Loss-of-Function Variants in the SYNPO2L Gene Are Associated With Atrial Fibrillation

Pathophysiology and clinical relevance of atrial myopathy

Atrial myopathy is a condition that consists of electrical, structural, contractile, and autonomic remodeling of the atria and is the substrate for development of atrial fibrillation, the most common arrhythmia. Pathophysiologic mechanisms driving atrial myopathy are inflammation, oxidative stress, atrial stretch, and neurohormonal signals, e.g., angiotensin-II and aldosterone. These mechanisms initiate the structural and functional remodeling of the atrial myocardium. Novel therapeutic strategies are being developed that target the pathophysiologic mechanisms of atrial myopathy. In this review, we will discuss the pathophysiology of atrial myopathy, as well as diagnostic and therapeutic strategies.

Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology

Recent genome-wide association studies have successfully identified associations between genetic variants and simple cardiac morphological parameters derived from cardiac magnetic resonance images. However, the emergence of large databases, including genetic data linked to cardiac magnetic resonance facilitates the investigation of more nuanced patterns of cardiac shape variability than those studied so far. Here we propose a framework for gene discovery coined unsupervised phenotype ensembles. The unsupervised phenotype ensemble builds a redundant yet highly expressive representation by pooling a set of phenotypes learnt in an unsupervised manner, using deep learning models trained with different hyperparameters. These phenotypes are then analysed via genome-wide association studies, retaining only highly confident and stable associations across the ensemble. We applied our approach to the UK Biobank database to extract geometric features of the left ventricle from image-derived three-dimensional meshes. We demonstrate that our approach greatly improves the discoverability of genes that influence left ventricle shape, identifying 49 loci with study-wide significance and 25 with suggestive significance. We argue that our approach would enable more extensive discovery of gene associations with image-derived phenotypes for other organs or image modalities.

Atrial fibrillation: pathophysiology, genetic and epigenetic mechanisms

Atrial fibrillation (AF) is the most common supraventricular arrhythmia affecting up to 1% of the general population. Its prevalence dramatically increases with age and could reach up to ∼10% in the elderly. The management of AF is a complex issue that is object of extensive ongoing basic and clinical research, it depends on its genetic and epigenetic causes, and it varies considerably geographically and also according to the ethnicity. Mechanistically, over the last decade, Genome Wide Association Studies have uncovered over 100 genetic loci associated with AF, and have shown that European ancestry is associated with elevated risk of AF. These AF-associated loci revolve around different types of disturbances, including inflammation, electrical abnormalities, and structural remodeling. Moreover, the discovery of epigenetic regulatory mechanisms, involving non-coding RNAs, DNA methylation and histone modification, has allowed unravelling what modifications reshape the processes leading to arrhythmias. Our review provides a current state of the field regarding the identification and functional characterization of AF-related genetic and epigenetic regulatory networks, including ethnic differences. We discuss clear and emerging connections between genetic regulation and pathophysiological mechanisms of AF.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

Risk stratification of atrial fibrillation and stroke using single nucleotide polymorphism and circulating biomarkers

BACKGROUND

Atrial fibrillation (AF) is the most common sustained arrhythmia, and it causes a high rate of complications such as stroke. It is known that AF begins as paroxysmal form and gradually progresses to persistent form, and sometimes it is difficult to identify paroxysmal AF (PAF) before having stroke. The aim of this study is to evaluate the risk of PAF and stroke using genetic analysis and circulating biomarkers.

MATERIALS AND METHODS

A total of 600 adult subjects were enrolled (300 from PAF and control groups). Peripheral blood was drawn to identify the genetic variation and biomarkers. Ten single nucleotide polymorphisms (SNPs) were analyzed, and circulating cell-free DNA (cfDNA) was measured from plasma. Four microRNAs (miR-99a-5p, miR-192-5p, miR-214-3p, and miR-342-5p) were quantified in serum using quantitative RT-PCR.

RESULTS

Genotyping identified 4 single nucleotide polymorphisms (SNPs) that were significantly associated with AF (rs6817105, rs3807989, rs10824026, and rs2106261), and the genetic risk score using 4 SNPs showed the area under the curve (AUC) of 0.631. Circulating miRNAs and cfDNA did not show significant differences between PAF and control groups. The concentration of cfDNA was significantly higher in patients with a history of stroke, and the AUC was 0.950 to estimate the association with stroke.

