key: cord-0290227-kvu0hgjf
authors: Muri, Jonathan; Cecchinato, Valentina; Cavalli, Andrea; Shanbhag, Akanksha A.; Matkovic, Milos; Biggiogero, Maira; Maida, Pier Andrea; Toscano, Chiara; Ghovehoud, Elaheh; Danelon-Sargenti, Gabriela; Gong, Tao; Piffaretti, Pietro; Bianchini, Filippo; Crivelli, Virginia; Podešvová, Lucie; Pedotti, Mattia; Jarrossay, David; Sgrignani, Jacopo; Thelen, Sylvia; Uhr, Mario; Bernasconi, Enos; Rauch, Andri; Manzo, Antonio; Ciurea, Adrian; Rocchi, Marco B.L.; Varani, Luca; Moser, Bernhard; Thelen, Marcus; Garzoni, Christian; Franzetti-Pellanda, Alessandra; Uguccioni, Mariagrazia; Robbiani, Davide F.
title: Anti-chemokine antibodies after SARS-CoV-2 infection correlate with favorable disease course
date: 2022-05-23
journal: bioRxiv
DOI: 10.1101/2022.05.23.493121
sha: 892f802f2c23d1082ab47a20e586325fb7f5ed83
doc_id: 290227
cord_uid: kvu0hgjf

Infection by SARS-CoV-2 leads to diverse symptoms, which can persist for months. While antiviral antibodies are protective, those targeting interferons and other immune factors are associated with adverse COVID-19 outcomes. Instead, we discovered that antibodies against specific chemokines are omnipresent after COVID-19, associated with favorable disease, and predictive of lack of long COVID symptoms at one year post infection. Anti-chemokine antibodies are present also in HIV-1 and autoimmune disorders, but they target different chemokines than those in COVID-19. Finally, monoclonal antibodies derived from COVID- 19 convalescents that bind to the chemokine N-loop impair cell migration. Given the role of chemokines in orchestrating immune cell trafficking, naturally arising anti-chemokine antibodies associated with favorable COVID-19 may be beneficial by modulating the inflammatory response and thus bear therapeutic potential. One-Sentence Summary Naturally arising anti-chemokine antibodies associate with favorable COVID-19 and are predictive of lack of long COVID.

The spectrum of disease manifestations upon infection with Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is broad (1). Factors that predispose people to hospitalization and death include age, gender, ethnicity, obesity, genetic predisposition, autoantibodies against interferon, and comorbidities such as hypertension, diabetes, and coronary heart disease (2) (3) (4) (5) (6) . 5

Coronavirus disease 2019 (COVID-19) convalescent individuals often lament protracted symptoms over months, a condition referred to as long COVID or PASC (Post-Acute Sequelae of COVID), and are at increased risk of cardiovascular events (7-13). Some evidence points to a role for immune dysregulation and autoimmunity as contributors to long COVID, although virus persistence has also been proposed (14) (15) (16) . Overall, there is however little understanding 10 of the biology underlying long COVID and of the reasons for the differences in COVID-19 manifestation.

Chemokines are chemotactic cytokines that mediate leukocyte trafficking and activity by binding to seven-transmembrane G protein-coupled receptors (17, 18) . Chemokines play a 15 fundamental role in health and disease, and the proper trafficking of leukocyte subsets is governed by the combinatorial diversity of their responsiveness to chemokines (18) . In addition to elevated levels of pro-inflammatory cytokines (e.g. IL-6, TNF, and IL1β), higher levels of certain chemokines are observed in acute COVID-19 (e.g. CCL2, CCL3, CCL4, CCL7, CCL8, CCL19, CXCL2, CXCL5, CXCL8, CXCL9, CXCL10, CXCL13, CXCL16 and 20 CXCL17) and multiomic studies recently identified plasma chemokines among the most significant factors associated with COVID-19 severity (19) (20) (21) (22) (23) (24) (25) . Accordingly, neutrophils and monocytes are recruited by chemokines to sites of infection, where they play a key role in the pathophysiology of COVID-19 by sustaining inflammation and causing tissue damage and fibrosis, including in the inflammatory phase that follows virus clearance (20, 24, (26) (27) (28) (29) . Anti-25 inflammatory treatments, such as steroids and IL-6 blockade, are efficacious in hospitalized COVID-19 patients, and therapies targeting the chemokine system are under development for immunological disorders and have been proposed for COVID-19 (18, 22, 30, 31) .

