31 March, 2023

Using the precaution adoption process model to understand decision-making about the COVID-19 booster vaccine in England -

Background: COVID-19 continues to pose a threat to public health. Booster vaccine programmes are critical to achieve population-level immunity. Stage theory models of health behaviour can help our understanding of vaccine decision-making in the context of perceived threats of COVID-19. Purpose: To use the Precaution Adoption Process Model (PAPM) to understand decision-making about the COVID-19 booster vaccine (CBV) in England. Methods: An online, cross-sectional survey informed by the PAPM, the extended Theory of Planned Behaviour and Health Belief Model administered to people over the age of 50 residing in England, UK in October 2021. A multivariate, multinomial logistic regression model was used to examine associations with the different stages of CBV decision-making. Results: Of the total 2,004 participants: 135 (6.7%) were unengaged with the CBV programme; 262 (13.1%) were undecided as to whether to have a CBV; 31 (1.5%) had decided not to have a CBV; 1,415 (70.6%) had decided to have a CBV; and 161 (8.0%) had already had their CBV. Being unengaged was positively associated with beliefs in their immune system to protect against COVID-19, being employed, and low household income; and negatively associated with CBV knowledge, a positive COVID-19 vaccine experience, subjective norms, anticipated regret of not having a CBV, and higher academic qualifications. Being undecided was positively associated with beliefs in their immune system and having previously received the Oxford/AstraZeneca (as opposed to Pfizer/BioNTech) vaccine; and negatively associated with CBV knowledge, positive attitudes regarding CBV, a positive COVID-19 vaccine experience, anticipated regret of not having a CBV, white British ethnicity, and living in East Midlands (vs. London). Conclusions: Public health interventions promoting CBV may improve uptake through tailored messaging directed towards the specific decision stage relating to having a COVID-19 booster.

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One for all - Human kidney Caki-1 cells are highly susceptible to infection with corona- and other respiratory viruses -

In vitro investigations of host-pathogen interactions of viruses are reliant on suitable cell and tissue culture models. Results are only as good as the model they have been generated in. However, choosing cell models for in vitro work often depends on what is available in labs or what has previously been used. Despite the vast increase in coronavirus research activity over the past few years, researchers are still heavily reliant on: non-human cells, for example Vero E6, highly heterogeneous or not fully differentiated cells, such as Calu-3, or naturally unsusceptible cells requiring overexpression of receptors and other accessory factors, such as ACE2 and TMPRSS2. Complex cell models, such as primary cell-derived air-liquid interface epithelial models are highly representative of human tissues but are expensive and time-consuming to develop and maintain. They have limited suitability for large-scale and high-throughput analysis. Using tissue-specific expression pattern as a selection criteria, we identified human kidney cells as an ideal target for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and broader coronavirus infection. We show the use of the highly characterized human kidney cell line Caki-1 for infection with three human coronaviruses: Betacoronaviruses SARS-CoV-2 and Middle Eastern respiratory syndrome coronavirus (MERS-CoV) and Alphacoronavirus human coronavirus 229E (hCoV-229E). Caki-1 cells show equal or superior susceptibility to all three coronaviruses when compared to other commonly used cell lines for the cultivation of the respective virus. Antibody staining against SARS-CoV-2 N protein shows comparable replication rates. Using a panel of 21 antibodies in infected Caki-1 cells using immunocytochemistry shows the location of viral proteins during replication. In addition, Caki-1 cells were found to be susceptible to two other human respiratory viruses, influenza A virus and respiratory syncytial virus, making them an ideal model for cross-comparison of not only a broad range of coronaviruses but respiratory viruses in general.

🖺 Full Text HTML: One for all - Human kidney Caki-1 cells are highly susceptible to infection with corona- and other respiratory viruses

Improving mRNA vaccine safety and efficiency with cationized lipid nanoparticle formula -

The widespread use of Covid-19 mRNA vaccines has highlighted the need to address rare but concerning side effects. Systemic off-target gene expression has been identified as a primary cause of acute adverse reactions and side effects associated with nucleoside-modified mRNA vaccines. In this study, we incorporated the permanent cationic lipid Dotap component into the mRNA-LNP formula associated with the FDA-approved mRNA vaccine Comirnaty to create a novel positively charged LNP carrier for mRNA vaccine delivery. Using the optimized LNP formula to prepare SARS-Cov-2 Spike mRNA vaccines for immunogenicity testing, Balb/c mice exhibited improved immunogenicity kinetics with initial antibody titers being lower but showing a continuous upward trend, ultimately reaching levels comparable to those of control mRNA vaccines 8 weeks after boost immunization. The mRNA vaccines encapsulated in the modified LNPs have demonstrated a superior safety profile in respect to systemic delivery of LNP constituents, off-target gene expression, and the systemic pro-inflammatory stimulation. Consequently, it may represent a safer alternative of conventional mRNA-LNP vaccines.

