Immune correlates analysis of the mRNA-1273 COVID-19 vaccine efficacy clinical trial

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Abstract

Antibody levels predict vaccine efficacy

Symptomatic COVID-19 infection can be prevented by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines. A “correlate of protection” is a molecular biomarker to measure how much immunity is needed to fight infection and is key for successful global immunization programs. Gilbert et al. determined that antibodies are the correlate of protection in vaccinated individuals enrolled in the Moderna COVE phase 3 clinical trial (see the Perspective by Openshaw). By measuring binding and neutralizing antibodies against the viral spike protein, the authors found that the levels of both antibodies correlated with the degree of vaccine efficacy. The higher the antibody level, the greater the protection afforded by the messenger RNA (mRNA) vaccine. Antibody levels that predict mRNA vaccine efficacy can therefore be used to guide vaccine regimen modifications and support regulatory approvals for a broader spectrum of the population. —PNK

Abstract

SARS-CoV-2 binding and neutralizing antibodies correlate with the degree of vaccine efficacy and protection for the Moderna mRNA COVID-19 vaccine.

Abstract

In the coronavirus efficacy (COVE) phase 3 clinical trial, vaccine recipients were assessed for neutralizing and binding antibodies as correlates of risk for COVID-19 disease and as correlates of protection. These immune markers were measured at the time of second vaccination and 4 weeks later, with values reported in standardized World Health Organization international units. All markers were inversely associated with COVID-19 risk and directly associated with vaccine efficacy. Vaccine recipients with postvaccination 50% neutralization titers 10, 100, and 1000 had estimated vaccine efficacies of 78% (95% confidence interval, 54 to 89%), 91% (87 to 94%), and 96% (94 to 98%), respectively. These results help define immune marker correlates of protection and may guide approval decisions for messenger RNA (mRNA) COVID-19 vaccines and other COVID-19 vaccines.

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Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine

Lindsey Baden, Hana El Sahly, Brandon Essink … (2020)

Abstract Background Vaccines are needed to prevent coronavirus disease 2019 (Covid-19) and to protect persons who are at high risk for complications. The mRNA-1273 vaccine is a lipid nanoparticle–encapsulated mRNA-based vaccine that encodes the prefusion stabilized full-length spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes Covid-19. Methods This phase 3 randomized, observer-blinded, placebo-controlled trial was conducted at 99 centers across the United States. Persons at high risk for SARS-CoV-2 infection or its complications were randomly assigned in a 1:1 ratio to receive two intramuscular injections of mRNA-1273 (100 μg) or placebo 28 days apart. The primary end point was prevention of Covid-19 illness with onset at least 14 days after the second injection in participants who had not previously been infected with SARS-CoV-2. Results The trial enrolled 30,420 volunteers who were randomly assigned in a 1:1 ratio to receive either vaccine or placebo (15,210 participants in each group). More than 96% of participants received both injections, and 2.2% had evidence (serologic, virologic, or both) of SARS-CoV-2 infection at baseline. Symptomatic Covid-19 illness was confirmed in 185 participants in the placebo group (56.5 per 1000 person-years; 95% confidence interval [CI], 48.7 to 65.3) and in 11 participants in the mRNA-1273 group (3.3 per 1000 person-years; 95% CI, 1.7 to 6.0); vaccine efficacy was 94.1% (95% CI, 89.3 to 96.8%; P<0.001). Efficacy was similar across key secondary analyses, including assessment 14 days after the first dose, analyses that included participants who had evidence of SARS-CoV-2 infection at baseline, and analyses in participants 65 years of age or older. Severe Covid-19 occurred in 30 participants, with one fatality; all 30 were in the placebo group. Moderate, transient reactogenicity after vaccination occurred more frequently in the mRNA-1273 group. Serious adverse events were rare, and the incidence was similar in the two groups. Conclusions The mRNA-1273 vaccine showed 94.1% efficacy at preventing Covid-19 illness, including severe disease. Aside from transient local and systemic reactions, no safety concerns were identified. (Funded by the Biomedical Advanced Research and Development Authority and the National Institute of Allergy and Infectious Diseases; COVE ClinicalTrials.gov number, NCT04470427.)

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Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

Merryn Voysey, Sue Ann Costa Clemens, Shabir Madhi … (2022)

Background A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. Methods This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. Findings Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0–75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4–97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; p interaction =0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8–80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3–4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. Interpretation ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials. Funding UK Research and Innovation, National Institutes for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, Bill & Melinda Gates Foundation, Lemann Foundation, Rede D’Or, Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca.

