In multiple sclerosis (MS), B cell–depleting therapy using monoclonal anti-CD20 Abs, including rituximab (RTX) and ocrelizumab, effectively reduces disease activity. Based on indirect evidence, it is generally believed that elimination of the Ag-presenting capabilities and Ag nonspecific immune functions of B cells underlie the therapeutic efficacy. However, a small subset of T lymphocytes (T cells) was shown to also express CD20, but controversy prevails surrounding the true existence of this T cell subpopulation. Using single-cell imaging flow cytometry and expression profiling of sorted lymphocyte subsets, we unequivocally demonstrate the existence of CD3+CD20dim T cells. We show that in MS patients, increased levels of CD3+CD20dim T cells are effectively depleted by RTX. The pathological relevance of this T cell subset in MS remains to be determined. However, given their potential proinflammatory functionality, depletion of CD20-expressing T cells may also contribute to the therapeutic effect of RTX and other mAbs targeting CD20.

Ever since the first phase II clinical trials demonstrated rapid and sustained reduction of inflammatory disease activity following a single course of rituximab (RTX) treatment (1, 2), B cell depletion has emerged as a highly promising therapeutic approach in multiple sclerosis (MS). RTX is a chimeric monoclonal anti-CD20 Ab of the IgG1 isotype that triggers rapid complement and NK cell–mediated depletion of CD20-expressing B cells (3). B cell depletion using RTX does not affect the CD19+CD20 pro–B cell and CD20CD138+ plasma cell populations, and within 6–8 mo following RTX treatment, the CD20+ B cell compartment begins to replenish (4), mainly composed of naive B cells (4). B cells of the CD27+ memory phenotype remain at significantly lower levels in peripheral blood, often times beyond 12 mo, possibly accounting for a long-lasting beneficial effect of anti-CD20 therapies on MS disease activity that is sustained following repletion of circulating B cells (5).

Low percentages of CD20-expressing T cells in human blood were first described in 1993 (6), but the existence of this rather rare T cell subset has been disputed (7). Others have found that CD20-expressing T cells can exhibit proinflammatory capacity (8, 9). In rheumatoid arthritis (RA), CD20+ T cells make up a larger percentage of Th17 cells when compared with healthy individuals (9). However, the overall percentage of CD20+ T cells among all T cells does not differ between RA patients and healthy individuals, and the pathological relevance, if any, of CD20+ T cells in autoimmune diseases remains entirely unknown. Almost expectedly, during clinical trials in RA, it was noted that CD3+ T cells expressing low levels of CD20 are depleted by RTX (4).

In this study, we were interested in unequivocally demonstrating the existence of CD20+CD3+ cells and determining if these cells indeed belong to a T cell lineage. Furthermore, we sought to evaluate whether CD3+CD20+ cells were differentially present in the peripheral blood of MS patients compared with healthy donors and to determine their level of depletion in response to RTX treatment in MS patients. To address these questions, we performed extensive flow cytometric phenotypic characterization of B and T lymphocytes and gene expression profiling of CD20 T cells, B cells, and CD20+ T cells, from peripheral blood of healthy control subjects (HC), untreated (UNT) MS patients, and MS patients at different time points following RTX treatment.

Peripheral blood was obtained from patients with a confirmed diagnosis of MS who were UNT or had received standard-dose RTX therapy (two infusions of 1 g i.v. each, 2 wk apart) at different time points prior to sample acquisition or from healthy donors (see Table I for sample details). PBMCs were prepared using a Ficoll paque density gradient following standard protocols. These studies were approved by the University of California, San Francisco Committee on Human Research.

