ABSTRACT
As of November 2021, the viral pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing the coronavirus disease 2019 (COVID-19), has infected more than 250 million individuals worldwide and killed over 5 million people. In addition to known risk groups, also cancer patients are at increased risk for severe disease progression. Therefore, understanding the nature of the accompanying immune response is essential, especially the role of T cells for successful virus defense but also during immunopathology leading to severe disease outcomes. Furthermore, as neutralizing antibodies are reported to decay within months post infection or vaccination or are even absent due to cancer treatment, SARS-CoV-2-specific T cell persistence is discussed as an indicator of long-term protective immunity. Especially, in immunocompromised cancer patients, levels of SARS-CoV-2-specifc antibodies may not be efficiently detected. Therefore, we developed a rapid and easy flow cytometric assay for the analysis of SARS-CoV-2-reactive CD4+ and CD8+ T cells directly from whole blood.
ABSTRACT
Introduction: The emergence of SARS-CoV-2 virus, which causes COVID-19, is a major global health hazard. Therefore, a comprehensive characterization of the humoral and cellular immune responses to this virus is essential to combat the COVID-19 pandemic. Our goal was to develop reliable methods and tools for the analysis of humoral and cellular B- and T- cell responses, which will facilitate scientific research for prediction of disease progression, long-term immunity and will support vaccine development. Methods: Plasma samples and PBMCs of COVID-19 convalescent and healthy donors were obtained. For the detection of SARS-CoV-2 specific antibodies and identification of antigen-specific B cells, we manufactured recombinant mono-biotinylated protein variants of the Spike (S), Receptor Binding Domain (RBD) and Nucleoprotein (N). To identify antigen-reactive T cells, SARS-CoV-2 peptide pools were synthetized for the S, N and Membrane (M) antigens and used for stimulation. The peptide pools consist of mainly 15-mer peptides having an 11-mer amino acid overlap and thereby overspan a whole protein sequence. Results: To determine the presence of SARS-CoV-2 reactive antibodies a flow-based bead assay using recombinant, mono-biotinylated SARS-CoV-2 antigens loaded onto Streptavidin (SAV)-coated-PMMA beads was set up. The beads were incubated with plasma samples and fluorochrome conjugated anti-human isotype specific antibodies for flow cytometric analysis. All the antigens tested were shown to be suitable for the detection of antibodies to SARS-CoV-2 in COVID-19 convalescent plasma. To assess the feasibility of recombinant antigens for the detection and isolation of antigen-specific B cells, the mono-biotinylated Spike and RBD antigens were tetramerized on fluorochrome-conjugated SAV. These tetramers were used for staining, magnetic enrichment and flow cytometric sorting of B cells specific to SARS-CoV-2 antigens. We were able to demonstrate that our recombinant antigens can be used to assess the presence and enable the phenotyping and isolation of rare antigen-specific B cells. For further characterization of the SARS-CoV-2 reactive T cell immunity PBMCs were short term stimulated with the S, M and N peptide pools. After intracellular staining of IFNg, TNFa, IL-2 and CD154, reactive T cells were detected using flow cytometry. We could demonstrate T cell reactivity towards each peptide pool. However, strengths of T cell responses towards the S, M and N peptide pools were heterogeneous between different COVID-19 convalescent individuals. Conclusion: To support and improve current research activities for the identification and characterization of SARS-CoV-2 reactive humoral and cellular B- and T- cell responses, potent tools and assays were developed. Described here research solutions offer the opportunity to successfully address and contribute to the investigation on healthy and dysfunctional immune reactions towards SARS-CoV-2.
