COVID-19 infection is associated with increased frequencies of plasmablasts and proliferation of memory B cell subsets
B cell subpopulations were also altered in COVID-19 disease. Whereas naïve B cell frequencies were similar in COVID-19 patients and RD or HD, the frequencies of class-switched (IgD−CD27+) and not-class-switched (IgD+CD27+) memory B cells were significantly reduced (Fig. 4A). Conversely, frequencies of CD27−IgD− B cells and CD27+CD38+ PB were often robustly increased (Fig. 4, A and B). In some cases, PB represented >30% of circulating B cells, similar to levels observed in acute Ebola or Dengue virus infections (42, 43). However, these PB responses were only observed in ~2/3 of patients, with the remaining patients displaying PB frequencies similar to HD and RD (Fig. 4B). KI67 expression was markedly elevated in all B cell subpopulations in COVID-19 patients compared to either control group (Fig. 4C). This observation suggests a role for an antigen-driven response to infection and/or lymphopenia-driven proliferation. Higher KI67 in PB may reflect recent generation in the COVID-19 patients compared to HD or RD. CXCR5 expression was also reduced on all major B cell subsets in COVID-19 patients (Fig. 4D). Loss of CXCR5 was not specific to B cells, however, as expression was also decreased on non-naïve CD4 T cells (Fig. 4E). Changes in the B cell subsets were not associated with co-infection, immune suppression, or treatment with steroids or other clinical features, though a possible negative association of IL-6 and PB was revealed (fig. S5A). These observations suggest that the B cell response phenotype of COVID-19 disease was not simply due to systemic inflammation.
Fig. 4  Deep profiling of COVID-19 patient B cell populations reveals robust plasmablast populations and other B cell alterations.
(A) Gating strategy and frequencies of non-PB B cell subsets. (B) Representative flow cytometry plots and frequencies of PB; green line at upper decile of HD. (C) Representative flow cytometry plots and frequencies of KI67+ B cells. (D) (Left) Representative histograms of CXCR5 expression and (right) CXCR5 GMFI of B cell subsets. (E) CXCR5 GMFI of non-naïve CD4 T cells and cTfh. (F) Spearman correlation between PB and activated cTfh. (G) Spearman correlation between PB and anti-SARS-CoV2 IgG. (H and I) Spearman correlation between activated cTfh and anti-SARS-CoV2 (H) IgM and (I) IgG. (J) (Top) Global viSNE projection of B cells for all subjects pooled, with B cell populations of each cohort concatenated and overlaid. (Bottom) viSNE projections of indicated protein expression. (K) Hierarchical clustering of Earth Mover’s Distance (EMD) using Pearson correlation, calculated pairwise for B cell populations for all subjects; row-scaled z-score. (L) Percentage of cohort in each EMD group. (M) Global viSNE projection of B cells for all subjects pooled, with EMD groups 1-3 concatenated and overlaid. (N) B cell clusters identified by FlowSOM clustering. (O) MFI as indicated; column-scaled z-score. (P) Percentage of B cells from each cohort in each FlowSOM cluster. Boxes represent IQR. (A to F, P) Dots represent individual healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 (red) subjects. (A to E, P) Significance determined by unpaired Wilcoxon test with BH correction: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. (GtoI) Black horizontal line represents positive threshold. During acute viral infections or vaccination, PB responses are transiently detectable in the blood and correlate with cTfh responses (40). Comparing the frequency of PB to the frequency of total cTfh or activated cTfh, however, revealed a weak correlation only with activated cTfh (Fig. 4F and fig. S5, B and C). Furthermore, some patients had robust activated cTfh responses but PB frequencies similar to controls, whereas other patients with robust PB responses had relatively low frequencies of activated cTfh (Fig. 4F and fig. S5, B and C). However, there was also an association between PB frequency and CD38+HLA-DR+ or KI67+ CD4 T cells that might reflect a role for non-CXCR5+ CD4 T cell help (fig. S5D), but such a relationship did not exist for the equivalent CD8 T cell populations (fig. S5E). Although ~70% of COVID-19 patients analyzed made antibodies against SARS-CoV2 spike protein (79/111 IgG; 77/115 IgM (44)), antibody levels did not correlate with PB frequencies (Fig. 4G and fig. S5F). The occasional lack of antibody did not appear to be related to immunosuppression in a small number of patients (fig. S5G). The lack of PB correlation with antibody suggests that a proportion of these large PB responses were: i) generated against SARS-CoV2 antigens other than the spike protein or ii) inflammation-driven and perhaps non-specific or low affinity. Notably, anti-SARS-CoV2 IgG and IgM levels correlated with the activated, but not total, cTfh response, suggesting that at least a proportion of cTfh were providing SARS-CoV2-specific help to B cells (Fig. 4, H and I, and fig. S5, H and I). Although defining the precise specificity of the robust PB populations will require future studies, these data suggest that at least some of the PB response is specific for SARS-CoV2.
