Compromised Humoral Functional Evolution Tracks with SARS-CoV-2 Mortality
Open accessAbstract
The urgent need for an effective SARS-CoV-2 vaccine has forced development to progress in the absence of well-defined correlates of immunity. While neutralization has been linked to protection against other pathogens, whether neutralization alone will be sufficient to drive protection against SARS-CoV-2 in the broader population remains unclear. Therefore, to fully define protective humoral immunity, we dissected the early evolution of the humoral response in 193 hospitalized individuals ranging from moderate to severe. Although robust IgM and IgA responses evolved in both survivors and non-survivors with severe disease, non-survivors showed attenuated IgG responses, accompanied by compromised Fcɣ receptor binding and Fc effector activity, pointing to deficient humoral development rather than disease-enhancing humoral immunity. In contrast, individuals with moderate disease exhibited delayed responses that ultimately matured. These data highlight distinct humoral trajectories associated with resolution of SARS-CoV-2 infection and the need for early functional humoral immunity.
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.
Integrity signals
Registry
Cites
Statistics
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.
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?
Neutralization measurement does not account for Fc effector functions; Fcγ receptor or complement engagement by antibodies could confer protection.
“this measurement does not account for Fc effector functions; Fcγ receptor or complement protein engagement by non-, weakly-, or strongly- neutralizing antibodies that bind the SARS-CoV-2 spike protein on the surface of infected cells could confer substantial protection39–41.”
From Resistance of SARS-CoV-2 variants to neutralization by monoclonal and serum-derived polyclonal antibodies (2021) · cites this paper as [40]
A bias toward nucleocapsid antibodies over Spike antibodies in fatal cases is consistent with a role for Spike antibodies in reducing viral loads.
“A bias toward nucleocapsid antibodies over Spike antibodies in fatal cases was observed in a pair of studies (Atyeo et al., 2020; Zohar et al., 2020), which is consistent with a role for Spike antibodies in reducing viral loads.”
From Adaptive immunity to SARS-CoV-2 and COVID-19 (2021) · cites this paper as Zohar et al., 2020
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Scikit-learn: Machine Learning in Python
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Müller, A., Nothman, J., Louppe, G., et al. (2012) · arXiv · doi:10.48550/arxiv.1201.0490 · Cited by 71,016 · see citing works
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
Model selection and multimodel inference: a practical information-theoretic approach.
Guthery, F. S., Burnham, K. P., & Anderson, D. R. (2003) · The Journal of Wildlife Management · doi:10.2307/3802723 · Cited by 41,495 · see citing works
Information Theory and an Extension of the Maximum Likelihood Principle
Akaike, H. (1998) · Springer series in statistics · doi:10.1007/978-1-4612-1694-0_15 · Cited by 18,384 · see citing works
Wu, Z., & McGoogan, J. M. (2020) · JAMA · doi:10.1001/jama.2020.2648 · Cited by 17,016 · see citing works
Wold, S., Esbensen, K. H., & Geladi, P. L. M. (1987) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/0169-7439(87)80084-9 · Cited by 11,792 · see citing works
Fast, sensitive and accurate integration of single-cell data with Harmony
Korsunsky, I., Millard, N., Fan, J., Slowikowski, K., Zhang, F., Wei, K., Baglaenko, Y., Brenner, M., Loh, P.-R., & Raychaudhuri, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0619-0 · Cited by 10,488 · see citing works
Richardson, S., Hirsch, J. S., Narasimhan, M., Crawford, J. M., McGinn, T., Davidson, K. W., and the Northwell COVID-19 Research Consortium, Barnaby, D. P., Becker, L. B., Chelico, J. D., et al. (2020) · JAMA · doi:10.1001/jama.2020.6775 · Cited by 9,254 · see citing works
