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Cited by 352SARS-CoV-2 and COVID-19 ResearchCOVID-19 Clinical Research StudiesSARS-CoV-2 detection and testing

The DOI matches its Crossref record; 47 of the 52 references it cites were found in a registry or an index.

Distinct Early Serological Signatures Track with SARS-CoV-2 Survival

Open access
Atyeo, Caroline, Fischinger, Stephanie, Zohar, Tomer, Slein, Matthew D., Burke, John, Loos, Carolin, McCulloch, Denise J., Newman, Kira L., Wolf, Caitlin, Yu, Jingyou, Shuey, Kiel, Feldman, Jared, Hauser, Blake Marie, Caradonna, Tim, Schmidt, Aaron G., Suscovich, Todd J., Linde, Caitlyn, Cai, Yongfei, Barouch, Dan, Ryan, Edward T., Charles, Richelle C., Lauffenburger, Douglas, Chu, Helen, Alter, Galit·2020·Immunity
DOI 10.1016/j.immuni.2020.07.020PMC PMC7392190
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Abstract

As SARS-CoV-2 infections and death counts continue to rise, it remains unclear why some individuals recover from infection, whereas others rapidly progress and die. Although the immunological mechanisms that underlie different clinical trajectories remain poorly defined, pathogen-specific antibodies often point to immunological mechanisms of protection. Here, we profiled SARS-CoV-2-specific humoral responses in a cohort of 22 hospitalized individuals. Despite inter-individual heterogeneity, distinct antibody signatures resolved individuals with different outcomes. Although no differences in SARS-CoV-2-specific IgG levels were observed, spike-specific humoral responses were enriched among convalescent individuals, whereas functional antibody responses to the nucleocapsid were elevated in deceased individuals. Furthermore, this enriched immunodominant spike-specific antibody profile in convalescents was confirmed in a larger validation cohort. These results demonstrate that early antigen-specific and qualitative features of SARS-CoV-2-specific antibodies point to differences in disease trajectory, highlighting the potential importance of functional antigen-specific humoral immunity to guide patient care and vaccine development.

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Crossref · 10.1016/j.immuni.2020.07.020