Projecting the flow cytometry data for B cells from HD, RD, and COVID-19 patients in tSNE space revealed a distinct picture of B cell populations in COVID-19 compared to controls, whereas RD and HD were similar (Fig. 4J and fig. S5J). The COVID-19 patient B cell phenotype was dominated by loss of CXCR5 and IgD compared to B cells from HD and RD (Fig. 4J). Moreover, the robust PB response was apparent in the upper right section, highlighted by CD27, CD38, CD138, and KI67 (Fig. 4J). The expression of KI67 and CD95 in these CD27+CD38+CD138+ PB (Fig. 4J) could suggest recent generation and/or emigration from germinal centers. We next asked whether there were different groups of COVID-19 patients (or HD and RD) with global differences in the B cell response. We used Earth Movers Distance (EMD) (45) to calculate similarities between the probability distributions within the tSNE map (Fig. 4J) and clustered so that individuals with the most similar distributions grouped together (Fig. 4K). The majority of COVID-19 patients fell into two distinct groups (EMD Groups 1 and 3, Fig. 4L), suggesting two major “immunotypes” of the B cell response. The remainder of the COVID-19 patients (~25%) clustered with the majority of the HD and all of the RD controls, supporting the observation that some individuals had limited evidence of response to infection in their B cell compartment. To identify the population differences between HD, RD and COVID-19 patients, we performed FlowSOM clustering on the tSNE map, and also overlaid each individual EMD group onto this same tSNE map (Fig. 4, M and N). EMD Group 2 containing mostly HD and RD was enriched for naive B cells (IgD+CD27−, Cluster 10) and CXCR5+IgD−CD27+ switched memory (Cluster 2) and, indeed, Clusters 2 and 10 were statistically reduced in COVID-19 patients (Fig. 4P). EMD Groups 1 and 3 displayed distinct patterns across the FlowSOM clusters. B cells from individuals in EMD Group 1 were enriched for the FlowSOM Clusters 1, 5, and 6, all of which were increased in COVID-19 patients (Fig. 4P). FlowSOM Clusters 1 and 6 captured T-bet+ memory B cells whereas FlowSOM Cluster 5 contained the CD27+CD38+CD138+KI67+ PB, all of which were enriched in COVID-19 patients compared to controls (Fig. 4, O and P, and fig. S5K). In contrast, B cells from COVID-19 patients in EMD Group 3 also showed enrichment for the PB FlowSOM Cluster 5, though less prominent than for EMD Group 1, but the T-bet+ memory B cell Cluster 1 was substantially reduced in EMD Group 3. Thus, B cell responses were evident in many hospitalized COVID-19 patients, most often characterized by elevated PB, decreases in memory B cell subsets, enrichment in a T-bet+ B cell subset, and loss of CXCR5 expression. Whether all of these changes in the B cell compartment were due to direct antiviral responses is unclear. Although there was heterogeneity in the B cell responses, COVID-19 patients fell into two distinct patterns containing activated B cell responses and a third group of patients with little evidence of an active B cell response.