Table I.
Samples and experiments
Identification No. DxTherapySexAge (y)B Cell SubsetsT Cell SubsetsCD3 CD20ImageStreamMicroarray
13311d HC NA 43   
13411e HC NA 40    
27112a HC NA 33     
28112a HC NA 40     
29312a HC NA 27     
29412a HC NA 37     
29512a HC NA 22     
29812a HC NA 34  
30212a HC NA 21     
36613a HC NA 37    
36813a HC NA 26    
36913a HC NA 23    
41113a HC NA 51    
42113a HC NA 64    
47913a HC NA 62     
48313a HC NA 38   
49413a HC NA 21    
50013a HC NA 45    
50613a HC NA 53    
33112a RRMS UNT 41  
46413b RRMS UNT 44  
47413b PPMS UNT 44   
47713a RRMS UNT 25  
48413a CIS UNT 47   
48613a RRMS UNT 48   
48713a RRMS UNT 20     
48813b RRMS UNT 42   
49013a RRMS UNT 31    
49913a RRMS UNT 45    
50513a RRMS UNT 61    
50913a CIS UNT 51    
35012a PPMS RTX 0-12 w 53    
39713a PPMS RTX 0-12 w 63    
40813a SPMS RTX 0-12 w 53    
45713a RRMS RTX 0-12 w 36    
46613a RRMS RTX 0-12 w 39    
48113a SPMS RTX 0-12 w 71    
48213a RRMS RTX 0-12 w 54    
11911a SPMS RTX 13-24 w 59     
17212b PPMS RTX 13-24 w 38    
35112a SPMS RTX 13-24 w 39    
35913a PPMS RTX 13-24 w 57    
39013a SPMS RTX 13-24 w 43    
39813a PPMS RTX 13-24 w 49    
40413a SPMS RTX 13-24 w 64    
40513a PRMS RTX 13-24 w 68    
48513a RRMS RTX 13-24 w 34     
6211b SPMS RTX 25-36 w 47    
11611a SPMS RTX 25-36 w 59     
35813a PPMS RTX 25-36 w 42    
36313a PPMS RTX 25-36 w 62    
40613a RRMS RTX 25-36 w 49    
34812a PRMS RTX 37-52 w 48    
35212a SPMS RTX 37-52 w 70    
35713a RRMS RTX 37-52 w 53    
36513a SPMS RTX 37-52 w 51    
38713a PPMS RTX 37-52 w 43    
Identification No. DxTherapySexAge (y)B Cell SubsetsT Cell SubsetsCD3 CD20ImageStreamMicroarray
13311d HC NA 43   
13411e HC NA 40    
27112a HC NA 33     
28112a HC NA 40     
29312a HC NA 27     
29412a HC NA 37     
29512a HC NA 22     
29812a HC NA 34  
30212a HC NA 21     
36613a HC NA 37    
36813a HC NA 26    
36913a HC NA 23    
41113a HC NA 51    
42113a HC NA 64    
47913a HC NA 62     
48313a HC NA 38   
49413a HC NA 21    
50013a HC NA 45    
50613a HC NA 53    
33112a RRMS UNT 41  
46413b RRMS UNT 44  
47413b PPMS UNT 44   
47713a RRMS UNT 25  
48413a CIS UNT 47   
48613a RRMS UNT 48   
48713a RRMS UNT 20     
48813b RRMS UNT 42   
49013a RRMS UNT 31    
49913a RRMS UNT 45    
50513a RRMS UNT 61    
50913a CIS UNT 51    
35012a PPMS RTX 0-12 w 53    
39713a PPMS RTX 0-12 w 63    
40813a SPMS RTX 0-12 w 53    
45713a RRMS RTX 0-12 w 36    
46613a RRMS RTX 0-12 w 39    
48113a SPMS RTX 0-12 w 71    
48213a RRMS RTX 0-12 w 54    
11911a SPMS RTX 13-24 w 59     
17212b PPMS RTX 13-24 w 38    
35112a SPMS RTX 13-24 w 39    
35913a PPMS RTX 13-24 w 57    
39013a SPMS RTX 13-24 w 43    
39813a PPMS RTX 13-24 w 49    
40413a SPMS RTX 13-24 w 64    
40513a PRMS RTX 13-24 w 68    
48513a RRMS RTX 13-24 w 34     
6211b SPMS RTX 25-36 w 47    
11611a SPMS RTX 25-36 w 59     
35813a PPMS RTX 25-36 w 42    
36313a PPMS RTX 25-36 w 62    
40613a RRMS RTX 25-36 w 49    
34812a PRMS RTX 37-52 w 48    
35212a SPMS RTX 37-52 w 70    
35713a RRMS RTX 37-52 w 53    
36513a SPMS RTX 37-52 w 51    
38713a PPMS RTX 37-52 w 43    

Shown are patient identification numbers, diagnosis (Dx), treatment, age, sex, and experiments performed per sample.

B cell subsets, multicolor B cell subset panel; CD3CD20, additional samples studied using limited flow cytometry panel; F, female; ImageStream: samples used for single-cell flow cytometry imaging; M, male; Microarray, samples used for expression profiling using Affymetrix GeneChip2.0; T cell subsets, multicolor T cell subset panel.