Similar to earlier work linking anti-cytokine antibodies to mycobacterial, 30 staphylococcal and fungal diseases (32-34), autoantibodies against cytokines have been described in COVID- 19 . In particular, anti-type I Interferon antibodies distinguished ~10% of life-threatening pneumonia and ~20% of deaths from COVID-19 (6, 35, 36) . Moreover, autoantibodies characteristic of systemic autoimmune disorders, such as anti-phospholipid antibodies, anti-nuclear antibodies and rheumatoid factor, were reported in COVID-19 (37-41).

A recent high-throughput screening by yeast display of the secretome further revealed the presence of autoantibodies against a number of immune factors, including chemokines (42).

However, anti-chemokine antibodies were infrequent by this method, and there was neither 5 correlation with disease severity, or long COVID, nor information about the persistence of such autoantibodies over time.

We devised a peptide-based strategy to discover and measure antibodies that bind to a functional region of each of the 43 human chemokines. By examining a diverse cohort, which 10 contracted COVID-19 during 2020, we found that the presence of antibodies against specific chemokines helps to identify convalescent individuals with favorable COVID-19 disease course. Anti-chemokine monoclonal antibodies derived from these individuals block leukocyte migration and thus may be advantageous through modulation of the inflammatory response.

To determine whether SARS-CoV-2 infection induces antibodies that interfere with immune cell migration, we first analyzed cells expressing the CC chemokine receptor 2 (CCR2), a key 5 mediator of monocyte migration into the lung during infection and inflammation (43) (44) (45) . In vitro chemotaxis assays were performed with three CCR2 agonists (CCL2, CCL7 and CCL8) in the presence of IgGs purified from the plasma of COVID-19 convalescent individuals or uninfected controls (n=24 and n=8, respectively; see Methods). Cell migration to CCL8 was significantly impaired (26.0% reduction; p=0.0039), suggesting the presence of blocking 10 antibodies specific for CCL8 following COVID-19 (Fig. 1A) .

Since the N-terminal loop (N-loop) of chemokines is required for receptor binding, we reasoned that biologically active antibodies would likely target this region of the chemokine ( Fig. 1B) (46) . To test this hypothesis, we synthesized a peptide comprising the N-loop of CCL8 and used it in enzyme-linked immunosorbent assays (ELISA) to analyze plasma samples 15 obtained on average at 6 months (t=6m) after disease onset from a diverse COVID-19 cohort ( Fig. 1C ; tables S1 and S2). High levels of anti-CCL8 IgGs were found in two out of 71 COVID-19 convalescents, which was similar to antibodies against Interferon a2 (IFNa2; Fig.   1 , D and E) (6) . To examine the molecular features of anti-CCL8 antibodies, we purified memory B cells that bound to the CCL8 N-loop from the peripheral blood mononuclear cells 20 (PBMCs) of the donor with the highest reactivity in ELISA and sequenced the antibodies ( Fig. 1F; fig. S1A ; see Methods). Out of 23 IgG sequences, 20 were clonally related, and 4 were cloned to produce monoclonal antibodies (aCCL8.001, aCCL8.003, aCCL8.004, aCCL8.005; table S3). All 4 antibodies similarly bound to the CCL8 N-loop (half-maximal effective concentrations EC50 between 11-16 ng/mL) and inhibited the migration 25 of primary human monocytes towards CCL8 (Fig. 1 , G and H; data not shown; table S4). Anti-CCL8 antibodies were specific, because they failed to bind to the most similar chemokine N-loops (fig. S1B). By the same approach, we discovered chemotaxis-blocking antibodies specific for CCL20 (fig. S1, C to E; table S4). We conclude that in COVID-19 convalescents there can be antibodies that interfere with the biologic activity of chemokines. 30