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Post-infection treatment with the E protein inhibitor BIT225 reduces disease severity and increases survival of k18-hACE2 transgenic mice infected with a lethal dose of SARS-CoV-2 -

The Coronavirus envelope (E) protein is a small structural protein with ion channel activity that plays an important role in virus assembly, budding, immunopathogenesis and disease severity. The viroporin E is also located in Golgi and ER membranes of infected cells and is associated with inflammasome activation and immune dysregulation. Here we evaluated in vitro antiviral activity, mechanism of action and in vivo efficacy of BIT225 for the treatment of SARS-CoV-2 infection. BIT225 showed broad-spectrum direct-acting antiviral activity against SARS-CoV-2 in Calu3 and Vero cells with similar potency across 6 different virus strains. BIT225 inhibited ion channel activity of E-protein but did not inhibit endogenous calcium-induced ion channel activity or TMEM16A in Xenopus oocytes. BIT225 administered by oral gavage for 12 days starting 12 h before infection completely prevented body weight loss and mortality in SARS-CoV-2 infected K18 mice (100% survival, n=12), while all vehicle-dosed animals reached a mortality endpoint by day 9 across two studies (n=12). When treatment started at 24 h after infection, body weight loss, and mortality were also prevented (100% survival, n=5), while 4 of 5 mice maintained and increased body weight and survived when treatment started 48 hours after infection. Treatment efficacy was dependent on BIT225 dose and was associated with significant reductions in lung viral load (3.5 log10), virus titer (4000 pfu/ml) and lung and serum cytokine levels. These results validate viroporin E as a viable antiviral target and support the clinical study of BIT225 for treatment and prophylaxis of SARS-CoV-2 infection.

🖺 Full Text HTML: Post-infection treatment with the E protein inhibitor BIT225 reduces disease severity and increases survival of k18-hACE2 transgenic mice infected with a lethal dose of SARS-CoV-2

Broad and potent neutralizing mAbs are elicited in vaccinated individuals following Delta/BA.1 breakthrough infection -

Despite the success of COVID-19 vaccines in preventing infection and/or severe disease, with the emergence of SARS-CoV-2 variants of concern (VOC) which encode mutations in Spike, and the waning of vaccine induced immunity, there has been an increase in SARS-CoV-2 infections in vaccinated individuals which leads to increased serum neutralization breadth. However, how exposure to a heterologous Spike broadens the neutralizing response at the monoclonal antibody (mAb) level is not fully understood. Through isolation of 119 mAbs from three individuals receiving two-doses of BNT162b2 vaccine before becoming delta or omicron/BA.1-infected, we show that breadth arises from re-activation and maturation of B cells generated through previous COVID-19 vaccination rather than a de novo response specific to the VOC Spike. Isolated mAbs frequently show reduced neutralization of current circulating variants including BA.2.75.2, XBB, XBB.1.5 and BQ.1.1 confirming continuous selective pressure on Spike to evolve and evade neutralization. However, isolation of mAbs that display effective cross-neutralization against all variants indicate the presence of conserved epitopes on RBD and a lesser extent NTD. These findings have implications for selection of Spike antigens for next-generation COVID-19 vaccines.

🖺 Full Text HTML: Broad and potent neutralizing mAbs are elicited in vaccinated individuals following Delta/BA.1 breakthrough infection

NETosis Induced by Serum of Patients with COVID-19 is Reduced with Reparixin or Antibodies Against DEK and IL-8 -

DEK locates in the nucleus of the cells or the cytoplasmic granules of neutrophils and plays different roles in cellular processes including NETosis, a suicide mechanism of neutrophils. Here we showed that the interaction of rDEK with CXCR2 leads to NETosis, which could be reduced by the CXCR1/CXCR2 inhibitor reparixin. We found that IL-8, IL-6, IL1-{beta}, MPO, and CitH3 were increased whereas DEK was decreased in the serum of COVID-19 patients. Interestingly, reparixin or anti-DEK antibody reduced the NETosis induced by the serums of patients , suggesting that initial cytokine stimulation may further induce the release of DEK. Our results support the use of reparixin as a potential therapeutic strategy in COVID-19 and suggest that DEK-CXCR2 interaction plays a role in NETosis.

