Abstract
BackgroundThe purpose of this study was to explore the potential molecular targets of hyperlipidaemia and the related molecular mechanisms.MethodsThe 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.ResultsThe 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.ConclusionsSQLE and SCD are related to hyperlipidaemia, and SQLE/SCD may be new targets for cholesterol-lowering or triglyceride-lowering therapy, respectively.
Highlights
The purpose of this study was to explore the potential molecular targets of hyperlipidaemia and the related molecular mechanisms
Combined with the topological overlap matrix (TOM), the gene modules of each gene network were identified by the hierarchical average linkage clustering method, and twenty gene modules were identified by the dynamic tree cut algorithm (Fig. 3)
Weighted gene co-expression network analysis (WGCNA) identified that the royal blue module was significantly associated with total cholesterol (TC), TG and non-HDL
Summary
The purpose of this study was to explore the potential molecular targets of hyperlipidaemia and the related molecular mechanisms. Hyperlipidaemia (HLP) acts as a critical risk factor that gives rise to CAD and its complications. Several investigations have demonstrated that for every 2% decrease in high-density lipoprotein cholesterol (HDL-C) levels, there is a resultant increase in CAD risk by 1%. Every 1% decrease in low-density lipoprotein cholesterol (LDL-C) levels results in reducing CAD risk by 1% [9, 10]. Several compelling studies have demonstrated that combined effect in reducing the triglyceride (TG) [11], LDL-C [12] and total cholesterol (TC) [11] levels yielded higher decreases in cardiovascular risk compared to reduction of LDL-C levels alone [13]. The identification of novel therapeutic targets for HLP is expected to further reduce the risk of cardiovascular disease
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