Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection.


Journal

EBioMedicine
ISSN: 2352-3964
Titre abrégé: EBioMedicine
Pays: Netherlands
ID NLM: 101647039

Informations de publication

Date de publication:
Mar 2021
Historique:
received: 24 12 2020
revised: 09 02 2021
accepted: 09 02 2021
pubmed: 5 3 2021
medline: 7 4 2021
entrez: 4 3 2021
Statut: ppublish

Résumé

SARS-CoV-2 serology is used to identify prior infection at individual and at population level. Extended longitudinal studies with multi-timepoint sampling to evaluate dynamic changes in antibody levels are required to identify the time horizon in which these applications of serology are valid, and to explore the longevity of protective humoral immunity. Healthcare workers were recruited to a prospective cohort study from the first SARS-CoV-2 epidemic peak in London, undergoing weekly symptom screen, viral PCR and blood sampling over 16-21 weeks. Serological analysis (n =12,990) was performed using semi-quantitative Euroimmun IgG to viral spike S1 domain and Roche total antibody to viral nucleocapsid protein (NP) assays. Comparisons were made to pseudovirus neutralizing antibody measurements. A total of 157/729 (21.5%) participants developed positive SARS-CoV-2 serology by one or other assay, of whom 31.0% were asymptomatic and there were no deaths. Peak Euroimmun anti-S1 and Roche anti-NP measurements correlated (r = 0.57, p<0.0001) but only anti-S1 measurements correlated with near-contemporary pseudovirus neutralising antibody titres (measured at 16-18 weeks, r = 0.57, p<0.0001). By 21 weeks' follow-up, 31/143 (21.7%) anti-S1 and 6/150 (4.0%) anti-NP measurements reverted to negative. Mathematical modelling revealed faster clearance of anti-S1 compared to anti-NP (median half-life of 2.5 weeks versus 4.0 weeks), earlier transition to lower levels of antibody production (median of 8 versus 13 weeks), and greater reductions in relative antibody production rate after the transition (median of 35% versus 50%). Mild SARS-CoV-2 infection is associated with heterogeneous serological responses in Euroimmun anti-S1 and Roche anti-NP assays. Anti-S1 responses showed faster rates of clearance, more rapid transition from high to low level production rate and greater reduction in production rate after this transition. In mild infection, anti-S1 serology alone may underestimate incident infections. The mechanisms that underpin faster clearance and lower rates of sustained anti-S1 production may impact on the longevity of humoral immunity. Charitable donations via Barts Charity, Wellcome Trust, NIHR.

Sections du résumé

BACKGROUND BACKGROUND
SARS-CoV-2 serology is used to identify prior infection at individual and at population level. Extended longitudinal studies with multi-timepoint sampling to evaluate dynamic changes in antibody levels are required to identify the time horizon in which these applications of serology are valid, and to explore the longevity of protective humoral immunity.
METHODS METHODS
Healthcare workers were recruited to a prospective cohort study from the first SARS-CoV-2 epidemic peak in London, undergoing weekly symptom screen, viral PCR and blood sampling over 16-21 weeks. Serological analysis (n =12,990) was performed using semi-quantitative Euroimmun IgG to viral spike S1 domain and Roche total antibody to viral nucleocapsid protein (NP) assays. Comparisons were made to pseudovirus neutralizing antibody measurements.
FINDINGS RESULTS
A total of 157/729 (21.5%) participants developed positive SARS-CoV-2 serology by one or other assay, of whom 31.0% were asymptomatic and there were no deaths. Peak Euroimmun anti-S1 and Roche anti-NP measurements correlated (r = 0.57, p<0.0001) but only anti-S1 measurements correlated with near-contemporary pseudovirus neutralising antibody titres (measured at 16-18 weeks, r = 0.57, p<0.0001). By 21 weeks' follow-up, 31/143 (21.7%) anti-S1 and 6/150 (4.0%) anti-NP measurements reverted to negative. Mathematical modelling revealed faster clearance of anti-S1 compared to anti-NP (median half-life of 2.5 weeks versus 4.0 weeks), earlier transition to lower levels of antibody production (median of 8 versus 13 weeks), and greater reductions in relative antibody production rate after the transition (median of 35% versus 50%).
INTERPRETATION CONCLUSIONS
Mild SARS-CoV-2 infection is associated with heterogeneous serological responses in Euroimmun anti-S1 and Roche anti-NP assays. Anti-S1 responses showed faster rates of clearance, more rapid transition from high to low level production rate and greater reduction in production rate after this transition. In mild infection, anti-S1 serology alone may underestimate incident infections. The mechanisms that underpin faster clearance and lower rates of sustained anti-S1 production may impact on the longevity of humoral immunity.
FUNDING BACKGROUND
Charitable donations via Barts Charity, Wellcome Trust, NIHR.

