BACKGROUND: Metabolomics could provide new insights into the pathophysiology of cystic fibrosis (CF) by identifying profiles of endogenous metabolites. OBJECTIVES: To investigate whether metabolomics of exhaled breath condensate could discriminate between patients with unstable CF, stable CF and healthy subjects, and whether selected metabolites were responsible for between-group differences. METHODS: Twenty-nine patients with stable CF, 24 with unstable CF and 31 healthy subjects (age 9-24 years) participated in a cross-sectional study. Metabolomics was performed with high-resolution nuclear magnetic resonance spectroscopy. Partial least squares-discriminant analysis was used as classifier. The results were validated in a second independent study. RESULTS: Intraclass correlation coefficients for between-day and technical repeatability were 0.93 and 0.96, respectively. Bland-Altman analysis showed good within-day repeatability. Correct classification rate of CF (n=53) vs. healthy subjects (n=31) was 96% (R2=0.84; Q2=0.79). Model validation with a testing sample set obtained from subjects not included in the primary analysis (23 CF and 25 healthy subjects) showed a sensitivity of 91% and a specificity of 96%. The classification rate of stable CF (n=29) vs. unstable CF patients (n=24) was 95% (R2=0.82; Q2=0.78). Model external validation in 14 patients with stable CF and 16 with unstable CF showed a sensitivity of 86% and a specificity of 94%. Ethanol, acetate, 2-propanol and acetone were most discriminant between patients with CF and healthy subjects, whereas acetate, ethanol, 2-propanol and methanol were the most important metabolites for discriminating between patients with stable and unstable CF. CONCLUSIONS: Nuclear magnetic resonance spectroscopy of exhaled breath condensate is reproducible, discriminates patients with CF from healthy subjects and patients with unstable CF from those with stable CF, and identifies the metabolites responsible for between-group differences.
BACKGROUND: Metabolomics could provide new insights into the pathophysiology of cystic fibrosis (CF) by identifying profiles of endogenous metabolites. OBJECTIVES: To investigate whether metabolomics of exhaled breath condensate could discriminate between patients with unstable CF, stable CF and healthy subjects, and whether selected metabolites were responsible for between-group differences. METHODS: Twenty-nine patients with stable CF, 24 with unstable CF and 31 healthy subjects (age 9-24 years) participated in a cross-sectional study. Metabolomics was performed with high-resolution nuclear magnetic resonance spectroscopy. Partial least squares-discriminant analysis was used as classifier. The results were validated in a second independent study. RESULTS: Intraclass correlation coefficients for between-day and technical repeatability were 0.93 and 0.96, respectively. Bland-Altman analysis showed good within-day repeatability. Correct classification rate of CF (n=53) vs. healthy subjects (n=31) was 96% (R2=0.84; Q2=0.79). Model validation with a testing sample set obtained from subjects not included in the primary analysis (23 CF and 25 healthy subjects) showed a sensitivity of 91% and a specificity of 96%. The classification rate of stable CF (n=29) vs. unstable CF patients (n=24) was 95% (R2=0.82; Q2=0.78). Model external validation in 14 patients with stable CF and 16 with unstable CF showed a sensitivity of 86% and a specificity of 94%. Ethanol, acetate, 2-propanol and acetone were most discriminant between patients with CF and healthy subjects, whereas acetate, ethanol, 2-propanol and methanol were the most important metabolites for discriminating between patients with stable and unstable CF. CONCLUSIONS: Nuclear magnetic resonance spectroscopy of exhaled breath condensate is reproducible, discriminates patients with CF from healthy subjects and patients with unstable CF from those with stable CF, and identifies the metabolites responsible for between-group differences.
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