Figures
Abstract
Background
Changes in the blood lymphocyte composition probably both mediate and reflect the effects of natalizumab treatment in multiple sclerosis, with implications for treatment benefits and risks.
Methods
A broad panel of markers for lymphocyte populations, including states of activation and co-stimulation, as well as functional T cell responses to recall antigens and mitogens, were assessed by flow cytometry in 40 patients with relapsing multiple sclerosis before and after one-year natalizumab treatment.
Results
Absolute numbers of all major lymphocyte populations increased after treatment, most markedly for NK and B cells. The fraction of both memory and presumed regulatory B cell subsets increased, as did CD3-CD56dim cytotoxic NK cells, whereas CD3-CD56bright regulatory NK cells decreased. The increase in cell numbers was further associated with a restored T cell responsiveness to recall antigens and mitogens in functional assays.
Conclusions
Our data confirms that natalizumab treatment increases the number of lymphocytes in blood, likely mirroring the expression of VLA-4 being highest on NK and B cells. This finding supports reduction of lymphocyte extravasation as a main mode of action, although the differential effects on subpopulation composition suggests that cell-signalling may also be affected. The systemic increase in T cell responsiveness reflects the increase in numbers, and while augmenting anti-infectious responses systemically, localized responses may become correspondingly decreased.
Citation: Mellergård J, Edström M, Jenmalm MC, Dahle C, Vrethem M, Ernerudh J (2013) Increased B Cell and Cytotoxic NK Cell Proportions and Increased T Cell Responsiveness in Blood of Natalizumab-Treated Multiple Sclerosis Patients. PLoS ONE 8(12): e81685. https://doi.org/10.1371/journal.pone.0081685
Editor: Markus Reindl, Innsbruck Medical University, Austria
Received: March 14, 2013; Accepted: October 25, 2013; Published: December 2, 2013
Copyright: © 2013 Mellergård et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The study was supported by grants from The Swedish Association of Persons with Neurological Disabilities, The University Hospital of Linköping, The County Council of Östergötland and Linköping University. The study was further supported by an unrestricted grant from Biogen Idec Sweden. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: J. Mellergård has received speaker honorary from Biogen Idec. M. Edström has received speaker honorary from Biogen Idec. C. Dahle has received speaker honoraria from Biogen Idec and Merck Serono. M. Vrethem has received an unrestricted grant for research from Biogen Idec and speaker honoraria from Biogen Idec and Merck Serono. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.
Introduction
The pathogenesis of multiple sclerosis (MS) has been linked to T cells-mediated immune regulation, involving both CD4+ T helper and CD8+ T cytotoxic cells [1]. However, the pathogenic scenario has become more diverse including B cells [2,3], dendritic cells, natural killer (NK) cells and T cells with NK cell properties (NKT) [4]. Natalizumab, a humanized monoclonal antibody approved for the treatment of relapsing MS, is directed against the α4-chain of VLA-4 (α4β1) and α4β7 integrins present on lymphocytes. Natalizumab blocks the binding between these integrins and their endothelial receptors, vascular cell adhesion molecule-1 (VCAM-1) and mucosal addressin-cell adhesion molecule 1 (MadCAM-1) [5]. Consequently, treatment leads to a decline in the migration of potentially disease-promoting lymphocytes into the central nervous system (CNS), resulting in reduced intrathecal inflammation [6-8] and improvement in magnetic resonance imaging (MRI) measurements [9]. As a result of the decreased extravasation, a systemic accumulation of circulating NK cells [10], B cells [11] and pro-inflammatory T cells [12] has been observed after natalizumab treatment. In addition to reduced extravasation of lymphocytes and given the central role of integrins in cell-cell interactions, other immunomodulating mechanisms [13,14] probably contribute to the treatment outcome, including benefits and risks.
Since the first cases of progressive multifocal leukoencephalopathy (PML) in natalizumab-treated patients, it has been debated whether this JC-virus infection is merely a result of reduced immune surveillance in the CNS, or if other treatment mechanisms affecting lymphocyte populations may contribute. To further elucidate the mechanisms of treatment, the effects on lymphocyte populations have been investigated. However, several earlier reports were based on limited patient numbers and focused on restricted and specific blood lymphocyte populations such as CD4+ and CD8+ T cells [15-17], regulatory T cells (Treg) [18] and B cells [11,17], but did not address the simultaneous effects of natalizumab treatment on a broader panel of different lymphocyte populations and their expression of activation and co-stimulation markers. Furthermore, treatment effects as to functional capacity of lymphocytes have not previously been evaluated longitudinally in patients with MS.
We longitudinally followed 40 patients with MS before and after one-year natalizumab treatment, examining the numbers and proportions of circulating CD4+ and CD8+ T cells, Treg cells, B cells, NK cells, NKT cells as well as markers of activation and co-stimulation. In addition, functional studies of T cell responses to recall antigens and mitogens were performed. The aims were to explore changes in circulating lymphocyte subpopulation compositions and to assess the functional capacity of T cell responses during natalizumab treatment.
Methods
Ethics statement
The study was based on written informed consent, and approved by The Regional Ethics Committee in Linköping (Dnr M180-07 T130-09).
