., et al.Inflammatory Intrathecal Profiles and Cortical Damage in Multiple Sclerosis, Annals of Neurology. (2018) 83, no. 4, 739–755, 10.1002/ana.25197.

15. Cencioni M. T., Mattoscio M., Magliozzi R., Bar-Or A., and Muraro P. A., B Cells in Multiple Sclerosis—From Targeted Depletion to Immune Reconstitution Therapies, Nature Reviews Neurology. (2021) 17, no. 7, 399–414, 10.1038/s41582-021-00498-5.

16. Ferreira-Atuesta C., Reyes S. A., Giovanonni G., and Gnanapavan S., The Evolution of Neurofilament Light Chain in Multiple Sclerosis, Frontiers in Neuroscience. (2021) 6, no. 15, 642–384, 10.3389/fnins.2021.642384.

17. Jiang X., Zhang H., Liu Y., Sun B., and Mu G., Global Perspectives on the Contribution of B Cells to Multiple Sclerosis: An in-Depth Examination and Evaluation, Frontiers in Immunology. (2024) 15, 10.3389/fimmu.2024.1442694, 1442694.

18. Genc K., Dona D. L., and Reder A. T., Increased CD80(+) B Cells in Active Multiple Sclerosis and Reversal by Interferon Beta-1b Therapy, The Journal of Clinical Investigation. (1997) 99, no. 26, 64–71, 10.1172/JCI119455.

19. Charabati M., Wheeler M. A., Weiner H. L., and Quintana F. J., Multiple Sclerosis: Neuroimmune Crosstalk and Therapeutic Targeting, Cell. (2023) 186, no. 7, 1309–1327, 10.1016/j.cell.2023.03.008.

20. Fraussen J., Claes N., and Van Wijmeersch B., et al.B Cells of Multiple Sclerosis Patients Induce Autoreactive Proinflammatory T Cell Responses, Clinical of Immunology. (2016) 173, no. 1, 24–32, 10.1016/j.clim.2016.10.001.

21. Bar-Or A., Fawaz L., and Fan B., et al.Abnormal B-Cell Cytokine Responses a Trigger of T-Cell-Mediated Disease in MS?, Annals of Neurology. (2010) 67, no. 4, 52–61, 10.1002/ana.21939.

22. Duddy M. E., Alter A., and Bar-Or A., Distinct Profiles of Human B Cell Effector Cytokines: A Role in Immune Regulation?, Journal of Immunology. (2004) 172, no. 342, 2–7.

23. Duddy M., Niino M., and Adatia F., et al.Distinct Effector Cytokine Profiles of Memory and Naive Human B Cell Subsets and Implication in Multiple Sclerosis, Journal of Immunology. (2007) 178, no. 609, 2–9.

24. Miyazaki Y., Li R., and Rezk A., et al.A Novel microRNA-132-Sirtuin-1 Axis Underlies Aberrant B-Cell Cytokine Regulation in Patients With Relapsing-Remitting Multiple Sclerosis, PLoS ONE. (2014) 91, no. 5, 4–21.

25. Xie G., Chen X., and Gao Y., et al.Age-Associated B Cells in Autoimmune Diseases: Pathogenesis and Clinical Implications, Clinical Reviews in Allergy & Immunology. (2025) 68, no. 1, 10.1007/s12016-025-09021-w.

26. Kumar G. and Axtell R. C., Dual Role of B Cells in Multiple Sclerosis, International Journal of Molecular Sciences. (2023) 24, no. 3, 23–36, 10.3390/ijms24032336.

27. Kurtzke J. F., Disability Rating Scales in Multiple Sclerosis, Annals of the New York Academy of Sciences. (1984) 436, no. 1, 347–360, 10.1111/j.1749-6632.1984.tb14805.x.

28. Polman C. H., Reingold S. C., and Banwell B., et al.Diagnostic Criteria for Multiple Sclerosis: 2010 Revisions to the McDonald Criteria, Annals of Neurology. (2011) 69, no. 2, 292–302, 10.1002/ana.22366.

29. Grunwald C., Krętowska-Grunwald A., Adamska-Patruno E., Kochanowicz J., Kułakowska A., and Chorąży M., The Role of Selected Interleukins in the Development and Progression of Multiple Sclerosis—A Systematic Review, International Journal of Molecular Sciences. (2024) 25, no. 5, 10.3390/ijms25052589, 2589.

