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Regulatory mechanism of fibrosis-related genes in patients with heart failure

Background: Heart failure (HF) is a complex clinical syndrome characterized by the inability to match cardiac output with metabolic needs. Research on regulatory mechanism of fibrosis-related genes in patients with HF is very limited. In order to understand the mechanism of fibrosis in the developme...

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Detalles Bibliográficos
Autores principales: Tao, Yijing, Gao, ChengJie, Qian, Da, Cao, Donglai, Han, Leng, Yang, Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618712/
https://www.ncbi.nlm.nih.gov/pubmed/36324504
http://dx.doi.org/10.3389/fgene.2022.1032572
Descripción
Sumario:Background: Heart failure (HF) is a complex clinical syndrome characterized by the inability to match cardiac output with metabolic needs. Research on regulatory mechanism of fibrosis-related genes in patients with HF is very limited. In order to understand the mechanism of fibrosis in the development and progression of HF, fibrosis -related hub genes in HF are screened and verified. Methods: RNA sequencing data was obtained from the Gene Expression Omnibus (GEO) cohorts to identify differentially expressed genes (DEGs). Thereafter, fibrosis-related genes were obtained from the GSEA database and that associated with HF were screened out. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis was carried out to analyze the biological function of fibrosis-related DEGs. The protein-protein interaction (PPI) network of hub genes was constructed via the STRING database. Moreover, the diagnostic value of hub genes for HF was confirmed using ROC curves and expression analysis. Finally, quantitative real time PCR was used to detect the expression levels of mRNAs. Results: A total of 3, 469 DEGs were identified closely related to HF, and 1, 187 fibrosis-related DEGs were obtained and analyzed for GO and KEGG enrichment. The enrichment results of fibrosis-related DEGs were consistent with that of DEGs. A total of 10 hub genes (PPARG, KRAS, JUN, IL10, TLR4, STAT3, CXCL8, CCL2, IL6, IL1β) were selected via the PPI network. Receiver operating characteristic curve analysis was estimated in the test cohort, and 6 genes (PPARG, KRAS, JUN, IL10, TLR4, STAT3) with AUC more than 0.7 were identified as diagnosis genes. Moreover, miRNA-mRNA and TF-mRNA regulatory networks were constructed. Finally, quantitative real time PCR revealed these 6 genes may be used as the potential diagnostic biomarkers of HF. Conclusion: In this study, 10 fibrosis-related hub genes in the HF were identified and 6 of them were demonstrated as potential diagnostic biomarkers for HF.