Patients and controls
Natalizumab treatment (300 mg once a month) was initiated in 40 patients with MS (Table 1). Initiation of treatment was based on clinical and MRI parameters, suggesting an active relapsing disease. All included patients fulfilled the McDonald criteria of MS [19] and were consecutively recruited from the Department of Neurology at the University Hospital, Linköping. Sampling of peripheral blood was obtained before (median 0.75 months, range 0-5.0) and after one year (median 12.0 months, range 10-17) of treatment. Definition of Expanded Disability Status Scale (EDSS) [20] score and Multiple Sclerosis Severity Score (MSSS) [21] were done by a neurologist (CD, MV or JM). The Symbol Digit Modalities Test (SDMT) [22] and the Multiple Sclerosis Impact Scale (MSIS-29) [23] were also performed. In the lymphocyte activation assay (see below) personnel (n=23) at the Department of Clinical immunology and transfusion medicine were recruited as controls, median age 45 years (range 35-59), 21 women and 2 men. All controls were healthy and without drug therapy.
Number of subjects | 40 |
---|---|
Median age (years) | 36.5 (range 22-62) |
Sex (M/F) | 22/18 |
Median disease duration (years) a | 9.5 (range 0.9-30.0) |
Diagnosis (RRMS / PRMS) | 34/6 |
EDSS (no. of subjects) | |
0-3.5 | 32 |
4.0-5.5 | 4 |
6.0-7.0 | 4 |
Median EDSS | 2.5 (range 0-7.0) |
Median MSSS | 3.82 (range 0.19-8.55) |
Treatment b | |
Interferon-β | 25 |
Glatiramer acetate | 4 |
IVIG | 1 |
Corticosteroids c | 3 |
No treatment | 10 |
Median number of relapses last two years | 2.0 (range 0-8) |
Number of patients with relapse last two months | 10 |
Flow cytometry
Whole blood was drawn in EDTA tubes. FACS Lysing Solution (BD Biosciences, San José, CA) was added for removal of erythrocytes. In total, five tubes were used, with the following antibody combinations. Tube A; anti-CD45-PerCP, anti-CD3-FITC, anti-CD4-PE-Cy7, anti-CD8-APC-Cy7, anti-CD16/56-PE,anti-CD19-APC, tube B; anti-CD3-PerCP, anti-CD4-PE-Cy7, anti-CD8-APC-Cy7, anti-CD28-PE, anti-CD56-APC, anti-CD57-FITC, tube C; anti-CD3-PerCP, anti-CD4-PE-Cy7, anti-CD8-APC-Cy7, anti-CD56-APC, anti-HLA-DR-FITC, anti-CD69-PE, tube D; anti-CD3-PerCP, anti-CD4-PE-Cy7, anti-CD8-APC-Cy7, anti-CD25-FITC, anti-OX40L-PE, tube E; anti-CD45-FITC, anti-CD19-PE-Cy7, anti-CD5-PerCP-Cy5.5, anti-CD25-APC, anti-CD27-PE and anti-HLA-DR-APC-Cy7 (all antibodies from BD Biosciences). For analysis of absolute cell numbers, TruecountTM tubes (BD Biosciences) were used for tube A. Collection of data was performed using a FACS Canto II with the FACS Diva software (BD Biosciences). Data was analyzed using the Kaluza software v 1.1 (Beckman Coulter, Brea, CA).
Lymphocytes were gated through forward and side scatter properties, in tubes A and E with the support of a CD45+ gate. Populations were defined on the basis of forming discrete populations or by using other populations as negative or positive populations. In tube A, T cells were selected through CD3+ expression, and thereafter gated for CD4 and CD8 expression. NK cells (CD16/56+) and B cells (CD19+) were gated from the CD3- population. For tube B, C and D, CD3+ T cells were divided into CD4+ and CD8+ populations. In tube B, the negative gate for CD28, defining CD4+CD28– and CD8+CD28– cells, were set through CD28 expression on CD3– cells, and included cells were analyzed for CD56/CD57 expression. For tube C, CD3–CD56+ NK cells were further gated as CD3–CD56bright or CD3–CD56dim. CD3–CD56+, CD3+CD4+ and CD3+CD8+ cells were analyzed for CD69 and HLA-DR expression. Tube D CD3+CD4+ and CD3+CD8+ cells were analyzed for CD25 and OX40L expression. In addition, regulatory (CD3+)CD4dimCD25bright [24] T cells were analyzed. Finally, in tube E, CD19+ B cells were gated for CD25 and CD27 expression, respectively. Polymorphonuclear cells were used to set the gate for CD25+ and CD27+ B cells.
Lymphocyte activation assay
To evaluate lymphocyte function we used, with some modifications, the previously described FASCIA method [25]. Briefly, peripheral blood was drawn in Heparin tubes; 50 µL were diluted 1:10 in culturing media, consisting of RPMI 1640 (Gibco BRL, Paisley, Scotland, UK) supplemented with L-glutamine 584 µg/mL (Sigma Aldrich, Stockholm, Sweden), penicillin 200 IE/mL and streptomycin 200 µg/mL (both from Cambrex, New Jersey, USA). Cultures were stimulated with influenza antigen 1:1000 (Vaxigrip; Sanofi Pasteur, Solna, Sweden), purified protein derivate (PPD) 10 µg/mL (SSI, Copenhagen, Denmark), a mix of cytomegalovirus (CMV) peptides 0.125 µg (BD Biosciences), tetanus toxin 5.7 Lf/mL (SSI), phytohaemagglutinin (PHA) 5 µg/mL (Sigma Aldrich), pokeweed mitogen (PWM) 10 µg/mL (Sigma Aldrich) or myelin basic protein (MBP) 100 µg/mL (Sigma Aldrich). Negative controls without antigen were cultured separately. Culturing ensued for seven days at 37°C with 5% CO2, after which cells were harvested and labeled with anti-CD3-FITC, anti-CD4-PerCP, anti-CD8-APC and anti-CD108-PE. After labeling, erythrocytes were lysed by incubating cells with 0.8% NH4Cl. Collection and analyses of data were performed using a FACS Canto II system running the FACS Diva software.
