miR-194-3p regulates epithelial-mesenchymal transition in embryonic epicardial cells via p120/ß-catenin signaling.

The epicardium is integral to cardiac development and facilitates endogenous heart regeneration and repair. While miR-194-3p is associated with cellular migration and invasion, its impact on epicardial cells remains uncharted. In this work we use gain-of-function and loss-of-function methodologies to investigate the function of miR-194-3p in cardiac development. We culture embryonic epicardial cells in vitro and subject them to transforming growth factor ß (TGF-ß) treatment to induce epithelial-mesenchymal transition (EMT) and monitor miR-194-3p expression. In addition, the effects of miR-194-3p mimics and inhibitors on epicardial cell development and changes in EMT are investigated. To validate the binding targets of miR-194-3p and its ability to recover the target gene-phenotype, we produce a mutant vector p120-catenin-3'UTR-MUT. In epicardial cells, TGF-ß-induced EMT results in a notable overexpression of miR-194-3p. The administration of miR-194-3p mimics promotes EMT, which is correlated with elevated levels of mesenchymal markers. Conversely, miR-194-3p inhibitor attenuates EMT. Further investigations reveal a negative correlation between miR-194-3p and p120-catenin, which influences ß-catenin level in the cell adhesion pathway. The suppression of EMT caused by the miR-194-3p inhibitor is balanced by silencing of p120-catenin. In conclusion, miR-194-3p directly targets p120-catenin and modulates its expression, which in turn alters ß-catenin expression, critically influencing the EMT process in the embryonic epicardial cells via the cell adhesion mechanism.

Integrated analysis reveals ceRNA network of cardiac remodeling by SGLT2 inhibitor in middle-aged hypertensive rats.

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) represent an innovative class of antidiabetic agents that have demonstrated promise in mitigating cardiac remodeling. However, the transcriptional regulatory mechanisms underpinning their impact on blood pressure and the reversal of hypertension-induced cardiac remodeling remain largely unexplored. Given this context, our study concentrated on comparing the cardiac expression profiles of lncRNAs and mRNAs between Wistar-Kyoto (WKY) rats and spontaneously hypertensive rats (SHR). To validate our results, we performed blood pressure measurements, tissue staining, and qRT-PCR. The treatment led to a significant reduction in systolic blood pressure and improved cardiac remodeling by reducing myocardial fibrosis and regulating the inflammatory response. Our examination disclosed that ventricular tissue mRNA, regulated by hypertension, was primarily concentrated in the complement and coagulation cascades and cytokine-cytokine receptor interactions. Compared with SHR, the SGLT2i treatment group was associated with myocardial contraction. Investigation into the lncRNA-mRNA regulatory network and competing endogenous RNA (ceRNA) network suggested that the potential roles of these differentially expressed (DE) lncRNAs and mRNAs were tied to processes such as collagen fibril organization, inflammatory response, and extracellular matrix (ECM) modifications. We found that the expression of Col3a1, C1qa, and lncRNA NONRATT007139.2 were altered in the SHR group and that SGLT2i treatment reversed these changes. Our results suggest that dapagliflozin effectively reverses hypertension-induced myocardial remodeling through a lncRNA-mRNA transcriptional regulatory network, with immune cell-mediated ECM deposition as a potential regulatory target. This underlines the potentiality of SGLT2i and genes related to immunity as promising targets for the treatment of hypertension.

Single-cell and spatial heterogeneity landscapes of mature epicardial cells.

Tbx18, Wt1, and Tcf21 have been identified as epicardial markers during the early embryonic stage. However, the gene markers of mature epicardial cells remain unclear. Single-cell transcriptomic analysis was performed with the Seurat, Monocle, and CellphoneDB packages in R software with standard procedures. Spatial transcriptomics was performed on chilled Visium Tissue Optimization Slides (10x Genomics) and Visium Spatial Gene Expression Slides (10x Genomics). Spatial transcriptomics analysis was performed with Space Ranger software and R software. Immunofluorescence, whole-mount RNA in situ hybridization and X-gal staining were performed to validate the analysis results. Spatial transcriptomics analysis revealed distinct transcriptional profiles and functions between epicardial tissue and non-epicardial tissue. Several gene markers specific to postnatal epicardial tissue were identified, including Msln, C3, Efemp1, and Upk3b. Single-cell transcriptomic analysis revealed that cardiac cells from wildtype mouse hearts (from embryonic day 9.5 to postnatal day 9) could be categorized into six major cell types, which included epicardial cells. Throughout epicardial development, Wt1, Tbx18, and Upk3b were consistently expressed, whereas genes including Msln, C3, and Efemp1 exhibited increased expression during the mature stages of development. Pseudotime analysis further revealed two epicardial cell fates during maturation. Moreover, Upk3b, Msln, Efemp1, and C3 positive epicardial cells were enriched in extracellular matrix signaling. Our results suggested Upk3b, Efemp1, Msln, C3, and other genes were mature epicardium markers. Extracellular matrix signaling was found to play a critical role in the mature epicardium, thus suggesting potential therapeutic targets for heart regeneration in future clinical practice.

