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      Memory B cell responses to Omicron subvariants after SARS-CoV-2 mRNA breakthrough infection in humans

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          Abstract

          Wang et al. analyze memory B cell and antibody responses in SARS-CoV-2 mRNA vaccines to breakthrough infections with Delta or Omicron BA.1 variants. Breakthrough infection after two or three doses of mRNA vaccination was comparable to three doses of vaccination in eliciting broad and potent memory B cells. The findings provide insights on broad and strain-specific memory responses after mRNA vaccination with Wuhan-Hu-1.

          Abstract

          Individuals who receive a third mRNA vaccine dose show enhanced protection against severe COVID-19, but little is known about the impact of breakthrough infections on memory responses. Here, we examine the memory antibodies that develop after a third or fourth antigenic exposure by Delta or Omicron BA.1 infection, respectively. A third exposure to antigen by Delta breakthrough increases the number of memory B cells that produce antibodies with comparable potency and breadth to a third mRNA vaccine dose. A fourth antigenic exposure with Omicron BA.1 infection increased variant-specific plasma antibody and memory B cell responses. However, the fourth exposure did not increase the overall frequency of memory B cells or their general potency or breadth compared to a third mRNA vaccine dose. In conclusion, a third antigenic exposure by Delta infection elicits strain-specific memory responses and increases in the overall potency and breadth of the memory B cells. In contrast, the effects of a fourth antigenic exposure with Omicron BA.1 are limited to increased strain-specific memory with little effect on the potency or breadth of memory B cell antibodies. The results suggest that the effect of strain-specific boosting on memory B cell compartment may be limited.

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          Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals

          Summary Understanding adaptive immunity to SARS-CoV-2 is important for vaccine development, interpreting coronavirus disease 2019 (COVID-19) pathogenesis, and calibration of pandemic control measures. Using HLA class I and II predicted peptide ‘megapools’, circulating SARS-CoV-2−specific CD8+ and CD4+ T cells were identified in ∼70% and 100% of COVID-19 convalescent patients, respectively. CD4+ T cell responses to spike, the main target of most vaccine efforts, were robust and correlated with the magnitude of the anti-SARS-CoV-2 IgG and IgA titers. The M, spike and N proteins each accounted for 11-27% of the total CD4+ response, with additional responses commonly targeting nsp3, nsp4, ORF3a and ORF8, among others. For CD8+ T cells, spike and M were recognized, with at least eight SARS-CoV-2 ORFs targeted. Importantly, we detected SARS-CoV-2−reactive CD4+ T cells in ∼40-60% of unexposed individuals, suggesting cross-reactive T cell recognition between circulating ‘common cold’ coronaviruses and SARS-CoV-2.
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            Convergent Antibody Responses to SARS-CoV-2 in Convalescent Individuals

            During the COVID-19 pandemic, SARS-CoV-2 infected millions of people and claimed hundreds of thousands of lives. Virus entry into cells depends on the receptor binding domain (RBD) of the SARS-CoV-2 spike protein (S). Although there is no vaccine, it is likely that antibodies will be essential for protection. However, little is known about the human antibody response to SARS-CoV-2 1–5 . Here we report on 149 COVID-19 convalescent individuals. Plasmas collected an average of 39 days after the onset of symptoms had variable half-maximal pseudovirus neutralizing titers: less than 1:50 in 33% and below 1:1000 in 79%, while only 1% showed titers >1:5000. Antibody sequencing revealed expanded clones of RBD-specific memory B cells expressing closely related antibodies in different individuals. Despite low plasma titers, antibodies to three distinct epitopes on RBD neutralized at half-maximal inhibitory concentrations (IC50s) as low as single digit ng/mL. Thus, most convalescent plasmas obtained from individuals who recover from COVID-19 do not contain high levels of neutralizing activity. Nevertheless, rare but recurring RBD-specific antibodies with potent antiviral activity were found in all individuals tested, suggesting that a vaccine designed to elicit such antibodies could be broadly effective.
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              Covid-19 Vaccine Effectiveness against the Omicron (B.1.1.529) Variant