ABSTRACT
Background Pharmacologic immunosuppression and incomplete immune reconstitution after allogeneic stem cell transplant (alloSCT) may impair a patient's ability to mount an immune response to vaccines, including currently available COVID-19 vaccines. Since immunocompromised patients are susceptible to severe COVID-19 and likely to respond poorly to vaccination, we sought to characterize SARS-CoV-2 antibody responses after vaccination in alloSCT patients to determine predictors of serologic response, which may inform timing of vaccine administration. Methods This retrospective analysis included adult patients who underwent alloSCT at the University of Pennsylvania between 1/1/2019 and 1/1/2021. Chart review identified patients who had received COVID-19 vaccines and had post-vaccination antibody titers drawn by July 2021 as part of routine care (n=63). Antibodies to SARS-CoV-2 spike protein receptor binding domain were detected using an assay developed at the Hospital of the University of Pennsylvania. Variables analyzed include interval between transplant date and initial vaccination, active GVHD, concurrent immunosuppressive therapy, absolute CD4 count greater than or equal to 200 cells/mm3 peri-vaccination, and total IgG greater than or equal to 400 mg/dL peri-vaccination. Immunosuppressive therapy was defined as tacrolimus, rituximab, ruxolitinib, prednisone 10 mg daily or greater, or extracorporeal photopheresis. Predictors of positive antibody response were assessed using a multivariate, binary logistic regression. Results Median transplant to vaccine interval was 458 days (range 125 to 813) for the 63 vaccinated patients with serologies available. GVHD was present in 23/63 (37%), and 19/63 (30%) were receiving immunosuppressive therapies at the time of vaccination. CD4 count greater than 200 cells/mm3 was observed in 49 patients (78%), and total IgG greater than 400 mg/dL was observed in 51 patients (81%). In total, 50/63 patients (79%) were positive for SARS-CoV-2 IgG antibodies. Positive serologies were observed in 41/49 (84%) with CD4 counts greater than 200 cells/mm3, compared to 9/14 (64%) with CD4 less than 200 cells/mm3. Our model found that peri-vaccination CD4 count greater than 200 cells/mm3 was a significant predictor of positive SARS-CoV-2 IgG serologies in this population (OR 2.14, 97.5% CI = 0.7 to 3.8, p= 0.005). Transplant to vaccine interval, total IgG levels, GVHD status, and immunosuppressive therapies were not significant predictors of serologic response. As of July 2021 no patients had developed COVID-19 after vaccination, regardless of serologic response. Conclusions This retrospective observational study demonstrates that the majority of alloSCT patients vaccinated against COVID-19 within 2 years of transplant, including those with active GVHD and on immunosuppressive therapies, can mount serologic responses. CD4 count greater than 200 cells/mm3 is a significant predictor of positive serologic response, though even among patients with CD4 counts under 200 cells/mm3 over 60% developed SARS-CoV-2 IgG antibodies. Disclosures: Perry: Incyte: Consultancy, Speakers Bureau;Abbvie,: Speakers Bureau;Kadmon: Consultancy. Pratz: University of Pennsylvania: Current Employment;Abbvie: Consultancy, Honoraria, Research Funding;Astellas: Consultancy, Honoraria, Research Funding;Cellgene: Consultancy, Honoraria;Novartis: Consultancy;BMS: Consultancy, Honoraria;Agios: Consultancy;Millenium: Research Funding. Luger: Syros: Honoraria;Agios: Honoraria;Daiichi Sankyo: Honoraria;Jazz Pharmaceuticals: Honoraria;Brystol Myers Squibb: Honoraria;Acceleron: Honoraria;Astellas: Honoraria;Pfizer: Honoraria;Onconova: Research Funding;Celgene: Research Funding;Biosight: Research Funding;Hoffman LaRoche: Research Funding;Kura: Research Funding. Perl: Astellas: Consultancy, Research Funding;Loxo: Consultancy;AbbVie: Consultancy, Research Funding;Syndax: Consultancy;BMS/Celgene: Consultancy;Roche: Consultancy;Fujifilm: Research Funding;Daiichi Sankyo: Consultancy, Research Funding;Forma: Consult ncy;Arog: Research Funding;Genentech: Consultancy;Actinium: Consultancy;Onconova: Consultancy;Sumitomo Dainippon: Consultancy. Porter: ASH: Membership on an entity's Board of Directors or advisory committees;Incyte: Membership on an entity's Board of Directors or advisory committees;DeCart: Membership on an entity's Board of Directors or advisory committees;Genentech: Current equity holder in publicly-traded company, Ended employment in the past 24 months;American Society for Transplantation and Cellular Therapy: Honoraria;Kite/Gilead: Membership on an entity's Board of Directors or advisory committees;Janssen: Membership on an entity's Board of Directors or advisory committees;National Marrow Donor Program: Membership on an entity's Board of Directors or advisory committees;Novartis: Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding;Tmunity: Patents & Royalties;Wiley and Sons Publishing: Honoraria. Hexner: Blueprint medicines: Membership on an entity's Board of Directors or advisory committees, Research Funding;PharmaEssentia: Membership on an entity's Board of Directors or advisory committees;Tmunity Therapeutics: Research Funding. Frey: Sana Biotechnology: Consultancy;Kite Pharma: Consultancy;Syndax Pharmaceuticals: Consultancy;Novartis: Research Funding.