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101 · see citing works
Factors associated with COVID-19-related death using OpenSAFELY
Williamson, E. J., Walker, A. J., Bhaskaran, K., Bacon, S., Bates, C., Morton, C. E., Curtis, H. J., Mehrkar, A., Evans, D., Inglesby, P., et al. (2020) · Nature · doi:10.1038/s41586-020-2521-4 · Cited by 6,674 · see citing works
Fast gene set enrichment analysisPreprint
Korotkevich, G., Sukhov, V., Budin, N., Shpak, B., Artyomov, M. N., & Sergushichev, A. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/060012 · Cited by 3,742 · see citing works
Fcγ receptors as regulators of immune responses
Nimmerjahn, F., & Ravetch, J. V. (2008) · Nature Reviews Immunology · doi:10.1038/nri2206 · Cited by 2,947 · see citing works
Antibody responses to SARS-CoV-2 in patients with COVID-19
Long, Q.-X., Liu, B.-Z., Deng, H.-J., Wu, G.-C., Deng, K., Chen, Y.-K., Liao, P., Qiu, J.-F., Lin, Y., Cai, X.-F., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0897-1 · Cited by 2,876 · see citing works
IgG Subclasses and Allotypes: From Structure to Effector Functions
Vidarsson, G., Dekkers, G., & Rispens, T. (2014) · Frontiers in Immunology · doi:10.3389/fimmu.2014.00520 · Cited by 2,667 · see citing works
Folegatti, P. M., Ewer, K. J., Aley, P. K., Angus, B., Becker, S., Belij-Rammerstorfer, S., Bellamy, D., Bibi, S., Bittaye, M., Clutterbuck, E. A., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)31604-4 · Cited by 2,419 · see citing works
Convergent Antibody Responses to SARS-CoV-2 in Convalescent Individuals
Robbiani, D. F., Gaebler, C., Muecksch, F., Lorenzi, J. C. C., Wang, Z., Cho, A., Agudelo, M., Barnes, C. O., Gazumyan, A., Finkin, S., et al. (2020) · Nature · doi:10.1038/s41586-020-2456-9 · Cited by 1,853 · see citing works
A serological assay to detect SARS-CoV-2 seroconversion in humans
Amanat, F., Stadlbauer, D., Strohmeier, S., Nguyen, T. H. O., Chromikova, V., McMahon, M., Jiang, K., Arunkumar, G. A., Jurczyszak, D., Polanco, J., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0913-5 · Cited by 1,769 · see citing works
Correlates of protection induced by vaccination
Plotkin, S. A. (2010) · Clinical and Vaccine Immunology · doi:10.1128/cvi.00131-10 · Cited by 1,745 · see citing works
SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19
Braun, J., Loyal, L., Frentsch, M., Wendisch, D., Georg, P., Kurth, F., Hippenstiel, S., Dingeldey, M., Kruse, B., Fauchere, F., et al. (2020) · Nature · doi:10.1038/s41586-020-2598-9 · Cited by 1,310 · see citing works
Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans
Mateus, J., Grifoni, A., Tarke, A., Sidney, J., Ramirez, S. I., Dan, J. M., Burger, Z. C., Rawlings, S. A., Smith, D. M., Phillips, E., et al. (2020) · Science · doi:10.1126/science.abd3871 · Cited by 1,120 · see citing works
DNA vaccine protection against SARS-CoV-2 in rhesus macaques
Yu, J., Tostanoski, L. H., Peter, L., Mercado, N. B., McMahan, K., Mahrokhian, S. H., Nkolola, J. P., Liu, J., Li, Z., Chandrashekar, A., et al. (2020) · Science · doi:10.1126/science.abc6284 · Cited by 997 · see citing works
Self-citationChAdOx1 nCoV-19 vaccine prevents SARS-CoV-2 pneumonia in rhesus macaques
van Doremalen, N., Lambe, T., Spencer, A., Belij-Rammerstorfer, S., Purushotham, J. N., Port, J. R., Avanzato, V. A., Bushmaker, T., Flaxman, A., Ulaszewska, M., et al. (2020) · Nature · doi:10.1038/s41586-020-2608-y · Cited by 914 · see citing works
SARS-CoV-2 infection protects against rechallenge in rhesus macaques
Chandrashekar, A., Liu, J., Martinot, A. J., McMahan, K., Mercado, N. B., Peter, L., Tostanoski, L. H., Yu, J., Maliga, Z., Nekorchuk, M., et al. (2020) · Science · doi:10.1126/science.abc4776 · Cited by 816 · cited 1× · see citing works
“However, recent data from vaccine studies point to protective effects of antibodies against SARS-CoV-2 infection and disease (Chandrashekar et al., 2020).”
