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Integrated immune dynamics define correlates of COVID-19 severity and antibody responses

Summary SARS-CoV-2 causes a spectrum of COVID-19 disease, the immunological basis of which remains ill defined. We analyzed 85 SARS-CoV-2-infected individuals at acute and/or convalescent time points, up to 102 days after symptom onset, quantifying 184 immunological parameters. Acute COVID-19 presented with high levels of IL-6, IL-18, and IL-10 and broad activation marked by the upregulation of CD38 on innate and adaptive lymphocytes and myeloid cells. Importantly, activated CXCR3+cTFH1 cells in acute COVID-19 significantly correlate with and predict antibody levels and their avidity at convalescence as well as acute neutralization activity. Strikingly, intensive care unit (ICU) patients with severe COVID-19 display higher levels of soluble IL-6, IL-6R, and IL-18, and hyperactivation of innate, adaptive, and myeloid compartments than patients with moderate disease. Our analyses provide a comprehensive map of longitudinal immunological responses in COVID-19 patients and integrate key cellular pathways of complex immune networks underpinning severe COVID-19, providing important insights into potential biomarkers and immunotherapies.

Correspondence kkedz@unimelb.edu.au In brief Koutsakos et al. perform a broad analysis of 184 immune features using blood samples from 85 COVID-19 cases across time and severity groups. The study defines circulating T FH 1 cells as a correlate of antibody responses and sIL-6R, IL-6, and IL-18 as correlates of disease severity.

INTRODUCTION
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused >101 million infections and 2.18 million deaths worldwide (as of January 28, 2021). Infection with SARS-CoV-2 results in a spectrum of clinical presentations, called coronavirus disease 2019 (COVID- 19), ranging from asymptomatic to fatal disease. Disease severity has been associated with risk factors, including age, gender, and preexisting comorbidities, 1,2 that correlate with immune responses during acute infection. While robust, broad, and transient immune responses precede patients' recovery in non-severe cases, [3][4][5][6] severe COVID-19 can be associated with exuberant cytokine responses, hyperactivation of innate immune cells and T cells, 4,[6][7][8] and high titers of SARS-CoV-2-specific antibodies. 8 At convalescence, the majority of individuals has SARS-CoV-2specific antibodies and B cell and T cell responses. [9][10][11][12][13] CD4 + T cell responses appear more prominent than CD8 + T cell responses in primary SARS-CoV2 infection. 13,14 Our understanding of immune responses to SARS-CoV-2 informed the development and clinical evaluation of immunomodulatory therapies, including monoclonal antibodies that target the interleukin-6 (IL-6) signaling pathway and corticosteroids such as dexamethasone. 15 However, results from clinical trials examining the efficacies of current therapeutic approaches are inconsistent. 16 In parallel, global accelerated efforts are focused on the development of safe vaccines against SARS-CoV-2, with the main goal of eliciting neutralizing antibodies against the Spike protein. 17 Efforts are needed to understand integrated immune correlates of recovery and protection from COVID-19, and the complexity of innate and adaptive immune perturbations underpinning severe and fatal COVID-19 to inform the rational design of vaccines and identify predictors of protective immunity. symptom onset for immune profiling and serological analyses ( Figure 1B). Acute samples were obtained either during the hospital stay in hospitalized patients or within 2 weeks postsymptom onset for the non-hospitalized individuals (outpatient) ( Figure 1A, in red). Convalescent samples were obtained either after hospital discharge or at the earliest day 26 post-symptom onset for non-hospitalized individuals ( Figure 1A, in blue). Disease severity was determined according to whether the patients recovered at home (mild disease), the hospital ward (moderate disease), or the ICU (severe disease). A total of 66 healthy individuals and 11 non-COVID-19 hospitalized patients were assessed as controls. Our study included 1 ICU patient, no. 1-088, with a hematological malignancy treated with rituximab medication, thus lacking B cells. As this donor had no detectable SARS-CoV-2 antibodies, only cellular and cytokine data were included in the statistical analyses.