30. Kaskow B. J. and Baecher-Allan C., Effector T Cells in Multiple Sclerosis, Cold Spring Harbor Perspectives in Medicine. (2018) 8, no. 4, 10.1101/cshperspect.a029025, a029025.

31. Greenfield A. L. and Hauser S. L., B-Cell Therapy for Multiple Sclerosis: Entering an Era, Annals of Neurology. (2018) 83, no. 1, 13–26, 10.1002/ana.25119.

32. Brück W., Gold R., and Lund B. T., et al.Therapeutic Decisions in Multiple Sclerosis: Moving Beyond Efficacy, JAMA Neurology. (2013) 70, no. 10, 1315–1324, 10.1001/jamaneurol.2013.3510.

33. Ramgolam V. S., Sha Y., and Marcus K. L., et al.B Cells as a Therapeutic Target for IFN-β in Relapsing-Remitting Multiple Sclerosis, The Journal of Immunology. (2011) 186, no. 7, 4518–4526, 10.4049/jimmunol.1000271.

34. Häusler D., Hajiyeva Z., and Traub J. W., et al.Glatiramer Acetate Immune Modulates B-Cell Antigen Presentation in Treatment of MS, Neurology Neuroimmunology & Neuroinflammation. (2020) 7, no. 3, 10.1212/NXI.0000000000000698, e698.

35. Staun-Ram E., Najjar E., Volkowich A., and Miller A., Dimethyl Fumarate as a First- vs Second-Line Therapy in MS: Focus on B Cells, Neurology Neuroimmunology & Neuroinflammation. (2018) 5, no. 6, 10.1212/NXI.0000000000000508, e508.

36. Traub J., Traffehn S., and Ochs J., et al.Dimethyl Fumarate Impairs Differentiated B Cells and Fosters Central Nervous System Integrity in Treatment of Multiple Sclerosis, Brain Pathology. (2019) 29, no. 5, 640–657, 10.1111/bpa.12711.

37. Blumenfeld S., Staun-Ram E., and Miller A., Fingolimod Therapy Modulates Circulating B Cell Composition, Increases B Regulatory Subsets and Antigen of IL10 and TGFβ in Patients With Multiple Sclerosis, Journal of Autoimmunity. (2016) 70, 40–51, 10.1016/j.jaut.2016.03.012.

38. Cuculiza Henriksen A., Ammitzbøll C., and Petersen E. R., et al.Natalizumab Differentially Affects Plasmablasts and B Cells in Multiple Sclerosis, Multiple Sclerosis and Related Disorders. (2021) 52, 10.1016/j.msard.2021.102987, 102987.

39. Grimsholm O., Piano Mortari E., and Davydov A. N., et al.The Interplay Between CD27dull and CD27bright B Cells Ensures the Flexibility, Stability, and Resilience of Human B Cell Memory, Cell Reports. (2020) 30, no. 9, 2963–2977.e6, 10.1016/j.celrep.2020.02.022.

40. Grimsholm O., CD27 on Human Memory B Cells-More Than Just a Surface Marker, Clinical and Experimental Immunology. (2023) 213, no. 2, 164–172, 10.1093/cei/uxac114.

41. Scalfari A., Neuhaus A., and Degenhardt A., et al.The Natural History of Multiple Sclerosis: A Geographically Based Study 10: Relapses and Long-Term Disability, Brain. (2010) 133, no. 7, 1914–1929, 10.1093/brain/awq118.

42. Fuh-Ngwa V., Charlesworth J. C., and Zhou Y., et al.The Association Between Disability Progression, Relapses, and Treatment in Early Relapse Onset MS: An Observational, Multi-Centre, Longitudinal Cohort Study, Scientific Reports. (2023) 13, no. 1, 10.1038/s41598-023-38415-z, 11584.

43. Jacobi A. M., Mei H., and Hoyer B. F., et al.HLA-DRhigh/CD27High Plasmablasts Indicate Active Disease in Patients With Systemic Lupus Erythematosus, Annals of the Rheumatic Diseases. (2010) 69, no. 1, 305–308, 10.1136/ard.2008.096495.

44. Chen W., Hong S. H., and Jenks S. A., et al.Distinct Transcriptomes and Autocrine Cytokines Underpin Maturation and Survival of Antibody-Secreting Cells in Systemic Lupus Erythematosus, Nature Communications. (2024) 15, no. 1, 10.1038/s41467-024-46053-w, 1899.

