Identifying Key Genes and Related Molecules as Potential Biomarkers in Human Dilated Cardiomyopathy by Comprehensive Bioinformatics Analysis

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Dilated cardiomyopathy (DCM) is a non-ischemic heart disease that poses a substantial global health burden, but its underlying molecular mechanisms remain poorly understood.

Weighted gene co-expression network analysis, differential expression analysis of genes, enriched analysis and LASSO model construction were performed in R software. miRWalk 2.0 and StarBase v2.0 were used to predict the target miRNAs and circRNAs of hub genes, respectively.

Four hub genes (COL3A1, COL1A2, LUM and THBS4) were identified, which were significantly enriched in fibrosis pathways, including extracellular matrix, biological process, and the TGF beta signaling and focal adhesion pathways. The LASSO model accurately predicted the occurrence of DCM. Additionally, three miRNAs (hsa-let-7b-5p, hsa-let-7c-5p and hsa-miR-29b-3p) and 30 circRNAs (including GIT2_hsa_circRNA10114, ANKRD52_hsa_circRNA9983 and JARID2_hsa_circRNA6618) were found to be associated with DCM.

Bioinformatics analysis identified hub genes and related molecules that may be highly associated with DCM. These findings provide insights into potential targets for improving diagnosis and pharmacological therapies to prevent DCM progression.

https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2023.0018

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Yingrui Li, Jianlin Du and Bin Liu et al. Identifying Key Genes and Related Molecules as Potential Biomarkers in Human Dilated Cardiomyopathy by Comprehensive Bioinformatics Analysis. CVIA. 2023. Vol. 8(1). DOI: 10.15212/CVIA.2023.0018