Breadth of innate, adaptive, and myeloid immune responses in COVID-19
To understand the dynamics of immune responses to SARS-CoV-2 over time, we analyzed blood from acute and convalescent individuals using 3 multi-parameter flow cytometric panels. The acute group included moderate (ward) and severe (ICU) samples. Using a computational pipeline in the Spectre R package, encompassing the FlowSOM and UMAP (uniform manifold approximation and projection) algorithms, 18 we identified clusters representing major lymphocyte and myeloid lineages and their activation phenotype from the first panel, clusters of adaptive B cell and T cell subsets from the second panel, and cytotoxicity profiles of CD8 + and CD4 + T cells from the third panel ( Figure 1C). The UMAP analysis revealed different subsets of B helper and T H cells according to CD38 and CXCR3, respectively (second panel), and preferentially high expression of granzyme B and perforin on CD8 + effector memory (T EM ) and effector memory CD45RA + (T EMRA ) T cell subsets (third panel) ( Figure 1C). To assess immune profiles between acute and convalescent COVID-19 samples, we combined our FlowSOM clustered data with the data from 14 soluble mediators and plasma receptor binding domain (RBD)-specific immunoglobulin G (IgG), IgM, and IgA antibodies to generate a total of 184 immune features. During acute COVID-19 in hospitalized patients, we observed significant changes in immune compositions compared to healthy controls and/or convalescent samples, particularly a greater proportion of neutrophils, neutrophil-to-lymphocyte and neutrophil-to-T cell ratios, higher proportions of activated populations of CD38 + neutrophils, CD38 + eosinophils, CD38 expression on CD14 + and CD16 + monocytes, CD38 + CD56 dim NK cells, CD38 + gd T cells, antibody-secreting cells (ASCs), PD-1 + ICOS + cT FH cells, CD38 + CD4 + T cells, HLA-DR + CD4 + T cells, and higher proportions of T EMRA -like CD27 À CD45RA + , and CD38 + CD8 + T cells ( Figures 1D, S1, and S2). During convalescence, we found higher proportions of T CM CD8 + T cells, NK cells, T CM , and T EM CD4 + T cells (Figures 1D and S1; Table S4).
To assess immune activation over time, we implemented a time-series algorithm called TrackSOM on the first immunophenotyping panel. TrackSOM is a time series-based clustering and cluster evolution tracking algorithm that combines the single time point clustering capacity of FlowSOM with the tracking by ChronoClust 19 of cluster developments over time. TrackSOM clusters data from all time points using FlowSOM, and thus determines the temporal evolutions of the resulting metaclusters and clusters using the tracking mechanism of ChronoClust. With TrackSOM, we categorized, or ''binned,'' samples into 10 time intervals (''bins'') post-disease onset (i.e., bin 1 = 1-4, bin 2 = 5-8, bin 3 = 9-12 days, and so on) to allow for at least 4 samples (n = 4-15) per time bin (Figures 1E and S3; Table S3). Strikingly, the tracking pattern of the CD38 activation marker indicated dynamic activation of both innate and adaptive cells peaking within weeks 2-4 of disease onset (bins 4-6) before declining at later time bins ( Figure 1E). These patterns were still apparent when we excluded ICU patient no. 1-088, who had continuously high CD38 expression over 4 time points. The expression of HLA-DR was also dynamic across time points, but to a lesser extent. Overall, our analyses revealed differences in immune profiles across the time between acute and convalescent phases, with broad immune activation of innate, adaptive, and myeloid cells.

Rapid and transient activation of innate immune cells during COVID-19
To define the dynamics of innate responses, we compared 14 cytokines/chemokines in moderate and severe acute and convalescent COVID-19 plasma samples over time, in comparison to healthy controls. As IL-6 is a key driver of inflammation in COVID-19, possibly mediating pathology via engaging sIL-6R on cells expressing the gp130 co-receptor, 20 we also measured sIL-6R levels, since the role of sIL-6R in COVID-19 remains unknown. Inflammatory cytokines IL-6, IL-18, and IL-10 were significantly upregulated in acute samples compared to convalescent samples ( Figures 1F, 1G, and S4A), consistent with other studies. [21][22][23] The levels of monocyte chemoattractant protein-1 (MCP-1), interferon-g (IFN-g), and sIL-6R were also higher in acute samples from some patients compared to healthy controls, but these responses were variable ( Figures 1G, S4A, and S4B), possibly reflecting the grouping of all ward and ICU patients in this analysis.
To complement our computational analysis, we applied manual gating ( Figure S5) for immune subsets that contribute to antiviral immunity in COVID-19 and influenza. [24][25][26][27] Manual gating showed significantly higher activation of immune subsets in acute COVID-19 compared to convalescent and healthy donors ( Figure S6A). For innate populations, acute samples had significantly higher proportions of activated HLA-DR + NK cells, CD38 + HLA-DR + gd T cells, and effector-like CD27 -CD45RA + gd T cells, but lower levels of non-classical CD16 + monocytes, compared to convalescent and/or healthy donors (Figures 2A-2C; S6B, and S6C). The number of monocytes and gd T cells were comparable between acute and convalescent samples, while NK cell numbers were significantly lower in the acute samples ( Figure S6D). These highly activated innate cell populations were dynamic, peaking within the first 3-4 weeks and declining thereafter (Figures 2A-2C).