45. McCarron M. J., Park P. W., and Fooksman D. R., CD138 Mediates Selection of Mature Plasma Cells by Regulating Their Survival, Blood. (2017) 129, no. 20, 2749–2759, 10.1182/blood-2017-01-761643.

46. Krumbholz M., Theil D., and Cepok S., et al.Chemokines in Multiple Sclerosis: CXCL12 and CXCL13 up-Regulation is Differentially Linked to CNS Immune Cell Recruitment, Brain. (2006) 129, no. 1, 200–211, 10.1093/brain/awh680.

47. Schropp V., Chunder R., Dietel B., Tacke S., and Kuerten S., The Presence of Cerebellar B Cell Aggregates is Associated With a Specific Chemokine Profile in the Cerebrospinal Fluid in a Mouse Model of Multiple Sclerosis, Journal of Neuroinflammation. (2023) 20, no. 1, 10.1186/s12974-023-02695-z.

48. Disano K. D., Gilli F., and Pachner A. R., Intrathecally Produced CXCL13: A Predictive Biomarker in Multiple Sclerosis, Multiple Sclerosis Journal–Experimental, Translational and Clinical. (2020) 6, no. 4, 2055–2173, 10.1177/2055217320981396.

49. Tabata H., Matsuoka T., Endo F., Nishimura Y., and Matsushita S., Ligation of HLA-DR Molecules on B Cells Induces Enhanced Expression of IgM Heavy Chain Genes in Association With Syk Activation, Journal of Biological Chemistry. (2000) 275, no. 45, 34998–35005, 10.1074/jbc.M002089200.

50. Sabouri Z., Perotti S., and Spierings E., et al.IgD Attenuates the IgM-Induced Anergy Response in Transitional and Mature B Cells, Nature Communications. (2016) 7, no. 1, 33–81, 10.1038/ncomms13381.

51. Gutzeit C., Chen K., and Cerutti A., The Enigmatic Function of IgD: Some Answers at Last, European Journal of Immunology. (2018) 48, no. 7, 1101–1113.

52. Radomir L., Kramer M. P., and Perpinial M., et al.The Survival and Function of IL10-Producing Regulatory B Cells are Negatively Controlled by SLAMF5, Nature Communication. (2021) 12, no. 1, 1893.

53. Attfield K. E., Jensen L. T., and Kaufmann M., et al.The Immunology of Multiple Sclerosis, Nature Reviews Immunology. (2022) 22, 734–750.

54. Zhou Y., Zhang Y., Han J., Yang M., Zhu J., and Jin T., Transitional B Cells Involved in Autoimmunity and Their Impact on Neuroimmunological Diseases, Journal of Translational Medicine. (2020) 18, no. 1.

55. Flores-borja F., Bosma A., and Ng D., et al.CD19 + CD24 hi CD38 hi B Cells Maintain Regulatory T Cells While Limiting TH1 and TH17 Differentiation, Science Translational Medicine. (2013) 5, no. 173, 173ra23.

56. Lee-Chang C., Top I., and Zephir H., et al.Primed Status of Transitional B Cells Associated With Their Presence in the Cerebrospinal Fluid in Early Phases of Multiple Sclerosis, Clinical Immunology. (2011) 139, no. 1, 12–20.

57. Giacomini E., Rizzo F., and Etna M. P., et al.Thymosin-Alpha1 Expands Deficient IL10-Producing Regulatory B Cell Subsets in Relapsing-Remitting Multiple Sclerosis Patients, Multiple Sclerosis. (2018) 24, no. 2, 127–139.

58. Quan C., Yu H., and Qiao J., et al.Impaired Regulatory Function and Enhanced Intrathecal Activation of B Cells in Neuromyelitis Optica: Distinct From Multiple Sclerosis, Multiple Sclerosis. (2013) 19, no. 3, 289–298.

59. Blair P. A., Norena L. Y., and 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, no. 1, 129–140.

60. Miyazaki Y., Niino M., and Fukazawa T., et al.Suppressed Pro-Inflammatory Properties of Circulating B Cells in Patients With Multiple Sclerosis Treated With Fingolimod, Based on Altered Proportions of B-Cell Subpopulations, Clinical Immunology. (2014) 151, no. 2, 127–135.

