Editorial
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Aug 14, 2019; 25(30): 4043-4050
Published online Aug 14, 2019. doi: 10.3748/wjg.v25.i30.4043
Exhaled breath analysis in hepatology: State-of-the-art and perspectives
Antonio De Vincentis, Umberto Vespasiani-Gentilucci, Anna Sabatini, Raffaele Antonelli-Incalzi, Antonio Picardi
Antonio De Vincentis, Umberto Vespasiani-Gentilucci, Raffaele Antonelli-Incalzi, Antonio Picardi, Unit of Clinical Medicine and Hepatology, Unit of Geriatrics, Department of Medicine, Campus Bio-Medico University Hospital, Rome 00128, Italy
Anna Sabatini, Unit of Electronics for sensor systems, Department of Engineering, University Campus Bio-Medico of Rome, Rome 00128, Italy
Author contributions: All the authors contributed to writing and revising this manuscript.
Conflict-of-interest statement: The authors have no conflict of interest to declare.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Antonio De Vincentis, MD, Medical Assistant, Unit of Clinical Medicine and Hepatology, Unit of Geriatrics, Department of Medicine, Campus Bio-Medico University Hospital, via Alvaro del Portillo, 200, Rome 00128, Italy. a.devincentis@unicampus.it
Telephone: +39-06-225411445
Received: April 28, 2019
Peer-review started: April 28, 2019
First decision: May 24, 2019
Revised: June 11, 2019
Accepted: June 25, 2019
Article in press: June 26, 2019
Published online: August 14, 2019
Processing time: 110 Days and 2.4 Hours
Abstract

Liver disease is characterized by breath exhalation of peculiar volatile organic compounds (VOCs). Thanks to the availability of sensitive technologies for breath analysis, this empiric approach has recently gained increasing attention in the context of hepatology, following the good results obtained in other fields of medicine. After the first studies that led to the identification of selected VOCs for pathophysiological purposes, subsequent research has progressively turned towards the comprehensive assessment of exhaled breath for potential clinical application. Specific VOC patterns were found to discriminate subjects with liver cirrhosis, to rate disease severity, and, eventually, to forecast adverse clinical outcomes even beyond existing scores. Preliminary results suggest that breath analysis could be useful also for detecting and staging hepatic encephalopathy and for predicting steatohepatitis in patients with nonalcoholic fatty liver disease. However, clinical translation is still hampered by a number of methodological limitations, including the lack of standardization and the consequent poor comparability between studies and the absence of external validation of obtained results. Given the low-cost and easy execution at bedside of the new technologies (e-nose), larger and well-structured studies are expected in order to provide the adequate level of evidence to support VOC analysis in clinical practice.

Keywords: Exhaled breath analysis; Electronic nose; Gas chromatography; Breath print; Liver cirrhosis; Nonalcoholic fatty liver disease; Hepatic encephalopathy

Core tip: Since the liver plays a key metabolic role, different volatile organic compounds (VOCs) have been identified in the exhaled breath of hepatopathic patients. VOCs have been already analyzed with promising results concerning disease diagnosis and characterization. To date, translation to the clinic has been limited by the lack of standardization and external validation of the results obtained. Since VOC analysis with new technologies is easy, quick, and cheap, and it was proven to discriminate patients with liver cirrhosis, identify stage disease severity, and predict important adverse outcomes, it should be further explored and hopefully exported to clinical practice.