Biology subjects

Szebeni, J.

Publications and source records attributed to Szebeni, J..

4 recordsLinked to original sources

bioRxiv2023

The COVID-19 mRNA vaccine Comirnaty induces anaphylactic shock in an anti-PEG hyperimmune large animal model: Role of complement in cardiovascular, hematological, and inflammatory mediator changes

BackgroundComirnaty, Pfizer-BioNTechs polyethylene-glycol (PEG)-containing Covid-19 vaccine, can cause hypersensitivity reactions (HSRs) in a small fraction of immunized people which can, very rarely, culminate in life-threatening anaphylaxis. A role of anti-PEG antibodies (Abs) has been proposed, but causality has not yet been proven in an animal model. This study aimed to provide such evidence using anti-PEG hyperimmune pigs (i.e., pigs displaying very high levels of anti-PEG Abs). We also sought to find evidence for the role of complement (C) activation and thromboxane A2 (TXA2) release in blood as contributing effects to anaphylaxis. MethodsPigs (n=6) were immunized with 0.1 mg/kg PEGylated liposome (Doxebo) i.v. the rise of anti-PEG IgG and IgM was measured in serial blood samples with ELISA. After 2-3 weeks, during the height of seroconversion, the animals were injected i.v. with 1/3 human vaccine dose (HVD) of Comirnaty, and the hemodynamic (PAP, SAP), cardiopulmonary (HR, EtCO2,), hematological parameters (WBC, granulocyte, lymphocyte, and platelet counts) and blood immune mediators (anti-PEG IgM and IgG Abs, C3a and TXA2) were measured as endpoints of HSRs. ResultsA week after immunization of 6 pigs with Doxebo, the level of anti-PEG IgM and IgG rose 5-10-thousands-fold in all animals, and they all developed anaphylactic shock to i.v. injection of 1/3 HVD of Comirnaty. The reaction, starting within 1 min, led to the abrupt decline of SAP along with maximal pulmonary hypertension, decreased pulse pressure amplitude, tachycardia, granulo- and thrombocytopenia, and paralleling rises of plasma C3a and TXB2 levels. These vaccine effects were not observed in non-immunized pigs. ConclusionsConsistent with previous studies with PEGylated nano-liposomes, these data show a causal role of anti-PEG Abs in the anaphylaxis to Comirnaty. The reaction involves C activation, and, hence, it represents C activation-related pseudo-allergy (CARPA). The setup provides the first large-animal model for mRNA-vaccine-induced anaphylaxis in humans.

pharmacology and toxicology↗

bioRxiv2022

New insights into the structure of Comirnaty Covid-19 vaccine: A theory on soft nanoparticles with mRNA-lipid supercoils stabilized by hydrogen bonds

Despite the worldwide success of mRNA-LNP Covid-19 vaccines, the nanoscale structure of these formulations is still poorly understood. To fill this gap, we used a combination of atomic force microscopy (AFM), dynamic light scattering (DLS), transmission electron microscopy (TEM), cryogenic transmission electron microscopy (cryo-TEM) and the determination of LNP pH gradient to analyze the nanoparticles (NPs) in BNT162b2 (Comirnaty), comparing it with the well characterized pegylated liposomal doxorubicin (Doxil). Comirnaty NPs had similar size to Doxil, however, unlike Doxil liposomes, wherein the stable ammonium and pH gradient enables accumulation of 14C-methylamine in the intraliposomal aqueous phase, Comirnaty LNPs lack such pH gradient in spite of the fact that the pH 4, at which LNPs are prepared, is raised to pH 7.2 after loading of the mRNA. Mechanical manipulation of Comirnaty NPs with AFM revealed soft, compliant structures. The sawtooth-like force transitions seen during cantilever retraction implies that molecular strands, corresponding to mRNA, can be pulled out of NPs, and the process is accompanied by stepwise rupture of mRNA-lipid bonds. Unlike Doxil, cryo-TEM of Comirnaty NPs revealed a granular, solid core enclosed by mono- and bilayers. Negative staining TEM shows 2-5 nm electron-dense spots in the liposoms interior that are aligned into strings, semicircles, or labyrinth-like networks, which may imply crosslink-stabilized supercoils. The neutral intra-LNP core questions the dominance of ionic interactions holding together this scaffold, raising the alternative possibility of hydrogen bonding between the mRNA and the lipids. Such interaction, described previously for another mRNA/lipid complex, is consistent with the steric structure of ionizable lipid in Comirnaty, ALC-0315, displaying free =O and -OH groups. It is hypothesized that the latter groups can get into steric positions that enable hydrogen bonding with the nitrogenous bases in the mRNA. These newly recognized structural features of mRNA-LNP may be important for the vaccines efficacy.