Longitudinal dynamics of B cells, cT FH cells, Th1 CD4 + , and CD8 + T cells in COVID- 19 We next defined immune populations that underpin the induction of humoral and cellular adaptive immunity, B cells, cT FH cells, Th1 CD4 + cells, and CD8 + T cells. We observed significantly higher proportions and numbers of CD38 hi CD27 + ASCs and activated PD-1 + ICOS + CXCR5 + CD4 + cT FH cells ( Figures 2D, 2E, and S6E), a subset of lymphoid T FH cells, in the blood 28 of acute COVID-19 patients compared to subsets in convalescent or healthy donors. Moreover, the activation of cT FH cells by the co-expression of PD-1 and ICOS was attributed more to CXCR3 + cT FH -type 1 (cT FH 1) cells than CXCR3 À cT FH 2/cT FH 17 cells ( Figures 2F and S6E). Proportions of ASCs increased rapidly and transiently at disease onset, while activated cT FH 1 cells gradually increased, peaking after 3-4 weeks, similar to activated innate cells, with cT FH 1 cell numbers maintained at convalescence ( Figures 2G and S6E). There was substantial CD38 + HLA-DR + CD8 + and CD4 + T cell activation during the acute phase, as determined by increased proportions and numbers ( Figure S6F). Both populations peaked earlier within the first 2-3 weeks and declined thereafter for home and ward patients but remained high until weeks 6-7 for ICU patients (Figure 2H). We also observed greater proportions and numbers of activated PD-1 + CD38 + and CXCR3 + CD38 + CD8 + T cells (Figure S6F) and greater proportions of CD27 À CD45RA + T EMRAlike and CD27 À CD45RA À T EM -like CD8 + T cells in acute samples compared to convalescent or healthy controls ( Figure S5G). Similarly, greater proportions of CD27 À CD45RA À T EM CD4 + T cells were detected in acute samples ( Figure S6G). In line with the T H 1 environment of a viral infection, CXCR3 + T H 1 cells highly expressed CD38 with ICOS, factors that were absent in CXCR3 -T H 2/17 cells (Figures 2I and S6F).
To define cytotoxic profiles of CD8 + and CD4 + T cells, the expression of granzyme A, B, K, and M and perforin was assessed. Activated CD38 + HLA-DR + CD8 + T cells in acute samples expressed higher levels of granzyme A and B and perforin compared to healthy and/or convalescent patients ( Figures  S7A and S7B). In addition, activated CD38 + HLA-DR + CD8 + T cells in acute samples had higher proportions of cells expressing multiple cytotoxic molecules, with the majority of CD38 + HLA-DR + CD8 + T cells expressing 3 or 4 cytotoxic molecules (Figure 2J). Although the expression of granzyme B and perforin within CD38 + HLA-DR + CD8 + T cells significantly decreased at convalescence, interestingly, granzyme K and M were increased ( Figures S7A and S7B). The overall diversity of cytotoxic molecule expression, measured by the different combinations of molecules simultaneously expressed per cell, also differed at convalescence as compared to acute COVID-19 and healthy individuals ( Figure 2J).
While modest, activated CD38 + HLA-DR + CD4 + T cells also expressed higher levels of granzyme B in acute samples ( Figures  2J, S7C, and S7D). Similar patterns were found when the expression of granzymes and perforin were analyzed according to their T cell differentiation subsets by FlowSOM analysis ( Figure S8).
Overall, SARS-CoV-2 infection induced a prototypical antiviral adaptive immune response comprising ASCs, activated cT FH 1 cells, activated T H 1 CD4 + T cells, and highly cytotoxic CD8 + T cells that emerged during acute COVID-19 and contracted during convalescence.

