Evidence map›Paper›PMID 39990561›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Variant-specific antibody correlates of protection against SARS-CoV-2 Omicron symptomatic overall infections.

Jose Victor Zambrana, Ian A Mellis, Abigail Shotwell, Hannah E Maier, Yara Saborio, Carlos Barillas, Roger Lopez, Gerald Vasquez, Miguel Plazaola, Nery Sanchez and 8 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Jose Victor ZambranaDepartment of Epidemiology, University of Michigan, Ann Arbor, MI.
Ian A MellisAaron Diamond AIDS Research Center, Vagelos College of Physicians Surgeons, Columbia University Irving Medical Center, New York, NY.ORCID 0000-0002-6239-4821
Abigail ShotwellDepartment of Epidemiology, University of Michigan, Ann Arbor, MI.
Hannah E MaierDepartment of Epidemiology, University of Michigan, Ann Arbor, MI.
Yara SaborioSustainable Sciences Institute, Managua, Nicaragua.
Carlos BarillasSustainable Sciences Institute, Managua, Nicaragua.
Roger LopezSustainable Sciences Institute, Managua, Nicaragua.
Gerald VasquezSustainable Sciences Institute, Managua, Nicaragua.
Miguel PlazaolaSustainable Sciences Institute, Managua, Nicaragua.
Nery SanchezSustainable Sciences Institute, Managua, Nicaragua.
Sergio OjedaSustainable Sciences Institute, Managua, Nicaragua.
Isabel GilbertsonDepartment of Epidemiology, University of Michigan, Ann Arbor, MI.
Guillermina KuanSustainable Sciences Institute, Managua, Nicaragua.
Qian WangAaron Diamond AIDS Research Center, Vagelos College of Physicians Surgeons, Columbia University Irving Medical Center, New York, NY.
Lihong LiuAaron Diamond AIDS Research Center, Vagelos College of Physicians Surgeons, Columbia University Irving Medical Center, New York, NY.
Angel BalmasedaSustainable Sciences Institute, Managua, Nicaragua.
David D HoAaron Diamond AIDS Research Center, Vagelos College of Physicians Surgeons, Columbia University Irving Medical Center, New York, NY.
Aubree GordonDepartment of Epidemiology, University of Michigan, Ann Arbor, MI.

Funding

NIAID Centers of Excellence for Influenza Research and Response: Universal Influenza Vaccine Research Activities75N93021C00016 · NIAID · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI WEBBY, RICHARD · 2021 to 2025
$91.4M
NIAID Centers of Excellence for Influenza Research and Response: Universal Influenza Vaccine Research Activities75N93021C00014 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GARCIA-SASTRE, ADOLFO · 2021 to 2025
$62.6M
Flu Dynamics COVID-19 SupplementR01AI120997 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GORDON, AUBREE L · 2017 to 2021
$4.1M
Gates Foundation INV-019355NIAID NIH HHS 75N93021C00014NIAID NIH HHS 75N93021C00016NIAID NIH HHS HHSN272201400006CNIAID NIH HHS R01 AI120997
6 · The paper itself

Abstract

Background: Vaccination prior infection elicit neutralizing antibodies targeting SARS-CoV-2, yet the quantitative relationship between serum antibodies infection risk against viral variants remains uncertain, particularly in underrepresented regions. Methods: We investigated the protective correlation of pre-exposure serum neutralizing antibody levels, employing a panel of SARS-CoV-2 pseudoviruses (Omicron BA.1, Omicron BA.2, ancestral D614G), Spike-binding antibody levels, with symptomatic BA.1 or BA.2 SARS-CoV-2 infections overall infection, in 345 household contacts from a SARS-CoV-2 household cohort study. Results: A four-fold increase in homotypic-neutralizing (e.g., BA.1-neutralizing vs. BA.1 exposure) titers was correlated with protection from symptomatic infections (BA.1 protection: 28% [95%CI 12-42%]; BA.2 protection: 43% [20-62%]), ancestral-neutralizing titers were also correlated with protection from either variant, but only at higher average levels than homotypic. Mediation analyses revealed that homotypic D614G-neutralizing antibodies mediated protection from infection symptomatic infection both from prior infection vaccination. Conclusions: These findings underscore the importance of monitoring variant-specific antibody responses highlight that antibodies targeting circulating strains may be more predictive of protection from infection. Nevertheless, ancestral-strain-neutralizing antibodies remain relevant as a correlate of protection. Our study emphasizes the need for continued efforts to assess antibody correlates of protection. Funding: We acknowledge funding from the U.S. N.I.H., the Open Philanthropy Project, the Bill Melinda Gates Foundation.

Identifiers

PMID39990561
PMCPMC11844606

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.