Integrated bioinformatics analysis for identifying key genes and pathways in female and male patients with dilated cardiomyopathy

Abstract

Dilated cardiomyopathy (DCM) is a common cause of heart failure, and males are more likely to suffer from DCM than females. This research aimed at exploring possible DCM-associated genes and their latent regulatory effects in female and male patients. WGCNA analysis found that in the yellow module, 341 and 367 key DEGs were identified in females and males, respectively. A total of 22 hub genes in females and 17 hub genes in males were identified from the PPI networks of the key DEGs based on Metascape database. And twelve and eight potential TFs of the key DEGs were also identified in females and males, respectively. Eight miRNAs of 15 key DEGs were screened in both females and males, which may be differentially expressed in females and males. Dual-luciferase reporter assay demonstrated that miR-21-5P could directly target the key gene MATN2. Furthermore, Sex differences in KEGG pathways were identified. Both KOBAS and GSEA analysis identified 19 significantly enriched pathways related to immune response in both females and males, and the TGF-β signaling pathway was exclusively identified in males. Network pharmacology analysis revealed that seven key DEGs were potential targets for the treatment of DCM, of which the OLR1 gene was only identified in males, the expression levels of the seven genes were verified by RT-PCR. The above results could offer a novel understanding of sex differences in key genes and pathways in DCM progression.

Entropy pelican optimization algorithm (epoa) based feature selection and deep autoencoder (dae) of heart failure status prediction

“…Zhang et al (21) suggested the WGCNA to find possible biomarkers and therapeutic targets. According to the Meta scape database, PPI networks of the important DEG.…”

Identification of renal ischemia reperfusion injury-characteristic genes, pathways and immunological micro-environment features through bioinformatics approaches

“…Besides, gene correlation networks have been widely constructed to extensively understand the mechanism underlying the high-throughput sequencing data [3]. Weighted gene coexpression network analysis (WGCNA) was a common gene correlation analysis method [4], which supplied complete interpretation into the detail of molecular interactions [5][6][7][8]. In this study, RNA sequencing datasets referred to kidney IRI were collected from the Gene Expression Omnibus (GEO) database.…”