Seroconversion and antibody signatures during acute and convalescent COVID-19
As humoral immunity plays a key role in antiviral responses, we analyzed antibodies in acute and convalescent samples from 25 COVID-19 patients across multiple time points, by comparing RBD-specific IgG, IgM, and IgA antibodies by ELISA 9 with healthy controls (Figures 3A and S9). Antibody levels were Article ll OPEN ACCESS significantly higher in acute (log 10 median titer 3.52 IgG, 3.41 IgM, 2.77 IgA) and convalescent COVID-19 samples (log 10 median titer 3.38 IgG, 3.24 IgM, 2.15 IgA) compared to those in healthy, non-exposed individuals (log 10 median titer 1.68 IgG, 2.49 IgM, 2.15 IgA) ( Figure 3B). While IgG and IgM titers were maintained at similar levels between acute and convalescent samples, IgA titers had significantly decreased by convalescence. Paired analysis confirmed a significant increase in antibody titers from the first sampling following admission to just before discharge or at convalescence for all 3 isotypes (Figure 3C). At the first acute blood collection, 84%, 48%, and 68% of individuals seroconverted (log 10 antibody titer > mean + 23 SD of healthy individuals) for RBD-specific IgG, IgM, and IgA antibodies, respectively ( Figure 3D). IgG seroconversion rates increased to 88% and 100% at the last acute blood collection and at convalescence, respectively, although IgM and IgA were maintained at similar frequencies ( Figure 3D). In addition, the proportion of individuals with undetectable RBD-specific IgG, IgM, or IgA antibodies decreased from 20.8% during the acute phase to 0% at convalescence, with 100% of convalescent donors having at least an IgG response to RBD (Figure 3E). Consistently, the levels of RBD-specific IgG, IgM, and IgA antibodies rapidly increased in the first 3 weeks, with IgG and IgM levels being maintained between days 25 and 102 ( Figure 3F). We observed a trend toward decreased IgA levels from day 25 onward ( Figure 3F), but only in 3/25 patients. In addition, we measured Spike-specific antibodies by ELISA and detected higher IgG, IgM, and IgA antibodies against Spike in pooled acute and convalescent COVID-19 samples compared to healthy donors ( Figure 3G).
To determine the neutralizing activity of SARS-CoV-2-specific antibodies, a microneutralization (MN) assay was performed using live SARS-CoV-2 virus infection of Vero cells. 11 Neutralizing antibodies were detected at a low frequency in 3/8 acute patients, but were more prevalent in 11/13 convalescent samples, the latter being significantly higher than healthy non-exposed and hospitalized non-COVID patient control groups ( Figure 3H). Neutralizing activity increased from the acute to the convales-cent phase and was still detectable in 3/3 convalescent donors sampled at $100 days post-symptom onset ( Figure 3I). Several antibody measurements correlated significantly with each other (Figures 3J-3M). When we ranked COVID-19 patients according to the neutralizing activity of SARS-CoV-2-specific antibodies, COVID-19 patients with the highest MN activity had high levels of RBD-specific IgM, IgG, and IgA, suggesting that engagement of a broad range of antibody isotypes may lead to improved neutralizing activity ( Figure 3L). Importantly, antibodies against Spike and neutralizing antibody titers correlated with RBD-specific IgG, IgM, and IgA antibodies ( Figures 3J, 3K, and 3M).
Activated PD-1 + ICOS + cT FH 1 cells correlate with robust humoral immunity Consistent with previous observations, our analyses of SARS-CoV-2-specific antibodies demonstrated considerable variability among acute COVID-19 patients ( Figure 3B). To understand the basis of such variability and identify potential predictors of antibody signatures, we dissected correlations between antibody responses (RBD or Spike, IgG, IgM, or IgA, MN) and immune populations involved in humoral immunity, ASCs, and activated cT FH 1, cT FH 2/cT FH 17, T H 1, and T H 2/T H 17 subsets ( Figure 4A). We found significant positive correlations between the number of ASCs and MN titers (r s = 0.543) and Spike-specific IgA antibodies (r s = 0.597). The number of activated cT FH 1 cells positively correlated with the levels of RBD-and Spike-specific antibodies of all 3 isotypes (r s > 0.288 for RBD, r s > 0.549 for Spike) and MN titers (r s = 0.659). We observed no significant correlations between CXCR3 À cT FH 2/cT FH 17 cells or activated CD4 + T cells not belonging to the CXCR5 + T FH lineage and antibody responses.
