ArticleFrontiers in cellular and infection microbiology2022
Metabolomic profiling of exhaled breath condensate for the diagnosis of pulmonary aspergillosis.
Article in Frontiers in cellular and infection microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Exhaled breath condensate metabolomics reveals inflammation-associated metabolic alterations and metabolites with possible relevance to virulence-related processes in pulmonary cryptococcosis.Frontiers in cellular and infection microbiology · 2026Article
- Unlocking the Secrets: Causal Associations Between Blood Metabolites and Aspergillosis.Current microbiology · 2025Article
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Abstract
Objective: This study aims to ascertain the unique metabolic profile of exhaled breath condensate (EBC) samples in pulmonary aspergillosis (PA) patients, and explore their usefulness for the diagnosis of PA. Methods: A total of 133 patients were included in the study, including 66 PA patients (invasive pulmonary aspergillosis, n=3; chronic pulmonary aspergillosis, n=60; allergic bronchopulmonary aspergillosis, n=3) and controls (n=67). Ultra high-performance liquid chromatography coupled with high-resolution mass spectrometry(UHPLC-HRMS) was used to analyze EBC samples. Metabolic profiling of EBC samples that were collected from 22 CPA patients at various times during treatment (before treatment, <1 month, 1-2 months, 2-3 months, 3-6 months, and ≥6 months after treatment initiation) were performed using UHPLC-HRMS. Potential biomarkers were evaluated using cluster analysis, Venn diagram and receiver operating characteristic analysis (ROC). Results: A total of 47 metabolites of potential interest were detected in the EBC samples. Further investigation showed that Asperpyrone C, Kotanin, Terphenyllin, Terrelumamide B, and Cyclotryprostatin D could be used as a diagnostic biomarker for PA. The classification between metabolic profiling of EBC samples from PA patients and controls was good with a sensitivity of 100%, specificity 89.6% for patients with PA, respectively. Venn diagram analysis of these biomarker candidates displayed three main types of compounds, which could be used for the further discrimination of aspergilloma and chronic cavitary PA. In addition, antifungal treatment had a limited influence on the value of the EBC results. Conclusions: This metabolomic approach using UHPLC-HRMS could be used as a noninvasive method for the diagnosis of PA.
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