First, lymphocyte and lymphoblast gates were set using unstimulated samples (RPMI). The numbers of cells were calculated using TruecountTM tubes. Lymphoblasts were further gated into CD3+, CD3+CD4+ and CD3+CD8+ T cells. For each stimulus, the mean number of lymphoblasts in unstimulated cultures was subtracted from the number of lymphoblasts in the stimulated cultures, thereby compensating for baseline activation of cells. The numbers of CD4+, CD8+ and activated CD108+ cells for each stimulus were compared for patients before and after treatment.
To be able to make a baseline comparison regarding available cell numbers in blood between patients and controls, we calculated the numbers of total lymphocytes, CD3+, CD4+ and CD8+ T cells in unstimulated cultures after seven days of culture.
To further explore the responsiveness of cells before and after treatment, we calculated the fraction of lymphoblasts responding to different stimuli. Again, unstimulated (RPMI) cultures after seven days of culture were used to set gates for total lymphocytes and lymphoblasts based on FSC and SSC properties. Using these gates, we calculated the fractions of responsive lymphoblasts for the different stimuli, expressed as percentage of lymphocytes. This was achieved by dividing the number of gated blasts by the number of total lymphocytes after seven days of culture.
Statistics
For comparisons of flow cytometry and lymphocyte activation assay data, paired samples t-test was performed. Bi-variate correlation analyses (Pearson) were used to examine possible associations between flow cytometry and clinical variables. Flow cytometry data is given as mean values ± standard deviation (SD). For comparison between lymphocyte subpopulations at one-year follow-up, independent samples t test was used. For analyzing lymphocyte activation assay data, ANOVA with Tukey´s post-hoc test was used. Testing of activated lymphocyte fraction was analyzed with Kruskall-Wallis U test with Dunn´s post-hoc test. Due to multiple comparisons, p<0.01 was considered statistically significant and p<0.05 was considered a tendency. All statistical calculations were performed in SPSS 20.0 software (SPSS inc., Chicago, IL, USA).
Results
Clinical and CSF variables; changes after one year of natalizumab treatment
Although this was an observational study with the purpose of evaluating immunological effects of treatment, also clinical and CSF variables were recorded in a prospective manner. During the one-year follow-up, 34 patients were free from relapses, four patients had one relapse and two patients had two relapses. Four patients had a relapse within one month before follow-up sampling of peripheral blood, and two of these patients received treatment with methylprednisolone. The annualized relapse rate decreased from 1.0 to 0.1 on treatment. There was a significant improvement in clinical scoring systems as well as a decrease in CSF total white blood cell counts and IgG index at follow-up (Table 2).
Clinical /CSF parameters | Baseline | Follow-up | p |
---|---|---|---|
EDSS | 2.5 (0-7.0) | 2.5 (0-8.0) | 0.08 |
MSSS | 3.82 (0.19-8.55) | 3.20 (0.17-9.20) | <0.0005 |
MSIS-29 | |||
physical | 2.18 (1.00-4.75) | 1.40 (1.00-4.20) a | <0.0005 |
psychological | 2.11 (1.00-4.56) | 1.44 (1.00-4.56) a | <0.0005 |
SDMT | 48 (5-66) | 50 (11-65) b | 0.03 |
Total CSF wbc count | 2.55 (0.2-28.0) c | 1.1 (0.0-4.0) d | <0.0005 |
IgG index | 0.92 (0.48-3.0) c | 0.77 (0.45-2.4) d | <0.0005 |
Albumin ratio | 4.4 (2.1-11.4) c | 4.7 (1.8-10.1) d | 0.3 |
Changes in lymphocyte populations after one year of natalizumab treatment
Main lymphocyte populations.
Absolute numbers of all investigated lymphocyte populations were significantly increased at follow-up (Table 3). However, the relative size (percentage of parent population) of the increase differed across lymphocyte populations, leading to increased fractions of NK cells and CD8+ T cells, whereas fractions of CD3+ T cells and CD4+ T cells decreased (Figure 1 a-c, Table 3).
Number (cells/μl) | Percentage of parent population (%) | ||||||||
---|---|---|---|---|---|---|---|---|---|
baseline | follow-up | change | p | baseline | follow-up | change | p | ||
Lymphocytes | 1989 ± 630 | 3889 ±1163 | +96 % | <0.0005 | 27.7 ± 6.8 | 40.3 ± 7.0 | +45 % | <0.0005 | |
T cells | 1501 ± 554 | 2591 ± 915 | +73 % | <0.0005 | 75.0 ± 7.0 | 66.1 ± 6.7 | -12 % | <0.0005 | |
CD4+ | 896 ± 285 | 1435 ± 397 | +60 % | <0.0005 | 61.3 ± 9.7 | 56.6 ± 7.7 | -8 % | <0.0005 | |
CD8+ | 502 ± 316 | 975 ± 599 | +94 % | <0.0005 | 31.8 ± 8.4 | 35.9 ± 8.6 | +13 % | <0.0005 | |
NK cells | 277 ± 145 | 816 ± 248 | +195 % | <0.0005 | 14.3 ± 6.6 | 21.4 ± 5.2 | +50 % | <0.0005 | |
B cells | 258 ± 182 | 528 ± 296 | +105 % | <0.0005 | 12.5 ± 6.4 | 13.2 ± 5.1 | +6 % | 0.3 |
a: Distribution of lymphocytes (% of total leukocytes). Comparisons are pairwise. Bars denote mean values. b-c: Relative distribution of discrete lymphocyte subpopulations before (b) and after (c) natalizumab treatment.
CD4+ T cells.