To evaluate the potential of immune populations as predictors of the acute antibody response, we performed linear regression of each immune cell population against each antibody measurement and consistently found ASCs and activated cT FH 1 cells, but not other CD4 + T cell subsets, as significant positive predictors of matched RBD-specific, Spike-specific, and MN titers (Figure 4B). While in some instances, the correlations with immune Article ll OPEN ACCESS populations were strong (e.g., activated cT FH 1 cells and Spikespecific IgM, R 2 = 0.73) or modest (e.g., ASC and MN titers [MNTs], R 2 = 0.36), they were weak for RBD-specific antibodies (R 2 < 0.2). Activation of non-T FH cells was also a negative predictor of RBD-specific antibodies ( Figure 4B). We observed that higher ratios of activated cT FH 1 cells to activated cT FH 2/ cT FH 17 cells or activated cT FH 1 cells to activated T H 1 cells were significant positive predictors of matched MNTs (R 2 = 0.624 and R 2 = 0.404, respectively) and RBD-specific antibodies for all isotypes, albeit to a lesser extent (R 2 < 0.2) ( Figure 4C).
As our results are based on immune and antibody analyses from longitudinal samples during acute COVID-19, and are consistent with data in convalescent individuals, 11 we determined whether immune populations measured at the acute phase could act as biomarkers for convalescent antibody responses. We analyzed paired longitudinal data from individuals with acute immune and convalescent RBD antibody data (n = 14 patients) using the peak value of the immune cell population when >1 acute measurement was available. The levels of activated cT FH 1 cells were significant positive predictors of convalescent RBD-specific IgM antibodies, by both proportion and number of cells (R 2 = 0.531 and R 2 = 0.37, respectively) ( Figures  4D and S10A). Interestingly, while a similar result was also observed for the proportion of activated cT FH 2/cT FH 17 cells (p = 0.0407, R 2 = 0.305), this was not observed for cell numbers. Neither the proportion nor the numbers of acute ASCs were significant predictors of convalescent RBD-specific antibodies. Overall, activated cT FH 1 cells in the acute phase were associated with greater levels of RBD-specific IgM antibodies at convalescence.
Having shown that activated PD-1 + ICOS + cT FH 1 cells correlate with RBD-, Spike-, and MN antibody titers (thus magnitude), we asked whether these cT FH 1 cells could also be associated with qualitative features of antibodies. We measured the avidity of RBD-specific IgG and IgM antibodies using a urea dissociation assay. In paired COVID-19 plasma samples (n = 13) obtained >7 days apart, we found a significant increase in IgG and IgM avidity (percentage of antibody remaining after 6 M urea treatment) in the second plasma sample (Figures 4E and S10B). Avidity also increased with time, where RBD-specific IgG antibodies detected within the first week had significantly lower avidity than samples obtained R3 weeks later ( Figure S10C). The proportion of PD-1 + ICOS + cT FH 1 cells at the acute time points positively correlated with antibody avidity for RBD IgM (p = 0.0058, R 2 = 0.589), but not RBD IgG, at convalescence ( Figure 4F). Thus, activated PD-1 + ICOS + cT FH 1 cells in acute COVID-19 correlate with robust humoral immunity, in both a quantitative (RBDspecific, S-specific, and MN titers) and qualitative (IgM avidity) sense. Overall, robust antibody responses elicited during SARS-CoV-2 infection were associated with T FH activation; thus, cT FH responses may be valuable as potential biomarkers in vaccine clinical trials.
Hyperactivated CD38 + HLA-DR + innate and adaptive immune cells, sIL-6R, and IL-18 during severe COVID- 19 We selected 19 key innate and adaptive immune subsets identified to be prominent in acute versus convalescent COVID-19 samples (Figure 2) for broader analyses, including acute datasets for the 14 cytokines/chemokines and RBD-specific IgG/ IgM/IgA antibodies (total 36 features), while correcting for multiple comparisons ( Figure 5A), to elucidate immune mechanisms driving disease severity. In fact, 9/36 (25%) immune features were significantly enhanced in severely ill patients (ICU versus ward), including activated CD38 + HLA-DR + CD8 + , CD38 + HLA-DR + CD4 + , CD38 + HLA-DR + gd T cells, PD-1 + ICOS + cT FH 1 and cT FH 2/cT FH 17 cells, HLA-DR + NK cells, patrolling CD16 + monocytes, and higher levels of IL-18 and sIL-6R, reminiscent of prolonged and high expression of CD38 + HLA-DR + on CD8 + T cells associated with mortality in H7N9-infected patients. 26 In the hospitalized moderate patients who did not require ICU care, classical CD14 + monocytes were higher and RBD-specific antibodies were not significantly different ( Figure 5A). Nevertheless, the 10 features were sufficient to clearly separate samples from moderate (ward) and severe (ICU) patients by principal-component analysis (PCA), whereby the ward and ICU groups were separated along PC1 (explaining 41.4% of variance) and ICU samples further separated along PC2 (accounting for 18.1% of variance) ( Figure 5B).
