Epigenetic and Transcriptional Networks Underlying Atrial Fibrillation.
Ontology highlight
ABSTRACT:
SUBMITTER: van Ouwerkerk AF
PROVIDER: S-EPMC8315291 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundAtrial fibrillation (AF) often arises from structural abnormalities in the left atria (LA). Annotation of the noncoding genome in human LA is limited, as are effects on gene expression and chromatin architecture. Many AF-associated genetic variants reside in noncoding regions; this knowledge gap impairs efforts to understand the molecular mechanisms of AF and cardiac conduction phenotypes.MethodsWe generated a model of the LA noncoding genome by profiling 7 histone post-translational modifications (active: H3K4me3, H3K4me2, H3K4me1, H3K27ac, H3K36me3; repressive: H3K27me3, H3K9me3), CTCF binding, and gene expression in samples from 5 individuals without structural heart disease or AF. We used MACS2 to identify peak regions (P<0.01), applied a Markov model to classify regulatory elements, and annotated this model with matched gene expression data. We intersected chromatin states with expression quantitative trait locus, DNA methylation, and HiC chromatin interaction data from LA and left ventricle. Finally, we integrated genome-wide association data for AF and electrocardiographic traits to link disease-related variants to genes.ResultsOur model identified 21 epigenetic states, encompassing regulatory motifs, such as promoters, enhancers, and repressed regions. Genes were regulated by proximal chromatin states; repressive states were associated with a significant reduction in gene expression (P<2×10-16). Chromatin states were differentially methylated, promoters were less methylated than repressed regions (P<2×10-16). We identified over 15 000 LA-specific enhancers, defined by homeobox family motifs, and annotated several cardiovascular disease susceptibility loci. Intersecting AF and PR genome-wide association studies loci with long-range chromatin conformation data identified a gene interaction network dominated by NKX2-5, TBX3, ZFHX3, and SYNPO2L.ConclusionsProfiling the noncoding genome provides new insights into the gene expression and chromatin regulation in human LA tissue. These findings enabled identification of a gene network underlying AF; our experimental and analytic approach can be extended to identify molecular mechanisms for other cardiac diseases and traits.
| S-EPMC8240092 | biostudies-literature
Project description: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.
| S-EPMC10866930 | biostudies-literature
Project description:BackgroundAtrial fibrillation (AF) is one of the most prevalent causes of cryptogenic stroke. Also, apart from AF itself, structural and remodelling changes in the atria might be an underlying cause of cryptogenic stroke. We aimed to discover circulating proteins and reveal pathways altered in AF and atrial cardiomyopathy, measured by left atrial volume index (LAVI) and peak atrial longitudinal strain (PALS), in patients with cryptogenic stroke.MethodsAn aptamer array (including 1310 proteins) was measured in the blood of 20 cryptogenic stroke patients monitored during 28 days with a Holter device as a case-control study of the Crypto-AF cohort. Protein levels were compared between patients with (n = 10) and without AF (n = 10) after stroke, and the best candidates were tested in 111 patients from the same cohort (44 patients with AF and 67 without AF). In addition, in the first 20 patients, proteins were explored according to PALS and LAVI values.ResultsForty-six proteins were differentially expressed in AF cases. Of those, four proteins were tested in a larger sample size. Only DPP7, presenting lower levels in AF patients, was further validated. Fifty-seven proteins correlated with LAVI, and 270 correlated with PALS. NT-proBNP was common in all the discovery analyses performed. Interestingly, many proteins and pathways were altered in patients with low PALS.ConclusionsMultiple proteins and pathways related to AF and atrial cardiomyopathy have been revealed. The role of DPP7 as a biomarker for stroke aetiology should be further explored. Moreover, the present study may be considered hypothesis-generating.
| S-EPMC8913305 | biostudies-literature
Project description:Atrial fibrillation (AF) is the most common cardiac arrhythmia, yet the molecular signature of the vulnerable atrial substrate is not well understood. Here, we delineated a distinct transcriptional signature in right versus left atrial cardiomyocytes (CMs) at baseline and identified chamber-specific gene expression changes in patients with a history of AF in the setting of end-stage heart failure (AF+HF) that are not present in heart failure alone (HF). We observed that human left atrial (LA) CMs exhibited Notch pathway activation and increased ploidy in AF+HF but not in HF alone. Transient activation of Notch signaling within adult CMs in a murine genetic model is sufficient to increase ploidy in both atrial chambers. Notch activation within LA CMs generated a transcriptomic fingerprint resembling AF, with dysregulation of transcription factor and ion channel genes, including Pitx2, Tbx5, Kcnh2, Kcnq1, and Kcnip2. Notch activation also produced distinct cellular electrophysiologic responses in LA versus right atrial CMs, prolonging the action potential duration (APD) without altering the upstroke velocity in the left atrium and reducing the maximal upstroke velocity without altering the APD in the right atrium. Our results support a shared human/murine model of increased Notch pathway activity predisposing to AF.
