Familial aggregation of atrial fibrillation: a study in Danish twins

Childhood Smoking Initiation, Genetic Susceptibility, and Incident Cardiovascular Diseases in Adulthood

PURPOSE

We aimed to assess the associations of age of smoking initiation and polygenic risk scores (PRSs), individually and jointly, with the incidence of overall cardiovascular diseases (CVDs), coronary artery disease (CAD), atrial fibrillation (AF), and stroke in adulthood.

METHODS

Multivariable-adjusted accelerated failure time models were used to assess the impacts of age of smoking initiation and PRSs on incident overall CVDs, CAD, AF, and stroke in adulthood and to examine their joint effect on these outcomes.

RESULTS

Compared with never smokers, the time ratio (TR) with a 95% confidence interval (CI) for incident overall CVDs was 0.80 (0.78-0.82) among participants who initiated smoking at age 5-14 years, and 0.85 (0.84-0.86) at age 15-17 years. The corresponding TRs (95% CIs) for CAD were 0.74 (0.72-0.76) and 0.81 (0.79-0.83), respectively; for AF were 0.89 (0.86-0.91) and 0.91 (0.89-0.93), respectively; and for stroke were 0.84 (0.80-0.87) and 0.87 (0.85-0.90), respectively. Notably, participants with high PRSs who initiated smoking at age 5-14 years (vs. never smokers with low PRSs) were the fastest ones to develop overall CVDs (TR = 0.63, 95% CI = 0.61-0.65), CAD (TR = 0.48, 95% CI = 0.46-0.51), AF (TR = 0.55, 95% CI = 0.53-0.57), and stroke (TR = 0.70, 95% CI = 0.66-0.75).

DISCUSSION

Smoking initiation in childhood significantly accelerated the incidence of overall CVDs, CAD, AF, and stroke in adulthood. Of note, participants with high genetic susceptibility who initiated smoking in childhood had the earliest onset time of CVDs later in life.

Association between genotypes of ABCB1 and ABCG2 and the risk of atrial fibrillation

AIMS

Atrial fibrillation (AF) is a prevalent clinical condition worldwide, with a high global incidence that significantly impacts disease burden and mortality rates. Single nucleotide polymorphisms in ABCB1 and ABCG2 are common, but the clinical outcomes are poorly understood. This study examines the association between the genetic variations of ABCB1 and ABCG2 and the risk of AF in a Taiwanese population.

METHODS AND RESULTS

This case-control study recruited 216 AF patients from two hospitals in Taiwan between 2021 and 2023. Control groups were matched by age (± one year), gender, and AF-related variables from the Taiwan Biobank. Logistic regression analyzed the association between three genetic variants and AF risk. A significant association was noted between ABCG2 rs2231142 and AF risk. Those with ABCG2 rs2231142 G/T and T/T genotypes had a 1.91-fold (95 % CI = 1.04-3.53) increased risk of AF compared to those with the G/G genotype. This association was particularly pronounced in males in those carrying ABCG2 rs2231143 T/T genotype having a 4.47-fold (95 % CI = 1.02-19.67) increased risk after adjusting for covariates. There were no overall significant associations between AF risk and the polymorphisms of ABCB1 rs4148738 and rs1128503.

CONCLUSION

A robust risk association between the ABCG2 rs2231142 T allele and AF in Asian populations, particularly in male adults, suggests that genetic testing for this polymorphism could be integrated into risk assessment models for AF.

The Genetic Mechanisms and Pathology of Atrial Fibrillation: A Narrative Review

Atrial fibrillation (AF), the most prevalent tachyarrhythmia worldwide, is a complex condition influenced by genetic, structural, and environmental factors. While AF in the elderly is often associated with underlying cardiac disease, early-onset or "lone" AF (LAF) exhibits a stronger genetic predisposition. Studies have identified both monogenic and polygenic contributors to AF risk. Monogenic mutations, inherited in Mendelian patterns, often affect ion channels and regulatory proteins, while polygenic variants modulate susceptibility and interact with environmental factors. Genome-wide association studies (GWAS) and exosome-wide association studies (ExWAS) have expanded our understanding of AF genetics, identifying numerous susceptibility loci, though challenges remain in linking these variants to specific molecular mechanisms. Pathophysiologically, AF results from a balance of triggers, drivers, and substrates. Triggers, such as ectopic foci in the pulmonary veins, initiate AF episodes, while structural and electrical remodeling perpetuates the arrhythmia. Fibrosis, atrial dilation, and tachycardia-induced remodeling promote reentry circuits and irregular conduction, increasing AF vulnerability. The interplay between genetic predisposition and remodeling processes underscores the complexity of AF maintenance, particularly in persistent AF forms. Emerging insights into AF genetics and pathophysiology highlight the need for personalized approaches to its prevention and management. Understanding genetic risk, combined with targeted therapies addressing structural and electrical remodeling, holds promise for improved patient outcomes. Future research into AF's molecular and genetic mechanisms will be key to advancing precision medicine in this field.

