Carvedilol Alters Circulating MiR-1 and MiR-214 in Heart Failure

CircCAMTA1 facilitates atrial fibrosis by regulating the miR-214-3p/TGFBR1 axis in atrial fibrillation

Circular RNAs (circRNAs) have been shown to be associated with cardiac fibrosis. Atrial fibrosis is an important pathophysiological event in the progression of atrial fibrillation (AF). Although a novel circRNA calmodulin binding transcription activator 1 (circCAMTA1) has been reported to be related with the development of AF, the detailed molecular mechanisms remain largely unknown. In this study, we found that circCAMTA1 was upregulated in atrial muscle tissues of AF patients and angiotensin-II (Ang-II)-treated human atrial fibroblasts (HAFs). Moreover, circCAMTA1 expression was positively correlated with the expression of collagen (I and III) and α-SMA in atrial muscle tissues of AF patients. In vitro experiments, knockdown of circCAMTA1 significantly suppressed Ang-II-induced HAFs proliferation and reduced the expression of atrial fibrosis-associated genes, but overexpression of circCAMTA1 exhibited opposite results. In vivo experiments, circCAMTA1 knockdown ameliorated Ang-II-induced atrial fibrosis by reducing AF incidence, AF duration, and collagen synthesis. Functionally, circCAMTA1 facilitated Ang-II-induced atrial fibrosis in vitro and in vivo via downregulating the inhibitory effect of miR-214-3p on transforming growth factor β receptor 1 (TGFBR1) expression. In conclusions, circCAMTA1 knockdown alleviated atrial fibrosis through downregulating TGFBR1 expression intermediated by miR-214-3p in AF, suggesting circCAMTA1/miR-214-3p/TGFBR1 axis may be a novel therapeutic target for AF treatment in clinic.

Identification of the Potential Molecular Mechanism of TGFBI Gene in Persistent Atrial Fibrillation

Background

Transforming growth factor beta-induced protein (TGFBI, encoded by TGFBI gene), is an extracellular matrix protein, widely expressed in variety of tissues. It binds to collagens type I, II, and IV and plays important roles in the interactions of cell with cell, collagen, and matrix. It has been reported to be associated with myocardial fibrosis, and the latter is an important pathophysiologyical basis of atrial fibrillation (AF). However, the mechanism of TGFBI in AF remains unclear. We aimed to detect the potential mechanism of TGFBI in AF via bioinformatics analysis.

Methods

The microarray dataset of GSE115574 was examined to detect the genes coexpressed with TGFBI from 14 left atrial tissue samples of AF patients. TGFBI coexpression genes were then screened using the R package. Using online analytical tools, we determined the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) annotation, and protein-protein interaction (PPI) network of TGFBI and its coexpression genes. The modules and hub genes of the PPI-network were then identified. Another dataset, GSE79768 was examined to verify the hub genes. DrugBank was used to detect the potential target drugs.

Results

In GSE115574 dataset, a total of 1818 coexpression genes (769 positive and 1049 negative) were identified, enriched in 120 biological processes (BP), 38 cellular components (CC), 36 molecular functions (MF), and 39 KEGG pathways. A PPI-network with average 12.2-degree nodes was constructed. The genes clustered in the top module constructed from this network mainly play a role in PI3K-Akt signaling pathway, viral myocarditis, inflammatory bowel disease, and platelet activation. CXCL12, C3, FN1, COL1A2, ACTB, VCAM1, and MMP2 were identified and finally verified as the hub genes, mainly enriched in pathways like leukocyte transendothelial migration, PI3K-Akt signaling pathway, viral myocarditis, rheumatoid arthritis, and platelet activation. Pegcetacoplan, ocriplasmin, and carvedilol were the potential target drugs.

Conclusions

We used microdataset to identify the potential functions and mechanisms of the TGFBI and its coexpression genes in AF patients. Our findings suggest that CXCL12, C3, FN1, COL1A2, ACTB, VCAM1, and MMP2 may be the hub genes.

Heart failure and cancer: From active exposure to passive adaption

The human body seems like a "balance integrator." On the one hand, the body constantly actively receives various outside stimuli and signals to induce changes. On the other hand, several internal regulations would be initiated to adapt to these changes. In most cases, the body could keep the balance in vitro and in vivo to reach a healthy body. However, in some cases, the body can only get to a pathological balance. Actively exposed to unhealthy lifestyles and passively adapting to individual primary diseases lead to a similarly inner environment for both heart failure and cancer. To cope with these stimuli, the body must activate the system regulation mechanism and face the mutual interference. This review summarized the association between heart failure and cancer from active exposure to passive adaption. Moreover, we hope to inspire researchers to contemplate these two diseases from the angle of overall body consideration.

The microRNA Expression Profiling in Heart Failure: A Systematic Review and Meta-Analysis

Background

Heart failure (HF) is a main consequence of cardiovascular diseases worldwide. Abnormal expression levels of microRNAs (miRNAs) in HF are observed in current studies. Novel biomarkers miRNAs may play an important role in the development of HF. Nevertheless, the inconsistency of miRNA expression limits the clinical application. We thus perform this systematic review of the miRNAs expression profiling to identify potential HF biomarkers.

Methods

The electronic databases of Embase, Medline, and Cochrane Library were systematically searched to identify the miRNA expression profiles between HF subjects and non-HF controls before May 26th, 2021. The pooled results were shown as log10 odds ratios (logORs) with 95% confidence intervals (CI) using random-effect models. Subgroup analyses were conducted according to species, region, and sample source. The quality assessment of included studies was independently conducted based on Diagnostic Accuracy Study 2 (QUADAS-2). The sensitivity analysis was conducted based on sample size.

Results

A total of 55 miRNA expression articles reporting 276 miRNAs of HF were included. 47 consistently up-regulated and 10 down-regulated miRNAs were identified in the overall analysis, with the most up-regulated miR-21 (logOR 8.02; 95% CI: 6.76–9.27, P < 0.001) and the most down-regulated miR-30c (logOR 6.62; 95% CI: 3.04–10.20, P < 0.001). The subgroup analysis of sample source identified 35 up-regulated and 10 down-regulated miRNAs in blood sample, the most up-regulated and down-regulated miRNAs were miR-210-3p and miR-30c, respectively. In the region sub-groups, let-7i-5p and miR-129 were most up-regulated and down-regulated in Asian countries, while in non-Asian countries, let-7e-5p and miR-30c were the most dysregulated. It’s worth noting that miR-622 was consistently up-regulated in both Asian and non-Asian countries. Sensitivity analysis showed that 46 out of 58 (79.31%) miRNAs were dysregulated.

Conclusion

A total of 57 consistently dysregulated miRNAs related to HF were confirmed in this study. Seven dysregulated miRNAs (miR-21, miR-30c, miR-210-3p, let-7i-5p, miR-129, let-7e-5p, and miR-622) may be considered as potential non-invasive biomarkers for HF. However, further validation in larger-scale studies are needed to verify our conclusions.