EGR1 Is Implicated in Right Ventricular Cardiac Remodeling Associated with Pulmonary Hypertension

Laggner, Maria; Oberndorfer, Felicitas; Golabi, Bahar; Bauer, Jonas; Zuckermann, Andreas; Hacker, P.; Lang, Irene M.; Skoro-Sajer, Nika; Gerges, Christian; Taghavi, Shahrokh; Jaksch, Péter; Mildner, Michael; Ankersmit, Hendrik Jan; Moser, Bernhard

doi:10.3390/biology11050677

Cited by 9 publications

(3 citation statements)

References 91 publications

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“…HBB (hemoglobin subunit beta) [59], HBA1 [60], HLA-DQA1 [61], EGR1 [62], ATF3 [63], XIST (X inactive specific transcript) [64], S100A12 [65], CD163 [66] and S100A8 [67] are closely related to the progression of diabetes mellitus. HBA2 [68], HBA1 [68], EGR1 [69], XIST (X inactive specific transcript) [70], S100A12 [71] and CD163 [72] reported to play a central role in pulmonary hypertension. CHIT1 [73], EGR1 [74], S100A12 [75], CD163 [76] and S100A8 [77] have a critical role in initiating COPD.…”

Section: Discussionmentioning

confidence: 99%

Identification of key genes and biological pathways in chronic obstructive pulmonary disease using bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2024

Preprint

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Identification of accurate biomarkers is still particularly urgent for improving the poor survival of chronic obstructive pulmonary disease (COPD) patients. In this investigation, we aimed to identity the potential biomarkers in COPD via bioinformatics and next generation sequencing (NGS) data analysis. In this investigation, the differentially expressed genes (DEGs) in COPD were identified using NGS dataset (GSE239897) from Gene Expression Omnibus (GEO) database. Subsequently, gene ontology (GO) and pathway enrichment analysis was conducted to evaluate the underlying molecular mechanisms involved in progression of COPD. Protein-protein interaction (PPI), modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network analysis were performed to determine the hub genes, miRNAs and TFs. The receiver operating characteristic (ROC) analysis was performed to determine the diagnostic value of hub genes. A total of 956 overlapping DEGs (478 up regulated and 478 down regulated genes) were identified in the NGS dataset. DEGs were mainly associated with GO functional terms and pathways in cellular response to stimulus. response to stimulus, immune system and neutrophil degranulation. There were 10 hub genes (MYC, LMNA, VCAM1, MAPK6, DDX3X, SHMT2, PHGDH, S100A9, FKBP5 and RPS6KA2) identified by PPI, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network analysis. In conclusion, the DEGs, relative GO terms, pathways and hub genes identified in the present investigation might aid in understanding of the molecular mechanisms underlying COPD progression and provide potential molecular targets and biomarkers for COPD.

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Section: Discussionmentioning

confidence: 99%

Identification of key genes and biological pathways in chronic obstructive pulmonary disease using bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2024

Preprint

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“…We observed downregulation of EGR expression in HFpEF mice, which was reversed after the use of a ferroptosis inhibitor. However, one report suggests that Egr1 is significantly associated with right ventricular hypertrophy due to pulmonary hypertension [ 60 ]. The role of Egr1 in the development of HFpEF still needs further validation.…”

Section: Discussionmentioning

confidence: 99%

Inhibition of ferroptosis reverses heart failure with preserved ejection fraction in mice

