ArticleScientific reports2023
Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 9 citations in OpenAlex.
- A Nomogram Integrating CD169%, Neutrophil CD64 Index, and C-Reactive Protein for Differential Diagnosis of Mixed Respiratory Tract Infections.Diagnostics (Basel, Switzerland) · 2026Article
- Host gene expression analysis in the detection of bacterial and viral etiology in children hospitalized with a suspected severe infection.Communications medicine · 2026Article
- Early diagnosis and treatment of leptospirosis: Optimizing clinical outcomes.The Journal of infection · 2026Review
- Exploring Ebola virus-associated gene expression through comparative analysis.Frontiers in genetics · 2026Article
- Host- and pathogen-related determinants of pulmonaryEuropean respiratory review : an official journal of the European Respiratory Society · 2026Review
- Academic global health collaboration: the Ruhuna-Duke partnership.Global health action · 2025Article
- A four-gene signature from blood to exclude bacterial etiology of lower respiratory tract infection in adults.Nature communications · 2025Article
- Antibiotics for Paediatric Community-Acquired Pneumonia: What is the Optimal Course Duration?Paediatric drugs · 2025Review
- A Four-Gene Signature from Blood to Exclude Bacterial Etiology of Lower Respiratory Tract Infection in Adults.Research square · 2025Article
- Development of a host-signature-based machine learning model to diagnose bacterial and viral infections in febrile children.Frontiers in pediatrics · 2025Article
- Article
Corrections and comments
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Authors and funding
31 authors at 13 institutions in 5 countries.
Funding
Abstract
Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.
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