Repopulation of T, B, and NK cells following alemtuzumab treatment in relapsing-remitting multiple sclerosis

Abstract

Objective: To characterize long-term repopulation of peripheral immune cells following alemtuzumab-induced lymphopenia in relapsing-remitting MS (RRMS), with a focus on regulatory cell types, and to explore associations with clinical outcome measures.

Methods: The project was designed as a multicenter add-on longitudinal mechanistic study for RRMS patients enrolled in CARE-MS II, CARE-MS II extension at the University of Southern California and Stanford University, and an investigator-initiated study conducted at the Universities of British Columbia and Chicago. Methods involved collection of blood at baseline, prior to alemtuzumab administration, and at months 5, 11, 17, 23, 36, and 48 post-treatment. T cell, B cell, and natural killer (NK) cell subsets, chemokine receptor expression in T cells, in vitro cytokine secretion patterns, and regulatory T cell (Treg) function were assessed. Clinical outcomes, including expanded disability status score (EDSS), relapses, conventional magnetic resonance imaging (MRI) measures, and incidents of secondary autoimmunity were tracked.

Results: Variable shifts in lymphocyte populations occurred over time in favor of CD4+ T cells, B cells, and NK cells with surface phenotypes characteristic of regulatory subsets, accompanied by reduced ratios of effector to regulatory cell types. Evidence of increased Treg competence was observed after each treatment course. CD4+ and CD8+ T cells that express CXCR3 and CCR5 and CD8+ T cells that express CDR3 and CCR4 were also enriched after treatment, indicating heightened trafficking potential in activated T cells. Patterns of repopulation were not associated with measures of clinical efficacy or secondary autoimmunity, but exploratory analyses using a random generalized estimating equation (GEE) Poisson model provide preliminary evidence of associations between pro-inflammatory cell types and increased risk for gadolinium (Gd+) enhancing lesions, while regulatory subsets were associated with reduced risk. In addition, the risk for T2 lesions correlated with increases in CD3+CD8+CXCR3+ cells.

Conclusions: Lymphocyte repopulation after alemtuzumab treatment favors regulatory subsets in the T cell, B cell, and NK cell compartments. Clinical efficacy may reflect the sum of interactions among them, leading to control of potentially pathogenic effector cell types. Several immune measures were identified as possible biomarkers of lesion activity. Future studies are necessary to more precisely define regulatory and effector subsets and their contributions to clinical efficacy and risk for secondary autoimmunity in alemtuzumab-treated patients, and to reveal new insights into mechanisms of immunopathogenesis in MS.

Trial registration: Parent trials for this study are registered with ClinicalTrials.gov: CARE-MS II: NCT00548405, CARE-MS II extension: NCT00930553 and ISS: NCT01307332.

Keywords: Alemtuzumab; B cell subsets; Drug mechanisms; Immune regulation; Lymphocyte repopulation; Lymphopenia; Multiple sclerosis; Natural killer cell subsets; T cell subsets; Tolerance.

Conflict of interest statement

WG has received funding from Sanofi/Genzyme for investigator-initiated research and honoraria for service on advisory and scientific boards for Sanofi/Genzyme. BTL has received funding from Sanofi/Genzyme, Novartis Pharmaceuticals Corporation, and Teva Pharmaceuticals for investigator-initiated research and has received honoraria from Teva Pharmaceuticals. PL has no disclosures to report. AML has no disclosures to report. EEK has received funding for investigator-initiated research from Novartis Pharmaceuticals Corporation and Teva Pharmaceuticals. OA has no disclosures to report. SG has no disclosures to report. SYP has no disclosures to report. DP has received consultation honoraria from Biogen, EMD Serono, Genentech, Genzyme Corporation, Novartis Pharmaceuticals, and Teva Pharmaceuticals and research funding from Genzyme Corporation. LPW has no disclosures to report. AJ has received consultation honoraria from EMD-Serono, Sanofi-Genzyme, Novartis, Biogen, and Genentech. JED has received honoraria for participation on Advisory Boards from Genentech, Biogen, and Alexion and compensation for education programs from Novartis and Sanofi. ALT has received grant funding from the MS Society of Canada, Canadian Institute for Health Research, Roche, and Genzyme. He has received honoraria or travel grants from Teva Canada Innovation, Roche, Merck/EMD Serono, Genzyme, and Chugai Pharmaceuticals.

Figures

Fig. 1

Changes in CD4+ regulatory T cells (Treg), “effector” T cells (Teff), and Treg function in PBMC. a FACS gating strategy used to identify CD4 + CD25hiCD127lo/neg foxP3+ Tregs and CD4 + CD25 + CD127 + foxP3- Teff in PBMC (first four FACS plots, left to right) and in PBMC depleted of CD25+ Tregs (fifth FACS plot, right). b-e Illustrate changes over time at each study timepoint for each individual patient (open symbols), compared with baseline (M0) values. b Changes in Tregs. c Changes in Teff. d Changes in Teff:Treg ratio. e Changes in Treg function, indicated as percent rebound in CD25-depleted PBMC compared to undepleted PBMC. Data in all panels represent median/IQR values for all patients at each timepoint. p values indicate significant changes from baseline (M0) as follows: ****p ≤ 0.0001, ***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05; mixed effects ANOVA with Tukey’s corrections for multiple comparisons

