Peripheral B-cell dysregulation is associated with relapse after long-term quiescence in patients with multiple sclerosis

Abstract

B cells play a major role in multiple sclerosis (MS), with many successful therapeutics capable of removing them from circulation. One such therapy, alemtuzumab, is thought to reset the immune system without the need for ongoing therapy in a proportion of patients. The exact cells contributing to disease pathogenesis and quiescence remain to be identified. We utilized mass cytometry to analyze B cells from the blood of patients with relapse-remitting MS (RRMS) before and after alemtuzumab treatment, and during relapse. A complementary RRMS cohort was analyzed by single-cell RNA sequencing. The R package "Spectre" was used to analyze these data, incorporating FlowSOM clustering, sparse partial least squares-discriminant analysis and permutational multivariate analysis of variance. Immunoglobulin (Ig)A⁺ and IgG₁ ⁺ B-cell numbers were altered, including higher IgG₁ ⁺ B cells during relapse. B-cell linker protein (BLNK), CD40 and CD210 expression by B cells was lower in patients with RRMS compared with non-MS controls, with similar results at the transcriptomic level. Finally, alemtuzumab restored BLNK, CD40 and CD210 expression by IgA⁺ and IgG₁ ⁺ B cells, which was altered again during relapse. These data suggest that impairment of IgA⁺ and IgG₁ ⁺ B cells may contribute to MS pathogenesis, which can be restored by alemtuzumab.

Keywords: Alemtuzumab; B cells; mass cytometry; multiple sclerosis.

Figure 1

Clustered B‐cell repertoire differs between disease and treatment groups. FlowSOM clustering was first done on B cells from each patient. A total of 40 metaclusters were generated. (a–c) Data were then downsampled evenly across groups to 6000 cells to create FIt‐SNE plots. Colors represent labeled parameter (density, metacluster, CD20, CD24, CD27, CD38, IgA, IgD, IgG₁, IgG₂, IgG₃). (d) A heatmap was generated to visualize the relative marker expression (columns) across metaclusters (rows). Each marker was rescaled by minimum/maximum, to compare high (yellow) and low (black) marker expression. Median signal intensity for each marker was calculated for each metacluster. Markers (columns) were rescaled by minimum/maximum. Each metacluster was assigned to one of the conventional B‐cell subsets (transitional, naïve, CD24^hi naïve, unswitched memory, switched memory, double negative, IgG₃, IgG₁, IgG₂, IgA⁺CD20⁺, IgA⁺CD20⁻, CD20⁻ B cells). FIt‐SNE, fast interpolation‐based t‐distributed stochastic neighbor embedding; Ig, immunoglobulin.

Figure 2

Overall B‐cell compartment differs between groups. FlowSOM clustering was done to first identify 40 metaclusters. The levels of each metacluster were calculated as proportion of B cells or counts for each patient. sPLS‐DA plots were generated to visualize differences between groups, using (a) proportion + count, (d) proportion or (g) count data. Each symbol represents an individual patient. Symbol and colors represent the group each patient belongs to. Ellipses are 95% confidence intervals. (b, e, h) A PERMANOVA was performed using the metaclusters identified by sPLS‐DA. Results for each comparison are shown in the relevant table. (c, f, i) The metaclusters used in the first two components of the sPLS‐DA are shown. The conventional B‐cell subset each metacluster belongs to is annotated. 24N, CD24^hi naïve; DN, double negative; Ig, immunoglobulin; MS, multiple sclerosis; N, naïve; T, transitional; PERMANOVA, permutational multivariate analysis of variance; SM, switched memory; sPLS‐DA, sparse partial least squares‐discriminant analysis; UM, unswitched memory.

Figure 3

IgA⁺CD20⁺, IgG₁ ⁺ and IgG₂ ⁺ B cells are affected by alemtuzumab treatment and associated with relapse. (a) Manual gating of conventional B‐cell subsets. CD27, CD80, CD184 and CD185 were used to further differentiate IgA⁺CD20⁺, IgG₁ ⁺ and IgG₂ ⁺ B‐cell subsets. Manual gating strategy of more defined (b) IgA⁺CD20⁺, (c) IgG₁ ⁺ and (d) IgG₂ ⁺ B‐cell subsets. Numbers represent least to most developed B‐cell subset within each subset. (e) FIt‐SNE plots represent B‐cell repertoire between groups. Blue cells are IgA⁺CD20⁺ B cells, red cells are IgG₁ ⁺ B cells, and orange cells are IgG₂ ⁺ B cells. All other B‐cell subsets are dark gray. Counts of (f) IgA⁺CD20⁺, (g) IgG₁ ⁺ and (h) IgG₂ ⁺ B cells (and their respective subsets) are shown as scatter plots. Solid lines signify data are available for adjacent timepoints, while dotted lines indicate patients with nonadjacent timepoints. For comparisons of B‐cell subset levels between all five groups [non‐MS controls (n = 9), patients with untreated MS (prior, n = 11) and patients with MS post‐1 (up to 12 months after alemtuzumab dose, n = 8), post‐2 (greater than 12 months, n = 10) alemtuzumab and relapse (n = 3)], a PERMANOVA was performed followed by pairwise comparisons with Holm’s correction. Prior, post‐2 and relapse groups were compared with non‐MS controls (for three comparisons). An LMM was calculated when comparing between patients with MS before and after treatment. A total of 4999 permutations were then run to calculate P‐values. Five multiple comparisons were made (prior to post‐1, post‐2 and relapse; and post‐1 to post‐2 and post‐2 to relapse) using a further 4999 permutations with Holm’s correction. The mean is shown in non‐MS controls, P‐values < 0.1 are shown. Ig, immunoglobulin; LMM, linear mixed‐effects model; MS, multiple sclerosis; PERMANOVA, permutational multivariate analysis of variance.

