Jun 2017 DOI 10.14302/issn.2329-9487.jhc-17-1536
Md. Kamrul HossainCorresponding author
Over the last few decades, many research works highlighted the role of miRNAs on cardiac diseases. Ischaemic heart disease (IHD) or coronary heart disease is a condition that is mainly caused by atherosclerosis. It has been established that microribonucleic acids regulate many factors that are involved in the development and pathophysiology of IHD. As a result, there are great potential opportunities for miRNAs to be used as a biomarker for disease differentiation, as well as novel drug targets or therapeutics for the treatment and also as a diagnostic approach. As it is now evident that miRNAs play critical roles in the disease mechanisms, this review article tried to focus on the pathway, in which; the miRNAs stimulate the IHD to develop. By understanding the mechanisms, it will be possible to present a complete strategy of IHD treatment and also solving all the impediments that are highlighted in this article. Still, there are a number of limitations and obstacles on the way of developing a proper therapeutic approach that can be approved and well accepted. This review is mainly dependent on the potential of miRNAs as a promising arena on the field of cardiac treatment and the possible obstacles that are needed to be explored and overcome.
Mar 2017 DOI 10.14302/issn.2326-0793.jpgr-17-1447
D. Howard TimothyCorresponding author
Center for Genomics & Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
Factors that contribute to the onset of atherosclerosis may be elucidated by bioinformatic techniques applied to multiple sources of genomic and proteomic data. The results of genome wide association studies, such as the CardioGramPlusC4D study, expression data, such as that available from expression quantitative trait loci (eQTL) databases, along with protein interaction and pathway data available in Ingenuity Pathway Analysis (IPA), constitute a substantial set of data amenable to bioinformatics analysis. This study used bioinformatic analyses of recent genome wide association data to identify a seed set of genes likely associated with atherosclerosis. The set was expanded to include protein interaction candidates to create a network of proteins possibly influencing the onset and progression of atherosclerosis. Local average connectivity (LAC), eigenvector centrality, and betweenness metrics were calculated for the interaction network to identify top gene and protein candidates for a better understanding of the atherosclerotic disease process. The top ranking genes included some known to be involved with cardiovascular disease (APOA1, APOA5, APOB, APOC1, APOC2, APOE, CDKN1A, CXCL12, SCARB1, SMARCA4 and TERT), and others that are less obvious and require further investigation (TP53, MYC, PPARG, YWHAQ, RB1, AR, ESR1, EGFR, UBC and YWHAZ). Collectively these data help define a more focused set of genes that likely play a pivotal role in the pathogenesis of atherosclerosis and are therefore natural targets for novel therapeutic interventions.