Comparing antibody assays as correlates of protection against COVID-19 in the COVE mRNA-1273 vaccine efficacy trial
The best assay or marker to define mRNA-1273 vaccine-induced antibodies as a correlate of protection (CoP) is unclear. In the COVE trial, participants received two doses of the mRNA-1273 COVID-19 vaccine or placebo. We previously assessed IgG binding antibodies to the spike protein (spike IgG) or receptor binding domain (RBD IgG) and pseudovirus neutralizing antibody 50 or 80% inhibitory dilution titer measured on day 29 or day 57, as correlates of risk (CoRs) and CoPs against symptomatic COVID-19 over 4 months after dose. Here, we assessed a new marker, live virus 50% microneutralization titer (LV-MN50), and compared and combined markers in multivariable analyses. LV-MN50 was an inverse CoR, with a hazard ratio of 0.39 (95% confidence interval, 0.19 to 0.83) at day 29 and 0.51 (95% confidence interval, 0.25 to 1.04) at day 57 per 10-fold increase. In multivariable analyses, pseudovirus neutralization titers and anti-spike binding antibodies performed best as CoRs; combining antibody markers did not improve correlates. Pseudovirus neutralization titer was the strongest independent correlate in a multivariable model. Overall, these results supported pseudovirus neutralizing and binding antibody assays as CoRs and CoPs, with the live virus assay as a weaker correlate in this sample set. Day 29 markers performed as well as day 57 markers as CoPs, which could accelerate immunogenicity and immunobridging studies.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
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| Enthalten in: |
Science translational medicine - 15(2023), 692 vom: 19. Apr., Seite eade9078 |
| Sprache: |
Englisch |
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| Links: |
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| Anmerkungen: |
Date Completed 21.04.2023 Date Revised 30.09.2023 published: Print-Electronic ClinicalTrials.gov: NCT04470427 Citation Status MEDLINE |
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| doi: |
10.1126/scitranslmed.ade9078 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM355789698 |
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| 041 | |a eng | ||
| 100 | 1 | |a Benkeser, David |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Comparing antibody assays as correlates of protection against COVID-19 in the COVE mRNA-1273 vaccine efficacy trial |
| 264 | 1 | |c 2023 | |
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| 500 | |a Date Completed 21.04.2023 | ||
| 500 | |a Date Revised 30.09.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a ClinicalTrials.gov: NCT04470427 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a The best assay or marker to define mRNA-1273 vaccine-induced antibodies as a correlate of protection (CoP) is unclear. In the COVE trial, participants received two doses of the mRNA-1273 COVID-19 vaccine or placebo. We previously assessed IgG binding antibodies to the spike protein (spike IgG) or receptor binding domain (RBD IgG) and pseudovirus neutralizing antibody 50 or 80% inhibitory dilution titer measured on day 29 or day 57, as correlates of risk (CoRs) and CoPs against symptomatic COVID-19 over 4 months after dose. Here, we assessed a new marker, live virus 50% microneutralization titer (LV-MN50), and compared and combined markers in multivariable analyses. LV-MN50 was an inverse CoR, with a hazard ratio of 0.39 (95% confidence interval, 0.19 to 0.83) at day 29 and 0.51 (95% confidence interval, 0.25 to 1.04) at day 57 per 10-fold increase. In multivariable analyses, pseudovirus neutralization titers and anti-spike binding antibodies performed best as CoRs; combining antibody markers did not improve correlates. Pseudovirus neutralization titer was the strongest independent correlate in a multivariable model. Overall, these results supported pseudovirus neutralizing and binding antibody assays as CoRs and CoPs, with the live virus assay as a weaker correlate in this sample set. Day 29 markers performed as well as day 57 markers as CoPs, which could accelerate immunogenicity and immunobridging studies | ||
