Cited by 223SARS-CoV-2 and COVID-19 ResearchImmune responses and vaccinationsCOVID-19 Clinical Research Studies

The DOI matches its Crossref record, with a small difference in title or year; 58 of the 58 references it cites were found in a registry or an index.

Immunological imprinting of the antibody response in COVID-19 patients

Open access

Published version of a preprint

Abstract

In addition to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), humans are also susceptible to six other coronaviruses, for which consecutive exposures to antigenically related and divergent seasonal coronaviruses are frequent. Despite the prevalence of COVID-19 pandemic and ongoing research, the nature of the antibody response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear. Here we longitudinally profile the early humoral immune response against SARS-CoV-2 in hospitalized coronavirus disease 2019 (COVID-19) patients and quantify levels of pre-existing immunity to OC43, HKU1 and 229E seasonal coronaviruses, and find a strong back-boosting effect to conserved but not variable regions of OC43 and HKU1 betacoronaviruses spike protein. However, such antibody memory boost to human coronaviruses negatively correlates with the induction of IgG and IgM against SARS-CoV-2 spike and nucleocapsid protein. Our findings thus provide evidence of immunological imprinting by previous seasonal coronavirus infections that can potentially modulate the antibody profile to SARS-CoV-2 infection.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-021-23977-1

