Abstract
Background and Aims: The prevalence of chronic liver disease in adults exceeds 30% in some countries and there is significant interest in developing tests and treatments to help control disease progression and reduce healthcare burden. Breath is a rich sampling matrix that offers non-invasive so-lutions suitable for early-stage detection and disease moni-toring. Having previously investigated targeted analysis of a single biomarker, here we investigated a multiparametric approach to breath testing that would provide more robust and reliable results for clinical use. Methods: To identify candidate biomarkers we compared 46 breath samples from cirrhosis patients and 42 from controls. Collection and analysis used Breath Biopsy OMNI™, maximizing signal and contrast to background to provide high confidence biomarker detection based upon gas chromatography mass spectrometry (GC-MS). Blank samples were also analyzed to provide de-tailed information on background volatile organic compounds (VOCs) levels. Results: A set of 29 breath VOCs differed significantly between cirrhosis and controls. A classification model based on these VOCs had an area under the curve (AUC) of 0.95±0.04 in cross-validated test sets. The seven best performing VOCs were sufficient to maximize classification performance. A subset of 11 VOCs was correlated with blood metrics of liver function (bilirubin, albumin, prothrom-bin time) and separated patients by cirrhosis severity using principal component analysis. Conclusions: A set of seven VOCs consisting of previously reported and novel candidates show promise as a panel for liver disease detection and mon-itoring, showing correlation to disease severity and serum biomarkers at late stage.
Author supplied keywords
Cite
CITATION STYLE
Ferrandino, G., De Palo, G., Murgia, A., Birch, O., Tawfike, A., Smith, R., … Snowdon, V. K. (2023). Breath Biopsy® to Identify Exhaled Volatile Organic Compounds Biomarkers for Liver Cirrhosis Detection. Journal of Clinical and Translational Hepatology, 11(3), 638–648. https://doi.org/10.14218/JCTH.2022.00309
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.