              Background A rapid increase in coronavirus disease 2019 (Covid-19) cases due to the omicron (B.1.1.529) variant of severe acute respiratory syndrome coronavirus 2 in highly vaccinated populations has aroused concerns about the effectiveness of current vaccines. Methods We used a test-negative case–control design to estimate vaccine effectiveness against symptomatic disease caused by the omicron and delta (B.1.617.2) variants in England. Vaccine effectiveness was calculated after primary immunization with two doses of BNT162b2 (Pfizer–BioNTech), ChAdOx1 nCoV-19 (AstraZeneca), or mRNA-1273 (Moderna) vaccine and after a booster dose of BNT162b2, ChAdOx1 nCoV-19, or mRNA-1273. Results Between November 27, 2021, and January 12, 2022, a total of 886,774 eligible persons infected with the omicron variant, 204,154 eligible persons infected with the delta variant, and 1,572,621 eligible test-negative controls were identified. At all time points investigated and for all combinations of primary course and booster vaccines, vaccine effectiveness against symptomatic disease was higher for the delta variant than for the omicron variant. No effect against the omicron variant was noted from 20 weeks after two ChAdOx1 nCoV-19 doses, whereas vaccine effectiveness after two BNT162b2 doses was 65.5% (95% confidence interval [CI], 63.9 to 67.0) at 2 to 4 weeks, dropping to 8.8% (95% CI, 7.0 to 10.5) at 25 or more weeks. Among ChAdOx1 nCoV-19 primary course recipients, vaccine effectiveness increased to 62.4% (95% CI, 61.8 to 63.0) at 2 to 4 weeks after a BNT162b2 booster before decreasing to 39.6% (95% CI, 38.0 to 41.1) at 10 or more weeks. Among BNT162b2 primary course recipients, vaccine effectiveness increased to 67.2% (95% CI, 66.5 to 67.8) at 2 to 4 weeks after a BNT162b2 booster before declining to 45.7% (95% CI, 44.7 to 46.7) at 10 or more weeks. Vaccine effectiveness after a ChAdOx1 nCoV-19 primary course increased to 70.1% (95% CI, 69.5 to 70.7) at 2 to 4 weeks after an mRNA-1273 booster and decreased to 60.9% (95% CI, 59.7 to 62.1) at 5 to 9 weeks. After a BNT162b2 primary course, the mRNA-1273 booster increased vaccine effectiveness to 73.9% (95% CI, 73.1 to 74.6) at 2 to 4 weeks; vaccine effectiveness fell to 64.4% (95% CI, 62.6 to 66.1) at 5 to 9 weeks. Conclusions Primary immunization with two doses of ChAdOx1 nCoV-19 or BNT162b2 vaccine provided limited protection against symptomatic disease caused by the omicron variant. A BNT162b2 or mRNA-1273 booster after either the ChAdOx1 nCoV-19 or BNT162b2 primary course substantially increased protection, but that protection waned over time. (Funded by the U.K. Health Security Agency.)
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: Project administrationRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Role: Formal analysisRole: InvestigationRole: ValidationRole: VisualizationRole: Writing - review & editing
                Role: Investigation
                Role: InvestigationRole: Resources
                Role: MethodologyRole: Resources
                Role: InvestigationRole: ResourcesRole: ValidationRole: Visualization
                Role: MethodologyRole: Resources
                Role: Data curationRole: Investigation
                Role: Software
                Role: Visualization
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: Resources
                Role: Resources
                Role: Resources
                Role: ConceptualizationRole: Writing - review & editing
                Role: Project administrationRole: ResourcesRole: SupervisionRole: Validation
                Role: Software
                Role: Resources
                Role: ConceptualizationRole: Data curationRole: ResourcesRole: Writing - original draftRole: Writing - review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing - review & editing
                Role: Formal analysisRole: SupervisionRole: Writing - review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing - original draftRole: Writing - review & editing
                Journal
                J Exp Med
                J Exp Med
                jem
                The Journal of Experimental Medicine
                Rockefeller University Press
                0022-1007
                1540-9538
                05 December 2022
                23 September 2022
                23 September 2022
                : 219
                : 12
                : e20221006
                Affiliations
                [1 ] Laboratory of Molecular Immunology, The Rockefeller University, New York, NY
                [2 ] Laboratory of Retrovirology, The Rockefeller University, New York, NY
                [3 ] Howard Hughes Medical Institute, Chevy Chase, MD
                Author notes
                Correspondence to Michel C. Nussenzweig: nussen@ 123456rockefeller.edu
                Theodora Hatziioannou: thatziio@ 123456rockefeller.edu
                [*]

