The P323L substitution in the SARS-CoV-2 polymerase (NSP12) confers a selective advantage during infection

Background: The mutational landscape of SARS-CoV-2 varies at the dominant viral genome sequence and minor genomic variant population. During the COVID-19 pandemic, an early substitution in the genome was the D614G change in the spike protein, associated with an increase in transmissibility. Genomes with D614G are accompanied by a P323L substitution in the viral polymerase (NSP12). However, P323L is not thought to be under strong selective pressure. Results: Investigation of P323L/D614G substitutions in the population shows rapid emergence during the containment phase and early surge phase during the first wave. These substitutions emerge from minor genomic variants which become dominant viral genome sequence. This is investigated in vivo and in vitro using SARS-CoV-2 with P323 and D614 in the dominant genome sequence and L323 and G614 in the minor variant population. During infection, there is rapid selection of L323 into the dominant viral genome sequence but not G614. Reverse genetics is used to create two viruses (either P323 or L323) with the same genetic background. L323 shows greater abundance of viral RNA and proteins and a smaller plaque morphology than P323. Conclusions: These data suggest that P323L is an important contribution in the emergence of variants with transmission advantages. Sequence analysis of viral populations suggests it may be possible to predict the emergence of a new variant based on tracking the frequency of minor variant genomes. The ability to predict an emerging variant of SARS-CoV-2 in the global landscape may aid in the evaluation of medical countermeasures and non-pharmaceutical interventions

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely

Fewer COVID-19 neurological complications with dexamethasone and remdesivir

OBJECTIVE: To assess the impact of treatment with dexamethasone, remdesivir or both on neurological complications in acute COVID-19. METHODS: We used observational data from the International Severe Acute and emerging Respiratory Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK). Hospital inpatients aged ≥18 years with laboratory-confirmed SARS-CoV-2 infection admitted between 31 January 2020 and 29 June 2021 were included. Treatment allocation was non-blinded and performed by reporting clinicians. A propensity scoring methodology was used to minimize confounding. Treatment with remdesivir, dexamethasone or both was assessed against standard of care. The primary outcome was a neurological complication occurring at the point of death, discharge, or resolution of the COVID-19 clinical episode. RESULTS: Out of 89,297 hospital inpatients, 64,088 had severe COVID-19 and 25,209 had non-hypoxic COVID-19. Neurological complications developed in 4.8% and 4.5% respectively. In both groups, neurological complications associated with increased mortality, ICU admission, worse self-care on discharge and time to recovery. In severe COVID-19, treatment with dexamethasone (n=21,129), remdesivir (n=1,428) and both combined (n=10,846) associated with a lower frequency of neurological complications: OR=0.76 (95% CI=0.69-0.83), OR 0.69 (95% CI=0.51-0.90) and OR=0.54, (95% CI=0.47-0.61) respectively. In non-hypoxic COVID-19, dexamethasone (n=2,580) associated with less neurological complications (OR=0.78, 95% CI 0.62-0.97), while the dexamethasone/remdesivir combination (n=460) showed a similar trend (OR=0.63, 95% CI=0.31-1.15). INTERPRETATION: Treatment with dexamethasone, remdesivir or both in patients hospitalised with COVID-19 associated with a lower frequency of neurological complications in an additive manner, such that the greatest benefit was observed in patients who received both drugs together. This article is protected by copyright. All rights reserved

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England

BACKGROUND: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient's "bed pathway" - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. METHODS: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. RESULTS: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: "Ward, CC, Ward", "Ward, CC", "CC" and "CC, Ward". Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. CONCLUSIONS: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. TRIAL REGISTRATION: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR

Adeno-associated virus 2 infection in children with non-A–E hepatitis

Funding Information: We wish to acknowledge the contribution of the participating children and their parents who agreed to participate in the ISARIC CCP-UK and DIAMONDS studies, and the research teams who recruited the patients; S. Bennett-Slater from NHS Greater Glasgow and Clyde for assisting with sample location and testing; the histopathology team, Veterinary Diagnostic, University of Glasgow, for excellent technical assistance; P. Murcia for providing resources and advice; P. Olmo for administrative assistance; and E. J. Kremer from the Institut de Génétique Moléculaire de Montpellier, Université de Montpellier and A. Baker, University of Edinburgh, for advice. The work was funded by Public Health Scotland, the National Institute for Health Research (NIHR; award CO-CIN-01) and the Medical Research Council (MRC; grants MR/X010252/1, MC_UU_1201412, MC_UU_12018/12, MC_PC_19059, MC_PC_19025 and MC_PC_22004). DIAMONDS is funded by the European Union Horizon 2020 programme; grant 848196). M.P. acknowledges funding support from the Wellcome Trust (206369/Z/17/Z). M.G.S. acknowledges funding support from The Pandemic Institute, Liverpool and the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, and UK Health Security Agency. J.K.B. acknowledges funding support from a Wellcome Trust Senior Research Fellowship (223164/Z/21/Z), and MC_PC_20029, Sepsis Research (Fiona Elizabeth Agnew Trust), a BBSRC Institute Strategic Programme Grant to the Roslin Institute (BB/P013732/1, BB/P013759/1), and the Intensive Care Society of the United Kingdom. We acknowledge the support of Baillie Gifford and the Baillie Gifford Science Pandemic Hub at the University of Edinburgh. Parts of this research has been conducted using the UK Biobank Resource under project 788 and we would like to acknowledge the assistance of A. Tenesa in making this possible. Additional replication was also conducted using the UK Biobank Resource (Project 26041). This research was also funded by the National Institute for Health and Care Research (CO-CIN-01) and jointly by NIHR and UK Research and Innovation (CV220-169, MC_PC_19059). The views expressed in this article are those of the author(s) and not necessarily those of UKRI, the NIHR, or the Department of Health and Social Care. We also acknowledge the support of NHS Research Scotland (NRS) Greater Glasgow and Clyde Biorepository team. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Funding Information: We wish to acknowledge the contribution of the participating children and their parents who agreed to participate in the ISARIC CCP-UK and DIAMONDS studies, and the research teams who recruited the patients; S. Bennett-Slater from NHS Greater Glasgow and Clyde for assisting with sample location and testing; the histopathology team, Veterinary Diagnostic, University of Glasgow, for excellent technical assistance; P. Murcia for providing resources and advice; P. Olmo for administrative assistance; and E. J. Kremer from the Institut de Génétique Moléculaire de Montpellier, Université de Montpellier and A. Baker, University of Edinburgh, for advice. The work was funded by Public Health Scotland, the National Institute for Health Research (NIHR; award CO-CIN-01) and the Medical Research Council (MRC; grants MR/X010252/1, MC_UU_1201412, MC_UU_12018/12, MC_PC_19059, MC_PC_19025 and MC_PC_22004). DIAMONDS is funded by the European Union Horizon 2020 programme; grant 848196). M.P. acknowledges funding support from the Wellcome Trust (206369/Z/17/Z). M.G.S. acknowledges funding support from The Pandemic Institute, Liverpool and the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, and UK Health Security Agency. J.K.B. acknowledges funding support from a Wellcome Trust Senior Research Fellowship (223164/Z/21/Z), and MC_PC_20029, Sepsis Research (Fiona Elizabeth Agnew Trust), a BBSRC Institute Strategic Programme Grant to the Roslin Institute (BB/P013732/1, BB/P013759/1), and the Intensive Care Society of the United Kingdom. We acknowledge the support of Baillie Gifford and the Baillie Gifford Science Pandemic Hub at the University of Edinburgh. Parts of this research has been conducted using the UK Biobank Resource under project 788 and we would like to acknowledge the assistance of A. Tenesa in making this possible. Additional replication was also conducted using the UK Biobank Resource (Project 26041). This research was also funded by the National Institute for Health and Care Research (CO-CIN-01) and jointly by NIHR and UK Research and Innovation (CV220-169, MC_PC_19059). The views expressed in this article are those of the author(s) and not necessarily those of UKRI, the NIHR, or the Department of Health and Social Care. We also acknowledge the support of NHS Research Scotland (NRS) Greater Glasgow and Clyde Biorepository team. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Publisher Copyright: © 2023, The Author(s), under exclusive licence to Springer Nature Limited.An outbreak of acute hepatitis of unknown aetiology in children was reported in Scotland 1 in April 2022 and has now been identified in 35 countries2. Several recent studies have suggested an association with human adenovirus with this outbreak, a virus not commonly associated with hepatitis. Here we report a detailed case–control investigation and find an association between adeno-associated virus 2 (AAV2) infection and host genetics in disease susceptibility. Using next-generation sequencing, PCR with reverse transcription, serology and in situ hybridization, we detected recent infection with AAV2 in plasma and liver samples in 26 out of 32 (81%) cases of hepatitis compared with 5 out of 74 (7%) of samples from unaffected individuals. Furthermore, AAV2 was detected within ballooned hepatocytes alongside a prominent T cell infiltrate in liver biopsy samples. In keeping with a CD4+ T-cell-mediated immune pathology, the human leukocyte antigen (HLA) class II HLA-DRB1*04:01 allele was identified in 25 out of 27 cases (93%) compared with a background frequency of 10 out of 64 (16%; P = 5.49 × 10−12). In summary, we report an outbreak of acute paediatric hepatitis associated with AAV2 infection (most likely acquired as a co-infection with human adenovirus that is usually required as a ‘helper virus’ to support AAV2 replication) and disease susceptibility related to HLA class II status.Peer reviewe

Obesity, Ethnicity, and Risk of Critical Care, Mechanical Ventilation, and Mortality in Patients Admitted to Hospital with COVID-19: Analysis of the ISARIC CCP-UK Cohort

OBJECTIVE: The aim of this study was to investigate the association of obesity with in-hospital coronavirus disease 2019 (COVID-19) outcomes in different ethnic groups. METHODS: Patients admitted to hospital with COVID-19 in the United Kingdom through the Clinical Characterisation Protocol UK (CCP-UK) developed by the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) were included from February 6 to October 12, 2020. Ethnicity was classified as White, South Asian, Black, and other minority ethnic groups. Outcomes were admission to critical care, mechanical ventilation, and in-hospital mortality, adjusted for age, sex, and chronic diseases. RESULTS: Of the participants included, 54,254 (age = 76 years; 45.0% women) were White, 3,728 (57 years; 41.1% women) were South Asian, 2,523 (58 years; 44.9% women) were Black, and 5,427 (61 years; 40.8% women) were other ethnicities. Obesity was associated with all outcomes in all ethnic groups, with associations strongest for black ethnicities. When stratified by ethnicity and obesity status, the odds ratios for admission to critical care, mechanical ventilation, and mortality in black ethnicities with obesity were 3.91 (3.13-4.88), 5.03 (3.94-6.63), and 1.93 (1.49-2.51), respectively, compared with White ethnicities without obesity. CONCLUSIONS: Obesity was associated with an elevated risk of in-hospital COVID-19 outcomes in all ethnic groups, with associations strongest in Black ethnicities

Fitting to the UK COVID-19 outbreak, short-term forecasts and estimating the reproductive number

The COVID-19 pandemic has brought to the fore the need for policy makers to receive timely and ongoing scientific guidance in response to this recently emerged human infectious disease. Fitting mathematical models of infectious disease transmission to the available epidemiological data provides a key statistical tool for understanding the many quantities of interest that are not explicit in the underlying epidemiological data streams. Of these, the effective reproduction number, R, has taken on special significance in terms of the general understanding of whether the epidemic is under control (R < 1). Unfortunately, none of the epidemiological data streams are designed for modelling, hence assimilating information from multiple (often changing) sources of data is a major challenge that is particularly stark in novel disease outbreaks. Here, focusing on the dynamics of the first-wave (March-June 2020), we present in some detail the inference scheme employed for calibrating the Warwick COVID-19 model to the available public health data streams, which span hospitalisations, critical care occupancy, mortality and serological testing. We then perform computational simulations, making use of the acquired parameter posterior distributions, to assess how the accuracy of short-term predictions varied over the timecourse of the outbreak. To conclude, we compare how refinements to data streams and model structure impact estimates of epidemiological measures, including the estimated growth rate and daily incidence

Acute kidney injury in patients hospitalized with COVID-19 from the ISARIC WHO CCP-UK Study: a prospective, multicentre cohort study.

BACKGROUND: Acute kidney injury (AKI) is common in coronavirus disease 2019 (COVID-19). This study investigated adults hospitalized with COVID-19 and hypothesized that risk factors for AKI would include comorbidities and non-White race. METHODS: A prospective multicentre cohort study was performed using patients admitted to 254 UK hospitals with COVID-19 between 17 January 2020 and 5 December 2020. RESULTS: Of 85 687 patients, 2198 (2.6%) received acute kidney replacement therapy (KRT). Of 41 294 patients with biochemistry data, 13 000 (31.5%) had biochemical AKI: 8562 stage 1 (65.9%), 2609 stage 2 (20.1%) and 1829 stage 3 (14.1%). The main risk factors for KRT were chronic kidney disease (CKD) [adjusted odds ratio (aOR) 3.41: 95% confidence interval 3.06-3.81], male sex (aOR 2.43: 2.18-2.71) and Black race (aOR 2.17: 1.79-2.63). The main risk factors for biochemical AKI were admission respiratory rate >30 breaths per minute (aOR 1.68: 1.56-1.81), CKD (aOR 1.66: 1.57-1.76) and Black race (aOR 1.44: 1.28-1.61). There was a gradated rise in the risk of 28-day mortality by increasing severity of AKI: stage 1 aOR 1.58 (1.49-1.67), stage 2 aOR 2.41 (2.20-2.64), stage 3 aOR 3.50 (3.14-3.91) and KRT aOR 3.06 (2.75-3.39). AKI rates peaked in April 2020 and the subsequent fall in rates could not be explained by the use of dexamethasone or remdesivir. CONCLUSIONS: AKI is common in adults hospitalized with COVID-19 and it is associated with a heightened risk of mortality. Although the rates of AKI have fallen from the early months of the pandemic, high-risk patients should have their kidney function and fluid status monitored closely

Obesity, Ethnicity, and Risk of Critical Care, Mechanical Ventilation, and Mortality in Patients Admitted to Hospital with COVID-19: Analysis of the ISARIC CCP-UK Cohort.

OBJECTIVE: The aim of this study was to investigate the association of obesity with in-hospital coronavirus disease 2019 (COVID-19) outcomes in different ethnic groups. METHODS: Patients admitted to hospital with COVID-19 in the United Kingdom through the Clinical Characterisation Protocol UK (CCP-UK) developed by the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) were included from February 6 to October 12, 2020. Ethnicity was classified as White, South Asian, Black, and other minority ethnic groups. Outcomes were admission to critical care, mechanical ventilation, and in-hospital mortality, adjusted for age, sex, and chronic diseases. RESULTS: Of the participants included, 54,254 (age = 76 years; 45.0% women) were White, 3,728 (57 years; 41.1% women) were South Asian, 2,523 (58 years; 44.9% women) were Black, and 5,427 (61 years; 40.8% women) were other ethnicities. Obesity was associated with all outcomes in all ethnic groups, with associations strongest for black ethnicities. When stratified by ethnicity and obesity status, the odds ratios for admission to critical care, mechanical ventilation, and mortality in black ethnicities with obesity were 3.91 (3.13-4.88), 5.03 (3.94-6.63), and 1.93 (1.49-2.51), respectively, compared with White ethnicities without obesity. CONCLUSIONS: Obesity was associated with an elevated risk of in-hospital COVID-19 outcomes in all ethnic groups, with associations strongest in Black ethnicities