key: cord-0804657-hpbjdytv
authors: Oja, Anna E.; Saris, Anno; Ghandour, Cherien A.; Kragten, Natasja A.M.; Hogema, Boris M.; Nossent, Esther J.; Heunks, Leo M.A.; Cuvalay, Susan; Slot, Ed; Swaneveld, Francis H.; Vrielink, Hans; Rispens, Theo; van der Schoot, Ellen; van Lier, René A.W.; Brinke, Anja Ten; Hombrink, Pleun
title: Divergent SARS-CoV-2-specific T and B cell responses in severe but not mild COVID-19
date: 2020-06-18
journal: bioRxiv
DOI: 10.1101/2020.06.18.159202
sha: 40897ed0606a6a0e1eba23f7690270abdfc297ff
doc_id: 804657
cord_uid: hpbjdytv

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the current coronavirus disease 2019 (COVID-19) pandemic. Understanding both the immunological processes providing specific immunity and potential immunopathology underlying the pathogenesis of this disease may provide valuable insights for potential therapeutic interventions. Here, we quantified SARS-CoV-2 specific immune responses in patients with different clinical courses. Compared to individuals with a mild clinical presentation, CD4+ T cell responses were qualitatively impaired in critically ill patients. Strikingly, however, in these patients the specific IgG antibody response was remarkably strong. The observed disparate T and B cell responses could be indicative of a deregulated immune response in critically ill COVID-19 patients.

Peripheral blood of a total of 56 PCR-positive COVID-19 patients was collected, of whom 37% (n=21) recovered from disease and expressed mild symptoms (mild symptoms up to mild pneumonia), 25% (n=14) recovered from disease and expressed severe symptoms requiring hospitalization and 38% (n=21) critically ill requiring treatment in intensive care unit (ICU), referred to as mild, severe, and ICU groups from now on, respectively (Table 1, Extended Data Table 1 ). For all patients SARS-CoV-2 exposure was verified by serology testing of IgG titers against RBD of spike and nucleocapsid. For the ICU cohort, blood was taken during ICU stay for 18 patients, indicated in figures by square symbols, and after recovery for 3 patients, shown as circles in all figures. Samples were collected with at a median of 52 (mild), 45 (severe) and 34 (ICU) days after onset of symptoms (Table 1, Extended Data Table 1 ).

First the frequency of T cells in the blood of different COVID-19 patient groups was assessed by fluorescence-activated cell sorting (FACS) (general gating strategy shown in Extended Data Fig.1a) . The proportion of CD3+ T cells was decreased in the critical patient group during ICU stay as compared to healthy controls and T cell levels remained low for the severe patients at a median of 30 days after symptomatic recovery (Fig. 1a , Extended Data and ICU patient groups demonstrated higher frequencies of effector phenotype (CD45RA+CD27-) and severe patients had lower frequencies of naïve (CD45RA+CD27+) CD4+ T cells than mild patients or unexposed individuals (Fig. 1c) . Effector CD8+ T cells were also relatively increased in the ICU patients compared to patients with mild or severe symptoms, while naïve CD8+ T cells were significantly decreased compared to unexposed individuals and mild patients (Fig. 1d) . However, we cannot exclude that the skewed effector phenotype in the ICU patients is not due age or CMV seropositivity.

We next analyzed the cell surface expression of the inhibitory PD-1, expressed after T cell activation, to obtain a first view on the functionality of the T cell compartment. Frequencies of PD-1+ CD4+ and CD8+ T cells was increased in association with stage of infection, with the highest levels in ICU patients (Fig. 1e,f, Extended Data Fig. 1d,e) . Recovered ICU patients showed significantly lower PD-1 expression than the patients in the ICU at the time of sampling (Extended Data Fig. 1i,j) . Using constitutive expression of the 4-1BB receptor protein CD137 and absence of the conventional CD4+ T cell activation marker CD40L as a proxy for activated regulatory T cells (Treg) 14 , there was a significant decrease in activated Treg in blood of the mild group compared to unexposed individuals and ICU patients (Fig. 1g , Extended Data Fig. 1f,k) . This may indicate recruitment of Treg to tissues in the mild cohort which can prevent immunopathologies due to hyper-inflammatory responses, frequently observed in critically ill COVID-19 patients.

