RESUMO
BACKGROUND: The purpose of this study was to explore the potential molecular targets of hyperlipidaemia and the related molecular mechanisms. METHODS: The microarray dataset of GSE66676 obtained from patients with hyperlipidaemia was downloaded. Weighted gene co-expression network (WGCNA) analysis was used to analyse the gene expression profile, and the royal blue module was considered to have the highest correlation. Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were implemented for the identification of genes in the royal blue module using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool (version 6.8; http://david.abcc.ncifcrf.gov ). A protein-protein interaction (PPI) network was established by using the online STRING tool. Then, several hub genes were identified by the MCODE and cytoHubba plug-ins in Cytoscape software. RESULTS: The significant module (royal blue) identified was associated with TC, TG and non-HDL-C. GO and KEGG enrichment analyses revealed that the genes in the royal blue module were associated with carbon metabolism, steroid biosynthesis, fatty acid metabolism and biosynthesis pathways of unsaturated fatty acids. SQLE (degree = 17) was revealed as a key molecule associated with hypercholesterolaemia (HCH), and SCD was revealed as a key molecule associated with hypertriglyceridaemia (HTG). RT-qPCR analysis also confirmed the above results based on our HCH/HTG samples. CONCLUSIONS: SQLE and SCD are related to hyperlipidaemia, and SQLE/SCD may be new targets for cholesterol-lowering or triglyceride-lowering therapy, respectively.
RESUMO
BACKGROUND: The current research aimed to expound the genes and pathways that are involved in coronary artery disease (CAD) and ischaemic stroke (IS) and the related mechanisms. METHODS: Two array CAD datasets of (GSE66360 and GSE97320) and an array IS dataset (GSE22255) were downloaded. Differentially expressed genes (DEGs) were identified using the limma package. The online tool Database for Annotation, Visualization and Integrated Discovery (DAVID) (version 6.8; david.abcc.ncifcrf.gov) was used to annotate the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses of the DEGs. A protein-protein interaction (PPI) network was constructed by Cytoscape software, and then Molecular Complex Detection (MCODE) analysis was used to screen for hub genes. The hub genes were also confirmed by RT-qPCR and unconditional logistic regression analysis in our CAD and IS patients. RESULTS: A total of 20 common DEGs (all upregulated) were identified between the CAD/IS and control groups. Eleven molecular functions, 3 cellular components, and 49 biological processes were confirmed by GO enrichment analysis, and the 20 common upregulated DEGs were enriched in 21 KEGG pathways. A PPI network including 24 nodes and 68 edges was constructed with the STRING online tool. After MCODE analysis, the top 5 high degree genes, including Jun proto-oncogene (JUN, degree = 9), C-X-C motif chemokine ligand 8 (CXCL8, degree = 9), tumour necrosis factor (TNF, degree = 9), suppressor of cytokine signalling 3 (SOCS3, degree = 8) and TNF alpha induced protein 3 (TNFAIP3, degree = 8) were noted. RT-qPCR results demonstrated that the expression levels of CXCL8 were increased in IS patients than in normal participants and the expression levels of SOCS3, TNF and TNFAIP were higher in CAD/IS patients than in normal participants. Meanwhile, unconditional logistic regression analysis revealed that the incidence of CAD or IS was positively correlated with the CXCL8, SOCS3, TNF and TNFAIP3. CONCLUSIONS: The CXCL8, TNF, SOCS3 and TNFAIP3 associated with inflammation may serve as biomarkers for the diagnosis of CAD or IS. The possible mechanisms may involve the Toll-like receptor, TNF, NF-kappa B, cytokine-cytokine receptor interactions and the NOD-like receptor signalling pathways.