Cites

58 of 58 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Longitudinal antibody response to SARS-CoV-2 antigens. Serum from hospitalized COVID-19 patients was analyzed at baseline, at hospital recruitment and days 3 and 7. A subsequent sample was collected in the convalescence period in the COVID-19 survivors with mean time of 46 days. A Longitudinal profile of antibodies against SARS-CoV-2. Antibody titer was quantified as area under the curve (AUC) after serial serum dilution for each sample (Supplementary Fig. 1). Calculated AUC at each time is shown to quantify changes over time for each individual (small dots) against immunoglobulin G (IgG) spike, IgG receptor-binding domain (RBD), immunoglobulin M (IgM) spike and IgG nucleocapsid (N); and neutralizing activity (nAb) as inhibitory concentration 50% (IC50%). Geometric mean titer (GMT, big dots) and confidence interval (CI 95%) are also shown. B Boxplot diagram of geometric mean fold rise (GMFR) antibody titers against SARS-CoV-2 at the same time points: IgG spike, IgG RBD, IgM spike and IgG NP; and neutralizing activity (nAb). Related-samples Friedman’s two-way ANOVA was performed. Significant adjusted p values after pairwise comparisons are shown for each comparison. Black bar indicates GMFR values, box indicates IQR (Q1–Q3), lines indicate minimum and maximum. Outliers from the observed distribution are shown. Total n = 116 biologically independent serum samples (day 0 = 37, day 3 = 29, day 7 = 22, day 46 = 28). n = 116 biological samples examined against four different SARS-CoV-2 substrates for ELISA assays; ELISAs for each substrate were run once each. N = 116 serum samples examined over two independent experiments for neutralization assays.
Fig. 1 Longitudinal antibody response to SARS-CoV-2 antigens. Serum from hospitalized COVID-19 patients was analyzed at baseline, at hospital recruitment and days 3 and 7. A subsequent sample was collected in the convalescence period in the COVID-19 survivors with mean time of 46 days. A Longitudinal profile of antibodies against SARS-CoV-2. Antibody titer was quantified as area under the curve (AUC) after serial serum dilution for each sample (Supplementary Fig. 1). Calculated AUC at each time is shown to quantify changes over time for each individual (small dots) against immunoglobulin G (IgG) spike, IgG receptor-binding domain (RBD), immunoglobulin M (IgM) spike and IgG nucleocapsid (N); and neutralizing activity (nAb) as inhibitory concentration 50% (IC50%). Geometric mean titer (GMT, big dots) and confidence interval (CI 95%) are also shown. B Boxplot diagram of geometric mean fold rise (GMFR) antibody titers against SARS-CoV-2 at the same time points: IgG spike, IgG RBD, IgM spike and IgG NP; and neutralizing activity (nAb). Related-samples Friedman’s two-way ANOVA was performed. Significant adjusted p values after pairwise comparisons are shown for each comparison. Black bar indicates GMFR values, box indicates IQR (Q1–Q3), lines indicate minimum and maximum. Outliers from the observed distribution are shown. Total n = 116 biologically independent serum samples (day 0 = 37, day 3 = 29, day 7 = 22, day 46 = 28). n = 116 biological samples examined against four different SARS-CoV-2 substrates for ELISA assays; ELISAs for each substrate were run once each. N = 116 serum samples examined over two independent experiments for neutralization assays.CC BY · PubMed Central
Fig. 2 Conservation of SARS-CoV-2 S protein. A Multiple sequence alignment was generated by the ConSurf algorithm (https://consurf.tau.ac.il) using the chain A of the SARS-CoV-2 spike protein in the closed state (PDB ID 6VXX) as a reference. Amino acid conservation scores were classified into nine levels. Structure of the SARS-CoV-2 S protein (chain A) with amino acid residues colored according to conservation on a scale from green (1, most variable) to dark purple (9, most conserved) is also shown.
Fig. 2 Conservation of SARS-CoV-2 S protein. A Multiple sequence alignment was generated by the ConSurf algorithm (https://consurf.tau.ac.il) using the chain A of the SARS-CoV-2 spike protein in the closed state (PDB ID 6VXX) as a reference. Amino acid conservation scores were classified into nine levels. Structure of the SARS-CoV-2 S protein (chain A) with amino acid residues colored according to conservation on a scale from green (1, most variable) to dark purple (9, most conserved) is also shown.CC BY · PubMed Central
Fig. 3 Longitudinal antibody response to selected seasonal human coronaviruses antigens. Serum from hospitalized COVID-19 patients was analyzed at baseline, at hospital recruitment and days 3 and 7. A subsequent sample was collected in the convalescence period in the COVID-19 survivors with mean time of 46 days. A Longitudinal profile of antibodies against betacoronavirus (HKU1 and OC43) and alphacoronavirus (229E) antigens. Antibody titer was quantified as area under the curve (AUC) after serial serum dilution for each sample (Supplementary Fig. 1). Calculated AUC at each time is shown to quantify changes over time for each individual (small dots) against immunoglobulin G (IgG) HKU1 spike, IgG HKU1 S1, IgG OC43 spike and IgG 229E. Geometric mean titer (GMT, big dots) and confidence interval (CI 95%) are also shown. Hemagglutination inhibition (HI) assay were also performed for OC43 and GMT of end point titers are shown at each time point. B Boxplot diagram of geometric mean fold rise (GMFR) antibody titers against seasonal coronaviruses at the same time points: IgG HKU1 spike, IgG HKU1 S1, IgG OC43 spike and IgG 229E; and HI titer. Related-samples Friedman’s two-way ANOVA was performed. Significant adjusted p values after pairwise comparisons are shown for each comparison. Black bar indicates GMFR values, box indicates IQR (Q1–Q3), lines indicate minimum and maximum. Outliers from the observed distribution are shown. Total n = 116 biologically independent serum samples (day 0 = 37, day 3 = 29, day 7 = 22, day 46 = 28). n = 116 biological samples examined against four different seasonal coronavirus substrates for ELISA assays; ELISAs for each substrate were run once each. N = 116 serum samples examined over two independent experiments for hemagglutination assays.
