Genetics of atrial fibrillation. Heart Fail Clin. 2010;6:239-247. [PMID: 20347792 DOI: 10.1016/j.hfc.2009.12.004]

Towards Improved Human In Vitro Models for Cardiac Arrhythmia: Disease Mechanisms, Treatment, and Models of Atrial Fibrillation

Heart rhythm disorders, arrhythmias, place a huge economic burden on society and have a large impact on the quality of life of a vast number of people. Arrhythmias can have genetic causes but primarily arise from heart tissue remodeling during aging or heart disease. As current therapies do not address the causes of arrhythmias but only manage the symptoms, it is of paramount importance to generate innovative test models and platforms for gaining knowledge about the underlying disease mechanisms which are compatible with drug screening. In this review, we outline the most important features of atrial fibrillation (AFib), the most common cardiac arrhythmia. We will discuss the epidemiology, risk factors, underlying causes, and present therapies of AFib, as well as the shortcomings and opportunities of current models for cardiac arrhythmia, including animal models, in silico and in vitro models utilizing human pluripotent stem cell (hPSC)-derived cardiomyocytes.

Reviewing Atrial Fibrillation Pathophysiology from a Network Medicine Perspective: The Relevance of Structural Remodeling, Inflammation, and the Immune System

Atrial fibrillation (AF) is the most common type of sustained arrhythmia. The numerous gaps concerning the knowledge of its mechanism make improving clinical management difficult. As omics technologies allow more comprehensive insight into biology and disease at a molecular level, bioinformatics encompasses valuable tools for studying systems biology, as well as combining and modeling multi-omics data and networks. Network medicine is a subarea of network biology where disease traits are considered perturbations within the interactome. With this approach, potential disease drivers can be revealed, and the effect of drugs, novel or repurposed, used alone or in combination, may be studied. Thus, this work aims to review AF pathology from a network medicine perspective, helping researchers to comprehend the disease more deeply. Essential concepts involved in network medicine are highlighted, and specific research applying network medicine to study AF is discussed. Additionally, data integration through literature mining and bioinformatics tools, with network building, is exemplified. Together, all of the data show the substantial role of structural remodeling, the immune system, and inflammation in this disease etiology. Despite this, there are still gaps to be filled about AF.

Healing the Broken Hearts: A Glimpse on Next Generation Therapeutics

Cardiovascular diseases are the leading cause of death worldwide, accounting for 32% of deaths globally and thus representing almost 18 million people according to WHO. Myocardial infarction, the most prevalent adult cardiovascular pathology, affects over half a million people in the USA according to the last records of the AHA. However, not only adult cardiovascular diseases are the most frequent diseases in adulthood, but congenital heart diseases also affect 0.8–1.2% of all births, accounting for mild developmental defects such as atrial septal defects to life-threatening pathologies such as tetralogy of Fallot or permanent common trunk that, if not surgically corrected in early postnatal days, they are incompatible with life. Therefore, both congenital and adult cardiovascular diseases represent an enormous social and economic burden that invariably demands continuous efforts to understand the causes of such cardiovascular defects and develop innovative strategies to correct and/or palliate them. In the next paragraphs, we aim to briefly account for our current understanding of the cellular bases of both congenital and adult cardiovascular diseases, providing a perspective of the plausible lines of action that might eventually result in increasing our understanding of cardiovascular diseases. This analysis will come out with the building blocks for designing novel and innovative therapeutic approaches to healing the broken hearts.

Identification of Hub mRNAs and lncRNAs in Atrial Fibrillation Using Weighted Co-expression Network Analysis With RNA-Seq Data

