key: cord-0789234-1u3vv5ji
authors: Anft, Moritz; Paniskaki, Krystallenia; Blazquez-Navarro, Arturo; Doevelaar, Adrian; Seibert, Felix S.; Hölzer, Bodo; Skrzypczyk, Sarah; Kohut, Eva; Kurek, Julia; Zapka, Jan; Wehler, Patrizia; Kaliszczyk, Sviatlana; Bajda, Sharon; Thieme, Constantin J.; Roch, Toralf; Konik, Margarethe Justine; Berger, Marc Moritz; Brenner, Thorsten; Kölsch, Uwe; Meister, Toni L.; Pfaender, Stephanie; Steinmann, Eike; Tempfer, Clemens; Watzl, Carsten; Dolff, Sebastian; Dittmer, Ulf; Abou-El-Enein, Mohamed; Westhoff, Timm H.; Witzke, Oliver; Stervbo, Ulrik; Babel, Nina
title: COVID-19-induced ARDS is associated with decreased frequency of activated memory/effector T cells expressing tissue migration molecule CD11a++
date: 2020-10-08
journal: Mol Ther
DOI: 10.1016/j.ymthe.2020.10.001
sha: 3f199ad38be0d1b67016926038d74150ebb30ea6
doc_id: 789234
cord_uid: 1u3vv5ji

Preventing the progression to acute respiratory distress syndrome (ARDS) in COVID-19 is an unsolved challenge. The involvement of T cell immunity in this exacerbation remains unclear. To identify predictive markers of COVID-19 progress and outcome, we analyzed peripheral blood of 10 COVID-19-associated ARDS patients and 35 mild/moderate COVID-19 patients, not requiring intensive care. Using multi-parametric flow cytometry, we compared quantitative, phenotypic and functional characteristics of circulating bulk immune cells, and SARS-CoV-2 S-protein reactive T cell between the two groups. ARDS patients demonstrated significantly higher S-protein reactive CD4+ and CD8+ T cells compared to non-ARDS patients. Of interest, comparison of circulating bulk T cells in ARDS patients to non-ARDS patients demonstrated decreased frequencies of CD4+ and CD8+ T cell subsets with activated memory/effector T cells expressing tissue migration molecule CD11a++. Importantly, survival from ARDS (4/10) was accompanied by a recovery of the CD11a++ T cell subsets in peripheral blood. Conclusively, data on S-protein reactive polyfunctional T cells indicate the ability of ARDS patients to generate antiviral protection. Furthermore, decreased frequencies of activated memory/effector T cells expressing tissue migratory molecule CD11a++ observed in circulation of ARDS patients might suggest their involvement in ARDS development and propose CD11a-based immune signature as a possible prognostic marker.

The SARS-CoV-2 pandemic has confronted the global population with tremendous health, social, and economic challenges. SARS-CoV-2 infections have a broad spectrum of manifestations, ranging from mild to severe symptoms, encompassing pneumonia, acute respiratory distress syndrome (ARDS) and multi-organ failure 1,2 . Usually, a protective role of cellular immunity able to control viral infections is assumed [3] [4] [5] . However, an overwhelming immune response after viral infections leading to cell damage and organ failure was also reported 6 . Given that the host immune response to SARS-CoV-2 remains poorly understood, efforts are ongoing to characterize further both cellular and humoral host defense mechanisms. The current lack of knowledge surrounding the SARS-CoV-2 immune response also makes it difficult to interpret COVID-19 disease pathogenesis and potentially impedes vaccine development.

Despite the many similarities of the immune response to SARS-CoV-2 and SARS-CoV-1 7 , it is currently not clear if the disease severity is caused by uncontrolled virus replication, a hyperreactive immune response, or both [8] [9] [10] . There is mounting evidence that a cytokine storm with a high level of interleukin (IL)-6 production is associated with severe disease 2,11,12 suggesting a pathological immune dysregulation. Furthermore, immune paralysis has also been suggested 13 based on single-cell RNA sequencing, demonstrating an increase in CD4 + T cells and a decrease in CD8 + T cells in bronchial lavage samples from clinically wellcharacterized patients [14] [15] [16] . In contrast, markedly lower immune cell numbers and decreased activation levels of specific subsets of T cells have been associated with critical COVID-19 manifestations [17] [18] [19] . It has further been observed that a deficiency of Toll-like receptor 7 (TLR7), which is important for pathogen recognition and activation of innate immunity, results in a lack of interferon-gamma (IFNγ), which may lead to uncontrolled virus replication and ARDS development 20 . There are, however, conflicting data on the association of IFN-γ and COVID-19 severity 19, 21 .

