Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection
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...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-03-01
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| Series: | EBioMedicine |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352396421000529 |
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| author | Charlotte Manisty Thomas Alexander Treibel Melanie Jensen Amanda Semper George Joy Rishi K Gupta Teresa Cutino-Moguel Mervyn Andiapen Jessica Jones Stephen Taylor Ashley Otter Corrina Pade Joseph Gibbons Jason Lee Joanna Bacon Steve Thomas Chris Moon Meleri Jones Dylan Williams Jonathan Lambourne Marianna Fontana Daniel M Altmann Rosemary Boyton Mala Maini Aine McKnight Benjamin Chain Mahdad Noursadeghi James C Moon |
| author_facet | Charlotte Manisty Thomas Alexander Treibel Melanie Jensen Amanda Semper George Joy Rishi K Gupta Teresa Cutino-Moguel Mervyn Andiapen Jessica Jones Stephen Taylor Ashley Otter Corrina Pade Joseph Gibbons Jason Lee Joanna Bacon Steve Thomas Chris Moon Meleri Jones Dylan Williams Jonathan Lambourne Marianna Fontana Daniel M Altmann Rosemary Boyton Mala Maini Aine McKnight Benjamin Chain Mahdad Noursadeghi James C Moon |
| author_sort | Charlotte Manisty |
| collection | DOAJ |
| description | 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: 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: 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: 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: Charitable donations via Barts Charity, Wellcome Trust, NIHR. |
| first_indexed | 2024-12-16T18:48:39Z |
| format | Article |
| id | doaj.art-31bf5280b63b4318ae172879a741e59b |
| institution | Directory Open Access Journal |
| issn | 2352-3964 |
| language | English |
| last_indexed | 2024-12-16T18:48:39Z |
| publishDate | 2021-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EBioMedicine |
| spelling | doaj.art-31bf5280b63b4318ae172879a741e59b2022-12-21T22:20:45ZengElsevierEBioMedicine2352-39642021-03-0165103259Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infectionCharlotte Manisty0Thomas Alexander Treibel1Melanie Jensen2Amanda Semper3George Joy4Rishi K Gupta5Teresa Cutino-Moguel6Mervyn Andiapen7Jessica Jones8Stephen Taylor9Ashley Otter10Corrina Pade11Joseph Gibbons12Jason Lee13Joanna Bacon14Steve Thomas15Chris Moon16Meleri Jones17Dylan Williams18Jonathan Lambourne19Marianna Fontana20Daniel M Altmann21Rosemary Boyton22Mala Maini23Aine McKnight24Benjamin Chain25Mahdad Noursadeghi26James C Moon27Institute of Cardiovascular Sciences, University College London, London, UK; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UKInstitute of Cardiovascular Sciences, University College London, London, UK; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UKBarts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UKNational Infection Service, Public Health England, Porton Down, UKBarts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UKDivision of Infection and Immunity, University College London, London, UKDepartment of Virology, Barts Health NHS Trust, London, UKCentre for Cardiovascular Medicine and Devices, William Harvey Research Institute, Queen Mary University of London, London, UKNational Infection Service, Public Health England, Porton Down, UKNational Infection Service, Public Health England, Porton Down, UKNational Infection Service, Public Health England, Porton Down, UKBlizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UKBlizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UKBlizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UKNational Infection Service, Public Health England, Porton Down, UKNational Infection Service, Public Health England, Porton Down, UKNational Infection Service, Public Health England, Porton Down, UKWolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UKMRC Unit for Lifelong Health and Ageing, University College London, London, UK; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, SwedenDepartment of Infection, Barts Health NHS Trust, London, UKRoyal Free London NHS Foundation Trust, London, UK; Division of Medicine, University College London, London, UKDepartment of Immunology and Inflammation, Imperial College London, London, UKDepartment of Infectious Disease, Imperial College London, London, UKDivision of Infection and Immunity, University College London, London, UKWolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UKDivision of Infection and Immunity, University College London, London, UKDivision of Infection and Immunity, University College London, London, UK; Corresponding author.Institute of Cardiovascular Sciences, University College London, London, UK; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UKBackground: 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: 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: 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: 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: Charitable donations via Barts Charity, Wellcome Trust, NIHR.http://www.sciencedirect.com/science/article/pii/S2352396421000529SARS-CoV-2, Serology, Mathematical modelling, Sero-reversion |
| spellingShingle | Charlotte Manisty Thomas Alexander Treibel Melanie Jensen Amanda Semper George Joy Rishi K Gupta Teresa Cutino-Moguel Mervyn Andiapen Jessica Jones Stephen Taylor Ashley Otter Corrina Pade Joseph Gibbons Jason Lee Joanna Bacon Steve Thomas Chris Moon Meleri Jones Dylan Williams Jonathan Lambourne Marianna Fontana Daniel M Altmann Rosemary Boyton Mala Maini Aine McKnight Benjamin Chain Mahdad Noursadeghi James C Moon Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection EBioMedicine SARS-CoV-2, Serology, Mathematical modelling, Sero-reversion |
| title | Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection |
| title_full | Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection |
| title_fullStr | Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection |
| title_full_unstemmed | Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection |
| title_short | Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection |
| title_sort | time series analysis and mechanistic modelling of heterogeneity and sero reversion in antibody responses to mild sars cov 2 infection |
| topic | SARS-CoV-2, Serology, Mathematical modelling, Sero-reversion |
| url | http://www.sciencedirect.com/science/article/pii/S2352396421000529 |
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