Hyperactivation of immune cell subsets in ICU patients was further demonstrated by dissecting immune subsets individually. This was evident when analyzing the proportion of activated CD38 + HLA-DR + immune sets ( Figure 5C). Markedly higher proportions of CD38 + HLA-DR + CD4 + (18.25% versus 2.84%), CD38 + HLA-DR + CD8 + (28.9% versus 5.55%), CD38 + HLA-DR +  Article ll OPEN ACCESS gd T cells (30.3% versus 5.48%), HLA-DR + NK cells (8.87% versus 3.63%), and patrolling CD16 + monocytes (12.8% versus 8.26%) were found in the ICU compared to the ward group. Strikingly, in some ICU patients, levels of hyperactivated CD38 + HLA-DR + CD4 + T cells constituted $80% of all blood CD4 + T cells, while up to 50% of all blood CD8 + T cells, NK cells, and gd T cells were found in some ICU patients (Figure 5C) , indicating a non-specific bystander mode of activation. Moreover, immune cell activation was clearly higher in ICU patients as the total numbers for each parent population were comparable between severity groups ( Figure S11). Immune clustering further identified significant differences between ICU and ward, including higher levels of CD38 + HLA-DR + neutrophils, eosinophils, NK cells, gd, CD4 + , and CD8 + T cells in ICU samples ( Figure S12). We also found significantly higher neutrophil:lymphocyte and neutrophil:T cell ratios in ICU patients ( Figure S12).
Longitudinal analyses verified high levels of IL-18, IL-6, and sIL-6R in ICU patients when compared to the ward patients over time, while the ratio of IL-6:sIL-6R was variable among ICU and ward patients (Figures 5F and 5H). When paired IL-6 and sIL-6R data were analyzed, high IL-6 levels in acute COVID-19 did not imply high sIL-6R levels ( Figures 5G and  5H). Conversely, it appeared that acute (both ward and ICU) COVID-19 samples with the highest IL-6 plasma concentration had modest levels of sIL-6R. These results have important implications for IL-6/IL-6R immunotherapies and need to be further investigated in larger COVID-19 cohorts.
Further focus on the association of disease severity with SARS-CoV-2 antibody responses revealed significantly higher levels of RBD-specific IgG, IgM, and IgA antibodies in ICU than in ward patients ( Figures 5I and 5J), in agreement with previous reports. 8 Interestingly, convalescent patients who were originally hospitalized with COVID-19 had significantly higher RBD-specific IgG and IgA antibodies than those who were cared for at home ( Figure 5I). ICU patients had higher cT FH 1 responses, albeit insignificant in the proportions and numbers, but comparable ASC responses to those of the ward patients ( Figure 5C).
Thus, severe COVID-19 was associated with overwhelming immune activation of innate, adaptive lymphoid and myeloid compartments, higher antibody responses supported by greater cT FH 1 activation, and enhanced levels of IL-6, IL-18, and sIL-6R. Thus, IL-18 and CD38 + HLA-DR + expression may be useful biomarkers of COVID-19 severity, while sIL-6R levels are relatively low in COVID-19 patients (with the exception of ICU patients), in comparison to the levels detected in cancer patients (up to 195 ng/mL). 29 IL-6/sIL-6R and IL-18 hypercytokinemia associated with dysregulation of innate and adaptive immunity To gain insights into the basis of the immune hyperactivation profiles, we performed correlation analysis of 14 cytokines and 22 immune cell populations (Figures 6A-6C). IL-6 positively correlated with IL-8, IL-18, and IFN-g ( Figure 6A), where elevated levels of IL-6 were reported for severe influenza disease and mortality. 30,31 Consistent with other studies, 2 we found that IL-6 negatively correlated with lymphocyte numbers in blood ( Figure 6B), possibly reflecting the efflux of immune cells from blood to the site of infection. Importantly, we also found positive correlations between levels of IL-6 or IL-18 with T cells and NK cell hyperactivation (Figures 6B and 6C). IL-6 and IL-18 significantly correlated with the proportion of CD38 + HLA-DR + gd T cells (r s = 0.37, p = 0.004 and r s = 0.53, p < 0.0001, respectively) and IL-18 significantly correlated with the proportion of CD38 + I-COS + CD4 + T cells (r s = 0.29, p = 0.028) ( Figure 6C). We also found that the proportions of CD14 + and CD16 + monocytes were positively and negatively associated with the levels of MCP-1, respectively. Significant correlations were detected between the levels of sIL-6R and CD38 + HLA-DR + gd T cells (r s = 0.35, p = 0.008), CD38 + HLA-DR + CD8 + T cells (r s = 0.32, p = 0.012), CD38 + HLA-DR + CD4 + T cells (r s = 0.42, p = 0.0013), and HLA-DR + NK cells (r s = 0.36, p = 0.006). Interestingly, significant correlations were found between sIL-6R with RBD IgG, IgM, and IgA titers, with those being higher in ICU samples. We found consistent results when analyzing the proportions of immune cell clusters determined by FlowSOM, with IL-6 and IL-18 positively correlating with activation of myeloid cells, T cells, and NK cells (Figures 6D and S13).