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Total-Body Multiparametric PET Quantification of 18F-FDG Delivery and Metabolism in the Study of COVID-19 Recovery -

Conventional whole-body ¹⁸F-FDG PET imaging provides a semi-quantitative evaluation of overall glucose metabolism without gaining insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric ¹⁸F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19). Methods: The study included thirteen healthy subjects and twelve recovering COVID-19 subjects within eight weeks of confirmed diagnosis. Each subject had a dynamic ¹⁸F-FDG scan on the uEXPLORER total-body PET/CT system for one hour. Semiquantitative standardized uptake value (SUV) and SUV ratio relative to blood (SUVR) were calculated for regions of interest (ROIs) in different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify microparametric rate constants K₁ and k₃ that characterize ¹⁸F-FDG blood-to-tissue delivery and intracellular phosphorylation, respectively, and a macroparameter K_i that represents ¹⁸F-FDG net influx rate. Statistical tests were performed to examine differences between the healthy controls and recovering COVID-19 subjects. Impact of COVID-19 vaccination was investigated. We further generated parametric images to confirm the ROI-based analysis. Results: We detected no significant difference in lung SUV but significantly higher lung SUVR and K_i in the recovering COVID-19 subjects, indicating an improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k₃, but not with the delivery rate K₁, which suggests it is glucose phosphorylation, not glucose delivery, that drives the observed difference of glucose metabolism in the lungs. Meanwhile, there was no or little difference in bone marrow metabolism measured with SUV, SUVR and K_i, but a significant increase in bone-marrow ¹⁸F-FDG delivery rate K₁ in the COVID-19 group (p<0.05), revealing a difference of glucose delivery in this immune-related organ. The observed differences were lower or similar in vaccinated COVID-19 subjects as compared to unvaccinated ones. The organ ROI-based findings were further supported by parametric images. Conclusions: Higher lung glucose metabolism and bone-marrow glucose delivery were observed with total-body multiparametric ¹⁸F-FDG PET in recovering COVID-19 subjects as compared to healthy subjects, which suggests continued inflammation due to COVID-19 during the early stages of recovery. Total-body multiparametric PET of ¹⁸F-FDG delivery and metabolism can provide a more sensitive tool and more insights than conventional static whole-body ¹⁸F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.

🖺 Full Text HTML: Total-Body Multiparametric PET Quantification of 18F-FDG Delivery and Metabolism in the Study of COVID-19 Recovery

Lasting first impression: Pre-existing immunity restricts mucosal antibody responses during Omicron breakthrough -

Understanding mucosal antibody responses from SARS-CoV-2 infection and/or vaccination is crucial to develop strategies for longer term immunity, especially against emerging viral variants. We profiled serial paired mucosal and plasma antibodies from: COVID-19 vaccinated only vaccinees (vaccinated, uninfected), COVID-19 recovered vaccinees (convalescent, vaccinated) and individuals with breakthrough Delta or Omicron BA.2 infections (vaccinated, infected). Saliva from COVID-19 recovered vaccinees displayed improved antibody neutralizing activity, FcγR engagement and IgA compared to COVID-19 uninfected vaccinees. Furthermore, repeated mRNA vaccination boosted SARS-CoV-2-specific IgG2 and IgG4 responses in both mucosa biofluids (saliva and tears) and plasma. IgG, but not IgA, responses to breakthrough COVID-19 variants were dampened and narrowed by increased pre-existing vaccine-induced immunity to the ancestral strain. Salivary antibodies delayed initiation of boosting following breakthrough COVID-19 infection, especially Omicron BA.2, however, rose rapidly thereafter. Our data highlight how pre-existing immunity shapes mucosal SARS-CoV-2-specific antibody responses and has implications for long-term protection from COVID-19.

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Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic -

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests (with a high false negative rate) due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2s propensity for asymptomatic transmission, raise the question how reliable was contact tracing for COVID-19 in the United States? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62%-1.68%) of transmission events with PCR testing and 0.88% (95% uncertainty interval 0.86%-0.89%) with rapid antigen testing. When considering an optimal scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6%-62.8%). These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.

