Dataset Information

Identification of Key lncRNAs Associated With Atherosclerosis Progression Based on Public Datasets.

ABSTRACT: Atherosclerosis is one of the most common type of cardiovascular disease and the prime cause of mortality in the aging population worldwide. However, the detail mechanisms and special biomarkers of atherosclerosis remain to be further investigated. Lately, long non-coding RNAs (lncRNAs) has attracted much more attention than other types of ncRNAs. In our work, we found and confirmed differently expressed lncRNAs and mRNAs in atherosclerosis by analyzing GSE28829. We performed the weighted gene co-expression network analysis (WGCNA) by analyzing GSE40231 to confirm highly correlated genes. Gene Ontology (GO) analysis were utilized to assess the potential functions of differential expressed lncRNAs in atherosclerosis. Co-expression networks were also constructed to confirm hub lncRNAs in atherosclerosis. A total of 5784 mRNAs and 654 lncRNAs were found to be dysregulated in the progression of atherosclerosis. A total of 15 lncRNA-mRNA co-expression modules were identified in this study based on WGCNA analysis. Moreover, a few lncRNAs, such as ZFAS1, LOC100506730, LOC100506691, DOCK9-AS2, RP11-6I2.3, LOC100130219, were confirmed as important lncRNAs in atherosclerosis. Taken together, bioinformatics analysis revealed these lncRNAs were involved in regulating the leukotriene biosynthetic process, gene expression, actin filament organization, t-circle formation, antigen processing, and presentation, interferon-gamma-mediated signaling pathway, and activation of GTPase activity. We believed that this study would provide potential novel therapeutic and prognostic targets for atherosclerosis.

SUBMITTER: Wang CH

PROVIDER: S-EPMC6403132 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Identification of Key lncRNAs Associated With Atherosclerosis Progression Based on Public Datasets.

Wang Chuan-Hui CH Shi Hui-Hua HH Chen Lin-Hui LH Li Xiao-Li XL Cao Guo-Liang GL Hu Xiao-Feng XF

Frontiers in genetics 20190228

Atherosclerosis is one of the most common type of cardiovascular disease and the prime cause of mortality in the aging population worldwide. However, the detail mechanisms and special biomarkers of atherosclerosis remain to be further investigated. Lately, long non-coding RNAs (lncRNAs) has attracted much more attention than other types of ncRNAs. In our work, we found and confirmed differently expressed lncRNAs and mRNAs in atherosclerosis by analyzing GSE28829. We performed the weighted gene c ...[more]

PMID: 30873207

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Project description:Adipose tissue is the most important energy metabolism and secretion organ, and these functions are conferred during the adipogenesis process. However, the cause and the molecular events underlying adipogenesis are still unclear. In this study, we performed integrated bioinformatics analyses to identify vital genes involved in adipogenesis and reveal potential molecular mechanisms. Five mouse high-throughput expression profile datasets were downloaded from the Gene Expression Omnibus (GEO) database; these datasets contained 24 samples of 3T3-L1 cells during adipogenesis, including 12 undifferentiated samples and 12 differentiated samples. The five datasets were reanalyzed and integrated to select differentially expressed genes (DEGs) during adipogenesis via the robust rank aggregation (RRA) method. Functional annotation of these DEGs and mining of key genes were then performed. We also verified the expression levels of some potential key genes during adipogenesis. A total of 386 consistent DEGs were identified, with 230 upregulated genes and 156 downregulated genes. Gene Ontology (GO) analysis showed that the biological functions of the DEGs primarily included fat cell differentiation, lipid metabolic processes, and cell adhesion. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEGs were mainly associated with metabolic pathways, the peroxisome proliferator-activated receptor (PPAR) signaling pathway, regulation of lipolysis in adipocytes, the tumor necrosis factor (TNF) signaling pathway, and the FoxO signaling pathway. The 30 most closely related genes among the DEGs were identified from the protein?protein interaction (PPI) network and verified by real-time quantification during 3T3-L1 preadipocyte differentiation. In conclusion, we obtained a list of consistent DEGs during adipogenesis through integrated analysis, which may offer potential targets for the regulation of adipogenesis and treatment of adipose dysfunction.

Dataset Information

Identification of Key lncRNAs Associated With Atherosclerosis Progression Based on Public Datasets.

Publications

Identification of Key lncRNAs Associated With Atherosclerosis Progression Based on Public Datasets.

Similar Datasets

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