                Z. Wang, P. Zhou, F. Muecksch, and A. Cho contributed equally to this paper.

                Disclosures: P.D. Bieniasz reported personal fees from Pfizer outside the submitted work. M.C. Nussenzweig reported personal fees from Celldex, Walking Fish, Aerium, Frontier Bio, and Apriori Bio outside the submitted work; in addition, M.C. Nussenzweig had a patent to 63/371,285 pending. No other disclosures were reported.

                Author information
                https://orcid.org/0000-0002-2095-2151
                https://orcid.org/0000-0002-7736-2902
                https://orcid.org/0000-0002-0132-5101
                https://orcid.org/0000-0001-6354-6148
                https://orcid.org/0000-0002-5575-5035
                https://orcid.org/0000-0002-9243-867X
                https://orcid.org/0000-0002-4704-8461
                https://orcid.org/0000-0003-3214-284X
                https://orcid.org/0000-0003-3409-4968
                https://orcid.org/0000-0001-7731-6685
                https://orcid.org/0000-0003-4438-5590
                https://orcid.org/0000-0001-6393-0000
                https://orcid.org/0000-0001-7353-3420
                https://orcid.org/0000-0002-7067-6757
                https://orcid.org/0000-0001-9640-0559
                https://orcid.org/0000-0003-2247-3178
                https://orcid.org/0000-0001-7912-5516
                https://orcid.org/0000-0002-7030-294X
                https://orcid.org/0000-0003-1956-1169
                https://orcid.org/0000-0001-7684-219X
                https://orcid.org/0000-0001-9696-5234
                https://orcid.org/0000-0002-5976-9717
                https://orcid.org/0000-0002-2654-0879
                https://orcid.org/0000-0003-1727-8693
                https://orcid.org/0000-0001-7295-8128
                https://orcid.org/0000-0002-2368-3719
                https://orcid.org/0000-0002-7889-0766
                https://orcid.org/0000-0003-0592-8564
                Article
                jem.20221006
                10.1084/jem.20221006
                9513381
                36149398
                43ca9c83-9631-4f93-b599-37f771e8cfa5
                © 2022 Wang et al.

                This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/).

                History
                : 10 June 2022
                : 02 August 2022
                : 01 September 2022
                Funding
                Funded by: Rockefeller University, DOI http://dx.doi.org/10.13039/100012007;
                Funded by: National Institutes of Health, DOI http://dx.doi.org/10.13039/100000002;
                Award ID: P01-AI138398-S1
                Award ID: 2U19AI111825
                Award ID: R37-AI64003
                Award ID: R01AI78788
                Award ID: P01AI165075
                Funded by: National Center for Advancing Translational Sciences, DOI http://dx.doi.org/10.13039/100006108;
                Award ID: UL1 TR001866
                Funded by: Howard Hughes Medical Institute, DOI http://dx.doi.org/10.13039/100000011;
                Categories
                Article
                Covid-19
                Infectious Disease and Host Defense

                Medicine
                Medicine

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