Identifiants

pubmed: 33662833
pii: S2352-3964(21)00052-9
doi: 10.1016/j.ebiom.2021.103259
pmc: PMC7920816
pii:
doi:

Substances chimiques

Antibodies, Neutralizing 0
Antibodies, Viral 0
Coronavirus Nucleocapsid Proteins 0
Immunoglobulin A 0
Immunoglobulin G 0
Phosphoproteins 0
Spike Glycoprotein, Coronavirus 0
nucleocapsid phosphoprotein, SARS-CoV-2 0
spike protein, SARS-CoV-2 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103259

Subventions

Organisme : Medical Research Council
ID : MR/V027883/1
Pays : United Kingdom
Organisme : Department of Health
ID : DRF-2018-11-ST2-004
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/S019553/1
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W020610/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/V036939/1
Pays : United Kingdom
Organisme : British Heart Foundation
ID : FS/18/21/33447
Pays : United Kingdom

Informations de copyright

Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interests DA and RB report consultancy fees from Oxford Immunotec, RKG reports grants from NIHR, during the conduct of the study; CM reports grants from Barts Charity during the conduct of the study; MN reports grants from Wellcome Trust, during the conduct of the study; DW reports personal fees from Barts Health NHS Trust during the conduct of the study. The authors declare no conflicts of interest.

Auteurs

Charlotte Manisty (C)

Institute of Cardiovascular Sciences, University College London, London, UK; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK.

Thomas Alexander Treibel (TA)

Institute of Cardiovascular Sciences, University College London, London, UK; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK.

Melanie Jensen (M)

Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK.

Amanda Semper (A)

National Infection Service, Public Health England, Porton Down, UK.

George Joy (G)

Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK.

Rishi K Gupta (RK)

Division of Infection and Immunity, University College London, London, UK.

Teresa Cutino-Moguel (T)

Department of Virology, Barts Health NHS Trust, London, UK.

Mervyn Andiapen (M)

Centre for Cardiovascular Medicine and Devices, William Harvey Research Institute, Queen Mary University of London, London, UK.

Jessica Jones (J)

National Infection Service, Public Health England, Porton Down, UK.

Stephen Taylor (S)

National Infection Service, Public Health England, Porton Down, UK.

Ashley Otter (A)

National Infection Service, Public Health England, Porton Down, UK.

Corrina Pade (C)

Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Joseph Gibbons (J)

Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Jason Lee (J)

Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Joanna Bacon (J)

National Infection Service, Public Health England, Porton Down, UK.

Steve Thomas (S)

National Infection Service, Public Health England, Porton Down, UK.

Chris Moon (C)

National Infection Service, Public Health England, Porton Down, UK.

Meleri Jones (M)

Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Dylan Williams (D)

MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Jonathan Lambourne (J)

Department of Infection, Barts Health NHS Trust, London, UK.

Marianna Fontana (M)

Royal Free London NHS Foundation Trust, London, UK; Division of Medicine, University College London, London, UK.

Daniel M Altmann (DM)

Department of Immunology and Inflammation, Imperial College London, London, UK.

Rosemary Boyton (R)

Department of Infectious Disease, Imperial College London, London, UK.

Mala Maini (M)

Division of Infection and Immunity, University College London, London, UK.

Aine McKnight (A)

Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Benjamin Chain (B)

Division of Infection and Immunity, University College London, London, UK.

Mahdad Noursadeghi (M)

Division of Infection and Immunity, University College London, London, UK. Electronic address: m.noursadeghi@ucl.ac.uk.

James C Moon (JC)

Institute of Cardiovascular Sciences, University College London, London, UK; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK.

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Classifications MeSH