Respiratory infections caused by Pseudomonas aeruginosa and Staphylococcus aureus are the leading cause of morbidity and mortality in cystic fibrosis (CF) patients. The authors aimed to identify volatile biomarkers from bronchoalveolar lavage (BAL) samples that can guide breath biomarker development for pathogen identification. BAL samples (n = 154) from CF patients were analyzed using two-dimensional gas chromatography time-of-flight mass spectrometry. Random Forest was used to select suites of volatiles for identifying P. aeruginosa-positive and S. aureus-positive samples using multiple infection scenarios and validated using test sets. Using nine volatile molecules, we differentiated P. aeruginosa-positive (n = 7) from P. aeruginosa-negative (n = 53) samples with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI 0.71-1.00) and with positive and negative predictive values of 0.67 (95% CI 0.38-0.75) and 0.92 (95% CI 0.88-1.00), respectively. We were also able to discriminate S. aureus-positive (n = 15) from S. aureus-negative (n = 45) samples with an AUROC of 0.88 (95% CI 0.79-1.00) using eight volatiles and with positive and negative predictive values of 0.86 (95% CI 0.61-0.96) and 0.70 (95% CI 0.61-0.75), respectively. Prospective validation of identified biomarkers as screening tools in patient breath may lead to clinical application.
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