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Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model

Considering the urgent demand for faster methods to quantify neutralizing antibody titers in patients with coronavirus (CoV) disease 2019 (COVID-19), developing an analytical model or method to replace the conventional virus neutralization test (NT) is essential. Moreover, a “COVID-19 immunity passp...

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Autores principales: Liu, Kuan-Ting, Gong, Yu-Nong, Huang, Chung-Guei, Huang, Peng-Nien, Yu, Kar-Yee, Lee, Hou-Chen, Lee, Sun-Che, Chiang, Huan-Jung, Kung, Yu-An, Lin, Yueh-Te, Hsiao, Mei-Jen, Huang, Po-Wei, Huang, Sheng-Yu, Wu, Hsin-Tai, Wu, Chih-Ching, Kuo, Rei-Lin, Chen, Kuan-Fu, Hung, Chuan-Tien, Oguntuyo, Kasopefoluwa Y., Stevens, Christian S., Kowdle, Shreyas, Chiu, Hsin-Ping, Lee, Benhur, Chen, Guang-Wu, Shih, Shin-Ru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8809379/
https://www.ncbi.nlm.nih.gov/pubmed/35107336
http://dx.doi.org/10.1128/msphere.00883-21
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author Liu, Kuan-Ting
Gong, Yu-Nong
Huang, Chung-Guei
Huang, Peng-Nien
Yu, Kar-Yee
Lee, Hou-Chen
Lee, Sun-Che
Chiang, Huan-Jung
Kung, Yu-An
Lin, Yueh-Te
Hsiao, Mei-Jen
Huang, Po-Wei
Huang, Sheng-Yu
Wu, Hsin-Tai
Wu, Chih-Ching
Kuo, Rei-Lin
Chen, Kuan-Fu
Hung, Chuan-Tien
Oguntuyo, Kasopefoluwa Y.
Stevens, Christian S.
Kowdle, Shreyas
Chiu, Hsin-Ping
Lee, Benhur
Chen, Guang-Wu
Shih, Shin-Ru
author_facet Liu, Kuan-Ting
Gong, Yu-Nong
Huang, Chung-Guei
Huang, Peng-Nien
Yu, Kar-Yee
Lee, Hou-Chen
Lee, Sun-Che
Chiang, Huan-Jung
Kung, Yu-An
Lin, Yueh-Te
Hsiao, Mei-Jen
Huang, Po-Wei
Huang, Sheng-Yu
Wu, Hsin-Tai
Wu, Chih-Ching
Kuo, Rei-Lin
Chen, Kuan-Fu
Hung, Chuan-Tien
Oguntuyo, Kasopefoluwa Y.
Stevens, Christian S.
Kowdle, Shreyas
Chiu, Hsin-Ping
Lee, Benhur
Chen, Guang-Wu
Shih, Shin-Ru
author_sort Liu, Kuan-Ting
collection PubMed
description Considering the urgent demand for faster methods to quantify neutralizing antibody titers in patients with coronavirus (CoV) disease 2019 (COVID-19), developing an analytical model or method to replace the conventional virus neutralization test (NT) is essential. Moreover, a “COVID-19 immunity passport” is currently being proposed as a certification for people who travel internationally. Therefore, an enzyme-linked immunosorbent assay (ELISA) was designed to detect severe acute respiratory syndrome CoV 2 (SARS-CoV-2)-neutralizing antibodies in serum, which is based on the binding affinity of SARS-CoV-2 viral spike protein 1 (S1) and the viral spike protein receptor-binding domain (RBD) to antibodies. The RBD is considered the major binding region of neutralizing antibodies. Furthermore, S1 covers the RBD and several other regions, which are also important for neutralizing antibody binding. In this study, we assessed 144 clinical specimens, including those from patients with PCR-confirmed SARS-CoV-2 infections and healthy donors, using both the NT and ELISA. The ELISA results analyzed by spline regression and the two-variable generalized additive model precisely reflected the NT value, and the correlation between predicted and actual NT values was as high as 0.917. Therefore, our method serves as a surrogate to quantify neutralizing antibody titer. The analytic method and platform used in this study present a new perspective for serological testing of SARS-CoV-2 infection and have clinical potential to assess vaccine efficacy. IMPORTANCE Herein, we present a new approach for serological testing for SARS-CoV-2 antibodies using innovative laboratory methods that demonstrate a combination of biology and mathematics. The traditional virus neutralization test is the gold standard method; however, it is time-consuming and poses a risk to medical personnel. Thus, there is a demand for methods that rapidly quantify neutralizing antibody titers in patients with COVID-19 or examine vaccine efficacy at a biosafety level 2 containment facility. Therefore, we used a two-variable generalized additive model to analyze the results of the enzyme-linked immunosorbent assay and found the method to serve as a surrogate to quantify neutralizing antibody titers. This methodology has potential for clinical use in assessing vaccine efficacy.