Several recent studies have shown that hyperreactive immunity contributes to critical COVID-19 manifestations 16, 18, [22] [23] [24] [25] . One of these studies demonstrated detectable Spike proteinreactive T cells levels in COVID-19 patients with ARDS 25 . However, their role in the development of COVID-19-related ARDS remains unclear. Here, we perform a comparative analysis of S-protein reactive T cells collected from ARDS patients and non-ARDS patients to study the contribution of cellular immunity to disease progression. Moreover, we profile circulating T cells displaying an activated memory phenotype and migratory capacity using multiparametric flow cytometry to explore the T cell migration patterns associated with ARDS development. A detailed characterization of non-specific and SARS-CoV-2-reactive cellular and humoral immunity in a cohort of patients with different disease severity, as well as a healthy cohort, is presented here. This study may contribute to understanding the immune system's role in COVID-19 progression.

J o u r n a l P r e -p r o o f Six (6/10; 60.0%) of the ARDS patients succumbed to the infection, while four (4/10; 40.0%) of the ARDS patients survived and could be transferred from the intensive care unit to regular care about a month after enrollment in the study. All COVID-19 control patients recovered within approximately two weeks and were discharged. The detailed characteristics of study patients, study design, blood sampling, and therapy are presented in Table 1, Table S1 , and Fig. 1 . There were no statistically significant differences in age between the analyzed groups. A similar analysis could not be conducted for gender since all ARDS patients were male. Nevertheless, to exclude a potential bias of the results caused by the gender mismatch between the groups, we performed a bivariate regression analysis for all relevant factors (Table S2) ) and described in more details in the corresponding parts of results.

The absolute counts of circulating leukocytes, including lymphocytes, granulocytes, and monocytes, were below the reference level at first and at the follow-up visit for most patients (Fig. S1 ). At the initial visit, ARDS patients showed significantly lower lymphocyte, CD3 + T cell, and NK cell counts than the control group. Furthermore, we observed a significantly higher eosinophil count in ARDS patients at the initial visit.

To exclude patient-specific variations caused by lymphopenia, the analysis of the T cell compartments was based on relative values. For the initial visit, the relative frequency of lymphocytes within the leukocyte population was significantly lower in the ARDS group ( Fig. S1H ). At the same time, no significant differences were observed in subtypes of T cells in this group (Fig. S1I-K) . Interestingly, after the improvement of COVID-19 symptoms, the differences in the distribution of the lymphocyte frequency for the COVID-19 control group and ARDS survivors decreased. However, no general conclusion should be made from this observation due to the low number of ARDS survivors. The bivariate regression analysis J o u r n a l P r e -p r o o f found no evidence of a confounding effect of gender for the differences in circulating leukocytes between the two groups (P>0.05, Table S2 ).

Next, we analyzed whether ARDS patients were able to generate a SARS-CoV-2-reactive T cell response and how this response differed between the ARDS and COVID-19 control group. At the initial visit, we found more ARDS patients with detectable SARS-CoV-2reactive CD4 + CD154 + T cells as compared to the control group (10/17; 58.8% vs. 8/10; 80.0%, respectively); however, this difference was not statistically significant (Table S3 ). The number of patients with detectable S-protein-reactive CD4 + T cells increased to 100.0% at follow-up in both groups (12/12 vs. 4/4, respectively) (Table S3) . Interestingly, during the whole observation period, a lower percentage of patients in the COVID-19 control group had detectable CD8 + CD137 + T cells (Initial visit: 7/17; 41.2%, Follow-up: 5/12;41.7%), whereas, in the ARDS group, the frequency was comparable to that of CD4 + CD154 + T cells (Initial visit: 8/10;80.0% and Follow-up: 4/4; 100.0%). However, none of these differences were statistically significant, and caution is advised in the interpretation of these results, due to the low number of ARDS survivors in our study cohort.

