Assessment of SARS-CoV-2 immunity in convalescent children and adolescents (preprint)

Background: Persistence of protective immunity for SARS-CoV-2 is important against reinfection. Knowledge on SARS-CoV-2 immunity in pediatric patients is currently lacking. We opted to assess the SARS-CoV-2 adaptive immunity in recovered children and adolescents, addressing the pediatrics specific immunity towards COVID-19. Method: Two independent assays were performed to investigate humoral and cellular immunological memory in pediatric convalescent COVID-19 patients. Specifically, RBD IgG, CD4+, and CD8+ T cell responses were identified and quantified in recovered children and adolescents. Results: : SARS-CoV-2-specific RBD IgG detected in recovered patients had a half-life of 121.6 days and estimated duration of 7.9 months compared with baseline levels in controls. The specific T cell response was shown to be independent of recovery time. Both CD4+ and CD8+ T cells showed robust responses not only to spike (S) peptides (a main target of vaccine platforms) but were also similarly activated when stimulated by membrane (M) and nuclear (N) peptides. Importantly, we found the differences in the adaptive responses were correlated with the age of the recovered patients. The CD4+ T cell response to SARS-CoV-2 S peptide in children aged <12 years correlated with higher SARS-CoV-2 RBD IgG levels, whereas higher level of CD8+ T cells in children aged ≥12 years, suggesting the importance of a T cell-dependent humoral response in younger children under 12 years. Conclusion: Both cellular and humoral immunity against SARS-CoV-2 infections can be induced in pediatric patients. Our important findings provide fundamental knowledge on the immune memory responses to SARS-CoV-2 in recovered pediatric patients.

Impact of COVID-19 Pandemic on School-aged Children’s Physical Activity, Screen Time and Sleep in Hong Kong: a Cross-sectional Repeated Measures Study (preprint)

Despite concerns about the negative effects of social distancing and prolonged school closures on children’s lifestyle and physical activity (PA) during the COVID-19 pandemic, robust evidence is lacking on the impact of the COVID-19 pandemic on children’s wellbeing and daily life. This study aimed to examine changes in the PA levels, sleep patterns and screen time of school-aged children during the different phases of COVID-19 outbreak in Hong Kong using a repeated cross-sectional design. School students (Grades 1 to 12) were asked to report their daily electronic device usage and to fill in a sleep dairy recording their daily sleep and wake-up time. They were equipped with a PA monitor, Actigraph wGT3X-BT, to obtain objective data on their PA levels and sleep patterns. Students were recruited before the pandemic (Sep 2019 – Jan 2020; n=577), during school closures (Mar 2020 – Apr 2020; n=146), and after schools partially reopened (Oct 2020 – Jul 2021; n=227). Our results indicated lower PA levels, longer sleep duration, and longer screen time among participants recruited during school closures than those recruited before the COVID-19 outbreak. Primary school students were found to sleep on average for an extra hour during school closures. Our findings illustrate the impact of social distancing policies during the COVID-19 pandemic on the sleep pattern, screen time, and PA level in school-aged children in Hong Kong. Professionals should reinforce the importance of maintaining a physically active lifestyle, good sleep hygiene, and healthy use of electronic devices to parents and school-aged children during the COVID-19 Pandemic.

Benchmarking emergency department triage prediction models with machine learning and large public electronic health records (preprint)

The demand for emergency department (ED) services is increasing across the globe, particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have become increasingly challenging due to the shortage of medical resources and the strain on hospital infrastructure caused by the pandemic. As a result of the widespread use of electronic health records (EHRs), we now have access to a vast amount of clinical data, which allows us to develop predictive models and decision support systems to address these challenges. To date, however, there are no widely accepted benchmark ED triage prediction models based on large-scale public EHR data. An open-source benchmarking platform would streamline research workflows by eliminating cumbersome data preprocessing, and facilitate comparisons among different studies and methodologies. In this paper, based on the Medical Information Mart for Intensive Care IV Emergency Department (MIMIC-IV-ED) database, we developed a publicly available benchmark suite for ED triage predictive models and created a benchmark dataset that contains over 400,000 ED visits from 2011 to 2019. We introduced three ED-based outcomes (hospitalization, critical outcomes, and 72-hour ED reattendance) and implemented a variety of popular methodologies, ranging from machine learning methods to clinical scoring systems. We evaluated and compared the performance of these methods against benchmark tasks. Our codes are open-source, allowing anyone with MIMIC-IV-ED data access to perform the same steps in data processing, benchmark model building, and experiments. This study provides future researchers with insights, suggestions, and protocols for managing raw data and developing risk triaging tools for emergency care.