Atrial fibrillation (AF)/paroxysmal AF (PAF) is the main cause of cardiogenic embolism. In recent years, the progression from paroxysmal AF to persistent AF has attracted more and more attention. However, the molecular mechanism of the progression of AF is unclear. In this study, we performed RNA sequencing for normal samples, paroxysmal AF and persistent AF samples to identify differentially expressed gene (DEG) and explore the roles of these DEGs in AF. Totally, 272 differently expressed mRNAs (DEmRNAs) and 286 differentially expressed lncRNAs (DElncRNAs) were identified in paroxysmal AF compared to normal samples; 324 DEmRNAs and 258 DElncRNAs were found in persistent atrial fibrillation compared with normal samples; and 520 DEmRNAs and 414 DElncRNAs were identified in persistent AF compared to paroxysmal AF samples. Interestingly, among the DEGs, approximately 50% were coding genes and around 50% were non-coding RNAs, suggesting that lncRNAs may also have a crucial role in the progression of AF. Bioinformatics analysis demonstrated that these DEGs were significantly related to regulating multiple AF associated pathways, such as the regulation of vascular endothelial growth factor production and binding to the CXCR chemokine receptor. Furthermore, weighted gene co-expression network analysis (WGCNA) was conducted to identify key modules and hub RNAs and lncRNAs to determine their potential associations with AF. Five hub modules were identified in the progression of AF, including blue, brown, gray, turquoise and yellow modules. Interestingly, blue module and turquoise module were significantly negatively and positively correlated to the progression of AF respectively, indicating that they may have a more important role in the AF. Moreover, the hub protein-protein interaction (PPI) networks and lncRNA-mRNA regulatory network were constructed. Bioinformatics analysis on the hub PPI network in turquoise was involved in regulating immune response related signaling, such as leukocyte chemotaxis, macrophage activation, and positive regulation of α-β T cell activation. Our findings could clarify the underlying molecular changes associated fibrillation, and provide a useful resource for identifying AF marker.

Application of a time-series deep learning model to predict cardiac dysrhythmias in electronic health records

BACKGROUND

Cardiac dysrhythmias (CD) affect millions of Americans in the United States (US), and are associated with considerable morbidity and mortality. New strategies to combat this growing problem are urgently needed.

OBJECTIVES

Predicting CD using electronic health record (EHR) data would allow for earlier diagnosis and treatment of the condition, thus improving overall cardiovascular outcomes. The Guideline Advantage (TGA) is an American Heart Association ambulatory quality clinical data registry of EHR data representing 70 clinics distributed throughout the US, and has been used to monitor outpatient prevention and disease management outcome measures across populations and for longitudinal research on the impact of preventative care.

METHODS

For this study, we represented all time-series cardiovascular health (CVH) measures and the corresponding data collection time points for each patient by numerical embedding vectors. We then employed a deep learning technique-long-short term memory (LSTM) model-to predict CD from the vector of time-series CVH measures by 5-fold cross validation and compared the performance of this model to the results of deep neural networks, logistic regression, random forest, and Naïve Bayes models.

RESULTS

We demonstrated that the LSTM model outperformed other traditional machine learning models and achieved the best prediction performance as measured by the average area under the receiver operator curve (AUROC): 0.76 for LSTM, 0.71 for deep neural networks, 0.66 for logistic regression, 0.67 for random forest, and 0.59 for Naïve Bayes. The most influential feature from the LSTM model were blood pressure.

CONCLUSIONS

These findings may be used to prevent CD in the outpatient setting by encouraging appropriate surveillance and management of CVH.

Transcriptional factors in calcium mishandling and atrial fibrillation development

Healthy cardiac conduction relies on the coordinated electrical activity of distinct populations of cardiomyocytes. Disruption of cell-cell conduction results in cardiac arrhythmias, a leading cause of morbidity and mortality worldwide. Recent genetic studies have highlighted a major heritable component and identified numerous loci associated with risk of atrial fibrillation, including transcription factor genes, particularly those important in cardiac development, microRNAs, and long noncoding RNAs. Identification of such genetic factors has prompted the search to understand the mechanisms that underlie the genetic component of AF. Recent studies have found several mechanisms by which genetic alterations can result in AF formation via disruption of calcium handling. Loss of developmental transcription factors in adult cardiomyocytes can result in disruption of SR calcium ATPase, sodium calcium exchanger, calcium channels, among other ion channels, which underlie action potential abnormalities and triggered activity that can contribute to AF. This review aims to summarize the complex network of transcription factors and their roles in calcium handling.

Genetics and Epigenetics of Atrial Fibrillation

Atrial fibrillation (AF) is known to be the most common supraventricular arrhythmia affecting up to 1% of the general population. Its prevalence exponentially increases with age and could reach up to 8% in the elderly population. The management of AF is a complex issue that is addressed by extensive ongoing basic and clinical research. AF centers around different types of disturbances, including ion channel dysfunction, Ca²⁺-handling abnormalities, and structural remodeling. Genome-wide association studies (GWAS) have uncovered over 100 genetic loci associated with AF. Most of these loci point to ion channels, distinct cardiac-enriched transcription factors, as well as to other regulatory genes. Recently, the discovery of post-transcriptional regulatory mechanisms, involving non-coding RNAs (especially microRNAs), DNA methylation, and histone modification, has allowed to decipher how a normal heart develops and which modifications are involved in reshaping the processes leading to arrhythmias. This review aims to provide a current state of the field regarding the identification and functional characterization of AF-related epigenetic regulatory networks

Relationship of Neighborhood Greenness to Heart Disease in 249 405 US Medicare Beneficiaries

Background Nature exposures may be associated with reduced risk of heart disease. The present study examines the relationship between objective measures of neighborhood greenness (vegetative presence) and 4 heart disease diagnoses (acute myocardial infarction, ischemic heart disease, heart failure, and atrial fibrillation) in a population-based sample of Medicare beneficiaries. Methods and Results The sample included 249 405 Medicare beneficiaries aged 65 years and older whose location ( ZIP +4) in Miami-Dade County, Florida, did not change from 2010 to 2011. Analyses examined relationships between greenness, measured by mean block-level normalized difference vegetation index from satellite imagery, and 4 heart disease diagnoses. Hierarchical regression analyses, in a multilevel framework, assessed the relationship of greenness to each heart disease diagnosis, adjusting successively for individual sociodemographics, neighborhood income, and biological risk factors (diabetes mellitus, hypertension, and hyperlipidemia). Higher greenness was associated with reduced heart disease risk, adjusting for individual sociodemographics and neighborhood income. Compared with the lowest tertile of greenness, the highest tertile of greenness was associated with reduced odds of acute myocardial infarction by 25% (odds ratio, 0.75; 95% CI , 0.63-0.90), ischemic heart disease by 20% (odds ratio, 0.80; 95% CI , 0.77-0.83), heart failure by 16% (odds ratio, 0.84; 95% CI , 0.80-0.88), and atrial fibrillation by 6% (odds ratio, 0.94; 95% CI , 0.87-1.00). Associations were attenuated after adjusting for biological risk factors, suggesting that cardiometabolic risk factors may partly mediate the greenness to heart disease relationships. Conclusions Neighborhood greenness may be associated with reduced heart disease risk. Strategies to increase area greenness may be a future means of reducing heart disease at the population level.

Mechanisms and Drug Development in Atrial Fibrillation

Atrial fibrillation is a highly prevalent cardiac arrhythmia and the most important cause of embolic stroke. Although genetic studies have identified an increasing assembly of AF-related genes, the impact of these genetic discoveries is yet to be realized. In addition, despite more than a century of research and speculation, the molecular and cellular mechanisms underlying AF have not been established, and therapy for AF, particularly persistent AF, remains suboptimal. Current antiarrhythmic drugs are associated with a significant rate of adverse events, particularly proarrhythmia, which may explain why many highly symptomatic AF patients are not receiving any rhythm control therapy. This review focuses on recent advances in AF research, including its epidemiology, genetics, and pathophysiological mechanisms. We then discuss the status of antiarrhythmic drug therapy for AF today, reviewing molecular mechanisms, and the possible clinical use of some of the new atrial-selective antifibrillatory agents, as well as drugs that target atrial remodeling, inflammation and fibrosis, which are being tested as upstream therapies to prevent AF perpetuation. Altogether, the objective is to highlight the magnitude and endemic dimension of AF, which requires a significant effort to develop new and effective antiarrhythmic drugs, but also improve AF prevention and treatment of risk factors that are associated with AF complications.

Addressing Multimorbidity and Polypharmacy in Individuals With Atrial Fibrillation

PURPOSE OF REVIEW

The objectives of this review were to (1) discuss how multimorbidity and polypharmacy contributes to the complexity of management among individuals with AF and (2) identify any interventions to manage polypharmacy in relation to AF.

RECENT FINDINGS

Based on the four landmark clinical trials of novel anticoagulants, the most common comorbidities with AF are hypertension, heart failure, diabetes, stroke and myocardial infarction. Polypharmacy was also found prevalent in 76.5% of patients with AF, with a median of six drugs per patient. Despite the consequences of polypharmacy in AF, there is very little evidence-based intervention designed to manage it. Hence, there is a need for further research to examine interventions to manage polypharmacy in relation to AF. Atrial fibrillation (AF) is the most common type of cardiac arrhythmia requiring treatment in adults. Due to the structural and/or electrophysiological abnormalities that occur in AF, patients are managed through the use of prophylactic anticoagulant and rate and/or rhythm control medications. However, these medications are considered high risk and can increase the chances of medication misadventure. Additionally, AF rarely occurs in isolation and is known to coexist with multiple other medical comorbidities, i.e. multimorbidity. This also increases the number of medications, i.e. polypharmacy and pill burden which results in treatment non-compliance to prescribed therapy.

Association Between Rs3807989 Polymorphism in Caveolin-1 (CAV1) Gene and Atrial Fibrillation: A Meta-Analysis

Background

Atrial fibrillation (AF) is the most common sustained arrhythmia affected by multiple cardiovascular risk factors. It is reported that caveolin-1 gene (CAV1) rs3807989 polymorphism might be associated with AF risk. The goal of this meta-analysis was to confirm the association between CAV1 rs3807989 polymorphism and susceptibility to AF.

Material/Methods

We carried out a comprehensive literature search through the electronic databases PubMed, MEDLIN, and Web of Science. We performed a meta-analysis of all selected studies based on CAV1 rs3807989 polymorphism genotypes, including 3758 cases and 6126 controls.

Results

After meta-analysis with fixed- or random-effects models, we found significant associations in all 5 comparisons: allelic model (G/A; OR=1.228, 95%CI: 1.061–1.420; P=0.006), homozygote model (GG/AA; OR=1.439, 95%CI: 1.094–1.894; P=0.009), heterozygote model (GG/GA; OR=1.257, 95%CI: 1.064–1.486; P=0.007), dominant model (GG/AA+GA; OR=1.287, 95%CI: 1.076–1.540; P=0.006), and recessive model (AA/GA+GG; OR=0.738, 95%CI: 0.629–0.867; P<0.001). Sensitivity analysis results revealed the overall results were robust.

Conclusions

The results revealed a significant association between CAV1 gene rs3807989 polymorphism and susceptibility to AF, suggesting that the presence of allelic G might be one of the genetic factors conferring susceptibility to AF. To confirm this association, further well-designed studies are necessary.

The rs6771157 C/G polymorphism in SCN10A is associated with the risk of atrial fibrillation in a Chinese Han population

A recent genome wide associated study in European descent population identified the association of Atrial fibrillation (AF) risk with a single nucleotide polymorphism (SNP) in SCN10A. The aim of this study was to evaluate whether SCN10A polymorphisms are associated with AF risk in the Chinese Han population. A total of 2,300 individuals of Chinese Han origin were recruited and three potentially functional SNPs were genotyped. Logistic regression models were utilized to calculate odds ratios (ORs) at a 95% confidence intervals (CIs). Logistic regression analysis in an additive genetic model revealed that one SNP in SCN10A (rs6771157) was associated with an increased risk of AF (adjusted OR = 1.20, 95% CI: 1.06 - 1.36, P = 0.003). Stratification analysis of several main AF risk factors indicated that the risk associations with rs6771157 were not statistically different among different subgroups. In summary, our study suggests the possible involvement of the SCN10A variant in AF development in Chinese Han populations. Further biological function analyses are required to confirm our finding.