Figure 4

B‐cell protein and transcript expression of BLNK, CD40 and CD210 are decreased in patients with untreated MS, but are restored after alemtuzumab treatment. (a) Median signal intensity of BLNK, CD40 and CD210 were calculated across B‐cell subsets of non‐MS (black) and prior (red) patients. Mean and 95% confidence intervals are shown. (b) Median signal intensity of total B‐cell expression of BLNK, CD40 and CD210 is shown across groups. Solid lines signify data are available for adjacent timepoints, while dotted lines indicate patients with nonadjacent timepoints. For comparisons of B‐cell subset levels between all five groups [non‐MS controls (n = 9), patients with untreated MS (prior, n = 11) and patients with MS post‐1 (up to 12 months after alemtuzumab dose, n = 9), post‐2 (greater than 12 months, n = 10) alemtuzumab and relapse (n = 3)], a PERMANOVA was performed followed by pairwise comparisons with Holm’s correction. Prior, post‐2 and relapse groups were compared with non‐MS controls (for three comparisons). A LMM was calculated when comparing between patients with MS before and after treatment. A total of 4999 permutations were then run to calculate P‐values. Five multiple comparisons were made (prior to post‐1, post‐2 and relapse; and post‐1 to post‐2 and post‐2 to relapse) using a further 4999 permutations with Holm’s correction. The mean is shown in non‐MS controls, P‐values < 0.1 are shown. (c) Five B‐cell subsets, naïve (IgD⁺CD27⁻), double negative (IgD CD27⁻), unswitched memory (IgD⁺CD27⁺), switched memory (IgD⁻CD27⁺) and plasmablasts/plasma cells (IgD⁻CD27^hi), were first sorted and then underwent total RNA sequencing and calculated RPKM. The levels of BLNK, CD40 and IL10RA (CD210) were calculated. Solid lines signify data are available for adjacent timepoints. A LMM was calculated when comparing between patients with MS before and after treatment. A total of 4999 permutations were then run to calculate P‐values. Each group was compared with each other (10 comparisons) using a further 4999 permutations with Holm’s correction. The mean is shown for each subset. (d) Single‐cell RNA sequencing was performed on PBMCs from patients with RRMS and healthy controls. Clustering was first done to identify B cells, with FIt‐SNE plots for visualization. (e) Transcript levels of BLNK, CD40 and IL10RA. Permutation of t‐test, the mean is shown. 24 N, CD24^hi B cells; A20 ⁺ , IgA⁺CD20⁺ B cells; A20 ⁻ , IgA⁺CD20⁻ B cells; CD20 ⁻ , CD20⁻ B cells; DN, double negative B cells; G1, IgG₁ ⁺ B cells; G2, IgG₂ ⁺ B cells; G3, IgG₃ ⁺ B cells; Ig, immunoglobulin; IL, interleukin; MS, multiple sclerosis; N, naïve B cells; PBMCs, peripheral blood‐derived mononuclear cells; PERMANOVA, permutational multivariate analysis of variance; RPKM, reads per kilobase per million; RRMS, relapse‐remitting MS; SM, switched memory B cells; T, transitional B cells; UM, unswitched memory B cells.

Figure 5

BLNK, CD40 and CD210 levels are altered in IgA⁺CD20⁺, IgG₁ ⁺ and IgG₂ ⁺ B cells during treatment. The median signal intensity of BLNK, CD40 and CD210 was calculated for (a–c) IgA⁺CD20⁺, (d, e) IgG₁ ⁺ and (f, g) IgG₂ ⁺ B‐cell subsets. Solid lines signify data are available for adjacent timepoints, while dotted lines indicate patients with nonadjacent timepoints. For comparisons of B‐cell subset levels between all five groups [non‐MS controls (n = 9), patients with untreated MS (prior, n = 11) and patients with MS post‐1 (up to 12 months after alemtuzumab dose, n = 9), post‐2 (greater than 12 months, n = 10) alemtuzumab and relapse (n = 3)], a PERMANOVA was performed (with P‐values indicated on all figures) followed by pairwise comparisons with Holm’s correction. Prior, post‐2 and relapse groups were compared with non‐MS controls (for three comparisons). A LMM was calculated when comparing between patients with MS before and after treatment (with P‐values indicated on all figures). A total of 4999 permutations were then run to calculate P‐values. Five multiple comparisons were made (prior to post‐1, post‐2 and relapse; and post‐1 to post‐2 and post‐2 to relapse) using a further 4999 permutations with Holm’s correction. The mean is shown in non‐MS controls, P‐values < 0.1 are shown. Ig, immunoglobulin; LMM, linear mixed‐effects model; MS, multiple sclerosis; PERMANOVA, permutational multivariate analysis of variance.