Having validated the chemokine N-loop as target of functional antibodies, we designed peptides corresponding to the N-loop of all other human chemokines, with the goal of comprehensively examining anti-chemokine antibodies in COVID-19 ( Fig. 2A; table S2 ). Antibody levels were measured by ELISA of serial plasma dilutions and the signal plotted as 5 heatmap ( Fig. 2A; fig. S2 ; table S5). Analysis of all parameters by nonlinear dimensionality reduction with t-distributed stochastic neighbor embedding (t-SNE) revealed a clear separation between controls and COVID-19 convalescents ( fig. S3A ). Similar to CCL8, some convalescent plasma revealed high levels of IgGs to certain chemokines (for example CXCL13 and CXCL16). For these chemokines, antibody levels to the N-loop significantly correlated 10 with those against the C-terminal region of the same chemokine, suggesting that, when present, antibodies formed against multiple chemokine epitopes (Fig. 2, A; fig. S3B ). When considering antibodies against each chemokine individually, a significant difference in reactivity over uninfected control was observed for peptides corresponding to 23 of the 43 chemokines ( fig. S3C ). Antibodies to the three chemokines with p<10 -4 (CCL19, CCL22 and CXCL17; 15 "COVID-19 signature") clustered together, and by themselves were sufficient to correctly assign uninfected controls and COVID-19 convalescents with accuracies >95% (Fig. 2 To examine the relationship between anti-chemokine antibodies and other serologic 20 features of the COVID-19 cohort, we used ELISA and a pseudovirus-based neutralization assays to measure binding and neutralizing capacity of antibodies against SARS-CoV-2 (47).

In agreement with previous studies, IgG binding to SARS-CoV-2 Spike receptor binding domain (RBD) and plasma half-maximal neutralizing titers (NT50) against SARS-CoV-2 were variable but positively correlated with each other and with age ( fig. S4 , A to C) (47). In 25 contrast, there was no correlation between NT50 or anti-RBD IgGs and the levels of antibodies to the signature chemokines CCL19, CCL22 and CXCL17, or to the sum of all anti-chemokine IgG reactivities (cumulative area under the curve [AUC]; fig. S4D ). A weak negative correlation between age and the sum of all anti-chemokine IgG reactivities was observed ( fig.   S4D ), but there were no differences in the levels of antibodies to the signature chemokines 30 between males and females ( fig. S4E ). We conclude that, after COVID-19, antibodies against specific chemokines are not correlated with those against SARS-CoV-2.

To document the temporal evolution of anti-chemokine antibodies following COVID-19, we compared side-by-side the reactivities of plasma collected from the same cohort at approximately 6 months (t=6m) and 12 months (t=12m) from symptom onset (fig. S5A; table   S1 ). In agreement with earlier findings (48, 49), antibodies to the virus RBD significantly decreased in unvaccinated COVID-19 convalescents, while they increased in those receiving 5 at least one dose of mRNA-based COVID-19 vaccine ( fig. S5B ; table S1). Conversely, and regardless of vaccination status (data not shown), antibodies to the COVID-19 signature chemokine CCL19 significantly increased (2.1-fold, p<0.0001), those to CXCL17 remained generally stable, and those to CCL22 followed variable kinetics (Fig. 2D ). Similar to CCL19, antibody levels to CCL8, CCL13, CCL16, CXCL7 and CX3CL1 were also augmented at 12 10 months, while a reduction was observed for CXCL16 ( fig. S5C ). To further investigate the kinetics of COVID-19 signature antibodies, we analyzed cohort individuals for which acute samples were also available (n=12; fig. S5D ; table S1). During acute COVID-19, IgG antibodies to CCL19, but not to CCL22 or CXCL17, were already higher than in uninfected controls, and continued to increase until 12 months ( fig. S5E ). In contrast to natural infection, 15 no significant change in antibody reactivity to any of the chemokines was observed upon COVID-19 mRNA vaccination of SARS-CoV-2 naïve individuals after about 4 months (130 days on average; n=16; fig. S5F ; table S1). Therefore, unlike the antibodies to SARS-CoV-2 RBD, which decrease over time, the levels of some anti-chemokine antibodies that are present upon COVID-19 increase over one year of observation. 20

