Kinetics of humoral immune response over 17 months of COVID-19 pandemic in a large cohort of healthcare workers in Spain : the ProHEpiC-19 study
© 2022. The Author(s)..
BACKGROUND: Understanding the immune response to the SARS-CoV-2 virus is critical for efficient monitoring and control strategies. The ProHEpic-19 cohort provides a fine-grained description of the kinetics of antibodies after SARS-CoV-2 infection with an exceptional resolution over 17 months.
METHODS: We established a cohort of 769 healthcare workers including healthy and infected with SARS-CoV-2 in northern Barcelona to determine the kinetics of the IgM against the nucleocapsid (N) and the IgG against the N and spike (S) of SARS-CoV-2 in infected healthcare workers. The study period was from 5 May 2020 to 11 November 2021.We used non-linear mixed models to investigate the kinetics of IgG and IgM measured at nine time points over 17 months from the date of diagnosis. The model included factors of time, gender, and disease severity (asymptomatic, mild-moderate, severe-critical) to assess their effects and their interactions.
FINDINGS: 474 of the 769 participants (61.6%) became infected with SARS-CoV-2. Significant effects of gender and disease severity were found for the levels of all three antibodies. Median IgM(N) levels were already below the positivity threshold in patients with asymptomatic and mild-moderate disease at day 270 after the diagnosis, while IgG(N and S) levels remained positive at least until days 450 and 270, respectively. Kinetic modelling showed a general rise in both IgM(N) and IgG(N) levels up to day 30, followed by a decay with a rate depending on disease severity. IgG(S) levels remained relatively constant from day 15 over time.
INTERPRETATION: IgM(N) and IgG(N, S) SARS-CoV-2 antibodies showed a heterogeneous kinetics over the 17 months. Only the IgG(S) showed a stable increase, and the levels and the kinetics of antibodies varied according to disease severity. The kinetics of IgM and IgG observed over a year also varied by clinical spectrum can be very useful for public health policies around vaccination criteria in adult population.
FUNDING: Regional Ministry of Health of the Generalitat de Catalunya (Call COVID19-PoC SLT16_04; NCT04885478).
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
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| Enthalten in: |
BMC infectious diseases - 22(2022), 1 vom: 03. Sept., Seite 721 |
| Sprache: |
Englisch |
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| Links: |
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| Anmerkungen: |
Date Completed 07.09.2022 Date Revised 10.09.2022 published: Electronic ClinicalTrials.gov: NCT04885478 Citation Status MEDLINE |
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| doi: |
10.1186/s12879-022-07696-6 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM345747712 |
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| 245 | 1 | 0 | |a Kinetics of humoral immune response over 17 months of COVID-19 pandemic in a large cohort of healthcare workers in Spain |b the ProHEpiC-19 study |
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| 500 | |a Date Completed 07.09.2022 | ||
| 500 | |a Date Revised 10.09.2022 | ||
| 500 | |a published: Electronic | ||
| 500 | |a ClinicalTrials.gov: NCT04885478 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2022. The Author(s). | ||
| 520 | |a BACKGROUND: Understanding the immune response to the SARS-CoV-2 virus is critical for efficient monitoring and control strategies. The ProHEpic-19 cohort provides a fine-grained description of the kinetics of antibodies after SARS-CoV-2 infection with an exceptional resolution over 17 months | ||
| 520 | |a METHODS: We established a cohort of 769 healthcare workers including healthy and infected with SARS-CoV-2 in northern Barcelona to determine the kinetics of the IgM against the nucleocapsid (N) and the IgG against the N and spike (S) of SARS-CoV-2 in infected healthcare workers. The study period was from 5 May 2020 to 11 November 2021.We used non-linear mixed models to investigate the kinetics of IgG and IgM measured at nine time points over 17 months from the date of diagnosis. The model included factors of time, gender, and disease severity (asymptomatic, mild-moderate, severe-critical) to assess their effects and their interactions | ||
