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The global emergence of many severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants jeopardizes the protective antiviral immunity induced after infection or vaccination. To address the public health threat caused by the increasing SARS-CoV-2 genomic diversity, the National Institute of Allergy and Infectious Diseases within the National Institutes of Health established the SARS-CoV-2 Assessment of Viral Evolution (SAVE) programme. This effort was designed to provide a real-time risk assessment of SARS-CoV-2 variants that could potentially affect the transmission, virulence, and resistance to infection- and vaccine-induced immunity. The SAVE programme is a critical data-generating component of the US Government SARS-CoV-2 Interagency Group to assess implications of SARS-CoV-2 variants on diagnostics, vaccines and therapeutics, and for communicating public health risk. Here we describe the coordinated approach used to identify and curate data about emerging variants, their impact on immunity and effects on vaccine protection using animal models. We report the development of reagents, methodologies, models and notable findings facilitated by this collaborative approach and identify future challenges. This programme is a template for the response to rapidly evolving pathogens with pandemic potential by monitoring viral evolution in the human population to identify variants that could reduce the effectiveness of countermeasures.
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COVID-19 , SARS-CoV-2 , Animales , Evolución Biológica , Vacunas contra la COVID-19 , Humanos , National Institute of Allergy and Infectious Diseases (U.S.) , Pandemias/prevención & control , Variantes Farmacogenómicas , SARS-CoV-2/genética , SARS-CoV-2/patogenicidad , Estados Unidos/epidemiología , VirulenciaRESUMEN
Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. The group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.
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COVID-19 , SARS-CoV-2 , Estados Unidos/epidemiología , Humanos , SARS-CoV-2/genética , COVID-19/epidemiología , National Institutes of Health (U.S.)RESUMEN
The increasing use of monoclonal antibodies (mAbs) in biology and medicine necessitates efficient methods for characterizing their binding epitopes. Here, we developed a high-throughput antibody footprinting method based on binding profiles. We used an antigen microarray to profile 23 human anti-influenza hemagglutinin (HA) mAbs using HA proteins of 43 human influenza strains isolated between 1918 and 2018. We showed that the mAb's binding profile can be used to characterize its influenza subtype specificity, binding region, and binding site. We present mAb-Patch-an epitope prediction method that is based on a mAb's binding profile and the 3D structure of its antigen. mAb-Patch was evaluated using four mAbs with known solved mAb-HA structures. mAb-Patch identifies over 67% of the true epitope when considering only 50-60 positions along the antigen. Our work provides proof of concept for utilizing antibody binding profiles to screen large panels of mAbs and to down-select antibodies for further functional studies.
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Gripe Humana , Medicina , Humanos , Anticuerpos Monoclonales , Epítopos , Sitios de UniónRESUMEN
Obesity is a risk factor for severe disease and mortality for both influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. While previous studies show that individuals with obesity generate antibody responses following influenza vaccination, infection rates within the obese group were twice as high as those in the healthy-weight group. The repertoire of antibodies raised against influenza viruses following previous vaccinations and/or natural exposures is referred to here as baseline immune history (BIH). To investigate the hypothesis that obesity impacts immune memory to infections and vaccines, we profiled the BIH of obese and healthy-weight adults vaccinated with the 2010-2011 seasonal influenza vaccine in response to conformational and linear antigens. Despite the extensive heterogeneity of the BIH profiles in both groups, there were striking differences between obese and healthy subjects, especially with regard to A/H1N1 strains and the 2009 pandemic virus (Cal09). Individuals with obesity had lower IgG and IgA magnitude and breadth for a panel of A/H1N1 whole viruses and hemagglutinin proteins from 1933 to 2009 but increased IgG magnitude and breadth for linear peptides from the Cal09 H1 and N1 proteins. Age was also associated with A/H1N1 BIH, with young individuals with obesity being more likely to have reduced A/H1N1 BIH. We found that individuals with low IgG BIH had significantly lower neutralizing antibody titers than individuals with high IgG BIH. Taken together, our findings suggest that increased susceptibility of obese participants to influenza infection may be mediated in part by obesity-associated differences in the memory B-cell repertoire, which cannot be ameliorated by current seasonal vaccination regimens. Overall, these data have vital implications for the next generation of influenza virus and SARS-CoV-2 vaccines. IMPORTANCE Obesity is associated with increased morbidity and mortality from influenza and SARS-CoV-2 infection. While vaccination is the most effective strategy for preventing influenza virus infection, our previous studies showed that influenza vaccines fail to provide optimal protection in obese individuals despite reaching canonical correlates of protection. Here, we show that obesity may impair immune history in humans and cannot be overcome by seasonal vaccination, especially in younger individuals with decreased lifetime exposure to infections and seasonal vaccines. Low baseline immune history is associated with decreased protective antibody responses. Obesity potentially handicaps overall responses to vaccination, biasing it toward responses to linear epitopes, which may reduce protective capacity. Taken together, our data suggest that young obese individuals are at an increased risk of reduced protection by vaccination, likely due to altered immune history biased toward nonprotective antibody responses. Given the worldwide obesity epidemic coupled with seasonal respiratory virus infections and the inevitable next pandemic, it is imperative that we understand and improve vaccine efficacy in this high-risk population. The design, development, and usage of vaccines for and in obese individuals may need critical evaluation, and immune history should be considered an alternate correlate of protection in future vaccine clinical trials.