Self-citationBeyond binding: antibody effector functions in infectious diseases
Lu, L. L., Suscovich, T. J., Fortune, S. M., & Alter, G. (2017) · Nature reviews. Immunology · doi:10.1038/nri.2017.106 · Cited by 810 · see citing works
Self-citationLoss of Bcl-6-Expressing T Follicular Helper Cells and Germinal Centers in COVID-19
Kaneko, N., Kuo, H.-H., Boucau, J., Farmer, J. R., Allard-Chamard, H., Mahajan, V. S., Piechocka-Trocha, A., Lefteri, K., Osborn, M., Bals, J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.025 · Cited by 734 · see citing works
Self-citationComprehensive mapping of immune perturbations associated with severe COVID-19
Kuri-Cervantes, L., Pampena, M. B., Meng, W., Rosenfeld, A. M., Ittner, C. A. G., Weisman, A. R., Agyekum, R. S., Mathew, D., Baxter, A. E., Vella, L. A., et al. (2020) · Science Immunology · doi:10.1126/sciimmunol.abd7114 · Cited by 723 · see citing works
A DNA vaccine induces SARS coronavirus neutralization and protective immunity in mice
Yang, Z.-Y., Kong, W., Huang, Y., Roberts, A., Murphy, B., Subbarao, K., & Nabel, G. (2004) · Nature · doi:10.1038/nature02463 · Cited by 688 · see citing works
Permutation Tests for Studying Classifier Performance
Ojala, M., & Garriga, G. C. (2009) · Proceedings · doi:10.1109/icdm.2009.108 · Cited by 578 · see citing works
A Functional Role for Antibodies in Tuberculosis
Lu, L. L., Chung, A. W., Rosebrock, T. R., Ghebremichael, M. S., Yu, W., Grace, P. S., Schoen, M. K., Tafesse, F., Martin, C. J., Leung, V. W. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.072 · Cited by 560 · see citing works
Self-citationPermutation Tests for Complex Data: Theory, Applications and Software
Pesarin, F., & Salmaso, L. (2010) · Wiley Series in Probability and Statistics · doi:10.1002/9780470689516 · Cited by 515 · see citing works
Host Immune Response to Influenza A Virus Infection
Chen, X., Liu, S., Goraya, M. U., Maarouf, M., Huang, S., & Chen, J. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00320 · Cited by 461 · see citing works
A robust, high-throughput assay to determine the phagocytic activity of clinical antibody samples
Ackerman, M. E., Moldt, B., Wyatt, R. T., Dugast, A., McAndrew, E. G., Tsoukas, S., Jost, S., Berger, C. T., Sciaranghella, G., Liu, Q., et al. (2010) · Journal of Immunological Methods · doi:10.1016/j.jim.2010.12.016 · Cited by 454 · see citing works
Self-citationDissecting polyclonal vaccine-induced humoral immunity against HIV using Systems Serology
Chung, A., Kumar, M. P., Arnold, K. B., Yu, W.-H., Schoen, M., Dunphy, L. J., Suscovich, T., Frahm, N., Linde, C., Mahan, A. E., et al. (2015) · Cell · doi:10.1016/j.cell.2015.10.027 · Cited by 360 · see citing works
Self-citationDistinct Early Serological Signatures Track with SARS-CoV-2 Survival
Atyeo, C., Fischinger, S., Zohar, T., Slein, M. D., Burke, J., Loos, C., McCulloch, D. J., Newman, K. L., Wolf, C., Yu, J., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.07.020 · Cited by 349 · see citing works
Self-citationPermutation Tests for Studying Classifier Performance
Ojala, M., & Garriga, G. C. (2010) · Journal of Machine Learning Research · doi:10.5555/1756006.1859913 · Cited by 343 · see citing works
Jefferis, R., Lund, J., & Pound, J. D. (1998) · Immunological Reviews · doi:10.1111/j.1600-065x.1998.tb01188.x · Cited by 330 · see citing works
In the eye of the COVID-19 cytokine storm
Vaninov, N. (2020) · Nature reviews. Immunology · doi:10.1038/s41577-020-0305-6 · Cited by 315 · see citing works
Lessons Learned from Quantitative Dynamical Modeling in Systems Biology
