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Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis

BACKGROUND: Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human. METHODS: Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GE...

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Detalles Bibliográficos
Autores principales: Tan, Xiaowen, Zhang, Xiting, Pan, Lanlan, Tian, Xiaoxuan, Dong, Pengzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5684517/
https://www.ncbi.nlm.nih.gov/pubmed/29226137
http://dx.doi.org/10.1155/2017/4323496
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author Tan, Xiaowen
Zhang, Xiting
Pan, Lanlan
Tian, Xiaoxuan
Dong, Pengzhi
author_facet Tan, Xiaowen
Zhang, Xiting
Pan, Lanlan
Tian, Xiaoxuan
Dong, Pengzhi
author_sort Tan, Xiaowen
collection PubMed
description BACKGROUND: Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human. METHODS: Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO), including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs) were analyzed. RESULTS: 42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI) networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton. CONCLUSION: The present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis.
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spelling pubmed-56845172017-12-10 Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis Tan, Xiaowen Zhang, Xiting Pan, Lanlan Tian, Xiaoxuan Dong, Pengzhi Biomed Res Int Research Article BACKGROUND: Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human. METHODS: Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO), including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs) were analyzed. RESULTS: 42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI) networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton. CONCLUSION: The present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis. Hindawi 2017 2017-10-31 /pmc/articles/PMC5684517/ /pubmed/29226137 http://dx.doi.org/10.1155/2017/4323496 Text en Copyright © 2017 Xiaowen Tan et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Tan, Xiaowen
Zhang, Xiting
Pan, Lanlan
Tian, Xiaoxuan
Dong, Pengzhi
Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis
title Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis
title_full Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis
title_fullStr Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis
title_full_unstemmed Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis
title_short Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis
title_sort identification of key pathways and genes in advanced coronary atherosclerosis using bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5684517/
https://www.ncbi.nlm.nih.gov/pubmed/29226137
http://dx.doi.org/10.1155/2017/4323496
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