An atrial fibrillation-associated regulatory region modulates cardiac Tbx5 levels and arrhythmia susceptibility

Role of Genetic Variation in Transcriptional Regulatory Elements in Heart Rhythm

Genetic predisposition to cardiac arrhythmias has been a field of intense investigation. Research initially focused on rare hereditary arrhythmias, but over the last two decades, the role of genetic variation (single nucleotide polymorphisms) in heart rate, rhythm, and arrhythmias has been taken into consideration as well. In particular, genome-wide association studies have identified hundreds of genomic loci associated with quantitative electrocardiographic traits, atrial fibrillation, and less common arrhythmias such as Brugada syndrome. A significant number of associated variants have been found to systematically localize in non-coding regulatory elements that control the tissue-specific and temporal transcription of genes encoding transcription factors, ion channels, and other proteins. However, the identification of causal variants and the mechanism underlying their impact on phenotype has proven difficult due to the complex tissue-specific, time-resolved, condition-dependent, and combinatorial function of regulatory elements, as well as their modest conservation across different model species. In this review, we discuss research efforts aimed at identifying and characterizing-trait-associated variant regulatory elements and the molecular mechanisms underlying their impact on heart rate or rhythm.

Tbx5 maintains atrial identity in post-natal cardiomyocytes by regulating an atrial-specific enhancer network

Understanding how the atrial and ventricular heart chambers maintain distinct identities is a prerequisite for treating chamber-specific diseases. Here, we selectively knocked out (KO) the transcription factor Tbx5 in the atrial working myocardium to evaluate its requirement for atrial identity. Atrial Tbx5 inactivation downregulated atrial cardiomyocyte (aCM) selective gene expression. Using concurrent single nucleus transcriptome and open chromatin profiling, genomic accessibility differences were identified between control and Tbx5 KO aCMs, revealing that 69% of the control-enriched ATAC regions were bound by TBX5. Genes associated with these regions were downregulated in KO aCMs, suggesting they function as TBX5-dependent enhancers. Comparing enhancer chromatin looping using H3K27ac HiChIP identified 510 chromatin loops sensitive to TBX5 dosage, and 74.8% of control-enriched loops contained anchors in control-enriched ATAC regions. Together, these data demonstrate TBX5 maintains the atrial gene expression program by binding to and preserving the tissue-specific chromatin architecture of atrial enhancers.

CVD-associated SNPs with regulatory potential reveal novel non-coding disease genes

BACKGROUND

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) appearing in non-coding genomic regions in CVDs. The SNPs may alter gene expression by modifying transcription factor (TF) binding sites and lead to functional consequences in cardiovascular traits or diseases. To understand the underlying molecular mechanisms, it is crucial to identify which variations are involved and how they affect TF binding.

METHODS

The SNEEP (SNP exploration and analysis using epigenomics data) pipeline was used to identify regulatory SNPs, which alter the binding behavior of TFs and link GWAS SNPs to their potential target genes for six CVDs. The human-induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs), monoculture cardiac organoids (MCOs) and self-organized cardiac organoids (SCOs) were used in the study. Gene expression, cardiomyocyte size and cardiac contractility were assessed.

RESULTS

By using our integrative computational pipeline, we identified 1905 regulatory SNPs in CVD GWAS data. These were associated with hundreds of genes, half of them non-coding RNAs (ncRNAs), suggesting novel CVD genes. We experimentally tested 40 CVD-associated non-coding RNAs, among them RP11-98F14.11, RPL23AP92, IGBP1P1, and CTD-2383I20.1, which were upregulated in hiPSC-CMs, MCOs and SCOs under hypoxic conditions. Further experiments showed that IGBP1P1 depletion rescued expression of hypertrophic marker genes, reduced hypoxia-induced cardiomyocyte size and improved hypoxia-reduced cardiac contractility in hiPSC-CMs and MCOs.

CONCLUSIONS

IGBP1P1 is a novel ncRNA with key regulatory functions in modulating cardiomyocyte size and cardiac function in our disease models. Our data suggest ncRNA IGBP1P1 as a potential therapeutic target to improve cardiac function in CVDs.

Overview of programmed electrical stimulation to assess atrial fibrillation susceptibility in mice

Atrial fibrillation (AF) is the most common human arrhythmia and is associated with increased risk of stroke, dementia, heart failure, and death. Among several animal models that have been used to investigate the molecular determinants of AF, mouse models have become the most prevalent due to low cost, ease of genetic manipulation, and similarity to human disease. Programmed electrical stimulation (PES) using intracardiac or transesophageal atrial pacing is used to induce AF as most mouse models do not develop spontaneous AF. However, there is a lack of standardized methodology resulting in numerous PES protocols in the literature that differ with respect to multiple parameters, including pacing protocol and duration, stimulus amplitude, pulse width, and even the definition of AF. Given this complexity, the selection of the appropriate atrial pacing protocol for a specific model has been arbitrary. Herein we review the development of intracardiac and transesophageal PES, including commonly used protocols, selected experimental models, and advantages and disadvantages of both techniques. We also emphasize detection of artifactual AF induction due to unintended parasympathetic stimulation, which should be excluded from results. We recommend that the optimal pacing protocol to elicit an AF phenotype should be individualized to the specific model of genetic or acquired risk factors, with an analysis using several definitions of AF as an endpoint.