Anti-chemokine antibodies after SARS-CoV-2 infection correlate with favorable disease course

Abstract

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 infection and autoimmune disorders, but they target different chemokines than those in COVID-19. 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 predict lack of long COVID.

Extended Data Fig. 1.. Anti-chemokine N-loop antibodies in COVID-19, related to Fig. 1.

(a) Characteristics of the Lugano COVID-19 cohort. (b) Model of the interaction between a chemokine and its receptor. Arrows point to the area of putative interaction between the N-terminus of the receptor and the chemokine N-loop (shown by spheres). Chemokine is magenta and chemokine receptor is cyan. (c) The amount of plasma IgG antibodies against each chemokine N-loop was determined by ELISA for COVID-19 convalescents (n=71) and controls (n=23). Average optical density (OD₄₅₀) measurements of two independent experiments.

Extended Data Fig. 2.. Analyses of anti-chemokine antibodies, related to Fig. 1.

(a) t-SNE distribution of COVID-19 convalescents and controls, as determined with the 42 datasets combined. (b) Pearson correlations of antibodies to the N-loop and C-terminal peptides of the same chemokine. ELISA was performed in a cohort subset (Controls, n=5; COVID-19, n=31). Average of two independent experiments. (c) Differences in anti-chemokine antibodies between groups. Summary circle plot: circle size indicates significance; colors show the Log2 fold-change increase (red) or decrease (blue) in the COVID-19 group over control. Two-tailed Mann–Whitney U-tests. (d) Antibodies to CCL19, CCL22 and CXCL17 classify COVID-19 convalescents versus controls. Unsupervised hierarchical clustering analysis with the COVID-19 signature antibodies. The distribution of the groups within each cluster is also shown. Fisher’s exact test.

Extended Data Fig. 3.. Analyses of anti-chemokine antibodies in the validation cohorts of Milan and Zurich, related to Figs. 1–3.

(a) Characteristics of the COVID-19 cohorts. (b) Left, difference in autoantibodies to CCL19, CCL22 and CXCL17 (COVID-19 signature). Kruskal-Wallis test followed by Dunn’s multiple comparison test (Milan) and two-tailed Mann–Whitney U-tests (Zurich). Right, assignment of COVID-19 convalescents and controls based on the COVID-19 signature antibodies by logistic regression analysis. (c) Left, difference in autoantibodies to CXCL5, CXCL8 and CCL25 (COVID-19 hospitalization signature). Kruskal-Wallis test followed by Dunn’s multiple comparison test. Right, assignment of COVID-19 mild/outpatient and severe/hospitalized individuals based on the COVID-19 hospitalization signature antibodies by logistic regression analysis. (d) Left, difference in autoantibodies to CCL21, CXCL13 and CXCL16 (Long COVID signature). Two-tailed Mann–Whitney U-tests. Right, group assignment based on the Long COVID signature antibodies by logistic regression analysis in the Zurich cohort. In (b-d), horizontal bars indicate median values; dots on grey background are correctly assigned; data are shown as average AUC of two independent experiments.

Extended Data Fig. 4.. Correlation analyses of COVID-19 signature anti-chemokine antibodies, related to Fig. 1.

(a) Anti-RBD IgG antibodies in the cohort samples. Top, optical density reactivity (OD₄₅₀) of serial plasma dilutions to the receptor binding domain (RBD) of SARS-CoV-2 Spike, as determined by ELISA. Bottom, AUC of the data in the top panel. COVID-19 convalescents (n=71); controls (n=23). Average of two independent experiments. Horizontal bars indicate median values. Two-tailed Mann–Whitney U-tests. (b) Plasma neutralizing activity against SARS-CoV-2 pseudovirus. Top, relative luciferase units (RLU) normalized to no plasma control. Bottom, half-maximal neutralizing titers (NT₅₀) based on the data in the top panel. COVID-19 convalescents (n=71); controls (n=9). Average of two independent experiments. Horizontal bars indicate median values. Two-tailed Mann–Whitney U-tests. (c) Pearson correlations of anti-RBD IgG and NT₅₀ values to each other and with age. Average of two independent experiments. (d) Pearson correlations of anti-chemokine IgG with anti-RBD IgG, NT₅₀ values and age. COVID-19 signature antibodies individually, and cumulative signal of the IgGs against the peptides for all 43 chemokines. (e) Analysis of anti-signature chemokines IgG by gender. Data are shown as average AUC of two independent experiments. Horizontal bars indicate median values. Kruskal-Wallis test followed by Dunn’s multiple comparison test.

Extended Data Fig. 5.. Anti-chemokine antibodies over time and upon COVID-19 vaccination, related to Fig. 1.

