A four-gene signature from blood to exclude bacterial etiology of lower respiratory tract infection in adults

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.

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Publication Details

Journal
Nature Communications
Published
2025-11-24
DOI
https://doi.org/10.1038/s41467-025-65361-3
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
0.00

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article

A four-gene signature from blood to exclude bacterial etiology of lower respiratory tract infection in adults

Angela R Branche, Daniel P. Croft, Soumyaroop Bhattacharya, Michael Peasley et al.
Nature Communications
Gut microbiota and health
article

A four-gene signature from blood to exclude bacterial etiology of lower respiratory tract infection in adults

Angela R Branche, Daniel P. Croft, Soumyaroop Bhattacharya, Michael Peasley, Derick R. Peterson, Andrea Baran, John M. Ashton, Edward E. Walsh, Chin‐Yi Chu, Anthony Corbett, Thomas J. Mariani, Ann Regina Falsey
article en

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.

Nature CommunicationsVol. 16(1)
The Harley School (US), University of Rochester Medical Center (US), University of Rochester (US)
Georgia Clinical and Translational Science Alliance, National Institutes of Health, Medical Center, University of Rochester, National Institute of Allergy and Infectious Diseases, National Center for Advancing Translational Sciences
Openalex Percentile: Top 68%
Gut microbiota and health
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