A novel highly quantitative and reproducible assay for the detection of anti-SARS-CoV-2 IgG and IgM antibodies Article Swipe
Kenta Noda
,
Kouki Matsuda
,
Shigehiro Yagishita
,
Kenji Maeda
,
Yutaro Akiyama
,
Junko Terada-Hirashima
,
Hiromichi Matsushita
,
Satoshi Iwata
,
Kazuto Yamashita
,
Yusuke Atarashi
,
Shunsuke Watanabe
,
Nobuyuki Ide
,
Tomokazu Yoshida
,
Norio Ohmagari
,
Hiroaki Mitsuya
,
Akinobu Hamada
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-021-84387-3
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-021-84387-3
The quantitative range and reproducibility of current serological tests for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are not optimized. Herein, we developed a diagnostic test that detects SARS-CoV-2 IgG and IgM with high quantitativeness and reproducibility and low interference. The system was based on the high-sensitivity chemiluminescence enzyme immunoassay (HISCL) platform and detects IgG and IgM specific to SARS-CoV-2 spike and nucleocapsid proteins. Quantification accuracy and reproducibility were evaluated using serially diluted samples from 60 SARS-CoV-2-infected patients. Assay performance was evaluated using serum samples from the SARS-CoV-2-infected patients and 500 SARS-CoV-2-negative serum samples collected before the emergence of SARS-CoV-2. The system showed high quantification accuracy (range, 10 2 ), high reproducibility (within 5%), and no cross-reaction between SARS1- and MERS-S proteins. Detection accuracy was 98.3% and 93.3% for IgG and IgM against spike proteins and 100% and 71.7% for IgG and IgM against nucleocapsid proteins, respectively. Mean antibody levels were > 10 times that in negative samples upon admission and > 100 times that at convalescent periods. Clinical severity upon admission was not correlated with IgG or IgM levels. This highly quantitative, reproducible assay system with high clinical performance may help analyze temporal serological/immunological profiles of SARS-CoV-2 infection and SARS-CoV-2 vaccine effectiveness.
Related Topics
Concepts
Antibody
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Coronavirus disease 2019 (COVID-19)
Virology
Immunoglobulin M
2019-20 coronavirus outbreak
Immunoglobulin G
Sars virus
Immunology
Medicine
Outbreak
Infectious disease (medical specialty)
Pathology
Disease
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41598-021-84387-3
- OA Status
- gold
- Cited By
- 68
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3135203780
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3135203780Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41598-021-84387-3Digital Object Identifier
- Title
-
A novel highly quantitative and reproducible assay for the detection of anti-SARS-CoV-2 IgG and IgM antibodiesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-03-04Full publication date if available
- Authors
-
Kenta Noda, Kouki Matsuda, Shigehiro Yagishita, Kenji Maeda, Yutaro Akiyama, Junko Terada-Hirashima, Hiromichi Matsushita, Satoshi Iwata, Kazuto Yamashita, Yusuke Atarashi, Shunsuke Watanabe, Nobuyuki Ide, Tomokazu Yoshida, Norio Ohmagari, Hiroaki Mitsuya, Akinobu HamadaList of authors in order
- Landing page
-
https://doi.org/10.1038/s41598-021-84387-3Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1038/s41598-021-84387-3Direct OA link when available
- Concepts
-
Antibody, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Coronavirus disease 2019 (COVID-19), Virology, Immunoglobulin M, 2019-20 coronavirus outbreak, Immunoglobulin G, Sars virus, Immunology, Medicine, Outbreak, Infectious disease (medical specialty), Pathology, DiseaseTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
68Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 11, 2023: 19, 2022: 24, 2021: 13Per-year citation counts (last 5 years)
- References (count)
-
41Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_year | 2021 |
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