Raue, A., Schilling, M., Bachmann, J., Matteson, A., Schelke, M., Kaschek, D., Hug, S., Kreutz, C., Harms, B. D., Theis, F. J., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074335 · Cited by 307 · see citing works
ChAdOx1 nCoV-19 vaccination prevents SARS-CoV-2 pneumonia in rhesus macaques
van Doremalen, N., Lambe, T., Spencer, A., Belij-Rammerstorfer, S., Purushotham, J. N., Port, J. R., Avanzato, V., Bushmaker, T., Flaxman, A., Ulaszewska, M., et al. (2020) · doi:10.1101/2020.05.13.093195 · Cited by 246 · see citing works
Effects of aging on T cell function
Haynes, L., & Maue, A. C. (2009) · Current Opinion in Immunology · doi:10.1016/j.coi.2009.05.009 · Cited by 244 · see citing works
Non‐parametric combination and related permutation tests for neuroimaging
Winkler, A. M., Webster, M., Brooks, J. C. W., Tracey, I., Smith, S. M., & Nichols, T. E. (2016) · Human Brain Mapping · doi:10.1002/hbm.23115 · Cited by 237 · see citing works
High-throughput, multiplexed IgG subclassing of antigen-specific antibodies from clinical samples
Brown, E. P., Licht, A. F., Dugast, A.-S., Choi, I., Bailey-Kellogg, C., Alter, G., & Ackerman, M. E. (2012) · Journal of Immunological Methods · doi:10.1016/j.jim.2012.09.007 · Cited by 231 · see citing works
Self-citationDissecting antibody-mediated protection against SARS-CoV-2
Zohar, T., & Alter, G. (2020) · Nature reviews. Immunology · doi:10.1038/s41577-020-0359-5 · Cited by 231 · see citing works
Self-citationMurin, C. D., Wilson, I. A., & Ward, A. B. (2019) · Nature Microbiology · doi:10.1038/s41564-019-0392-y · Cited by 210 · see citing works
Fischinger, S., Fallon, J. K., Michell, A. R., Broge, T. A., Suscovich, T. J., Streeck, H., & Alter, G. (2019) · Journal of Immunological Methods · doi:10.1016/j.jim.2019.07.002 · Cited by 201 · see citing works
Self-citationCD4 T cell differentiation in type 1 diabetes
Walker, L. S. K., & von Herrath, M. (2015) · Clinical & Experimental Immunology · doi:10.1111/cei.12672 · Cited by 182 · see citing works
A versatile high-throughput assay to characterize antibody-mediated neutrophil phagocytosis
Karsten, C. B., Mehta, N., Shin, S. A., Diefenbach, T. J., Slein, M. D., Karpinski, W., Irvine, E. B., Broge, T. A., Suscovich, T. J., & Alter, G. (2019) · Journal of Immunological Methods · doi:10.1016/j.jim.2019.05.006 · Cited by 154 · see citing works
Self-citationHIV-1-specific antibody responses during acute and chronic HIV-1 infection
Tomaras, G. D., & Haynes, B. F. (2009) · Current Opinion in HIV and AIDS · doi:10.1097/coh.0b013e32832f00c0 · Cited by 149 · see citing works
Bergqvist, P. J., Stensson, A., Lycke, N. Y., & Bemark, M. (2010) · The Journal of Immunology · doi:10.4049/jimmunol.0901895 · Cited by 131 · see citing works
Plasmodium malaria and antimalarial antibodies in the first year of life
Dobbs, K. R., & Dent, A. E. (2016) · Parasitology · doi:10.1017/s0031182015001626 · Cited by 116 · see citing works
Obesity altered T cell metabolism and the response to infection
Green, W. D., & Beck, M. A. (2017) · Current Opinion in Immunology · doi:10.1016/j.coi.2017.03.008 · Cited by 105 · see citing works
The Fc receptor for IgA (FcαRI, CD89)
Otten, M. A., & van Egmond, M. (2004) · Immunology Letters · doi:10.1016/j.imlet.2003.11.018 · Cited by 103 · see citing works
Benchmark problems for dynamic modeling of intracellular processes
Hass, H., Loos, C., Raimúndez, E., Timmer, J., Hasenauer, J., & Kreutz, C. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz020 · Cited by 80 · see citing works
Self-citationA Case for Antibodies as Mechanistic Correlates of Immunity in Tuberculosis
Kawahara, J., Irvine, E. B., & Alter, G. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.00996 · Cited by 50 · see citing works
Self-citationNeutrophils mediate HIV-specific antibody-dependent phagocytosis and ADCC