CONCLUSION

The risk of AF could be assessed by genetic risk score. Furthermore, the risk of stroke might be evaluated by plasma cfDNA level.

Discovery of TBX20 as a Novel Gene Underlying Atrial Fibrillation

Atrial fibrillation (AF), the most prevalent type of sustained cardiac dysrhythmia globally, confers strikingly enhanced risks for cognitive dysfunction, stroke, chronic cardiac failure, and sudden cardiovascular demise. Aggregating studies underscore the crucial roles of inherited determinants in the occurrence and perpetuation of AF. However, due to conspicuous genetic heterogeneity, the inherited defects accounting for AF remain largely indefinite. Here, via whole-genome genotyping with genetic markers and a linkage assay in a family suffering from AF, a new AF-causative locus was located at human chromosome 7p14.2-p14.3, a ~4.89 cM (~4.43-Mb) interval between the markers D7S526 and D7S2250. An exome-wide sequencing assay unveiled that, at the defined locus, the mutation in the TBX20 gene, NM_001077653.2: c.695A>G; p.(His232Arg), was solely co-segregated with AF in the family. Additionally, a Sanger sequencing assay of TBX20 in another family suffering from AF uncovered a novel mutation, NM_001077653.2: c.862G>C; p.(Asp288His). Neither of the two mutations were observed in 600 unrelated control individuals. Functional investigations demonstrated that the two mutations both significantly reduced the transactivation of the target gene KCNH2 (a well-established AF-causing gene) and the ability to bind the promoter of KCNH2, while they had no effect on the nuclear distribution of TBX20. Conclusively, these findings reveal a new AF-causative locus at human chromosome 7p14.2-p14.3 and strongly indicate TBX20 as a novel AF-predisposing gene, shedding light on the mechanism underlying AF and suggesting clinical significance for the allele-specific treatment of AF patients.

Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure

Heart failure is a leading cause of cardiovascular morbidity and mortality. However, the contribution of common genetic variation to heart failure risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We report a multi-ancestry genome-wide association study meta-analysis of all-cause heart failure including up to 115,150 cases and 1,550,331 controls of diverse genetic ancestry, identifying 47 risk loci. We also perform multivariate genome-wide association studies that integrate heart failure with related cardiac magnetic resonance imaging endophenotypes, identifying 61 risk loci. Gene-prioritization analyses including colocalization and transcriptome-wide association studies identify known and previously unreported candidate cardiomyopathy genes and cellular processes, which we validate in gene-expression profiling of failing and healthy human hearts. Colocalization, gene expression profiling, and Mendelian randomization provide convergent evidence for the roles of BCKDHA and circulating branch-chain amino acids in heart failure and cardiac structure. Finally, proteome-wide Mendelian randomization identifies 9 circulating proteins associated with heart failure or quantitative imaging traits. These analyses highlight similarities and differences among heart failure and associated cardiovascular imaging endophenotypes, implicate common genetic variation in the pathogenesis of heart failure, and identify circulating proteins that may represent cardiomyopathy treatment targets.

Atrial cardiomyopathy: from cell to bedside

Atrial cardiomyopathy refers to structural and electrical remodelling of the atria, which can lead to impaired mechanical function. While historical studies have implicated atrial fibrillation as the leading cause of cardioembolic stroke, atrial cardiomyopathy may be an important, underestimated contributor. To date, the relationship between atrial cardiomyopathy, atrial fibrillation, and cardioembolic stroke remains obscure. This review summarizes the pathogenesis of atrial cardiomyopathy, with a special focus on neurohormonal and inflammatory mechanisms, as well as the role of adipose tissue, especially epicardial fat in atrial remodelling. It reviews the current evidence implicating atrial cardiomyopathy as a cause of embolic stroke, with atrial fibrillation as a lagging marker of an increased thrombogenic atrial substrate. Finally, it discusses the potential of antithrombotic therapy in embolic stroke with undetermined source and appraises the available diagnostic techniques for atrial cardiomyopathy, including imaging techniques such as echocardiography, computed tomography, and magnetic resonance imaging as well as electroanatomic mapping, electrocardiogram, biomarkers, and genetic testing. More prospective studies are needed to define the relationship between atrial cardiomyopathy, atrial fibrillation, and embolic stroke and to establish a prompt diagnosis and specific treatment strategies in these patients with atrial cardiomyopathy for the secondary and even primary prevention of embolic stroke.