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spelling pubmed-88093792022-02-09 Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model Liu, Kuan-Ting Gong, Yu-Nong Huang, Chung-Guei Huang, Peng-Nien Yu, Kar-Yee Lee, Hou-Chen Lee, Sun-Che Chiang, Huan-Jung Kung, Yu-An Lin, Yueh-Te Hsiao, Mei-Jen Huang, Po-Wei Huang, Sheng-Yu Wu, Hsin-Tai Wu, Chih-Ching Kuo, Rei-Lin Chen, Kuan-Fu Hung, Chuan-Tien Oguntuyo, Kasopefoluwa Y. Stevens, Christian S. Kowdle, Shreyas Chiu, Hsin-Ping Lee, Benhur Chen, Guang-Wu Shih, Shin-Ru mSphere Research Article Considering the urgent demand for faster methods to quantify neutralizing antibody titers in patients with coronavirus (CoV) disease 2019 (COVID-19), developing an analytical model or method to replace the conventional virus neutralization test (NT) is essential. Moreover, a “COVID-19 immunity passport” is currently being proposed as a certification for people who travel internationally. Therefore, an enzyme-linked immunosorbent assay (ELISA) was designed to detect severe acute respiratory syndrome CoV 2 (SARS-CoV-2)-neutralizing antibodies in serum, which is based on the binding affinity of SARS-CoV-2 viral spike protein 1 (S1) and the viral spike protein receptor-binding domain (RBD) to antibodies. The RBD is considered the major binding region of neutralizing antibodies. Furthermore, S1 covers the RBD and several other regions, which are also important for neutralizing antibody binding. In this study, we assessed 144 clinical specimens, including those from patients with PCR-confirmed SARS-CoV-2 infections and healthy donors, using both the NT and ELISA. The ELISA results analyzed by spline regression and the two-variable generalized additive model precisely reflected the NT value, and the correlation between predicted and actual NT values was as high as 0.917. Therefore, our method serves as a surrogate to quantify neutralizing antibody titer. The analytic method and platform used in this study present a new perspective for serological testing of SARS-CoV-2 infection and have clinical potential to assess vaccine efficacy. IMPORTANCE Herein, we present a new approach for serological testing for SARS-CoV-2 antibodies using innovative laboratory methods that demonstrate a combination of biology and mathematics. The traditional virus neutralization test is the gold standard method; however, it is time-consuming and poses a risk to medical personnel. Thus, there is a demand for methods that rapidly quantify neutralizing antibody titers in patients with COVID-19 or examine vaccine efficacy at a biosafety level 2 containment facility. Therefore, we used a two-variable generalized additive model to analyze the results of the enzyme-linked immunosorbent assay and found the method to serve as a surrogate to quantify neutralizing antibody titers. This methodology has potential for clinical use in assessing vaccine efficacy. American Society for Microbiology 2022-02-02 /pmc/articles/PMC8809379/ /pubmed/35107336 http://dx.doi.org/10.1128/msphere.00883-21 Text en Copyright © 2022 Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Liu, Kuan-Ting
Gong, Yu-Nong
Huang, Chung-Guei
Huang, Peng-Nien
Yu, Kar-Yee
Lee, Hou-Chen
Lee, Sun-Che
Chiang, Huan-Jung
Kung, Yu-An
Lin, Yueh-Te
Hsiao, Mei-Jen
Huang, Po-Wei
Huang, Sheng-Yu
Wu, Hsin-Tai
Wu, Chih-Ching
Kuo, Rei-Lin
Chen, Kuan-Fu
Hung, Chuan-Tien
Oguntuyo, Kasopefoluwa Y.
Stevens, Christian S.
Kowdle, Shreyas
Chiu, Hsin-Ping
Lee, Benhur
Chen, Guang-Wu
Shih, Shin-Ru
Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model
title Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model
title_full Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model
title_fullStr Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model
title_full_unstemmed Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model
title_short Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model
title_sort quantifying neutralizing antibodies in patients with covid-19 by a two-variable generalized additive model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8809379/
https://www.ncbi.nlm.nih.gov/pubmed/35107336
http://dx.doi.org/10.1128/msphere.00883-21
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