Analysis of blood and nasal epithelial transcriptomes to identify mechanisms associated with control of SARS-CoV-2 viral load in the upper respiratory tract (preprint)

Background: The amount of SARS-CoV-2 detected in the upper respiratory tract (URT viral load) is a key driver of transmission of infection. Current evidence suggests that mechanisms constraining URT viral load are different from those controlling lower respiratory tract viral load and disease severity. Understanding such mechanisms may help to develop treatments and vaccine strategies to reduce transmission. Combining mathematical modelling of URT viral load dynamics with transcriptome analyses we aimed to identify mechanisms controlling URT viral load. Methods: COVID-19 patients were recruited in Spain during the first wave of the pandemic. RNA sequencing of peripheral blood and targeted NanoString nCounter transcriptome analysis of nasal epithelium were performed and gene expression analysed in relation to paired URT viral load samples collected within 15 days of symptom onset. Proportions of major immune cells in blood were estimated from transcriptional data using computational differential estimation. Weighted correlation network analysis (adjusted for cell proportions) and fixed transcriptional repertoire analysis were used to identify associations with URT viral load, quantified as standard deviations (z-scores) from an expected trajectory over time. Results: Eighty-two subjects (50% female, median age 54 years (range 3-73)) with COVID-19 were recruited. Paired URT viral load samples were available for 16 blood transcriptome samples, and 17 respiratory epithelial transcriptome samples. Natural Killer (NK) cells were the only blood cell type significantly correlated with URT viral load z-scores (r = -0.62, P = 0.010). Twenty-four blood gene expression modules were significantly correlated with URT viral load z-score, the most significant being a module of genes connected around IFNA14 (Interferon Alpha-14) expression (r = -0.60, P = 1e-10). In fixed repertoire analysis, prostanoid-related gene expression was significantly associated with higher viral load. In nasal epithelium, only GNLY (granulysin) gene expression showed significant negative correlation with viral load. Conclusions: Correlations between the transcriptional host response and inter-individual variations in SARS-CoV-2 URT viral load, revealed many molecular mechanisms plausibly favouring or constraining viral load. Existing evidence corroborates many of these mechanisms, including likely roles for NK cells, granulysin, prostanoids and interferon alpha-14. Inhibition of prostanoid production, and administration of interferon alpha-14 may be attractive transmission-blocking interventions.

Network Contagion of COVID-19 on US Industries (preprint)

The applications of Network Science have been limited in finance, but recently Zhu et. al (2016) have created a methodology in which co-movements between a given industry and the overall stock market can be represented by nodes and transitions between these movement states can be represented as edges. This modeling approach creates network structures that provide information on the susceptibility of markets to contagious risk that can be studied with network methods. This paper builds on this methodology to study the effect of the COVID-19 pandemic on contagious financial risk across industrial sectors. I propose a novel metric to measure an industry’s susceptibility to contagion at a point in time. I apply this metric to a sample of U.S. industrial ETFs before and after the onset of the pandemic. My results suggest that COVID-19 led to increases in the susceptibility to contagious risk across all sectors.

Genomic Investigations of Acute Hepatitis of Unknown Aetiology in Children (preprint)

Since the first reports of hepatitis of unknown aetiology occurring in UK children, over 1000 cases have been reported worldwide, including 268 cases in the UK, with the majority younger than 6 years old. Using genomic, proteomic and immunohistochemical methods, we undertook extensive investigation of 28 cases and 136 control subjects. In five cases who underwent liver transplantation, we detected high levels of adeno-associated virus 2 (AAV2) in the explanted livers. AAV2 was also detected at high levels in blood from 10/11 non-transplanted cases. Low levels of Adenovirus (HAdV) and Human Herpesvirus 6B (HHV-6B), both of which enable AAV2 lytic replication, were also found in the five explanted livers and blood from 15/17 and 6/9 respectively, of the 23 non-transplant cases tested. In contrast, AAV2 was detected at low titre in 6/100 whole bloods from child controls from cohorts with presence or absence of hepatitis and/or adenovirus infection. Our data show an association of AAV2 at high titre in blood or liver tissue, with unexplained hepatitis in children infected in the recent HAdV-F41 outbreak. We were unable to find evidence by electron microscopy, immunohistochemistry or proteomics of HAdV or AAV2 viral particles or proteins in explanted livers, suggesting that hepatic pathology is not due to direct lytic infection by either virus. The potential that AAV2, although not previously associated with disease, may, together with HAdV-F41 and/or HHV-6, be causally implicated in the outbreak of unexplained hepatitis, requires further investigation.

Pseudotemporal whole blood transcriptional profiling of COVID-19 patients stratified by clinical severity reveals differences in immune responses and possible role of monoamine oxidase B (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with highly variable clinical outcomes. Studying the temporal dynamics of host whole blood gene expression during SARS-CoV-2 infection can elucidate the biological processes that underlie these diverse clinical phenotypes. We employed a novel pseudotemporal approach using MaSigPro to model and compare the trajectories of whole blood transcriptomic responses in patients with mild, moderate and severe COVID-19 disease. We identified 5,267 genes significantly differentially expressed (SDE) over pseudotime and between severity groups and clustered these genes together based on pseudotemporal trends. Pathway analysis of these gene clusters revealed upregulation of multiple immune, coagulation, platelet and senescence pathways with increasing disease severity and downregulation of T cell, transcriptional and cellular metabolic pathways. The gene clusters exhibited differing pseudotemporal trends. Monoamine oxidase B was the top SDE gene, upregulated in severe>moderate>mild COVID-19 disease. This work provides new insights into the diversity of the host response to SARS-CoV-2 and disease severity and highlights the utility of pseudotemporal approaches in studying evolving immune responses to infectious diseases.

