உயிரியல், வேளாண்மை & சுகாதார அறிவியல் பற்றிய குளோபல் ஜர்னல்

சுருக்கம்

Construction of miRNAs and Gene Expression Profiles Associated with Ischemic Cardiomyopathy: Bioinformatics Analysis

Phong Son Dinh, Jun-Hua Peng, ChauMy Thanh Tran, Thanh Loan Tran, Shang-Ling Pan

Objective: Ischemic Cardiomyopathy (ICM) has ranked as the most common cause morbidity and mortality in the elderly over the past decades. One of the most important reasons for this is that its exact underlying mechanism remains poorly understood.

Method: Five datasets were downloaded from the GEO database. Differential Gene Expression (DGE) was identified by the R RobustRankAggreg package. Differential miRNA expression was evaluated by the Limma package. Gene potential functions were then determined by the clusterProfiler database. The miRNA-DGE regulatory network was predicted by cyTargetLinker. Then, a protein-protein interaction network was constructed by STRING tool, MCODE, and BiNGO tool.

Results: 91 miRNAs and 274 potential genes were identified. Of these, COL1A1, IGF1 and CCND1 were found to be involved in many signaling pathways; and miR-9-5p was found to play critical roles in ICM.

Conclusion: Our study has unraveled the potential key genes and miRNAs as well as the possible underlying molecular pathogenesis of ICM, which is a crucial step leading to a new avenue for the early intervention of this disorder.

Objective: Ischemic Cardiomyopathy (ICM) has ranked as the most common cause morbidity and mortality in the elderly over the past decades. One of the most important reasons for this is that its exact underlying mechanism remains poorly understood.

Method: Five datasets were downloaded from the GEO database. Differential Gene Expression (DGE) was identified by the R RobustRankAggreg package. Differential miRNA expression was evaluated by the Limma package. Gene potential functions were then determined by the clusterProfiler database. The miRNA-DGE regulatory network was predicted by cyTargetLinker. Then, a protein-protein interaction network was constructed by STRING tool, MCODE, and BiNGO tool.

Results: 91 miRNAs and 274 potential genes were identified. Of these, COL1A1, IGF1 and CCND1 were found to be involved in many signaling pathways; and miR-9-5p was found to play critical roles in ICM.

Conclusion: Our study has unraveled the potential key genes and miRNAs as well as the possible underlying molecular pathogenesis of ICM, which is a crucial step leading to a new avenue for the early intervention of this disorder.