| S-EPMC7526559 | biostudies-literature
Project description:ImportanceAtrial fibrillation (AF) has a substantial genetic component. The importance of polygenic risk is well established, while the contribution of rare variants to disease risk warrants characterization in large cohorts.ObjectiveTo identify rare predicted loss-of-function (pLOF) variants associated with AF and elucidate their role in risk of AF, cardiomyopathy (CM), and heart failure (HF) in combination with a polygenic risk score (PRS).Design, setting, and participantsThis was a genetic association and nested case-control study. The impact of rare pLOF variants was evaluated on the risk of incident AF. HF and CM were assessed in cause-specific Cox regressions. End of follow-up was July 1, 2022. Data were analyzed from January to October 2023. The UK Biobank enrolled 502 480 individuals aged 40 to 69 years at inclusion in the United Kingdom between March 13, 2006, and October 1, 2010. UK residents of European ancestry were included. Individuals with prior diagnosis of AF were excluded from analyses of incident AF.ExposuresRare pLOF variants and an AF PRS.Main outcomes and measuresRisk of AF and incident HF or CM prior to and subsequent to AF diagnosis.ResultsA total of 403 990 individuals (218 489 [54.1%] female) with a median (IQR) age of 58 (51-63) years were included; 24 447 were diagnosed with incident AF over a median (IQR) follow-up period of 13.3 (12.4-14.0) years. Rare pLOF variants in 6 genes (TTN, RPL3L, PKP2, CTNNA3, KDM5B, and C10orf71) were associated with AF. Of these, TTN, RPL3L, PKP2, CTNNA3, and KDM5B replicated in an external cohort. Combined with high PRS, rare pLOF variants conferred an odds ratio of 7.08 (95% CI, 6.03-8.28) for AF. Carriers with high PRS also had a substantial 10-year risk of AF (16% in female individuals and 24% in male individuals older than 60 years). Rare pLOF variants were associated with increased risk of CM both prior to AF (hazard ratio [HR], 3.13; 95% CI, 2.24-4.36) and subsequent to AF (HR, 2.98; 95% CI, 1.89-4.69).Conclusions and relevanceRare and common genetic variation were associated with an increased risk of AF. The findings provide insights into the genetic underpinnings of AF and may aid in future genetic risk stratification.
| S-EPMC11209175 | biostudies-literature
Project description:BackgroundIt is known that expanded epicardial fat is associated with atrial fibrillation (AF). However, infiltrated intraatrial fat has not been previously quantified in individuals at risk as determined by the ARIC AF risk score.MethodsPatients in sinus rhythm (N=90, age 57 ± 10 years; 55 men [63.2%]), in 3 groups at risk of AF as determined by the ARIC AF risk score [low (≤ 11 points; n=15), moderate (12-18 points; n=40), high (≥ 19 points; n=23) risk of AF], and paroxysmal AF (n=12) underwent cardiac magnetic resonance study. Intraatrial and epicardial fat was analyzed with a Dark-blood DIR-prepared Fat-Water-separated sequence in the horizontal longitudinal axis. OsiriX DICOM viewer (Geneva, Switzerland) was used to quantify the intraatrial fat area. Width of the cephalad portion of the interatrial septum was measured at the level of the fossa ovalis.ResultsIntraatrial fat monotonically increased with growing AF risk in study groups (low AF risk 16 ± 4 vs. moderate AF risk 32 ± 18 vs. high AF risk 81 ± 83 mm(2); ANOVA P=0.012). Log-transformed intraatrial fat predicted ARIC AF risk score in multivariate ordered probit regression after adjustment for sex, race, left and right atrial area indices, and body mass index (β-coefficient 0.50 [95% CI 0.03-0.97]; P=0.037), whereas epicardial fat did not. Interatrial septum width showed similar association (3.0 ± 1.4 vs. 5.0 ± 1.8 vs. 7.1 ± 2.7 mm; ANOVA P<0.001; adjusted β-coefficient 2.80 [95% CI 1.19-4.41]; P=0.001).ConclusionsInfiltrated intraatrial fat characterizes evolving substrate in individuals at risk of AF.
