title: A new ensemble-based algorithm for identifying breath gas marker candidates in liver disease using ion molecule reaction mass spectrometry.
abstract: BACKGROUND
  Alcoholic fatty liver disease (AFLD) and non-AFLD (NAFLD) can progress to severe liver diseases such as steatohepatitis, cirrhosis and cancer. Thus, the detection of early liver disease is essential; however, minimal invasive diagnostic methods in clinical hepatology still lack specificity.
  
  
  RESULTS
  Ion molecule reaction mass spectrometry (IMR-MS) was applied to a total of 126 human breath gas samples comprising 91 cases (AFLD, NAFLD and cirrhosis) and 35 healthy controls. A new feature selection modality termed Stacked Feature Ranking (SFR) was developed to identify potential liver disease marker candidates in breath gas samples, relying on the combination of different entropy- and correlation-based feature ranking methods including statistical hypothesis testing using a two-level architecture with a suggestion and a decision layer. We benchmarked SFR against four single feature selection methods, a wrapper and a recently described ensemble method, indicating a significantly higher discriminatory ability of up to 10-15% for the SFR selected gas compounds expressed by the area under the ROC curve (AUC) of 0.85-0.95. Using this approach, we were able to identify unexpected breath gas marker candidates in liver disease of high predictive value. A literature study further supports top-ranked markers to be associated with liver disease. We propose SFR as a powerful tool for biomarker search in breath gas and other biological samples using mass spectrometry.
  
  
  BACKGROUND
  The algorithm SFR and IMR-MS datasets are available under http://biomed.umit.at/page.cfm?pageid=526.
authors.affiliation: Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at
authors.forename: M
authors.initials: M
authors.lastname: Netzer
authors.forename: G
authors.initials: G
authors.lastname: Millonig
authors.forename: M
authors.initials: M
authors.lastname: Osl
authors.forename: B
authors.initials: B
authors.lastname: Pfeifer
authors.forename: S
authors.initials: S
authors.lastname: Praun
authors.forename: J
authors.initials: J
authors.lastname: Villinger
authors.forename: W
authors.initials: W
authors.lastname: Vogel
authors.forename: C
authors.initials: C
authors.lastname: Baumgartner
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000032:analysis; D001944:Breath Tests; D015331:Cohort Studies; D006801:Humans; D008107:Liver Diseases / Q000175:diagnosis* / Q000378:metabolism; D013058:Mass Spectrometry / Q000379:methods*; D008875:Middle Aged
chemical_list: D015415:Biomarkers