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

Tao, Yijing; Gao, Chengjie; Da, Qian; Cao, Donglai; Han, Lei; Yang, Ling

doi:10.3389/fgene.2022.1032572

Cited by 5 publications

(5 citation statements)

References 49 publications

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“…Activation of TLR4 leads to the progression of cardiac hypertrophy and tissue damage [92]. In accordance with this evidence, Tao et al found TLR4 to be a hub gene capable of discriminating between HF and healthy human cardiomyocytes [90]. This observation suggests that FOXC1, as a regulator of TLR4, may play a role in the fibrotic processes associated with the development of heart failure.…”

Section: Variations In Transcription Factor Activity Profilesmentioning

confidence: 82%

“…The role of this Transcription Factor in HF possibly relates to the myocardial fibrosis process, defined as the excessive deposition of extracellular matrix in the cardiac interstitium, proliferation of cardiac fibroblasts, tissue repair, and scar formation [89]. Heart failure is often coupled with cardiac remodeling, a process characterized by various pathological changes, chief amongst which is myocardial fibrosis [90].…”

Section: Variations In Transcription Factor Activity Profilesmentioning

confidence: 99%

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A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

Pepe,

Appierdo,

Ausiello

et al. 2024

IJMS

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Cardiovascular diseases (CVDs) represent a major concern for global health, whose mechanistic understanding is complicated by a complex interplay between genetic predisposition and environmental factors. Specifically, heart failure (HF), encompassing dilated cardiomyopathy (DC), ischemic cardiomyopathy (ICM), and hypertrophic cardiomyopathy (HCM), is a topic of substantial interest in basic and clinical research. Here, we used a Partial Correlation Coefficient-based algorithm (PCC) within the context of a meta-analysis framework to construct a Gene Regulatory Network (GRN) that identifies key regulators whose activity is perturbed in Heart Failure. By integrating data from multiple independent studies, our approach unveiled crucial regulatory associations between transcription factors (TFs) and structural genes, emphasizing their pivotal roles in regulating metabolic pathways, such as fatty acid metabolism, oxidative stress response, epithelial-to-mesenchymal transition, and coagulation. In addition to known associations, our analysis also identified novel regulators, including the identification of TFs FPM315 and OVOL2, which are implicated in dilated cardiomyopathies, and TEAD1 and TEAD2 in both dilated and ischemic cardiomyopathies. Moreover, we uncovered alterations in adipogenesis and oxidative phosphorylation pathways in hypertrophic cardiomyopathy and discovered a role for IL2 STAT5 signaling in heart failure. Our findings underscore the importance of TF activity in the initiation and progression of cardiac disease, highlighting their potential as pharmacological targets.

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Section: Variations In Transcription Factor Activity Profilesmentioning

confidence: 82%

Section: Variations In Transcription Factor Activity Profilesmentioning

confidence: 99%

A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

Pepe,

Appierdo,

Ausiello

et al. 2024

IJMS

View full text Add to dashboard Cite

show abstract

“…In accordance with this evidence, Tao at al. found TLR4 to be a hub gene, capable of discriminating between HF and healthy human cardiomyocytes 72 . This observation suggests that FOXC1, as a regulator of TLR4, may play a role in the fibrotic processes associated with the development of heart failure.…”

Section: Variations In Transcription Factor Activity Profilesmentioning

confidence: 99%

“…The role of this Transcription Factor in HF possibly relates to the myocardial fibrosis process, defined as the excessive deposition of extracellular matrix in the cardiac interstitium, proliferation of cardiac fibroblasts, tissue repair, and scar formation 71 . Heart failure is often coupled with cardiac remodeling, a process characterized by various pathological changes, chief amongst which is myocardial fibrosis 72 .…”

Section: Variations In Transcription Factor Activity Profilesmentioning

confidence: 99%

A meta-analysis approach to gene regulatory network inference identifies key regulators of cardiovascular diseases

