Gene Expression Risk Scores for COVID-19 Illness Severity.
J Infect Dis
; 227(3): 322-331, 2023 02 01.
Article
en En
| MEDLINE
| ID: mdl-34850892
ABSTRACT
BACKGROUND:
The correlates of coronavirus disease 2019 (COVID-19) illness severity following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are incompletely understood.METHODS:
We assessed peripheral blood gene expression in 53 adults with confirmed SARS-CoV-2 infection clinically adjudicated as having mild, moderate, or severe disease. Supervised principal components analysis was used to build a weighted gene expression risk score (WGERS) to discriminate between severe and nonsevere COVID-19.RESULTS:
Gene expression patterns in participants with mild and moderate illness were similar, but significantly different from severe illness. When comparing severe versus nonsevere illness, we identified >4000 genes differentially expressed (false discovery rate < 0.05). Biological pathways increased in severe COVID-19 were associated with platelet activation and coagulation, and those significantly decreased with T-cell signaling and differentiation. A WGERS based on 18 genes distinguished severe illness in our training cohort (cross-validated receiver operating characteristic-area under the curve [ROC-AUC] = 0.98), and need for intensive care in an independent cohort (ROC-AUC = 0.85). Dichotomizing the WGERS yielded 100% sensitivity and 85% specificity for classifying severe illness in our training cohort, and 84% sensitivity and 74% specificity for defining the need for intensive care in the validation cohort.CONCLUSIONS:
These data suggest that gene expression classifiers may provide clinical utility as predictors of COVID-19 illness severity.Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
COVID-19
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Adult
/
Humans
Idioma:
En
Revista:
J Infect Dis
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos