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Cited by 1,137SARS-CoV-2 and COVID-19 ResearchCOVID-19 Clinical Research Studiesvaccines and immunoinformatics approaches

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

Open access
Gilbert, Peter B., Montefiori, David C., McDermott, Adrian B., Fong, Youyi, Benkeser, David, Deng, Weiping, Zhou, Honghong, Houchens, Christopher R., Martins, Karen, Jayashankar, Lakshmi, Castellino, Flora, Flach, Britta, Lin, Bob C., O’Connell, Sarah, McDanal, Charlene, Eaton, Amanda, Sarzotti-Kelsoe, Marcella, Lu, Yiwen, Yu, Chenchen, Borate, Bhavesh, van der Laan, Lars W. P., Hejazi, Nima S., Huynh, Chuong, Miller, Jacqueline, El Sahly, Hana M., Baden, Lindsey R., Baron, Mira, De La Cruz, Luis, Gay, Cynthia, Kalams, Spyros, Kelley, Colleen F., Andrasik, Michele P., Kublin, James G., Corey, Lawrence, Neuzil, Kathleen M., Carpp, Lindsay N., Pajon, Rolando, Follmann, Dean, Donis, Ruben O., Koup, Richard A., Immune Assays Team§, Moderna, Inc. Team§, Coronavirus Vaccine Prevention Network (CoVPN)/Coronavirus Efficacy (COVE) Team§, United States Government (USG)/CoVPN Biostatistics Team§·2022·Science
DOI 10.1126/science.abm3425PMC PMC8366808

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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