Worley, M. J., Fei, K., López‐Denman, A. J., Kelleher, A. D., Kent, S. J., & Chung, A. W. (2018) · Journal of Immunological Methods · doi:10.1016/j.jim.2018.03.007 · Cited by 43 · see citing works
Robust parameter estimation for dynamical systems from outlier-corrupted data
Maier, C., Loos, C., & Hasenauer, J. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw703 · Cited by 34 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- Pesarin F. Salmaso L. Permutation Tests for Complex Data 2010 John Wiley & Sons, Ltd
Cited by
Sorted by citations
Adaptive immunity to SARS-CoV-2 and COVID-19
Sette, A., & Crotty, S. (2021) · Cell · doi:10.1016/j.cell.2021.01.007 · Cited by 1,860 · see citing works
Chen, R. E., Zhang, X., Case, J. B., Winkler, E. S., Liu, Y., VanBlargan, L. A., Liu, J., Errico, J. M., Xie, X., Suryadevara, N., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01294-w · Cited by 881 · see citing works
Winkler, E. S., Gilchuk, P., Yu, J., Bailey, A. L., Chen, R. E., Chong, Z., Zost, S. J., Jang, H., Huang, Y., Allen, J. D., et al. (2021) · Cell · doi:10.1016/j.cell.2021.02.026 · Cited by 366 · see citing works
Self-citationRichardson, S. I., Madzorera, V. S., Spencer, H., Manamela, N. P., van der Mescht, M. A., Lambson, B. E., Oosthuysen, B., Ayres, F., Makhado, Z., Moyo-Gwete, T., et al. (2022) · Cell Host & Microbe · doi:10.1016/j.chom.2022.03.029 · Cited by 119 · see citing works
Graham, C., Seow, J., Huettner, I., Khan, H., Kouphou, N., Acors, S., Winstone, H., Pickering, S., Galao, R. P., Lista, M. J., et al. (2021) · doi:10.1101/2021.02.03.429355 · Cited by 27 · see citing works
Decay of Fc-dependent antibody functions after mild to moderate COVID-19
Lee, W. S., Selva, K. J., Davis, S. K., Wines, B. D., Reynaldi, A., Esterbauer, R., Kelly, H. G., Haycroft, E. R., Tan, H.-X., Juno, J. A., et al. (2020) · doi:10.1101/2020.12.13.20248143 · Cited by 80 · see citing works
- Authors
- Zohar, T., Loos, C., Fischinger, S., Atyeo, C., Wang, C., Slein, M. D., Burke, J., Yu, J., Feldman, J., Hauser, B. M., Caradonna, T., Schmidt, A. G., Cai, Y., Streeck, H., Ryan, E. T., Barouch, D. H., Charles, R. C., Lauffenburger, D. A., & Alter, G.
- Affiliations
- Ragon Institute of MGH, MIT and Harvard (US)
- Harvard University (US)
- Massachusetts Institute of Technology (US)
- Beth Israel Deaconess Medical Center (US)
- Boston Children's Hospital (US)
- University of Bonn (DE)
- Corresponding author
- Charles, Richelle C.
- Lauffenburger, Douglas A.
- Alter, Galit
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 183
- Issue
- 6
- Pages
- 1508-1519.e12
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC7608014
- OpenAlex
- W3095217725
- Cited by
- 297
- References
- 56
- Citations by year
- 2026: 11 · 2025: 20 · 2024: 38 · 2023: 43 · 2022: 97 · 2021: 81 · 2020: 6
- FWCI
- 7.45
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- ImmPort
- Funders
- National Institute of Allergy and Infectious Diseases
- Centers for Disease Control and Prevention
- Massachusetts General Hospital
- National Institutes of Health
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Life Sciences › Immunology and Microbiology › Immunology › Immune responses and vaccinations
- Keywords
- SARS-CoV-2, humoral immunity, neutralizing antibodies, IgG antibody response, Fcγ receptor binding, Fc effector functions, COVID-19 mortality, hospitalized patients, disease severity, antibody kinetics, vaccine correlates of protection
- MeSH terms
- COVID-19, SARS-CoV-2, Female, Humans, Immunoglobulin A, Immunoglobulin M, Male, Receptors, IgG, HL-60 Cells, Immunity, Humoral
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
