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Four SARS-CoV-2 vaccines induce quantitatively different antibody responses against SARS-CoV-2 variants (preprint)
medrxiv; 2021.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2021.09.27.21264163
ABSTRACT
BackgroundEmerging and future SARS-CoV-2 variants may jeopardize the effectiveness of vaccination campaigns. Therefore, it is important to know how the different vaccines perform against diverse SARS-CoV-2 variants. MethodsIn a prospective cohort of 165 SARS-CoV-2 naive health care workers, vaccinated with either one of four vaccines (BNT162b2, mRNA-1273, AZD1222 or Ad26.COV2.S), we performed a head-to-head comparison of the ability of sera to recognize and neutralize SARS-CoV-2 variants of concern (VOCs; Alpha, Beta, Gamma, Delta and Omicron). Repeated serum sampling was performed 5 times during a year (from January 2021 till January 2022), including before and after booster vaccination with BNT162b2. FindingsFour weeks after completing the initial vaccination series, SARS-CoV-2 wild-type neutralizing antibody titers were highest in recipients of BNT162b2 and mRNA-1273 (geometric mean titers (GMT) of 197 [95% CI 149-260] and 313 [95% CI 218-448], respectively), and substantially lower in those vaccinated with the adenovirus vector-based vaccines AZD1222 and Ad26.COV2.S (GMT of 26 [95% CI 18-37] and 14 [95% CI 8-25] IU/ml, respectively). These findings were robust for adjustment to age and sex. VOCs neutralization was reduced in all vaccine groups, with the largest (9- to 80-fold) reduction in neutralization observed against the Omicron variant. The booster BNT162b2 vaccination increased neutralizing antibody titers for all groups with substantial improvement against the VOCs including the Omicron variant. Study limitations include the lack of cellular immunity data. ConclusionsOverall, this study shows that the mRNA vaccines appear superior to adenovirus vector-based vaccines in inducing neutralizing antibodies against VOCs four weeks after initial vaccination and after booster vaccination.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Language:
English
Year:
2021
Document Type:
Preprint
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