Overall, our study provides a comprehensive map of longitudinal immunological responses in COVID-19 patients at acute and convalescent phases of SARS-CoV-2 infection ( Figure S14) and demonstrates prototypical antiviral immunity in mild/moderate cases, but dysregulated immune hyperactivation in severe COVID-19. Our analyses unify the levels of IL-6, sIL-6R, and IL-18 and their association with severe COVID-19 with the immune hyperactivation profiles at the cellular level characterized by high CD38 expression ( Figure 6D).

DISCUSSION
Immune responses toward non-severe SARS-CoV-2 infection resemble a prototypical antiviral immune response, with transient activation of innate myeloid and lymphoid populations at the acute phase. These include cT FH 1 cells, T H 1 CD4 + T cells, highly cytotoxic CD38 + HLA-DR + CD8 + T cells, SARS-CoV-2specific B cells, and antibodies. This is followed by the subsequent contraction of immune responses after disease resolution, as shown by us and others, 3,6,11 similar to other acute respiratory infections. 27,32 Despite prototypical immune responses found in mild/moderate COVID-19 cases, profoundly dysregulated innate and adaptive immunity underlie severe COVID-19, including elevated plasma IL-18 and sIL-6R levels, and hyperactivation of innate, adaptive, and myeloid compartments in ICU COVID-19 patients. Our study provides a comprehensive map of longitudinal immunological responses in COVID-19 patients at acute and convalescent phases and integrates key cellular pathways of complex perturbed immune networks underpinning critical COVID-19, providing important insights into biomarkers and immunotherapies.
Our analysis of humoral immune responses to SARS-CoV-2 demonstrated generation of RBD-and Spike-specific IgG, IgM, and IgA antibodies and their correlation with SARS-CoV-2 neutralization activity. Early activation of ASCs, likely of extrafollicular origin, was associated with Spike-specific IgG, IgM, and IgA antibodies, antibody neutralization activity, and, to a lesser extent, RBD-specific titers. Our data are in agreement with the emergence of IgG, IgM, and IgA ASC in COVID-19 patients, some specific for non-Spike antigens (e.g., nucleocapsid protein), which may explain the lack of a strong correlation between ASCs and RBD-specific antibodies in our cohort and other studies. 4,6 Activation of cT FH 1 cells is an important correlate of antibody responses following influenza vaccination, 25 yellow fever, 33 and hepatitis C virus (HCV). 34 Although the lack of Bcl6 + T FH cells in lymphoid organs of severely ill COVID-19 patients was shown, 35 cT FH response at the convalescent phase was associated with antibody responses to SARS-CoV-2. 11 Our analysis extends this observation to the acute phase and importantly associates acute cT FH 1 responses with convalescent IgM antibody titers. It also demonstrates an association between cT FH 1 responses and an increase in antibody avidity, potentially reflecting affinity maturation in germinal centers. We found that greater activation of cT FH 1 cells relative to other CD4 + T cell subsets was associated with greater RBD-specific responses and better neutralization activity. Our findings thus support the use of adjuvants that can induce strong T FH responses to improve vaccine efficacies. In humans, GLA-SE in the malaria vaccine induced greater cT FH responses than alum, 36 while in non-human primates and mice, MF59 enhanced cT FH activation and antibody responses to HIV-1 and influenza, respectively. 37,38 Since some of the SARS-CoV-2 vaccines in clinical trials are formulated with alum or MF59, 39 it may be important to compare immunogenicity across vaccine formulations.
