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Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics
High-calorie diets lead to hepatic steatosis and to the development of non-alcoholic fatty liver disease (NAFLD), which can evolve over many years into the inflammatory form of non-alcoholic steatohepatitis (NASH), posing a risk for the development of hepatocellular carcinoma (HCC). Due to diet and...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9408600/ https://www.ncbi.nlm.nih.gov/pubmed/36012106 http://dx.doi.org/10.3390/ijms23168841 |
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author | Sydor, Svenja Dandyk, Christian Schwerdt, Johannes Manka, Paul Benndorf, Dirk Lehmann, Theresa Schallert, Kay Wolf, Maximilian Reichl, Udo Canbay, Ali Bechmann, Lars P. Heyer, Robert |
author_facet | Sydor, Svenja Dandyk, Christian Schwerdt, Johannes Manka, Paul Benndorf, Dirk Lehmann, Theresa Schallert, Kay Wolf, Maximilian Reichl, Udo Canbay, Ali Bechmann, Lars P. Heyer, Robert |
author_sort | Sydor, Svenja |
collection | PubMed |
description | High-calorie diets lead to hepatic steatosis and to the development of non-alcoholic fatty liver disease (NAFLD), which can evolve over many years into the inflammatory form of non-alcoholic steatohepatitis (NASH), posing a risk for the development of hepatocellular carcinoma (HCC). Due to diet and liver alteration, the axis between liver and gut is disturbed, resulting in gut microbiome alterations. Consequently, detecting these gut microbiome alterations represents a promising strategy for early NASH and HCC detection. We analyzed medical parameters and the fecal metaproteome of 19 healthy controls, 32 NASH patients, and 29 HCC patients, targeting the discovery of diagnostic biomarkers. Here, NASH and HCC resulted in increased inflammation status and shifts within the composition of the gut microbiome. An increased abundance of kielin/chordin, E3 ubiquitin ligase, and nucleophosmin 1 represented valuable fecal biomarkers, indicating disease-related changes in the liver. Although a single biomarker failed to separate NASH and HCC, machine learning-based classification algorithms provided an 86% accuracy in distinguishing between controls, NASH, and HCC. Fecal metaproteomics enables early detection of NASH and HCC by providing single biomarkers and machine learning-based metaprotein panels. |
format | Online Article Text |
id | pubmed-9408600 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94086002022-08-26 Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics Sydor, Svenja Dandyk, Christian Schwerdt, Johannes Manka, Paul Benndorf, Dirk Lehmann, Theresa Schallert, Kay Wolf, Maximilian Reichl, Udo Canbay, Ali Bechmann, Lars P. Heyer, Robert Int J Mol Sci Article High-calorie diets lead to hepatic steatosis and to the development of non-alcoholic fatty liver disease (NAFLD), which can evolve over many years into the inflammatory form of non-alcoholic steatohepatitis (NASH), posing a risk for the development of hepatocellular carcinoma (HCC). Due to diet and liver alteration, the axis between liver and gut is disturbed, resulting in gut microbiome alterations. Consequently, detecting these gut microbiome alterations represents a promising strategy for early NASH and HCC detection. We analyzed medical parameters and the fecal metaproteome of 19 healthy controls, 32 NASH patients, and 29 HCC patients, targeting the discovery of diagnostic biomarkers. Here, NASH and HCC resulted in increased inflammation status and shifts within the composition of the gut microbiome. An increased abundance of kielin/chordin, E3 ubiquitin ligase, and nucleophosmin 1 represented valuable fecal biomarkers, indicating disease-related changes in the liver. Although a single biomarker failed to separate NASH and HCC, machine learning-based classification algorithms provided an 86% accuracy in distinguishing between controls, NASH, and HCC. Fecal metaproteomics enables early detection of NASH and HCC by providing single biomarkers and machine learning-based metaprotein panels. MDPI 2022-08-09 /pmc/articles/PMC9408600/ /pubmed/36012106 http://dx.doi.org/10.3390/ijms23168841 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sydor, Svenja Dandyk, Christian Schwerdt, Johannes Manka, Paul Benndorf, Dirk Lehmann, Theresa Schallert, Kay Wolf, Maximilian Reichl, Udo Canbay, Ali Bechmann, Lars P. Heyer, Robert Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics |
title | Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics |
title_full | Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics |
title_fullStr | Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics |
title_full_unstemmed | Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics |
title_short | Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics |
title_sort | discovering biomarkers for non-alcoholic steatohepatitis patients with and without hepatocellular carcinoma using fecal metaproteomics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9408600/ https://www.ncbi.nlm.nih.gov/pubmed/36012106 http://dx.doi.org/10.3390/ijms23168841 |
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