Phenotypic analysis of B and T cells was performed using multicolor FACS; see Table I for experiments performed per sample. PBMC were resuspended in PBS/1% BSA, and FcR blocking was performed using mouse serum (The Jackson Laboratory). For B cell analyses, cells were stained with pretitrated volumes of fluorescent-labeled Abs: CD19 (allophycocyanin-Cy7), IgD (PE Cy7), CD27 (Qdot 605), CD24 (PE Alexa 610), CD38 (PerCP Cy5.5), IgM (PE Cy5), IgG (allophycocyanin), CD20 (FITC), CD138 (PE), and CD3 (Pacific Blue). DAPI was added to discriminate dying/dead cells; samples were analyzed on a four-laser FACSAria III (BD Biosciences). CD19+ B cells were gated from singlet lymphocytes after exclusion of CD3+ T cell and dead cells (DAPI+). T cell subsets were separately stained using the following Abs: CD3 (allophycocyanin), CD4 (PerCP Cy5.5), CD8 (allophycocyanin–Alexa Fluor 750), CD20 (FITC), CD27 (Qdot 605), CCR7 (PE), and CD45RA (PE Cy5). CD3+ T cells were identified on singlet lymphocytes and further divided into subsets. The CD20 cutoff for negative versus positive was determined by using fluorescence-minus-one control.

PBMC were stained with anti-CD20 FITC (Beckman Coulter), anti-CD19 PE (Beckman Coulter), and anti-CD3 allophycocyanin (Beckman Coulter); dead cells were labeled with DAPI (Invitrogen). Cytometry gating was performed first on lymphocytes, then live cells (DAPI-negative), then on either CD19+ or CD3+, and lastly on CD20+ among CD19+ or CD3+ cells.

PBMC were stained with Abs against CD3, CD19, and CD20; three populations of lymphocytes were sorted on a MoFlo Astrios (Beckman Coulter) directly into RLT lysis buffer (Qiagen): 1) CD19+CD20+; 2) CD3+CD20; and 3) CD3+CD19CD20+. Immediately after sorting, cells were frozen in RLT buffer at −80°C. RNA was extracted using the Qiagen micro RNA kit with DNAse treatment (Qiagen). RNA concentrations were measured using a UV spectrophotometer (Nanodrop), and RNA quality was assessed using Pico-RNA chips (Agilent 2100 Bioanalyzer; Agilent Technologies). Microarray hybridizations were performed at the University of California, San Francisco–affiliated Gladstone Institutes’ Genomics Core Facility. The NuGEN Pico V2 kit (NuGEN) was used for cDNA amplification, fragmentation, and biotinylation; biotinylated cDNA was hybridized to Human GeneChipR Gene 2.0 ST microarrays (Affymetrix). The signal intensity fluorescent images were read using the Affymetrix Model 3000 Scanner (Affymetrix) and converted into GeneChip probe results files (CEL). Microarray data were analyzed using the statistical programming language R/Bioconductor. Quality of the analyzed arrays was ascertained using the arrayQualityMetrics package (10). Raw data were processed using the rma function in the "oligo” package (11). Log2-transformed data were filtered for variance using the “genefilter” package (keeping only probes showing a difference between the 10 and 90% quantiles of >1). Hierarchical clustering was performed using the heatmap.2 function of the “gplots” package.

Statistical analyses were performed using GraphPad Prism 6.0 (GraphPad). Statistical methods are indicated in the text and figure legends where applicable.

We studied T cell and B cell subsets in HC and treatment-naive MS patients (Table I). In all subjects (HC and MS), we found CD3+ T cells coexpressing low levels of CD20 (Fig. 1A), generally representing <10% of total CD3+ cells (Fig. 1B). Given their potentially proinflammatory function (9), we sought to determine if the frequency of CD3+CD20dim T cells in peripheral blood was increased in MS; indeed, the frequency of CD3+CD20dim among all CD3+ T cells was modestly higher in MS (7.2 ± 3.6%, mean ± SD; n = 11) compared with 5.4 ± 2.4% (mean ± SD) in HC (n = 18) (p = 0.02, one-tailed t test) (Fig. 1B). To clearly define the lymphocyte lineage of CD3+CD20dim cells, we performed fluorescent flow cytometry imaging (Amnis ImageStream) on HC (n = 3) and treatment-naive MS patients (n = 3), unequivocally revealing CD3 and CD20 expression at the single-cell level (Fig. 1C); >100 CD3+CD20dim T cells were imaged for this experiment (not shown). Lack of expression of CD19 on these cells confirms that they do not belong to a canonical B cell phenotype (Fig. 1C). Transcription profiling and hierarchical clustering of sorted CD3+CD20, CD19+CD20+, and CD3+CD20dim cells from HC (n = 2) further confirmed the T cell lineage of CD3+CD20dim population (Fig. 1D); they express both α/β- and γ/δ-TCRs as indicated by increased expression of TCRα constant chain and TCRγ constant chain (Fig. 1E) compared with B cells. CD20+ T cells expressed lower levels of CD20 compared with CD19+ B cells (Fig. 1E), hence their designation as CD3+CD20dim T cells.

