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      Waning cellular immune responses and predictive factors in maintaining cellular immunity against SARS-CoV-2 six months after BNT162b2 mRNA vaccination

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          Abstract

          Several clinical trials have shown that the humoral response produced by anti-spike antibodies elicited by coronavirus disease 2019 (COVID-19) vaccines gradually declines. The kinetics, durability and influence of epidemiological and clinical factors on cellular immunity have not been fully elucidated. We analyzed cellular immune responses elicited by BNT162b2 mRNA vaccines in 321 health care workers using whole blood interferon-gamma (IFN-γ) release assays. IFN-γ, induced by CD4 + and CD8 + T cells stimulated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike epitopes (Ag2), levels were highest at 3 weeks after the second vaccination (6 W) and decreased by 37.4% at 3 months (4 M) and 60.0% at 6 months (7 M), the decline of which seemed slower than that of anti-spike antibody levels. Multiple regression analysis revealed that the levels of IFN-γ induced by Ag2 at 7 M were significantly correlated with age, dyslipidemia, focal adverse reactions to full vaccination, lymphocyte and monocyte counts in whole blood, Ag2 levels before the second vaccination, and Ag2 levels at 6 W. We clarified the dynamics and predictive factors for the long-lasting effects of cellular immune responses. The results emphasize the need for a booster vaccine from the perspective of SARS-CoV-2 vaccine-elicited cellular immunity.

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          Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine

          Fernando P Polack, Stephen J. Thomas, Nicholas R.E. Kitchin … (2023)
          Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the resulting coronavirus disease 2019 (Covid-19) have afflicted tens of millions of people in a worldwide pandemic. Safe and effective vaccines are needed urgently. Methods In an ongoing multinational, placebo-controlled, observer-blinded, pivotal efficacy trial, we randomly assigned persons 16 years of age or older in a 1:1 ratio to receive two doses, 21 days apart, of either placebo or the BNT162b2 vaccine candidate (30 μg per dose). BNT162b2 is a lipid nanoparticle–formulated, nucleoside-modified RNA vaccine that encodes a prefusion stabilized, membrane-anchored SARS-CoV-2 full-length spike protein. The primary end points were efficacy of the vaccine against laboratory-confirmed Covid-19 and safety. Results A total of 43,548 participants underwent randomization, of whom 43,448 received injections: 21,720 with BNT162b2 and 21,728 with placebo. There were 8 cases of Covid-19 with onset at least 7 days after the second dose among participants assigned to receive BNT162b2 and 162 cases among those assigned to placebo; BNT162b2 was 95% effective in preventing Covid-19 (95% credible interval, 90.3 to 97.6). Similar vaccine efficacy (generally 90 to 100%) was observed across subgroups defined by age, sex, race, ethnicity, baseline body-mass index, and the presence of coexisting conditions. Among 10 cases of severe Covid-19 with onset after the first dose, 9 occurred in placebo recipients and 1 in a BNT162b2 recipient. The safety profile of BNT162b2 was characterized by short-term, mild-to-moderate pain at the injection site, fatigue, and headache. The incidence of serious adverse events was low and was similar in the vaccine and placebo groups. Conclusions A two-dose regimen of BNT162b2 conferred 95% protection against Covid-19 in persons 16 years of age or older. Safety over a median of 2 months was similar to that of other viral vaccines. (Funded by BioNTech and Pfizer; ClinicalTrials.gov number, NCT04368728.)
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            Welcome to the Tidyverse

            Hadley Wickham, Mara Averick, Jennifer Bryan … (2019)
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              Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection

              David Khoury, Deborah Cromer, Arnold Reynaldi … (2021)
              Predictive models of immune protection from COVID-19 are urgently needed to identify correlates of protection to assist in the future deployment of vaccines. To address this, we analyzed the relationship between in vitro neutralization levels and the observed protection from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using data from seven current vaccines and from convalescent cohorts. We estimated the neutralization level for 50% protection against detectable SARS-CoV-2 infection to be 20.2% of the mean convalescent level (95% confidence interval (CI) = 14.4-28.4%). The estimated neutralization level required for 50% protection from severe infection was significantly lower (3% of the mean convalescent level; 95% CI = 0.7-13%, P = 0.0004). Modeling of the decay of the neutralization titer over the first 250 d after immunization predicts that a significant loss in protection from SARS-CoV-2 infection will occur, although protection from severe disease should be largely retained. Neutralization titers against some SARS-CoV-2 variants of concern are reduced compared with the vaccine strain, and our model predicts the relationship between neutralization and efficacy against viral variants. Here, we show that neutralization level is highly predictive of immune protection, and provide an evidence-based model of SARS-CoV-2 immune protection that will assist in developing vaccine strategies to control the future trajectory of the pandemic.
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                Author and article information

                Contributors
                Takashi Ishii: taishii-tky@umin.ac.jp
                Shintaro Yanagimoto: yanagimoto@hc.u-tokyo.ac.jp
                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 13 June 2023
                Publication date PMC-release: 13 June 2023
                Publication date Collection: 2023
                Volume: 13
                Electronic Location Identifier: 9607
                Affiliations
                [1 ]GRID grid.26999.3d, ISNI 0000 0001 2151 536X, Division for Health Service Promotion, , The University of Tokyo, ; Hongo 7-3-1, Bunkyo, TokyoTokyo, 113-8655 Japan
                [2 ]GRID grid.412708.8, ISNI 0000 0004 1764 7572, Department of Infectious Diseases, , The University of Tokyo Hospital, ; Tokyo, Japan
                [3 ]GRID grid.412708.8, ISNI 0000 0004 1764 7572, Department of Infection Control and Prevention, , The University of Tokyo Hospital, ; Tokyo, Japan
                Article
                Publisher ID: 36397
                DOI: 10.1038/s41598-023-36397-6
                PMC ID: 10263378
                PubMed ID: 37311763
                SO-VID: 9bcf763c-d99a-4ddc-b4c2-ca99d8001a52
                Copyright © © The Author(s) 2023
                License:

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 1 February 2023
                Date accepted : 2 June 2023
                Categories
                Subject: Article
                Custom metadata
                issue-copyright-statement © Springer Nature Limited 2023

                ScienceOpen disciplines: Uncategorized
                Keywords: immunology,medical research
                Data availability:
                ScienceOpen disciplines: Uncategorized
                Keywords: immunology, medical research

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