Volatile organic compound breath signatures of children with cystic fibrosis by real-time SESI-HRMS

Ronja Weber; Naemi Haas; Astghik Baghdasaryan; Tobias Bruderer; Demet Inci; Srdjan Micic; Nathan Perkins; Renate Spinas; Renato Zenobi; Alexander Moeller

doi:10.1183/23120541.00171-2019

Volatile organic compound breath signatures of children with cystic fibrosis by real-time SESI-HRMS

ERJ Open Res. 2020 Jan 10;6(1):00171-2019. doi: 10.1183/23120541.00171-2019. eCollection 2020 Jan.

Authors

Ronja Weber¹, Naemi Haas¹, Astghik Baghdasaryan^{1

2}, Tobias Bruderer^{1

3}, Demet Inci¹, Srdjan Micic¹, Nathan Perkins⁴, Renate Spinas¹, Renato Zenobi³, Alexander Moeller^{1

5}

Affiliations

¹ Division of Respiratory Medicine and Childhood Research Center, University Children's Hospital Zürich, Zürich, Switzerland.
² Joint Medical Center Arabkir, Division of Pulmonology, Yerevan, Armenia.
³ ETH Zürich, Dept of Chemistry and Applied Bioscience, Zürich, Switzerland.
⁴ Division of Clinical Chemistry and Biochemistry, University Children's Hospital Zürich, Zürich, Switzerland.
⁵ A list of the members of the Paediatric Exhalomics Group can be found at the end of this article.

Abstract

Early pulmonary infection and inflammation result in irreversible lung damage and are major contributors to cystic fibrosis (CF)-related morbidity. An easy to apply and noninvasive assessment for the timely detection of disease-associated complications would be of high value. We aimed to detect volatile organic compound (VOC) breath signatures of children with CF by real-time secondary electrospray ionisation high-resolution mass spectrometry (SESI-HRMS). A total of 101 children, aged 4-18 years (CF=52; healthy controls=49) and comparable for sex, body mass index and lung function were included in this prospective cross-sectional study. Exhaled air was analysed by a SESI-source linked to a high-resolution time-of-flight mass spectrometer. Mass spectra ranging from m/z 50 to 500 were recorded. Out of 3468 m/z features, 171 were significantly different in children with CF (false discovery rate adjusted p-value of 0.05). The predictive ability (CF versus healthy) was assessed by using a support-vector machine classifier and showed an average accuracy (repeated cross-validation) of 72.1% (sensitivity of 77.2% and specificity of 67.7%). This is the first study to assess entire breath profiles of children with SESI-HRMS and to extract sets of VOCs that are associated with CF. We have detected a large set of exhaled molecules that are potentially related to CF, indicating that the molecular breath of children with CF is diverse and informative.