Vascular smooth muscle cell phenotypic transition regulates gap junctions of cardiomyocyte

Analyses of m6A regulatory genes and subtype classification in atrial fibrillation

Objective

To explore the role of m6A regulatory genes in atrial fibrillation (AF), we classified atrial fibrillation patients into subtypes by two genotyping methods associated with m6A regulatory genes and explored their clinical significance.

Methods

We downloaded datasets from the Gene Expression Omnibus (GEO) database. The m6A regulatory gene expression levels were extracted. We constructed and compared random forest (RF) and support vector machine (SVM) models. Feature genes were selected to develop a nomogram model with the superior model. We identified m6A subtypes based on significantly differentially expressed m6A regulatory genes and identified m6A gene subtypes based on m6A-related differentially expressed genes (DEGs). Comprehensive evaluation of the two m6A modification patterns was performed.

Results

The data of 107 samples from three datasets, GSE115574, GSE14975 and GSE41177, were acquired from the GEO database for training models, comprising 65 AF samples and 42 sinus rhythm (SR) samples. The data of 26 samples from dataset GSE79768 comprising 14 AF samples and 12 SR samples were acquired from the GEO database for external validation. The expression levels of 23 regulatory genes of m6A were extracted. There were correlations among the m6A readers, erasers, and writers. Five feature m6A regulatory genes, ZC3H13, YTHDF1, HNRNPA2B1, IGFBP2, and IGFBP3, were determined (p < 0.05) to establish a nomogram model that can predict the incidence of atrial fibrillation with the RF model. We identified two m6A subtypes based on the five significant m6A regulatory genes (p < 0.05). Cluster B had a lower immune infiltration of immature dendritic cells than cluster A (p < 0.05). On the basis of six m6A-related DEGs between m6A subtypes (p < 0.05), two m6A gene subtypes were identified. Both cluster A and gene cluster A scored higher than the other clusters in terms of m6A score computed by principal component analysis (PCA) algorithms (p < 0.05). The m6A subtypes and m6A gene subtypes were highly consistent.

Conclusion

The m6A regulatory genes play non-negligible roles in atrial fibrillation. A nomogram model developed by five feature m6A regulatory genes could be used to predict the incidence of atrial fibrillation. Two m6A modification patterns were identified and evaluated comprehensively, which may provide insights into the classification of atrial fibrillation patients and guide treatment.

Myofibroblast specific targeting approaches to improve fibrosis treatment

Fibrosis has been shown to develop in individuals with underlying health conditions, especially chronic inflammatory diseases. Fibrosis is often diagnosed in various organs, including the liver, lungs, kidneys, heart, and skin, and has been described as excessive accumulation of extracellular matrix that can affect specific organs in the body or systemically throughout the body. Fibrosis as a chronic condition can result in organ failure and result in death of the individual. Understanding and identification of specific biomarkers associated with fibrosis has emerging potential in the development of diagnosis and targeting treatment modalities. Therefore, in this review, we will discuss multiple signaling pathways such as TGF-β, collagen, angiotensin, and cadherin and outline the chemical nature of the different signaling pathways involved in fibrogenesis as well as the mechanisms. Although it has been well established that TGF-β is the main catalyst initiating and driving multiple pathways for fibrosis, targeting TGF-β can be challenging as this molecule regulates essential functions throughout the body that help to keep the body in homeostasis. We also discuss collagen, angiotensin, and cadherins and their role in fibrosis. We comprehensively discuss the various delivery systems used to target collagen, angiotensin, and cadherins to manage fibrosis. Nevertheless, understanding the steps by which this molecule drives fibrosis development can aid in the development of specific targets of its cascading mechanism. Throughout the review, we will demonstrate the mechanism of fibrosis targeting to improve targeting delivery and therapy.

Molecular feature of arterial remodeling in the brain arteriovenous malformation revealed by arteriovenous shunt rat model and RNA sequencing

PURPOSE

Morphological research suggested the feeding artery of brain arteriovenous malformation (bAVM) had vascular remodeling under the high blood flow; however, the underlying molecular mechanisms were unclear.

