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Review of "Distinct Immune Signatures Discriminate SARS-CoV-2 Vaccine Combinations"

Reviewer: Z Hu (Fudan University) | 📗📗📗📗◻️

Published onOct 29, 2022
Review of "Distinct Immune Signatures Discriminate SARS-CoV-2 Vaccine Combinations"
key-enterThis Pub is a Review of
Distinct immune signatures discriminate SARS-CoV-2 vaccine combinations
Description

AbstractSeveral vaccines have been found effective against COVID-19, usually administered in homologous regimens, with the same vaccine used for the prime and boost doses. However, recent studies have demonstrated improved protection via heterologous mix-and-match COVID-19 vaccine combinations, and a direct comparison among these regimens is needed to identify the best employment strategies. Here, we show a single-cohort comparison of changes to the humoral and cellular immune compartments following five different COVID-19 vaccines spanning three technologies (adenoviral, mRNA and inactivated vaccines). These vaccines were administered in a combinatorial fashion, resulting in sixteen different homologous and heterologous regimens. SARS-CoV-2-targeting antibody titres were highest when the boost dose consisted of mRNA-1273, independent of the vaccine used for priming. Priming with BBIBP-CorV induced less class-switching among spike-binding memory B cells and the highest antigen-specific T cell responses in heterologous combinations. These were generally more immunogenic in terms of specific antibodies and cellular responses compared to homologous regimens. Finally, single-cell analysis of 754 samples revealed specific B and T cell signatures of the vaccination regimens, indicating distinctive differences in the immune responses. These data provide new insights on the immunological effects of COVID-19 vaccine combinations and a framework for the design of improved vaccination strategies for other pathogens and cancer.

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Reviewer (Zhidong H…) | 📗📗📗📗◻️

RR:C19 Strength of Evidence Scale Key

📕 ◻️◻️◻️◻️ = Misleading

📙📙 ◻️◻️◻️ = Not Informative

📒📒📒 ◻️◻️ = Potentially Informative

📗📗📗📗◻️ = Reliable

📘📘📘📘📘 = Strong

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