FIGURE 1.

CD3+CD20dim cells belong to the T cell lineage and are increased in MS versus HC. (A) Flow cytometry gating strategy to identify CD19CD3+CD20dim cells. (B) Percentages of CD3+CD20dim T cells of total CD3+ T cells in HC (n = 18) and UNT MS (n = 11); p = 0.03, one-tailed t test. (C) ImageStream single-cell flow cytometry imaging of the cell types indicated on the left. Each image per row shows the same cells as visible in the “BF” column; DAPI, marker for apoptotic (dead) cells; CD20, FITC-labeled anti-CD20 Ab; CD19, PE-labeled anti-CD19 Ab; BF, brightfield image; and CD3, allophycocyanin-labeled anti-CD3 Ab. (D) Unsupervised hierarchical clustering of different cell types (B cells: CD19+CD20+; T cells: CD3+CD20, CD3+CD20dim T cells) from two healthy donors according to the expression of variance filtered transcripts. The columns are different genes; the rows reflect different samples. Blue depicts low and yellow high expression. The expression profiles of CD3+CD20dim cells and CD3+ T cells are more similar to each other than to the profile of B cells, hence T cell subtypes cluster together. (E) Radar-graph representation of microarray expression levels of indicated transcripts. Note that CD3+CD20dim cells have intermediate levels of CD20 transcripts and that, overall, CD3+CD20dim T cells overlap with CD3+ T cells; both types of T cells have transcripts for CD4 and CD8, TCR α-chain (TRAC), and γ-chain (TRGC2).

FIGURE 1.

CD3+CD20dim cells belong to the T cell lineage and are increased in MS versus HC. (A) Flow cytometry gating strategy to identify CD19CD3+CD20dim cells. (B) Percentages of CD3+CD20dim T cells of total CD3+ T cells in HC (n = 18) and UNT MS (n = 11); p = 0.03, one-tailed t test. (C) ImageStream single-cell flow cytometry imaging of the cell types indicated on the left. Each image per row shows the same cells as visible in the “BF” column; DAPI, marker for apoptotic (dead) cells; CD20, FITC-labeled anti-CD20 Ab; CD19, PE-labeled anti-CD19 Ab; BF, brightfield image; and CD3, allophycocyanin-labeled anti-CD3 Ab. (D) Unsupervised hierarchical clustering of different cell types (B cells: CD19+CD20+; T cells: CD3+CD20, CD3+CD20dim T cells) from two healthy donors according to the expression of variance filtered transcripts. The columns are different genes; the rows reflect different samples. Blue depicts low and yellow high expression. The expression profiles of CD3+CD20dim cells and CD3+ T cells are more similar to each other than to the profile of B cells, hence T cell subtypes cluster together. (E) Radar-graph representation of microarray expression levels of indicated transcripts. Note that CD3+CD20dim cells have intermediate levels of CD20 transcripts and that, overall, CD3+CD20dim T cells overlap with CD3+ T cells; both types of T cells have transcripts for CD4 and CD8, TCR α-chain (TRAC), and γ-chain (TRGC2).

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Extensive flow cytometry immunophenotyping of T cells was performed using PBMC from MS patients (n = 10) and HC (n = 12). The CD3+CD20dim population comprised both CD4+ helper and CD8+ cytotoxic subsets (Fig. 2A). Interestingly, among CD3+CD20dim T cells, CD8+ were modestly increased in MS patients (60.3 ± 14.7%) compared with HC (48 ± 15%) (p = 0.03, one-tailed t test) (Fig. 2B); no significant difference was found between MS and HC in the percentages of CD4+ among CD3+CD20dim T cells (42.7 ± 15.7% in HC versus 36 ± 15.6% in MS; p = 0.17, one-tailed t test) (Fig. 2B) or of CD4+ or CD8+ total CD3+ T cells (Supplemental Fig. 1).

FIGURE 2.

In MS, CD8+ T cells are increased among CD3+CD20dim T cells. Shown are CD3+CD20dim T cell gating strategy (A) and scatter plots (B; mean and 95% CI) of CD4+ and CD8+ cells among CD3+CD20dim T cells in UNT MS patients (MS) and HC. Comparisons between MS and HC were made using one-sided t test.

FIGURE 2.