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Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection

David Khoury, Deborah Cromer, Arnold Reynaldi … (2021)

Predictive models of immune protection from COVID-19 are urgently needed to identify correlates of protection to assist in the future deployment of vaccines. To address this, we analyzed the relationship between in vitro neutralization levels and the observed protection from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using data from seven current vaccines and from convalescent cohorts. We estimated the neutralization level for 50% protection against detectable SARS-CoV-2 infection to be 20.2% of the mean convalescent level (95% confidence interval (CI) = 14.4-28.4%). The estimated neutralization level required for 50% protection from severe infection was significantly lower (3% of the mean convalescent level; 95% CI = 0.7-13%, P = 0.0004). Modeling of the decay of the neutralization titer over the first 250 d after immunization predicts that a significant loss in protection from SARS-CoV-2 infection will occur, although protection from severe disease should be largely retained. Neutralization titers against some SARS-CoV-2 variants of concern are reduced compared with the vaccine strain, and our model predicts the relationship between neutralization and efficacy against viral variants. Here, we show that neutralization level is highly predictive of immune protection, and provide an evidence-based model of SARS-CoV-2 immune protection that will assist in developing vaccine strategies to control the future trajectory of the pandemic.

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Author and article information

Contributors

Peter B. Gilbert:

ORCID: https://orcid.org/0000-0002-2662-9427

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

David C. Montefiori:

ORCID: https://orcid.org/0000-0003-0856-6319

Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - review & editing

Adrian B. McDermott:

ORCID: https://orcid.org/0000-0003-0616-9117

Role: ConceptualizationRole: Data curationRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: Visualization

Youyi Fong: Role: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

David Benkeser: Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing - review & editing

Weiping Deng: Role: Formal analysisRole: SoftwareRole: Validation

Honghong Zhou: Role: ConceptualizationRole: Data curationRole: Software

Christopher R. Houchens:

ORCID: https://orcid.org/0000-0001-8125-4173

Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing - review & editing

Karen Martins:

ORCID: https://orcid.org/0000-0001-6536-3492

Role: ConceptualizationRole: Project administrationRole: ResourcesRole: Writing - review & editing

Lakshmi Jayashankar:

ORCID: https://orcid.org/0000-0003-0384-2388

Role: ConceptualizationRole: Project administrationRole: ResourcesRole: Writing - review & editing

Flora Castellino: Role: Investigation

Britta Flach: Role: MethodologyRole: Validation

Bob C. Lin: Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: Validation

Sarah O’Connell: Role: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: ValidationRole: Writing - original draft

Charlene McDanal: Role: Investigation

Amanda Eaton:

ORCID: https://orcid.org/0000-0003-3064-2947

Role: InvestigationRole: Project administrationRole: ResourcesRole: Validation

Marcella Sarzotti-Kelsoe: Role: MethodologyRole: Resources

Yiwen Lu: Role: Formal analysisRole: SoftwareRole: Validation

Chenchen Yu: Role: Formal analysis

Bhavesh Borate: Role: Software

Lars W. P. van der Laan: Role: Formal analysisRole: MethodologyRole: Software

Nima S. Hejazi: Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Chuong Huynh: Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing - review & editing

Jacqueline Miller:

ORCID: https://orcid.org/0000-0002-7083-2182

Role: ConceptualizationRole: Project administrationRole: Supervision

Hana M. El Sahly:

ORCID: https://orcid.org/0000-0003-0489-0074

Role: ConceptualizationRole: Data curationRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing - review & editing

Lindsey R. Baden: Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: Writing - review & editing

Mira Baron:

ORCID: https://orcid.org/0000-0001-8833-3659

Role: InvestigationRole: Resources

Cynthia Gay: Role: InvestigationRole: Project administrationRole: ResourcesRole: Writing - review & editing

Spyros Kalams: Role: Data curationRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing - review & editing

Colleen F. Kelley:

ORCID: https://orcid.org/0000-0001-5611-0119

Role: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing - review & editing

Michele P. Andrasik:

ORCID: https://orcid.org/0000-0003-1952-7825

Role: Project administrationRole: SupervisionRole: ValidationRole: Writing - review & editing

James G. Kublin:

ORCID: https://orcid.org/0000-0003-1279-3741

Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: Supervision

Lawrence Corey:

ORCID: https://orcid.org/0000-0002-2179-2436

Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing - original draftRole: Writing - review & editing

Kathleen M. Neuzil:

ORCID: https://orcid.org/0000-0001-9480-2714

Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing - review & editing

Lindsay N. Carpp:

ORCID: https://orcid.org/0000-0003-0333-5925

Role: VisualizationRole: Writing - original draftRole: Writing - review & editing

Rolando Pajon: Role: ConceptualizationRole: InvestigationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - review & editing

Dean Follmann:

ORCID: https://orcid.org/0000-0003-4073-0393

Role: ConceptualizationRole: MethodologyRole: Writing - review & editing

Ruben O. Donis:

ORCID: https://orcid.org/0000-0001-6137-8312

Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - original draftRole: Writing - review & editing

Richard A. Koup:

ORCID: https://orcid.org/0000-0002-3090-7282

Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - review & editing

Journal

Journal ID (nlm-ta): Science

Journal ID (iso-abbrev): Science

Journal ID (publisher-id): science

Title: Science (New York, N.y.)