| 650 | 4 | |a Randomized Controlled Trial | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, U.S. Gov't, Non-P.H.S. | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 7 | |a 2019-nCoV Vaccine mRNA-1273 |2 NLM | |
| 650 | 7 | |a EPK39PL4R4 |2 NLM | |
| 650 | 7 | |a Antibodies, Neutralizing |2 NLM | |
| 650 | 7 | |a Immunoglobulin G |2 NLM | |
| 650 | 7 | |a Antibodies, Viral |2 NLM | |
| 700 | 1 | |a Montefiori, David C |e verfasserin |4 aut | |
| 700 | 1 | |a McDermott, Adrian B |e verfasserin |4 aut | |
| 700 | 1 | |a Fong, Youyi |e verfasserin |4 aut | |
| 700 | 1 | |a Janes, Holly E |e verfasserin |4 aut | |
| 700 | 1 | |a Deng, Weiping |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Honghong |e verfasserin |4 aut | |
| 700 | 1 | |a Houchens, Christopher R |e verfasserin |4 aut | |
| 700 | 1 | |a Martins, Karen |e verfasserin |4 aut | |
| 700 | 1 | |a Jayashankar, Lakshmi |e verfasserin |4 aut | |
| 700 | 1 | |a Castellino, Flora |e verfasserin |4 aut | |
| 700 | 1 | |a Flach, Britta |e verfasserin |4 aut | |
| 700 | 1 | |a Lin, Bob C |e verfasserin |4 aut | |
| 700 | 1 | |a O'Connell, Sarah |e verfasserin |4 aut | |
| 700 | 1 | |a McDanal, Charlene |e verfasserin |4 aut | |
| 700 | 1 | |a Eaton, Amanda |e verfasserin |4 aut | |
| 700 | 1 | |a Sarzotti-Kelsoe, Marcella |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Yiwen |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Chenchen |e verfasserin |4 aut | |
| 700 | 1 | |a Borate, Bhavesh |e verfasserin |4 aut | |
| 700 | 1 | |a van der Laan, Lars W P |e verfasserin |4 aut | |
| 700 | 1 | |a Hejazi, Nima S |e verfasserin |4 aut | |
| 700 | 1 | |a Kenny, Avi |e verfasserin |4 aut | |
| 700 | 1 | |a Carone, Marco |e verfasserin |4 aut | |
| 700 | 1 | |a Williamson, Brian D |e verfasserin |4 aut | |
| 700 | 1 | |a Garver, Jennifer |e verfasserin |4 aut | |
| 700 | 1 | |a Altonen, Erin |e verfasserin |4 aut | |
| 700 | 1 | |a Rudge, Thomas |e verfasserin |4 aut | |
| 700 | 1 | |a Huynh, Chuong |e verfasserin |4 aut | |
| 700 | 1 | |a Miller, Jacqueline |e verfasserin |4 aut | |
| 700 | 1 | |a El Sahly, Hana M |e verfasserin |4 aut | |
| 700 | 1 | |a Baden, Lindsey R |e verfasserin |4 aut | |
| 700 | 1 | |a Frey, Sharon |e verfasserin |4 aut | |
| 700 | 1 | |a Malkin, Elissa |e verfasserin |4 aut | |
| 700 | 1 | |a Spector, Stephen A |e verfasserin |4 aut | |
| 700 | 1 | |a Andrasik, Michele P |e verfasserin |4 aut | |
| 700 | 1 | |a Kublin, James G |e verfasserin |4 aut | |
| 700 | 1 | |a Corey, Lawrence |e verfasserin |4 aut | |
| 700 | 1 | |a Neuzil, Kathleen M |e verfasserin |4 aut | |
| 700 | 1 | |a Carpp, Lindsay N |e verfasserin |4 aut | |
| 700 | 1 | |a Pajon, Rolando |e verfasserin |4 aut | |
| 700 | 1 | |a Follmann, Dean |e verfasserin |4 aut | |
| 700 | 1 | |a Donis, Ruben O |e verfasserin |4 aut | |
| 700 | 1 | |a Koup, Richard A |e verfasserin |4 aut | |
| 700 | 1 | |a Gilbert, Peter B |e verfasserin |4 aut | |
| 700 | 0 | |a Immune Assays |e verfasserin |4 aut | |
| 700 | 0 | |a Moderna Inc. |e verfasserin |4 aut | |
| 700 | 0 | |a Coronavirus Vaccine Prevention Network (CoVPN)/Coronavirus Efficacy (COVE) |e verfasserin |4 aut | |
| 700 | 0 | |a United States Government (USG)/CoVPN Biostatistics Teams |e verfasserin |4 aut | |
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