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Figure 1: (A) Anti-Spike IgG concentration and (B) pseudovirus neutralization cID50 titer by COVID-19 outcome status. Data points are from baseline negative per-protocol vaccine recipients selected into the case-cohort set. The violin plots contain interior box plots with upper and lower horizontal edges the 25th and 75th percentiles of antibody level and middle line the 50th percentile. Each side shows a rotated probability density (estimated by a kernel density estimator with a default Gaussian kernel) of the data. Positive response rates were computed with inverse probability of sampling weighting. Pos.Cut, Positivity cut-off. LoD, limit of detection. ULoQ, upper limit of quantitation; ULOQ = 10,919 for cID50 (above all data points). Post Day 57 cases are COVID-19 endpoints starting 7 days post Day 57 visit; Intercurrent cases are COVID-19 endpoints starting 7 days post Day 29 visit through 6 days post Day 57 visit. cID50: ID50 nAb titer calibrated to the WHO International Standard.
Figure 1: (A) Anti-Spike IgG concentration and (B) pseudovirus neutralization cID50 titer by COVID-19 outcome status. Data points are from baseline negative per-protocol vaccine recipients selected into the case-cohort set. The violin plots contain interior box plots with upper and lower horizontal edges the 25th and 75th percentiles of antibody level and middle line the 50th percentile. Each side shows a rotated probability density (estimated by a kernel density estimator with a default Gaussian kernel) of the data. Positive response rates were computed with inverse probability of sampling weighting. Pos.Cut, Positivity cut-off. LoD, limit of detection. ULoQ, upper limit of quantitation; ULOQ = 10,919 for cID50 (above all data points). Post Day 57 cases are COVID-19 endpoints starting 7 days post Day 57 visit; Intercurrent cases are COVID-19 endpoints starting 7 days post Day 29 visit through 6 days post Day 57 visit. cID50: ID50 nAb titer calibrated to the WHO International Standard.CC BY-NC-ND · PubMed Central
Figure 2. Covariate-adjusted cumulative incidence of COVID-19 by Low, Medium, High tertile of Day 57 IgG concentration or pseudovirus neutralization titer. (A) Anti-Spike IgG concentration; (B) cID50 titer; (C) IgG (Spike, RBD) and (cID50, cID80). The overall p-value is from a generalized Wald test of whether the hazard rate of COVID-19 differed across the Low, Medium, and High subgroups. cID50, cID80: ID50 or ID80 nAb titer calibrated to the WHO International Standard.
Figure 2. Covariate-adjusted cumulative incidence of COVID-19 by Low, Medium, High tertile of Day 57 IgG concentration or pseudovirus neutralization titer. (A) Anti-Spike IgG concentration; (B) cID50 titer; (C) IgG (Spike, RBD) and (cID50, cID80). The overall p-value is from a generalized Wald test of whether the hazard rate of COVID-19 differed across the Low, Medium, and High subgroups. cID50, cID80: ID50 or ID80 nAb titer calibrated to the WHO International Standard.CC BY-NC-ND · PubMed Central
Figure 3. Covariate-adjusted hazard ratios of COVID-19 per 10-fold increase in each Day 57 antibody marker in baseline negative per-protocol vaccine recipients overall and in subgroups. (A) Inferences for IgG (Spike, RBD) and (cID50, cID80); (B) Forest plots for Spike IgG; (C) Forest plots for cID50. cID50, cID80: ID50 or ID80 neutralizing antibody titer calibrated to the WHO International Standard. Comm. of color = all participants other than White Non-Hispanic.
Figure 3. Covariate-adjusted hazard ratios of COVID-19 per 10-fold increase in each Day 57 antibody marker in baseline negative per-protocol vaccine recipients overall and in subgroups. (A) Inferences for IgG (Spike, RBD) and (cID50, cID80); (B) Forest plots for Spike IgG; (C) Forest plots for cID50. cID50, cID80: ID50 or ID80 neutralizing antibody titer calibrated to the WHO International Standard. Comm. of color = all participants other than White Non-Hispanic.CC BY-NC-ND · PubMed Central
Figure 4. (A) Covariate-adjusted cumulative incidence of COVID-19 by 100 days post Day 57 by subgroups defined by Day 57 cID50 level above a threshold, with reverse cumulative distribution function of Day 57 cID50 level overlaid in green. The gray shaded area is pointwise 95% confidence intervals (CIs). The upper boundary of the green shaded area is the estimate of the reverse cumulative distribution function (CDF) of the marker in baseline SARS-CoV-2 negative per-protocol vaccine recipients. (B) Covariate-adjusted cumulative incidence of COVID-19 by 100 days post Day 57 by Day 57 cID50 level. The dotted lines indicate bootstrap point-wise 95% CIs. (C) Vaccine efficacy by Day 57 cID50 level, estimated using the method of Gilbert, Fong, and Carone.39 The dashed lines indicate bootstrap point-wise 95% CIs. In (B) and (C), covariate adjustment was based on an inverse probability samplingweighted Cox model; the green histograms are an estimate of the density of Day 57 cID50 level in baseline negative per-protocol vaccine recipients. LOD, limit of detection. cID50: ID50 nAb titer calibrated to the WHO International Standard.
Figure 4. (A) Covariate-adjusted cumulative incidence of COVID-19 by 100 days post Day 57 by subgroups defined by Day 57 cID50 level above a threshold, with reverse cumulative distribution function of Day 57 cID50 level overlaid in green. The gray shaded area is pointwise 95% confidence intervals (CIs). The upper boundary of the green shaded area is the estimate of the reverse cumulative distribution function (CDF) of the marker in baseline SARS-CoV-2 negative per-protocol vaccine recipients. (B) Covariate-adjusted cumulative incidence of COVID-19 by 100 days post Day 57 by Day 57 cID50 level. The dotted lines indicate bootstrap point-wise 95% CIs. (C) Vaccine efficacy by Day 57 cID50 level, estimated using the method of Gilbert, Fong, and Carone.39 The dashed lines indicate bootstrap point-wise 95% CIs. In (B) and (C), covariate adjustment was based on an inverse probability samplingweighted Cox model; the green histograms are an estimate of the density of Day 57 cID50 level in baseline negative per-protocol vaccine recipients. LOD, limit of detection. cID50: ID50 nAb titer calibrated to the WHO International Standard.CC BY-NC-ND · PubMed Central

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Research works printed but not linked: 5

