Nat Commun. 2025 Nov 24;16(1):10383. doi: 10.1038/s41467-025-65361-3.
ABSTRACT
Unnecessary antibiotic use is a major driver of antimicrobial resistance, an urgent public health threat. Acute respiratory infection (ARI) is a leading cause of inappropriate antibiotic use, creating an unmet need for improved diagnostics to identify bacterial etiology in ARI. In this work we show a 4-gene signature defining the absence of bacterial ARI which may be useful for managing antibiotics in ARI. Hospitalized adults with ARI underwent comprehensive microbiologic testing and those with definitive viral (n = 280), bacterial (n = 129), or mixed viral-bacterial infection (n = 95) had whole blood RNA sequencing. A hard-thresholded, mostly relaxed, LASSO-constrained logistic regression model is used to select a parsimonious gene set (ITGB4, ITGA7, IFI27, FAM20A) highly capable of discriminating any bacterial from nonbacterial infection (cross-validated AUC = 0.90). The 4-gene signature is validated in five independent adult RNAseq cohorts (AUC = 0.89-0.98), two adult microarray cohorts (AUC = 0.73-0.90), and one pediatric pneumonia RNAseq cohort (AUC 0.74). Thresholding the 4-gene risk score to yield 90% sensitivity to detect bacterial infection results in 71% specificity and 91% negative predictive value.
PMID:41285807 | DOI:10.1038/s41467-025-65361-3
