Dataset Information

Integrated analysis of gene expression changes associated with coronary artery disease.

ABSTRACT: BACKGROUND:This study investigated the pathways and genes involved in coronary artery disease (CAD) and the associated mechanisms. METHODS:Two array data sets of GSE19339 and GSE56885 were downloaded. The limma package was used to analyze the differentially expressed genes (DEGs) in normal and CAD specimens. Examination of DEGs through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology annotation was achieved by Database for Annotation, Visualization and Integrated Discovery (DAVID). The Cytoscape software facilitated the establishment of the protein-protein interaction (PPI) network and Molecular Complex Detection (MCODE) was performed for the significant modules. RESULTS:We identified 413 DEGs (291 up-regulated and 122 down-regulated). Approximately 256 biological processes, only 1 cellular component, and 21 molecular functions were identified by GO analysis and 10 pathways were enriched by KEGG. Moreover, 264 protein pairs and 64 nodes were visualized by the PPI network. After the MCODE analysis, the top 4 high degree genes, including interleukin 1 beta (IL1B, degree?=?29), intercellular adhesion molecule 1 (ICAM1, degree?=?25), Jun proto-oncogene (JUN, degree?=?23) and C-C motif chemokine ligand 2 (CCL2, degree?=?20) had been identified to validate in RT-PCR and Cox proportional hazards regression between CAD and normals. CONCLUSIONS:The relative expression of IL1B, ICAM1 and CCL2 was higher in CAD than in normal controls (P?

SUBMITTER: Miao L

PROVIDER: S-EPMC6454774 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated analysis of gene expression changes associated with coronary artery disease.

Miao Liu L Yin Rui-Xing RX Huang Feng F Yang Shuo S Chen Wu-Xian WX Wu Jin-Zhen JZ

Lipids in health and disease 20190409 1

<h4>Background</h4>This study investigated the pathways and genes involved in coronary artery disease (CAD) and the associated mechanisms.<h4>Methods</h4>Two array data sets of GSE19339 and GSE56885 were downloaded. The limma package was used to analyze the differentially expressed genes (DEGs) in normal and CAD specimens. Examination of DEGs through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology annotation was achieved by Database for Annotation, Visualizati ...[more]

PMID: 30961613

Similar Datasets

Project description:The present study aimed to investigate the key genes and microRNAs (miRNA/miRs) associated with coronary artery disease (CAD) progression. The gene expression profile of GSE20680 and GSE12288, and the miRNA expression profile of GSE28858 were downloaded from the gene expression omnibus database. The differentially expressed genes (DEGs) in GSE20680 and GSE12288, and the differentially expressed miRNAs in GSE28858 were screened using the limma package in R software. Common DEGs between GSE20680 and GSE12288 were selected. Functions and pathways of DEGs and miRNAs were enriched using the DAVID tool from the GO and KEGG databases. The regulatory network of miRNA and selected CAD‑associated DEGs was constructed. A total of 270 DEGs (167 upregulated and 103 downregulated) based on the GSE20680 dataset, and 2,268 DEGs (534 upregulated and 1,734 downregulated) based on the GSE12288 dataset, were screened. For the differentially expressed miRNAs, 214 were identified (102 upregulated and 112 downregulated) in CAD samples and were screened. Interferon regulatory factor 2 (IRF2) and cell death‑inducing DFFA‑like effector b (CIDEB), which are regulated by signal transducer and activator of transcription 3 and myc‑associated factor X, were identified as common DEGs for CAD. miR‑455‑5p, miR‑455‑3p and miR‑1257, which are involved in the major histocompatibility complex (MHC)protein assembly pathway and peptide antigen assembly with MHC class I protein complex pathway, may regulate various miRNAs and target genes, including pro‑opiomelancortin (POMC), toll‑like receptor 4 (TLR4), interleukin 10 (IL10), activating transcription factor 6 (ATF6) and calreticulin (CALR). The current study identified IRF2 and CIDEB as crucial genes, and miRNA‑455‑5p, miRNA‑455‑3p and miR‑1257 along with their target genes POMC, TLR4 and CALR, as miRNAs involved in CAD progression. Thus, the present study may provide a basis for future research into the progression mechanism of CAD.