Cardiovascular risk factors for acute stroke: Risk profiles in the different subtypes of ischemic stroke

Timely diagnosis and control of cardiovascular risk factors is a priority objective for adequate primary and secondary prevention of acute stroke. Hypertension, atrial fibrillation and diabetes mellitus are the most common risk factors for acute cerebrovascular events, although novel risk factors, such as sleep-disordered breathing, inflammatory markers or carotid intima-media thickness have been identified. However, the cardiovascular risk factors profile differs according to the different subtypes of ischemic stroke. Atrial fibrillation and ischemic heart disease are more frequent in patients with cardioembolic infarction, hypertension and diabetes in patients with lacunar stroke, and vascular peripheral disease, hypertension, diabetes, previous transient ischemic attack and chronic obstructive pulmonary disease in patients with atherothrombotic infarction. This review aims to present updated data on risk factors for acute ischemic stroke as well as to describe the usefulness of new and emerging vascular risk factors in stroke patients.

Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network

BACKGROUND AND PURPOSE

NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium.

METHODS

Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases.

RESULTS

The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75).

CONCLUSIONS

This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.

The rs3807989 G/A polymorphism in CAV1 is associated with the risk of atrial fibrillation in Chinese Han populations

BACKGROUND

A recent meta-analysis of several genome-wide association studies identified six new susceptibility single nucleotide polymorphisms (SNPs) for atrial fibrillation (AF) in individuals of the European ancestry. We aimed to replicate the associations between these SNPs and the risk of AF in a Chinese Han population.

METHODS

We genotyped six SNPs (rs3903239 in PRRX1, rs3807989 in CAV1, rs10821415 in C9orf3, rs10824026 in SYNPO2L, rs1152591 in SYNE2, and rs7164883 in HCN4) using the middle-throughput iPLEX Sequenom MassARRAY platform. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in logistic regression models.

RESULTS

We enrolled a total of 1,593 Chinese Han origin individuals in the study, including 597 AF patients and 996 non-AF controls. Among the six SNPs analyzed in the study, the SNP rs3807989 in CAV1 on chromosome 7q31 was found to be significantly associated with a decreased risk of AF (crude OR = 0.76, 95% CI: 0.64-0.89, P = 0.001; adjusted OR = 0.75, 95% CI: 0.63-0.89, P = 0.001). There were no significant associations between the other five loci and AF risk.

CONCLUSION

Our results confirmed that CAV1 rs3807989 may contribute to a decreased AF risk in Chinese Han populations. However, further validation studies with different ethnic backgrounds and biological function analyses are warranted to confirm our finding.

Genetic polymorphisms in ZFHX3 are associated with atrial fibrillation in a Chinese Han population

Background

The gene zinc finger homeobox 3 (ZFHX3) encodes a transcription factor with cardiac expression and its genetic variants are associated with atrial fibrillation (AF). We aimed to explore the associations between single nucleotide polymorphisms (SNPs) of ZFHX3 and the risk of AF in a Chinese Han population.

Methods

We genotyped eight SNPs, including seven potentially functional SNPs and one previously reported SNP by using the middle-throughput iPLEX Sequenom MassARRAY platform. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in logistic regression models.

Results

We enrolled a total of 1,593 Chinese Han origin individuals in the study, including 597 AF patients and 996 non-AF controls. Logistic regression analyses revealed that potentially functional SNPs rs6499600 and rs16971436 were associated with a decreased risk of AF (adjusted OR  = 0.73, 95% CI: 0.63–0.86, P = 1.07×10⁻⁴; adjusted OR  = 0.74, 95% CI: 0.56–0.98, P = 0.039, respectively). In addition, rs2106261 showed a robust association with an increased risk of AF (adjusted OR  = 1.71, 95% CI: 1.46–2.00, P = 1.85×10⁻¹¹). After multiple comparisons, rs16971436 conferred a borderline significant association with the risk of AF. Stratification analysis indicated that the risks of AF were statistically different among subgroups of age for rs2106261, and the effect for rs16971436 was more evident in subgroups of patients with coronary artery disease.

Conclusion

In summary, our study investigated the role of genetic variants of ZFHX3 in AF and two SNPs (rs2106261, rs6499600) showed significant associations while rs16971436 conferred a borderline significant association with AF risk in Chinese Han populations. However, further large and functional studies are warranted to confirm our findings.

