Dataset Information

Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis.

ABSTRACT: The aim of the present study was to screen the differentially expressed genes (DEGs) associated with familial combined hyperlipidemia (FCHL) and examine the changing patterns. The transcription profile of GSE18965 was obtained from the NCBI Gene Expression Omnibus database, including 12 FCHL samples and 12 control specimens. The DEGs were identified using a linear models for microarray data package in the R programming language. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed. Protein?protein interaction (PPI) networks of the DEGs were constructed using the EnrichNet online tool. In addition, cluster analysis of the genes in networks was performed using ClusterONE. A total of 879 DEGs were screened, including 394 upregulated and 485 downregulated genes. Enrichment analysis identified four important KEGG pathways associated with FCHL: One carbon pool by folate, ??linolenic acid metabolism, asthma and the glycosphingolipid biosynthesis?globo series. GO annotation identified 12 enriched biological processes, including one associated with hematopoiesis and four associated with bone cell differentiation. This identification was in accordance with clinical data and experiments into hyperlipidemia and bone lesions. Based on PPI networks, these DEGs had a close association with immune responses, hormone responses and cytokine?cytokine receptors. In conclusion, these DEGs may be used as specific therapeutic molecular targets in the treatment of FCHL. The present findings may provide the basis for understanding the pathogenesis of FCHL in future studies. However, further experiments are required to confirm these results.

SUBMITTER: Luo X

PROVIDER: S-EPMC4394960 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis.

Luo Xiaoli X Yu Changqing C Fu Chunjiang C Shi Weibin W Wang Xukai X Zeng Chunyu C Wang Hongyong H

Molecular medicine reports 20150127 6

The aim of the present study was to screen the differentially expressed genes (DEGs) associated with familial combined hyperlipidemia (FCHL) and examine the changing patterns. The transcription profile of GSE18965 was obtained from the NCBI Gene Expression Omnibus database, including 12 FCHL samples and 12 control specimens. The DEGs were identified using a linear models for microarray data package in the R programming language. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Gen ...[more]

PMID: 25625967

Similar Datasets

Project description:BackgroundMethylation plays a key role in the aetiology and pathogenesis of prostate cancer (PCa). This study aimed to identify aberrantly methylated differentially expressed genes (DEGs) and pathways in PCa and explore the underlying mechanisms of tumourigenesis.MethodsExpression profile (GSE29079) and methylation profile (GSE76938) datasets were obtained from the Gene Expression Omnibus (GEO). We used R 3.4.4 software to assess aberrantly methylated DEGs. The Cancer Genome Atlas (TCGA) RNA sequencing and Illumina HumanMethylation450 DNA methylation data were utilized to validate screened genes. Functional enrichment analysis of the screened genes was performed, and a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Gens (STRING). The results were visualized in Cytoscape. After confirmation using TCGA, cBioPortal was used to examine alterations in genes of interest. Then, protein localization in PCa cells was observed using immunohistochemistry.ResultsOverall, 536 hypomethylated upregulated genes were identified that were enriched in biological processes such as negative regulation of transcription, osteoblast differentiation, intracellular signal transduction, and the Wnt signalling pathway. Pathway enrichment showed significant changes in factors involved in AMPK signalling, cancer, and adherens junction pathways. The hub oncogenes were AKT1, PRDM10, and FASN. Additionally, 322 hypermethylated downregulated genes were identified that demonstrated enrichment in biological processes including positive regulation of the MAPK cascade, muscle contraction, ageing, and signal transduction. Pathway analysis indicated enrichment in arrhythmogenic right ventricular cardiomyopathy (ARVC), focal adhesion, dilated cardiomyopathy, and PI3K-AKT signalling. The hub tumour suppressor gene was FLNA. Immunohistochemistry showed that AKT1, FASN, and FLNA were mainly expressed in PCa cell cytoplasm, while PRDM10 was mainly expressed in nuclei.ConclusionsOur results identify numerous novel genetic and epigenetic regulatory networks and offer molecular evidence crucial to understanding the pathogenesis of PCa. Aberrantly methylated hub genes, including AKT1, PRDM10, FASN, and FLNA, can be used as biomarkers for accurate PCa diagnosis and treatment. In conclusion, our study suggests that AKT1, PRDM10, and FASN may be tumour promoters and that FLNA may be a tumour suppressor in PCa. We hope these findings will draw more attention to these hub genes in future cancer studies.

Project description:Introduction: Ulcerative colitis (UC) is a chronic inflammatory disease of the intestine whose cause and underlying mechanisms are not fully understood. The aim of this study was to use bioinformatics analysis to identify differentially expressed genes (DEGs) with diagnostic and therapeutic potential in UC. Materials and methods: Three UC datasets (GSE179285, GSE75214, GSE48958) were downloaded from the Gene Expression Omnibus (GEO) database. DEGs between normal and UC tissues were identified using the GEO2R online tool. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed using Metascape. Protein-protein interaction network (PPI) analysis and visualization using STRING and Cytoscape. Finally, the miRNA gene regulatory network was constructed by Cytoscape to predict potential microRNAs (miRNAs) associated with DEGs. Results: A total of 446 DEGs were identified, consisting of 309 upregulated genes and 137 downregulated genes. The enriched functions and pathways of the DEGs include extracellular matrix, regulation of cell adhesion, inflammatory response, response to cytokine, monocarboxylic acid metabolic process, response to toxic substance. The analysis of KEGG pathway indicates that the DEGs were significantly enriched in Complement and coagulation cascades, Amoebiasis, TNF signaling pathway, bile secretion, and Mineral absorption. Combining the results of the PPI network and CytoHubba, 9 hub genes including CXCL8, ICAM1, CXCR4, CD44, IL1B, MMP9, SPP1, TIMP1, and HIF1A were selected. Based on the DEG-miRNAs network construction, 7 miRNAs including miR-335-5p, mir-204-5p, miR-93-5p, miR106a-5p, miR-21-5p, miR-146a-5p, and miR-155-5p were identified as potential critical miRNAs. Conclusion: In summary, we identified DEGs that may be involved in the progression or occurrence of UC. A total of 446 DEGs,9 hub genes and 7 miRNAs were identified, which may be considered as biomarkers of UC. Further studies, however, are needed to elucidate the biological functions of these genes in UC.

Dataset Information

Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis.

Publications

Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets