TY - JOUR
T1 - Combining viral genomics and clinical data to assess risk factors for severe COVID-19 (mortality, ICU admission, or intubation) amongst hospital patients in a large acute UK NHS hospital Trust
AU - The COVID-19 Genomics UK (COG-UK) Consortium
AU - Foxley-Marrable, Max
AU - D'Cruz, Leon
AU - Meredith, Paul
AU - Glaysher, Sharon
AU - Beckett, Angela H
AU - Goudarzi, Salman
AU - Fearn, Christopher
AU - Cook, Kate F
AU - Loveson, Katie F
AU - Dent, Hannah
AU - Paul, Hannah
AU - Elliott, Scott
AU - Wyllie, Sarah
AU - Lloyd, Allyson
AU - Bicknell, Kelly
AU - Lumley, Sally
AU - McNicholas, James
AU - Prytherch, David
AU - Lundgren, Andrew
AU - Graur, Or
AU - Chauhan, Anoop J
AU - Robson, Samuel C
AU - Bashton, Matthew
AU - Smith, Darren
AU - Nelson, Andrew
AU - Young, Gregory R.
N1 - Matthew Bashton, Andrew Nelson, Clare McCann, Greg Young and Darren Smith are members of the COVID-19 Genomics UK consortium.
This work was primarily funded by the COVID-19 Genomics UK (COG-UK) consortium (https://www.cogconsortium.uk/), under their Internal Principal Investigator Research Funding Scheme. COG-UK is supported by funding from the Medical Research Council (MRC; https://www.ukri.org/councils/mrc/) part of UK Research & Innovation (UKRI; https://www.ukri.org/), the National Institute of Health Research (NIHR; https://www.nihr.ac.uk/) [grant code: MC_PC_19027], and Genome Research Limited, operating as the Wellcome Sanger Institute (https://www.sanger.ac.uk/). The authors acknowledge the use of data generated through the COVID-19 Genomics Programme funded by the Department of Health and Social Care (DHSC; https://www.gov.uk/government/organisations/department-of-health-and-social-care). The views expressed are those of the author and not necessarily those of the Department of Health and Social Care or PHE or UKHSA. MFM, AL, and OG were also supported by a UKRI Science & Technology Facilities Council (STFC) Impact Accelerator Account awarded to the Institute of Cosmology and Gravitation (ICG) at the University of Portsmouth. Additional funding for the project came from the University of Portsmouth Faculty of Science and Health (https://www.port.ac.uk/about-us/structure-and-governance/organisational-structure/our-academic-structure/faculty-of-science-and-health), and the Wessex Academic Health Sciences Centre (AHSC; https://wessexahsn.org.uk/). In addition, SCR and AHB are funded by Research England’s Expanding Excellence in England (E3) Fund.
PY - 2023/3/23
Y1 - 2023/3/23
N2 - Throughout the COVID-19 pandemic, valuable datasets have been collected on the effects of the virus SARS-CoV-2. In this study, we combined whole genome sequencing data with clinical data (including clinical outcomes, demographics, comorbidity, treatment information) for 929 patient cases seen at a large UK hospital Trust between March 2020 and May 2021. We identified associations between acute physiological status and three measures of disease severity; admission to the intensive care unit (ICU), requirement for intubation, and mortality. Whilst the maximum National Early Warning Score (NEWS2) was moderately associated with severe COVID-19 (A = 0.48), the admission NEWS2 was only weakly associated (A = 0.17), suggesting it is ineffective as an early predictor of severity. Patient outcome was weakly associated with myriad factors linked to acute physiological status and human genetics, including age, sex and pre-existing conditions. Overall, we found no significant links between viral genomics and severe outcomes, but saw evidence that variant subtype may impact relative risk for certain sub-populations. Specific mutations of SARS-CoV-2 appear to have little impact on overall severity risk in these data, suggesting that emerging SARS-CoV-2 variants do not result in more severe patient outcomes. However, our results show that determining a causal relationship between mutations and severe COVID-19 in the viral genome is challenging. Whilst improved understanding of the evolution of SARS-CoV-2 has been achieved through genomics, few studies on how these evolutionary changes impact on clinical outcomes have been seen due to complexities associated with data linkage. By combining viral genomics with patient records in a large acute UK hospital, this study represents a significant resource for understanding risk factors associated with COVID-19 severity. However, further understanding will likely arise from studies of the role of host genetics on disease progression.
AB - Throughout the COVID-19 pandemic, valuable datasets have been collected on the effects of the virus SARS-CoV-2. In this study, we combined whole genome sequencing data with clinical data (including clinical outcomes, demographics, comorbidity, treatment information) for 929 patient cases seen at a large UK hospital Trust between March 2020 and May 2021. We identified associations between acute physiological status and three measures of disease severity; admission to the intensive care unit (ICU), requirement for intubation, and mortality. Whilst the maximum National Early Warning Score (NEWS2) was moderately associated with severe COVID-19 (A = 0.48), the admission NEWS2 was only weakly associated (A = 0.17), suggesting it is ineffective as an early predictor of severity. Patient outcome was weakly associated with myriad factors linked to acute physiological status and human genetics, including age, sex and pre-existing conditions. Overall, we found no significant links between viral genomics and severe outcomes, but saw evidence that variant subtype may impact relative risk for certain sub-populations. Specific mutations of SARS-CoV-2 appear to have little impact on overall severity risk in these data, suggesting that emerging SARS-CoV-2 variants do not result in more severe patient outcomes. However, our results show that determining a causal relationship between mutations and severe COVID-19 in the viral genome is challenging. Whilst improved understanding of the evolution of SARS-CoV-2 has been achieved through genomics, few studies on how these evolutionary changes impact on clinical outcomes have been seen due to complexities associated with data linkage. By combining viral genomics with patient records in a large acute UK hospital, this study represents a significant resource for understanding risk factors associated with COVID-19 severity. However, further understanding will likely arise from studies of the role of host genetics on disease progression.
KW - Humans
KW - COVID-19/epidemiology
KW - SARS-CoV-2/genetics
KW - Pandemics
KW - State Medicine
KW - Trust
KW - Intensive Care Units
KW - Risk Factors
KW - Hospitals
KW - Intubation, Intratracheal
KW - United Kingdom/epidemiology
UR - http://www.scopus.com/inward/record.url?scp=85150726593&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0283447
DO - 10.1371/journal.pone.0283447
M3 - Article
C2 - 36952555
SN - 1932-6203
VL - 18
JO - PLoS One
JF - PLoS One
IS - 3
M1 - e0283447
ER -