Project description:ObjectivesTo analyze the gene expression profile of peripheral blood monocytes in different stages of coronary artery disease (CAD) by transcriptome sequencing, and to explore potential genes and pathway involved in CAD pathogenesis.MethodsAccording to the screening of coronary angiography and quality control of blood samples, eight intermediate coronary lesion patients were selected, then eight patients with acute myocardial infarction, and eight patients with normal coronary angiography were matched by age and gender. Transcriptomics sequencing was conducted for the peripheral blood monocytes of these 24 samples by using the Illumina HiSeq high-throughput platform. Then, differentially expressed genes (DEGs) were analyzed. Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, and protein-protein interaction (PPI) network were applied to annotate the potential functions of DEGs.ResultsCompared with the normal coronary angiography group, we identified a total of 169 DEGs in the intermediate coronary lesion group, which were significantly enriched in 59 GO terms and 17 KEGG pathways. Compared with the normal coronary angiography group, we found a total of 2,028 DEGs, which were significantly enriched in 311 GO terms and 20 KEGG pathways in the acute myocardial infarction group. The cross-comparison between normal versus intermediate coronary lesion group, and normal versus acute myocardial infarction group included 98 differential genes with 65 up regulated and 33 down regulated genes, which were significantly enriched in 46 GO terms and 10 KEGG pathways. During the progression of CAD, there was a significant up-regulated expression of CSF3, IL-1A, CCR7, and IL-18, and down-regulated expression of MAPK14. Besides GO items such as inflammatory response was significantly enriched, KEGG analysis showed the most remarkable enrichments in IL-17 signaling pathway and cytokine-cytokine receptor interactions.ConclusionsTranscriptomics profiles vary in patients with different severity of CAD. CSF3, IL-1A, CCR7, IL-18, and MAPK14, as well as IL-17 signaling pathway and cytokine and cytokine receptor interaction signaling pathway related with inflammatory response might be the potential biomarker and targets for the treatment of coronary artery disease.

Project description:Coronary artery disease (CAD) is a major cause of end-stage cardiac disease. Although profound efforts have been made to illuminate the pathogenesis, the molecular mechanisms of CAD remain to be analyzed. To identify the candidate genes in the advancement of CAD, microarray dataset GSE23766 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified, and pathway and gene ontology (GO) enrichment analyses were performed. The protein-protein interaction network was constructed and the module analysis was performed using the Biological General Repository for Interaction Datasets (BioGRID) and Cytoscape. Additionally, target genes-miRNA regulatory network and target genes-TF regulatory network were constructed and analyzed. There were 894 DEGs between male human CAD samples and female human CAD samples, including 456 up regulated genes and 438 down regulated genes. Pathway enrichment analyses revealed that DEGs (up and down regulated) were mostly enriched in the superpathway of steroid hormone biosynthesis, ABC transporters, oxidative ethanol degradation III and Complement and coagulation cascades. Similarly, geneontology enrichment analyses revealed that DEGs (up and down regulated) were mostly enriched in the forebrain neuron differentiation, filopodium membrane, platelet degranulation and blood microparticle. In the PPI network and modules (up and down regulated), MYC, NPM1, TRPC7, UBC, FN1, HEMK1, IFT74 and VHL were hub genes. In the target genes-miRNA regulatory network and target genes-TF regulatory network (up and down regulated), TAOK1, KHSRP, HSD17B11 and PAH were target genes. In conclusion, the pathway and GO ontology enriched by DEGs may reveal the molecular mechanism of CAD. Its hub and target genes, MYC, NPM1, TRPC7, UBC, FN1, HEMK1, IFT74, VHL, TAOK1, KHSRP, HSD17B11 and PAH were expected to be new targets for CAD. Our finding provided clues for exploring molecular mechanism and developing new prognostics, diagnostic and therapeutic strategies for CAD.

Project description:The current research attempted to identify possible hub genes and pathways of coronary artery disease (CAD) and to detect the possible mechanisms. Array data from GSE90074 were downloaded from the Gene Expression Omnibus (GEO) database. Integrated weighted gene co-expression network analysis (WGCNA) was performed to analyze the gene module and clinical characteristics. Gene Ontology annotation (GO), Disease Ontology (DO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by clusterProfiler and the DOSE package in R. A protein-protein interaction (PPI) network was established using Cytoscape software, and significant modules were analyzed using Molecular Complex Detection (MCODE) to identify hub genes. Then, further functional validation of hub genes in other microarrays and population samples was performed, and survival analysis was performed to investigate the prognosis. A total of 660 genes were located in three modules and associated with CAD. GO functions identified 484 biological processes, 39 cellular components, and 22 molecular functions with an adjusted P < 0.05. In total, 38 pathways were enriched in KEGG pathway analysis, and 147 DO items were identified with an adjusted P < 0.05 (false discovery rate, FDR set at < 0.05). There was a total of four modules with a score > 10 after PPI network analysis using the MCODE app, and two hub genes (TLR2 and CD14) were identified. Then, we validated the information from the GSE60993 dataset using the GSE59867 dataset and population samples, and we found that these two genes were associated with plaque vulnerability. These two genes varied at different time points after myocardial infarction, and both of them had the lowest prognosis of heart failure when they were expressed at low levels. We performed an integrated WGCNA and validated that TLR2 and CD14 were closely associated with the severity of coronary artery disease, plaque instability and the prognosis of heart failure after myocardial infarction.

Dataset Information

Integrated analysis of gene expression changes associated with coronary artery disease.

Publications

Integrated analysis of gene expression changes associated with coronary artery disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets