Superiority of transcriptional profiling over procalcitonin for distinguishing bacterial from viral lower respiratory tract infections in hospitalized adults

Abstract

Background. Distinguishing between bacterial and viral lower respiratory tract infection (LRTI) remains challenging. Transcriptional profiling is a promising tool for improving diagnosis in LRTI. Methods. We performed whole blood transcriptional analysis in 118 patients (median age [interquartile range], 61 [50-76] years) hospitalized with LRTI and 40 age-matched healthy controls (median age, 60 [46-70] years). We applied class comparisons, modular analysis, and class prediction algorithms to identify and validate diagnostic biosignatures for bacterial and viral LRTI. Results. Patients were classified as having bacterial (n = 22), viral (n = 71), or bacterial-viral LRTI (n = 25) based on comprehensive microbiologic testing. Compared with healthy controls, statistical group comparisons (P bacterial-viral > viral), and those with viral LRTI displayed significantly greater overexpression of interferon genes (viral > bacterial-viral > bacterial). The K-nearest neighbors algorithm identified 10 classifier genes that discriminated between bacterial and viral LRTI with a 95% sensitivity (95% confidence interval, 77%-100%) and 92% specificity (77%-98%), compared with a sensitivity of 38% (18%-62%) and a specificity of 91% (76%-98%) for procalcitonin. Conclusions. Transcriptional profiling is a helpful tool for diagnosis of LRTI.