Furthermore, we compared the magnitude of T cell responses between the groups. At the initial visit, we found a significantly higher frequency of S-protein reactive CD4 + CD154 + and CD8 + CD137 + T cells in ARDS patients as compared to controls (Fig. 2) . The absolute counts of S-protein reactive T cells showed statistically significant differences only for CD8 + CD137 + . CD4 + CD154 + T cells demonstrated a tendency toward a higher number in ARDS patients but did not reach statistical significance, presumably due to general lymphopenia (Fig. S2 ). Looking at CD4 + T cells, we further detected a significant difference in the frequency of CD4 + CD154 + T cells producing IL-2 ( Fig. 2A ). Similar to CD4 + CD154 + cells, the data on absolute counts of IL-2 producing CD4 + CD154 + T cells did not reach statistical significance due to lymphopenia (Fig. S2A ). Although we found significantly higher frequencies and counts for CD8 + CD137 + cells in ARDS patients, the number of S-protein-reactive CD8 + CD137 + T cells was generally very low, and no interpretation of the differences in cytokine-producing CD8 + CD137 + T cells could be achieved. Interestingly, despite the low number of ARDS survivors (4/10), these patients still showed significantly higher CD8 + CD137 + cell counts at the follow-up visit. We found no evidence of a confounding effect of gender for the encountered differences between ARDS patients and COVID-19 control and in SARS-CoV-2-reactive T cells (P>0.05, Table S2 ).

Polyfunctional T cells, defined by expression of more than one cytokine, have been described as a hallmark of protective immunity in viral infections 26 . Thus, we evaluated the combined expression of IL-2, TNF-α, IFN-γ, and Granzyme B. At both visits the CD4 + T cell response was dominated by double cytokine-producing T cells in ARDS patients and the COVID-19 control (Table S4) . While all ARDS patients demonstrated bi-functional CD4 + T cells, only 70%-80% of patients in the COVID-19 control showed double cytokine-producing CD4 + T J o u r n a l P r e -p r o o f cells + . CD4 + T cells simultaneously producing 3 or 4 cytokines were detected in fewer patients for both groups at the initial visit. However, at follow up, 100% of ARDS patients demonstrated detectable tri-functional CD4 + T cells as compared to only 53 % in the control group. A similar prevalence of bi-functional cells was found for CD8 + T cells, with the number of patients with detectable 3-and 4-functional CD8 + T cells being lower in both groups. However, comparing both groups at the initial and follow up visits, we observed a significantly higher prevalence of patients with tri-functional CD8 + T cells in ARDS patients, as compared to the COVID-19 controls.

To better evaluate the specificity of the findings on S-protein reactive T cells in COVID-19 patients, we analyzed S-protein reactive T cells in blood samples of a small cohort of SARS-CoV-2 unexposed healthy donors (n=10) and compared them to the COVID-19 control group (Fig. S3) . While a general tendency for more S-protein reactive T cells with significant differences for CD4 + CD154 + , CD4 + CD154 + IL-2 +, and CD4 + CD154 + TNFa + were observed in COVID-19 patients, a CD4 + and CD8 + T cell response against the S-protein was also detectable in several SARS-CoV-2 unexposed, healthy donors. As already demonstrated in previous studies 27, 28 , these findings might indicate reactivity against common cold corona viruses [29] [30] [31] in non-COVID-19 subjects.

The activation of B cells by CD4 + T cells is crucial for the induction of a robust antibody response. As expected, we found a correlation between humoral and cellular immunity. Samples with detectable SARS-CoV-2-reactive CD4 + CD154 + T cells had significantly higher antibody titers, independent of the visit time points (Fig. 2C) . Moreover, among the samples with a detectable anti-SARS-CoV-2 CD4 + response, both frequency and counts of CD4 + CD154 + T cells correlated significantly with the magnitude of the humoral response (Fig. S2C) . Importantly, we also observed a strong correlation between antibody titers and the 50% neutralization dose (Fig. 2 C) indicating neutralizing capacity of the majority of anti-SARS-CoV-2 antibodies.