Fig. 3 Longitudinal antibody response to selected seasonal human coronaviruses antigens. Serum from hospitalized COVID-19 patients was analyzed at baseline, at hospital recruitment and days 3 and 7. A subsequent sample was collected in the convalescence period in the COVID-19 survivors with mean time of 46 days. A Longitudinal profile of antibodies against betacoronavirus (HKU1 and OC43) and alphacoronavirus (229E) antigens. Antibody titer was quantified as area under the curve (AUC) after serial serum dilution for each sample (Supplementary Fig. 1). Calculated AUC at each time is shown to quantify changes over time for each individual (small dots) against immunoglobulin G (IgG) HKU1 spike, IgG HKU1 S1, IgG OC43 spike and IgG 229E. Geometric mean titer (GMT, big dots) and confidence interval (CI 95%) are also shown. Hemagglutination inhibition (HI) assay were also performed for OC43 and GMT of end point titers are shown at each time point. B Boxplot diagram of geometric mean fold rise (GMFR) antibody titers against seasonal coronaviruses at the same time points: IgG HKU1 spike, IgG HKU1 S1, IgG OC43 spike and IgG 229E; and HI titer. Related-samples Friedman’s two-way ANOVA was performed. Significant adjusted p values after pairwise comparisons are shown for each comparison. Black bar indicates GMFR values, box indicates IQR (Q1–Q3), lines indicate minimum and maximum. Outliers from the observed distribution are shown. Total n = 116 biologically independent serum samples (day 0 = 37, day 3 = 29, day 7 = 22, day 46 = 28). n = 116 biological samples examined against four different seasonal coronavirus substrates for ELISA assays; ELISAs for each substrate were run once each. N = 116 serum samples examined over two independent experiments for hemagglutination assays.CC BY · PubMed Central
Fig. 4 Antibody response according to disease severity and viral loads in the BACO cohort. A Boxplot diagram of ELISA as area under the curve (AUC) titers against SARS-CoV-2 and endemic human coronaviruses at each time point in mild/moderate vs. severe COVID-19: IgG spike, IgG RBD, IgM spike and IgG NP; and neutralizing titer (IC50%); and HKU1 IgG spike, HKU1 IgG S1 subunit, OC43 IgG spike and 229E IgG spike; and OC43 hemagglutination titers. Black bar indicated median values, box indicates IQR (Q1–Q3), and lines indicate minimum and maximum. Outliers from the observed distribution are shown when present in each case. Total n = 116 biologically independent serum samples (day 0 = 37, day 3 = 29, day 7 = 22, day 46 = 28). n = 116 biological samples examined against eight different SARS-CoV-2 and seasonal coronavirus substrates for ELISA assays; ELISAs for each substrate were run once each. N = 116 serum samples examined over two independent experiments for neutralization and hemagglutination assays. B Boxplot diagram of mean threshold cycle (Ct) values in mild/moderate vs. severe COVID-19 during the follow-up. N protein was detected by RT-qPCR. Black bars indicate median values, the box indicates IQR (Q1–Q3), and lines indicate minimum and maximum. Outliers from the observed distribution are shown when present in each case. Total n = 93 biologically independent nasopharyngeal swab (day 0 = 37, day 3 = 28, day 7 = 22, day 46 = 6). n = 93 biological samples examined against two different SARS-CoV-2 primers over two independent experiments each. Mann–Whitney U test for independent samples was performed. Reported p values are based on two‐tailed tests. C Scatterplot of the relationship between measured SARS-CoV-2 and seasonal coronaviruses antibody responses and Ct values in the COVID-19 patients. Pearson coefficient of statistically significant correlations is indicated in red. Matrix axis are log10 values scaled from 0 to 4. Total n = 93 biologically independent nasopharyngeal (NP) swab and 93 paired serum samples. Pearson correlation was calculated based on matched NP and serum samples. P values for statistically significant values are shown and based on two‐tailed tests. Source data are provided as a Source Data File.
Fig. 4 Antibody response according to disease severity and viral loads in the BACO cohort. A Boxplot diagram of ELISA as area under the curve (AUC) titers against SARS-CoV-2 and endemic human coronaviruses at each time point in mild/moderate vs. severe COVID-19: IgG spike, IgG RBD, IgM spike and IgG NP; and neutralizing titer (IC50%); and HKU1 IgG spike, HKU1 IgG S1 subunit, OC43 IgG spike and 229E IgG spike; and OC43 hemagglutination titers. Black bar indicated median values, box indicates IQR (Q1–Q3), and lines indicate minimum and maximum. Outliers from the observed distribution are shown when present in each case. Total n = 116 biologically independent serum samples (day 0 = 37, day 3 = 29, day 7 = 22, day 46 = 28). n = 116 biological samples examined against eight different SARS-CoV-2 and seasonal coronavirus substrates for ELISA assays; ELISAs for each substrate were run once each. N = 116 serum samples examined over two independent experiments for neutralization and hemagglutination assays. B Boxplot diagram of mean threshold cycle (Ct) values in mild/moderate vs. severe COVID-19 during the follow-up. N protein was detected by RT-qPCR. Black bars indicate median values, the box indicates IQR (Q1–Q3), and lines indicate minimum and maximum. Outliers from the observed distribution are shown when present in each case. Total n = 93 biologically independent nasopharyngeal swab (day 0 = 37, day 3 = 28, day 7 = 22, day 46 = 6). n = 93 biological samples examined against two different SARS-CoV-2 primers over two independent experiments each. Mann–Whitney U test for independent samples was performed. Reported p values are based on two‐tailed tests. C Scatterplot of the relationship between measured SARS-CoV-2 and seasonal coronaviruses antibody responses and Ct values in the COVID-19 patients. Pearson coefficient of statistically significant correlations is indicated in red. Matrix axis are log10 values scaled from 0 to 4. Total n = 93 biologically independent nasopharyngeal (NP) swab and 93 paired serum samples. Pearson correlation was calculated based on matched NP and serum samples. P values for statistically significant values are shown and based on two‐tailed tests. Source data are provided as a Source Data File.CC BY · PubMed Central
