| Title: |
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 |
| Authors: |
Max Foxley-Marrable, Leon D’Cruz, Paul Meredith, Sharon Glaysher, Angela H. Beckett, Salman Goudarzi, Christopher Fearn, Kate F. Cook, Katie F. Loveson, Hannah Dent, Hannah Paul, Scott Elliott, Sarah Wyllie, Allyson Lloyd, Kelly Bicknell, Sally Lumley, James McNicholas, David Prytherch, Andrew Lundgren, Or Graur, Anoop J. Chauhan, Samuel C. Robson |
| Source: |
PLoS ONE, Vol 18, Iss 3 (2023) |
| Publisher Information: |
Public Library of Science (PLoS), 2023. |
| Publication Year: |
2023 |
| Collection: |
LCC:Medicine
LCC:Science |
| Subject Terms: |
Medicine, Science |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1932-6203 |
| Relation: |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035897/?tool=EBI; https://doaj.org/toc/1932-6203 |
| Access URL: |
https://doaj.org/article/aef3f15c194b44b9958937b4fc1f35ba |
| Accession Number: |
edsdoj.f3f15c194b44b9958937b4fc1f35ba |
| Database: |
Directory of Open Access Journals |