| S-EPMC3987908 | biostudies-literature
Project description:BackgroundThe global age-adjusted mortality rate related to atrial fibrillation (AF) registered a rapid growth in the last four decades, i.e., from 0.8 to 1.6 and 0.9 to 1.7 per 100,000 for men and women during 1990-2010, respectively. In this context, this study uses convolutional neural networks for classifying (diagnosing) AF, employing electrocardiogram data in a general hospital.MethodsData came from Anam Hospital in Seoul, Korea, with 20,000 unique patients (10,000 normal sinus rhythm and 10,000 AF). 30 convolutional neural networks were applied and compared for the diagnosis of the normal sinus rhythm vs. AF condition: 6 Alex networks with 5 convolutional layers, 3 fully connected layers and the number of kernels changing from 3 to 256; and 24 residual networks with the number of residuals blocks (or kernels) varying from 8 to 2 (or 64 to 2).ResultsIn terms of the accuracy, the best Alex network was one with 24 initial kernels (i.e., kernels in the first layer), 5,268,818 parameters and the training time of 89?s (0.997), while the best residual network was one with 6 residual blocks, 32 initial kernels, 248,418 parameters and the training time of 253?s (0.999). In general, the performance of the residual network improved as the number of its residual blocks (its depth) increased.ConclusionFor AF diagnosis, the residual network might be a good model with higher accuracy and fewer parameters than its Alex-network counterparts.
| S-EPMC6819477 | biostudies-literature
Project description:Atrial fibrillation (AF) is a progressive arrhythmia for which current therapy is inadequate. During AF, rapid stimulation causes atrial remodeling that promotes further AF. The cellular signals that trigger this process remain poorly understood, however, and elucidation of these factors would likely identify new therapeutic targets. We have previously shown that immortalized mouse atrial (HL-1) myocytes subjected to 24 hr of rapid stimulation in culture undergo remodeling similar to that seen in animal models of atrial tachycardia (AT) and human AF. This preparation is devoid of confounding in vivo variables that can modulate gene expression (e.g., hemodynamics). Therefore, we investigated the transcriptional profile associated with early atrial cell remodeling. RNA was harvested from HL-1 cells cultured for 24 hr in the absence and presence of rapid stimulation and subjected to microarray analysis. Data were normalized using Robust Multichip Analysis (RMA), and genes exhibiting significant differential expression were identified using the Significance Analysis of Microarrays (SAM) method. Using this approach, 919 genes were identified that were significantly altered with rapid stimulation (763 up-regulated and 156 down-regulated). For many individual transcripts, changes typical of AF/AT were observed, with marked up-regulation of genes encoding BNP and ANP precursors, heat shock proteins, and MAP kinases, while novel signaling pathways and molecules were also identified. Both stress and survival response were evident, as well as up-regulation of multiple transcription factors. Genes were also functionally classified based on cellular component, biologic process, and molecular function using the Gene Ontology database to permit direct comparison of our data with other gene sets regulated in human AF and experimental AT. For broad categories of genes grouped by functional classification, there was striking conservation between rapidly stimulated HL-1 cells and AF/AT. Results were confirmed using real-time quantitative RT-PCR on 13 genes selected by physiological relevance in AF/AT and regulation in the microarray analysis (up, down, and nonregulated). Rapidly-stimulated atrial myocytes provide a complementary experimental paradigm to explore the initial cellular signals in AT remodeling to identify novel targets in the treatment of AF. Keywords: stimulated atrial myocytes human atrial fibrillation
2008-10-01 | GSE10598 | GEO
Project description:The aim of this study is to perform transcriptome analysis on mouse left atrium tissue after long-term ibrutinib treatment or cardiac CSK knockout, in order to compared the enriched gene clusters.
2020-04-01 | GSE139427 | GEO
Project description:KCNQ1 is a voltage-gated potassium channel that is modulated by the beta-subunit KCNE1 to generate IKs, the slow delayed rectifier current, which plays a critical role in repolarizing the cardiac action potential. Two KCNQ1 gain-of-function mutations that cause a genetic form of atrial fibrillation, S140G and V141M, drastically slow IKs deactivation. However, the underlying gating alterations remain unknown. Voltage clamp fluorometry (VCF) allows simultaneous measurement of voltage sensor movement and current through the channel pore. Here, we use VCF and kinetic modeling to determine the effects of mutations on channel voltage-dependent gating. We show that in the absence of KCNE1, S140G, but not V141M, directly slows voltage sensor movement, which indirectly slows current deactivation. In the presence of KCNE1, both S140G and V141M slow pore closing and alter voltage sensor-pore coupling, thereby slowing current deactivation. Our results suggest that KCNE1 can mediate changes in pore movement and voltage sensor-pore coupling to slow IKs deactivation and provide a key step toward developing mechanism-based therapies.
| S-EPMC5382920 | biostudies-literature