Breath Biopsy^(®) to Identify Exhaled Volatile Organic Compounds Biomarkers for Liver Cirrhosis Detection
作者机构:Owlstone MedicalCambridgeUK Department of OncologyUniversity of CambridgeHutchison/MRC Research CentreCambridgeUK Department of Pharmacology and ToxicologySchool for Nutrition and Translational Research in Metabo-lism(NUTRIM)Maastricht University Medical Centerthe Netherlands Department of MedicineUniversity of CambridgeAddenbrooke’s HospitalCambridgeUK Addenbrookes Hepatology and Liver Transplantation UnitAddenbrookes Hospi-talCambridgeUK MRC Cancer UnitHutchison/MRC Research CentreUniversity of CambridgeCambridgeUK CRUK Cambridge InstituteCambridgeUK
出 版 物:《Journal of Clinical and Translational Hepatology》 (临床与转化肝病杂志(英文版))
年 卷 期:2023年第11卷第3期
页 面:638-648页
核心收录:
学科分类:1002[医学-临床医学] 100201[医学-内科学(含:心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学]
基 金:funding from the Cancer Re-search UK for the CRUK Cambridge Centre Early Detection Program and International Alliance for Cancer Early Detection(CRUK grant refs:A25117 and RG97677) the NIHR Cambridge Biomedical Research Centre(BRC-1215-20014)
主 题:Breath Biopsy Non-invasive Biomarker Cirrhosis Liver function test.
摘 要:Background and Aims:The prevalence of chronic liver dis-ease 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 *** is a rich sampling matrix that offers non-invasive so-lutions suitable for early-stage detection and disease *** 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 ***:To identify can-didate biomarkers we compared 46 breath samples from cir-rhosis patients and 42 from *** and analysis used Breath Biopsy OMNI™,maximizing signal and contrast to background to provide high confidence biomarker detec-tion based upon gas chromatography mass spectrometry(GC-MS).Blank samples were also analyzed to provide de-tailed information on background volatile organic compounds(VOCs)***: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 *** seven best performing VOCs were sufficient to maximize classifica-tion 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 ***: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.