  1. Moderna “Moderna Announces TeenCOVE Study of its COVID-19 Vaccine in Adolescents Meets Primary Endpoint and Plans to Submit Data to Regulators in Early June” (press release 25 May 2021); https://investors.modernatx.com/news-releases/news-release-details/moderna-announces-teencove-study-its-covid-19-vaccine.
  2. S. A. Plotkin P. B. Gilbert in Plotkin’s Vaccines S. A. Plotkin W. A. Orenstein P. A. Offit K. M. Edwards Eds. (Elsevier seventh ed. 2018) chap. 3.
  3. Regeneron “Phase 3 Prevention Trial Showed 81% Reduced Risk of Symptomatic SARS-CoV-2 Infections with Subcutaneous Administration of REGEN-COV™ (casirivimab with imdevimab)” (press release 12 April 2021); https://investor.regeneron.com/news-releases/news-release-details/phase-3-prevention-trial-showed-81-reduced-risk-symptomatic-sars.
  4. 10.1016/S0140-6736(21)02046-8 · DOI
  5. P. H. Westfall S. S. Young Resampling-Based Multiple Testing: Examples and Methods for P-Value Adjustment vol. 279 of Wiley Series in Probability and Statistics (Wiley 1993).

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Authors
Gilbert, P. B., Montefiori, D. C., McDermott, A. B., Fong, Y., Benkeser, D., Deng, W., Zhou, H., Houchens, C. R., Martins, K., Jayashankar, L., Castellino, F., Flach, B., Lin, B. C., O’Connell, S., McDanal, C., Eaton, A., Sarzotti-Kelsoe, M., Lu, Y., Yu, C., Borate, B., van der Laan, L. W. P., Hejazi, N. S., Huynh, C., Miller, J., El Sahly, H. M., Baden, L. R., Baron, M., De La Cruz, L., Gay, C., Kalams, S., Kelley, C. F., Andrasik, M. P., Kublin, J. G., Corey, L., Neuzil, K. M., Carpp, L. N., Pajon, R., Follmann, D., Donis, R. O., Koup, R. A., Immune Assays Team§, Moderna, I. T., Coronavirus Vaccine Prevention Network (CoVPN)/Coronavirus Efficacy (COVE) Team§, & United States Government (USG)/CoVPN Biostatistics Team§
Affiliations
  • University of Washington (US)
  • Duke University (US)
  • National Institutes of Health (US)
  • Fred Hutch Cancer Center (US)
  • Emory University (US)
  • Moderna Therapeutics (United States) (US)
  • Biomedical Advanced Research and Development Authority (US)
  • Department of Surgery and Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC, USA.
  • Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
  • Brigham and Women's Hospital (US)
  • Palm Beach Research Center (US)
  • Keystone Vitalink Research, Greenville, SC, USA.
  • University of North Carolina at Chapel Hill (US)
  • Vanderbilt University Medical Center (US)
  • University of Maryland, Baltimore (US)
  • Moderna, Inc., Cambridge, MA, USA.
  • Biomedical Advanced Research and Development Authority, Washington, DC, USA.
Corresponding author
  • Gilbert, Peter B.
  • Montefiori, David C.
  • McDermott, Adrian B.
  • Koup, Richard A.
ORCID
Venue
Science
Publisher
American Association for the Advancement of Science (AAAS)
Published
2022-01-07
Volume
375
Issue
6576
Pages
43-50
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
DOI
10.1126/science.abm3425
PMC
PMC8366808
OpenAlex
W3217661335
Cited by
1,137
References
47
Citations by year
2026: 65 · 2025: 114 · 2024: 197 · 2023: 278 · 2022: 412
FWCI
123.36
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Science (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by-nc-nd)
Funders
  • Wellcome Trust
  • National Institutes of Health (1s10od028685-01, UL1TR002384)
  • National Institute of Allergy and Infectious Diseases (S10AI174104, U01AI068635, UM1AI068614, UM1AI068635, UM1AI148575, UM1AI069476, R37AI054165, UM1AI148684, UM1AI069412)
  • National Center for Advancing Translational Sciences
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
Keywords
mRNA-1273 vaccine, COVID-19 vaccine efficacy, SARS-CoV-2, neutralizing antibodies, binding antibodies, correlates of protection, vaccine immunogenicity, vaccine approval

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