METHODS

We constructed 32 simplified AVM rat models in four groups: the control group (n = 6), 1-week high-blood-flow group (n = 9), 3-week high-blood-flow group (n = 7) and 6-week high-blood-flow group (n = 10). The circumference, blood velocity, blood flow, pressure, and wall shear of the feeding artery were measured or calculated. The arterial wall change was observed by Masson staining. RNA sequencing (RNA-seq) of feeding arteries was performed, followed by bioinformatics analysis to detect the potential molecular mechanism for bAVM artery remodeling under the high blood flow.

RESULTS

We observed hemodynamic injury and vascular remodeling on the feeding artery under the high blood flow. RNA-seq showed immune/inflammation infiltration and vascular smooth muscle cell (VSMC) phenotype transformation during remodeling. Weighted gene co-expression network analysis (WGCNA) and time series analysis further identified 27 key genes and pathways involved in remodeling. Upstream miRNA and molecular drugs were predicted targeting these key genes.

CONCLUSIONS

We depicted molecular change of bAVM arterial remodeling via RNA-seq in high-blood-flow rat models. Twenty-seven key genes may regulate immune/inflammation infiltration and VSMC phenotype transform in bAVM arterial remodeling.

Unravelling Atrioventricular Block Risk in Inflammatory Diseases: Systemic Inflammation Acutely Delays Atrioventricular Conduction via a Cytokine-Mediated Inhibition of Connexin43 Expression

Background

Recent data suggest that systemic inflammation can negatively affect atrioventricular conduction, regardless of acute cardiac injury. Indeed, gap‐junctions containing connexin43 coupling cardiomyocytes and inflammation‐related cells (macrophages) are increasingly recognized as important factors regulating the conduction in the atrioventricular node. The aim of this study was to evaluate the acute impact of systemic inflammatory activation on atrioventricular conduction, and elucidate underlying mechanisms.

Methods and Results

We analyzed: (1) the PR‐interval in patients with inflammatory diseases of different origins during active phase and recovery, and its association with inflammatory markers; (2) the existing correlation between connexin43 expression in the cardiac tissue and peripheral blood mononuclear cells (PBMC), and the changes occurring in patients with inflammatory diseases over time; (3) the acute effects of interleukin(IL)‐6 on atrioventricular conduction in an in vivo animal model, and on connexin43 expression in vitro. In patients with elevated C‐reactive protein levels, atrioventricular conduction indices are increased, but promptly normalized in association with inflammatory markers reduction, particularly IL‐6. In these subjects, connexin43 expression in PBMC, which is correlative of that measured in the cardiac tissue, inversely associated with IL‐6 changes. Moreover, direct IL‐6 administration increased atrioventricular conduction indices in vivo in a guinea pig model, and IL‐6 incubation in both cardiomyocytes and macrophages in culture, significantly reduced connexin43 proteins expression.

Conclusions

The data evidence that systemic inflammation can acutely worsen atrioventricular conduction, and that IL‐6‐induced down‐regulation of cardiac connexin43 is a mechanistic pathway putatively involved in the process. Though reversible, these alterations could significantly increase the risk of severe atrioventricular blocks during active inflammatory processes.

Cardiac Tissue Engineering: Inclusion of Non-cardiomyocytes for Enhanced Features

Engineered cardiac tissues (ECTs) are 3D physiological models of the heart that are created and studied for their potential role in developing therapies of cardiovascular diseases and testing cardio toxicity of drugs. Recreating the microenvironment of the native myocardium in vitro mainly involves the use of cardiomyocytes. However, ECTs with only cardiomyocytes (CM-only) often perform poorly and are less similar to the native myocardium compared to ECTs constructed from co-culture of cardiomyocytes and nonmyocytes. One important goal of co-culture tissues is to mimic the native heart's cellular composition, which can result in better tissue function and maturity. In this review, we investigate the role of nonmyocytes in ECTs and discuss the mechanisms behind the contributions of nonmyocytes in enhancement of ECT features.