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Graphical abstract
Graphical abstract CC BY · PubMed Central
Figure 1 Heterogeneity in Antibody Responses across SARS-CoV-2 Antigens in Individuals Who Recover or Pass Away 22 plasma samples from SARS-CoV-2 infected individuals were profiled at the time of hospitalization against SARS-CoV-2 S, RBD, and N antigens. (A) The heatmap shows the humoral immune responses across individuals who later passed away (deceased) or recovered (convalescent). The heatmap is split by SARS-CoV-2 S, RBD, and N antigens. Rows correspond to individuals. Columns correspond to antibody features (background subtracted and Z-scored), including neutralization, isotype, subclass, and antibody effector functions. High responses are shown in red, and low responses are depicted in blue. (B–G): Violin plots show the distribution of each antibody feature split across convalescent (purple) and deceased (orange) individuals across antigens. The dashed gray line indicates the median value of each distribution. A two-sided Mann-Whitney U test was used to calculate uncorrected p values. No significance was detected after a Holm-Bonferroni correction for multiple hypothesis testing.
Figure 1 Heterogeneity in Antibody Responses across SARS-CoV-2 Antigens in Individuals Who Recover or Pass Away 22 plasma samples from SARS-CoV-2 infected individuals were profiled at the time of hospitalization against SARS-CoV-2 S, RBD, and N antigens. (A) The heatmap shows the humoral immune responses across individuals who later passed away (deceased) or recovered (convalescent). The heatmap is split by SARS-CoV-2 S, RBD, and N antigens. Rows correspond to individuals. Columns correspond to antibody features (background subtracted and Z-scored), including neutralization, isotype, subclass, and antibody effector functions. High responses are shown in red, and low responses are depicted in blue. (B–G): Violin plots show the distribution of each antibody feature split across convalescent (purple) and deceased (orange) individuals across antigens. The dashed gray line indicates the median value of each distribution. A two-sided Mann-Whitney U test was used to calculate uncorrected p values. No significance was detected after a Holm-Bonferroni correction for multiple hypothesis testing.CC BY · PubMed Central
Figure 2 Deceased Individuals Showed Less Coordinated and N-Directed Antibody Responses (A) The correlation heatmap shows pairwise Spearman correlation matrices of antigen-specific antibody titers and effector functions for convalescent (left) and deceased (right) patients. For each feature analyzed, the bar covers the S, RBD, and N antigens, shown in the legend on the right. Statistical significance is indicated by gray asterisks with Holm-Bonferroni correction for multiple hypothesis testing (p < 0.001). Negative correlations are indicated in blue, and positive correlations are denoted in red. (B) The Nightingale rose plots show the mean percentile of antibody features within the deceased (top) and convalescent (bottom) groups. Plots represent the S-, RBD-, and N-specific responses across deceased (top) and convalescent (bottom) individuals. Each wedge represents a SARS-CoV-2 antibody feature. The size of the wedge depicts the magnitude of the value. The colors represent the type of feature: orange, antibody functions; purple, antibody isotypes and subclasses.
Figure 2 Deceased Individuals Showed Less Coordinated and N-Directed Antibody Responses (A) The correlation heatmap shows pairwise Spearman correlation matrices of antigen-specific antibody titers and effector functions for convalescent (left) and deceased (right) patients. For each feature analyzed, the bar covers the S, RBD, and N antigens, shown in the legend on the right. Statistical significance is indicated by gray asterisks with Holm-Bonferroni correction for multiple hypothesis testing (p < 0.001). Negative correlations are indicated in blue, and positive correlations are denoted in red. (B) The Nightingale rose plots show the mean percentile of antibody features within the deceased (top) and convalescent (bottom) groups. Plots represent the S-, RBD-, and N-specific responses across deceased (top) and convalescent (bottom) individuals. Each wedge represents a SARS-CoV-2 antibody feature. The size of the wedge depicts the magnitude of the value. The colors represent the type of feature: orange, antibody functions; purple, antibody isotypes and subclasses.CC BY · PubMed Central
Figure 3 Select Antibody Features Distinguish Convalescent and Deceased Individuals (A) The PLSDA score plot shows the degree of discrimination that was achievable across the groups following feature-down selection. Each dot represents an individual: convalescent (purple) and deceased (orange). Ellipses correspond to the 95% confidence intervals for each group. (B) The line graph shows the variable importance in projection (VIP) score of the selected features. As few as 5 features were required to separate the groups. The magnitude indicates the importance of the feature in driving separation in the model. The color of the feature corresponds to the group in which the feature is enriched. (C) The violin plots show the distributions of repeated classification accuracy tests using the actual data, shuffled labels, and randomly selected size-matched features, illustrating the performance and robustness of the model. Green squares indicate the median accuracies. (D) The predictive power of the model built on the selected features is shown in the LV1 column. In addition, the predictive power of each individual selected feature is represented in gray. The predictive power is illustrated as the area under the curve (AUC) of the receiver operating characteristic (ROC) curves for the model (LV1) or each feature alone. (E) The radar plot shows the Z-scored univariate values of the selected features across both groups. (F) The correlation network illustrates the co-correlated features (small nodes) that are significantly correlated with the model-selected features (large nodes). Edge transparency corresponds to correlation strength. Antigens are indicated by different colors (S, teal; N, gray; RBD, black).
Figure 3 Select Antibody Features Distinguish Convalescent and Deceased Individuals (A) The PLSDA score plot shows the degree of discrimination that was achievable across the groups following feature-down selection. Each dot represents an individual: convalescent (purple) and deceased (orange). Ellipses correspond to the 95% confidence intervals for each group. (B) The line graph shows the variable importance in projection (VIP) score of the selected features. As few as 5 features were required to separate the groups. The magnitude indicates the importance of the feature in driving separation in the model. The color of the feature corresponds to the group in which the feature is enriched. (C) The violin plots show the distributions of repeated classification accuracy tests using the actual data, shuffled labels, and randomly selected size-matched features, illustrating the performance and robustness of the model. Green squares indicate the median accuracies. (D) The predictive power of the model built on the selected features is shown in the LV1 column. In addition, the predictive power of each individual selected feature is represented in gray. The predictive power is illustrated as the area under the curve (AUC) of the receiver operating characteristic (ROC) curves for the model (LV1) or each feature alone. (E) The radar plot shows the Z-scored univariate values of the selected features across both groups. (F) The correlation network illustrates the co-correlated features (small nodes) that are significantly correlated with the model-selected features (large nodes). Edge transparency corresponds to correlation strength. Antigens are indicated by different colors (S, teal; N, gray; RBD, black).CC BY · PubMed Central
Figure 4 Converging Shift in Immunity across a Second Acute Infection Cohort (A and B) The Nightingale rose plots show the mean percentile of the spike:nucleocapsid (S:N) ratio of each readout are depicted for (A) the Seattle or discovery cohort and (B) the Boston or validation cohort for convalescents (left) and deceased (right). Titers are shown as pink wedges and functions as blue wedges. (C) The whisker boxplots show the number of S features that are greater than their N counterparts for all individuals in the Seattle or discovery cohort (left) and the Boston or validation cohort (right). Differences across the 2 groups were assessed using a one-sided Mann-Whitney U test.
Figure 4 Converging Shift in Immunity across a Second Acute Infection Cohort (A and B) The Nightingale rose plots show the mean percentile of the spike:nucleocapsid (S:N) ratio of each readout are depicted for (A) the Seattle or discovery cohort and (B) the Boston or validation cohort for convalescents (left) and deceased (right). Titers are shown as pink wedges and functions as blue wedges. (C) The whisker boxplots show the number of S features that are greater than their N counterparts for all individuals in the Seattle or discovery cohort (left) and the Boston or validation cohort (right). Differences across the 2 groups were assessed using a one-sided Mann-Whitney U test.CC BY · PubMed Central