Autoantibodies have been detected in a portion of hospitalized COVID-19 patients, linking their presence to severe illness (6, 38, 42) . To evaluate the relationship between the severity of acute COVID-19 and convalescent anti-chemokine IgGs, we compared individuals in our cohort who were either hospitalized because of the infection (n=50) or remained as outpatients (n=21; Fig. 2E ). No significant difference in age distribution 25 was observed between groups (age [years]: mean±SD; 60±14 in hospitalized, 57±15 in outpatients; p=0.3487), while a higher proportion of males was observed among hospitalized but not outpatients (60% and 38.1%, respectively; table S1) (5).

When the most significant differences in autoantibody levels were taken into account (p<10 -4 ), only the antibodies against CCL19 were higher in hospitalized individuals over 30 uninfected controls, while antibodies against 8 chemokines (CXCL8, CCL22, CXCL16, CCL27, CXCL7, CCL20, CX3CL1, in addition to CCL19) were increased in outpatients ( Fig.   2E; fig. S6A ). Consistent with this finding, the outpatient but not the hospitalized individuals displayed significantly higher cumulative anti-chemokine reactivity (p=0.0038; Fig. 2F ). Thus, a broader pattern and higher overall amounts of anti-chemokine antibodies are observed at 6 months in those COVID-19 convalescents, who were outpatients during the acute phase of the disease.

Direct comparison of previously hospitalized and outpatient individuals by t-SNE 5 analysis of all anti-chemokine datasets separated the two groups (Fig. 2G ). Antibodies against three chemokines highly significantly distinguished outpatients from hospitalized subjects 

A fraction of individuals who recover from COVID-19 experience long-term sequelae (7-10).

To determine whether a specific pattern of anti-chemokine antibodies at t=6m is predictive of 25 the persistence of symptoms, we collected this information from the cohort at t=12m (Fig. 3) .

65.1% of all participants reported persistence of at least one symptom related to COVID-19.

Among these, the average number of long-term symptoms was 3.3, and they were more frequent among formerly hospitalized individuals than outpatients (72.7% versus 47.4%; Fig.   3A ; fig. S8 , A and B; table S1). No differences in age, gender distribution or time from disease 30 onset to second visit were observed between individuals with and without protracted symptoms

Convalescents with long-term sequelae showed significantly lower cumulative levels of anti-chemokine antibodies compared to those without symptoms (p=0.0135; Fig. 3B ). This was particularly true for outpatients and among females (fig. S8, D and E). In contrast, anti-RBD IgG and NT50 values were comparable between the two groups (Fig. 3B ). The total levels of anti-chemokine antibodies did not correlate with the number of symptoms ( fig. S8F ). These 5 data indicate that overall higher levels of anti-chemokine antibodies at 6 months after COVID-19 are associated with absence of long-term symptoms at 12 months.

IgG antibodies against three chemokines distinguished the groups with high significance: CCL21 (p=0.0001), CXCL13 (p=0.0010) and CXCL16 (p=0.0011; Fig. 3C; fig.   S8G ; "Long COVID signature"). Logistic regression analysis using the antibody values for 10 these 3 chemokines predicted the absence of persistent symptoms with 77.8% accuracy (Fig. 3D) . These results indicate that specific patterns of anti-chemokine antibodies at 6 months predict the longer-term persistence of symptoms after COVID-19.

