Key result
A dysregulated lncRNA-mRNA network distinguishes CAD from normal samples with ~0.96 AUC.
Why the study?
The expression profile of lncRNAs in CAD patients had not yet been fully explored, prompting investigation into lncRNA-based prognostic biomarkers for CAD.
Observational
Effect estimate: AUC 0.958
Systematic bioinformatics analysis of expression profiles identified novel lncRNA-mRNA regulatory pairs with high diagnostic accuracy for coronary artery disease and potential drug targets.
May support CAD diagnostic development; leaves open prospective validation before clinical use.
BACKGROUND: The expression profile of lncRNAs in coronary artery disease (CAD) patients has not yet been fully explored. Therefore, the current study aimed to investigate lncRNA-based prognostic biomarkers for CAD. METHODS: The expression profiles of lncRNA and messenger RNA (mRNA) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed lncRNA (DElncRNAs) and DEmRNAs were identified from CAD and normal samples, and weighted gene co-expression network analysis (WGCNA) was conducted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the principal functions of significantly dysregulated genes. The potential drugs of new CAD-specific genes were identified by network distance method. Receiver operating characteristic (ROC) was used to verify the classification performance of genes. RESULTS: A total of 512 differentially expressed genes (DEGs) and 308 DElncRNAs were identified from GSE113079 dataset to classify CAD samples. Through WGCNA co-expression analysis, 24 co-expression modules were obtained. A total of 187 DElncRNAs and 253 DEGs were determined from 7 modules correlated with CAD. Functional enrichment analysis showed that these DEGs were mainly related to inflammatory and immune-related pathways. Furthermore, 36 regulatory pairs of significantly shared micro RNAs (miRNAs) were identified as dysregulated lncRNA-mRNA (LRM-CAD), which contained 11 lncRNAs and 33 genes. Compared with a single lncRNA or gene, LRM-CAD showed stronger classification performance [average area under the curve (AUC) =0.958]. We screened 3 potential therapeutic drugs, DB09105, DB12371, and DB12612, a by binding drug-target gene interaction network. Molecular docking verified that the S1PR1 gene bound relatively closely to DB12371 and DB12612. The ROC analysis on external data sets showed that S1PR1, AC012640.4, and S1PR1-AC012640.4 could effectively distinguish CAD samples from control samples. CONCLUSIONS: We provided a transcriptome overview of abnormally expressed lncRNAs in CAD patients and identified novel biomarkers for diagnosing CAD.
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Chen et al. (2021) conducted an observational in Coronary artery disease. Dysregulated lncRNA-mRNA network (LRM-CAD) vs. Single lncRNA or gene was evaluated on Classification performance for CAD (AUC 0.958). A dysregulated lncRNA-mRNA network (LRM-CAD) demonstrated strong classification performance for distinguishing coronary artery disease from normal samples (average AUC = 0.958).
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