Identification of key genes and mechanisms of epicardial adipose tissue in patients with diabetes through bioinformatic analysis.

Background: In recent years, peri-organ fat has emerged as a diagnostic and therapeutic target in metabolic diseases, including diabetes mellitus. Here, we performed a comprehensive analysis of epicardial adipose tissue (EAT) transcriptome expression differences between diabetic and non-diabetic participants and explored the possible mechanisms using various bioinformatic tools. Methods: RNA-seq datasets GSE108971 and GSE179455 for EAT between diabetic and non-diabetic patients were obtained from the public functional genomics database Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were identified using the R package DESeq2, then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed. Next, a PPI (protein-protein interaction) network was constructed, and hub genes were mined using STRING and Cytoscape. Additionally, CIBERSORT was used to analyze the immune cell infiltration, and key transcription factors were predicted based on ChEA3. Results: By comparing EAT samples between diabetic and non-diabetic patients, a total of 238 DEGs were identified, including 161 upregulated genes and 77 downregulated genes. A total of 10 genes (IL-1ß, CD274, PDCD1, ITGAX, PRDM1, LAG3, TNFRSF18, CCL20, IL1RN, and SPP1) were selected as hub genes. GO and KEGG analysis showed that DEGs were mainly enriched in the inflammatory response and cytokine activity. Immune cell infiltration analysis indicated that macrophage M2 and T cells CD4 memory resting accounted for the largest proportion of these immune cells. CSRNP1, RELB, NFKB2, SNAI1, and FOSB were detected as potential transcription factors. Conclusion: Comprehensive bioinformatic analysis was used to compare the difference in EAT between diabetic and non-diabetic patients. Several hub genes, transcription factors, and immune cell infiltration were identified. Diabetic EAT is significantly different in the inflammatory response and cytokine activity. These findings may provide new targets for the diagnosis and treatment of diabetes, as well as reduce potential cardiovascular complications in diabetic patients through EAT modification.

Transcription factor Foxp1 stimulates angiogenesis in adult rats after myocardial infarction.

Forkhead box protein P1 (FoxP1) is essential for cardiac development and the regulation of neovascularization, but its potential for cardiac angiogenesis has not been explored. This study aims to investigate the angiogenic role of FoxP1 in a rat model of myocardial infarction (MI). Adult male rats were subjected to MI, and Foxp1 was knocked down with lentivirus FoxP1 siRNA. Endothelial cell proliferation, angiogenesis, and cardiac function were also assessed. Cell scratch assay and tubule formation analysis were used to detect the migration ability and tube formation ability of human umbilical vein endothelial cells (HUVECs). Compared with that in the sham group, results showed that the expression of FoxP1 was significantly increased in the MI group. Foxp1 knockdown decreases FoxP1 expression, reduces angiogenesis, and increases collagen deposition. When Foxp1 was knocked down in HUVECs using FoxP1 siRNA lentivirus, cell proliferation, migration, and tube formation abilities decreased significantly. Our study showed that FoxP1 elicits pleiotropic beneficial actions on angiogenesis in the post-MI heart by promoting the proliferation of endothelial cells. FoxP1 should be considered a candidate for therapeutic cardiac angiogenesis.

Predicting the Key Genes Involved in Aortic Valve Calcification Through Integrated Bioinformatics Analysis.

Background: Valvular heart disease is obtaining growing attention in the cardiovascular field and it is believed that calcific aortic valve disease (CAVD) is the most common valvular heart disease (VHD) in the world. CAVD does not have a fully effective treatment to delay its progression and the specific molecular mechanism of aortic valve calcification remains unclear. Materials and Methods: We obtained the gene expression datasets GSE12644 and GSE51472 from the public comprehensive free database GEO. Then, a series of bioinformatics methods, such as GO and KEGG analysis, STING online tool, Cytoscape software, were used to identify differentially expressed genes in CAVD and healthy controls, construct a PPI network, and then identify key genes. In addition, immune infiltration analysis was used via CIBERSORT to observe the expression of various immune cells in CAVD. Results: A total of 144 differential expression genes were identified in the CAVD samples in comparison with the control samples, including 49 up-regulated genes and 95 down-regulated genes. GO analysis of DEGs were most observably enriched in the immune response, signal transduction, inflammatory response, proteolysis, innate immune response, and apoptotic process. The KEGG analysis revealed that the enrichment of DEGs in CAVD were remarkably observed in the chemokine signaling pathway, cytokine-cytokine receptor interaction, and PI3K-Akt signaling pathway. Chemokines CXCL13, CCL19, CCL8, CXCL8, CXCL16, MMP9, CCL18, CXCL5, VCAM1, and PPBP were identified as the hub genes of CAVD. It was macrophages that accounted for the maximal proportion among these immune cells. The expression of macrophages M0, B cells memory, and Plasma cells were higher in the CAVD valves than in healthy valves, however, the expression of B cells naïve, NK cells activated, and macrophages M2 were lower. Conclusion: We detected that chemokines CXCL13, CXCL8, CXCL16, and CXCL5, and CCL19, CCL8, and CCL18 are the most important markers of aortic valve disease. The regulatory macrophages M0, plasma cells, B cells memory, B cells naïve, NK cells activated, and macrophages M2 are probably related to the occurrence and the advancement of aortic valve stenosis. These identified chemokines and these immune cells may interact with a subtle adjustment relationship in the development of calcification in CAVD.