Since anti-chemokine antibodies to CXCL13 and CXCL16 are associated with favorable long COVID outcome, we next derived corresponding memory B cell antibodies 15 from available PBMC samples (table S3; antibodies against CCL8 and CCL20 ( Fig. 1; fig. S1 ), antibodies that bind to the N-loop of CXCL13 and CXCL16 interfere with cell migration.

To examine the relevance of anti-chemokine antibodies beyond COVID-19, we measured their 25 presence in plasma from patients chronically infected with HIV-1 (n=24), and from individuals 

We discovered that autoantibodies against chemokines are omnipresent after SARS-CoV-2 infection, and that higher levels of specific anti-chemokine antibodies are associated with favorable disease outcomes. Our findings contrast previous reports that connected autoantibodies to severe COVID-19 illness. For example, autoantibodies against type I 5 interferon were detected in 10-20% of individuals with COVID-19 pneumonia or dying from COVID-19 (6, 35) , and autoantibodies against a panel of immune molecules (including chemokines) and other self-antigens were described to occur sporadically and more frequently (19) (20) (21) (22) (23) . We find the levels of autoantibodies against CXCL8, CCL25 and 15 CXCL5 to be augmented in COVID-19 patients with milder disease over those that require hospitalization. Since these chemokines attract neutrophils and other cell types that promote inflammation and tissue remodeling, the presence of the corresponding autoantibodies suggests a protective role through dampening of the damaging inflammatory response associated with severe COVID-19. A disease-modifying role of the chemokine system in COVID-19 is further 20 supported by transcriptomic analyses and by genetic studies identifying regions of chromosome 3 encoding for chemokine receptors to be linked to critical illness (3, 53, 54) .

Similar to those associated with milder disease, autoantibodies to three other chemokines (CCL21, CXCL13 and CXCL16) are increased in individuals without long COVID one year after the infection. These chemokines are important for tissue trafficking and 25 activation of T and B lymphocytes. Therefore, it is conceivable that the corresponding autoantibodies positively impact the long-term outcome of COVID-19 by antagonizing or otherwise modulating the activation, recruitment and retention of these cells during the immune response (55). In keeping with this observation, persistent inflammation has been proposed as a mechanism leading to the development of long COVID (7). 30

Regardless of disease trajectory, the presence of three other anti-chemokine antibodies is generally associated with COVID-19 infection: CCL19, CCL22 and CXCL17. Interestingly, IgG autoantibodies to CCL19, but not to CCL22 or CXCL17, are detected early on during the acute phase, suggesting that they are either pre-existing or that they rapidly develop following the infection. The early detection of anti-CCL19 antibodies is consistent with the rapid upregulation of CCL19 during COVID-19 (25). Furthermore, we observe that antibody levels to CCL19 and to some other chemokines continue to increase between 6 and 12 months from disease onset. While dependent on the initial infection, since mRNA-based COVID-19 5 vaccination does not appear to induce anti-chemokine antibodies, this is unlikely to be related to chronic SARS-CoV-2 infection, because antiviral antibodies decrease during this time (48).

Rather, the finding would be consistent with the persistence of the autoantigens within germinal centers, leading to continuous generation of antibody-secreting plasma cells (56).

Chemokines play an important role in HIV-1 and in autoimmune disorders (18, 57, 58) . 10 We find anti-chemokine antibodies also in these illnesses, but the patterns are different when compared to each other and to COVID-19. In HIV-1, a chronic viral infection, antibodies are significantly enhanced against more than half of all the chemokines, but do not include antibodies to either CCL19 or CXCL17, which are characteristic of COVID-19. Antibodies to the chemokine ligands of the HIV-1 coreceptors (CXCR4 and CCR5) are also detected at 15 higher levels (59). Autoantibodies in the three autoimmune disorders are generally similar to each other, but distinct from those in infection. We speculate that these differences reflect the unique role of chemokines in each of these diseases.

