ArticleMicroorganisms2023
A Severe Acute Respiratory Syndrome Coronavirus 2 Anti-Spike Immunoglobulin G Assay: A Robust Method for Evaluation of Vaccine Immunogenicity Using an Established Correlate of Protection.
Article in Microorganisms, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 21 citations in OpenAlex.
- Safety and immunogenicity of a COVID-19-Influenza Combination nanoparticle vaccine (CIC) containing SARS-CoV-2 recombinant spike and quadrivalent influenza hemagglutinin with Matrix-M® adjuvant: A phase 1/2 clinical trial.Human vaccines & immunotherapeutics · 2026Trial
- Trial
- Immunogenicity and Safety of Heterologous Omicron BA.1 and Bivalent SARS-CoV-2 Recombinant Spike Protein Booster Vaccines: A Phase 3 Randomized Clinical Trial.The Journal of infectious diseases · 2024Trial
- Corrected and republished from: "Clinical validation of an RSV neutralization assay and analysis of cross-sectional sera associated with 2021-2023 RSV outbreaks to investigate the immunity debt hypothesis".Microbiology spectrum · 2026Article
- Article
- A Pseudovirus-Based Neutralization Assay for SARS-CoV-2 Variants: A Rapid, Cost-Effective, BSL-2-Based High-Throughput Assay Useful for Vaccine Immunogenicity Evaluation.Microorganisms · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 1 institution in 1 country.
Funding
Abstract
As the COVID-19 pandemic continues, variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge. Immunogenicity evaluation of vaccines and identification of correlates of protection for vaccine effectiveness is critical to aid the development of vaccines against emerging variants. Anti-recombinant spike (rS) protein immunoglobulin G (IgG) quantitation in the systemic circulation (serum/plasma) is shown to correlate with vaccine efficacy. Thus, an enzyme-linked immunosorbent assay (ELISA)-based binding assay to detect SARS-CoV-2 (ancestral and variant strains) anti-rS IgG in human serum samples was developed and validated. This assay successfully met acceptance criteria for inter/intra-assay precision, specificity, selectivity, linearity, lower/upper limits of quantitation, matrix effects, and assay robustness. The analyte in serum was stable for up to 8 freeze/thaw cycles and 2 years in -80 °C storage. Similar results were observed for the Beta, Delta, and Omicron BA.1/BA.5/XBB.1.5 variant-adapted assays. Anti-rS IgG assay results correlated significantly with neutralization and receptor binding inhibition assays. In addition, usage of international reference standards allows data extrapolation to WHO international units (BAU/mL), facilitating comparison of results with other IgG assays. This anti-rS IgG assay is a robust, high-throughput method to evaluate binding IgG responses to S protein in serum, enabling rapid development of effective vaccines against emerging COVID-19 variants.
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Registered trials
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.