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bioRxiv · 10.1101/2023.02.22.529500

Identification of novel prognostic targets in coronary artery disease and related complications using bioinformatics and next generation sequencing data analysis

Vastrad, B. M.·Vastrad, C. M.
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Abstract

Coronary artery disease (CAD) is the most common cardiovascular disorder and the leading cause of heart-related deaths in world. Increasing molecular targets have been discovered for CAD and CAD - related complications prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might help the diagnosis and treatment of CAD and CAD - related complications. We searched next generation sequencing (NGS) dataset (GSE202625) and identified differentially expressed genes (DEGs) by comparing CAD and normal control samples using DESeq2. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g:Profiler online database. The protein-protein interaction (PPI) network was plotted with IMEx interactome and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. MiRNA - hub gene regulatory network and TF - hub gene regulatory network analysis was performed to identify the hub genes, miRNAs and TFs. Receiver operating characteristic (ROC) curve analysis was used to predict the diagnostic effectiveness of the hub genes. A total of 118 DEGs (479 up regulated genes and 479 down regulated genes) were detected. The GO enrichment analysis indicated that the DEGs most significantly enriched in cellular response to stimulus and biosynthetic process. The REACTOME pathway enrichment analysis revealed that the DEGs were most significantly enriched in immune system and eukaryotic translation elongation. PPI network, modules, miRNA - hub gene regulatory network and TF - hub gene regulatory network analysis demonstrated that EGR1, SIRT1, STAT1, LRRK2, HIF1A, CSNK2B, RPS3, RPS2, RPS4X and HDAC11 were the hub genes. On the whole, the findings of this study enhance our understanding of the potential molecular mechanisms of CAD and CAD-related complications, and provide potential targets for further research.

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Vastrad, B. M., Vastrad, C. M.. 2023-02-22. Identification of novel prognostic targets in coronary artery disease and related complications using bioinformatics and next generation sequencing data analysis. https://doi.org/10.1101/2023.02.22.529500

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