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  3. Do quantitative levels of antispike-IgG antibodies aid in predicting protection from SARS-CoV-2 infection? Results from a longitudinal study in a police cohort.

Do quantitative levels of antispike-IgG antibodies aid in predicting protection from SARS-CoV-2 infection? Results from a longitudinal study in a police cohort.

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DOI
10.48350/184289
Publisher DOI
10.1002/jmv.28904
PubMed ID
37386901
Abstract
In a COVID-19 sero-surveillance cohort study with predominantly healthy and vaccinated individuals, the objectives were (i) to investigate longitudinally the factors associated with the quantitative dynamics of antispike (anti-S1) IgG antibody levels, (ii) to evaluate whether the levels were associated with protection from SARS-CoV-2 infection, and (iii) to assess whether the association was different in the pre-Omicron compared with the Omicron period. The QuantiVac Euroimmun ELISA test was used to quantify anti-S1 IgG levels. The entire study period (16 months), the 11-month pre-Omicron period and the cross-sectional analysis before the Omicron surge included 3219, 2310, and 895 reactive serum samples from 949, 919, and 895 individuals, respectively. Mixed-effect linear, mixed-effect time-to-event, and logistic regression models were used to achieve the objectives. Age and time since infection or vaccination were the only factors associated with a decline of anti-S1 IgG levels. Higher antibody levels were significantly associated with protection from SARS-CoV-2 infection (0.89, 95% confidence interval [CI] 0.82-0.97), and the association was higher during the time period when Omicron was predominantly circulating compared with the ones when Alpha and Delta variants were predominant (adjusted hazard ratio for interaction 0.66, 95% CI 0.53-0.84). In a prediction model, it was estimated that >8000 BAU/mL anti-S1 IgG was required to reduce the risk of infection with Omicron variants by approximately 20%-30% for 90 days. Though, such high levels were only found in 1.9% of the samples before the Omicron surge, and they were not durable for 3 months. Anti-S1 IgG antibody levels are statistically associated with protection from SARS-CoV-2 infection. However, the prediction impact of the antibody level findings on infection protection is limited.
Date Issued
2023-07
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services
500 Science > 570 Life sciences; biology
Subjects
COVID-19 SARS-CoV-2 antispike-IgG quantitaive antispike-IgG serology
Language(s)
en
Author(s)
Sendi, Parham  orcid-logo
Institut für Infektionskrankheiten (IFIK) - Streptococcal Biology  
Institut für Infektionskrankheiten (IFIK)  
Widmer, Nadja
Branca, Mattia  
Clinical Trials Unit Bern (CTU) - Statistics & Methodology (Bütikofer)  
Thierstein, Marc
Büchi, Annina Elisabeth  orcid-logo
Universitätsklinik für Pneumologie und Allergologie  
Güntensperger, Dominik Bruno  
Clinical Trials Unit Bern (CTU) - Data Management  
Blum, Manuel  orcid-logo
Allgemeine Innere Medizin  
Berner Institut für Hausarztmedizin (BIHAM)  
Universitätsklinik für Allgemeine Innere Medizin  
Baldan, Rossella  
Institut für Infektionskrankheiten (IFIK) - Forschung  
Tinguely, Caroline
Heg, Dierik Hans  orcid-logo
Clinical Trials Unit Bern (CTU) - Statistics & Methodology (Heg)  
Theel, Elitza S
Berbari, Elie
Tande, Aaron J
Endimiani, Andrea  orcid-logo
Institut für Infektionskrankheiten (IFIK)  
Gowland, Peter
Niederhauser-Lüthi, Christoph Peter  
Institut für Infektionskrankheiten (IFIK) - Forschung  
Additional Credits
Universitätsklinik für Pneumologie und Allergologie  
Berner Institut für Hausarztmedizin (BIHAM)  
Institut für Infektionskrankheiten (IFIK) - Forschung  
Allgemeine Innere Medizin  
Clinical Trials Unit Bern (CTU) - Data Management  
Universitätsklinik für Allgemeine Innere Medizin  
Institut für Infektionskrankheiten (IFIK) - Streptococcal Biology  
Clinical Trials Unit Bern (CTU) - Statistics & Methodology (Bütikofer)  
Institut für Infektionskrankheiten (IFIK)  
Clinical Trials Unit Bern (CTU) - Statistics & Methodology (Heg)  
Journal
Journal of medical virology
Publisher
Wiley
ISSN
0146-6615
Access(Rights)
open.access
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