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Abstract Details
Prediction of Advanced Fibrosis in Non-Alcoholic Fatty Liver Disease Using Gut Microbiota-Based Approaches Compared With Simple Non-Invasive Tools
Sci Rep. 2020 Jun 10;10(1):9385. doi: 10.1038/s41598-020-66241-0.
Sonja Lang12, Fedja Farowski345, Anna Martin1, Hilmar Wisplinghoff678, Maria J G T Vehreschild345, Marcin Krawczyk910, Angela Nowag68, Anne Kretzschmar6, Claus Scholz6, Philipp Kasper1, Christoph Roderburg11, Frank Lammert9, Tobias Goeser1, Hans-Michael Steffen1, Münevver Demir1213
Author information
1University of Cologne, Faculty of Medicine, and University Hospital Cologne, Department of Gastroenterology and Hepatology, Cologne, Germany.
2Department of Medicine, University of California San Diego, La Jolla, CA, USA.
3University of Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany.
4German Centre for Infection Research (DZIF), partner site Bonn/Cologne, Cologne, Germany.
5Department of Internal Medicine, Infectious Diseases, Goethe University Frankfurt, Frankfurt am Main, Germany.
6Wisplinghoff Laboratories, Cologne, Germany.
7Institute for Virology and Medical Microbiology, University Witten/Herdecke, Witten, Germany.
8University of Cologne, Faculty of Medicine, Institute for Medical Microbiology, Immunology and Hygiene, University Hospital of Cologne, Cologne, Germany.
9Department of Medicine II, Saarland University Medical Center, Homburg, Germany.
10Laboratory of Metabolic Liver Diseases, Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.
11Department of Hepatology and Gastroenterology, Campus Virchow Clinic, Charité University Medicine, Berlin, Germany.
12University of Cologne, Faculty of Medicine, and University Hospital Cologne, Department of Gastroenterology and Hepatology, Cologne, Germany. muenevver.demir@charite.de.
13Department of Hepatology and Gastroenterology, Campus Virchow Clinic, Charité University Medicine, Berlin, Germany. muenevver.demir@charite.de.
Free PMC article
Abstract
Liver fibrosis is the major determinant of liver related complications in patients with non-alcoholic fatty liver disease (NAFLD). A gut microbiota signature has been explored to predict advanced fibrosis in NAFLD patients. The aim of this study was to validate and compare the diagnostic performance of gut microbiota-based approaches to simple non-invasive tools for the prediction of advanced fibrosis in NAFLD. 16S rRNA gene sequencing was performed in a cohort of 83 biopsy-proven NAFLD patients and 13 patients with non-invasively diagnosed NAFLD-cirrhosis. Random Forest models based on clinical data and sequencing results were compared with transient elastography, the NAFLD fibrosis score (NFS) and FIB-4 index. A Random Forest model containing clinical features and bacterial taxa achieved an area under the curve (AUC) of 0.87 which was only marginally superior to a model without microbiota features (AUC 0.85). The model that aimed to validate a published algorithm achieved an AUC of 0.71. AUC's for NFS and FIB-4 index were 0.86 and 0.85. Transient elastography performed best with an AUC of 0.93. Gut microbiota signatures might help to predict advanced fibrosis in NAFLD. However, transient elastography achieved the best diagnostic performance for the detection of NAFLD patients at risk for disease progression.