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Research works printed but not linked: 1

  1. Wang, 2020, Neutralizing Antibodies Responses to SARS-CoV-2 in COVID-19 Inpatients and Convalescent Patients, Clin. Infect. Dis.

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Metadata

Authors
Atyeo, C., Fischinger, S., Zohar, T., Slein, M. D., Burke, J., Loos, C., McCulloch, D. J., Newman, K. L., Wolf, C., Yu, J., Shuey, K., Feldman, J., Hauser, B. M., Caradonna, T., Schmidt, A. G., Suscovich, T. J., Linde, C., Cai, Y., Barouch, D., Ryan, E. T., Charles, R. C., Lauffenburger, D., Chu, H., & Alter, G.
Affiliations
  • Harvard University (US)
  • Ragon Institute of MGH, MIT and Harvard (US)
  • University of Washington (US)
  • Beth Israel Deaconess Medical Center (US)
  • Boston Children's Hospital (US)
  • Massachusetts General Hospital (US)
  • Massachusetts Institute of Technology (US)
Corresponding author
  • Chu, Helen
  • Alter, Galit
ORCID
Venue
Immunity
Publisher
Elsevier BV
Published
2020-09
Volume
53
Issue
3
Pages
524-532.e4
ISSN
1074-7613 (ISSN-L)
DOI
10.1016/j.immuni.2020.07.020
PMC
PMC7392190
OpenAlex
W3045933491
Cited by
349
References
52
Citations by year
2026: 7 · 2025: 20 · 2024: 30 · 2023: 41 · 2022: 69 · 2021: 138 · 2020: 44
FWCI
9.58
Type
journal article
Language
en
Open access
Licence
Locations
  • Immunity (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Universitätsbibliographie, Universität Duisburg-Essen (submittedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
Funders
  • National Institute of Allergy and Infectious Diseases
  • Centers for Disease Control and Prevention
  • Bill and Melinda Gates Foundation
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
Keywords
SARS-CoV-2, COVID-19 pandemic, humoral immunity, spike-specific antibodies, nucleocapsid antibodies, disease outcome prediction, convalescence, hospitalized patients, immunodominant epitopes
MeSH terms
Betacoronavirus, COVID-19, SARS-CoV-2, Coronavirus Nucleocapsid Proteins, Adult, Aged, Aged, 80 and over, Antibodies, Viral, Female, Humans, Immunoglobulin G, Male, Middle Aged, Phosphoproteins, Pneumonia, Viral, Coronavirus Infections, Nucleocapsid Proteins, Immunity, Humoral, Pandemics, Spike Glycoprotein, Coronavirus

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