Publisher: American Association for the Advancement of Science

ISSN (Print): 0036-8075

ISSN (Electronic): 1095-9203

Publication date (Electronic, pub): 23 November 2021

Publication date (Print, pub): 07 January 2022

Publication date PMC-release: 23 November 2021

Volume: 375

Issue: 6576

Pages: 43-50

Affiliations

[1 ]Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

[2 ]Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

[3 ]Department of Biostatistics, University of Washington, Seattle, WA, USA.

[4 ]Department of Surgery and Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC, USA.

[5 ]Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.

[6 ]Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

[7 ]Moderna, Inc., Cambridge, MA, USA.

[8 ]Biomedical Advanced Research and Development Authority, Washington, DC, USA.

[9 ]Division of Biostatistics, School of Public Health, University of California Berkeley, Berkeley, CA, USA.

[10 ]Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.

[11 ]Brigham and Women’s Hospital, Boston, MA, USA.

[12 ]Palm Beach Research Center, West Palm Beach, FL, USA.

[13 ]Keystone Vitalink Research, Greenville, SC, USA.

[14 ]Department of Medicine, Division of Infectious Diseases, UNC HIV Cure Center, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA.

[15 ]Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.

[16 ]Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine and the Grady Health System, Atlanta, GA, USA.

[17 ]Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.

[18 ]Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA.

[19 ]Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.

Author notes

[* ]Corresponding author. Email: pgilbert@ 123456fredhutch.org

[†]

These authors contributed equally to this work.

[‡]

These authors contributed equally to this work.

[§]

The members of the Immune Assays Team; Moderna, Inc. Team; CoVPN/COVE Team; and USG/CoVPN Biostatistics Team and their affiliations are listed in the supplementary materials.

Author information

Peter B. Gilbert https://orcid.org/0000-0002-2662-9427

David C. Montefiori https://orcid.org/0000-0003-0856-6319

Adrian B. McDermott https://orcid.org/0000-0003-0616-9117

Christopher R. Houchens https://orcid.org/0000-0001-8125-4173

Karen Martins https://orcid.org/0000-0001-6536-3492

Lakshmi Jayashankar https://orcid.org/0000-0003-0384-2388

Amanda Eaton https://orcid.org/0000-0003-3064-2947

Jacqueline Miller https://orcid.org/0000-0002-7083-2182

Hana M. El Sahly https://orcid.org/0000-0003-0489-0074

Mira Baron https://orcid.org/0000-0001-8833-3659

Colleen F. Kelley https://orcid.org/0000-0001-5611-0119

Michele P. Andrasik https://orcid.org/0000-0003-1952-7825

James G. Kublin https://orcid.org/0000-0003-1279-3741

Lawrence Corey https://orcid.org/0000-0002-2179-2436

Kathleen M. Neuzil https://orcid.org/0000-0001-9480-2714

Lindsay N. Carpp https://orcid.org/0000-0003-0333-5925

Dean Follmann https://orcid.org/0000-0003-4073-0393

Ruben O. Donis https://orcid.org/0000-0001-6137-8312

Richard A. Koup https://orcid.org/0000-0002-3090-7282

Article

Publisher ID: abm3425

DOI: 10.1126/science.abm3425

PMC ID: 9017870

PubMed ID: 34812653

SO-VID: 762d786c-4246-463a-82a7-c4dc30e108e5

Copyright © Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 16 September 2021

Date accepted : 16 November 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;

Award ID: UM1AI068635

Funded by: FundRef http://dx.doi.org/10.13039/100012399, Biomedical Advanced Research and Development Authority;

Award ID: Contract No. 75A50120C00034

Funded by: FundRef http://dx.doi.org/10.13039/100016958, Office of Research Infrastructure Programs, National Institutes of Health;

Award ID: S10OD028685

Funded by: Moderna, Inc.;

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Immune correlates analysis of the mRNA-1273 COVID-19 vaccine efficacy clinical trial

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Abstract

Antibody levels predict vaccine efficacy

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Most cited references 34

Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection

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Cited by 494

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