In MS, CD8+ T cells are increased among CD3+CD20dim T cells. Shown are CD3+CD20dim T cell gating strategy (A) and scatter plots (B; mean and 95% CI) of CD4+ and CD8+ cells among CD3+CD20dim T cells in UNT MS patients (MS) and HC. Comparisons between MS and HC were made using one-sided t test.

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CD3+CD20dim T cells also express CD27, CCR7, and CD45RA (Fig. 3A) in different combinations, highlighting the developmental diversity contained within this T cell subset. We evaluated a number of defined subpopulations among CD3+CD20dim T cells; in UNT MS patients the following distribution was found: CD45RA+CCR7+ naive T cells (28.3 ± 12.3%); CD45RACCR7+ central memory T cells (28.8 ± 13.4%); CD45RACCR7 effector memory T cells (16.8 ± 8.6%), and CD45RA+CCR7 RA+ memory T cells (27.5 ± 12.1%) (not shown). There was no significant difference between MS and HC for any of these CD3+CD20dim T cell subsets (not shown). Lastly, surface markers commonly found on B cells (CD19, HLADR, CD24, CD38, CD138, IgD, IgM, and IgG) were not observed on CD3+CD20dim T cells (Fig. 3B).

FIGURE 3.

CD3+CD20dim T cells express typical T cell surface markers but not B cell markers. Phenotypes of CD3+CD20dim T cells were compared with CD3+CD4+CD20 and CD3+CD8+CD20 T cells (A), and naive CD19+CD20+CD27 B cells and memory CD19+CD20+CD27 B cells (B) using the indicated surface markers. Shown are FACS histograms of the indicated markers on lymphocytes gated on T and B cell subsets.

FIGURE 3.

CD3+CD20dim T cells express typical T cell surface markers but not B cell markers. Phenotypes of CD3+CD20dim T cells were compared with CD3+CD4+CD20 and CD3+CD8+CD20 T cells (A), and naive CD19+CD20+CD27 B cells and memory CD19+CD20+CD27 B cells (B) using the indicated surface markers. Shown are FACS histograms of the indicated markers on lymphocytes gated on T and B cell subsets.

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To study the effect of RTX on CD3+CD20dim T cells and other lymphocyte subsets, we collected PBMC from cross-sectional cohorts of UNT MS patients and compared lymphocyte subsets to their distribution in RTX-treated patients at different time points: 1–12 wk post-RTX treatment (n = 7); 13–24 wk post-RTX (n = 8); 25–36 wk post-RTX (n = 5); and 37–52 wk post-RTX (n = 5). We found near-complete depletion of CD3+CD20dim T cells during weeks 1–12, with mean frequencies of 0.36% (± 0.36) compared with 7.8% (± 3.7) in UNT patients; during weeks 25–36 and weeks 57–52, partial repletion of CD3+CD20dim T cells was observed, with values of 2.7% (± 2.3) and 2.8% (± 1.5), respectively (Fig. 4A). Apart from a slightly increased proportion of overall CD3+ T cells during weeks 13–24, no significant effect of RTX on the overall CD3+ T cell compartment was present (Fig. 4B), suggesting that following depletion of CD3+CD20dim T cells by RTX, there was rapid homeostatic repopulation with CD20 T cells. A typical representation of the depletion and gradual repopulation of CD3+CD20dim T cells is depicted in Supplemental Fig. 2. As also observed for B cells, very small numbers of CD3+CD20dim T cells remained detectable in PBMC even during RTX treatment (Fig. 4A). Interestingly, the nondepleted CD3+CD20dim T cells that remained in the circulation 1–12 wk following RTX infusion were predominantly comprised of CD4+ T cells (Fig. 4C). In contrast, the overall distribution of CD3+CD4+ and CD3+CD8+ T cells remained unchanged at all time points following RTX therapy (Fig. 4D).

FIGURE 4.

CD3+CD20dim T cells are effectively depleted from peripheral blood of MS patients. Shown are scatter plots (mean and 95% CI) for CD3+CD20dim T cells as percentages of CD3+ T cells (A), CD3+ T cells as percentages of lymphocytes (B), and of CD4+ and CD8+ cells among CD3+CD20dim (C) and all CD3+ (D) T cells at different time points after RTX treatment (UNT; indicated weeks after treatment). RTX almost completely depletes CD3+CD20dim T cells (A) but has only a small effect on the overall CD3+ T cell compartment (B); RTX leads to significantly higher depletion of CD8+ than CD4+ cells among CD3+CD20dim T cells (C) but not among overall CD3+ T cells. Comparisons between UNT samples and cohorts at different time points after RTX treatment were made using Kruskal–Wallis test; significance levels are: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

FIGURE 4.