Infection can trigger antibody polyreactivity and autoimmunity that are generally deleterious (60-62). Since here we show that post-infectious autoantibodies can be associated 20 with positive outcomes, we favor the view of post-infectious autoantibodies as disease modifiers. In COVID-19, the infection induces the expression of chemokines, leading to a proinflammatory milieu that clears infected cells but also causes collateral damage (20, 24, (26) (27) (28) (29) . The variety and amount of anti-chemokine antibodies that are present or induced upon infection in each individual may modulate the strength and quality of the inflammatory 25 response, which in turn would impact disease manifestation, severity and long COVID. This could in part explain the variable success of convalescent plasma treatment in COVID-19 (63), for which donors were selected based on virus neutralizing activity and not for the presence of autoantibodies that could modulate the inflammatory response.

We discovered and characterized the first, human-derived monoclonal antibodies 30 against four chemokines, including anti-CXCL13 and anti-CXCL16 antibodies that are relevant for long COVID. Consistent with the 2-step model of chemokine receptor activation (46, 64), all the N-loop antibodies that were tested effectively reduced chemotaxis. Similar to steroids and IL-6 blockers, which are currently deployed in the clinic, we propose that agents 10 Data and materials availability: All data are available in the main text or the supplementary materials. Computer code for antibody sequence, logistic regression, clustering and t-SNE analyses will be deposited at GitHub upon publication (https://github.com). Materials will be made available upon MTA. 15

Figs. S1 to S10 Tables S1 to S5 20 References (65-85) 

anti-chemokine IgG Written informed consent was obtained from all participants, and all samples were coded to remove identifiers at the time of blood withdrawal. Demographic, clinical, and serological features are reported in tables S1 and S5. Inhibition of chemotaxis by monoclonal antibodies (Fig. 1H, and Fig. 3, F and H; fig. S1E ):

Experiments were performed with monoclonal antibodies at a final concentration of 30 µg/ml ( Fig. 1H) or 50 µg/ml (Fig. 3, F and H; fig. S1E ). Baseline migration was determined in the absence of chemoattractant (buffer control). 

Antibody genes were sequenced, cloned and expressed as previously reported (75-77). Briefly, reverse-transcription of RNA from FACS-sorted single cells was performed to obtain cDNA, which was then used for amplification of the immunoglobulin IGH, IGK and IGL genes by nested PCR. Amplicons from this first PCR reaction served as templates for 5 sequence and ligation independent cloning (SLIC) into human IgG1 antibody expression were determined by aligning the IGHV and IGLV nucleotide sequence against their closest germlines using the blastn function of IgBlast. Differences outside CDR3 were considered as mutations.

To generate (HIV-1/NanoLuc2AEGFP)-SARS-CoV-2 particles, HEK293T cells were cotransfected with the three plasmids pHIVNLGagPol, pCCNanoLuc2AEGFP, and SARS-CoV-2 S as described elsewhere (47, 80) . Supernatants containing virions were collected 48 h after transfection, and virion infectivity was determined by titration on 293TACE2 cells. The plasma 30 neutralizing activity was measured as previously reported (47, 80) . Briefly, threefold serially diluted plasma samples (from 1:50 to 1:328'050) were incubated with SARS-CoV-2 pseudotyped virus for 1h at 37 °C, and the virus-plasma mixture was subsequently incubated with 293TACE2 cells for 48 h. Cells were then washed with PBS and lysed with Luciferase Cell Culture Lysis 5× reagent (Promega). Nanoluc Luciferase activity in cell lysates was measured using the Nano-Glo Luciferase Assay System (Promega) with Modulus II Microplate Reader User interface (TURNER BioSystems). The obtained relative luminescence units were normalized to those derived from cells infected with SARS-CoV-2 pseudotyped virus in the 5 absence of plasma. The NT50 values were determined using four-parameter nonlinear regression with bottom and top constrains equal to 0 and 1, respectively (GraphPad Prism). The dotted line (NT50=5) in the plots represents the lower limit of detection of the assay. 10 The illustrative model in Fig. 1 