(a) Diagram of the time points of blood collection after onset of COVID-19 symptoms. (b) Anti-RBD IgG antibodies at 6 and 12 months in vaccinated and non-vaccinated convalescents, as determined by ELISA. Average AUC from two independent experiments. Wilcoxon signed-rank test. (c) Anti-chemokine IgG antibodies at 6 and 12 months in convalescents. AUC from two independent experiments. Wilcoxon signed-rank test. (d) Diagram of the time points of blood collection after onset of COVID-19 symptoms in a subset of COVID-19 hospitalized individuals. (e) Anti-chemokine IgG antibodies at 15 days (Acute), 6, 12 and 18 months after onset of COVID-19 symptoms. Average optical density (OD₄₅₀) values from two independent experiments. One-way ANOVA test followed by Tukey’s multiple comparison test. Data are shown as median±range. (f) Anti-chemokine IgG antibodies before and approximately 4 months after COVID-19 mRNA vaccination of uninfected individuals (n=16). AUC from two independent experiments. Pink lines represent the signal of a positive control plasma sample with broad reactivity (CLM70). Anti-RBD IgG is shown alongside as control (right panel). Wilcoxon signed-rank test with false discovery rate (FDR) approach.

Extended Data Fig. 6.. Anti-chemokine antibodies in COVID-19 outpatient and hospitalized individuals and correlation analyses of COVID-19 hospitalization signature antibodies, related to Fig. 1.

(a) Difference in anti-chemokine antibodies in outpatient versus hospitalized individuals at 6 months. Average AUC of two independent experiments. Horizontal bars indicate median values. Kruskal-Wallis test followed by Dunn’s multiple comparison test. (b) Difference in anti-chemokine antibodies between COVID-19 outpatient and hospitalized individuals. Summary circle plot: circle size indicates significance; colors show the Log2 fold-change increase (red) or decrease (blue) over outpatients. Kruskal-Wallis test followed by Dunn’s multiple comparison test. (c) Pearson correlations of anti-chemokine IgGs with anti-RBD IgG, NT₅₀ values and age. COVID-19 hospitalization signature antibodies individually. Average of two independent experiments. (d) Analysis of anti-signature chemokine IgGs by gender. Data are shown as average AUC of two independent experiments. Horizontal bars indicate median values. Kruskal-Wallis test followed by Dunn’s multiple comparison test. (e) Analysis of anti-RBD IgG and NT₅₀ values by group and by gender. Average of two independent experiments. Horizontal bars indicate median values. Two-tailed Mann–Whitney U-tests.

Extended Data Fig. 7.. Anti-chemokine antibodies and long-term COVID-19 symptoms, related to Fig. 2.

(a) Classification of long-term COVID-19 symptoms at 12 months (t=12m). (b) Incidence of symptoms at 12 months. Participants are grouped in outpatient and hospitalized individuals. (c) Analysis of age (left), gender distribution (middle) and time from COVID-19 onset to 2^nd visit (t=12m; right). Horizontal bars indicate median values. Two-tailed Mann–Whitney U-tests. (d,e) Difference in cumulative anti-chemokine antibodies according to the presence or absence of symptoms at 12 months in disease severity groups (d) or by gender (e). Data are shown as average AUC of two independent experiments. Horizontal bars indicate median values. Two-tailed Mann–Whitney U-tests. (f) Pearson correlation of anti-chemokine antibodies and the number of symptoms at 12 months. Average of two independent experiments. (g) Difference in anti-chemokines antibodies at 6 months and the presence or absence of symptoms at 12 months. Data are shown as average AUC of two independent experiments. Horizontal bars indicate median values. Two-tailed Mann–Whitney U-tests. The exact P-value is given for the 3 chemokines displaying the highest significance.

Extended Data Fig. 8.. Human monoclonal antibodies that impede chemotaxis, related to Fig. 2.