It was recently shown that circulating follicular helper T cells (cTfh) are increased in Covid-19 patients and rise over the course of the infection 8, 15, 16 . However, possible differences in relation to disease severity were not assessed. Thus, we also analyzed the frequencies of circulating follicular T helper cells (cTfh). The highest frequencies of cTfh, based on PD-1 and CXCR5 expression, were found in ICU patients (Fig. 1h, Extended Data Fig. 1g ,l). Since the recovered ICU patients showed a trend towards lower frequencies of cTfh (Extended Data Fig. 1g ), it is unclear whether frequencies of cTfh correlate with stage of disease or disease severity. On the other hand, concomitant with the lymphopenia, we found fewer CXCR5 expressing CD4+ T cells in the ICU but not in the recovered mild and severe COVID-19 patient groups (Fig. i, Extended Data Fig. 1h,m) . This might reflect homing to CXCL13 gradients in secondary lymphoid tissues at the site of antigen accumulation under conditions of inflammation.

Following a primary respiratory viruses infection, a population of tissue resident memory T cells (TRM) is generated, that persist in the tissue for prolonged periods of time 17, 18 . In healthy human lungs, TRM express canonical phenotypic markers for retention, adhesion and migration to tissues (CD69, CD103, CD49a, CXCR6) and express high levels of the inhibitory molecule PD-1 19, 20 . Since both airway CD4+ and CD8+ T cells were reported to be required for optimal protection against the emerging coronavirus SARS-CoV-2 21,22 , we set out to sample bronchoalveolar lavage fluid (BALF) and blood of 8 critical COVID-19 patients during ICU stay, for monitoring T cell phenotypes. Under healthy circumstances, T cells in BALF reflect the composition of the barrier tissue and exhibit predominant TRM phenotypes 23 . The CD4:CD8 T cell ratio in BALF was not significantly different when compared to that derived from paired blood (Fig. 2a) . The BALF contained lower frequencies of naïve (CD45RA+CD27+) and higher frequencies of effector memory (CD45RA-CD27-) CD4+ and CD8+ T cells compared to blood-derived PBMCs (Figure 2b,c) . Nonetheless, the high frequency of naïve cells in the BALF was striking, since under normal conditions very few to no naïve cells are found in the BALF 23 .

We further examined whether memory T cells in the BALF exhibited a TRM phenotype, by measuring CD69 and CD103 expression on non-naïve CD4+ and CD8+ T cells. In line with the abundance of T cells with a circulating phenotype, we also found very few CD4+ or CD8+ T cells expressing CD69 or CD69 and CD103 (Fig. 2d) . Thus BALF T cells in ICU COVID-19 patients are not cells that have the canonical TRM phenotype, but rather appear to be cells that normally belong to the circulating pool. 3b ). We further added up the responses to all these antigens to estimate the total CD4+ T cell response to SARS-CoV-2 and compared this to the frequencies of CMV pp65 specific CD4+ T cells. The magnitude of SARS-CoV-2 specific CD4+ T cells was significantly higher than that of CMV pp65 specific CD4+ T cells (Fig. 3c) . The CMV responses varied, likely due to seropositivity, while all patients showed a robust response to SARS-CoV-2.

To investigate whether these high responses against S were SARS-CoV-2-specific or if they also consisted of cross-reactive T cells to "common cold" coronavirus strains, we stimulated these same PBMC samples with two Spike peptide pools, 299E and OC43, from two different "common cold" coronavirus strains. The frequencies of SARS-CoV-2 S-specific CD4+ T cells were significantly higher than S-299E-or S-OC43-specific CD4+ T cells (Fig.   3d ). Furthermore, the frequencies of 299E-and OC43-specific CD4+ T cells were not significantly higher than the paired unstimulated samples. This demonstrates that the responses we observe against S were predominantly due to COVID-19.

In line with this, we also determined the responses of unexposed healthy donor PBMCs to these SARS-CoV-2 antigens (Extended data Fig 2b) . While the response frequencies to the individual antigens were not significantly higher than the unstimulated, there was a trend towards higher frequencies of S-specific CD4+ T cells (Fig. 3e) . When the low frequent responses were added up this was higher than the unstimulated, but not significantly different from frequencies of CMV pp65 specific CD4+ T cells (Fig. 3f) . We further compared the CD4+ T cell responses to SARS-CoV-2-S and "common cold" S-299E and S-OC43 peptide pools and found no differences in the frequencies between the three spike peptide pools (Fig. 3g) . These data indicate that unexposed healthy donors have low frequencies of cross-reactive CD4+ T cells to S of SARS-CoV-2.