The fraction of activated T helper cells, expressed as CD4+CD25+ (including both CD25dim and CD25bright cells) among CD4+ cells, decreased (from 23 ± 7.4 to 18 ± 4.6, Figure 2 a). However, the percentage of activated T helper cells as defined by the early activation marker CD69 (CD4+CD69+ cells), tended to increase (from 1.0 ± 0.5 to 1.5 ± 1.0, Figure 2 b). Fractions of CD4+OX40L+, representing activated immunomodulatory T cells, decreased (from 1.5 ± 1.5 to 0.6 ± 0.5, Figure 2 d) and CD4dimCD25bright Treg cells tended to decrease (from 3.1 ± 0.8 to 2.6 ± 0.8, Figure 2 f). The fractions of CD4+HLA-DR+, and CD4+CD28- subpopulations did not change pre- to post-treatment (Figure 2 c, e).
p<0.01 is considered statistically significant. Comparisons are pairwise. Bars show mean values, whiskers denote SD.
CD8+ T cells.
The fraction of late activated cytotoxic T cells, represented by CD8+HLA-DR+ cells among CD8+ cells, tended to increase (from 21 ± 12 to 24 ± 13, Figure 3 c). Fractions of CD8+OX40L+ T cells, representing activated immunomodulatory T cells, decreased from 2.4 ± 2.2 to 1.1 ± 0.8 Figure 3 d). Senescent cytotoxic CD8+CD28-CD57+ T cells decreased (from 72 ± 18 to 56 ± 21, Figure 3 f). The fractions of CD8+CD25+, CD8+CD69+ and CD8+CD28- subpopulations did not change pre- to post-treatment (Figure 3 a-b, e)
p<0.01 is considered statistically significant. Comparisons are pairwise. Bars show mean values, whiskers denote SD.
B cells, NK and NKT cells.
The fraction of CD19+CD27+ cells, representing memory B cells, increased (from 25 ± 11 to 45 ± 12), as did the fraction of CD19+CD25+ cells, presumably representing regulatory B cells (Breg) (from 25 ± 12 to 35 ± 14, Figure 4 a-b). The increase in the fraction of memory B cells was higher than the increase in the Breg population (p=0.005). Among CD3-CD56+ NK cells, an increase in the percentage of CD3-CD56dim NK cells (from 89 ± 7.2 to 92 ± 3.3, Figure 4 c) was accompanied by a decrease in CD3-CD56bright NK cells (from 11.1 ± 7.2 to 7.6 ±3.3, Figure 4 d). Early activated CD3-CD56+CD69+ NK cells tended to decrease (from 9.9 ± 12 to 5.8 ± 3.6, Figure 4 e). The percentages of CD3-CD56+HLA-DR+and total CD3+CD56+ NKT cells did not change pre-to post-treatment (Figure 4 f-g), as was also true for percentages of total NK cells and CD4+CD56+ NKT and CD8+CD56+ NKT subpopulations (data not shown).
p<0.01 is considered statistically significant. Comparisons are pairwise. Bars show mean values, whiskers denote SD.
Lymphocyte activation assay
The number of influenza antigen-activated CD4+ lymphoblasts increased after treatment (from 39 ± 85 cells/μl to 170 ± 236 cells/μl), as did the PPD-activated lymphoblasts (from 595 ± 914 to 1060 ± 1043, Figure 5 a-b). In addition, CD4 responses to both PWM (p<0.05) and CMV (p<0.05) tended to increase (data not shown). For CD8+ cells, an increased response was observed upon stimulation with PPD (from 11 ± 16 to 23 ± 25), PWM (from 262 ± 180 to 385 ± 215) and CMV (from 10 ± 17 to 68 ± 130, Figure 5 c-e). CD4+CD108+ activated T helper cells showed a stronger response towards influenza antigen post-treatment (from 3.6 ± 5.1 to 9.7 ± 10, Figure 5 f). Furthermore, MBP-induced responses tended to increase among CD4+CD108+ cells in treated patients (from 0.2 ± 0.7 to 0.7 ± 1.2, p=0.034). A similar tendency was seen in CD8+CD108+ activated cytotoxic cells after influenza stimulation (0.2 ± 0.7 to 0.8 ± 1.4, p=0.013).
Pairwise comparisons between patients before and after one year of natalizumab treatment. n=37 in both groups.
As controls, we analyzed the response of cell cultures in peripheral blood of healthy individuals. We found a stronger response in healthy individuals compared with pre-treatment levels of patients regarding influenza antigen-induced CD4+ and CD4+CD108+ T cell responses (166 ± 247 versus 39 ± 85 and 9.7 ± 14 versus 3.6 ± 5.1, respectively, Figure 6 a). However, post-treatment levels of patients were in the same range as those for controls. Since the FASCIA method used for these analyses takes into account both the total number of cells in the culture, as well as the responsiveness of these cells, we wanted to further explore the nature of the decreased response observed in pre-treatment patients compared to that of healthy controls. Analysis of unstimulated (RPMI) cultures revealed that numbers of cells were comparable between pre-treatment patients and controls, while post-treatment patients exhibited significantly increased cell numbers compared to pre-treatment patients, as well as compared to controls (see Figure S1 a-d). This finding implies that the decreased responsiveness in pre-treatment patients is not dependent on a low number of cells in culture and indicates that the increase in cell numbers post-treatment has a major impact on the increase in responsiveness.
a: Responses towards antigens and mitogens in healthy controls and patients before and after one year of natalizumab treatment. For visualization purposes, data are normalized to the average of the healthy controls for the respective antigens. Analysis performed with one-way ANOVA with Tukey´s post hoc test. * p<0.05, comparison between controls and pre-treatment patients. ¶ p<0.05, comparison between pre- and post-treatment patients. n=23 for controls, n=37 for both pre- and post-treatment groups. Bars show mean values, whiskers denote SEM. b-c: Fraction of activated lymphocytes in response to influenza (b) and CMV (c). Groups compared with Kruskall-Wallis test, utilizing Dunn´s post-hoc test. Median and interquartile range are shown. * p<0.05, ** p<0.01, *** p<0.005.