Causal inference in the field of arrhythmia: An introduction to mendelian randomization

Mendelian randomization (MR) uses genetic variants associated with an exposure (eg, high blood pressure) as instrumental variables to test causal effects on an outcome (eg, atrial fibrillation [AF]). By leveraging the random assortment of genetic variants during gamete formation, MR reduces biases like confounding and reverse causation. We screened 391 papers, examining 277 that applied MR to investigate arrhythmia and, in others, cardiovascular traits, lifestyle, behavioral traits, and body composition. Our analysis focused on MR studies of arrhythmia and cardiovascular traits. Key findings highlight high systolic blood pressure, low resting heart rate, elevated cardiac troponin I levels, coronary artery disease, and heart failure as risk factors for AF, whereas AF itself increases heart failure risk. As genetic data become more accessible, MR's relevance grows. Sensitivity analyses and integrating MR with other methodologies in a triangulation framework enhance the robustness of causal inferences by navigating different biases.

Genetic and Molecular Underpinnings of Atrial Fibrillation

Atrial fibrillation (AF), the most common sustained arrhythmia, increases stroke and heart failure risks. Here we review genes linked to AF and mechanisms by which they alter AF risk. We highlight gene expression differences between atrial and ventricular cardiomyocytes, regulatory mechanisms responsible for these differences, and their potential contribution to AF. Understanding AF mechanisms through the lens of atrial gene regulation is crucial to improving AF treatment.

Effectiveness of receiving cardiovascular disease genetic risk information on health behaviors, psychological responses, and associated risk factor modification in individuals: a systematic review protocol

OBJECTIVE

This review aims to assess the effectiveness of receiving cardiovascular disease (CVD) genetic risk information on individual health behaviors, psychological responses, and risk factor modification.

INTRODUCTION

Advancements in genomics have identified strong genetic predispositions for CVD, leading to the development of CVD genetic risk information. Integrating genetic risk information into clinical practice shows promise in predicting CVD risk and facilitating multifactorial management.

INCLUSION CRITERIA

This review will focus on randomized controlled trials assessing individual responses to CVD genetic risk information. Participants will be adults aged 18 or older, either with or without CVD. The review will compare the effectiveness of receiving genetic risk information with receiving traditional risk information or no risk information, assessing outcomes such as health behaviors, psychological responses, and risk factor modification.

METHODS

Cochrane CENTRAL, MEDLINE, Embase, and Emcare will be searched for relevant studies. Current or unpublished trials will be searched for in ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform. Articles will be screened and assessed for inclusion by 2 independent reviewers. Methodological quality will be assessed using the standardized instrument from JBI. Data will be extracted and synthesized according to the objectives of the review. If data are sufficient, a meta-analysis will be conducted; otherwise, the findings will be presented in narrative format, including tables and figures. The certainty of evidence will be assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

REVIEW REGISTRATION

PROSPERO CRD42023390876.

Joint and interactive associations of body mass index and genetic factors with cardiovascular disease: a prospective study in UK Biobank

BACKGROUND

Both body mass index (BMI) and genetic factors independently contribute to cardiovascular disease (CVD). However, it is unclear whether genetic risk modifies the association between BMI and the risk of incident CVD. This study aimed to investigate whether BMI categories and genetic risk jointly and interactively contribute to incident CVD events, including hypertension (HTN), atrial fibrillation (AF), coronary heart disease (CHD), stroke, and heart failure (HF).

METHODS

A total of 496,851 participants from the UK Biobank with one or more new-onset CVD events were included in the analyses. BMI was categorized as normal weight (< 25.0 kg/m2), overweight (25.0-29.9 kg/m2), and obesity (≥ 30.0 kg/m2). Genetic risk for each outcome was defined as low (lowest tertile), intermediate (second tertile), and high (highest tertile) using polygenic risk score. The joint associations of BMI categories and genetic risk with incident CVD were investigated using Cox proportional hazard models. Additionally, additive interactions were evaluated.

