In a new publication from Cardiovascular Innovations and Applications, Yukuan Chen, Xiaohui Wu, Danchun Hu and Wei Wang, from the Shantou University Medical College, Shantou, China and Second Affiliated Hospital of Shantou University Medical College, Shantou, China consider the importance of mitochondrial-related genes in dilated cardiomyopathy.
The authors designed this study to identify potential key protein interaction networks, genes, and correlated pathways in dilated cardiomyopathy (DCM) via bioinformatics methods.
A GSE3586 microarray dataset was selected, consisting of 15 dilated cardiomyopathic heart biopsy samples and 13 nonfailing heart biopsy samples. Initially, the GSE3586 dataset was downloaded and was analyzed with the limma package to identify differentially expressed genes (DEGs).
A total of 172 DEGs consisting of 162 upregulated genes and ten downregulated genes in DCM were selected by the criterion of adjusted Pvalues less than 0.01 and the log2-fold change of 0.6 or greater.
Gene Ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to view the biological processes, cellular components, molecular function, and KEGG pathways of the DEGs. Protein-protein interactions were constructed, and the hub protein modules were identified.
The key genes DLD, UQCRC2, DLAT, SUCLA2, ATP5A1, PRDX3, FH, SDHD, and NDUFV1, were then selected; these are involved in a wide range of biological activities, such as the citrate cycle, oxidation-reduction processes and cellular respiration, and energy derivation by oxidation of organic compounds in mitochondria.
The authors found that currently there are no related gene-targeting drugs after exploring the predicted interactions between key genes and drugs, and transcription factors, providing greater understanding of the pathogenesis and underlying molecular mechanisms in DCM.
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Journal reference:
Wang, W., et al. (2020) Importance of Mitochondrial-Related Genes in Dilated Cardiomyopathy Based on Bioinformatics Analysis. Cardiovascular Innovations and Applications. doi.org/10.15212/CVIA.2019.0588.