MSACL 2018 US Abstract

Topic: Metabolomics

Early Detection of Cystic Fibrosis Acute Pulmonary Exacerbations by Exhaled Breath Condensate Metabolomics

Facundo Fernández (Presenter)
Georgia Institute of Technology

Authorship: Xiaoling Zang(1), María Eugenia Monge(1,2), Nael A. McCarty(3), Arlene Stecenko(3), Facundo M. Fernández(1)
(1) School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta GA 30332, USA (2) Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina (3) Emory+Children's Center for Cystic Fibrosis and Airways Disease Research and Department of Pediatrics, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, GA 30322, USA

Short Abstract Progressive lung function decline in cystic fibrosis (CF) patients 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 of death in CF patients and the diagnosis remains challenging. The objective of this research is to develop reliable methods to predict oncoming APEs in order to prevent associated lung function loss, mortality and morbidity. In this study, non-targeted metabolomics profiling of exhaled breath condensate (EBC) samples from 36 pre-APE (CF patients 1 to 3 months before an APE) and 97 stable CF patients (CF subjects who are clinically stable without an APE for ≥3 months) was performed using ultra performance liquid chromatography coupled to ultra-high resolution accurate mass high-field Orbitrap mass spectrometry. A supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model, was able to distinguish pre-APE from stable CF samples with good accuracy (88.5-89.7%), sensitivity (81.0-84.6%) and specificity (89.6-93.6%), suggesting significant alterations in epithelial lining lung fluid monitored through EBC could be useful to detect APEs early, therefore improving patient outcomes.

Long Abstract

Progressive lung function decline in cystic fibrosis (CF) patients 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 of death in CF patients and the diagnosis remains challenging. The objective of this research is to develop reliable methods to predict oncoming APEs in order to prevent associated lung function loss, mortality and morbidity. In this study, non-targeted metabolomics profiling of exhaled breath condensate (EBC) samples from 36 pre-APE (CF patients 1 to 3 months before an APE) and 97 stable CF patients (CF subjects who are clinically stable without an APE for ≥3 months) was performed using ultra performance liquid chromatography coupled to ultra-high resolution accurate mass high-field Orbitrap mass spectrometry. A supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model, was able to distinguish pre-APE from stable CF samples with good accuracy (88.5-89.7%), sensitivity (81.0-84.6%) and specificity (89.6-93.6%), suggesting significant alterations in epithelial lining lung fluid monitored through EBC could be useful to detect APEs early, therefore improving patient outcomes.

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