ARDS is associated with decreased frequencies of lymphocytes with a differentiated and activated cytotoxic phenotype Given the observed increased magnitude of antiviral T cell responses in ARDS patients, we further explored the activation/differentiation status of T cells in the peripheral circulation. We evaluated and compared the alteration of various T and B cell subsets between ARDS patients and COVID-19 controls at the initial and at follow-up visits (Fig. 3) . ARDS patients displayed a significantly lower number of central memory CD4 + cells, but not CD8 + cells ( Fig. 3A-B ). No significant difference was observed for TEMRA cells. However, a strong trend toward a reduced CD8 + cell count in the ARDS population at the initial visit was observed (p=0.08) ( Fig. 3C-D) . We then analyzed the expression of MHC-Class II HLA-DR, which is expressed on activated and proliferating T cells, CD57, which is mainly expressed on highly cytotoxic but senescent T cells and CD28, which is a co-stimulatory molecule and essential for T cell activation, survival and proliferation [32] [33] [34] . We found significantly lower J o u r n a l P r e -p r o o f frequencies of T cells with an activated effector phenotype expressing HLA-DR ( Fig. 3E -F) in ARDS patients compared to COVID-19 controls. While no clear effect on CD57 + was observed ( Fig. 3G-H) , a significant reduction of CD28 + CD4 + T cells but not CD28 + CD8 + T cells was also observed in ARDS patients ( Fig. 3I-J) . Interestingly, we found significantly lower frequencies of CD11a-expressing CD4 + and CD8 + T cells in all ARDS patients ( Fig.  3K -L). In the B cell compartment, we found a significant reduction in the frequencies of transitional CD19 + cells in all ARDS patients (Fig. 3M ). At the same time, no effect of disease severity was observed on marginal zone B cells or plasmablasts ( Fig. 3N-O) . With the improvement of the clinical manifestations at the follow-up visit, the differences between the two groups became less marked, except for the frequencies of transitional CD19 + cells, which remained low for all ARDS patients (Fig. 3M ).

Overall, we observed a decrease in the frequency of activated and differentiated effector T cells in the peripheral circulation of ARDS patients. We further analyzed the changes in the T cell subsets for the four ARDS survivors (Fig. 4) . Interestingly, despite the low patient numbers, a significant recovery of the reduced frequencies of CD11a ++ T cells among CD4 + and CD8 + (Fig. 4A -B) was observed. We could find a significant increase in CD8 + CD11a ++ cells expressing HLA-DR, CD28, and CD57 ( Fig. 4D , F). CD4 + CD11a ++ cells expressing HLA-DR, CD28, and CD57 also increased, however, without reaching statistical significance ( Fig. 4C , E, H). Importantly, a comparison with a small cohort of patients on mechanical ventilation due to non-COVID-19 pneumonia and sepsis seemed to support the hypothesis that the observed alterations were specific for SARS-CoV-2 infection (Fig. S4 ).

In addition, bivariate regression was performed to exclude a possible confounding effect of gender for the identified cellular alterations (Table S2) . Here, a potential confounding gender effect for CD4 + CD11a ++ was observed. However, this effect can be neglected, since the same ARDS patients showed a very strong recovery for the described subsets at follow-up (Fig.  S4A ). For the other markers significantly associated with COVID-19 ARDS, no significant gender effect was found (Table S2) .

To confirm that the observed results were not due to the differences in follow up duration, we performed additional analyses using samples of both groups obtained at similar time points in days after initial diagnosis (7 [3] [4] [5] [6] [7] [8] [9] [10] days for the COVID-19 control vs. 8 [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] days for the ARDS cohort; P=0.766). The comparison was performed for all markers that showed significant differences at the initial visit (Fig. S5 ). With all of these precautions in place, the differences in leukocyte subsets were still found to be significant, except for the eosinophil counts ( Fig. S5A-E) , where the difference detected at the initial visit disappeared with time. While no differences were observed for CD4 + CD154 + cells, an apparent difference remained for CD8 + CD137 + cells ( Fig. S5F-H) . Importantly, none of the differentiation and activation markers associated with ARDS showed evidence for a bias of time: for CD4 + CM, CD4 + HLA-DR + , CD8 + HLA-DR + , CD4 + CD11a ++ , CD8CD11a ++ , CD4 + CD28 + and transitional B cells a

Here we present a comprehensive immune profiling study in a cohort of 45 COVID-19 patients, where 35 patients had mild to moderate symptoms, and ten patients suffered from severe COVID-19-associated ARDS. Our data suggest an intriguing association with the quantitative composition and functionality of several immune cell subsets and the clinical manifestation of COVID-19, pointing to a potential pathogenic immune response in ARDS patients. The most potent SARS-CoV-2 specific T cell immunity was detected in patients with the worst lung tissue damage, similar to findings described in previous studies 35 . Furthermore, this is a hitherto unreported significant and temporary reduction of circulating CD11a ++ T cells, suggesting that migration of these cells from the vasculature into the adjacent tissue followed by a specific immune reaction may constitute a pathophysiological mechanism for tissue injury in COVID-19.

