RNA-Seq and Microarray Data Analysis of Coronary Artery Calcification, Coronary Artery Disease and Ischemic Cardiomyopathy for the Identification of Potential Biomarkers

Abstract

Cardiovascular diseases are the major cause of death globally. The biomarker profile of heart diseases can improve the risk prediction or prognosis. As cardiovascular diseases involve several pathophysiological processes involved in a disease, a single marker is not sufficient to identify the disease severity. Microarray and nextgeneration sequencing techniques are useful in understanding the disease at the transcriptome level. Differential gene expression along with pathway analysis and gene ontology was performed to identify key candidate genes involved in these three disease phenotypes i.e. CAC, CAD, and ICM. The thresholds for differentially expressed genes were maintained similar for p-value as <0.05 and -0.5>log2FC>0.5 for log2FC. Pathway analysis revealed three common enriched pathways based on p-value in both techniques are regulation of actin cytoskeleton, Herpes simplex virus 1 infection, and neuroactive ligand-receptor interaction. Pathway analysis revealed genes i.e. CXCL12, CCL5, CXCR4, PAK1/3, MYLPF, F2, MAP2K1/2, CALCR, and GRM2 that are important in these disease phenotypes. CXCL12 and CXCR4 were found common in all phenotypes and in both techniques. Several proteins like integrin family proteins and zinc finger family proteins were also found important and need further evaluation. Pathway analysis revealed some other vital cascades that need to be further examined in the future i.e. cell adhesion molecules, complement and coagulation cascades, MAPK signaling, chemokine signaling, and sphingolipid signaling pathway. A gene set of twelve common differentially expressed genes including VAMP8, ARHGAP15, RABGAP1L, CXCL12, CXCR4, PRDM1, TXLNGY, MYBL1, SPP1, PTGS2, HLA-DPB1 and CTSK in RNA-Seq and microarray and among coronary artery calcification, coronary artery disease and ischemic cardiomyopathy can serve as as potential biomarkers in future for the prediction of these heart diseases however, it requires wet lab experimentation.