Antoine A. F. de Vries

This is the first population-based study of circulating bone morphogenetic protein 10 (BMP10), a heart-specific protein mainly secreted by atrial cardiomyocytes. In over 5,800 community-dwelling adults, BMP10 showed distinct physiological and pathophysiological correlates, including higher levels in women, an inverse association with fat mass and inflammation (CRP), and a positive association with incident atrial fibrillation. These findings represent an important first step toward understanding the role of BMP10 in atrial biology and disease.

Heart failure is a common and deadly disease requiring new treatments. The neuregulin-1/ERBB4 pathway offers cardioprotective benefits, but using recombinant neuregulin-1 as therapy has limitations due to the need for intravenous delivery and lack of receptor specificity. We hypothesize that small-molecule activation of ERBB4 could protect against heart damage and fibrosis. To test this, we conduct a screening of 10,240 compounds and identify eight structurally similar ones (EF-1 to EF-8) that induce ERBB4 dimerization, with EF-1 being the most effective. EF-1 reduces cell death and hypertrophy in cardiomyocytes and decreases collagen production in cardiac fibroblasts in an ERBB4-dependent manner. In wild-type mice, EF-1 inhibits angiotensin-II-induced fibrosis in males and females and reduces heart damage caused by doxorubicin and myocardial infarction in females, but not in Erbb4-null mice. This study shows that small-molecule ERBB4 activation is feasible and may lead to a novel class of drugs for treating heart failure.

In 2024, we celebrate the 100th anniversary of Willem Einthoven receiving the Nobel Prize for his discovery of the mechanism of the electrocardiogram (ECG). Building on Einthoven’s legacy, electrocardiography allows the monitoring of cardiac bioelectricity through solutions to the so-called forward and inverse problems. These solutions link local cardiac electrical signals with the morphology of the ECG, offering a reversible connection between the heart’s electrical activity and its representation on the body surface. Inspired by Einthoven’s work, researchers have explored the transition from monitoring to modulation of bioelectrical activity in the heart for the development of new anti-arrhythmic strategies, e.g. via optogenetics. In this review, we demonstrate the lasting influence that Einthoven has on our understanding of cardiac electrophysiology in general, and the diagnosis and treatment of cardiac arrhythmias in particular.

Diseased atria are characterized by functional and structural heterogeneities, adding to abnormal impulse generation and propagation. These heterogeneities are thought to lie at the origin of fractionated electrograms recorded during sinus rhythm (SR) in atrial fibrillation (AF) patients and are assumed to be involved in the onset and perpetuation (e.g. by re-entry) of this disorder. The underlying mechanisms, however, remain incompletely understood. Here, we tested whether regions of dense fibrosis could create an electrically isolated conduction pathway (EICP) in which re-entry could be established via ectopy and local block to become ‘trapped’. We also investigated whether this could generate local fractionated electrograms and whether the re-entrant wave could ‘escape’ and cause a global tachyarrhythmia due to dynamic changes at a connecting isthmus. To precisely control and explore the geometrical properties of EICPs, we used light-gated depolarizing ion channels and patterned illumination for creating specific non-conducting regions in silico and in vitro. Insight from these studies was used for complementary investigations in virtual human atria with localized fibrosis. We demonstrated that a re-entrant tachyarrhythmia can exist locally within an EICP with SR prevailing in the surrounding tissue and identified conditions under which re-entry could escape from the EICP, thereby converting a local latent arrhythmic source into an active driver with global impact on the heart. In a realistic three-dimensional model of human atria, unipolar epicardial pseudo-electrograms showed fractionation at the site of ‘trapped re-entry’ in coexistence with regular SR electrograms elsewhere in the atria. Upon escape of the re-entrant wave, acute arrhythmia onset was observed. Trapped re-entry as a latent source of arrhythmogenesis can explain the sudden onset of focal arrhythmias, which are able to transgress into AF. Our study might help to improve the effectiveness of ablation of aberrant cardiac electrical signals in clinical practice.

The quick and easy creation of fast in-silico models of excitable media is, for instance, needed for patient-specific predictions in diagnostics and decision making in cardiac electrophysiology. We here present a model creation pipeline that not only generates new models quickly, but also only requires data from one easily measurable spatio-temporal variable. These data may, for instance, be an optical voltage mapping recording of the electrical waves in cardiac muscle tissue controlling the heart beat. We use exponential moving averages and compute standard deviations to extract additional states from this one variable to span a sparse discretised state space. The standard deviation in a neighbourhood can be used as a proxy for the gradient. To this augmented state space, we fit a simple polynomial model to predict the evolution of this one state variable. For optical voltage mapping data of human atrial myocyte monolayers electrically stimulated by stochastic burst pacing, the data-driven model is able to describe the excitation and recovery of the system, as well as wave propagation. The data-driven model is also able to predict spiral waves only based on data from focal waves. In contrast to conventional models, with our model creation pipeline new models can be generated in a matter of hours from experiment to fitting, rather than months or years. Highlights: Models of excitation waves can be created in minutes from experiment to fitting. One variable in space and time is sufficient to create a working excitation model. A polynomial can predict excitation waves based on useful extracted features. Spiral waves in heart muscle tissue can be predicted from focal wave data. Graphical

Background: Heart development relies on tight spatiotemporal control of cardiac gene expression. Genes involved in this intricate process have been identified using animals and pluripotent stem cell-based models of cardio(myo)genesis. Recently, the repertoire of cardiomyocyte differentiation models has been expanded with iAM-1, a monoclonal line of conditionally immortalized neonatal rat atrial myocytes (NRAMs), which allows toggling between proliferative and differentiated (ie, excitable and contractile) phenotypes in a synchronized and homogenous manner. Methods: In this study, the unique properties of conditionally immortalized NRAMs (iAMs) were exploited to identify and characterize (lowly expressed) genes with an as-of-yet uncharacterized role in cardiomyocyte differentiation. Results: Transcriptome analysis of iAM-1 cells at different stages during one cycle of differentiation and subsequent dedifferentiation identified ≈13 000 transcripts, of which the dynamic changes in expression upon cardiomyogenic differentiation mostly opposed those during dedifferentiation. Among the genes whose expression increased during differentiation and decreased during dedifferentiation were many with known (lineage-specific) functions in cardiac muscle formation. Filtering for cardiac-enriched low-abundance transcripts, identified multiple genes with an uncharacterized role during cardio(myo)genesis including Sbk2 (SH3 domain binding kinase family member 2). Sbk2 encodes an evolutionarily conserved putative serine/threonine protein kinase, whose expression is strongly up- and downregulated during iAM-1 cell differentiation and dedifferentiation, respectively. In neonatal and adult rats, the protein is muscle-specific, highly atrium-enriched, and localized around the A-band of cardiac sarcomeres. Knockdown of Sbk2 expression caused loss of sarcomeric organization in NRAMs, iAMs and their human counterparts, consistent with a decrease in sarcomeric gene expression as evinced by transcriptome and proteome analyses. Interestingly, co-immunoprecipitation using Sbk2 as bait identified possible interaction partners with diverse cellular functions (translation, intracellular trafficking, cytoskeletal organization, chromatin modification, sarcomere formation). Conclusions: iAM-1 cells are a relevant and suitable model to identify (lowly expressed) genes with a hitherto unidentified role in cardiomyocyte differentiation as exemplified by Sbk2: a regulator of atrial sarcomerogenesis.