Evidence map›Paper›PMID 33412089›Full record

ArticleCell2021

COVID-19-neutralizing antibodies predict disease severity and survival.

Wilfredo F Garcia-Beltran, Evan C Lam, Michael G Astudillo, Diane Yang, Tyler E Miller, Jared Feldman, Blake M Hauser, Timothy M Caradonna, Kiera L Clayton, Adam D Nitido and 10 more

Abstract read
In one paragraph

Article in Cell, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 492 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
492citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

492 citing papers in PubMed, 1 synthesis or guideline pooled it.

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432 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors.

Wilfredo F Garcia-BeltranDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
Evan C LamRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
Michael G AstudilloDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
Diane YangDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
Tyler E MillerDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
Jared FeldmanRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
Blake M HauserRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
Timothy M CaradonnaRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
Kiera L ClaytonRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
Adam D NitidoRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
Mandakolathur R MuraliDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
Galit AlterRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
Richelle C CharlesInfectious Disease Unit, Massachusetts General Hospital, Boston, MA 02114, USA.
Anand DigheDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
John A BrandaDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
Jochen K LennerzDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
Daniel LingwoodRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
Aaron G SchmidtRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA.
A John IafrateDepartment of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.
Alejandro B BalazsRagon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA. Electronic address: abalazs@mgh.harvard.edu.

Funding

Medical Scientist Training ProgramT32GM007753 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI WALENSKY, LOREN DAVID · 1985 to 2021
$50.0M
MOLECULAR BIOPHYSICS TRAINING GRANTT32GM008313 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI MURTHY, VENKATESH N · 1989 to 2023
$14.6M
MOLECULAR BASIS OF VIRAL INFECTIVITYT32AI007245 · NIAID · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI Aaron Gregory Schmidt · 1985 to 2026
$11.3M
Epitope focusing to the receptor binding motif for a universal coronavirus vaccineR01AI146779 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI SCHMIDT, AARON GREGORY · 2019 to 2023
$4.2M
Innate-like BCR activity as a template for universal vaccination against influenza virusR01AI137057 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI CHACKERIAN, BRYCE C, LINGWOOD, DANIEL · 2018 to 2022
$2.6M
Engineering Humoral Immunity to Functionally Cure HIV InfectionDP2DA040254 · NIDA · MASSACHUSETTS GENERAL HOSPITAL · PI BALAZS, ALEJANDRO BENJAMIN · 2015 to 2015
$2.6M
Defining and Exploiting a Genetic Template for an HIV VaccineDP2DA042422 · NIDA · MASSACHUSETTS GENERAL HOSPITAL · PI LINGWOOD, DANIEL · 2016 to 2016
$2.6M
Triggering germline-encoded broadly neutralizing antibody responses against influenza virusR01AI153098 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI BATISTA, FACUNDO DAMIAN, LINGWOOD, DANIEL · 2020 to 2023
$2.1M
CDRH3-independent B cell stimulation to selectively expand VRC01 lineages from a fully humanized immunoglobulin repertoireR01AI124378 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI CHACKERIAN, BRYCE C, LINGWOOD, DANIEL · 2017 to 2020
$2.0M
Systemic coordination of pro-inflammatory immune reactions through dendritic cell-restricted sIL6R biogenesisR01AI155447 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI LINGWOOD, DANIEL · 2021 to 2025
$2.0M
Borrelia antigen detection assay for urine-based diagnosis of early Lyme diseaseR21AI119457 · NIAID · BOSTON CHILDREN'S HOSPITAL · PI POLLOCK, NIRA · 2015 to 2016
$551k
Characterization of CD8+ T cell killer activity and the mechanisms responsible for detachment from dead target cellsF32AI143480 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI CLAYTON, KIERA L. · 2019 to 2020
$133k
NIAID NIH HHS F32 AI143480NIAID NIH HHS R01 AI124378NIAID NIH HHS R01 AI137057NIAID NIH HHS R01 AI146779NIAID NIH HHS R01 AI153098NIAID NIH HHS R01 AI155447NIAID NIH HHS R21 AI119457NIAID NIH HHS T32 AI007245NIDA NIH HHS DP2 DA040254NIDA NIH HHS DP2 DA042422NIGMS NIH HHS T32 GM007753NIGMS NIH HHS T32 GM008313
6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) exhibits variable symptom severity ranging from asymptomatic to life-threatening, yet the relationship between severity and the humoral immune response is poorly understood. We examined antibody responses in 113 COVID-19 patients and found that severe cases resulting in intubation or death exhibited increased inflammatory markers, lymphopenia, pro-inflammatory cytokines, and high anti-receptor binding domain (RBD) antibody levels. Although anti-RBD immunoglobulin G (IgG) levels generally correlated with neutralization titer, quantitation of neutralization potency revealed that high potency was a predictor of survival. In addition to neutralization of wild-type SARS-CoV-2, patient sera were also able to neutralize the recently emerged SARS-CoV-2 mutant D614G, suggesting cross-protection from reinfection by either strain. However, SARS-CoV-2 sera generally lacked cross-neutralization to a highly homologous pre-emergent bat coronavirus, WIV1-CoV, which has not yet crossed the species barrier. These results highlight the importance of neutralizing humoral immunity on disease progression and the need to develop broadly protective interventions to prevent future coronavirus pandemics.

Indexed as

AdultAntibodies, NeutralizingAntibodies, ViralBiomarkersComorbidityCoronavirusCOVID-19Cross ReactionsCytokinesEnzyme-Linked Immunosorbent AssayFemaleHumansImmunoglobulin AImmunoglobulin GImmunoglobulin MMaleAntibodies, NeutralizingAntibodies, ViralBiomarkersCytokinesImmunoglobulin AImmunoglobulin GImmunoglobulin MSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2COVID-19D614Gdisease severityELISAneutralizing antibodiespro-inflammatory cytokinesRBDSARS-CoV-2spikeWIV1-CoV

Identifiers

PMID33412089
PMCPMC7837114

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.