Stroke Genetics Network (SiGN) study: design and rationale for a genome-wide association study of ischemic stroke subtypes

BACKGROUND AND PURPOSE

Meta-analyses of extant genome-wide data illustrate the need to focus on subtypes of ischemic stroke for gene discovery. The National Institute of Neurological Disorders and Stroke SiGN (Stroke Genetics Network) contributes substantially to meta-analyses that focus on specific subtypes of stroke.

METHODS

The National Institute of Neurological Disorders and Stroke SiGN includes ischemic stroke cases from 24 genetic research centers: 13 from the United States and 11 from Europe. Investigators harmonize ischemic stroke phenotyping using the Web-based causative classification of stroke system, with data entered by trained and certified adjudicators at participating genetic research centers. Through the Center for Inherited Diseases Research, the Network plans to genotype 10,296 carefully phenotyped stroke cases using genome-wide single nucleotide polymorphism arrays and adds to these another 4253 previously genotyped cases, for a total of 14,549 cases. To maximize power for subtype analyses, the study allocates genotyping resources almost exclusively to cases. Publicly available studies provide most of the control genotypes. Center for Inherited Diseases Research-generated genotypes and corresponding phenotypes will be shared with the scientific community through the US National Center for Biotechnology Information database of Genotypes and Phenotypes, and brain MRI studies will be centrally archived.

CONCLUSIONS

The Stroke Genetics Network, with its emphasis on careful and standardized phenotyping of ischemic stroke and stroke subtypes, provides an unprecedented opportunity to uncover genetic determinants of ischemic stroke.

Atrial Fibrillation - A Common Ground for Neurology and Cardiology

Atrial fibrillation (AF) has a huge impact on clinical stroke because it is the primary cause of cardio-embolism, which constitutes ~20% of all strokes. As a result, there is a great need to explore safer and more effective primary and secondary prophylactic agents. In this article, we discuss the overlapping issues pertaining to AF from both a neurology and cardiology standpoint. We focus on the dynamic interplay of neurovascular and cardiovascular diseases in relation to AF, traditional and novel risk factors for AF leading to stroke, impact of AF on cognitive decline, and current upstream medical and surgical options for embolism prophylaxis.

Functional modeling in zebrafish demonstrates that the atrial-fibrillation-associated gene GREM2 regulates cardiac laterality, cardiomyocyte differentiation and atrial rhythm

Atrial fibrillation (AF) is the most common cardiac arrhythmia and carries a significant risk of stroke and heart failure. The molecular etiologies of AF are poorly understood, leaving patients with limited therapeutic options. AF has been recognized as an inherited disease in almost 30% of patient cases. However, few genetic loci have been identified and the mechanisms linking genetic variants to AF susceptibility remain unclear. By sequencing 193 probands with lone AF, we identified a Q76E variant within the coding sequence of the bone morphogenetic protein (BMP) antagonist gremlin-2 (GREM2) that increases its inhibitory activity. Functional modeling in zebrafish revealed that, through regulation of BMP signaling, GREM2 is required for cardiac laterality and atrial differentiation during embryonic development. GREM2 overactivity results in slower cardiac contraction rates in zebrafish, and induction of previously identified AF candidate genes encoding connexin-40, sarcolipin and atrial natriuretic peptide in differentiated mouse embryonic stem cells. By live heart imaging in zebrafish overexpressing wild-type or variant GREM2, we found abnormal contraction velocity specifically in atrial cardiomyocytes. These results implicate, for the first time, regulators of BMP signaling in human AF, providing mechanistic insights into the pathogenesis of the disease and identifying potential new therapeutic targets.

Atrial Fibrillation and Long QT Syndrome Presenting in a 12-Year-Old Girl

Atrial fibrillation (AF) is rare in the pediatric population; however, there is increasing recognition that AF can be inherited. Long QT syndrome (LQTS), likewise, can be both acquired and inherited with mutations leading to abnormalities in cardiac ion channel function. Mutations in KCNQ1 are the most common cause of LQTS. Although rare, mutations in KCNQ1 also can cause familial AF. This report describes a child with a KCNQ1 missense mutation who uniquely expresses concomitant AF and LQTS. Due to the potential for increased morbidity and mortality, young patients who present with AF and a family history suggestive of inherited arrhythmias should trigger further investigation for LQTS and subsequent familial genetic counseling.