Fig. 5 Immunological imprinting on SARS-CoV-2 antibody response. A, B Heat map of Pearson correlation matrices between pre-existing levels of seasonal hCoV (A IgG HKU1 S; and B IgG OC43 S) and fold induction of SARS-CoV-2 antibodies at each time point: neutralizing (nAb), IgG spike, IgG RBD, IgM spike and IgG NP. Statistically significant correlations in the underlined intersections are indicated with asterisk (*); D3: day 3; D7: day 7; C: convalescence. C, D Scatterplot of baseline IgG levels for HKU1 and OC43 S protein and fold induction of SARS-CoV-2 antibodies: neutralizing (nAb), IgG spike, IgG RBD. Overlay shows relationship with induction of de novo antibodies against SARS-CoV-2 at each time point. Fitted linear regression and standardized beta coefficient (95% confidence interval, CI) for significant linear regressions are shown.
Fig. 5 Immunological imprinting on SARS-CoV-2 antibody response. A, B Heat map of Pearson correlation matrices between pre-existing levels of seasonal hCoV (A IgG HKU1 S; and B IgG OC43 S) and fold induction of SARS-CoV-2 antibodies at each time point: neutralizing (nAb), IgG spike, IgG RBD, IgM spike and IgG NP. Statistically significant correlations in the underlined intersections are indicated with asterisk (*); D3: day 3; D7: day 7; C: convalescence. C, D Scatterplot of baseline IgG levels for HKU1 and OC43 S protein and fold induction of SARS-CoV-2 antibodies: neutralizing (nAb), IgG spike, IgG RBD. Overlay shows relationship with induction of de novo antibodies against SARS-CoV-2 at each time point. Fitted linear regression and standardized beta coefficient (95% confidence interval, CI) for significant linear regressions are shown.CC BY · PubMed Central
Fig. 6 Cross-reactivity with conserved epitopes against selected betacoronaviruses predicts negative influence on de novo anti-SARS-CoV-2 antibody responses. A–D Scatterplot of baseline IgG levels for HKU1, OC43 and 229E S protein; and HKU1 S1 and fold induction of SARS-CoV-2 antibodies: neutralizing (nAb), IgG spike, IgG RBD, IgM spike, and nucleoprotein. Overlay shows relationship with induction of de novo antibodies against SARS-CoV-2 at each time point. Fitted linear regression and standardized beta coefficient (95% Confidence Interval, CI) for significant linear regressions are shown. Reported p values are based on two‐tailed tests.
Fig. 6 Cross-reactivity with conserved epitopes against selected betacoronaviruses predicts negative influence on de novo anti-SARS-CoV-2 antibody responses. A–D Scatterplot of baseline IgG levels for HKU1, OC43 and 229E S protein; and HKU1 S1 and fold induction of SARS-CoV-2 antibodies: neutralizing (nAb), IgG spike, IgG RBD, IgM spike, and nucleoprotein. Overlay shows relationship with induction of de novo antibodies against SARS-CoV-2 at each time point. Fitted linear regression and standardized beta coefficient (95% Confidence Interval, CI) for significant linear regressions are shown. Reported p values are based on two‐tailed tests.CC BY · PubMed Central
Fig. 7 Influence of levels of back-boosting to HKU1 and OC43 normalized by levels of anti- SARS-CoV-2 antibodies on neutralizing antibodies induction. A–D Scatterplot of baseline and day 3 IgG levels for HKU1 and OC43 S protein normalized by the levels of SARS-CoV-2 IgG and their relationships with fold induction of SARS-CoV-2 neutralizing antibodies (nAb) over time. Overlay shows linear regression at each time point. Fitted linear regression and standardized beta coefficient (95% confidence interval, CI) for significant regression are shown. Reported p values are based on two‐tailed tests.
Fig. 7 Influence of levels of back-boosting to HKU1 and OC43 normalized by levels of anti- SARS-CoV-2 antibodies on neutralizing antibodies induction. A–D Scatterplot of baseline and day 3 IgG levels for HKU1 and OC43 S protein normalized by the levels of SARS-CoV-2 IgG and their relationships with fold induction of SARS-CoV-2 neutralizing antibodies (nAb) over time. Overlay shows linear regression at each time point. Fitted linear regression and standardized beta coefficient (95% confidence interval, CI) for significant regression are shown. Reported p values are based on two‐tailed tests.CC BY · PubMed Central
Fig. 8 Imprinting and antibody response against emerging variants of SARS-CoV-2. A ELISA against the receptor-binding domains (RBDs) of Wuhan-Hu-1 (reference), and mutated RBDs representative of UK (N501Y) and South African (K417N, E484K and N501Y) variants. B Neutralizing titers against the authentic hCoV-19/England/204820464/2020 (B.1.1.7) and hCoV-19/South Africa/KRISP-K005325/2020 (B.1.351). Errors indicate geometric mean titer (GMT) and confidence interval (CI 95%) at each time point for ELISA against each RBD or neutralizing titers against each variant. Percentage of decrease titers compared to reference has been calculated and data are shown in the right for ELISA and nAb titers. Total n = 116 biologically independent serum samples (day 0 = 37, day 3 = 29, day 7 = 22, day 46 = 28). n = 116 biological samples examined against three different SARS-CoV-2 RBDs; ELISAs for each substrate were run once each. N = 116 serum samples examined for three different SARS-CoV-2 variants over two independent experiments each. C–D Heat map of Pearson correlation matrices between pre-existing levels of seasonal CoVs: IgG HKU1 S; and B IgG OC43 S; and fold induction of antibodies against RBD N501Y and RBD N501Y, K417N, E484K RBD at each time point. D3 day 3, D7 day 7, C convalescence.
Fig. 8 Imprinting and antibody response against emerging variants of SARS-CoV-2. A ELISA against the receptor-binding domains (RBDs) of Wuhan-Hu-1 (reference), and mutated RBDs representative of UK (N501Y) and South African (K417N, E484K and N501Y) variants. B Neutralizing titers against the authentic hCoV-19/England/204820464/2020 (B.1.1.7) and hCoV-19/South Africa/KRISP-K005325/2020 (B.1.351). Errors indicate geometric mean titer (GMT) and confidence interval (CI 95%) at each time point for ELISA against each RBD or neutralizing titers against each variant. Percentage of decrease titers compared to reference has been calculated and data are shown in the right for ELISA and nAb titers. Total n = 116 biologically independent serum samples (day 0 = 37, day 3 = 29, day 7 = 22, day 46 = 28). n = 116 biological samples examined against three different SARS-CoV-2 RBDs; ELISAs for each substrate were run once each. N = 116 serum samples examined for three different SARS-CoV-2 variants over two independent experiments each. C–D Heat map of Pearson correlation matrices between pre-existing levels of seasonal CoVs: IgG HKU1 S; and B IgG OC43 S; and fold induction of antibodies against RBD N501Y and RBD N501Y, K417N, E484K RBD at each time point. D3 day 3, D7 day 7, C convalescence.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