Furthermore, to evaluate the function on a cell-by-cell basis, the fraction of lymphoblasts responsive to stimuli (expressed as proportion (%) of lymphoblasts out of lymphocytes) revealed that the fraction of cells responding to Influenza antigen and CMV were lower in pre-treatment patients compared to controls (p<0.005 for Influenza, p<0.01 for CMV, Figure 6 b-c). The fractions of stimulated cells tended to increase in post-treatment compared with pre-treatment samples (p<0.05 for both Influenza and CMV, Figure 6 b-c), and post-treatment there was no difference between patient and controls. Thus, the increased responsiveness seen in patients post-treatment might in part be attributable to a component of increased per-cell responsiveness, in addition to increased lymphocyte cell numbers.
Lymphocyte population composition versus clinical variables
No associations were found between pre-treatment peripheral blood composition of major lymphocyte population numbers (total lymphocytes, T, B and NK cells, CD4+ and CD8+ cells) or subpopulation fractions of lymphocytes (CD3+CD56+ NKT, CD3-CD56bright and CD3-CD56dim NK cells, CD4dimCD25bright Treg cells, CD19+CD27+ memory B cells, CD19+CD25+ Breg cells) versus pre-treatment clinical data (disease duration, number of relapses last two years, MSSS) (data not shown). Furthermore, no associations were found between one-year change in different lymphocyte population numbers (total lymphocytes, CD3+, CD4+, CD8+, CD3-CD19+, CD3-CD56+) or subpopulation fractions of T cells (CD3+CD56+, CD3-CD56bright, CD3-CD56dim, CD4+CD25bright, CD19+CD27+, CD19+CD25+) versus number of relapses during one-year treatment (data not shown).
Discussion
In this one-year longitudinal observational study, by assessing changes in circulating lymphocyte compositions of 40 patients with relapsing MS treated with natalizumab, we demonstrated a significant increase in absolute numbers of all major populations, most markedly for NK cells and B cells, as well as restored CD4+ and CD8+ T cell responsiveness to recall antigens and mitogens.
An increase in numbers of circulating lymphocytes during natalizumab treatment corroborates with the natalizumab´s blocking effect on lymphocyte extravasation [5]. The parallel findings of a reduction in leukocyte counts and IgG index intrathecally also support the blocking effect of natalizumab on CNS cell-trafficking [6,7]. VLA-4 (α4β1) is widely expressed on many different lymphocyte populations including T cells, B cells, NK cells as well as on a majority of monocytes and macrophages. The interaction of VLA-4 and its ligands is not specific for the blood-brain barrier (BBB) since VCAM-1 is expressed on activated endothelium throughout the body [26]. Thus, the overall effect of VLA-4 interference on lymphocyte populations measured in blood is not only a result of reduced migration across the BBB but also across endothelium in other peripheral tissues. Furthermore, considering the low numbers of lymphocytes intrathecally compared with numbers in the periphery, it is unlikely that reduced migration to the CNS may account for the total increase in circulating lymphocytes during natalizumab treatment. In addition, it was found that natalizumab mobilizes hematopoietic progenitor cells out of the bone marrow [27]. Also, besides effects on cell migration, a co-stimulatory effect on VLA-4 by natalizumab, may also contribute to changes in circulating lymphocyte subsets [28].
VLA-4 expression varies between different lymphocyte populations, being higher on B cells than on T cells, and higher on CD8+ than on CD4+ T cells [13]. Furthermore, the amount of natalizumab binding to CD3- NK cells may be higher than the amount binding to CD19+ B cells and CD3+ T cells in a descendant scale [29]. This diversity in binding preference of natalizumab is well in line with our observation of the highest increase in the number of NK cells after treatment (195% increase compared with baseline), followed by B cells (105% increase compared with baseline) and T cells (73% increase compared with baseline).
NK cells are part of the innate immune system and have both cytotoxic and regulatory properties [30]. Even though NK cells were observed to have the most pronounced relative increase of all circulating lymphocytes, the fraction of regulatory NK cells (CD3- CD56bright) decreased with a concomitant increase in cytotoxic NK cells (CD3- CD56dim). Based on different expression of chemokine receptors and adhesion molecules, cytotoxic NK cells and regulatory NK cells have different migration preferences with CD56dim migrating to inflammatory sites while CD56bright preferentially home to secondary lymphoid organs [31]. Our novel finding of an increase in the fraction of cytotoxic NK cells in blood after treatment seems logic when considering these cells preference for homing to inflammatory sites but now sequestered in the circulation due to natalizumab. Since VCAM-1 is up-regulated at sites of inflammation, cytotoxic NK cells may be relatively more affected by the blocking effect on VLA-4 compared with regulatory NK cells.
The OX40-OX40L interaction has been ascribed an important role in promoting survival and clonal expansion of effector and memory T cells, regulating T cell-mediated cytokine production [32] and facilitating Th2 immune responses [33]. In the murine model of MS, experimental allergic encephalomyelitis (EAE), blocking the OX40-OX40L interaction ameliorated the disease [34]. We here report a significant decline in proportions of both CD4+OX40L+ and CD8+OX40L+ cells after natalizumab treatment, indicating an attenuation of effector T cell responses in the periphery. Since OX40-OX40L interactions favor Th2 immune responses [33], our result may also have implications on the Th1-Th2 balance systemically.
