Host Transcriptional Signatures Predict Etiology in Community-Acquired Pneumonia: Potential Antibiotic Stewardship Tools

宿主转录组特征预测社区获得性肺炎的病因:潜在的抗生素管理工具

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Abstract

BACKGROUND: Current approaches for pathogen identification in community-acquired pneumonia (CAP) remain suboptimal, leaving most patients without a microbiological diagnosis. If better diagnostic tools were available for differentiating between viral and bacterial CAP, unnecessary antibacterial therapy could be avoided in viral CAP patients. METHODS: In 156 adults hospitalized with CAP classified to have bacterial, viral, or mixed viral-bacterial infection based on microbiological testing or both microbiological testing and procalcitonin (PCT) levels, we aimed to identify discriminatory host transcriptional signatures in peripheral blood samples acquired at hospital admission, by applying Dual-color-Reverse-Transcriptase-Multiplex-Ligation-dependent-Probe-Amplification (dc-RT MLPA). RESULTS: In patients classified by microbiological testing, a 9-transcript signature showed high accuracy for discriminating bacterial from viral CAP (AUC 0.91, 95% CI 0.85-0.96), while a 10-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.91, 95% CI 0.86-0.96). In patients classified by both microbiological testing and PCT levels, a 13-transcript signature showed excellent accuracy for discriminating bacterial from viral CAP (AUC 1.00, 95% CI 1.00-1.00), while a 7-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.93, 95% CI 0.87-0.98). CONCLUSION: Our findings support host transcriptional signatures in peripheral blood samples as a potential tool for guiding clinical decision-making and antibiotic stewardship in CAP.

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