CD3+CD20dim T cells are effectively depleted from peripheral blood of MS patients. Shown are scatter plots (mean and 95% CI) for CD3+CD20dim T cells as percentages of CD3+ T cells (A), CD3+ T cells as percentages of lymphocytes (B), and of CD4+ and CD8+ cells among CD3+CD20dim (C) and all CD3+ (D) T cells at different time points after RTX treatment (UNT; indicated weeks after treatment). RTX almost completely depletes CD3+CD20dim T cells (A) but has only a small effect on the overall CD3+ T cell compartment (B); RTX leads to significantly higher depletion of CD8+ than CD4+ cells among CD3+CD20dim T cells (C) but not among overall CD3+ T cells. Comparisons between UNT samples and cohorts at different time points after RTX treatment were made using Kruskal–Wallis test; significance levels are: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

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We were also interested in determining the response of CD19+ B cells (Fig. 5A), CD19+CD20+ B cells (Fig. 5B), and other B cell subpopulations (Fig. 6) to RTX treatment in our patient cohort. Representative flow cytometry plots and gating strategies for B cell subpopulation analysis are shown in Supplemental Fig. 3. In the UNT MS group, the overall CD19+ B cell fraction ranged between 4.2 and 11.6% of lymphocytes (8.9 ± 2.8%) (Fig. 5A). As expected (4), RTX induced near-complete depletion of CD19+ and CD19+CD20+ B cells with replenishment during weeks 25–36 (Fig. 5A, 5B); the majority of B cells in replenishing repertoires were composed of Ag-inexperienced IgD+CD27 naive and transitional B cell subsets, suggesting influx from CD20 pro–B cells (Fig. 6A). Memory B cell populations and IgDCD27 B cells remained depleted for significantly longer and were low even during weeks 37–52 (Fig. 6A, 6B). We found small percentages of residual B cells at every time point after RTX treatment; interestingly, in the 1–12 wk cohort, the residual B cell compartment was almost entirely composed of IgDCD27 (i.e., double-negative [DN]) B cells (Fig. 6B). We also found that the percentage of CD19+CD27hiCD38hi plasma cells/plasmablasts (PC) was significantly reduced by RTX during weeks 1–12 and 13–24 (Fig. 6B). Among CD19+ cells, PC did not show significant changes in either cohort, but trended toward making up higher numbers among residual CD19+ cells (Fig. 6B).

FIGURE 5.

RTX efficiently depletes the B cell compartment. Shown are CD19+ B cells relative to all lymphocytes (% Lymphocytes) (A) and CD19+CD20+ B cells as percentages of CD19+ B cells (B) at the indicated time points. In UNT patients, 8.9 ± 2.8% (mean ± SD) of lymphocyte are B cells (A), virtually all of which are CD20+ (B). B cells are efficiently depleted by RTX, with replenishment beginning 25–36 wk after treatment. Comparisons between UNT samples and cohorts at different time points after RTX treatment were made using the Kruskal–Wallis test; significance levels are: **p < 0.01, ***p < 0.001, ****p < 0.0001.

FIGURE 5.

RTX efficiently depletes the B cell compartment. Shown are CD19+ B cells relative to all lymphocytes (% Lymphocytes) (A) and CD19+CD20+ B cells as percentages of CD19+ B cells (B) at the indicated time points. In UNT patients, 8.9 ± 2.8% (mean ± SD) of lymphocyte are B cells (A), virtually all of which are CD20+ (B). B cells are efficiently depleted by RTX, with replenishment beginning 25–36 wk after treatment. Comparisons between UNT samples and cohorts at different time points after RTX treatment were made using the Kruskal–Wallis test; significance levels are: **p < 0.01, ***p < 0.001, ****p < 0.0001.

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FIGURE 6.

Composition of the B cell compartment at different time points after RTX treatment. Shown are B cell subsets relative to all lymphocytes (% Lymphocytes) or all B cells (% CD19+ cells) at the indicated time points. (A) Naive B cells (N), transitional B cells (Tr), and unswitched memory B cells (USM). (B) DN B cells, switched memory B cells (SM), and PC. Indicated are percentages (mean and 95% CI). Please refer to Supplemental Fig. 3 for the flow cytometry gating strategy. Comparisons between samples from UNT patients and cohorts at different time points after RTX treatment were made using the Kruskal–Wallis test; significance levels are: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

FIGURE 6.

