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Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes
In order to better understand the etiology of obese type 2 diabetes (T2D) at the molecular level, the present study investigated the gene expression and DNA methylation profiles associated with T2D via systemic analysis. Gene expression (GSE64998) and DNA methylation profiles (GSE65057) from liver t...
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/PMC5983955/ https://www.ncbi.nlm.nih.gov/pubmed/29620215 http://dx.doi.org/10.3892/mmr.2018.8804 |
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author | Shen, Juan Zhu, Bin |
author_facet | Shen, Juan Zhu, Bin |
author_sort | Shen, Juan |
collection | PubMed |
description | In order to better understand the etiology of obese type 2 diabetes (T2D) at the molecular level, the present study investigated the gene expression and DNA methylation profiles associated with T2D via systemic analysis. Gene expression (GSE64998) and DNA methylation profiles (GSE65057) from liver tissues of healthy controls and obese patients with T2D were downloaded from the Gene Expression Omnibus database. Differentially-expressed genes (DEGs) and differentially-methylated genes (DMGs) were identified using the Limma package, and their overlapping genes were additionally determined. Enrichment analysis was performed using the BioCloud platform on the DEGs and the overlapping genes. Using Cytoscape software, protein-protein interaction (PPI), transcription factor target networks and microRNA (miRNA) target networks were then constructed in order to determine associated hub genes. In addition, a further GSE15653 dataset was utilized in order to validate the DEGs identified in the GSE64998 dataset analyses. A total of 251 DEGs, including 124 upregulated and 127 downregulated genes, were detected, and a total of 9,698 genes were demonstrated to be differentially methylated in obese patients with T2D compared with non-obese healthy controls. A total of 103 overlapping genes between the two datasets were revealed, including 47 upregulated genes and 56 downregulated genes. The identified overlapping genes were revealed to be strongly associated with fatty acid and glucose metabolic pathways, in addition to oxidation/reduction. The overlapping genes cyclin D1 (CCND1), PPARG coactivator α (PPARGC1A), fatty acid synthase (FASN), glucokinase (GCK), steraroyl-coA desaturase (SCD) and tyrosine aminotransferase (TAT) had higher degrees in the PPI, transcription target networks and miRNA target networks. In addition, among the 251 DEGs, a total of 35 DEGs were validated to be being shared genes between the datasets, which included a number of key genes in the PPI network, including CCND1, FASN and TAT. Abnormal gene expression and DNA methylation patterns that were implicated in fatty acid and glucose metabolic pathways and oxidation/reduction reactions were detected in obese patients with T2D. Furthermore, the CCND1, PPARGC1A, FANS, GCK, SCD and TAT genes may serve a role in the development of obesity-associated T2D. |
format | Online Article Text |
id | pubmed-5983955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-59839552018-06-04 Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes Shen, Juan Zhu, Bin Mol Med Rep Articles In order to better understand the etiology of obese type 2 diabetes (T2D) at the molecular level, the present study investigated the gene expression and DNA methylation profiles associated with T2D via systemic analysis. Gene expression (GSE64998) and DNA methylation profiles (GSE65057) from liver tissues of healthy controls and obese patients with T2D were downloaded from the Gene Expression Omnibus database. Differentially-expressed genes (DEGs) and differentially-methylated genes (DMGs) were identified using the Limma package, and their overlapping genes were additionally determined. Enrichment analysis was performed using the BioCloud platform on the DEGs and the overlapping genes. Using Cytoscape software, protein-protein interaction (PPI), transcription factor target networks and microRNA (miRNA) target networks were then constructed in order to determine associated hub genes. In addition, a further GSE15653 dataset was utilized in order to validate the DEGs identified in the GSE64998 dataset analyses. A total of 251 DEGs, including 124 upregulated and 127 downregulated genes, were detected, and a total of 9,698 genes were demonstrated to be differentially methylated in obese patients with T2D compared with non-obese healthy controls. A total of 103 overlapping genes between the two datasets were revealed, including 47 upregulated genes and 56 downregulated genes. The identified overlapping genes were revealed to be strongly associated with fatty acid and glucose metabolic pathways, in addition to oxidation/reduction. The overlapping genes cyclin D1 (CCND1), PPARG coactivator α (PPARGC1A), fatty acid synthase (FASN), glucokinase (GCK), steraroyl-coA desaturase (SCD) and tyrosine aminotransferase (TAT) had higher degrees in the PPI, transcription target networks and miRNA target networks. In addition, among the 251 DEGs, a total of 35 DEGs were validated to be being shared genes between the datasets, which included a number of key genes in the PPI network, including CCND1, FASN and TAT. Abnormal gene expression and DNA methylation patterns that were implicated in fatty acid and glucose metabolic pathways and oxidation/reduction reactions were detected in obese patients with T2D. Furthermore, the CCND1, PPARGC1A, FANS, GCK, SCD and TAT genes may serve a role in the development of obesity-associated T2D. D.A. Spandidos 2018-06 2018-03-28 /pmc/articles/PMC5983955/ /pubmed/29620215 http://dx.doi.org/10.3892/mmr.2018.8804 Text en Copyright: © Shen 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 Shen, Juan Zhu, Bin Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes |
title | Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes |
title_full | Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes |
title_fullStr | Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes |
title_full_unstemmed | Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes |
title_short | Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes |
title_sort | integrated analysis of the gene expression profile and dna methylation profile of obese patients with type 2 diabetes |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983955/ https://www.ncbi.nlm.nih.gov/pubmed/29620215 http://dx.doi.org/10.3892/mmr.2018.8804 |
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