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Identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis
Due to economic development and lifestyle changes, the incidence of non-alcoholic fatty liver disease (NAFLD) has gradually increased in recent years. However, the pathogenesis of NAFLD is not yet fully understood. To identify candidate genes that contribute to the development and progression of NAF...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983972/ https://www.ncbi.nlm.nih.gov/pubmed/29620197 http://dx.doi.org/10.3892/mmr.2018.8852 |
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author | Li, Lin Liu, Huabao Hu, Xiaoyu Huang, Yi Wang, Yanan He, Yansha Lei, Qingsong |
author_facet | Li, Lin Liu, Huabao Hu, Xiaoyu Huang, Yi Wang, Yanan He, Yansha Lei, Qingsong |
author_sort | Li, Lin |
collection | PubMed |
description | Due to economic development and lifestyle changes, the incidence of non-alcoholic fatty liver disease (NAFLD) has gradually increased in recent years. However, the pathogenesis of NAFLD is not yet fully understood. To identify candidate genes that contribute to the development and progression of NAFLD, two microarray datasets were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified and functional enrichment analyses were performed. A protein-protein interaction network was constructed and modules were extracted using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. The enriched functions and pathways of the DEGs included ‘cellular macromolecule biosynthetic process’, ‘cellular response to chemical stimulus’, ‘extracellular matrix organization’, ‘metabolic pathways’, ‘insulin resistance’ and ‘forkhead box protein O1 signaling pathway’. The DEGs, including type-1 angiotensin II receptor, formin-binding protein 1-like, RNA-binding protein with serine-rich domain 1, Ras-related C3 botulinum toxin substrate 1 and polyubiquitin-C, were identified using multiple bioinformatics methods and validated in vitro with reverse transcription-quantitative polymerase chain reaction analysis. In conclusion, five hub genes were identified in the present study, and they may aid in understanding of the molecular mechanisms underlying the development and progression of NAFLD. |
format | Online Article Text |
id | pubmed-5983972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-59839722018-06-04 Identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis Li, Lin Liu, Huabao Hu, Xiaoyu Huang, Yi Wang, Yanan He, Yansha Lei, Qingsong Mol Med Rep Articles Due to economic development and lifestyle changes, the incidence of non-alcoholic fatty liver disease (NAFLD) has gradually increased in recent years. However, the pathogenesis of NAFLD is not yet fully understood. To identify candidate genes that contribute to the development and progression of NAFLD, two microarray datasets were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified and functional enrichment analyses were performed. A protein-protein interaction network was constructed and modules were extracted using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. The enriched functions and pathways of the DEGs included ‘cellular macromolecule biosynthetic process’, ‘cellular response to chemical stimulus’, ‘extracellular matrix organization’, ‘metabolic pathways’, ‘insulin resistance’ and ‘forkhead box protein O1 signaling pathway’. The DEGs, including type-1 angiotensin II receptor, formin-binding protein 1-like, RNA-binding protein with serine-rich domain 1, Ras-related C3 botulinum toxin substrate 1 and polyubiquitin-C, were identified using multiple bioinformatics methods and validated in vitro with reverse transcription-quantitative polymerase chain reaction analysis. In conclusion, five hub genes were identified in the present study, and they may aid in understanding of the molecular mechanisms underlying the development and progression of NAFLD. D.A. Spandidos 2018-06 2018-04-05 /pmc/articles/PMC5983972/ /pubmed/29620197 http://dx.doi.org/10.3892/mmr.2018.8852 Text en Copyright: © Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Li, Lin Liu, Huabao Hu, Xiaoyu Huang, Yi Wang, Yanan He, Yansha Lei, Qingsong Identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis |
title | Identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis |
title_full | Identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis |
title_fullStr | Identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis |
title_full_unstemmed | Identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis |
title_short | Identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis |
title_sort | identification of key genes in non-alcoholic fatty liver disease progression based on bioinformatics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983972/ https://www.ncbi.nlm.nih.gov/pubmed/29620197 http://dx.doi.org/10.3892/mmr.2018.8852 |
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