Impaired immune regulation and increased inflammation have been reported for patients with SARS-CoV-2-related ARDS 18, 25 . Patients with ARDS showed IL-6-driven hyperinflammation and T and B cell lymphopenia 18 . In line with these findings, we found lower numbers of circulating T and B cell subsets in COVID-19-associated ARDS patients compared to mild/moderate COVID-19 control patients. The ARDS group had significantly lower frequencies of T cell subsets with advanced differentiation, activation, and functional properties, that are known to be involved in immune activation and cytotoxic response against foreign antigens [36] [37] [38] . The reason for the reduction in these effector T cells in the circulation of this group of patients is not yet fully understood. It could potentially be caused by activationinduced apoptosis or by inflammation-triggered cell migration 39 . The latter is more plausible given that CD11a is a key T cell integrin, essential for T cell activation and migration 40 . This hypothesis is further supported by the clinical improvement in the four ARDS survivors being accompanied by a normalization of the frequency of CD11a ++ T cells in the peripheral blood.

Although the information is sparse, several groups have reported on lung infiltrating T cells in COVID-19 patients to a more considerable degree than observed for influenza infection 41, 42 . An increase in CD4 + T cells and a decrease in CD8 + T cells in patients with severe manifestations have been identified using single-cell RNA sequencing of bronchoalveolar lavage from COVID-19 patients 14, 43 . Furthermore, a negative association between IL-6 serum levels, a cytokine known to upregulate the expression of the migratory chemokine receptors CXCR6 and CCR5 on memory T cells 44 and the number of T cells in the circulation have been observed 45, 46 . There are also reports showing increased expression of CXCR6 on lung T cells, as compared to peripheral blood T cells 47, 48 . As such, we deem it a likely hypothesis that lymphocyte migration into tissues, triggered by inflammation, may be responsible for the reduction of activated terminally differentiated T cell subsets in the peripheral blood. This hyposthesis should be tested in future studies, keeping in mind that lungs might not be the only target for the migrating T cells, as extrapulmonary manifestations of COVID-19 have been reported [49] [50] [51] [52] [53] .

Our findings support the proposed hypothesis of immunopathogenesis as a leading cause of COVID-19 severe morbidity and mortality 10, [54] [55] [56] . In the studied patients, we observed an increased frequency of SARS-CoV-2 S-protein-reactive CD4 + and CD8 + T cells in the ARDS group. The antiviral activity of the detected T cells could be confirmed by their polyfunctionality as defined by the simultaneous release/expression of several cytokines 26 . The magnitude of the S-protein-reactive T cell response is also comparable with earlier data reported on S-protein-reactive T cells in patients with COVID-19-associated ARDS 25 . The reason for the observed higher number of SARS-CoV-2-reactive T cells in ARDS patients might potentially be explained by a disturbed migration of antigen-specific cells into the infected tissue leading to impaired viral clearance. Another explanation is the unspecific migration of effector T cells into this area through bystander activation, leading to increased inflammation within infected tissue and the relative abundance of S-protein-reactive T cells in the circulation. Therefore, the evaluation of S-protein reactive T cells expressing the tissue homing marker CD11a may be an important prognostic tool to understand the migratory behavior of antiviral T cells and should be performed in following studies. However, it is also possible that the composition of the peripheral immune cells mirrors the situation in the infected tissue, where severe virus infection with high antigen load lead to generation of the large number of antigen-reactive effector T cells causing injury of the affected organ.

Although the protective capacity of SARS-CoV-2-reactive T cells still needs to be evaluated, COVID-19 disease progression was accompanied by a higher magnitude of IL-2-, IFN-γ-and TNF-α-producing cells. This finding has important clinical implications in terms of the potential therapeutic effects of immunosuppressive approaches at this stage of the disease. Indeed, recent studies described a positive effect of anti-IL-6 or anti-IL-1 therapy, with similar observations reported in the Randomised Evaluation of COVID-19 Therapy (RECOVERY) study (NCT04381936) for Dexamethasone in ARDS patients 18, 24, 55, 57, 58 .

In conclusion, the data presented here are supportive of immune pathogenesis as an underlying cause of COVID-19-associated ARDS. Additionally, the identified CD11a-based immune signature could be used as a novel prognostic marker for disease progression. Since most immunodiagnostic laboratories already offer the proposed marker analysis, multi-center evaluation of this marker should be contemplated, so it can readily be utilized for patient monitoring in the current pandemic.