After identifying S, N, and M as the immunodominant antigens of SARS-CoV-2, we assessed the CD4+ T cell responses in the two additional patient cohorts, severe (hospitalized) and ICU (Extended Data Fig 2c,d) . Also in these patient cohorts, S was most frequently recognized, followed by N and M ( Fig. 4a,b) . The majority of the S-and N-specific CD4+ T cells had a memory (CD45RA-CD27+) phenotype. (Fig. 4c,d) . We also sought to determine the antigen-specificity of CD4+ T cells in paired BALF and PBMC samples. In one sample, we found S-specific CD4+ T cells in both BALF and PBMCs and in both tissues the Sspecific CD4+ T cells had a circulating memory rather than a TRM phenotype (Extended Data To determine whether T cell responses were influenced by disease severity, we compared the magnitude of response to S and N between the three cohorts. Overall, by polyclonal aCD3 stimulation, CD4+ T cells from all patient cohorts, in disregard of disease severity, produce relatively similar cytokine profiles. A bias to increased expression of IL-4 and IL-21 production was observed for the by ICU patient cohort, which we attribute to aging effects (Extended Data Fig. 4a ). Intriguingly, the severe patient cohort showed higher frequencies of S-specific CD4+ T cells compared to both the mild and ICU cohorts (Fig. 4e) . The severe patients also had higher frequencies of N-specific CD4+ T cells (Fig. 4f) . While the magnitude of the response to SARS-CoV-2 is important, the quality of the response is also crucial. Therefore, we assessed the cytokine profile of the CD4+ T cells that showed at least a 0.01% response frequency. Regardless of disease severity, SARS-CoV-2-specific CD4+ T cells conformed to a type 1 cytokine profile, predominantly producing IFN-γ and TNF-α ( Figure 5a ,b, Extended Data Fig. 4b,c) . Although ICU patient CD4+ T cells also skewed towards a type 1 response, the S-and N-specific CD4+ T cells produced less IFN-γ compared to the mild group. Although not produced to the same magnitude as TNF-α and IFN-γ, N-specific CD4+ T cells of mild COVID-19 patients also produced significantly more IL-21 than severe or ICU patient CD4+ T cells and a similar trend was observed for Sspecific CD4+ T cells. Furthermore, S-specific CD4+ T cells of mild produced significantly more IL-4 than the CD4+ T cells from ICU patients, with a similar trend for the N-specific CD4+ T cells. Thus, the critically ill ICU patients demonstrated a diminished CD4+ T cell response not only in quantity but also in quality of the response.

B cell responses in patients with COVID-19 develop from around one week after symptom onset 8 . Coronavirus-neutralizing antibodies primarily target the receptor binding domain (RBD) of the S protein to prevent entry into host cells 24, 25 . Neutralizing antibody (nAb) responses begin to develop around week 2 in most patients. IgG responses to the RBD of S was analyzed in the different patient groups. Serum antibody levels correlated with clinical severity (Fig. 6a) . Similarly, nucleocapsid (N) IgG titers were increased in the severe and ICU patients compared to the mild group (Fig. 6b) . The titers for S-RBD and N correlated well so we focused our analysis on S-RBD from here onwards (Fig. 6c) . Since effective antibody responses and isotype switching rely on CD4+ T cell help, we assessed whether SARS-CoV-2 antibody titers were associated with CD4+ T cell responses. As S-specific CD4+ T cell responses were detected in all COVID-19 patients and was indicative for the CD4+ T cell response to the total SARS-CoV-2 antigen pool (Extended Data Fig. 5a ), we assessed whether CD4+ T cell responses were associated with antibody titers to SARS-CoV-2 ( Fig.   6d ). For the mild patient group we found S-specific CD4+ T cell responses, as a proxy for total SARS-CoV-2-specific CD4+ T cell responses, to correlate with the magnitude of anti-S-RBD titers, in line with previous reports 7, 26 . No correlation was observed for the severe and ICU patient groups (we acknowledge smaller group sizes) ( In line with recent reports, we also detected cross-reactive T cell responses in PBMCs of healthy blood donors obtained before the SARS-CoV-2 pandemic 6,7 . Interestingly, while cross-reactivity with "common cold" coronavirus strains is plausible due to the overlapping epitopes between the viruses, we did not observe significant recognition of 299E and OC43 encoded spike proteins, including the well-conserved S2 domain 34 , in the COVID-19 patients.

Nevertheless, the association between the prevalence of cross-reactive T cells and disease severity in patients with COVID-19 needs evaluation in asymptomatic patients including most SARS-CoV-2 infected children 35 . The absence of substantial T cell responses to commoncold coronavirus strains could be causative factor to initiate symptoms, due to delayed control of viral loads.

