Are anti-SARS-CoV-2 S/N IgG/IgM antibodies always predictive of previous SARS-CoV-2 infection?
© 2023 the author(s), published by De Gruyter, Berlin/Boston..
Objectives: We planned this study to verify whether immunoassays for quantifying anti-SARS-CoV-2 IgG/IgM antibodies against both spike (S) and nucleocapsid (N) proteins may be used for identifying previous SARS-CoV-2 infections.
Methods: The study population consisted of a cohort of fully vaccinated healthcare workers. All study subjects underwent regular medical visits and molecular testing for diagnosing SARS-CoV-2 infections every 2-4 weeks between 2020-2022. Venous blood was drawn for measuring anti-SARS-CoV-2 antibodies with MAGLUMI 2019-nCoV lgG/IgM CLIA Assays directed against both SARS-CoV-2 S and N proteins.
Results: Overall, 31/53 (58.5%) subjects had tested positive for SARS-CoV-2 by RT-PCR throughout the study (24 once, 7 twice). No positive correlation was found between anti-SARS-CoV-2 S/N IgM antibodies and molecular test positivity. In univariate regression analysis, both a molecular test positivity (r=0.33; p=0.015) and the number of positive molecular tests (r=0.43; p=0.001), but not vaccine doses (r=-0.12; p=0.392), were significantly correlated with anti-SARS-CoV-2 S/N IgG antibodies. These two associations remained significant in multiple linear regression analysis (p=0.029 and p<0.001, respectively) after adjusting for sex, age, body mass index, and vaccine doses. In ROC curve analysis, anti-SARS-CoV-2 S/N IgG antibodies significantly predicted molecular test positivity (AUC, 0.69; 95% CI; 0.55-0.84), with the best cutoff of 0.05 AU/mL displaying 67.9% accuracy, 0.97 sensitivity, and 0.27 specificity.
Conclusions: Although anti-SARS-CoV-2 S/N IgG antibodies provide helpful information for identifying previous SARS-CoV-2 infections, a lower cutoff than that of sample reactivity should be used. Anti-SARS-CoV-2 S/N IgM antibodies using conventional cutoffs seem useless for this purpose.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2023 |
---|---|
Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:4 |
---|---|
Enthalten in: |
Advances in laboratory medicine - 4(2023), 2 vom: 01. Juni, Seite 175-184 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Lippi, Giuseppe [VerfasserIn] |
---|
Links: |
---|
Themen: |
Antibodies |
---|
Anmerkungen: |
Date Revised 05.04.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
---|
doi: |
10.1515/almed-2023-0008 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM365667498 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | NLM365667498 | ||
003 | DE-627 | ||
005 | 20240405233259.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231226s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1515/almed-2023-0008 |2 doi | |
028 | 5 | 2 | |a pubmed24n1366.xml |
035 | |a (DE-627)NLM365667498 | ||
035 | |a (NLM)38075941 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Lippi, Giuseppe |e verfasserin |4 aut | |
245 | 1 | 0 | |a Are anti-SARS-CoV-2 S/N IgG/IgM antibodies always predictive of previous SARS-CoV-2 infection? |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Revised 05.04.2024 | ||
500 | |a published: Electronic-eCollection | ||
500 | |a Citation Status PubMed-not-MEDLINE | ||
520 | |a © 2023 the author(s), published by De Gruyter, Berlin/Boston. | ||
520 | |a Objectives: We planned this study to verify whether immunoassays for quantifying anti-SARS-CoV-2 IgG/IgM antibodies against both spike (S) and nucleocapsid (N) proteins may be used for identifying previous SARS-CoV-2 infections | ||
520 | |a Methods: The study population consisted of a cohort of fully vaccinated healthcare workers. All study subjects underwent regular medical visits and molecular testing for diagnosing SARS-CoV-2 infections every 2-4 weeks between 2020-2022. Venous blood was drawn for measuring anti-SARS-CoV-2 antibodies with MAGLUMI 2019-nCoV lgG/IgM CLIA Assays directed against both SARS-CoV-2 S and N proteins | ||
520 | |a Results: Overall, 31/53 (58.5%) subjects had tested positive for SARS-CoV-2 by RT-PCR throughout the study (24 once, 7 twice). No positive correlation was found between anti-SARS-CoV-2 S/N IgM antibodies and molecular test positivity. In univariate regression analysis, both a molecular test positivity (r=0.33; p=0.015) and the number of positive molecular tests (r=0.43; p=0.001), but not vaccine doses (r=-0.12; p=0.392), were significantly correlated with anti-SARS-CoV-2 S/N IgG antibodies. These two associations remained significant in multiple linear regression analysis (p=0.029 and p<0.001, respectively) after adjusting for sex, age, body mass index, and vaccine doses. In ROC curve analysis, anti-SARS-CoV-2 S/N IgG antibodies significantly predicted molecular test positivity (AUC, 0.69; 95% CI; 0.55-0.84), with the best cutoff of 0.05 AU/mL displaying 67.9% accuracy, 0.97 sensitivity, and 0.27 specificity | ||
520 | |a Conclusions: Although anti-SARS-CoV-2 S/N IgG antibodies provide helpful information for identifying previous SARS-CoV-2 infections, a lower cutoff than that of sample reactivity should be used. Anti-SARS-CoV-2 S/N IgM antibodies using conventional cutoffs seem useless for this purpose | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a COVID-19 | |
650 | 4 | |a SARS-CoV-2 | |
650 | 4 | |a antibodies | |
650 | 4 | |a infection | |
650 | 4 | |a serology | |
700 | 1 | |a Henry, Brandon M |e verfasserin |4 aut | |
700 | 1 | |a Pighi, Laura |e verfasserin |4 aut | |
700 | 1 | |a De Nitto, Simone |e verfasserin |4 aut | |
700 | 1 | |a Salvagno, Gian Luca |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Advances in laboratory medicine |d 2020 |g 4(2023), 2 vom: 01. Juni, Seite 175-184 |w (DE-627)NLM358605490 |x 2628-491X |7 nnns |
773 | 1 | 8 | |g volume:4 |g year:2023 |g number:2 |g day:01 |g month:06 |g pages:175-184 |
856 | 4 | 0 | |u http://dx.doi.org/10.1515/almed-2023-0008 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 4 |j 2023 |e 2 |b 01 |c 06 |h 175-184 |