Fig. 2

Changes in CD4+ and CD8+ T cells expressing chemokine receptors in whole blood. a Total CD3+CD4+ T lymphocytes. b Total CD3+ CD8+ T cells. c and d Show CD3+CD4+ T cells expressing CXCR3 and CCR5, respectively, which are enriched in Th1 cells. e and f Show CD3+CD4+ T cells expressing CCR3 and CCR4, respectively, which are enriched in Th2 cells. g–j Show CD3+CD8+ T cells that express CXCR3, CCR5, CCR3, and CCR4, respectively. Data represent median/IQR values for all patients at each timepoint; open circles indicate data points for each individual patient. p values indicate significant changes from baseline (M0) values as follows: ****p ≤ 0.0001, ***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05; mixed effects ANOVA with Tukey’s corrections for multiple comparisons

Fig. 3

Changes in B cell subsets in thawed PBMC. a FACS gating strategy used to identify CD19+20+CD27+ total memory B cells, CD19+20+ total naïve B cells, and CD19+ CD20+CD27-CD24hiCD38hi B cells. b Total CD19+CD20+CD27+ memory B cells. c CD19+CD20+CD27- total naïve B cells. d CD19+CD20+CD27-CD24hiCD38hi B cells. e Ratio of total memory B cells to naïve “regulatory” CD24hiCD38hi B cells. f Ratio of total naïve B cells to CD19+CD20+CD27-CD24hiCD38hi B cells. Data represent median/IQR values for all patients at each timepoint; open circles indicate data points for each individual patient. p values indicate significant changes from baseline (M0) values as follows: ****p ≤ 0.0001, ***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05; Kruskal-Wallis test

Fig. 4

Changes in NK cell subsets in whole blood. a FACS gating strategy used to identify CD3-CD56+ total NK cells, CD3-CD56bright NK cells, and CD3+CD56+ NKT cells. b Total CD3-CD56+ NK cells. c CD3-CD56bright NK cells. d CD3+ CD56+ NKT cells. e Ratio of NKT cells:CD3-CD56bright T cells. Data represent median/IQR values for all patients at each timepoint; open circles indicate data points for each individual patient. p values indicate significant changes from baseline (M0) values as follows: ****p ≤ 0.0001, ***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05; mixed effects ANOVA with Tukey’s corrections for multiple comparisons

Fig. 5

Clinical and imaging outcomes. a Expanded disability status scores (EDSS), measured every 6 months. b Number of new T2 lesions. c T2 volume. d Number of Gd+ lesions at baseline; subsequent timepoints represent new Gd+ lesions. e Brain parenchymal fraction (BPF). Data are expressed as median/IQR values for all patients at each timepoint. p values indicate significant changes from baseline (M0), where applicable, as follows: **p ≤ 0.01, *p ≤ 0.05; Kruskal-Wallis test for EDSS, number of new T2 and Gd+ lesions, and mixed effects ANOVA with Tukey’s corrections for T2 volume and BPF. f Number of patients with new T2 lesions in the first year (up to M12), second year (M13–M24), third year (M25–M36), and fourth year (M37–M48) accompanied by total number for all timepoints on study. g Total number of new lesions in each year. h Number of patients with Gd+ lesions at M0 [11] and new Gd+ lesions in each year, accompanied by the total number of new Gd+ lesions from M12 to M48. i Total number Gd+ lesions at M0 and new Gd+ lesions in each year. j Number of patients who experienced relapses in each year on study, accompanied by the total for all years. k Number of patients who experienced relapses and/or new Gd+ lesions (active disease) or had no relapses or Gd+ lesions (stable disease) on study

Fig. 6

Lack of significant differences in selected lymphocyte subsets stratified for patients with active and stable disease activity during the 48-month study period. Each row represents data from one lymphocyte subset, with the left panels in each row illustrating between-subjects analyses, followed by within-subjects analyses for patients with active (middle panels) and stable (right panels) disease activity. a–c Changes in CD4+CD25+CD127+foxP3- Teff. d–f Changes in CD4+CD25hiCD127lo/neg foxP3+ Tregs. g–i Changes in CD19+CD20+CD27- total naïve B cells. j–l Changes in CD19+CD20+CD27-CD24hi CD38hi B cells. m–o Changes in CD3-CD56bright NK cells. p–r Changes in CD3+CD56+ NKT cells. Data represent median/IQR; closed symbols indicate patients with active disease, and open symbols indicate patients with stable disease. Data were subjected to between- and within-subject analyses using a linear mixed effects model for repeated measures

Fig. 7

Lack of significant differences in selected lymphocyte subsets stratified for patients with and without secondary autoimmunity during the 48-month study period. Each row represents data from one lymphocyte subset, with the left panels in each row illustrating between-subjects analyses, followed by within-subjects analyses for patients with secondary autoimmunity (middle panels) and without secondary autoimmunity (right panels) disease activity. a–c Changes in CD4+CD25+CD127+foxP3- Teff. d–f Changes in CD4+CD25hiCD127lo/neg foxP3+ Tregs. g–i Changes in CD19+CD20+CD27- total naïve B cells. j–l Changes in CD19+CD20+CD27-CD24hi CD38hi B cells. m–o Changes in CD3-CD56bright NK cells. p–r Changes in CD3+CD56+ NKT cells. Data represent median/IQR; closed symbols indicate patients with secondary autoimmunity, and open symbols indicate patients without secondary autoimmunity. Differences over time between and within groups were not statistically significant (linear mixed effects model for repeated measures)