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Journal articleSamanta R, Dunning J, Taylor A, et al., 2020,
Identification of novel mechanistically distinct endotypes of pandemic influenza-associated acute respiratory failure
, MedRxivRespiratory viral pandemics result in large numbers of cases of acute respiratory failure arising from a single etiology, thus reducing the heterogeneity of precepting insult and allowing improved insight into the variation of host responses. In 2009-2011, an influenza pandemic occurred, with pH1N1 infecting millions of people worldwide. Here, we have used novel bioinformatic methods to combine clinical, protein biomarker, and genomic data from patients with influenza-associated acute respiratory failure to identify three mechanistically discrete sub-types with significantly different clinical outcomes. The three endotypes identified can be described as “neutrophil-driven” (16.3%), “adaptive” (51.9%), and “endothelial leak” (31.7%). The neutrophil driven patients display evidence of innate immune activation with associated multi-organ dysfunction and reduced 30-day survival. These patients could be differentiated from the adaptive endotype by an alteration in the GAIT-mechanism, a late transcriptional regulatory response to IFN-γ that acts to suppress innate immunity by reducing caeruloplasmin mRNA translation. Patients with the neutrophil-driven endotype had significantly increased IFN-γ levels but appeared unable to suppress their innate immune response. The endothelial leak endotype could be distinguished from both the neutrophil driven and adaptive endotypes by alterations in Slit-Robo signalling, a pathway important in the maintenance of endothelial barrier integrity; Although patients with this endotype required mechanical ventilation, they did not develop multi-organ failure in the manner of the neutrophil-driven endotype patients, and had significantly better clinical outcomes. Importantly, the endotypes identified were stable over 48 hours opening up the possibility of stratified interventional clinical trials in the future. <h4>One Sentence Summary</h4> We have identified three new mechanistically
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Journal articleZhou J, Otter JA, Price JR, et al., 2020,
Investigating SARS-CoV-2 surface and air contamination in an acute healthcare setting during the peak of the COVID-19 pandemic in London
, Clinical Infectious Diseases, Vol: 2020, Pages: 1-1, ISSN: 1058-4838BACKGROUND: Evaluation of SARS-CoV-2 surface and air contamination during the COVID-19 pandemic in London. METHODS: We performed this prospective cross-sectional observational study in a multi-site London hospital. Air and surface samples were collected from seven clinical areas, occupied by patients with COVID-19, and a public area of the hospital. Three or four 1.0 m3 air samples were collected in each area using an active air sampler. Surface samples were collected by swabbing items in the immediate vicinity of each air sample. SARS-CoV-2 was detected by RT-qPCR and viral culture; the limit of detection for culturing SARS-CoV-2 from surfaces was determined. RESULTS: Viral RNA was detected on 114/218 (52.3%) of surfaces and 14/31 (38.7%) air samples but no virus was cultured. The proportion of surface samples contaminated with viral RNA varied by item sampled and by clinical area. Viral RNA was detected on surfaces and in air in public areas of the hospital but was more likely to be found in areas immediately occupied by COVID-19 patients than in other areas (67/105 (63.8%) vs. 29/64 (45.3%) (odds ratio 0.5, 95% confidence interval 0.2-0.9, p=0.025, Chi squared test)). The high PCR Ct value for all samples (>30) indicated that the virus would not be culturable. CONCLUSIONS: Our findings of extensive viral RNA contamination of surfaces and air across a range of acute healthcare settings in the absence of cultured virus underlines the potential risk from environmental contamination in managing COVID-19, and the need for effective use of PPE, physical distancing, and hand/surface hygiene.
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Journal articleYang B, Lessler J, Zhu H, et al., 2020,
Life course exposures continually shape antibody profiles and risk of seroconversion to influenza
, PLOS PATHOGENS, Vol: 16, ISSN: 1553-7366- Author Web Link
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- Citations: 9
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Journal articleBruni T, Lalvani A, Richeldi L, 2020,
Telemedicine-enabled accelerated discharge of patients hospitalized with COVID-19 to isolation in repurposed hotel rooms.
, American Journal of Respiratory and Critical Care Medicine, Vol: 202, Pages: 508-510, ISSN: 1073-449X -
Journal articlePeng Y, Mentzer AJ, Liu G, et al., 2020,
Broad and strong memory CD4 + and CD8 + T cells induced by SARS-CoV-2 in UK convalescent COVID-19 patients.