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COVID-19 , Subtipo H1N1 del Virus de la Influenza A , Vacunas contra la Influenza , Gripe Humana , Adulto , Humanos , Vacunas contra la COVID-19 , SARS-CoV-2 , Gripe Humana/prevención & control , Anticuerpos Antivirales , Obesidad , Inmunoglobulina GRESUMEN
Vaccination, especially with multiple doses, provides substantial population-level protection against COVID-19, but emerging variants of concern (VOC) and waning immunity represent significant risks at the individual level. Here we identify correlates of protection (COP) in a multicenter prospective study following 607 healthy individuals who received three doses of the Pfizer-BNT162b2 vaccine approximately six months prior to enrollment. We compared 242 individuals who received a fourth dose to 365 who did not. Within 90 days of enrollment, 239 individuals contracted COVID-19, 45% of the 3-dose group and 30% of the four-dose group. The fourth dose elicited a significant rise in antibody binding and neutralizing titers against multiple VOCs reducing the risk of symptomatic infection by 37% [95%CI, 15%-54%]. However, a group of individuals, characterized by low baseline titers of binding antibodies, remained susceptible to infection despite significantly increased neutralizing antibody titers upon boosting. A combination of reduced IgG levels to RBD mutants and reduced VOC-recognizing IgA antibodies represented the strongest COP in both the 3-dose group (HR = 6.34, p = 0.008) and four-dose group (HR = 8.14, p = 0.018). We validated our findings in an independent second cohort. In summary combination IgA and IgG baseline binding antibody levels may identify individuals most at risk from future infections.
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Vacunas contra la COVID-19 , COVID-19 , Humanos , Vacuna BNT162 , Estudios Prospectivos , COVID-19/prevención & control , SARS-CoV-2 , Inmunoglobulina A , Inmunoglobulina GRESUMEN
BACKGROUND AND AIMS: Crohn's disease (CD) is a chronic inflammatory bowel disease associated with psychological stress that is regulated primarily by the hypothalamus-pituitary-adrenal (HPA) axis. Here, we determined whether the psychological characteristics of CD patients associate with their inflammatory state, and whether a 3-month trial of cognitive-behavioral and mindfulness-based stress reduction (COBMINDEX) impacts their inflammatory process. METHODS: Circulating inflammatory markers and a wide range of psychological parameters related to stress and well-being were measured in CD patients before and after COBMINDEX. Inflammatory markers in CD patients were also compared to age- and sex-matched healthy controls (HCs). RESULTS: CD patients exhibited increased peripheral low-grade inflammation compared with HCs, demonstrated by interconnected inflammatory modules represented by IL-6, TNFα, IL-17, MCP-1 and IL-18. Notably, higher IL-18 levels correlated with higher score of stress and a lower score of wellbeing in CD patients. COBMINDEX was accompanied by changes in inflammatory markers that coincided with changes in cortisol: changes in serum levels of cortisol correlated positively with those of IL-10 and IFNα and negatively with those of MCP-1. Furthermore, inflammatory markers of CD patients at baseline predicted COBMINDEX efficacy, as higher levels of distinct cytokines and cortisol at baseline, correlated negatively with changes in disease activity (by Harvey-Bradshaw Index) and psychological distress (global severity index measure) following COBMINDEX. CONCLUSION: CD patients have a characteristic immunological profile that correlates with psychological stress, and disease severity. We suggest that COBMINDEX induces stress resilience in CD patients, which impacts their well-being, and their disease-associated inflammatory process.
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T-cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages experimentally inferred antigen-associated TCRs to form meta-clonotypes - groups of biochemically similar TCRs - that can be used to robustly quantify functionally similar TCRs in bulk repertoires across individuals. We apply the framework to TCR data from COVID-19 patients, generating 1831 public TCR meta-clonotypes from the SARS-CoV-2 antigen-associated TCRs that have strong evidence of restriction to patients with a specific human leukocyte antigen (HLA) genotype. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 59.7% (1093/1831) were more abundant among COVID-19 patients that expressed the putative restricting HLA allele (false discovery rate [FDR]<0.01), demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, tcrdist3, that implements this framework and facilitates flexible workflows for distance-based TCR repertoire analysis.
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Antígenos Virales/genética , COVID-19/inmunología , Antígenos HLA/genética , Receptores de Antígenos de Linfocitos T/genética , SARS-CoV-2/inmunología , Antígenos Virales/inmunología , Biomarcadores , COVID-19/genética , Regiones Determinantes de Complementariedad/inmunología , Biología Computacional/métodos , Epítopos/genética , Epítopos/inmunología , Genotipo , Antígenos HLA/inmunología , Humanos , Receptores de Antígenos de Linfocitos T/inmunologíaRESUMEN
As highlighted by the ongoing COVID-19 pandemic, vaccination is critical for infectious disease prevention and control. Obesity is associated with increased morbidity and mortality from respiratory virus infections. While obese individuals respond to influenza vaccination, what is considered a seroprotective response may not fully protect the global obese population. In a cohort vaccinated with the 2010-2011 trivalent inactivated influenza vaccine, baseline immune history and vaccination responses were found to significantly differ in obese individuals compared to healthy controls, especially towards the 2009 pandemic strain of A/H1N1 influenza virus. Young, obese individuals displayed responses skewed towards linear peptides versus conformational antigens, suggesting aberrant obese immune response. Overall, these data have vital implications for the next generation of influenza vaccines, and towards the current SARS-CoV-2 vaccination campaign.
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As the mechanistic basis of adaptive cellular antigen recognition, T cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages antigen-enriched repertoires to form meta-clonotypes - groups of biochemically similar TCRs - that can be used to robustly identify and quantify functionally similar TCRs in bulk repertoires. We apply the framework to TCR data from COVID-19 patients, generating 1831 public TCR meta-clonotypes from the 17 SARS-CoV-2 antigen-enriched repertoires with the strongest evidence of HLA-restriction. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 59.7% (1093/1831) were more abundant among COVID-19 patients that expressed the putative restricting HLA allele (FDR < 0.01), demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, tcrdist3, that implements this framework and facilitates flexible workflows for distance-based TCR repertoire analysis.