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Weighted gene co-expression network analysis reveals similarities and differences of molecular features between dilated and ischemic cardiomyopathies

Authors :
Felix K. Biwott
Ni-Ni Rao
Chang-Long Dong
Guang-Bin Wang
Source :
Journal of Electronic Science and Technology, Vol 21, Iss 2, Pp 100193- (2023)
Publication Year :
2023
Publisher :
KeAi Communications Co., Ltd., 2023.

Abstract

Cardiomyopathies represent the most common clinical and genetic heterogeneous group of diseases that affect the heart function. Though progress has been made to elucidate the process, molecular mechanisms of different classes of cardiomyopathies remain elusive. This paper aims to describe the similarities and differences in molecular features of dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM). We firstly detected the co-expressed modules using the weighted gene co-expression network analysis (WGCNA). Significant modules associated with DCM/ICM were identified by the Pearson correlation coefficient (PCC) between the modules and the phenotype of DCM/ICM. The differentially expressed genes in the modules were selected to perform functional enrichment. The potential transcription factors (TFs) prediction was conducted for transcription regulation of hub genes. Apoptosis and cardiac conduction were perturbed in DCM and ICM, respectively. TFs demonstrated that the biomarkers and the transcription regulations in DCM and ICM were different, which helps make more accurate discrimination between them at molecular levels. In conclusion, comprehensive analyses of the molecular features may advance our understanding of DCM and ICM causes and progression. Thus, this understanding may promote the development of innovative diagnoses and treatments.

Details

Language :
English
ISSN :
2666223X
Volume :
21
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Journal of Electronic Science and Technology
Publication Type :
Academic Journal
Accession number :
edsdoj.09685bfb164647418c661c564f652547
Document Type :
article
Full Text :
https://doi.org/10.1016/j.jnlest.2023.100193