We found a substantial population of antigen-inexperienced naïve T cells in the BALF of COVID-19 ICU patients. Accompanied with low frequencies of memory T cells with a resident memory (CD69+CD103-or CD69+CD103+) phenotype these data indicate a compromised vascular integrity and epithelial barrier function and thus alveolar leakage. In one ICU patient, in which we were able to obtain representative data of antigen-specific CD4+ T cell in BALF, the S-specific CD4+ T cell response in both BALF and PBMC showed typical phenotypes of circulating cells but not TRM, further supporting the notion of vascular leakage. These data support previous findings where increased expansion of T cell clones, indicating possible SARS-CoV-2 specificity, were mainly detected in BALF of moderate but not critical COVID-19 patients 10 . Although these results do not rule out that the lymphopenia in critically ill COVID-19 patients is partly mediated by recruitment of T cells to the lungs, the low number of SARS-CoV-2 specific T cells in the blood and BALF, may rather suggest a compromised expansion or selective depletion, as has been postulated by others 11, 36 . Although the role of Our study results imply the requirement of a balanced participation of B and T cells to curb SARS-CoV-2 infection and indicate that T cells cope less efficiently with the rapid viral load peaks observed in COVID-19. SARS-CoV-2 viral load peaks at day 10 after symptom onset while that of previous emerging coronaviruses peaked a few days later [37] [38] [39] [40] . Viral loads correlated with disease severity and decreased T cell count, and patient age 40, 41 . In line with this, we found patients that developed severe COVID-19, but did not require ICU treatment, to exhibit higher SARS-CoV-2-specific T cell responses alongside high titers for S-RBD and N IgG. On the other hand, critical ICU patients failed to generate substantial T cell responses but generated a strong antibody response already early on. Timing appears to be crucial as the ratio between viral loads and antibody titers during the early phase of disease may be predictive for disease severity 42 . A delayed effective T cell control of viral loads, supplemented with a compromised innate immune function, frequently observed in elderly 43 , could tip the balance towards more severe symptoms mediated by pathological consequences of viral specific antibodies. Such a model may explain the differences observed between the severe and critically ill patient cohorts in our study, where an increased magnitude of anti-S and anti-N specific T cells are associated with lower antibody titers and disease severity. In line with others, we find age to be a risk factor for disease severity. Aging related senescence of potential cross-reactive T cells, combined with a compromised generation of T cell responses to new antigens may make the elderly more susceptible to COVID-19. T cell responses that are generated in critically ill patients may also be dampened by either suppressed expansion or apoptosis induced by a cytokine storm, the main contributor to ARDS observed in critically ill ICU patients 36, 44 .

Failure of antiviral T cell responses to control SARS-CoV-2 replication could underlie the hyper-inflammatory responses and associated immunopathology characterizing critically ill COVID-19 patients. These observations seem counterintuitive as B cells require CD4+ T cell help from Tfh for optimal GC responses and class-switching 45 . Circulating Tfh (cTfh) are poorly understood blood counterparts of GC Tfh cells. ICOS+CXCR3+ cTfh correlate with nAb responses upon viral infection or vaccination [46] [47] [48] [49] . cTfh increase over the course of SARS-CoV-2 infection 8, 15, 16 . In our study the cTfh frequency was highest in the ICU patients, patients that also demonstrated the highest antibody titers, with indications of levels decreasing upon recovery. Interestingly CXCR3+cTfh, produce IL-21, which was found less in SARS-CoV-2-specific CD4+ T cells in ICU patients. Although IL-21 is also produced by TH2 cells, and serum levels may not be associated with cTfh numbers, we cannot rule out the On the other hand, B cells also play a role in antigen presentation to activate CD4+ T cells.

Interestingly, the quality of the B cell response appears to be specifically altered in critically ill ICU patients with COVID-19. These patients, in contrast to patients with mild symptoms, produce afucosylated IgG antibodies against the S protein 51 . Afucosylated antibodies exhibit increased binding affinity to Fc receptors and enhance antibody dependent cellular cytotoxicity (ADCC), which may account for the hyper immune response in ICU patients.

Since crosslinking of Fc receptors is required for optimal antigen-cross presentation and priming of T cells, future studies may direct whether IgG variants without core fucosylation prime T cells equally well as their fucosylated counterparts, and as such contribute to the lower frequency of antigen-specific CD4+ T cells observed in ICU patients. It was recently proposed that signaling through a co-signal receptor may alter the glyco-programming of B cells 51 . Whether CD4+ T cell, in particular Tfh, induced signaling through co-stimulatory molecules or secreted cytokines, such as IL-21, can alter B cell glyco-programming in COVID-19 remains to be elucidated and can be of great importance for vaccine strategies.