Forty-five patients with a mild and moderate COVID-19 course (COVID-19 Control; n=35) or COVID-19-associated ARDS (ARDS; n=10) consecutively admitted to University Hospitals Essen and Bochum, Germany, were recruited into the study. The classification of COVID-19 manifestation was performed following Siddiqi and Mehra, 2020 1 . Subjects were eligible for enrollment if they met the following inclusion criteria: (i) a positive SARS-CoV2 PCR test and (ii) signed written informed consent. The patients of COVID-19 Control were recruited after COVID-19 diagnosis (initial visit). For ARDS patients, recruitment took place at the first available time point after ARDS diagnosis. The second sample was available after clinical improvement at patient discharge (follow-up visit). A small cohort of patients with non-COVID-19 pneumonia requiring mechanical ventilation (n=3), and SARS-CoV-2 unexposed healthy donors (n=10) recruited before COVID-19 pandemics were also included as controls.

Demographics and clinical characteristics of patients are shown in Table 1 and Supplementary  Table S1 .

Peripheral blood was collected in S-Monovette K3 EDTA blood collection tubes (Sarstedt). Collected blood was pre-diluted in PBS/BSA (Gibco) at a 1:1 ratio and underlaid with 15 mL Ficoll-Paque Plus (GE Healthcare). Tubes were centrifuged at 800 g for 20 minutes at room temperature. Isolated PBMCs were washed twice with PBS/BSA and stored at -80°C until use as previously described 59 . 6 PBMCs were thawed and plated for each condition in 96-UWell Plates in RPMI media (Life Technologies), supplemented with 1% Penicillin-Streptomycin-Glutamine (Sigma Aldrich), and 10% FCS (PAN-Biotech) and were stimulated or left untreated as a control for 16 hours. As a positive control, cells were stimulated with SEB (1 µg/ml, Sigma Aldrich) and negative control was with vehicle (a medium to dissolve peptide pools). After 2 hours, Brefeldin A (1µg/ml, Sigma Aldrich) was added. As previously applied by our groups and others, antigenspecific responses were considered positive after the non-specific background was subtracted, and more than 0.001% or at least 15 positive cells were detectable 5, 61 . Negative values were set to zero. Flow cytometry EDTA-treated whole blood was stained with optimal concentrations of each antibody for 10 minutes at room temperature in the dark. Erythrocytes were lysed using VersaLyse (Beckman-Coulter) with 2.5% IOTest 3 Fixative Solution (Beckman-Coulter) for 30 minutes at room temperature in the dark. Samples for general phenotyping were immediately acquired, while samples for T-and B cell subsets were washed twice with PBS/BSA. Samples for the B cell subset were washed twice with PBS prior to staining with antibodies.

T cells stimulated with SARS-Cov-2 OPP were stained with optimal concentrations of antibodies for 10 minutes at room temperature in the dark. Stained cells were washed twice with PBS/BSA before preparation for intracellular staining using the Intracellular Fixation & Permeabilization Buffer Set (Thermo Fisher Scientific) as per manufacturer's instructions. Fixed and permeabilized cells were stained for 30 minutes at room temperature in the dark with an optimal dilution of antibodies against the intracellular antigen.

All samples were immediately acquired on a CytoFlex flow cytometer (Beckman Coulter). Quality control was performed daily using the recommended CytoFlex Daily QC Fluorospheres (Beckman Coulter). No modification to the compensation matrices was required throughout the study.

Peripheral blood was collected in S-Monovette Z-Gel (Sarstedt). SARS-CoV-2 IgG titers were analyzed in purified serum using a SARS-CoV-2 IgG kit (EUROIMMUN, Lübeck, Germany). The test was performed according to the manufacturer's instructions. Briefly, serum samples were diluted 1:100 and added to plates coated with recombinant SARS-CoV-2 antigen. Bound SARS-Cov-2 S1 protein-specific IgG was detected by an HRP-conjugated anti-human IgG. The absorbance was read on a microplate reader at 450 nm with reference at 620 nm and evaluated as the ratio the absorbance of the sample to the absorbance of the internal standard.

To determine the capacity of serum antibodies to neutralize the virus, a propagationincompetent VSV*DG (firefly luciferase) pseudovirus system bearing the SARS-CoV-2 spike protein in the envelope was employed. The pseudovirus system was incubated with serial dilutions of sera prior to the infection of Vero E6 cells employing pseudovirus. Vero E6 cells were maintained in Dulbecco's minimal essential medium (Life Technologies, Zug, Switzerland) supplemented with 10% fetal bovine serum and non-essential amino acids (Life Technologies). 18 hours after infection, firefly luciferase reporter activity was determined. The 50% neutralization dose was determined as the reciprocal antibody dilution causing 50% inhibition of the calculated luciferase reporter.

