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

被引：42

作者：

Manisty, Charlotte ^{[1
,2
]}

Treibel, Thomas Alexander ^{[1
,2
]}

Jensen, Melanie ^{[2
]}

Semper, Amanda ^{[3
]}

Joy, George ^{[2
]}

Gupta, Rishi K. ^{[4
]}

Cutino-Moguel, Teresa ^{[5
]}

Andiapen, Mervyn ^{[6
]}

Jones, Jessica ^{[3
]}

Taylor, Stephen ^{[3
]}

Otter, Ashley ^{[3
]}

Pade, Corrina ^{[7
]}

Gibbons, Joseph ^{[7
]}

Lee, Jason ^{[7
]}

Bacon, Joanna ^{[3
]}

Thomas, Steve ^{[3
]}

Moon, Chris ^{[3
]}

Jones, Meleri ^{[8
]}

Williams, Dylan ^{[9
,10
]}

Lambourne, Jonathan ^{[11
]}

Fontana, Marianna ^{[12
,13
]}

Altmann, Daniel M. ^{[14
]}

Boyton, Rosemary ^{[15
]}

Maini, Mala ^{[4
]}

McKnight, Aine ^{[8
]}

Chain, Benjamin ^{[4
]}

Noursadeghi, Mahdad ^{[4
]}

Moon, James C. ^{[1
,2
]}

机构：

[1] UCL, Inst Cardiovasc Sci, London, England

[2] St Bartholomews Hosp, Barts Heart Ctr, Barts Hlth NHS Trust, London, England

[3] Publ Hlth England, Natl Infect Serv, Porton Down, England

[4] UCL, Div Infect & Immun, London, England

[5] Barts Hlth NHS Trust, Dept Virol, London, England

[6] Queen Mary Univ London, Ctr Cardiovasc Med & Devices, William Harvey Res Inst, London, England

[7] Queen Mary Univ London, Barts & London Sch Med & Dent, Blizard Inst, London, England

[8] Queen Mary Univ London, Barts & London Sch Med & Dent, Wolfson Inst Prevent Med, London, England

[9] UCL, MRC Unit Lifelong Hlth & Ageing, London, England

[10] Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden

[11] Barts Hlth NHS Trust, Dept Infect, London, England

[12] Royal Free London NHS Fdn Trust, London, England

[13] UCL, Div Med, London, England

[14] Imperial Coll London, Dept Immunol & Inflammat, London, England

[15] Imperial Coll London, Dept Infect Dis, London, England

来源：

EBIOMEDICINE | 2021年 / 65卷

基金：

英国惠康基金; 欧盟地平线“2020”;

关键词：

SARS-CoV-2; Serology; Mathematical modelling; Sero-reversion; HEALTH-CARE WORKERS;

D O I：

10.1016/j.ebiom.2021.103259

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

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. Inmild 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. (C) 2021 The Authors. Published by Elsevier B.V.

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