Genetic and non-genetic risk factors associated with atrial fibrillation

Atrial fibrillation (AF) is the most common arrhythmic disorder and its prevalence in the United States is projected to increase to more than twelve million cases in 2030. AF increases the risk of other forms of cardiovascular disease, including stroke. As the incidence of atrial fibrillation increases dramatically with age, it is paramount to elucidate risk factors underlying AF pathogenesis. Here, we review tissue and cellular pathways underlying AF, as well as critical components that impact AF susceptibility including genetic and environmental risk factors. Finally, we provide the latest information on potential links between SARS-CoV-2 and human AF. Improved understanding of mechanistic pathways holds promise in preventative care and early diagnostics, and also introduces novel targeted forms of therapy that might attenuate AF progression and maintenance.

Genetics of atrial fibrillation-an update of recent findings

Atrial fibrillation (AF) is a common cardiac arrhythmia and a major risk factor for stroke, heart failure, and premature death. AF has a strong genetic predisposition. This review highlights the recent findings on the genetics of AF from genome-wide association studies (GWAS) and high-throughput sequencing studies. The consensus from GWAS implies that AF is both polygenic and pleiotropic in nature. With the advent of whole-genome sequencing and whole-exome sequencing, rare variants associated with AF pathogenesis have been identified. The recent studies have contributed towards better understanding of AF pathogenesis.

Ultrastructural Assessment and Proteomic Analysis in Myofibrillogenesis in the Heart Primordium After Heartbeat Initiation in Rats

Myofibrillogenesis is an essential process for cardiogenesis and is closely related to excitation-contraction coupling and the maintenance of heartbeat. It remains unclear whether the formation of myofibrils and sarcomeres is associated with heartbeat initiation in the early embryonic heart development. Here, we investigated the association between the ultrastructure of myofibrils assessed by transmission electron microscopy and their proteomic profiling assessed by data-independent acquisition mass spectrometry (DIA-MS) in the rat heart primordia before and after heartbeat initiation at embryonic day 10.0, when heartbeat begins in rats, and in the primitive heart tube at embryonic day 11.0. Bundles of myofilaments were scattered in a few cells of the heart primordium after heartbeat initiation, whereas there were no typical sarcomeres in the heart primordia both before and after heartbeat initiation. Sarcomeres with Z-lines were identified in cells of the primitive heart tube, though myofilaments were not aligned. DIA-MS proteome analysis revealed that only 43 proteins were significantly upregulated by more than 2.0 fold among a total of 7,762 detected proteins in the heart primordium after heartbeat initiation compared with that before heartbeat initiation. Indeed, of those upregulated proteins, 12 (27.9%) were constituent proteins of myofibrils and 10 (23.3%) were proteins that were accessories and regulators for myofibrillogenesis, suggesting that upregulated proteins that are associated with heartbeat initiation were enriched in myofibrillogenesis. Collectively, our results suggest that the establishment of heartbeat is induced by development of bundles of myofilaments with upregulated proteins associated with myofibrillogensis, whereas sarcomeres are not required for the initial heartbeat.

Cap analysis of gene expression reveals alternative promoter usage in a rat model of hypertension

The role of alternative promoter usage in tissue-specific gene expression has been well established; however, its role in complex diseases is poorly understood. We performed cap analysis of gene expression (CAGE) sequencing from the left ventricle of a rat model of hypertension, the spontaneously hypertensive rat (SHR), and a normotensive strain, Brown Norway to understand the role of alternative promoter usage in complex disease. We identified 26,560 CAGE-defined transcription start sites in the rat left ventricle, including 1,970 novel cardiac transcription start sites. We identified 28 genes with alternative promoter usage between SHR and Brown Norway, which could lead to protein isoforms differing at the amino terminus between two strains and 475 promoter switching events altering the length of the 5' UTR. We found that the shift in Insr promoter usage was significantly associated with insulin levels and blood pressure within a panel of HXB/BXH recombinant inbred rat strains, suggesting that hyperinsulinemia due to insulin resistance might lead to hypertension in SHR. Our study provides a preliminary evidence of alternative promoter usage in complex diseases.