Tests for statistical significance: Statistical significance between two groups was determined 20 using non-parametric two-tailed Mann-Whitney U-tests, or Wilcoxon signed-rank test, for unpaired or paired samples, respectively. Upon testing of parametric assumptions, statistical significance between more than two groups was evaluated using Kruskal-Wallis test (followed by Dunn multiple comparisons), one-way ANOVA (followed by Tukey multiple comparisons), or two-way Repeated Measures ANOVA (followed by Šídák multiple comparisons), as 25 described in the figure legends. Statistical significance of the signature chemokines (CCL19, CCL22, CXCL17, CXCL8, CCL25, CXCL5, CCL21, CXCL13 and CXCL16) was also confirmed when applying the Bonferroni criterion in order to guarantee a familywise level of significance equal to 0.05. Statistical significance from a 2x2 contingency table was determined with Fisher's exact test. Correlations were assessed using Pearson correlation analysis. A p-30 value of less than 0.05 was considered statistically significant. In the figures, significance is shown as follow: ns p≥0.05 (not significant), *p<0.05, **p<0.01, ***p<0.001 and ****p<0.0001. Data and statistical analyses were performed with GraphPad Prism. t-SNE: t-SNE analysis was performed using the Rtsne R package v 0.15 (https://CRAN.Rproject.org/package=Rtsne) using the AUC values for all chemokines. The theta parameter for the accuracy of the mapping was set to zero in all cases for exact TSNE.

Clustering: Hierarchical clustering was created using the hclust R function v 4.1.1. Clustering analysis was performed using the correlation as distance and the Ward's method as 5 agglomerative criterion. Heatmaps were created with either GraphPad Prism ( Fig. 2A; fig.   S3D ) or the Pretty Heatmaps (pheatmap) R package v 1.0.12 (fig. S10B ). In fig. S10B , each column containing a distinct chemokine was scaled with the scaling function provided by R, which sets the mean and the standard deviation to 0 and 1, respectively. *** C C L 1 C C L 2 C C L 3 C C L 4 C C L 5 C C L 7 C C L 8 C C L 1 1 C C L 1 3 C C L 1 4 C C L 1 5 C C L 1 6 C C L 1 7 C C L 1 8 C C L 1 9 C C L 2 0 C C L 2 1 C C L 2 2 C C L 2 3 C C L 2 4 C C L 2 5 C C L 2 6 C C L 2 7 C C L 2 8 C X C L 1 C X C L 2 C X C L 3 C X C L 4 C X C L 5 C X C L 6 C X C L 7 C X C L 8 C X C L 9 C X C L 1 0 C X C L 1 1 C X C L 1 2 C X C L 1 3 C X C L 1 4 C X C L 1 6 C X C L 1 7 X C L 1 / X C L 2 C X 3 C L 1 Horizontal bars indicate median values. Two-tailed Mann-Whitney U-tests. CCL2  CCL3  CCL4  CCL5  CCL7  CCL8  CCL11  CCL13  CCL14  CCL15  CCL16  CCL17  CCL18  CCL19  CCL20  CCL21  CCL22  CCL23  CCL24  CCL25  CCL26  CCL27  CCL28  CXCL1  CXCL2  CXCL3  CXCL4  CXCL5  CXCL6  CXCL7  CXCL8  CXCL9  CXCL10  CXCL11  CXCL12  CXCL13  CXCL14  CXCL16  CXCL17  XCL1/ 

Log 2 FC anti-chemokine IgG C A B COVID-19/Controls CCL1 CCL2 CCL3 CCL4 CCL5 CCL7 CCL8 CCL11 CCL13 CCL14 CCL15 CCL16 CCL17 CCL18 CCL19 CCL20 CCL21 CCL22 CCL23 CCL24 CCL25 CCL26 CCL27 CCL28 CXCL1 CXCL2 CXCL3 CXCL4 CXCL5 CXCL6 CXCL7 CXCL8 CXCL9 CXCL10 CXCL11 CXCL12 CXCL13 CXCL14 CXCL16 CXCL17 XCL1/XCL2 CX3CL1

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