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Systematic review of primary and booster COVID-19 sera neutralizing ability against SARS-CoV-2 omicron variant.

ABSTRACT: Virus neutralization data using post-vaccination sera are an important tool in informing vaccine use policy decisions, however, they often pose interpretive challenges. We systematically reviewed the pre-print and published literature for neutralization studies against Omicron using sera collected after both primary and booster vaccination. We found a high proportion of post-primary vaccination sera were not responding against Omicron but boosting increased both neutralizing activity and percent of responding sera. We recommend reporting percent of responders alongside neutralization data to portray vaccine neutralization ability more accurately.

SUBMITTER: Sitaras I

PROVIDER: S-EPMC9665011 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Systematic review of primary and booster COVID-19 sera neutralizing ability against SARS-CoV-2 omicron variant.

Sitaras Ioannis I Jacobsen Henning H Higdon Melissa M MM Dowling William E WE Bar-Zeev Naor N Deloria Knoll Maria M

NPJ vaccines 20221115 1

Virus neutralization data using post-vaccination sera are an important tool in informing vaccine use policy decisions, however, they often pose interpretive challenges. We systematically reviewed the pre-print and published literature for neutralization studies against Omicron using sera collected after both primary and booster vaccination. We found a high proportion of post-primary vaccination sera were not responding against Omicron but boosting increased both neutralizing activity and percent ...[more]

PMID: 36379935

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Project description:Mucosal immunity plays a pivotal role in providing comprehensive protection against upper-airway infections and effectively limiting the shedding and transmission of SARS-CoV-2. Despite its critical importance, there remains a notable absence of nasal spray vaccines endorsed for global use by the World Health Organization. This could be due to the inability of current intranasal vaccines to induce strong mucosal and systemic responses in humans, thus urgently entailing a next-generation of intranasal COVID-19 vaccines with novel and safe technologies. In this study, we prepared a two-component intranasal vaccine that combines adenovirus vectors with a self-assembled subunit protein. Specifically, the adenovirus vector expresses the spike protein of XBB.1.5 variant (Ad5XBB.1.5), and were mixed with the recombinant protein that developed derived from the receptor binding domain (RBD) of XBB.1.5 (RBDXBB.1.5-HR). Combination of Ad5XBB.1.5 and RBDXBB.1.5-HR elicited superior humoral and cellular immunity against XBB.1.5-included variants compared with the individual components. Importantly, the STING signaling pathway was found to be crucial for the adjuvant effect of the adenovirus vector. In addition, to increase the broad-spectrum neutralizing capacities, a trimeric protein derived from the BA.5 variant (RBDBA.5-HR) was incorporated to formulate a three-component vaccine (Ad5XBB.1.5+RBDXBB.1.5-HR+RBDBA.5-HR), indicating the utilization of a combination of an adenovirus-vectored and subunit protein vaccines has the potential to serve as a next-generation intranasal vaccine platform. Of note, intranasally delivery of two-component vaccine provided protective immunity against live Omicron XBB.1.16 virus challenge in mice. Furthermore, the combination of adenovirus and subunit protein vaccine demonstrates excellent tolerability and safety in human subjects, and is able to induce enhanced mucosal immunity as well as high levels of sera neutralizing antibody in all participants. These findings underscore its suitability for clinical application in the prevention of SARS-CoV-2 variants encompassing XBB lineages.

Dataset Information

Systematic review of primary and booster COVID-19 sera neutralizing ability against SARS-CoV-2 omicron variant.

Publications

Systematic review of primary and booster COVID-19 sera neutralizing ability against SARS-CoV-2 omicron variant.

Similar Datasets

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