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Prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools
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...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286895/ https://www.ncbi.nlm.nih.gov/pubmed/32523101 http://dx.doi.org/10.1038/s41598-020-66241-0 |
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author | Lang, Sonja Farowski, Fedja Martin, Anna Wisplinghoff, Hilmar Vehreschild, Maria J. G. T. Krawczyk, Marcin Nowag, Angela Kretzschmar, Anne Scholz, Claus Kasper, Philipp Roderburg, Christoph Lammert, Frank Goeser, Tobias Steffen, Hans-Michael Demir, Münevver |
author_facet | Lang, Sonja Farowski, Fedja Martin, Anna Wisplinghoff, Hilmar Vehreschild, Maria J. G. T. Krawczyk, Marcin Nowag, Angela Kretzschmar, Anne Scholz, Claus Kasper, Philipp Roderburg, Christoph Lammert, Frank Goeser, Tobias Steffen, Hans-Michael Demir, Münevver |
author_sort | Lang, Sonja |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7286895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72868952020-06-15 Prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools Lang, Sonja Farowski, Fedja Martin, Anna Wisplinghoff, Hilmar Vehreschild, Maria J. G. T. Krawczyk, Marcin Nowag, Angela Kretzschmar, Anne Scholz, Claus Kasper, Philipp Roderburg, Christoph Lammert, Frank Goeser, Tobias Steffen, Hans-Michael Demir, Münevver Sci Rep Article 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. Nature Publishing Group UK 2020-06-10 /pmc/articles/PMC7286895/ /pubmed/32523101 http://dx.doi.org/10.1038/s41598-020-66241-0 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lang, Sonja Farowski, Fedja Martin, Anna Wisplinghoff, Hilmar Vehreschild, Maria J. G. T. Krawczyk, Marcin Nowag, Angela Kretzschmar, Anne Scholz, Claus Kasper, Philipp Roderburg, Christoph Lammert, Frank Goeser, Tobias Steffen, Hans-Michael Demir, Münevver Prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools |
title | Prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools |
title_full | Prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools |
title_fullStr | Prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools |
title_full_unstemmed | Prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools |
title_short | Prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools |
title_sort | prediction of advanced fibrosis in non-alcoholic fatty liver disease using gut microbiota-based approaches compared with simple non-invasive tools |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286895/ https://www.ncbi.nlm.nih.gov/pubmed/32523101 http://dx.doi.org/10.1038/s41598-020-66241-0 |
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