Composition of the B cell compartment at different time points after RTX treatment. Shown are B cell subsets relative to all lymphocytes (% Lymphocytes) or all B cells (% CD19+ cells) at the indicated time points. (A) Naive B cells (N), transitional B cells (Tr), and unswitched memory B cells (USM). (B) DN B cells, switched memory B cells (SM), and PC. Indicated are percentages (mean and 95% CI). Please refer to Supplemental Fig. 3 for the flow cytometry gating strategy. Comparisons between samples from UNT patients and cohorts at different time points after RTX treatment were made using the Kruskal–Wallis test; significance levels are: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

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In this report, we unequivocally establish the existence of CD3+CD20dim cells belonging to the T cell lineage in healthy donors and MS patients, thus lending strong support to earlier data suggesting the presence of a CD20-expressing T cell population (6). We confirm that CD20 expression is generally dim on these cells when studied by flow cytometry, further supported by lower levels of CD20 transcripts in these cells. Although we did not perform functional assays, we show that CD3+CD20dim T cells can be either CD4+ Th cells or CD8+ cytotoxic T cells. Together with previous reports that CD3+CD20dim T cells can assume a proinflammatory Th17 phenotype (9), our data suggest that CD3+CD20dim T cells represent a functionally heterogeneous population that may also potentially be involved in the MS disease process.

A vast body of evidence assigns important roles to T cells in the immune pathology of MS. Partially driven by the strong genetic association of MS susceptibility with HLA-DRB1*1501 and other genes known to be important to Th functions (reviewed in Ref. 12) and by the knowledge that in disease models adoptive transfer of myelin-reactive CD4+ T cells elicits MS-like pathology (reviewed in Ref. 13), Th cells are considered necessary contributors to autoimmune demyelination in MS (reviewed in Ref. 14). Accumulating evidence also suggests an important role of CD8+ T cells in MS immune pathology. Oligoclonal CD8+ T cells are overrepresented in MS lesions (15, 16), and myelin-reactive CD8+ T cells are present in peripheral blood of MS patients (17), outnumbering myelin-reactive CD4+ T cells (18). In animal models, CD8+ T cells reactive against myelin basic protein and myelin oligodendrocyte glycoprotein are encephalitogenic (19), and CD8+ T cells reactive against the glial fibrillary acidic protein were recently shown to mediate relapsing-remitting experimental disease (20). In this context, it is interesting that we find increased numbers of CD8+ cells among CD3+CD20dim T cells in UNT MS patients compared with HC. In addition, RTX appears to have, overall, a greater impact on the CD8+ than the CD4+ subset of CD3+CD20dim T cells. It is not known if CD3+CD8+CD20dim T cells contribute to autoimmunity in MS and whether depletion of the CD3+CD20dim T cell population contributes to the therapeutic effect of CD20-targeting therapies in MS (21, 22). Based on the preliminary, but highly encouraging clinical results of anti-CD20 therapies in MS, plus the hypothesis that B cell depletion is responsible for this effect, a number of additional B cell–targeting therapeutic approaches are being actively pursued. In particular, a mAb targeting the B cell lineage restricted marker CD19 (23) is currently in phase I clinical evaluation for the treatment of MS (MEDI-551) (24). Compared with anti-CD20 approaches, anti-CD19 therapy targets a broader spectrum of B cells at different developmental stages but is not expected to deplete CD3+CD20dim T cells; accordingly, a difference in therapeutic efficacy between anti-CD19 and anti-CD20 approaches may indirectly identify a pathogenic role, should it exist, of CD3+CD20dim T cells in MS.

A number of studies have also demonstrated effects of anti-CD20 therapy on the T cell compartment. In humans, RTX treatment reduced T cell numbers in the CSF (25, 26) and in the circulation diminished proinflammatory Th1 and Th17 responses of CD4+ and CD8+ T cells (27). Similarly, in a B cell–dependent model of experimental autoimmune encephalomyelitis induced by immunization of mice with the recombinant extracellular domain of myelin oligodendrocyte glycoprotein, anti-CD20 treatment reduced proinflammatory T cell responses (28, 29). These effects have generally been thought to result from indirect effects of B cell depletion on pathogenic T cells, presumably via blocking B cell–mediated Ag presentation or secretion of proinflammatory B cell cytokines. However, the current data raise the possibility that some of the known effects of RTX on the T cell compartment (2527), and perhaps also that some of the beneficial effects of RTX in RA and MS, may result from depletion of CD3+CD20dim T cells. Irrespective of the mechanism, in this study, we expand the spectrum of immunological changes induced by CD20-targeting therapy in MS to include near-complete direct depletion of CD3+CD20dim T cells for at least 1 y following RTX infusion. In this regard, it is of great interest that, in preliminary clinical studies of both RTX and ocrelizumab in MS, long-term protection against focal inflammatory disease activity was found even after repletion of circulating B cells occurred (5), consistent with the hypothesis that CD3+CD20dim T cells could have some pathogenic role in MS.