🖺 Full Text HTML: Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic

Single-cell analysis of bronchoalveolar cells in inflammatory and fibrotic post-COVID lung disease -

Rationale: Persistent pulmonary sequelae are evident in many survivors of acute coronavirus disease 2019 (COVID-19) but the molecular mechanisms responsible are incompletely understood. Post-COVID radiological lung abnormalities comprise two broad categories, organising pneumonia and reticulation, interpreted as indicative of subacute inflammation and fibrosis, respectively. Whether these two patterns represent distinct pathologies, likely to require different treatment strategies is not known. Objectives: We sought to identify differences at molecular and cellular level, in the local immunopathology of post-COVID inflammation and fibrosis. Methods: We compared single-cell transcriptomic profiles and T cell receptor (TCR) repertoires of bronchoalveolar cells obtained from convalescent individuals with each radiological pattern of post-COVID lung disease (PCLD). Measurements and Main Results: Inflammatory and fibrotic PCLD single-cell transcriptomes closely resembled each other across all cell types. However, CD4 central memory T cells (TCM) and CD8 effector memory T cells (TEM) were significantly more abundant in inflammatory PCLD. A greater proportion of CD4 TCM also exhibited clonal expansion in inflammatory PCLD. High levels of clustering of similar TCRs from multiple donors was a striking feature of both PCLD phenotypes, consistent with tissue localised antigen-specific immune responses, but there was no enrichment for known SARS-CoV-2 reactive TCRs. Conclusions: There is no evidence that radiographic organising pneumonia and reticulation in PCLD are associated with differential immmunopathological pathways. Inflammatory radiology is characterised by greater bronchoalveolar T cell accumulation. Both groups show evidence of shared antigen-specific T cell responses, but the antigenic target for these T cells remains to be identified.

🖺 Full Text HTML: Single-cell analysis of bronchoalveolar cells in inflammatory and fibrotic post-COVID lung disease

Coronavirus pathogenesis in mice explains the SARS-CoV-2 multi-organ spread by red blood cell hitch-hiking -

SARS-CoV-2 infection causes a multisystemic disease that affects numerous organs beyond the respiratory system. Thus, it is well known that COVID-19 is associated with a wide range of hematological disorders; however, it remains unclear how the SARS-CoV-2 virus is able to navigate from tissue to tissue. In this work, we performed a comprehensive analysis of the pleiotropic effects of a prototypical coronavirus in its natural host, the validated preclinical model of murine hepatitis virus (MHV). Throughout this study we compared our results with the real-world data from COVID-19 patients (including autopsies). Thus, the presence of viral RNA was only detected in less than 25% of the human serum samples, whereas all had multiple positive nasal swabs for SARS-CoV-2. Notably, we found viral RNA not only in lungs, but also in heart and kidney of deceased COVID-19 patients. Subsequently, we investigated the association between viral organotropism and clinical manifestations employing the MHV murine model. Results from RT-qPCR and viral infectivity showcased the presence of viral RNA and infectious particles in multiple organs including liver, lung, brain, heart, kidney, spleen and pancreas, and even the blood of infected mice. Surprisingly, when comparing plasma and red blood cells (RBCs)-enriched fraction, higher viral load levels were detected in RBCs, with decreased RBC count, and hematocrit and hemoglobin levels in infected mice. Next, we treated infected mice with hemin triggering more aggressive symptoms. Strikingly, when combining hemin treatment with chloroquine (a compound that known to interact with the heme group and induces a conformational change in its structure) the infection and its clinical manifestations were distinctly attenuated. Computational docking suggested that heme is able to bind to MHV Spike protein in a similar way to the one, experimentally observed for SARS-CoV-2. Overall, our results lead to a global perspective of COVID-19 beyond the canonical focus on the respiratory system, and strongly support the multi-organ extent of coronavirus infection through specific interactions with RBC hemoproteins.

🖺 Full Text HTML: Coronavirus pathogenesis in mice explains the SARS-CoV-2 multi-organ spread by red blood cell hitch-hiking

Diagnosing and remediating harmful data shifts for the responsible deployment of clinical AI models -