Designing Advance Market Commitments for New Vaccines

Advance market commitments (AMCs) provide a mechanism to stimulate investment by suppliers of products to low-income countries. In an AMC, donors commit to a fund from which a specified subsidy is paid per unit purchased by low-income countries until the fund is exhausted, strengthening suppliers' incentives to invest in research, development, and capacity. Last decade saw the launch of a $1.5 billion pilot AMC to distribute pneumococcal vaccine to the developing world;in the current pandemic, variations on AMCs are being used to fund Covid-19 vaccines. This paper undertakes the first formal analysis of AMCs. We construct a model in which an altruistic donor negotiates on behalf of a low-income country with a vaccine supplier after the supplier has sunk investments. We use this model to explain the logic of an AMC—as a solution to a hold-up problem—and to analyze alternative design features under various economic conditions (cost uncertainty, supplier competition). A key finding is that optimal AMC design differs markedly depending on where the product is in its development cycle.

Characterisation of the blood RNA host response underpinning severity in COVID-19 patients (preprint)

Infection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups. Increasing COVID-19 severity was characterised by an abundance of inflammatory immune response genes and pathways, including many related to neutrophils and macrophages, in addition to an upregulation of immunoglobulin genes. Our insights into COVID-19 severity reveal the role of immune dysregulation in the progression to severe disease and highlight the need for further research exploring the interplay between SARS-CoV-2 and the inflammatory immune response.

Discovery and Validation of a 3-Gene Transcriptional Signature to Distinguish COVID-19 and Other Viral Infections from Bacterial Sepsis in Adults; A Case-Control then Observational Cohort Study (preprint)

Background: Emergency hospital admissions for infection often lack microbiological diagnostic certainty. Novel approaches to discriminate likelihood of bacterial and viral infections are required to support antimicrobial prescribing decisions and infection control practice. We sought to derive and validate a blood transcriptional signature to differentiate bacterial infections from viral infections including COVID-19.Methods: Blood RNA sequencing was performed on a discovery cohort of adults attending the Emergency Department with confirmed bacteraemia or viral infection. Differentially expressed host genes were subjected to feature selection to derive the most parsimonious discriminating signature. RT-qPCR validation of the signature was then performed in a prospective cohort of patients presenting with undifferentiated fever and a second case-control cohort of patients with bacteraemia or COVID-19.Findings: A 3-gene transcript signature was derived from the discovery cohort of 56 definite bacterial and 27 viral infection cases. In the validation cohort, the signature differentiated bacterial and viral infections with an area under receiver operating characteristic curve (AUC) of 0.976 (95% CI: 0.919-1.000), sensitivity 97.3% and specificity of 100%. The AUC for C-reactive protein and leucocyte count was 0.833 (95% CI: 0.694-0.944) and 0.938 (95% CI: 0.840-0.986) respectively. In the second validation analysis the signature discriminated 34 SARS-CoV-2 positive COVID-19 from 35 bacterial infections with AUC of 0.953 (95% CI: 0.893-0.992), sensitivity 88.6% and specificity of 94.1%.Interpretation: This novel 3-gene signature discriminates viral infections including COVID-19 from bacterial sepsis in adults, outperforming both leucocyte count and CRP, thus potentially providing significant clinical utility in managing acute presentations with infection.Funding Statement: Work in this study was funded by the NIHR Imperial Biomedical Research Centre, the Medical Research Council, the Wellcome Trust and the European Union FP7 (EC-GA 279185) (EUCLIDS).Declaration of Interests: None of the authors have any relevant interest to declare. Ethics Approval Statement: Ethical approval was obtained to take deferred consent from patients from whom an RNA specimen had been collected (or from next of kin or nominated consultee) (REC references 14/SC/0008 and 19/SC/0116).

A national consensus management pathway for Paediatric Inflammatory Multisystem Syndrome - Temporally associated with SARS-CoV-2 (PIMS-TS): The results of a national Delphi process (preprint)

ObjectiveTo develop a consensus management pathway for children with Paediatric Inflammatory Multisystem Syndrome - Temporally associated with SARS-CoV-2 (PIMS-TS). DesignA three-phase online Delphi process and virtual consensus meeting sought consensus over the investigation, management and research priorities from 98 multidisciplinary participants caring for children with PIMS-TS. 46 participants (47%) completed all three phases. Participants were grouped into three panels and scored each statement from 1 (disagree) to 9 (strongly agree). In phase two participants were shown their panels scores, and in phase three all panels scores. Consensus agreement was defined as [≥]70% of participants in each panel scoring the statement 7-9, and <15% scoring 1-3, and consensus disagreement was the opposite of this. Statements which achieved consensus in 2/3 panels were discussed at the consensus meeting, and when [≥]70% participants agreed with the statement it achieved consensus. Results255 statements were assessed, with consensus agreement achieved for 111 (44%), consensus disagreement for 29 (11%), and no consensus for 115 (45%). The 140 consensus statements were used to derive the consensus management pathway. ConclusionsA national consensus pathway has been developed for children suspected of having the novel syndrome PIMS-TS in a timely, cost-efficient manner, in the midst of a global pandemic. Use of a rapid online Delphi process has made this consensus process possible. Future evidence will inform updates to this guidance, which in the interim provides a solid framework to support clinicians caring for children with PIMS-TS.