, bioRxivCOVID-19 is an ongoing global crisis in which the development of effective vaccines and therapeutics will depend critically on understanding the natural immunity to the virus, including the role of SARS-CoV-2-specific T cells. We have conducted a study of 42 patients following recovery from COVID-19, including 28 mild and 14 severe cases, comparing their T cell responses to those of 16 control donors. We assessed the immune memory of T cell responses using IFNγ based assays with overlapping peptides spanning SARS-CoV-2 apart from ORF1. We found the breadth, magnitude and frequency of memory T cell responses from COVID-19 were significantly higher in severe compared to mild COVID-19 cases, and this effect was most marked in response to spike, membrane, and ORF3a proteins. Total and spike-specific T cell responses correlated with the anti-Spike, anti-Receptor Binding Domain (RBD) as well as anti-Nucleoprotein (NP) endpoint antibody titre (p<0.001, <0.001 and =0.002). We identified 39 separate peptides containing CD4 + and/or CD8 + epitopes, which strikingly included six immunodominant epitope clusters targeted by T cells in many donors, including 3 clusters in spike (recognised by 29%, 24%, 18% donors), two in the membrane protein (M, 32%, 47%) and one in the nucleoprotein (Np, 35%). CD8+ responses were further defined for their HLA restriction, including B*4001-restricted T cells showing central memory and effector memory phenotype. In mild cases, higher frequencies of multi-cytokine producing M- and NP-specific CD8 + T cells than spike-specific CD8 + T cells were observed. They furthermore showed a higher ratio of SARS-CoV-2-specific CD8 + to CD4 + T cell responses. Immunodominant epitope clusters and peptides containing T cell epitopes identified in this study will provide critical tools to study the role of virus-specific T cells in control and resolution of SARS-CoV-2 infections. The identification of T cell specificity and functionality associated wi
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Journal articlePalmieri C, Palmer D, Openshaw PJM, et al., 2020,
Cancer datasets and the SARS-CoV-2 pandemic: establishing principles for collaboration
, ESMO Open, Vol: 5, Pages: 1-3, ISSN: 2059-7029 -
Journal articleDocherty AB, Harrison EM, Green CA, et al., 2020,
Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study
, BMJ, Vol: 369, Pages: 1-12, ISSN: 1759-2151Objective To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase of the first wave of this outbreak who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study, and to explore risk factors associated with mortality in hospital.Design Prospective observational cohort study with rapid data gathering and near real time analysis.Setting 208 acute care hospitals in England, Wales, and Scotland between 6 February and 19 April 2020. A case report form developed by ISARIC and WHO was used to collect clinical data. A minimal follow-up time of two weeks (to 3 May 2020) allowed most patients to complete their hospital admission.Participants 20 133 hospital inpatients with covid-19.Main outcome measures Admission to critical care (high dependency unit or intensive care unit) and mortality in hospital.Results The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity. Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date. 17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to receive
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Journal articlede Lusignan S, Carlyon T, Lalvani A, 2020,
COVID-19: REMOTE ASSESSMENT IN PRIMARY CARE Removing the handle of the Broad Street pump: measures to slow the spread of covid-19 in primary care teams
, BMJ-BRITISH MEDICAL JOURNAL, Vol: 369, Pages: 1-1, ISSN: 1756-1833 -
Journal articleGoya S, Galiano M, Nauwelaers I, et al., 2020,
Toward unified molecular surveillance of RSV: A proposal for genotype definition
, Influenza and Other Respiratory Viruses, Vol: 14, Pages: 274-285, ISSN: 1750-2640BackgroundHuman respiratory syncytial virus (RSV) is classified into antigenic subgroups A and B. Thirteen genotypes have been defined for RSV‐A and 20 for RSV‐B, without any consensus on genotype definition.MethodsWe evaluated clustering of RSV sequences published in GenBank until February 2018 to define genotypes by using maximum likelihood and Bayesian phylogenetic analyses and average p‐distances.ResultsWe compared the patterns of sequence clustering of complete genomes; the three surface glycoproteins genes (SH, G, and F, single and concatenated); the ectodomain and the 2nd hypervariable region of G gene. Although complete genome analysis achieved the best resolution, the F, G, and G‐ectodomain phylogenies showed similar topologies with statistical support comparable to complete genome. Based on the widespread geographic representation and large number of available G‐ectodomain sequences, this region was chosen as the minimum region suitable for RSV genotyping. A genotype was defined as a monophyletic cluster of sequences with high statistical support (≥80% bootstrap and ≥0.8 posterior probability), with an intragenotype p‐distance ≤0.03 for both subgroups and an intergenotype p‐distance ≥0.09 for RSV‐A and ≥0.05 for RSV‐B. In this work, the number of genotypes was reduced from 13 to three for RSV‐A (GA1‐GA3) and from 20 to seven for RSV‐B (GB1‐GB7). Within these, two additional levels of classification were defined: subgenotypes and lineages. Signature amino acid substitutions to complement this classification were also identified.ConclusionsWe propose an objective protocol for RSV genotyping suitable for adoption as an international standard to support the global expansion of RSV molecular surveillance.
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Journal articleHay JA, Minter A, Ainslie KEC, et al., 2020,
An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver
, PLOS COMPUTATIONAL BIOLOGY, Vol: 16, ISSN: 1553-734X- Author Web Link
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- Citations: 8
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