Xiong,

Liu,

Jiang

et al. 2024

J Transl Med

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Background Heart failure with preserved ejection fraction (HFpEF) accounts for approximately 50% of heart failure cases. The molecular mechanisms by which HFpEF leads to impaired diastolic function of the heart have not been clarified, nor have the drugs that target the clinical symptoms of HFpEF patients. Methods HFpEF chip data (GSE180065) was downloaded from the National Center for Biotechnology Information (NCBI) database. Differentially expressed genes (DEGs) were filtered by the limma package in R and processed for GO and KEGG pathway analyses. Then, ferroptosis-related genes in HFpEF were identified by taking the intersection between DEGs and ferroptosis-related genes. CytoHubba and MCODE were used to screen ferroptosis-related hub DEGs in the protein–protein interaction (PPI) network. Establishment of a mouse HFpEF model to validate the transcript levels of ferroptosis-related hub DEGs and ferroptosis-related phenotypes. Transcript levels of ferroptosis-related hub DEGs and HFpEF phenotypic changes in the hearts of HFpEF mice were further examined after the use of ferroptosis inhibitors. Results GO and KEGG enrichment analyses suggested that the DEGs in HFpEF were significantly enriched in ferroptosis-related pathways. A total of 24 ferroptosis-related DEGs were identified between the ferroptosis gene dataset and the DEGs. The established PPI network was further analyzed by CytoHubba and MCODE modules, and 11 ferroptosis-related hub DEGs in HFpEF were obtained. In animal experiments, HFpEF mice showed significant abnormal activation of ferroptosis. The expression trends of the 11 hub DEGs associated with ferroptosis, except for Cdh1, were consistent with the results of the bioinformatics analysis. Inhibition of ferroptosis alters the transcript levels of 11 ferroptosis-related hub DEGs and ameliorates HFpEF phenotypes. Conclusions The present study contributes to a deeper understanding of the specific mechanisms by which ferroptosis is involved in the development of HFpEF and suggests that inhibition of ferroptosis may mitigate the progression of HFpEF. In addition, eleven hub genes were recognized as potential drug binding targets.

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“…Pan, J et al noted that EGR1 downregulation alleviated cardiac injury caused by acute myocardial infarction in a TLR4/NFκB signaldependent manner [43]. Furthermore, EGR1 regulates various cardiovascular diseases, including pulmonary hypertension [44], atherosclerosis [45][46][47], and cardiac hypertrophy [48][49][50].…”

Section: Discussionmentioning

confidence: 99%

Identification of TGF-β-related genes in cardiac hypertrophy and heart failure based on single cell RNA sequencing

Huang

et al. 2023

Aging

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Background: Heart failure (HF) remains a huge medical burden worldwide. Pathological cardiac hypertrophy is one of the most significant phenotypes of HF. Several studies have reported that the TGF-β pathway plays a double-sided role in HF. Therefore, TGF-β-related genes (TRGs) may be potential therapeutic targets for cardiac hypertrophy and HF. However, the roles of TRGs in HF at the single-cell level remain unclear. Method: In this study, to analyze the expression pattern of TRGs during the progress of cardiac hypertrophy and HF, we used three public single-cell RNA sequencing datasets for HF (GSE161470, GSE145154, and GSE161153), one HF transcriptome data (GSE57338), and one hypertrophic cardiomyopathy transcriptome data (GSE141910). Weighted gene co-expression network analysis (WGCNA), functional enrichment analysis and machine learning algorithms were used to filter hub genes. Transverse aortic constriction mice model, CCK-8, wound healing assay, quantitative real-time PCR and western blotting were used to validate bioinformatics results. Results: We observed that cardiac fibroblasts (CFs) and endothelial cells showed high TGF-β activity during the progress of HF. Three modules (royalblue, brown4, and darkturquoize) were identified to be significantly associated with TRGs in HF. Six hub genes (TANC2, ADAMTS2, DYNLL1, MRC2, EGR1, and OTUD1) showed anomaly trend in cardiac hypertrophy. We further validated the regulation of the TGF-β-MYC-ADAMTS2 axis on CFs activation in vitro. Conclusions: This study identified six hub genes (TANC2, ADAMTS2, DYNLL1, MRC2, EGR1, and OTUD1) by integrating scRNA and transcriptome data. These six hub genes might be therapeutic targets for cardiac hypertrophy and HF.

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EGR1 Is Implicated in Right Ventricular Cardiac Remodeling Associated with Pulmonary Hypertension

Cited by 9 publications

References 91 publications

Identification of key genes and biological pathways in chronic obstructive pulmonary disease using bioinformatics and next generation sequencing data analysis

Identification of key genes and biological pathways in chronic obstructive pulmonary disease using bioinformatics and next generation sequencing data analysis

Inhibition of ferroptosis reverses heart failure with preserved ejection fraction in mice

Identification of TGF-β-related genes in cardiac hypertrophy and heart failure based on single cell RNA sequencing

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