Exhaled Breath Condensate Cystic Fibrosis Markers Through the Eye of High Resolution Mass Spectrometry

XIAOLING ZANG; MARÍA EUGENIA MONGE; NAEL A. MCCARTY; ARLENE A. STECENKO; FACUNDO M. FERNÁNDEZ

Providence

Conferencia; SciX 2015; 2015

The Federation of Analytical Chemistry and Spectroscopy Societies

Progressive lung function decline from in cystic fibrosis (CF) often does not proceed in a linear fashion, rather is punctuated by acute pulmonary exacerbations (APEs). The frequency of APEs severe enough to require hospitalization is a crucial factor that may contribute to death from CF. APE diagnosis remains challenging due to changes in patient symptoms over time, as observed by the attending clinician. Reliable measurements to predict oncoming APEs would enable early clinical intervention and potentially prevent loss of lung function. Herein we address this issue using ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry and a supervised classification model to profile and identify metabolites in exhaled breath condensate (EBC) samples, thereby facilitating discrimination of pre-APE patient samples from stable CF patient samples. EBC samples from 4 pre-APE patients (CF patients 1 to 3 months before an APE) and 19 stable CF patients (EBC samples from CF subjects who are clinically stable without an APE for ≥3 months) were profiled using a Waters ACQUITY Ultra Performance liquid chromatograph coupled to a Xevo G2 quadrupole-time-of-flight mass spectrometer (QTof-MS) . A total of 389 spectral features (Rt, m/z pairs) were quantitatively detected in EBC metabolome profiles from the cohort. Out of the 389 spectral features, 174 were present in at least 50% of pre-APE or stable CF patient samples. Twenty-seven out of these 174 spectral features had tentative endogenous identities after searching through databases. Reverse interval PLSDA feature selection was performed on the 27 tentatively identified spectral features, which resulted in the selection of 8 discriminant features. The 8 discriminant features tentatively identified comprised a metabolic profile that distinguished the 4 pre-APE EBC samples from the 19 stable EBC samples with excellent accuracy, specificity and sensitivity using the oPLSDA model. Three of the key differentiating metabolites were tentatively identified as lactic acid, pterins and their derivatives, and eicosanoids and their metabolites. These 3 metabolites were all elevated in pre-APE patient EBC samples, compared to stable CF patient EBC samples. Interestingly, lactic acid has been reported to be elevated in the bronchoalveolar lavage fluid (BALF) of CF patients, relative to control subjects. Novel aspect (Limit 20 words) High classification accuracy suggests this approach is a promising tool for the reliable prediction of the onset of an APE.