61. Claes N., Dhaeze T., and Fraussen J., et al.Compositional Changes of B and T Cell Subtypes During Fingolimod Treatment in Multiple Sclerosis Patients: A 12-Month Follow-up Study, PLoS ONE. (2014) 9, 111–115.

62. Grutzke B., Hucke S., and Gross C. C., et al.Fingolimod Treatment Promotes Regulatory Phenotype and Function of B Cells, Annals of Clinical. Translational Neurology. (2015) 2, 119–130.

63. Schubert R. D., Hu Y., and Kumar G., et al.IFN-Beta Treatment Requires B Cells for Efficacy in Neuroautoimmunity, Journal of Immunology. (2015) 194, 2110–2116.

64. Dooley J., Pauwels I., and Franckaert D., et al.Immunologic Profiles of Multiple Sclerosis Treatments Reveal Shared Early B Cell Alterations, Neurology Neuroimmunology & Neuroinflammation. (2016) 3.

65. Lundy S. K., Wu Q., and Wang Q., et al.Dimethyl Fumarate Treatment of Relapsing-Remitting Multiple Sclerosis Influences B-Cell Subsets, Neurology Neuroimmunology & Neuroinflammation. (2016) 3.

66. Li R., Rezk A., and Ghadiri M., et al.Dimethyl Fumarate Treatment Mediates an Anti-Inflammatory Shift in B Cell Subsets of Patients With Multiple Sclerosis, Journal of Immunology. (2017) 198, 691–698.

67. Matsumoto M., Baba A., and Yokota T., et al.Interleukin-10-Producing Plasmablasts Exert Regulatory Function in Autoimmune Inflammation, Immunity. (2014) 41, no. 6, 1040–1051.

68. Havenar Newsome S. D., Binns C., Kaunzner U. W., Morgan S., and Halper J., No Evidence of Disease Activity (NEDA) as a Clinical Assessment Tool for Multiple Sclerosis: Clinician and Patient Perspectives [Narrative Review], Neurology and Therapy. (2023) 12, no. 6, 1909–1935.

69. Jeannin S., Deschamps R., Chausson N., and Cabre P., Response to Interferon-Beta Treatment in Afro-Caribbeans With Multiple Sclerosis, Multiple Sclerosis International. (2011) 2011, 950126.

70. Ferreira Vasconcelos C. C., Cruz Dos Santos G. A., Thuler L. C., Camargo S. M., and Papais Alvarenga R. M., African Ancestry is a Predictor Factor to Secondary Progression in Clinical Course of Multiple Sclerosis, International Scholarly Research Notices. (2012) 2012, 410629.

71. Howard J., Battaglini M., and Babb J. S., et al.MRI Correlates of Disability in African-Americans With Multiple Sclerosis, PLoS One. (2012) 7, no. 8, e43061.

72. Aurenção J. C., Vasconcelos C. C., Thuler L. C., and Alvarenga R. M., Disability and Progression in Afro-Descendant Patients With Multiple Sclerosis, Neuro-Psiquiatria. (2016) 74, no. 10, 836–841.

73. Telesford K. M., Smith C., and Mettlen M., et al.Neuron-Binding Antibody Responses are Associated With Black Ethnicity in Multiple Sclerosis During Natalizumab Treatment, Brain Communications. (2023) 5, no. 4, fcad218.

Associated Data

Supplementary Materials

Supporting Information 1 Figure S1: Flow cytometry supporting information and representative dot‐plots of different B cell (CD19 + ) subsets in healthy and RRMS patients.

Supporting Information 2 Figure S2: Analysis of the different RRMS‐derived B cell subsets according to treatment. In DMT‐treated RRMS patients.

Supporting Information 3 Figure S3: The stimulation‐induced IL‐17 and IL‐10 response by B cells in healthy and RRMS patients.

Supporting Information 4 Table S1: Multivariate firth logistic regression.

Supporting Information 5 Table S2: ROC analysis of firth logistic regression models.

Supporting Information 6 Table S3: LOOCV validation of firth logistic regression models.

Supporting Information 7 Table S4: Correlation between CXCL13, NfL and cytokine‐producing B cell subsets from MS patients.

Supporting Information 8 Figure S4: The frequency of total CXCR5 + B cells in healthy and stable and relapsed RRMS patients.

Data Availability Statement

The datasets generated during and/or analyzed in the current study are available from the corresponding author upon reasonable request.