Absolute numbers of B cells also increased after treatment. Interestingly, the fractions of both memory B cells (CD19+CD27+) and presumed Breg cells (CD19+CD25+) [35] increased. In contrast to naïve B cells (CD19+CD27-), memory B cells secrete the pro-inflammatory cytokines tumor necrosis factor (TNF) and lymphotoxin (LT) upon stimulation [36], and Breg cells suppress CD4+ T cell proliferation and enhance Treg cell properties [37]. The increase was higher in memory B cells than in presumed Breg cells, which may have implications for B cell responses both in the periphery and in the CNS. The increase in the fraction of memory B cells is in accordance with recent reports where an increase in memory B cells was observed while the population of naïve B cells decreased [17,38]. The latter finding was suggested to depend on differences in α4-integrin expression between these two B cell subsets. Taken together, the marked increase in circulating B cells during natalizumab treatment is a consistent finding throughout many studies and further yields this lymphocyte population a probably essential role in treatment effects and side effects.
In addition to the profound changes in lymphocyte populations, we observed increased CD4+ and CD8+ T cell responses to recall antigens and mitogens in whole blood during treatment. Although different subpopulations of T cells showed some variations in responses to different antigens, the overall pattern was consistent with higher responses post-treatment. Prevention of immune cell entry into tissues by natalizumab may lead to an increase in the number of reactive memory cells in the circulation, in accordance with the observation by Börnsen et al. [16], for T cells and our present observation for B cells. Furthermore, the overall reduction in T cell responsiveness noted in pre-treatment MS patients compared with healthy controls, was restored by natalizumab treatment.
The FASCIA method that we used reckons both the number and function of cells, thus providing a measure of the total functional capacity, which indeed is of clinical relevance. A detailed analysis taking into account both total numbers of cells available in the sample and the proportion of cells responding to stimuli showed that the increase in responsiveness observed after natalizumab treatment to a large extent was explained by an increase in cell numbers but there was also an increase in function on a cell-by-cell basis. This finding is not in full agreement with the finding of Börnsen et al [16], since they found no functional difference between untreated and natalizumab-treated MS patients regarding responses to tetanus and MBP. This discrepancy may be explained by material selection, as for example the untreated group [16] comprised mainly early-phase MS patients. Although our finding of lowered T cell responsiveness in MS patients compared with controls was not included as an aim of the study, it is an interesting observation that is in line with some previous literature indicating a defect responsiveness in MS for example to anti-CD3 stimulation [39] to PWM [40] as well as to stimulation by viral antigens [40,41]. However, our finding of lowered responsiveness in MS patients compared to controls may also depend on treatment prior inclusion, since 30 patients out of 40 received immunomodulating treatment within four months before baseline.
In conclusion, our findings indicate a preserved or increased ability for immune responses systemically after one-year natalizumab treatment. However, since natalizumab reduces lymphocyte extravasation not only to the CNS, immune surveillance and responses in peripheral tissues may be insufficient, which should be accounted for in treatment considerations. The systemic increase in the major populations (NK cells more than B cells more than T cells, respectively) may be explained by expression levels of VLA-4 on these populations, thus reflecting the effect of natalizumab on cell trafficking. However, the differential effects on subsets of these populations, including markers of activation and co-stimulation, are unlikely to be explained by cell traffic effects alone, indicating additional effects of natalizumab involving also cell-signalling.
Supporting Information
Figure S1.
Absolute number of unstimulated cells after 7 days of culturing. Mean and SD values are shown. Differences shown mark comparisons between pre- and post-treatment patients, and for post-treatment patients and controls, respectively. All comparisons were made using one-way ANOVA with Tukey’s post-hoc test. No significant differences were observed when comparing pre-treatment patients and controls. **: p<0.01, ***: p<0.005.
https://doi.org/10.1371/journal.pone.0081685.s001
(TIF)
Acknowledgments
The staff at the Department of Neurology is acknowledged for their help in collecting samples and Carina Andersson, Karin Backteman, Maria Petersson and Christina Sandell at the Department of Clinical Immunology and Transfusion Medicine are acknowledged for performing the flow cytometry procedures. We also thank Petra Cassel at the Department of Clinical Immunology for help with sample logistics.
Author Contributions
Conceived and designed the experiments: JM ME MJ CD MV JE. Performed the experiments: ME JM. Analyzed the data: JM ME JE. Contributed reagents/materials/analysis tools: MJ CD MV JE. Wrote the manuscript: JM ME JE.
References
- 1. Fletcher JM, Lalor SJ, Sweeney CM, Tubridy N, Mills KH (2010) T cells in multiple sclerosis and experimental autoimmune encephalomyelitis. Clin Exp Immunol 162: 1-11. doi:https://doi.org/10.1111/j.1365-2249.2010.04143.x. PubMed: 20682002.
- 2. Disanto G, Morahan JM, Barnett MH, Giovannoni G, Ramagopalan SV (2012) The evidence for a role of B cells in multiple sclerosis. Neurology 78: 823-832. doi:https://doi.org/10.1212/WNL.0b013e318249f6f0. PubMed: 22411958.
- 3. Knippenberg S, Peelen E, Smolders J, Thewissen M, Menheere P et al. (2011) Reduction in IL-10 producing B cells (Breg) in multiple sclerosis is accompanied by a reduced naive/memory Breg ratio during a relapse but not in remission. J Neuroimmunol 239: 80-86. doi:https://doi.org/10.1016/j.jneuroim.2011.08.019. PubMed: 21940055.