Mutation spectrum of the GATA4 gene in patients with idiopathic atrial fibrillation

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia associated with substantially increased morbidity and mortality. Growing evidence strongly implicates hereditary determinants in the pathogenesis of AF. However, AF is genetically heterogeneous and the genetic defects responsible for AF in the majority of cases remain to be identified. In this study, all the coding exons and splice junctions of GATA4, a gene encoding a zinc-finger transcription factor critical for normal cardiac morphogenesis, were sequenced in a cohort of 150 unrelated patients with idiopathic AF. The available relatives of the mutation carriers and a total of 200 unrelated ethnically matched healthy individuals used as controls were genotyped for the presence of mutations identified in index patients. The functional effect of the mutant GATA4 was characterized using a luciferase reporter assay system. As a result, two novel heterozygous GATA4 mutations (p.Y38D and p.P103A) were identified in 2 unrelated families with AF, respectively. In each family the mutation co-segregated with AF and was absent in the 400 control chromosomes. Functional analysis showed that the mutations of GATA4 were associated with a significantly decreased transcriptional activity. The findings expand the mutation spectrum of GATA4 linked to AF, and further support the notion that compromised GATA4 confers genetic susceptibility to AF.

The role of the renin-angiotensin system blocking in the management of atrial fibrillation

OBJECTIVE

To review current available evidence for the role of renin-angiotensin system blockade in the management of atrial fibrillation.

METHOD

We conducted a PubMed and Medline literature search (January 1980 through July 2011) to identify all clinical trials published in English concerning the use of angiotensin converting enzyme inhibitors or angiotensin II receptor blockers for primary and secondary prevention of atrial fibrillation. We also discussed renin-angiotensin system and its effects on cellular electrophysiology.

CONCLUSION

The evidence from the current studies discussed does not provide a firm definitive indication for the use of angiotensin converting enzyme inhibitors or angiotensin II receptor blockers in the primary or secondary prevention of atrial fibrillation. Nevertheless, modest benefits were observed in patients with left ventricular dysfunction. In view of the possible benefits and the low incidence of side-effects with angiotensin converting enzyme inhibitors and angiotensin II receptor blockers, they can be given to patients with recurrent AF, specifically those with hypertension, heart failure and diabetes mellitus.

Augmented rififylin is a risk factor linked to aberrant cardiomyocyte function, short-QT interval and hypertension

Using congenic strains of the Dahl salt-sensitive (S) rat introgressed with genomic segments from the normotensive Lewis rat, a blood pressure quantitative trait locus was previously mapped within 104 kb on chromosome 10. The goal of the current study was to conduct extensive phenotypic studies and to further fine-map this locus. At 14 weeks of age, the blood pressure of the congenic rats fed a low-salt diet was significantly higher by 47 mm Hg (P<0.001) compared with that of the S rat. A time-course study showed that the blood pressure effect was significant from very young ages of 50 to 52 days (13 mm Hg; P<0.01). The congenic strain implanted with electrocardiography transmitters demonstrated shorter-QT intervals and increased heart rate compared with S rats (P<0.01). The average survival of the congenic strain was shorter (134 days) compared with the S rat (175 days; P<0.0007). The critical region was narrowed to <42.5 kb containing 171 variants and a single gene, rififylin. Both the mRNA and protein levels of rififylin were significantly higher in the hearts of the congenic strain. Overexpression of rififylin is known to delay endocytic recycling. Endocytic recycling of fluorescently labeled holotransferrin from cardiomyocytes of the congenic strain was slower than that of S rats (P<0.01). Frequency of cardiomyocyte beats in the congenic strain (62±9 bpm) was significantly higher than that of the S rat (24±6 bpm; P<0.001). Taken together, our study provides evidence to suggest that early perturbations in endocytic recycling caused by the overexpression of Rffl is a novel physiological mechanism potentially underlying the development of hypertension.