Taken together, these data suggest that a balanced participation of B and T cells is required to control SARS-CoV-2 infection and provide rationale for future evaluation of vaccine strategies. Further studies on the direct and indirect interactions between the humoral and cellular adaptive immune response are required for a better understanding of COVID-19 pathophysiology.

Blood was collected from ex-COVID-19 patients donating convalescent plasma at Sanquin Blood Bank, Amsterdam, the Netherlands. All donors were diagnosed with SARS-CoV-2 infection by PCR prior to inclusion. All patients admitted to the intensive care unit (ICU) of the VU medical center that received a diagnostic BAL were included in this study. Sanquin Blood Supply Foundation, Amsterdam, the Netherlands supplied the buffy coats of regular donors used as unexposed healthy controls. 

Antibody titers were determined by ELISA analogously. Briefly, samples were tested at 100 -1200 fold dilutions (in PBS supplemented with 0.1% polysorbate-20 and 0.3% gelatin (PTG) in microtiter plates coated with RBD or (nucleocapsid) NP and incubated for 1h at RT. Both proteins were produced as described 51 . After washing, 0.5 µg/mL HRP-conjugated antihuman IgG (MH16, Sanquin) was added in PTG and incubated for 1h. Following enzymatic conversion of TMB substrate, absorbance was measured at 450 nm and 540 nm and the difference used to evaluate antibody binding by comparison to a reference plasma pool of convalescent COVID-19 patients.

Peripheral blood mononuclear cells (PBMCs) were isolated from heparinized blood samples using standard Ficoll-Paque density gradient centrifugation. During diagnostic bronchoscopy lungs were flushed with 40ml NaCl to collect bronchoalveolar lavage fluid (BALF). BALF was centrifuged (to collect BALF supernatant; 300g, 10min) and the cell pellet was resuspended in 2mM dithiotreitol (Sigma, Zwijndrecht, the Netherlands). After 30 min at 4°C, cells were washed with PBS+1%BSA and mononuclear cells were isolated using Ficoll-Paque density gradient centrifugation. PBMC and BALF MC samples were either used directly for experimentation or cryopreserved in liquid nitrogen until further analysis.

The details of the peptide pools (JPT, Germany) used in this study are listed in Extended Data Table 2 . Peptide pools against spike (S1 and S2), nucleocapsid (N), membrane protein and uncharacterized proteins referred to as ORF pool; containing NS6, NS7B, NS7A, NS8, ORD10, ORF9B and Y14, were used when indicated. When samples allowed, the S1 and S2

were added up and referred to as S1+S2 in the figures. Peptide pools were used at a final concentration 100 ng/mL. 

One-and two-way ANOVA and Tukey's multiple comparisons test using GraphPad Prism 8 were used to determine the significance of our results as indicated in figure legends. p value of less than 0.05 was considered statistically significant (* p<0.05; ** p<0.01; *** p<0.001; **** p<0.0001). Pearson's correlations were calculated to define correlations throughout the manuscript. Significance of the results was determined using one-way ANOVA with Tuckey's multiple comparisons test. c,d,, Bars show mean values with SD and the significance was determined using two-way ANOVA with Tukey's multiple comparisons test, color of asterix indicate the groups which are compared. a, N=13, N=13, N=13, N=6, N=9 patients for unstim, S1, S2, N, and M conditions respectively. b, N=16, N=15, N=9, N=7 patients for unstim, S1+S2, N, and M conditions respectively. e, N=21, N=13, N=12 for mild, severe, and ICU patients, respectively. f, =21, N=13, N=10 for mild, severe, and ICU patients, respectively. during ICU stay. Significance of the results was determined using two-way ANOVA with Tukey's multiple comparisons test. For S-specific N=19, N=10, and N=12 patients for mild, severe, and ICU cohorts respectively. For N-specific N=21, N=10, and N=7 patients for mild, severe, and ICU cohorts respectively.

a,b, S-RBD IgG (a) and N IgG (b) titers were determined in the mild, severe, and ICU cohorts. c-f, Correlation between N IgG and RBD IgG titers (c), frequency of S-specific CD4+ T cells and RBD IgG titers (d), RBD IgG titers and days after symptoms (e), and frequency of S-specific CD4+ T cells and days after symptoms (f) were assessed in mild, severe, and ICU patients. Circles indicate samples obtained after clearance of symptoms during recovery phase. Squares indicate samples obtained during ICU stay. c-f, P and R values are shown for the correlation calculated for each cohort separately. a-c,e, N=22, N=12, and N=21 patients for mild, severe, and ICU cohorts respectively. d,f, N=22, N=12, and N=21 patients for mild, severe, and ICU cohorts respectively.

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Authors declare no competing interests.