- 4. Gandhi R, Laroni A, Weiner HL (2010) Role of the innate immune system in the pathogenesis of multiple sclerosis. J Neuroimmunol 221: 7-14. doi:https://doi.org/10.1016/j.jneuroim.2009.10.015. PubMed: 19931190.
- 5. Rice GP, Hartung HP, Calabresi PA (2005) Anti-alpha4 integrin therapy for multiple sclerosis: mechanisms and rationale. Neurology 64: 1336-1342. doi:https://doi.org/10.1212/01.WNL.0000158329.30470.D0. PubMed: 15851719.
- 6. Stüve O, Marra CM, Jerome KR, Cook L, Cravens PD et al. (2006) Immune surveillance in multiple sclerosis patients treated with natalizumab. Ann Neurol 59: 743-747. doi:https://doi.org/10.1002/ana.20858. PubMed: 16634029.
- 7. Mellergård J, Edström M, Vrethem M, Ernerudh J, Dahle C (2010) Natalizumab treatment in multiple sclerosis: marked decline of chemokines and cytokines in cerebrospinal fluid. Mult Scler 16: 208-217. doi:https://doi.org/10.1177/1352458509355068. PubMed: 20007431.
- 8. Khademi M, Bornsen L, Rafatnia F, Andersson M, Brundin L et al. (2009) The effects of natalizumab on inflammatory mediators in multiple sclerosis: prospects for treatment-sensitive biomarkers. Eur J Neurol 16: 528-536. doi:https://doi.org/10.1111/j.1468-1331.2009.02532.x. PubMed: 19220425.
- 9. Polman CH, O'Connor PW, Havrdova E, Hutchinson M, Kappos L et al. (2006) A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N Engl J Med 354: 899-910. doi:https://doi.org/10.1056/NEJMoa044397. PubMed: 16510744.
- 10. Skarica M, Eckstein C, Whartenby KA, Calabresi PA (2011) Novel mechanisms of immune modulation of natalizumab in multiple sclerosis patients. J Neuroimmunol 235: 70-76. doi:https://doi.org/10.1016/j.jneuroim.2011.02.010. PubMed: 21550672.
- 11. Krumbholz M, Meinl I, Kümpfel T, Hohlfeld R, Meinl E (2008) Natalizumab disproportionately increases circulating pre-B and B cells in multiple sclerosis. Neurology 71: 1350-1354. doi:https://doi.org/10.1212/01.wnl.0000327671.91357.96. PubMed: 18936427.
- 12. Kivisäkk P, Healy BC, Viglietta V, Quintana FJ, Hootstein MA et al. (2009) Natalizumab treatment is associated with peripheral sequestration of proinflammatory T cells. Neurology 72: 1922-1930. doi:https://doi.org/10.1212/WNL.0b013e3181a8266f. PubMed: 19487650.
- 13. Niino M, Bodner C, Simard ML, Alatab S, Gano D et al. (2006) Natalizumab effects on immune cell responses in multiple sclerosis. Ann Neurol 59: 748-754. doi:https://doi.org/10.1002/ana.20859. PubMed: 16634035.
- 14. Sato T, Tachibana K, Nojima Y, D'Avirro N, Morimoto C (1995) Role of the VLA-4 molecule in T cell costimulation. Identification of the tyrosine phosphorylation pattern induced by the ligation of VLA-4. J Immunol 155: 2938-2947. PubMed: 7673711.
- 15. Stüve O, Marra CM, Bar-Or A, Niino M, Cravens PD et al. (2006) Altered CD4+/CD8+ T-cell ratios in cerebrospinal fluid of natalizumab-treated patients with multiple sclerosis. Arch Neurol 63: 1383-1387. doi:https://doi.org/10.1001/archneur.63.10.1383. PubMed: 17030653.
- 16. Börnsen L, Christensen JR, Ratzer R, Oturai AB, Sørensen PS et al. (2012) Effect of Natalizumab on Circulating CD4(+) T-Cells in Multiple Sclerosis. PLOS ONE 7: e47578. doi:https://doi.org/10.1371/journal.pone.0047578. PubMed: 23226199.
- 17. Planas R, Jelčić I, Schippling S, Martin R, Sospedra M (2012) Natalizumab treatment perturbs memory- and marginal zone-like B-cell homing in secondary lymphoid organs in multiple sclerosis. Eur J Immunol 42: 790-798. doi:https://doi.org/10.1002/eji.201142108. PubMed: 22144343.
- 18. Stenner MP, Waschbisch A, Buck D, Doerck S, Einsele H et al. (2008) Effects of natalizumab treatment on Foxp3+ T regulatory cells. PLOS ONE 3: e3319. doi:https://doi.org/10.1371/journal.pone.0003319. PubMed: 18836525.
- 19. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP et al. (2001) Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 50: 121-127. doi:https://doi.org/10.1002/ana.1032. PubMed: 11456302.
- 20. Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33: 1444-1452. doi:https://doi.org/10.1212/WNL.33.11.1444. PubMed: 6685237.
- 21. Roxburgh RH, Seaman SR, Masterman T, Hensiek AE, Sawcer SJ et al. (2005) Multiple Sclerosis Severity Score: using disability and disease duration to rate disease severity. Neurology 64: 1144-1151. doi:https://doi.org/10.1212/01.WNL.0000156155.19270.F8. PubMed: 15824338.
- 22. Smith A (1991) Los Angeles: Western. Psychological Services.
- 23. Hobart J, Lamping D, Fitzpatrick R, Riazi A, Thompson A (2001) The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure. Brain 124: 962-973. doi:https://doi.org/10.1093/brain/124.5.962. PubMed: 11335698.
