Circulating proteins to predict COVID-19 severity.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
17 04 2023
17 04 2023
Historique:
received:
02
06
2022
accepted:
17
03
2023
medline:
19
4
2023
entrez:
17
4
2023
pubmed:
18
4
2023
Statut:
epublish
Résumé
Predicting COVID-19 severity is difficult, and the biological pathways involved are not fully understood. To approach this problem, we measured 4701 circulating human protein abundances in two independent cohorts totaling 986 individuals. We then trained prediction models including protein abundances and clinical risk factors to predict COVID-19 severity in 417 subjects and tested these models in a separate cohort of 569 individuals. For severe COVID-19, a baseline model including age and sex provided an area under the receiver operator curve (AUC) of 65% in the test cohort. Selecting 92 proteins from the 4701 unique protein abundances improved the AUC to 88% in the training cohort, which remained relatively stable in the testing cohort at 86%, suggesting good generalizability. Proteins selected from different COVID-19 severity were enriched for cytokine and cytokine receptors, but more than half of the enriched pathways were not immune-related. Taken together, these findings suggest that circulating proteins measured at early stages of disease progression are reasonably accurate predictors of COVID-19 severity. Further research is needed to understand how to incorporate protein measurement into clinical care.
Identifiants
pubmed: 37069249
doi: 10.1038/s41598-023-31850-y
pii: 10.1038/s41598-023-31850-y
pmc: PMC10107586
doi:
Substances chimiques
Proteins
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
6236Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : U24 CA224319
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK124165
Pays : United States
Organisme : Medical Research Council
Pays : United Kingdom
Organisme : Bill & Melinda Gates Foundation
ID : INV-017895
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA196521
Pays : United States
Organisme : Department of Health
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C18281/A29019
Pays : United Kingdom
Informations de copyright
© 2023. The Author(s).
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