Sorted by citations

See all 223

Metadata

Authors
Aydillo, T., Rombauts, A., Stadlbauer, D., Aslam, S., Abelenda-Alonso, G., Escalera, A., Amanat, F., Jiang, K., Krammer, F., Carratala, J., & García-Sastre, A.
Affiliations
  • Icahn School of Medicine at Mount Sinai (US)
  • Instituto de Salud Carlos III (ES)
Corresponding author
Krammer, Florian
Venue
Nature Communications
Published
2021-06-18
Volume
12
Issue
1
Pages
3781-3781
ISSN
2041-1723 (ISSN-L)
OpenAlex
W3171762393
Cited by
223
References
57
Citations by year
2026: 14 · 2025: 24 · 2024: 25 · 2023: 46 · 2022: 69 · 2021: 44
FWCI
14.57
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • ImmPort
Funders
Division of Intramural Research, National Institute of Allergy and Infectious Diseases (75N93019C00051)
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Life Sciences › Immunology and Microbiology › Immunology › Immune responses and vaccinations
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
Keywords
immunological imprinting, SARS-CoV-2, COVID-19 pandemic, antibody response, humoral immunity, seasonal coronaviruses, HCoV-OC43, HCoV-HKU1, 229E, spike protein, nucleocapsid protein, pre-existing immunity, IgG, IgM, hospitalized patients
MeSH terms
COVID-19, SARS-CoV-2, Aged, Antibodies, Viral, Antibody Formation, Cross Reactions, Female, Humans, Male, Spike Glycoprotein, Coronavirus

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review