| 520 | |a FINDINGS: 474 of the 769 participants (61.6%) became infected with SARS-CoV-2. Significant effects of gender and disease severity were found for the levels of all three antibodies. Median IgM(N) levels were already below the positivity threshold in patients with asymptomatic and mild-moderate disease at day 270 after the diagnosis, while IgG(N and S) levels remained positive at least until days 450 and 270, respectively. Kinetic modelling showed a general rise in both IgM(N) and IgG(N) levels up to day 30, followed by a decay with a rate depending on disease severity. IgG(S) levels remained relatively constant from day 15 over time | ||
| 520 | |a INTERPRETATION: IgM(N) and IgG(N, S) SARS-CoV-2 antibodies showed a heterogeneous kinetics over the 17 months. Only the IgG(S) showed a stable increase, and the levels and the kinetics of antibodies varied according to disease severity. The kinetics of IgM and IgG observed over a year also varied by clinical spectrum can be very useful for public health policies around vaccination criteria in adult population | ||
| 520 | |a FUNDING: Regional Ministry of Health of the Generalitat de Catalunya (Call COVID19-PoC SLT16_04; NCT04885478) | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Antibodies | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a Clinical spectrum | |
| 650 | 4 | |a Cohort | |
| 650 | 4 | |a Health care workers | |
| 650 | 4 | |a Humoral immunity | |
| 650 | 4 | |a IgG | |
| 650 | 4 | |a IgM | |
| 650 | 4 | |a Kinetics | |
| 650 | 4 | |a Non-linear mixed models | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 4 | |a Seroprevalence | |
| 650 | 7 | |a Antibodies, Viral |2 NLM | |
| 650 | 7 | |a Immunoglobulin G |2 NLM | |
| 650 | 7 | |a Immunoglobulin M |2 NLM | |
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| 700 | 1 | |a Costa, Magda Alemany |e investigator |4 oth | |
| 700 | 1 | |a Ortega, Eva Olivares |e investigator |4 oth | |
| 700 | 1 | |a Camacho, Alba Pachón |e investigator |4 oth | |
| 700 | 1 | |a Devesa, Marta Bujalance |e investigator |4 oth | |
| 700 | 1 | |a Espinoza, Mariella Soto |e investigator |4 oth | |
| 700 | 1 | |a Palma, Antonio Negrete |e investigator |4 oth | |
| 700 | 1 | |a de San José, Mariana Martinez |e investigator |4 oth | |
| 700 | 1 | |a Varas, Ester Lucas |e investigator |4 oth | |
| 700 | 1 | |a Perich, Ester Badia |e investigator |4 oth | |
| 700 | 1 | |a Rodriguez, Mónica Piña |e investigator |4 oth | |
| 700 | 1 | |a Graells, Elena Domenech |e investigator |4 oth | |
| 700 | 1 | |a Gabriel, Eduard Moreno |e investigator |4 oth | |
| 700 | 1 | |a Cintas, Victòria Sabaté |e investigator |4 oth | |
| 700 | 1 | |a González, Mª Jose Argerich |e investigator |4 oth | |
| 700 | 1 | |a Duran, Asumció Vazquez |e investigator |4 oth | |
| 700 | 1 | |a Roca, Alex Ortega |e investigator |4 oth | |
| 700 | 1 | |a Pradells, Anna Devesa |e investigator |4 oth | |
| 700 | 1 | |a Kielpilanen, Athina |e investigator |4 oth | |
| 700 | 1 | |a Lombarte, Oscar Blanch |e investigator |4 oth | |
| 700 | 1 | |a Lopez, Miguel Angel Marin |e investigator |4 oth | |
| 700 | 1 | |a Carabelli, Julieta |e investigator |4 oth | |
| 700 | 1 | |a Poderós, Ruth Peña |e investigator |4 oth | |
| 700 | 1 | |a Moyano, Esther Jimenez |e investigator |4 oth | |
| 700 | 1 | |a Segura, Eulalia Grau |e investigator |4 oth | |
| 700 | 1 | |a Rosa, Laia Bernard |e investigator |4 oth | |
| 700 | 1 | |a Caballero, Raul Pérez |e investigator |4 oth | |
| 700 | 1 | |a Lozano, Felipe Rodriguez |e investigator |4 oth | |
| 700 | 1 | |a Rivas, Gema Fernández |e investigator |4 oth | |
| 700 | 1 | |a Abos, Sonia Molinos |e investigator |4 oth | |
| 700 | 1 | |a de Osaba, Jaume Barallat Martinez |e investigator |4 oth | |
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| 700 | 1 | |a Cano, Cristina Perez |e investigator |4 oth | |
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| 700 | 1 | |a Martínez, Anabel López |e investigator |4 oth | |
| 700 | 1 | |a Iglesias, Inmaculada Agüera |e investigator |4 oth | |
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