IL-6 is the key driver of an inflammatory cascade in severe COVID-19; 1,2,20 thus, therapies targeting sIL-6R are in clinical trials for SARS-CoV-2 infection. Two humanized monoclonal anti-bodies against IL-6R, tocilizumab (Roche) and sarilumab (Sanofi), safely used for autoimmune diseases, are being evaluated in COVID-19, but neither has met the primary endpoints. 40,41 There have been limited analyses of sIL-6R in acute and convalescent COVID-19 patients. Surprisingly, although the plasma sIL-6R levels were significantly elevated in severe COVID-19 compared to moderate disease, they remained within the healthy range (up to 80 ng/mL). 42 Interestingly, while IL-6 was considerably elevated in acute COVID-19 samples, patients with the highest IL-6 concentrations had only modest sIL-6R levels, and levels of sIL-6R did not correlate with IL-6 or any other cytokines. In addition, the elevated levels of IL-6 and IL-18 found in critically ill COVID-19 patients are in the same range as those of patients with non-COVID-19 acute respiratory distress syndrome (ARDS) or sepsis. 43 Our results suggest that patients should be screened for both IL-6 and sIL-6R before the initiation of anti-IL-6R therapy, especially since critically ill COVID-19 patients receiving anti-IL-6R therapies may be at higher risk of nosocomial infections. 44 Interestingly, the levels of IL-6 correlate with lymphocytopenia in our cohort and others, 2 and treatment with anti-sIL-6R therapies can restore lymphocyte numbers. We also found a correlation between sIL-6R and the activation of CD8 + , CD4 + , and gd T cells. Since activated T cells are considered a major source of sIL-6R 45 and severe COVID-19 presents with T cell hyperactivation, this may explain the elevated levels of sIL-6R and support the idea that sIL-6R may be an informative biomarker.
IL-18 was also associated with COVID-19 severity in our analysis and another report. 7 We found a correlation between IL-18 levels and the activation of innate NK cells and gd T cells, as well as CD4 + and CD8 + T cells, which is consistent with the potential of IL-18/IL-18R signaling to induce bystander activation of innate and adaptive T cells. [46][47][48] These observations unify the elevated levels of cytokines, such as IL-6 and IL-18, and their signaling pathways with hallmark observations of severe COVID-19 disease, like hyperactivation of T cells and elevated antibody levels, and thus provide insights into underlying mechanisms and a potential therapeutic role for anti-IL-18 therapies. 49,50 The use of dexamethasone showed benefits in severely ill COVID-19 patients, 15 consistent with immune hyperactivation observed in those patients. However, neither sIL-6R nor IL-18 were universally higher in ICU patients, nor do they fully explain the immunological differences between ward and ICU samples. Our data further highlight the need for multiparameter immune profiling of severe COVID-19 patients to identify and appropriately select personalized immune-modulatory treatments.
The hyperactivation of immune cells in severe ICU cases, suggestive of substantial immune dysregulation, was clearly evident from elevated CD38 expression on a broad range of immune cells. The upregulation of CD38 and HLA-DR on T cells in COVID-19 in our study and by others 4,6,8 is consistent with the high levels of CD38 + HLA-DR + CD8 + T cells observed in HIV, 51 Ebola, 52 HCV, 53 and dengue. 54 Our data from severe COVID-19 cases support our previous study showing high and prolonged proportion of CD38 + HLA-DR + CD8 + T cells (up to 50% for $30 days) in patients who died from avian A/H7N9 influenza. 26 Numerically, 50%-80% of CD38 + HLA-DR + T cells found in the peripheral blood of severe H7N9 or COVID-19 cases unlikely reflect epitope-specific T cell activation. In fatal H7N9 cases, delayed clonal expansion of H7N9-specific CD8 + T cells and distinct transcriptome signatures of CD38 + HLA-DR + CD8 + T cells were indicative of bystander activation. In COVID-19 patients, such T cell hyperactivation was associated with elevated cytokine levels that may drive bystander activation, similar to H7N9 hypercytokinemia. 31 Thus, while rapid and transient CD38 + HLA-DR + expression can be detected in patients with relatively rapid recovery, 26 prolonged and high expression levels are associated with severe and/or fatal outcomes in COVID-19 and avian H7N9. 3,26 Given that high CD38 expression is a poor prognostic factor in cancers and HIV, 55 monitoring CD38 expression on a wide range of immune cells may be a useful marker of immune hyperactivation and disease progression in COVID-19.

Limitations of study
We recognize that some of the analyses performed are limited to a relatively small number of patients available. This is particularly relevant to the analysis of ICU samples, the longevity analysis of antibodies, and the analysis of neutralizing titers. In addition, we could not stratify our cohort based on age groups or the use of immunomodulatory treatments, which should be the focus of future studies.

STAR+METHODS
Detailed methods are provided in the online version of this paper and include the following: