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Ebola virus antibody decay–stimulation in a high proportion of survivors

Abstract

Neutralizing antibody function provides a foundation for the efficacy of vaccines and therapies1,2,3. Here, using a robust in vitro Ebola virus (EBOV) pseudo-particle infection assay and a well-defined set of solid-phase assays, we describe a wide spectrum of antibody responses in a cohort of healthy survivors of the Sierra Leone EBOV outbreak of 2013–2016. Pseudo-particle virus-neutralizing antibodies correlated with total anti-EBOV reactivity and neutralizing antibodies against live EBOV. Variant EBOV glycoproteins (1995 and 2014 strains) were similarly neutralized. During longitudinal follow-up, antibody responses fluctuated in a ‘decay–stimulation–decay’ pattern that suggests de novo restimulation by EBOV antigens after recovery. A pharmacodynamic model of antibody reactivity identified a decay half-life of 77–100 days and a doubling time of 46–86 days in a high proportion of survivors. The highest antibody reactivity was observed around 200 days after an individual had recovered. The model suggests that EBOV antibody reactivity declines over 0.5–2 years after recovery. In a high proportion of healthy survivors, antibody responses undergo rapid restimulation. Vigilant follow-up of survivors and possible elective de novo antigenic stimulation by vaccine immunization should be considered in order to prevent EBOV viral recrudescence in recovering individuals and thereby to mitigate the potential risk of reseeding an outbreak.

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Fig. 1: EBOV-GP HIV-1 pseudo-typed virus neutralization assay.
Fig. 2: Convalescent plasma neutralizing antibody titres.
Fig. 3: Rates of EBOV antibody decay and recovery following the 2013–2016 West Africa outbreak.

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Data availability

All datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Source data are provided with this paper.

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Acknowledgements

We thank colleagues variously for their support and encouragement: the Sierra Leone Association of Ebola Survivors (Freetown, Sierra Leone); the members of the Convalescent Products and Allied Therapy Intervention Technical Committee; the Research Ethics Committee and the Pharmacy Board Committee (all Ministry of Health and Sanitation, Republic of Sierra Leone); staff in Virus Reference Department Public Health England for handling and clearing samples from quarantine; G. McCann and L. Matthews for project management; I. Bates for expertise in strengthening transfusion services; W. A. Brooks; M. P. Kieny; C. Burm and D. Arango; N. F. Walker; A. Jones; colleagues from the World Health Organization (WHO); and the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC). Proofreading support provided by M. de Baar and graphical support provided by S. Yee. The study “Convalescent plasma for early Ebola virus disease in Sierra Leone (Ebola CP)” (ISRCTN13990511 and PACTR201602001355272) was supported by the Wellcome Trust (Award 106491) and Bill and Melinda Gates Foundation; Public Health England Ebola Emergency Response; and the Blood Safety Programme, National Health Service Blood and Transplant. J.T.S. was supported by the Wellcome Trust. M.G.S. and J.T.S. were supported by the UK National Institute for Health Research Health Protection Research Unit in Emerging and Zoonotic Infections at the University of Liverpool. The funders had no role in the collection and analysis of the samples, in the interpretation of data, in writing the report, or in the decision to submit the paper for publication.

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Authors and Affiliations

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Contributions

G.P., W.A.P., J.T.S. and M.G.S. initiated and designed the study. C.A., R.S.T., J.T.S., R.S., R.J.D. and R.G. collected data and/or performed the analysis. C.A., G.P. and W.A.P. wrote the manuscript. M.G.S., J.T.S., G.P., R.S.T., R.J.D. and W.A.P. edited the manuscript. M.G.S. sourced the funding and is Ebola-CP Consortium Lead Investigator. All authors were critical for study delivery whether through recruitment, coordination, collection of participant data and material, assay development or analysis of samples. All authors read and approved the contents of the manuscript. GSK was not involved in the design, conduct or analysis of the study.

Corresponding author

Correspondence to Georgios Pollakis.

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The authors declare no competing interests.

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Peer review information Nature thanks Jayajit Das and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Development and characterization of Ebola pseudo-particle virus.

a, Variant pEBOV14-GP plasmid concentrations were transfected alongside 2000 ng of pSG3-HIV-1 backbone. The resulting pseudo-typed virus, quantified by a HIV-1-p24 capsid ELISA (squares), was tested for infectivity in TZM-bl cells as measured by luciferase activity (data are mean ± s.d.). The red marked square identifies the glycoprotein concentrations that can be used in the assay. b, Inhibition profiles with negative plasma donated from six individuals (grey squares), indicating no specific plasma inhibition during the neutralization assay. All negative assays and plasmas were combined to define the range within which negative plasma control were acceptable (red squares) thus defining a valid assay. The blue line shows the lack of reactivity on the HIV-1-enveloped pseudo-typed virus by EBOV neutralizing convalescent plasma (CP) (squares and circles indicate the median and the vertical lines the standard error). c, Neutralization profiles of pEBOV14-GP by the WHO reference panel of anti-EBOV CP. The standard identifiers are shown. d, Reproducibility of the neutralization assay determined by measuring the IC50 of CP on the three EBOV isolates (yellow-pEBOV14-GP, purple- pEBOV95-GP and green- pEBOV14m-GP). The two-tailed parametric paired t-test was used. e, Neutralization potential of CPs against three virus strains (pEBOV14-GP/n = 83, pEBOV95-GP/n = 69 and pEBOV14m-GP/n = 77) expressed in IC70 (data are presented as mean values ± s.d. Kruskal–Wallis test was performed). f, delta-IC70 neutralization titres between virus strain pairs by each post-cure study participant. g, Positive association between PPV IC70 titres the live virus plaque reduction neutralization test (PRNT). h, Positive association between PPV IC70 neutralization titres and the double antigen bridging assay (DABA).

Source data

Extended Data Fig. 2 Pseudo-particle virus neutralization profiles by convalescent plasma.

ac, Anti-EBOV14-GP (an = 92), anti-EBOV14m-GP (bn = 70) and anti-EBOV95-GP (cn = 76) neutralization curves using serial dilutions of CP inhibiting PPV cell entry, as described in methods. The plasma samples were deciphered as possessing low (blue), intermediate (magenta) or high (orange) neutralization to demonstrate the similar profiles of the three virus glycoproteins studied. The red square curve indicates the range of inhibition by control plasma. d, Comparison of the analyses (n = 30) (i) considering the 0% inhibition value whenever two reciprocal consecutive high plasma dilutions produced equal infection levels, and (ii) considering 0% inhibition as the infection values of virus in the absence of convalescent plasma performed in each individual experiment. The Pearson correlation coefficients were computed.

Source data

Extended Data Fig. 3 Association of IC50 and IC70 neutralizing dilutions of the post-cure plasma samples inhibiting cell entry of pseudotyped virus particles harbouring the variant EBOV GP molecules.

The Pearson correlation coefficients were computed.

Source data

Extended Data Fig. 4 Longitudinal post convalescence nAb variation in the plasma of individuals 18, 19 and 21 demonstrated by pseudotyped virus particle neutralization.

Anti-EBOV14-GP (light blue) and anti-EBOV95-GP (dark blue) nAb titres were overlaid with the blocking EIAs carried out for the detection of antibody against the nucleoprotein [NP] (brown squares), the viral matrix protein 40 [VP40] (purple squares) and the glycoprotein [GP] (green squares).

Source data

Extended Data Fig. 5 Longitudinal G-capture and competitive EIAs performed using plasma from individuals 18, 19, 21, 45 and 49 against the glycoprotein as previously described.

The longitudinal G-capture (pink) and competitive (green) EIAs were performed against the glycoprotein as previously described21. The antibody reactivities were overlaid with pseudotyped virus particle IC50 neutralization values against EBOV14-GP (light blue) and EBOV95-GP (dark blue).

Source data

Extended Data Fig. 6 Total antibody reactivity as measured by double antigen bridging assay (DABA) (average of a duplicate measurement) for the Ebola post-cure cohort participants with longitudinal follow up (≥2 data points, n = 51) demonstrating decline–restimulation–decline (in any order) of antibody reactivity over time.

Decline is indicated by a black line and restimulation by a yellow horizontal line.

Source data

Extended Data Fig. 7 Total antibody reactivity as measured by double antigen bridging assay (DABA).

‘Lowest titre following decline’ is the last point in a participant presenting antibody titre decline, while ‘High titre upon stimulation’ is the subsequent point demonstrating antibody stimulation. Two-tailed parametric paired t-test (P = 0.0014).

Source data

Extended Data Fig. 8 Observed versus predicted plots for the growth and decay models as determined by the DABA assay.

ab, Plots for selected logistic growth model for antibody stimulation. a, Population predicted values. b, Individual predicted values. c, d, Plots for selected two-compartment decay model with saturable recycling for antibody stimulation. c, Population predicted values. d, Individual predicted values. Solid red circles represent the individual observed or model-predicted Ab values. Solid blue line and dotted red line represent the line of regression and line of unity, respectively.

Source data

Extended Data Fig. 9 Flow diagram describing the observed antibody decrease and increase events as measured by DABA.

These were used to develop the compartmental population pharmacodynamic models.

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Adaken, C., Scott, J.T., Sharma, R. et al. Ebola virus antibody decay–stimulation in a high proportion of survivors. Nature 590, 468–472 (2021). https://doi.org/10.1038/s41586-020-03146-y

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  1. I wonder if the reported incidences recrudescence of SARS-CoV-2 could be due to the same "reservoir" effect and whether anybody is already researching this area?

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