Flow cytometry data were analyzed using FlowJo version 10.6.2 (BD Biosciences); gating strategies are presented in Fig. S6 -S10. For the analysis of anti-SARS-CoV-2 T cells, a threshold of 0.001% was employed to define a detectable response. For the analysis of the antibody neutralization dose, the data were log-transformed, assigning a value of zero for those with a value below the detection limit. Here, extremely high values were excluded from analysis; these were determined based on Tukey's fences (k=3), estimated for all values with a detectable response.

Statistical analysis was performed using R 62 , version 3.6.2. Categorical variables are summarized as numbers and frequencies; quantitative variables are reported as median and interquartile range. Box plots depict the median and the first and third quartiles. The whiskers correspond to 1.5 times the interquartile range. All applied statistical tests are two-sided. Unless otherwise stated, differences between groups for categorical variables were calculated using Fisher's exact test. Differences in quantitative variables between groups are analyzed using the Mann-Whitney U test. The dynamics of quantitative variables were analyzed employing the paired t-test, assuming a normal distribution for the differences between the initial and follow-up visit. Correlation size and significance were calculated using Spearman's correlation coefficient. Bivariate regression analysis was performed to exclude potential bias in the analysis due to the unbalanced distribution of the biological sex within the groups. Thus, for factors significantly associated with illness severity, regression analysis was performed with sex and COVID-19 severity as independent variables, without interactions. P values below 0.050 were considered significant; only significant P values are reported in the figures. P values were not corrected for multiple testing, as this study was of exploratory nature 63 .

The study was approved by the ethical committee of the Ruhr-University Bochum and University Hospital Essen (20-9214-BO). Written informed consent was obtained from all participants. Figure 1 : Study outline. 45 patients consecutively admitted to Marienhospital Herne -Universitätsklinikum der Ruhr-Universität Bochum (North Rhine-Westphalia, Germany) and Universitätsklinikum Essen (North Rhine-Westphalia, Germany) were enrolled in this study. The patients were classified based on their symptoms as non-critical COVID-19 course (COVID-19 Control) or COVID-19-associated ARDS (ARDS). The patients were analyzed at two time points: Shortly after hospitalization (initial visit) and after clinical improvement (follow-up visit). For the ARDS group, the initial visit corresponds to the first available visit after ARDS symptoms are observed, the follow-up visit corresponds to discharge from ICU. The profiling included evaluation of SARS-CoV-2 S-protein specific IgG serum antibodies, as well as phenotyping of all major immune cell populations by flow cytometry, and characterization of B and T cell subsets. T cells reactive to the SARS-CoV-2 S-protein were also analyzed by application of overlapping peptide pools.

The presence and functional status of SARS-CoV-2-reactive T cells was evaluated using PBMCs, isolated from the peripheral blood of 27 patients (17 COVID-19 control, in white, and 10 ARDS, in grey). Defrosted PBMCs rested for 24 hours before treatment with overlapping peptide pools covering immune dominant regions of the SARS-CoV-2 S-protein.

The cells were stimulated for a total of 16 hours and in the presence of Brefeldin A for the last 14 hours. The complete gating strategy is presented in Fig. S6 . No measurements of IgG antibodies were available for ARDS patients. (A) CD4 + CD154 + frequency (first row) for ARDS and COVID-19 Control patients at the initial visit (left boxplots) and follow-up (right boxplots), and frequencies of CD4 + CD154 + cells expressing granzyme B (GrB), INF-γ, IL-2, and TNF-α (row two to four). (B) CD8 + CD137 + frequency (first row) for ARDS and COVID-19 Control patients at the initial visit (left boxplots) and follow-up (right boxplots), and frequencies of CD8+CD137+ cells expressing granzyme B (GrB), INF-γ, IL-2, and TNF-α among (row two to four). (C) On the left side: Comparison of the relative titers of SARS-CoV-2 S-protein specific IgG antibodies, measured by ELISA and evaluated as ratio to an internal control for samples with SARS-CoV-2 specific CD4 + T cells; comparison of the relative titers classified depending on whether they had detectable virus-specific CD4 + T-cells and correlation of the relative titers with the frequency of virus-specific CD4 + T-cells. On the right side, comparison of the relative titers of SARS-CoV-2 S-protein specific IgG antibodies with the 50% neutralization dose. For the analysis of the antibody neutralization dose, the data were log-transformed, assigning a value of zero for those with a value below the detection limit.