Multimorbidity and adverse events of special interest associated with CoronaVac (Sinovac) and Comirnaty (Pfizer-BioNTech) (preprint)

We examined the potential additional risk of adverse events of special interest (AESI) within 28 days post-Covid-19 vaccination with CoronaVac or Comirnaty (Pfizer-BioNTech) imposed by multimorbidity (2 + chronic conditions). Using a territory-wide public healthcare database with linkage to population-based vaccination records in Hong Kong, we conducted a retrospective cohort study of patients with chronic diseases. Thirty AESI according to World Health Organization’s Global Advisory Committee on Vaccine Safety were examined. In total, 883,416 patients were included. During follow-up, 2,807 (0.3%) patients had AESI. Weighted Cox models suggested that vaccinated patients had lower risks of any AESI than those unvaccinated, that multimorbidity was associated with an increased risk regardless of vaccination status, and there was no significant effect modification of the association of vaccination with AESI by multimorbidity status. To conclude, we found no evidence that multimorbidity imposes extra risks of AESI within 28 days following Covid-19 vaccination.

COVID-19 infection and subsequent thromboembolism: A self-controlled case series analysis of a population cohort (preprint)

Importance: An unexpectedly large number of people infected with Covid-19 appear to have experienced ischaemic stroke or thrombotic event. Objective: This study aims to assess the risk associations between Covid-19 infection and thromboembolism. Design: This is a self-controlled case-series study in Scotland. Their incidence rates during the risk interval (5 days before to 56 days after the positive test) and the control interval (the remaining periods) were compared intra-personally. Setting: Population-based. Participants: Individuals with confirmed (positive test) Covid-19 and at least one thromboembolic event between March 2018 and October 2020. Exposure: Covid-19 test positive. Main Outcomes and Measures: Myocardial infarction (MI), ischaemic stroke, deep-vein thrombosis (DVT), and pulmonary embolism (PE) hospital admissions and deaths. Results: Across Scotland, 1,449 individuals tested positive for Covid-19 and experienced a thromboembolic event. The risk of thromboembolism was significantly elevated over the whole risk period but highest in the 7 days following the positive test (IRR 12.01, 95% CI 9.91-14.56), especially among people >=75 years (IRR 22.78, 95% CI 17.58-29.53). Risk of MI, stroke, PE and DVT were all significantly higher in the week following a positive test. The risk of PE and DVT was particularly high and remained significantly elevated even 56 days following the test. Conclusions and relevance: Confirmed Covid-19 infection was associated with early elevated risk of MI, ischaemic stroke, and stronger and long elevations in risk with DVT and PE, reinforcing the need to consider monitoring and early diagnosis. Treatment and prevention trials may need to be considered out of hospital on the basis of risk stratification.

Whole Genome Sequencing for Revealing the Point Mutations of SARS-CoV-2 Genome in Bangladeshi Isolates and their Structural Effects on Viral Proteins (preprint)

Coronavirus disease-19 (COVID-19) is the recent global pandemic caused by the virus Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The virus has already killed more than one million people worldwide and billions are at risk of getting infected. As of now, there is neither any drug nor any vaccine in sight with conclusive scientific evidence that it can cure or provide protection against the illness. Since novel coronavirus is a new virus, mining its genome sequence is of crucial importance for drug/vaccine(s) development. Whole genome sequencing is a helpful tool in identifying genetic changes that occur in a virus when it spreads through the population. In this study, we performed complete genome sequencing of SARS-CoV-2 to unveil the genomic variation and indel, if present. We discovered thirteen (13) mutations in Orf1ab, S and N gene where seven (7) of them turned out to be novel mutations from our sequenced isolate. Besides, we found one (1) insertion and seven (7) deletions from the indel analysis among the 323 Bangladeshi isolates. However, the indel did not show any effect on proteins. Our energy minimization analysis showed both stabilizing and destabilizing impact on viral proteins depending on the mutation. Interestingly, all the variants were located in the binding site of the proteins. Furthermore, drug binding analysis revealed marked difference in interacting residues in mutants when compared to the wild type. Our analysis also suggested that eleven (11) mutations could exert damaging effects on their corresponding protein structures. The analysis of SARS-CoV-2 genetic variation and their impacts presented in this study might be helpful in gaining a better understanding of the pathogenesis of this deadly virus.

