Cited by 678SARS-CoV-2 and COVID-19 ResearchSARS-CoV-2 detection and testingvaccines and immunoinformatics approaches

Viral epitope profiling of COVID-19 patients reveals cross-reactivity and correlates of severity

Open access
Shrock, Ellen, Fujimura, Eric, Kula, Tomasz, Timms, Richard T., Lee, I-Hsiu, Leng, Yumei, Robinson, Matthew L., Sie, Brandon M. +144 more·2020·Science

Abstract

Profiling coronaviruses: Among the coronaviruses that infect humans, four cause mild common colds, whereas three others, including the currently circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), result in severe infections. Shrock et al. used a technology known as VirScan to probe the antibody repertoires of hundreds of coronavirus disease 2019 (COVID-19) patients and pre–COVID-19 era controls. They identified hundreds of antibody targets, including several antibody epitopes shared by the mild and severe coronaviruses and many specific to SARS-CoV-2. A machine-learning model accurately classified patients infected with SARS-CoV-2 and guided the design of an assay for rapid SARS-CoV-2 antibody detection. The study also looked at how the antibody response and viral exposure history differ in patients with diverging outcomes, which could inform the production of improved vaccine and antibody therapies. Science , this issue p. eabd4250

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 · 10.1126/science.abd4250

Cites

39 of 39 references verified0 citation errors · 0 not checkable

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.

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?

  • COVID-19 severity has been linked to the incidence of CMV.

    “COVID-19 severity has been linked to the incidence of CMV, a primary pathogen associated with memory inflation, but more work is needed to establish how CMV and other latent viruses of the elderly affect new memory T cell formation, function, and longevity146.”

    From SARS-CoV-2, COVID-19 and the aging immune system (2021) · cites this paper as [146]

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

Flagged first, then by citations

Research works printed but not linked: 1

  1. [9]National Center for Biotechnology Information, National Library of Medicine, Protein database (2004) [cited 29 February 2020]; www.ncbi.nlm.nih.gov/protein/.

Cited by

Sorted by citations

Authors
Shrock, E., Fujimura, E., Kula, T., Timms, R. T., Lee, I.-H., Leng, Y., Robinson, M. L., Sie, B. M., Li, M. Z., Chen, Y., Logue, J., Zuiani, A., McCulloch, D., Lelis, F. J. N., Henson, S., Monaco, D. R., Travers, M., Habibi, S., Clarke, W. A., Caturegli, P., Laeyendecker, O., Piechocka-Trocha, A., Li, J. Z., Khatri, A., Chu, H. Y., MGH COVID-19 Collection & Processing Team, Villani, A.-C., Kays, K., Goldberg, M. B., Hacohen, N., Filbin, M. R., Yu, X. G., Walker, B. D., Wesemann, D. R., Larman, H. B., Lederer, J. A., Elledge, S. J., Lavin-Parsons, K., Parry, B., Lilley, B., Lodenstein, C., McKaig, B., Charland, N., Khanna, H., Margolin, J., Gonye, A., Gushterova, I., Lasalle, T., Sharma, N., Russo, B. C., Rojas-Lopez, M., Sade-Feldman, M., Manakongtreecheep, K., Tantivit, J., Thomas, M. F., Abayneh, B. A., Allen, P., Antille, D., Armstrong, K., Boyce, S., Braley, J., Branch, K., Broderick, K., Carney, J., Chan, A., Davidson, S., Dougan, M., Drew, D., Elliman, A., Flaherty, K., Flannery, J., Forde, P., Gettings, E., Griffin, A., Grimmel, S., Grinke, K., Hall, K., Healy, M., Henault, D., Holland, G., Kayitesi, C., LaValle, V., Lu, Y., Luthern, S., Marchewka (Schneider), J., Martino, B., McNamara, R., Nambu, C., Nelson, S., Noone, M., Ommerborn, C., Pacheco, L. C., Phan, N., Porto, F. A., Ryan, E., Selleck, K., Slaughenhaupt, S., Sheppard, K. S., Suschana, E., Wilson, V., Alter, G., Balazs, A., Bals, J., Barbash, M., Bartsch, Y., Boucau, J., Chevalier, J., Chowdhury, F., Einkauf, K., Fallon, J., Fedirko, L., Finn, K., Garcia-Broncano, P., Hartana, C., Jiang, C., Kaplonek, P., Karpell, M., Lam, E. C., Lefteri, K., Lian, X., Lichterfeld, M., Lingwood, D., Liu, H., Liu, J., Ly, N., Michell, A., Millstrom, I., Miranda, N., O’Callaghan, C., Osborn, M., Pillai, S., Rassadkina, Y., Reissis, A., Ruzicka, F., Seiger, K., Sessa, L., Sharr, C., Shin, S., Singh, N., Sun, W., Sun, X., Ticheli, H., Trocha-Piechocka, A., Worrall, D., Zhu, A., Daley, G., Golan, D., Heller, H., Sharpe, A., Jilg, N., Rosenthal, A., & Wong, C.
Affiliations
  • Brigham and Women's Hospital (US)
  • Harvard University (US)
  • Johns Hopkins University (US)
  • University of Washington (US)
  • National Institutes of Health (US)
  • Massachusetts Consortium on Pathogen Readiness, Boston, MA, USA.
  • Massachusetts General Hospital (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Shrock, Ellen
  • Fujimura, Eric
  • Kula, Tomasz
  • Timms, Richard T.
  • Elledge, Stephen J.
Venue
Science
Published
2020-11-27
Volume
370
Issue
6520
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W3091214020
Cited by
678
References
38
Citations by year
2026: 31 · 2025: 44 · 2024: 67 · 2023: 105 · 2022: 156 · 2021: 236 · 2020: 39
FWCI
17.56
Type
journal article
Language
en
Open access
Locations
  • Science (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (AI139538)
  • National Cancer Institute (U24)
  • MassCPR (No Number)
  • U.S. Department of Defense (W81XWH-16-1-0464)
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
Keywords
SARS-CoV-2, COVID-19 pandemic, humoral immune response, cross-reactive antibodies, neutralizing antibodies, spike protein, nucleocapsid protein, ORF1, pre-existing antibodies, disease severity, cytomegalovirus, herpes simplex virus type 1, sex differences in antibody response, hospitalized patients
MeSH terms
Seroconversion, COVID-19, SARS-CoV-2, COVID-19 Serological Testing, Antibody Formation, Epitopes, Cross Reactions, Female, Humans, Male, Protein Conformation, Severity of Illness Index, Epitope Mapping, Cryoelectron Microscopy, Antibodies, Neutralizing

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