immunology↗

bioRxiv2022

Zymosan-induced leukocyte and cytokine changes in pigs: a new model for streamlined drug testing against severe COVID-19

Injection of 0.1 mg/kg zymosan in pigs i.v. elicited transient hemodynamic disturbance within minutes, without major blood cell changes. In contrast, infusion of 1 mg/kg zymosan triggered maximal pulmonary hypertension with tachycardia, lasting for 30 min. This change was followed by a transient granulopenia with a trough at 1 h, and then, up to about 6 h, a major granulocytosis, resulting in a 3-4-fold increase of neutrophil-to-lymphocyte ratio (NLR). In parallel with the changes in WBC differential, qRT-PCR and ELISA analyses showed increased transcription and/or release of inflammatory cytokines and chemokines into blood, including IL-6, TNF-, CCL-2, CXCL-10, and IL-1RA. The expression of IL-6 peaked at already 1.5-2.5 h, and we observed significant correlation between lymphopenia and IL-6 gene expression. While these changes are consistent with zymosans known stimulatory effect on both the humoral and cellular arms of the innate immune system, what gives novel clinical relevance to the co-manifestation of above hemodynamic, hematological, and immune changes is that they represent independent bad prognostic indicators in terminal COVID-19 and other diseases involving cytokine storm. Thus, within a 6 h experiment, the model enables consecutive reproduction of a symptom triad that is characteristic of late-stage COVID-19. Given the limitations of modeling cytokine storm in animals and effectively treating severe COVID-19, the presented relatively simple large animal model may advance the R&D of drugs against these conditions. One of these disease markers (NLR), obtained from a routine laboratory endpoint (WBC differential), may also enable streamlining the model for high throughput drug screening against innate immune overstimulation.

immunology↗

bioRxiv2021

COVIDOUTCOME - Estimating COVID Severity Based on Mutation Signatures in the SARS-CoV-2 Genome

IntroductionNumerous studies demonstrate frequent mutations in the genome of SARS-CoV-2. Our goal was to statistically link mutations to severe disease outcome. MethodsWe used an automated machine learning approach where 1,594 viral genomes with available clinical follow-up data were used as the training set (797 "severe" and 797 "mild"). The best algorithm, based on random forest classification combined with the LASSO feature selection algorithm was employed to the training set to link mutation signatures and outcome. The performance of the final model was estimated by repeated, stratified, 10-fold cross validation (CV), then adjusted for multiple testing with Bootstrap Bias Corrected CV. ResultsWe identified 26 protein and UTR mutations significantly linked to severe outcome. The best classification algorithm uses a mutation signature of 22 mutations as well as the patients age as the input and shows high classification efficiency with an AUC of 0.94 (CI: [0.912, 0.962]) and a prediction accuracy of 87% (CI: [0.830, 0.903]). Finally, we established an online platform (https://covidoutcome.com/) which is capable to use a viral sequence and the patients age as the input and provides a percentage estimation of disease severity. DiscussionWe demonstrate a statistical association between mutation signatures of SARS-CoV-2 and severe outcome of COVID-19. The established analysis platform enables a real-time analysis of new viral genomes. KEY MESSAGESO_LIA statistical link between SARS-Cov-2 mutation status and severe COVID outcome was established using automated machine learning techniques based on random forest and logistic regression combined with feature selection algorithms. C_LIO_LIA mutation signature based on 3,779 protein coding and 36 UTR mutations capable to identify severe outcome cases was established. C_LIO_LIThe trained model showed high classification performance (AUC=0.94 (CI: [0.912, 0.962]), accuracy=0.87 (CI: [0.830, 0.903])). C_LIO_LIA registration-free web-server for automated classification of new samples was set up and is accessible at http://www.covidoutcome.com. C_LIO_LIThe established pipeline provides a quick assessment of future patients warranting a prospective clinical validation. C_LI

bioinformatics↗