ABSTRACT
Introduction: Viral infections may trigger diabetes. Clinical data suggest infection with the pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing coronavirus disease 2019 (COVID-19), may impact glucose homeostasis in patients. Notably, cases of new-onset diabetes upon SARS-CoV-2 infection have been reported. However, experimental evidence of pancreatic infection is still controversial. Aims & Methods: Here, we employ cadaveric human pancreatic islets, as well as pancreatic tissue from deceased COVID-19 patients to investigate the impact of SARS-CoV-2 on the pancreas. Results: We show that human β-cells express viral entry proteins ACE2 and TMPRSS2, making them susceptible to SARS-CoV-2 infection and replication. Our data further demonstrates that SARS-CoV-2 infects and replicates in ex vivo cultured human islets and infection. This infection is associated with morphological, transcriptional and functional changes, such as reduction of insulin-secretory granules in β-cells and impaired glucose-stimulated insulin secretion. In COVID-19 post-mortem examinations, we detected SARS-CoV-2 nucleocapsid protein in pancreatic exocrine cells, and in cells that stain positive for the β-cell marker NKX6.1 in all patients investigated. Conclusion: Taken together, our data define the human pancreas as a target of SARS-CoV-2 infection and suggest that β-cell infection might contribute to the metabolic dysregulation observed in patients with COVID- 19.
ABSTRACT
The susceptible-infected-recovered (SIR) model is used in epidemiology to simulate the transmission of infectious diseases. The continuous formulation of the SIR model is represented by a set of three coupled differential equations that can be solved numerically. Due to the dynamics of the simulation, the SIR model is best when simulating diseases that confer a lasting immunity. More complex models for disease transmission are typically derived from this base model and can include features such as additional infectious stages, stochastic frameworks, vaccines, and finite immunity. In this case study, I first examine the features of the continuous model. Then, I create a discrete model, which simulates individuals that transmit the disease based on proximity. With this basic framework established, one can examine strategies that change the spread of the infection, such as social distancing.
ABSTRACT
The ongoing COVID-19 pandemic threatens the health of humans, causes great economic losses and may disturb the stability of the societies. Mathematical models can be used to understand aspects of the dynamics of epidemics and to increase the chances of control strategies. We propose a SIR graph network model, in which each node represents an individual and the edges represent contacts between individuals. For this purpose, we use the healthy S (susceptible) population without immune behavior, two I-compartments (infectious) and two R-compartments (recovered) as a SIR model. The time steps can be interpreted as days and the spatial spread (limited in distance for a singe step) shell take place on a 200 by 200 torus, which should simulate 40 thousand individuals. The disease propagation form S to the I-compartment should be possible on a k by k square (k=5 in order to be in small world network) with different time periods and strength of propagation probability in the two I compartments. After the infection, an immunity of different lengths is to be modeled in the two R compartments. The incoming constants should be chosen so that realistic scenarios can arise. With a random distribution and a low case number of diseases at the beginning of the simulation, almost periodic patterns similar to diffusion processes can arise over the years. Mean value operators and the Laplace operator on the torus and its eigenfunctions and eigenvalues are relevant reference points. The torus with five compartments is well suited for visualization. Realistic neighborhood relationships can be viewed with a inhomogeneous graph theoretic approach, but they are more difficult to visualize. Superspreaders naturally arise in inhomogeneous graphs: there are different numbers of edges adjacent to the nodes and should therefore be examined in an inhomogeneous graph theoretical model. The expected effect of corona control strategies can be evaluated by comparing the results with various constants used in simulations. The decisive benefit of the models results from the long-term observation of the consequences of the assumptions made, which can differ significantly from the primarily expected effects, as is already known from classic predator-prey models.