Peripheral blood from 37 patients from the COVID-19 Control (n=27, in white) or ARDS (n=10, in gray) groups was subjected to evaluation for differentiation and activation state of T and B cell subsets using multiparametric flow cytometry. The subsets of the CD3 + T cells and the CD19 + B lymphocyte were identified according to the gating strategy depicted in Fig. S8 -S10. In all cases, the left boxplots show the data for the initial visit, while the right boxplots depict the data at follow-up. The shaded area indicates the reference range as detected in healthy individuals. q q q q q q q q q q q q qq q q q q qq q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q qq q q q q qq q q q q q q q q q q q q q q q q q q q 

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Beneficial effects of colchicine for moderate to severe COVID-19: an interim analysis of a randomized, double-blinded, placebo controlled clinical trial

Remdesivir for the Treatment of Covid-19 -Preliminary Report

Dexamethasone in Hospitalized Patients with Covid-19 -Preliminary Report

Phenotype and kinetics of SARS-CoV-2-specific T cells in COVID-19 patients with acute respiratory distress syndrome

Functional Heterogeneity of Memory CD4 T Cell Responses in Different Conditions of Antigen Exposure and Persistence

SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19

Targets of T cell responses to SARS-CoV-2 coronavirus in Humans with COVID-19 disease and unexposed individuals

Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans

SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls

SARS-CoV-2 reactive T cells in uninfected individuals are likely expanded by beta-coronaviruses

An enigmatic tail of CD28 signaling

CD57 in human natural killer cells and T-lymphocytes

Flow cytometric analysis of activation markers on stimulated T cells and their correlation with cell proliferation

Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications

Characterization of Human CD8 T Cell Responses in Dengue Virus-Infected Patients from India

CD8+CD28− and CD8+CD57+ T cells and their role in health and disease: CD8+CD28− (CD8+CD57+) T cells in health and disease

High Cytotoxic and Specific Migratory Potencies of Senescent CD8+CD57+ Cells in HIV-Infected and Uninfected Individuals

Single-cell landscape of immunological responses in patients with COVID-19

LFA-1 in T Cell Migration and Differentiation

Pathological findings of COVID-19 associated with acute respiratory distress syndrome

Pulmonary Vascular Endothelialitis, Thrombosis, and Angiogenesis in Covid-19

Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients

Enhanced T cell responses to IL-6 in type 1 diabetes are associated with early clinical disease and increased IL-6 receptor expression

Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus Disease 2019 (COVID-19)

Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients

CC Chemokine Receptor 5 and CXC Chemokine Receptor 6 Expression by Lung CD8+ Cells Correlates with Chronic Obstructive Pulmonary Disease Severity

Expression of CXCR6 and its ligand CXCL16 in the lung in health and disease

Extrapulmonary manifestations of COVID-19

Multiple organ infection and the pathogenesis of SARS

Organ distribution of severe acute respiratory syndrome (SARS) associated coronavirus (SARS-CoV) in SARS patients: implications for pathogenesis and virus transmission pathways

Immune monitoring facilitates the clinical decision in multifocal COVID-19 of a pancreas-kidney transplant patient

Allograft infiltration and meningoencephalitis by SARS-CoV-2 in a pancreas-kidney transplant recipient

How does SARS-CoV-2 cause COVID-19?

E (2020). T cell responses in patients with COVID-19

Longitudinal analyses reveal immunological misfiring in severe COVID-19

Interleukin-1 blockade with high-dose anakinra in patients with COVID-19, acute respiratory distress syndrome, and hyperinflammation: a retrospective cohort study

Tocilizumab for severe COVID-19 pneumonia

The Role of pre-existing cross-reactive central memory CD4 T-cells in vaccination with previously unseen influenza strains

Preliminary Identification of Potential Vaccine Targets for the COVID-19 Coronavirus (SARS-CoV-2) Based on SARS-CoV Immunological Studies

BK-VP3 as a new target of cellular immunity in BK virus infection

R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing

An introduction to multiplicity issues in clinical trials: the what, why, when and how

We want to express our deepest gratitude to the patients who donated their blood samples and clinical data for this project. This work was supported by grants from the Mercator Foundation (St-2018-0014), BMBF e:KID (01ZX1612A), BMBF NoChro (FKZ 13GW0338B) and SepsisDataNet (EFRE-0800984).

The authors declare no competing interests.J o u r n a l P r e -p r o o f