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