- 24. Mjösberg J, Svensson J, Johansson E, Hellström L, Casas R et al. (2009) Systemic reduction of functionally suppressive CD4dimCD25highFoxp3+ Tregs in human second trimester pregnancy is induced by progesterone and 17beta-estradiol. J Immunol 183: 759-769. doi:https://doi.org/10.4049/jimmunol.0803654. PubMed: 19535629.
- 25. Svahn A, Linde A, Thorstensson R, Karlén K, Andersson L et al. (2003) Development and evaluation of a flow-cytometric assay of specific cell-mediated immune response in activated whole blood for the detection of cell-mediated immunity against varicella-zoster virus. J Immunol Methods 277: 17-25. doi:https://doi.org/10.1016/S0022-1759(03)00111-X. PubMed: 12799036.
- 26. McMurray RW (1996) Adhesion molecules in autoimmune disease. Semin Arthritis Rheum 25: 215-233. doi:https://doi.org/10.1016/S0049-0172(96)80034-5. PubMed: 8834012.
- 27. Zohren F, Toutzaris D, Klärner V, Hartung HP, Kieseier B et al. (2008) The monoclonal anti-VLA-4 antibody natalizumab mobilizes CD34+ hematopoietic progenitor cells in humans. Blood 111: 3893-3895. doi:https://doi.org/10.1182/blood-2007-10-120329. PubMed: 18235044.
- 28. Mittelbrunn M, Molina A, Escribese MM, Yáñez-Mó M, Escudero E et al. (2004) VLA-4 integrin concentrates at the peripheral supramolecular activation complex of the immune synapse and drives T helper 1 responses. Proc Natl Acad Sci U S A 101: 11058-11063. doi:https://doi.org/10.1073/pnas.0307927101. PubMed: 15263094.
- 29. Harrer A, Pilz G, Einhaeupl M, Oppermann K, Hitzl W et al. (2012) Lymphocyte subsets show different response patterns to in vivo bound natalizumab--a flow cytometric study on patients with multiple sclerosis. PLOS ONE 7: e31784. doi:https://doi.org/10.1371/journal.pone.0031784. PubMed: 22363732.
- 30. Moretta A, Marcenaro E, Parolini S, Ferlazzo G, Moretta L (2008) NK cells at the interface between innate and adaptive immunity. Cell Death Differ 15: 226-233. doi:https://doi.org/10.1038/sj.cdd.4402170. PubMed: 17541426.
- 31. Campbell JJ, Qin S, Unutmaz D, Soler D, Murphy KE et al. (2001) Unique subpopulations of CD56+ NK and NK-T peripheral blood lymphocytes identified by chemokine receptor expression repertoire. J Immunol 166: 6477-6482. PubMed: 11359797.
- 32. Croft M, So T, Duan W, Soroosh P (2009) The significance of OX40 and OX40L to T-cell biology and immune disease. Immunol Rev 229: 173-191. doi:https://doi.org/10.1111/j.1600-065X.2009.00766.x. PubMed: 19426222.
- 33. Ohshima Y, Yang LP, Uchiyama T, Tanaka Y, Baum P et al. (1998) OX40 costimulation enhances interleukin-4 (IL-4) expression at priming and promotes the differentiation of naive human CD4(+) T cells into high IL-4-producing effectors. Blood 92: 3338-3345. PubMed: 9787171.
- 34. Weinberg AD, Wegmann KW, Funatake C, Whitham RH (1999) Blocking OX-40/OX-40 ligand interaction in vitro and in vivo leads to decreased T cell function and amelioration of experimental allergic encephalomyelitis. J Immunol 162: 1818-1826. PubMed: 9973447.
- 35. Brisslert M, Bokarewa M, Larsson P, Wing K, Collins LV et al. (2006) Phenotypic and functional characterization of human CD25+ B cells. Immunology 117: 548-557. doi:https://doi.org/10.1111/j.1365-2567.2006.02331.x. PubMed: 16556269.
- 36. Duddy M, Niino M, Adatia F, Hebert S, Freedman M et al. (2007) Distinct effector cytokine profiles of memory and naive human B cell subsets and implication in multiple sclerosis. J Immunol 178: 6092-6099. PubMed: 17475834.
- 37. Kessel A, Haj T, Peri R, Snir A, Melamed D et al. (2012) Human CD19(+)CD25(high) B regulatory cells suppress proliferation of CD4(+) T cells and enhance Foxp3 and CTLA-4 expression in T-regulatory cells. Autoimmun Rev 11: 670-677. doi:https://doi.org/10.1016/j.autrev.2011.11.018. PubMed: 22155204.
- 38. Haas J, Bekeredjian-Ding I, Milkova M, Balint B, Schwarz A et al. (2011) B cells undergo unique compartmentalized redistribution in multiple sclerosis. J Autoimmun 37: 289-299. doi:https://doi.org/10.1016/j.jaut.2011.08.003. PubMed: 21924866.
- 39. Brod SA, Scott M (1994) Defective CD3 mediated proliferation and LPS responsiveness in multiple sclerosis. Autoimmunity 17: 143-148. doi:https://doi.org/10.3109/08916939409014669. PubMed: 7520286.
- 40. Walker JE, Cook JD (1979) Lymphoblastic transformation in response to viral antigens in multiple sclerosis. Neurology 29: 1341-1347. doi:https://doi.org/10.1212/WNL.29.10.1341. PubMed: 225695.
- 41. Ilonen J, Reunanen M, Salmi A, Tiilikainen A (1981) Lymphocyte blast transformation responses and viral antibodies in relation to HLA antigens in multiple sclerosis. J Neurol Sci 49: 117-133. doi:https://doi.org/10.1016/0022-510X(81)90194-5. PubMed: 6259296.