Elevated SARS-CoV-2 Antibodies Distinguish Severe Disease in Early COVID-19 Infection (preprint)

BackgroundSARS-CoV-2 has caused over 36,000,000 cases and 1,000,000 deaths globally. Comprehensive assessment of the multifaceted anti-viral antibody response is critical for diagnosis, differentiation of severe disease, and characterization of long-term immunity. Initial observations suggest that severe disease is associated with higher antibody levels and greater B cell/plasmablast responses. A multi-antigen immunoassay to define the complex serological landscape and clinical associations is essential. MethodsWe developed a multiplex immunoassay and evaluated serum/plasma from adults with RT-PCR-confirmed SARS-CoV-2 infections during acute illness (N=52) and convalescence (N=69); and pre-pandemic (N=106) and post-pandemic (N=137) healthy adults. We measured IgA, IgG, and/or IgM against SARS-CoV-2 Nucleocapsid (N), Spike domain 1 (S1), receptor binding domain (S1-RBD) and S1-N-terminal domain (S1-NTD). ResultsTo diagnose infection, the combined [IgA+IgG+IgM] or IgG for N, S1, and S1-RBD yielded AUC values -0.90 by ROC curves. From days 6-30 post-symptom onset, the levels of antigen-specific IgG, IgA or [IgA+IgG+IgM] were higher in patients with severe/critical compared to mild/moderate infections. Consistent with excessive concentrations of antibodies, a strong prozone effect was observed in sera from severe/critical patients. Notably, mild/moderate patients displayed a slower rise and lower peak in anti-N and anti-S1 IgG levels compared to severe/critical patients, but anti-RBD IgG and neutralization responses reached similar levels at 2-4 months. ConclusionThis SARS-CoV-2 multiplex immunoassay measures the magnitude, complexity and kinetics of the antibody response against multiple viral antigens. The IgG and combined-isotype SARS-CoV-2 multiplex assay is highly diagnostic of acute and convalescent disease and may prognosticate severity early in illness. One Sentence SummaryIn contrast to patients with moderate infections, those with severe COVID-19 develop prominent, early antibody responses to S1 and N proteins.

The aging whole blood transcriptome reveals a potential role of FASLG in COVID-19 (preprint)

The risk for severe illness from COVID-19 increases with age as older patients are at the highest risk. Although it is still unclear whether the virus is blood-transmitted, the viral RNA is detected in serum. Identifying how Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) interacts with specific blood components during aging is expected to guide proper therapies. Considering that all human coronavirus require host cellular molecules to promote infection, we investigated the aging whole blood transcriptome from the Genotype-Tissue Expression (GTEx) database to explore differentially expressed genes (DEGs) translated into proteins potentially interacting with viral proteins. From a total of 22 DEGs in aged blood, five genes (FASLG, CTSW, CTSE, VCAM1, and BAG3) changed expression during aging. These age-related genes are involved in immune response, inflammation, cell component and cell adhesion, and platelet activation/aggregation. Both males and females older than 50 overexpress FASLG compared with younger adults (20-30 years old), possibly inducing a hyper-inflammatory cascade that activates specific immune cells. Furthermore, the expression of cathepsins (CTSW and CTSE) and the anti-apoptotic co-chaperone molecule BAG3 was significantly increased throughout aging in both gender. By exploring publicly available Single-Cell RNA-Sequencing (scRNA-Seq) data on peripheral blood of SARS-CoV-2-infected patients, we found FASLG and CTSW expressed mainly in natural killer (NK) cells and CD8+ (cytotoxic) T lymphocytes whereas BAG3 was expressed in CD4+ T cells, naive T cells, and CD14+ monocytes. The increased expression of FASLG in blood during aging may explain why older patients are more prone to severe acute viral infection complications. These results indicate FASLG as a prognostic candidate and potential therapeutic target for more aggressive clinical manifestation of COVID-19.