RESULTS

Among the 496,851 participants, 270,726 (54.5%) were female, with a mean (SD) age was 56.5 (8.1) years. Over a median follow-up (IQR) of 12.4 (11.5-13.1) years, 102,131 (22.9%) participants developed HTN, 26,301 (5.4%) developed AF, 32,222 (6.9%) developed CHD, 10,684 (2.2%) developed stroke, and 13,304 (2.7%) developed HF. Compared with the normal weight with low genetic risk, the obesity with high genetic risk had the highest risk of CVD: HTN (HR: 3.96; 95%CI: 3.84-4.09), AF (HR: 3.60; 95%CI: 3.38-3.83), CHD (HR: 2.76; 95%CI: 2.61-2.91), stroke (HR: 1.44; 95%CI: 1.31-1.57), and HF (HR: 2.47; 95%CI: 2.27-2.69). There were significant additive interactions between BMI categories and genetic risk for HTN, AF, and CHD, with relative excess risk of 0.53 (95%CI: 0.43-0.62), 0.67 (95%CI: 0.51-0.83), and 0.37 (95%CI: 0.25-0.49), respectively.

CONCLUSIONS

BMI and genetic factors jointly and interactively contribute to incident CVD, especially among participants with high genetic risk. These findings have public health implications for identifying populations more likely to have cardiovascular benefit from weight loss interventions.

Sex differences in early-onset atrial fibrillation in Norwegian primary care: a retrospective national database analysis

BACKGROUND

Individual variation in the need for healthcare constitutes knowledge gaps for young atrial fibrillation (AF) patients. We aimed to estimate the prevalence and primary care burden of early-onset AF in Norway, emphasising sex differences, in a nationwide healthcare database.

METHODS

We used data from the Norwegian Control and Payment of Health Reimbursement database to identify all Norwegian residents ≥18 years of age registered with a primary care physician (PCP) in 2019, with onset of AF at ≤50 years of age (early-onset AF) in the period 2006-2019. From the accumulated number of early-onset AF cases among current residents, we calculated the prevalence in 2019. The group-level primary care burden was calculated as the total number of annual AF consultations divided by the annual number of AF patients (2014-2018), and individual burden as the mean number of consultations per AF patient per year within the study period. We analysed the distribution of AF consultations between PCP and primary care emergency room (ER) services in total and by sex.

RESULTS

We identified 10 925 Norwegian residents with early-onset AF in 2019 (26.3% women, mean age 48.4 years). The prevalence of early-onset AF was 0.34% (women: 0.19%, men: 0.50%). The early-onset AF population had on average one annual primary care consultation for AF. The individual burden of annual AF consultations varied widely; <1: 66% of women and 54% of men, (1-5]: 25% of women and 36% of men, (5-10]: 6% of women and 8% of men, ≥10: 2% of women and 2% of men. A higher proportion of men (71%) than women (38%) attended both PCP and ER services due to AF.

CONCLUSIONS

The study confirmed a low prevalence of early-onset AF, with substantial sex differences and individual variation in primary healthcare needs. Our results signal a need for a higher resolution with regard to age groups in future research on burden and sex differences in early-onset AF.

Fibrinaloid Microclots and Atrial Fibrillation

Atrial fibrillation (AF) is a comorbidity of a variety of other chronic, inflammatory diseases for which fibrinaloid microclots are a known accompaniment (and in some cases, a cause, with a mechanistic basis). Clots are, of course, a well-known consequence of atrial fibrillation. We here ask the question whether the fibrinaloid microclots seen in plasma or serum may in fact also be a cause of (or contributor to) the development of AF. We consider known 'risk factors' for AF, and in particular, exogenous stimuli such as infection and air pollution by particulates, both of which are known to cause AF. The external accompaniments of both bacterial (lipopolysaccharide and lipoteichoic acids) and viral (SARS-CoV-2 spike protein) infections are known to stimulate fibrinaloid microclots when added in vitro, and fibrinaloid microclots, as with other amyloid proteins, can be cytotoxic, both by inducing hypoxia/reperfusion and by other means. Strokes and thromboembolisms are also common consequences of AF. Consequently, taking a systems approach, we review the considerable evidence in detail, which leads us to suggest that it is likely that microclots may well have an aetiological role in the development of AF. This has significant mechanistic and therapeutic implications.

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.