(a) Gating strategy for sorting CCL8 N-loop specific B cells by flow cytometry. (b) Human B cells specific for CXCL16. Representative flow cytometry plots identifying human B cells binding to the CXCL16 N-loop peptide (gate). The frequency of antigen-specific B cells is shown. (c) Human B cells specific for CXCL13. Representative flow cytometry plots identifying human B cells binding to the CXCL13 N-loop peptide (gate). The frequency of antigen-specific B cells is shown. (d) Identification of individuals with high anti-CCL8 N-loop antibodies. Area under the curve (AUC), as determined by ELISA. Average of two independent experiments. COVID-19 convalescents (n=71); controls (n=23). Horizontal bars indicate median values. (e) CCL8 binding human B cells. Flow cytometry plots identify human B cells binding to the CCL8 N-loop peptide (gate). The frequency of antigen-specific B cells is shown. (f) Monoclonal antibodies to the CCL8 N-loop. ELISA binding curves of representative antibodies. Average of two independent experiments (Mean+SEM). (g) Chemotaxis of human monocytes towards CCL8 is inhibited by monoclonal antibodies. Mean±SEM of migrated cells in 5 high-power fields (HPF). At least 3 independent experiments with cells from different donors. Up-pointing triangle is antibody alone, and down-pointing triangle is buffer control. Two-way RM ANOVA followed by Šídák’s multiple comparisons test. (h) Identification of individuals with high anti-CCL20 N-loop antibodies. Area under the curve (AUC), as determined by ELISA. Average of two independent experiments. COVID-19 convalescents (n=71); controls (n=23). Horizontal bars indicate median values. (i) Monoclonal antibodies to the CCL20 N-loop. ELISA binding curve of a representative antibody. Average of two independent experiments (Mean+SEM). (j) Anti-CCL20 N-loop antibodies inhibit CCL20 chemotaxis to CCR6. Relative cell migration towards CCL20. Mean+SEM of at least 3 independent experiments. Two-tailed Mann–Whitney U-tests. (k) Polyclonal IgGs from COVID-19 convalescents inhibit chemotaxis. Chemotaxis of preB 300.19 cells expressing either CCR2 or CXCR1 towards the indicated chemokines (CCL7 or CCL8 for CCR2; CXCL8 for CXCR1) was measured in the presence of plasma IgGs from COVID-19 convalescents (n=24 for CCL7 and CCL8; n=16 for CXCL8) or controls (n=8). Technical triplicates (Mean±SEM) of migrated cells in 5 high-power fields (HPF). Two-tailed Mann–Whitney U-tests.

Extended Data Fig. 9.. Anti-chemokine N-loop antibodies in HIV-1, autoimmune and Lyme diseases, related to Fig. 4.

(a) The amount of plasma IgG antibodies against each chemokine N-loop was determined by ELISA for HIV-1 infected (n=24, blue) and autoimmune patients (n=39, orange). Autoimmune patients were subdivided in Ankylosing Spondylitis (AS, n=13), Rheumatoid Arthritis (RA, n=13), and Sjögren’s syndrome (SjS, n=13). Values from controls (n=23, black), and COVID-19 convalescents (n=71, green) are shown alongside. Average AUC of two independent experiments. Horizontal bars indicate median values. Statistical significance was determined using Kruskal-Wallis test followed by Dunn’s multiple comparison test over rank of the control group. (b) The amount of plasma IgG antibodies against each chemokine N-loop was determined by ELISA for Borrelia-infected patients (n=27, Lyme disease with erythema migrans) in the acute phase and at 6 months post infection, as measured by ELISA. Average AUC of two independent experiments. Horizontal bars indicate median values. Statistical significance was determined using Kruskal-Wallis test followed by Dunn’s multiple comparison test.

Extended Data Fig. 10.. Clustering of COVID-19, HIV-1 and autoimmune diseases based on anti-chemokine antibodies, related to Fig. 4.

(a) Venn diagram of the chemokines targeted by autoantibodies across the autoimmune disorders AS, RA and SjS. Red and blue colors indicate either an increase or decrease over controls with p<10⁻⁴. (b) Anti-chemokine antibodies correctly classify COVID-19 convalescents, HIV-1-infected, and patients with autoimmune disorders. Heatmap representing the normalized plasma IgG binding to 42 peptides comprising the N-loop sequence of all 43 human chemokines. Unsupervised hierarchical clustering analysis. The distribution of the groups within each cluster is shown.

Fig. 1.. Distinct patterns of anti-chemokine antibodies in COVID-19 convalescents with different severity of acute disease.

