Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis. (31st October 2017)

• Record Type: Journal Article
• Authors: Tan, Xiaowen; Zhang, Xiting; Pan, Lanlan; Tian, Xiaoxuan; Dong, Pengzhi
• Other Names: Schroeder Harry W. Academic Editor.
• Is Part Of: BioMed research international. Volume 2017(2017)
• Publication Date: 2017-10-31
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2017/4323496
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : 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.