Harmful data shifts occur when the distribution of data used to train a clinical AI system differs significantly from the distribution of data encountered during deployment, leading to erroneous predictions and potential harm to patients. We evaluated the impact of data shifts on an early warning system (EWS) for in-hospital mortality that uses electronic health record (EHR) data from patients admitted to a general internal medicine service. We found model performance to differ across subgroups of clinical diagnoses, sex and age. To explore the robustness of the model, we evaluated potentially harmful data shifts across demographics, hospital types, seasons, times of hospital admission, and whether the patient was admitted from an acute care institution or nursing home, without relying on model performance. Interestingly, we found that models trained on community hospitals experience harmful data shifts when evaluated on academic hospitals, whereas the models trained on academic hospitals transfer well to the community hospitals. To improve model performance across hospital sites we employed transfer learning, a strategy that stores knowledge gained from learning one domain and applies it to a different but related domain. We found hospital type-specific models that leverage transfer learning, perform better than models that use all available hospitals. Furthermore, we monitored data shifts over time and identified model deterioration during the COVID-19 pandemic. Typically machine learning models remain locked after deployment, however, this can lead to model deterioration due to data shifts that occur over time. We used continual learning, the process of learning from a continual stream of data in a sequential manner, to mitigate data shifts over time and improve model performance. Overall, our study is a crucial step towards the deployment of clinical AI models, by providing strategies and workflows to ensure the safety and efficacy of these models in real-world settings.

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Effectiveness of nirmatrelvir-ritonavir for the treatment of patients with mild to moderate COVID-19 and at high risk of hospitalization: Systematic review and meta-analyses of observational studies -

Abstract Objective To assess the effectiveness of nirmatrelvir-ritonavir in the treatment of outpatients with mild to moderate COVID-19 who are at higher risk of developing severe illness, through a systematic review with meta-analyses of observational studies. Methods A systematic search was performed, in accordance with the Cochrane search methods, to identify observational studies that met the inclusion criteria. The outcomes of mortality and hospitalization were analyzed. Search was conducted on PubMed, EMBASE, and The Cochrane Library. Two reviewers independently screened references, selected the studies, extracted the data, assessed the risk of bias using ROBINS-I tool and evaluated the quality of evidence using the GRADE tool. This study followed the PRISMA reporting guideline. Results A total of 16 observational studies and 1,482,923 patients were finally included. The results of the meta-analysis showed that in comparison to standard treatment without antivirals, nirmatrelvir-ritonavir reduced the risk of death by 62% (OR= 0.38; 95% CI: 0.30-0.46; moderate certainty of evidence). In addition, a 53% reduction in the risk of hospital admission was observed (OR = 0.47; 95% CI: 0.36–0.60, with very low certainty of evidence). For the composite outcome of hospitalization and/or mortality, there was a 56% risk reduction (OR=0.44; 95% CI: 0.31-0.64, moderate certainty of evidence). Conclusion The results suggest that nirmatrelvir-ritonavir could be effective in reducing mortality and hospitalization. The results were valid in vaccinated or unvaccinated high-risk individuals with COVID-19. Data from ongoing and future trials may further advance our understanding of the effectiveness and safety of nirmatrelvir-ritonavir and help improve treatment guidelines for COVID-19.

🖺 Full Text HTML: Effectiveness of nirmatrelvir-ritonavir for the treatment of patients with mild to moderate COVID-19 and at high risk of hospitalization: Systematic review and meta-analyses of observational studies

Exploring the Impact of the Covid-19 Pandemic on Health-Related Behaviours: A Person-Centred Analysis of Two British Longitudinal Cohort Studies -

The current study explored the impact of the Covid-19 pandemic on health-related behaviours in the United Kingdom. We conducted a repeated measures latent class analysis with five indicators of health-related behaviours; frequency of alcohol consumption, binge drinking, smoking, BMI and sleep, to identify distinct subgroups of individuals with similar patterns of change across three timepoints during the first 9 months of the pandemic. We hypothesised that various psychosocial risk factors, such as a history of adverse childhood experiences would predict membership in latent classes with a higher probability of engaging in risky health behaviours, and that protective factors, like social support, would be associated with membership in classes with less risky health behaviours. We identified 5 latent classes, and multinomial logistic regression analyses revealed multiple predictors of class membership. Our findings did not support the relationship between poor mental health and the adoption of risky health behaviours. Keywords: Repeated Measures Latent Class Analysis, Covid-19, Adverse Childhood Experiences, Health Related Behaviours

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Modelling Disease Mitigation at Mass Gatherings: A Case Study of COVID-19 at the 2022 FIFA World Cup. -

The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework. Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day outperformed RT-PCR screenings 1.5 days before match day. A combination of pre-travel RT-PCR and pre-match RA testing proved to be the most successful screening-based regime. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. The research outlined here suggests a policy requiring visitors to have had a recent COVID-19 vaccination may have prevented the increase in COVID-19 cases and hospitalisations during the world cup.

🖺 Full Text HTML: Modelling Disease Mitigation at Mass Gatherings: A Case Study of COVID-19 at the 2022 FIFA World Cup.

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