The long-term depletion of CD3+CD20dim T cells also suggests that this population may represent an early developmental stage of T cells that is not rapidly replenished, similar to the prolonged depletion of memory B cells observed after RTX treatment (4). In fact, the diversity of T cell–associated markers expressed by CD20dim T cells, including helper, cytotoxic, naive, and memory populations detected by flow cytometry and α/β- and γ/δ-TCRs by transcriptomics, all suggest that CD20 expression may be an early thymic event in the development of a diverse CD3+CD20dim T cell population. To our knowledge, no murine equivalent to human CD3+CD20dim T cells has been identified. However, a murine CD20 homolog, MS4aB1, that is expressed on T cells but not B cells was recently described (30). In murine experimental autoimmune encephalomyelitis, treatment with an anti-MS4aB1 Ab was found to ameliorate disease severity and reduce proinflammatory T cell responses (31), theoretically mimicking the therapeutic effect of anti-CD20–mediated CD3+CD20dim T cell depletion, in the absence of B cell depletion, in humans.

CD20 is traditionally considered a B cell lineage-specific marker. CD20 is a trans-membrane protein (32) expressed on the majority of peripheral B cell subsets, but not on early bone marrow pro–B cells or on a subset of terminally differentiated plasma cells primarily residing in secondary lymphoid tissues. There is no known ligand for CD20; functions of CD20 have been proposed to include calcium transport (33) and boosting of T cell–independent B cell responses (34). CD20-targeting therapies are commonly referred to as B cell–depleting therapy; accordingly, we also find the previously described significant impact of RTX on the B cell compartment, with long-term depletion of memory B cells, early replenishment with naive B cell phenotypes, and also reduction of plasmablasts, possibly owing to the higher turnover rates of short-lived plasmablasts (35, 36). We also show for the first time, to our knowledge, that normally rather infrequent CD19+CD27IgD (DN) B cells become significantly depleted by RTX but at the same time comprise the majority of the small B cell population present in peripheral blood of RTX-treated patients; this may suggest relative resistance of DN B cells to CD20-targeted lymphocyte-depleting therapy. Presently, very little is known regarding immunological function of DN B cells, and it has been speculated that this B cell subset may also contribute to autoimmunity, at least in systemic lupus erythematosus (37). The relevance of DN B cells in MS immune pathology is a matter of ongoing investigation.

In summary, we show that in MS increased numbers of a previously neglected T cell subset, CD3+CD20dim T cells, are effectively depleted by RTX. Further studies will be required to understand the developmental origin and evolutionary relevance of CD3+ CD20dim T cells and whether they differ functionally from CD20 T cells. Understanding the pathological relevance of this T cell subset in MS and other autoimmune disorders will likely broaden our understanding of the pathology of human autoimmunity and may reveal novel therapeutic avenues. Current studies in our laboratory are aimed at delineating the functional properties of CD3+CD20dim T cells, defining their potential contribution to MS immune pathology and elucidating the dynamics of the CD3+CD20dim T cell subpopulation through longitudinal follow-up studies of individuals treated with CD20-depleting therapy.

We thank the patients who agreed to participate in this research. We also thank Erica Eggers for excellent technical assistance and the Gladstone Institutes Genomics Core Facility for performing microarray experiments.

This work was supported by grants from the National Multiple Sclerosis Society (RG-4868 to H.-C.v.B.) and the National Institutes of Health/National Institute of Neurological Disorders and Stroke (K02NS072288 to H.-C.v.B. and R01NS026799 to S.L.H.). H.-C.v.B. was also supported by an endowment from the Rachleff Family Foundation. S.E.B. is a Harry Weaver Neuroscience Fellow of the National Multiple Sclerosis Society.

The online version of this article contains supplemental material.

Abbreviations used in this article:

     
  • DN

    double negative

  •  
  • HC

    healthy control subject

  •  
  • MS

    multiple sclerosis

  •  
  • PC

    plasma cell/plasmablast

  •  
  • RTX

    rituximab

  •  
  • UNT

    untreated.

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D.L. is an employee of F. Hoffmann-La Roche Ltd. H.-C.v.B. has received research funding from F. Hoffmann-La Roche Ltd.

Supplementary data