Whole-transcriptome sequencing analysis reveal mechanisms of Yiqi Huoxue Yangyin (YHY) decoction in ameliorating D-gal-induced cardiac aging

Wang, Xue; Zhang, Jiaqi; Xiu, Chengkui; Yang, Jing; Liu, Yiqing; Yan, Lei

doi:10.18632/aging.204532

Cited by 1 publication

(1 citation statement)

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“…For protein interaction analysis and identification of crucial protein genes associated with mitophagy-DEGs, we built a PPI network using STRING, considering interactions with a score > 0.4. PPI network was generated through Cytoscape version 3.8.2 [ 18 ], and significant modules were identified using MCODE, a Cytoscape plugin that applies specific criteria including degree cut-off = 2, MCODE scores > 5, max depth = 100, k-score = 2, and node score cutoff = 0.2. Lastly, we performed cytoHubba analysis to identify hub genes by applying the MCC method to rank the top six genes in the network.…”

Section: Methodsmentioning

confidence: 99%

Bioinformatics integration reveals key genes associated with mitophagy in myocardial ischemia-reperfusion injury

Chen,

Liu,

Yuan

et al. 2024

BMC Cardiovasc Disord

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Background Myocardial ischemia is a prevalent cardiovascular disorder associated with significant morbidity and mortality. While prompt restoration of blood flow is essential for improving patient outcomes, the subsequent reperfusion process can result in myocardial ischemia–reperfusion injury (MIRI). Mitophagy, a specialized autophagic mechanism, has consistently been implicated in various cardiovascular disorders. However, the specific connection between ischemia–reperfusion and mitophagy remains elusive. This study aims to elucidate and validate central mitophagy-related genes associated with MIRI through comprehensive bioinformatics analysis. Methods We acquired the microarray expression profile dataset (GSE108940) from the Gene Expression Omnibus (GEO) and identified differentially expressed genes (DEGs) using GEO2R. Subsequently, these DEGs were cross-referenced with the mitophagy database, and differential nucleotide sequence analysis was performed through enrichment analysis. Protein–protein interaction (PPI) network analysis was employed to identify hub genes, followed by clustering of these hub genes using cytoHubba and MCODE within Cytoscape software. Gene set enrichment analysis (GSEA) was conducted on central genes. Additionally, Western blotting, immunofluorescence, and quantitative polymerase chain reaction (qPCR) analyses were conducted to validate the expression patterns of pivotal genes in MIRI rat model and H9C2 cardiomyocytes. Results A total of 2719 DEGs and 61 mitophagy-DEGs were identified, followed by enrichment analyses and the construction of a PPI network. HSP90AA1, RPS27A, EEF2, EIF4A1, EIF2S1, HIF-1α, and BNIP3 emerged as the seven hub genes identified by cytoHubba and MCODE of Cytoscape software. Functional clustering analysis of HIF-1α and BNIP3 yielded a score of 9.647, as determined by Cytoscape (MCODE). In our MIRI rat model, Western blot and immunofluorescence analyses confirmed a significant elevation in the expression of HIF-1α and BNIP3, accompanied by a notable increase in the ratio of LC3II to LC3I. Subsequently, qPCR confirmed a significant upregulation of HIF-1α, BNIP3, and LC3 mRNA in the MIRI group. Activation of the HIF-1α/BNIP3 pathway mediates the regulation of the degree of Mitophagy, thereby effectively reducing apoptosis in rat H9C2 cardiomyocytes. Conclusions This study has identified seven central genes among mitophagy-related DEGs that may play a pivotal role in MIRI, suggesting a correlation between the HIF-1α/BNIP3 pathway of mitophagy and the pathogenesis of MIRI. The findings highlight the potential importance of mitophagy in MIRI and provide valuable insights into underlying mechanisms and potential therapeutic targets for further exploration in future studies.

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Section: Methodsmentioning

confidence: 99%