(a) Anti-chemokine antibodies 6 months after COVID-19. Heatmap representing plasma IgG binding to 42 peptides comprising the N-loop sequence of all 43 human chemokines, as determined by ELISA (Area Under the Curve [AUC], average of two independent experiments). Samples are ranked according to the level of anti-SARS-CoV-2-RBD reactivity. Anti-chemokine IgGs are ordered by unsupervised clustering analysis of ELISA signal. SARS-CoV-2 pseudovirus neutralizing activity (NT₅₀) and IgG binding to peptides corresponding to negative control, IFNα2 and SARS-CoV-2 nucleocapsid protein (N) are shown. COVID-19 convalescents (n=71); controls (n=23). (b) Difference in IgG antibodies to CCL19, CCL22 and CXCL17 (COVID-19 signature). Horizontal bars indicate median values. Two-tailed Mann–Whitney U-tests. (c) Assignment of COVID-19 convalescents and controls based on the COVID-19 signature antibodies by logistic regression analysis. Dots on grey background are correctly assigned. (d) Anti-COVID-19 signature chemokine IgG antibodies at 6 and 12 months in convalescents. AUC from two independent experiments. Wilcoxon signed-rank test. (e) Difference in anti-chemokine antibodies between COVID-19 groups and controls. Summary circle plot: circle size indicates significance; colors show the Log2 fold-change increase (red) or decrease (blue) over controls. Kruskal-Wallis test followed by Dunn’s multiple comparison test. (f) Difference in total anti-chemokine antibodies. Cumulative signal of the IgGs against the 42 peptides comprising the N-loop sequence of all 43 human chemokines. Horizontal bars indicate median values. Kruskal-Wallis test followed by Dunn’s multiple comparison test. (g) t-SNE distribution of COVID-19 outpatient and hospitalized individuals, as determined with the 42 datasets combined. (h) Assignment of COVID-19 outpatient and hospitalized individuals based on the COVID-19 hospitalization signature antibodies by logistic regression analysis. Dots on grey background are correctly assigned. See also Extended Data Figs. 1–6.

Fig. 2.. Anti-chemokine antibodies and long COVID.

(a) Characteristics of the COVID-19 convalescent Lugano cohort at 12 months. (b) Persisting symptoms (Sx) at 12 months and anti-chemokine IgG (cumulative; left), anti-RBD IgG (middle), and NT₅₀ (right) values at 6 months. Horizontal bars indicate median values. Average AUC from two independent experiments. Kruskal-Wallis test followed by Dunn’s multiple comparison test. (c) Difference in antibodies to CCL21, CXCL13 and CXCL16 (Long COVID signature). Horizontal bars indicate median values. Average AUC from two independent experiments. Two-tailed Mann–Whitney U-tests. (d) Group assignment based on the Long COVID signature antibodies at 6 months against CCL21, CXCL13 and CXCL16, by logistic regression analysis. Dots on grey background are correctly assigned. (e) Anti-CXCL16 antibodies binding to the CXCL16 N-loop in ELISA. Average of two independent experiments (Mean+SEM). (f) Inhibition of chemotaxis by anti-CXCL16 N-loop antibodies. Relative cell migration towards CXCL16 by cells uniquely expressing CXCR6 (see Methods). Mean+SEM of 3 independent experiments. Paired, two-tailed Student’s t test. (g) Anti-CXCL13 antibodies binding to the CXCL13 N-loop in ELISA. Average of two independent experiments (Mean+SEM). (h) The anti-CXCL13 N-loop antibody aCXCL13.001 inhibits CXCL13 chemotaxis of primary CD19⁺ human B cells. Mean±SEM of migrated cells in 5 high-power fields (HPF). Average of 3 independent experiments with cells from different donors. Up-pointing triangles indicate antibody alone, and down-pointing triangle is buffer control. Two-way RM ANOVA followed by Šídák’s multiple comparisons test. See also Extended Data Figs. 7 and 8.

Fig. 3.. Chemokines in plasma during or after COVID-19.

(a) Plasma chemokine levels in the Milan (n=44) and Lugano (n=12) cohorts at the indicated time points after disease onset. Horizontal bars indicate median values. Kruskal-Wallis test followed by Dunn’s multiple comparison test over controls. (b) Levels of COVID-19 hospitalization signature chemokines (CXCL5, CXCL8 and CCL25) in mild versus severe patients (Milan cohort). Horizontal bars indicate median values. Kruskal-Wallis test followed by Dunn’s multiple comparison test. (c) Correlation between chemokine and autoantibody levels determined by Pearson correlation analysis.

Fig. 4.. Distinct patterns of anti-chemokine antibodies in COVID-19, HIV-1 or autoimmune diseases.

(a) Difference in anti-chemokine antibodies between diseases and controls. Summary circle plot: circle size indicates significance; colors show the Log2 fold-change increase (red) or decrease (blue) over controls. Kruskal-Wallis test followed by Dunn’s multiple comparison test. (b) Difference in antibodies to CCL19, CCL4, CCL2, CXCL9 and CXCL12 across groups. Controls (n=23), COVID-19 (n=71), HIV-1 (n=24), Ankylosing Spondylitis (AS, n=13), Rheumatoid Arthritis (RA, n=13), and Sjögren’s syndrome (SjS, n=13). Horizontal bars indicate median values. Average AUC from two independent experiments. Kruskal-Wallis test followed by Dunn’s multiple comparison test over rank of the control group. (c) t-SNE distribution of disease samples, as determined with the 42 datasets combined. See also Extended Data Figs. 9 and 10.