Pepe,

Appierdo,

Ausiello

et al. 2024

Preprint

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Cardiovascular diseases (CVDs) represent a major concern for global health whose mechanistic understanding is complicated by a complex interplay between genetic predisposition and environmental factors.Specifically, heart failure (HF), encompassing dilated cardiomyopathy (DC), ischemic cardiomyopathy (ICM), and hypertrophic cardiomyopathy (HCM), is a topic of substantial interest in basic and clinical research. Here we used a Partial Correlation Coefficient-based algorithm (PCC) within the context of a meta-analysis framework, to construct a Gene Regulatory Network (GRN) that identifies key regulators whose activity is perturbed in Heart Failure. By integrating data from multiple independent studies, our approach unveiled crucial regulatory associations between transcription factors (TFs) and structural genes, emphasizing their pivotal roles in regulating metabolic pathways, such as fatty acid metabolism, oxidative stress response, epithelial-to-mesenchymal transition, and coagulation. In addition to known associations, our analysis also identified novel regulators, including the identification of TFs FPM315 and MOVO-B, which are implicated in dilated cardiomyopathies, and TEAD1 and TEAD2 in both dilated and ischemic cardiomyopathies. Moreover, we uncovered alterations in adipogenesis and oxidative phosphorylation pathways in hypertrophic cardiomyopathy, and discovered a role for IL2 STAT5 signaling in heart failure.Our findings underscore the importance of TFs activity in the initiation and progression of cardiac disease, highlighting their potential as pharmacological targets.

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“…The application of these techniques has become widespread in the exploration of disease pathogenesis and molecular mechanisms, deepening our comprehension and knowledge of disease. A bioinformatics analysis revealed that six genes were identi ed as diagnostic brosis-related genes (FRGs) in heart failure, suggesting that they may be novel biomarkers for the treatment of heart failure [10]. KLF2 is strongly associated with brosis in hepatocellular carcinoma, which might be an essential promoter of cancer progression [11].…”

Section: Introductionmentioning

confidence: 99%

Revealing the meaning of fibrosis-related genes in the diagnosis, subtype and treatment of renal interstitial fibrosis

Jia,

Liu,

et al. 2023

Preprint

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Background: During the course of CKD, the patient's renal function continues to deteriorate, eventually progressing to ESRD. Renal interstitial fibrosis (RIF) is the end result of the progression of almost all types of CKD and a major cause of ESRD. However, effective and feasible treatments against RIF are comparatively rare in the clinic. Methods: In the study, we obtained 299 samples from the GEO to investigate the significance of fibrosis-related genes (FRGs). To model RIF, we employed several methods, including SVM-RFE, RF, LASSO analysis, and PPI network analysis to identify crucial FRGs. We constructed a nomogram that included four FRGs to forecast the occurrence of RIF. Besides, we used the consensus clustering algorithm to recognize subtype classifications for RIF. We adopted the ssGSEA method to explore the immune landscape in RIF. Lastly, we performed the PCA method to investigate the FRG expression pattern in RIF patients. Results: A total of 177 FRGs were identified from the genecards database, and the nomogram model was developed from the four hub FRGs (CCL5, TIMP1, ALB, and IFNG) to explore the underlying pathological mechanism of RIF. The calibration curve analysis suggested that the nomogram model possesses accurate predictive ability. The consensus clustering algorithm found that CCL5, TIMP1, and IFNG were more highly expressed in FRG cluster A, while ALB was expressed more highly in FRG cluster B. The ssGSEA results showed that apart from neutrophils, type 17 T helper cells, and immature dendritic cells, the abundance of other immune cells was higher in FRG cluster A. Our results found that FRG cluster A is closely related to RIF features. Conclusion: We identified four hub FRGs (CCL5, TIMP1, ALB, and IFNG) and constructed a nomogram to forecast the occurrence of RIF. The FRG cluster A is strongly linked to RIF characteristics. Our findings provided new insights into identifying RIF progression and early prevention and treatment of CKD.

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

Cited by 5 publications

References 49 publications

A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

A meta-analysis approach to gene regulatory network inference identifies key regulators of cardiovascular diseases

Revealing the meaning of fibrosis-related genes in the diagnosis, subtype and treatment of renal interstitial fibrosis

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