Inhibition of Notch Signaling Promotes the Differentiation of Epicardial Progenitor Cells into Adipocytes.

BACKGROUND: The role of Notch signaling pathway in the differentiation of epicardial progenitor cells (EPCs) into adipocytes is unclear. The objective is to investigate the effects of Notch signaling on the differentiation of EPCs into adipocytes. METHODS: Frozen sections of C57BL/6J mouse hearts were used to observe epicardial adipose tissue (EAT), and genetic lineage methods were used to trace EPCs. EPCs were cultured in adipogenic induction medium with Notch ligand jagged-1 or γ-secretase inhibitor DAPT. The adipocyte markers, Notch signaling, and adipogenesis transcription factors were determined. RESULTS: There was EAT located at the atrial-ventricular groove in mouse. By using genetic lineage tracing methods, we found that EPCs were a source of epicardial adipocytes. EPCs had lipid droplet accumulation, and the expression of adipocyte markers FABP-4 and perilipin-1 was upregulated under adipogenic induction. Activating the Notch signaling with jagged-1 attenuated the adipogenic differentiation of EPCs and downregulated the key adipogenesis transcription factor peroxisome proliferator activated receptor-γ (PPAR-γ), while inhibiting the signaling promoted adipogenic differentiation and upregulated PPAR-γ. When blocking PPAR-γ, the role of Notch signaling in promoting adipogenic differentiation was inhibited. CONCLUSIONS: EPCs are a source of epicardial adipocytes. Downregulation of the Notch signaling pathway promotes the differentiation of EPCs into adipocytes via PPAR-γ.

Investigation of the underlying genes and mechanism of familial hypercholesterolemia through bioinformatics analysis.

BACKGROUND: Familial hypercholesterolemia (FH) is one of the commonest inherited metabolic disorders. Abnormally high level of low-density lipoprotein cholesterol (LDL-C) in blood leads to premature atherosclerosis onset and a high risk of cardiovascular disease (CVD). However, the specific mechanisms of the progression process are still unclear. Our study aimed to investigate the potential differently expressed genes (DEGs) and mechanism of FH using various bioinformatic tools. METHODS: GSE13985 and GSE6054 were downloaded from the Gene Expression Omnibus (GEO) database for bioinformatic analysis in this study. First, limma package of R was used to identify DEGs between blood samples of patients with FH and those from healthy individuals. Then, the functional annotation of DEGs was carried out by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Ontology (GO) analysis. Based on Search Tool for the Retrieval of Interacting Genes (STRING) tool, we constructed the Protein-Protein Interactions (PPIs) network among DEGs and mined the core genes as well. RESULTS: A total of 102 communal DEGs (49 up-regulated and 53 down-regulated) are identified in FH samples compared with control samples. The functional changes of DEGs are mainly associated with the focal adhere and glucagon signaling pathway. Ten genes (ITGAL, TLN1, POLR2A, CD69, GZMA, VASP, HNRNPUL1, SF1, SRRM2, ITGAV) were identified as core genes. Bioinformatic analysis showed that the core genes are mainly enriched in numerous processes related to cell adhesion, integrin-mediated signaling pathway and cell-matrix adhesion. In the transcription factor (TF) target regulating network, 219 nodes were detected, including 214 DEGs and 5 TFs (SP1, EGR3, CREB, SEF1, HOX13). In conclusion, the DEGs and hub genes identified in this study may help us understand the potential etiology of the occurrence and development of AS. CONCLUSION: Up-regulated ITGAL, TLN1, POLR2A, VASP, HNRNPUL1, SF1, SRRM2, and down-regulated CD69, GZMA and ITGAV performed important promotional effects for the formation of atherosclerotic plaques those suffering from FH. Moreover, SP1, EGR3, CREB, SEF1 and HOX13 were the potential transcription factors for DEGs and could serve as underlying targets for AS rupture prevention. These findings provide a theoretical basis for us to understand the potential etiology of the occurrence and development of AS in FH patients and we may be able to find potential diagnostic and therapeutic targets.