Minimalistic transcriptomic signatures permit accurate early prediction of COVID-19 mortality.
Ontology highlight
ABSTRACT: BACKGROUNDAccurate prognostic assays for COVID-19 represent an unmet clinical need. We sought to identify and validate early parsimonious transcriptomic signatures that accurately predict fatal outcomes.METHODSWe studied 894 patients enrolled in the prospective, multicenter Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) with peripheral blood mononuclear cells (PBMC) and nasal swabs collected within 48 hours of admission. Host gene expression was measured with RNA-Seq. We trained parsimonious prognostic classifiers incorporating host gene expression, age, and SARS-CoV-2 viral load to predict 28-day mortality in 70% of the cohort. Classifier performance was determined in the remaining 30% and externally validated in a contemporary COVID-19 cohort (n = 137) with vaccinated patient
SUBMITTER: Narendra R
PROVIDER: S-EPMC12643502 | biostudies-literature | 2025 Nov
REPOSITORIES: biostudies-literature
ACCESS DATA