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Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study
OBJECTIVE: Despite extensive vaccination campaigns to combat the coronavirus disease (COVID-19) pandemic, variants of concern, particularly the Omicron variant (B.1.1.529 or BA.1), may escape the antibodies elicited by vaccination against SARS-CoV-2. Therefore, this study aimed to evaluate 50% neutr...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10126441/ https://www.ncbi.nlm.nih.gov/pubmed/37113226 http://dx.doi.org/10.3389/fmicb.2023.1126527 |
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author | Goto, Atsushi Miyakawa, Kei Nakayama, Izumi Yagome, Susumu Xu, Juan Kaneko, Makoto Ohtake, Norihisa Kato, Hideaki Ryo, Akihide |
author_facet | Goto, Atsushi Miyakawa, Kei Nakayama, Izumi Yagome, Susumu Xu, Juan Kaneko, Makoto Ohtake, Norihisa Kato, Hideaki Ryo, Akihide |
author_sort | Goto, Atsushi |
collection | PubMed |
description | OBJECTIVE: Despite extensive vaccination campaigns to combat the coronavirus disease (COVID-19) pandemic, variants of concern, particularly the Omicron variant (B.1.1.529 or BA.1), may escape the antibodies elicited by vaccination against SARS-CoV-2. Therefore, this study aimed to evaluate 50% neutralizing activity (NT(50)) against SARS-CoV-2 D614G, Delta, Omicron BA.1, and Omicron BA.2 and to develop prediction models to predict the risk of infection in a general population in Japan. METHODS: We used a random 10% of samples from 1,277 participants in a population-based cross-sectional survey conducted in January and February 2022 in Yokohama City, the most populous municipality in Japan. We measured NT(50) against D614G as a reference and three variants (Delta, Omicron BA.1, and BA.2) and immunoglobulin G against SARS-CoV-2 spike protein (SP-IgG). RESULTS: Among 123 participants aged 20–74, 93% had received two doses of SARS-CoV-2 vaccine. The geometric means (95% confidence intervals) of NT(50) were 65.5 (51.8–82.8) for D614G, 34.3 (27.1–43.4) for Delta, 14.9 (12.2–18.0) for Omicron BA.1, and 12.9 (11.3–14.7) for Omicron BA.2. The prediction model with SP-IgG titers for Omicron BA.1 performed better than the model for Omicron BA.2 (bias-corrected R(2) with bootstrapping: 0.721 vs. 0.588). The models also performed better for BA.1 than for BA.2 (R(2) = 0.850 vs. 0.150) in a validation study with 20 independent samples. CONCLUSION: In a general Japanese population with 93% of the population vaccinated with two doses of SARS-CoV-2 vaccine, neutralizing activity against Omicron BA.1 and BA.2 were substantially lower than those against D614G or the Delta variant. The prediction models for Omicron BA.1 and BA.2 showed moderate predictive ability and the model for BA.1 performed well in validation data. |
format | Online Article Text |
id | pubmed-10126441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101264412023-04-26 Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study Goto, Atsushi Miyakawa, Kei Nakayama, Izumi Yagome, Susumu Xu, Juan Kaneko, Makoto Ohtake, Norihisa Kato, Hideaki Ryo, Akihide Front Microbiol Microbiology OBJECTIVE: Despite extensive vaccination campaigns to combat the coronavirus disease (COVID-19) pandemic, variants of concern, particularly the Omicron variant (B.1.1.529 or BA.1), may escape the antibodies elicited by vaccination against SARS-CoV-2. Therefore, this study aimed to evaluate 50% neutralizing activity (NT(50)) against SARS-CoV-2 D614G, Delta, Omicron BA.1, and Omicron BA.2 and to develop prediction models to predict the risk of infection in a general population in Japan. METHODS: We used a random 10% of samples from 1,277 participants in a population-based cross-sectional survey conducted in January and February 2022 in Yokohama City, the most populous municipality in Japan. We measured NT(50) against D614G as a reference and three variants (Delta, Omicron BA.1, and BA.2) and immunoglobulin G against SARS-CoV-2 spike protein (SP-IgG). RESULTS: Among 123 participants aged 20–74, 93% had received two doses of SARS-CoV-2 vaccine. The geometric means (95% confidence intervals) of NT(50) were 65.5 (51.8–82.8) for D614G, 34.3 (27.1–43.4) for Delta, 14.9 (12.2–18.0) for Omicron BA.1, and 12.9 (11.3–14.7) for Omicron BA.2. The prediction model with SP-IgG titers for Omicron BA.1 performed better than the model for Omicron BA.2 (bias-corrected R(2) with bootstrapping: 0.721 vs. 0.588). The models also performed better for BA.1 than for BA.2 (R(2) = 0.850 vs. 0.150) in a validation study with 20 independent samples. CONCLUSION: In a general Japanese population with 93% of the population vaccinated with two doses of SARS-CoV-2 vaccine, neutralizing activity against Omicron BA.1 and BA.2 were substantially lower than those against D614G or the Delta variant. The prediction models for Omicron BA.1 and BA.2 showed moderate predictive ability and the model for BA.1 performed well in validation data. Frontiers Media S.A. 2023-04-11 /pmc/articles/PMC10126441/ /pubmed/37113226 http://dx.doi.org/10.3389/fmicb.2023.1126527 Text en Copyright © 2023 Goto, Miyakawa, Nakayama, Yagome, Xu, Kaneko, Ohtake, Kato and Ryo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Goto, Atsushi Miyakawa, Kei Nakayama, Izumi Yagome, Susumu Xu, Juan Kaneko, Makoto Ohtake, Norihisa Kato, Hideaki Ryo, Akihide Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study |
title | Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study |
title_full | Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study |
title_fullStr | Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study |
title_full_unstemmed | Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study |
title_short | Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study |
title_sort | prediction models for neutralization activity against emerging sars-cov-2 variants: a cross-sectional study |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10126441/ https://www.ncbi.nlm.nih.gov/pubmed/37113226 http://dx.doi.org/10.3389/fmicb.2023.1126527 |
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