Current RNA strategies in treating cardiovascular diseases

Cardiovascular disease (CVD) continues to impose a significant global health burden, necessitating the exploration of innovative treatment strategies. Ribonucleic acid (RNA)-based therapeutics have emerged as a promising avenue to address the complex molecular mechanisms underlying CVD pathogenesis. We present a comprehensive review of the current state of RNA therapeutics in the context of CVD, focusing on the diverse modalities that bring about transient or permanent modifications by targeting the different stages of the molecular biology central dogma. Considering the immense potential of RNA therapeutics, we have identified common gene targets that could serve as potential interventions for prevalent Mendelian CVD caused by single gene mutations, as well as acquired CVDs developed over time due to various factors. These gene targets offer opportunities to develop RNA-based treatments tailored to specific genetic and molecular pathways, presenting a novel and precise approach to address the complex pathogenesis of both types of cardiovascular conditions. Additionally, we discuss the challenges and opportunities associated with delivery strategies to achieve targeted delivery of RNA therapeutics to the cardiovascular system. This review highlights the immense potential of RNA-based interventions as a novel and precise approach to combat CVD, paving the way for future advancements in cardiovascular therapeutics.

Pathophysiology of Atrial Fibrillation and Approach to Therapy in Subjects Less than 60 Years Old

Atrial fibrillation (AF) is an arrhythmia that affects the left atrium, cardiac function, and the patients' survival rate. Due to empowered diagnostics, it has become increasingly recognized among young individuals as well, in whom it is influenced by a complex interplay of autoimmune, inflammatory, and electrophysiological mechanisms. Deepening our understanding of these mechanisms could contribute to improving AF management and treatment. Inflammation is a complexly regulated process, with interactions among various immune cell types, signaling molecules, and complement components. Addressing circulating antibodies and designing specific autoantibodies are promising therapeutic options. In cardiomyopathies or channelopathies, the first manifestation could be paroxysmal AF; persistent forms tend not to respond to antiarrhythmic drugs in these conditions. Further research, both in vitro and in vivo, on the use of genomic biotechnology could lead to new therapeutic approaches. Additional triggers that can be encountered in AF patients below 60 years of age are systemic hypertension, overweight, diabetes, and alcohol abuse. The aims of this review are to briefly report evidence from basic science and results of clinical studies that might explain the juvenile burden of the most encountered sustained supraventricular tachyarrhythmias in the general population.

Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance

Many studies have been conducted with the goal of correctly predicting diagnostic status of a disorder using the combination of genomic data and machine learning. It is often hard to judge which components of a study led to better results and whether better reported results represent a true improvement or an uncorrected bias inflating performance. We extracted information about the methods used and other differentiating features in genomic machine learning models. We used these features in linear regressions predicting model performance. We tested for univariate and multivariate associations as well as interactions between features. Of the models reviewed, 46% used feature selection methods that can lead to data leakage. Across our models, the number of hyperparameter optimizations reported, data leakage due to feature selection, model type, and modeling an autoimmune disorder were significantly associated with an increase in reported model performance. We found a significant, negative interaction between data leakage and training size. Our results suggest that methods susceptible to data leakage are prevalent among genomic machine learning research, resulting in inflated reported performance. Best practice guidelines that promote the avoidance and recognition of data leakage may help the field avoid biased results.

Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study

Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.

Air pollution, genetic susceptibility, and the risk of atrial fibrillation: A large prospective cohort study

To date, no study has explored the extent to which genetic susceptibility modifies the effects of air pollutants on the risk of atrial fibrillation (AF). This study was designed to investigate the separate and joint effects of long-term exposure to air pollutants and genetic susceptibility on the risk of AF events. This study included 401,251 participants without AF at baseline from UK Biobank. We constructed a polygenic risk score and categorized it into three categories. Cox proportional hazards models were fitted to assess the separate and joint effects of long-term exposure to air pollutants and genetics on the risk of AF. Additionally, we further evaluated the effect modification of genetic susceptibility. The hazard ratios and corresponding 95% confidence intervals of incident AF for per interquartile range increase in particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5) or 10 µm (PM10), nitrogen dioxide (NO2), and nitrogen oxide (NOx) were 1.044 (1.025, 1.063), 1.063 (1.044, 1.083), 1.061 (1.042, 1.081), and 1.039 (1.023, 1.055), respectively. For the combined effects, participants exposed to high air pollutants levels and high genetic risk had approximately 149.2% (PM2.5), 181.7% (PM10), 170.2% (NO2), and 157.2% (NOx) higher risk of AF compared to those with low air pollutants levels and low genetic risk, respectively. Moreover, the significant additive interactions between PM10 and NO2 and genetic risk on AF risk were observed, with around 16.4% and 35.1% of AF risk could be attributable to the interactive effects. In conclusion, long-term exposure to air pollutants increases the risk of AF, particularly among individuals with high genetic susceptibility.

Association of genetic risk and outcomes in patients with atrial fibrillation: interactions with early rhythm control in the EAST-AFNET4 trial

AIMS

The randomized Early Treatment of Atrial Fibrillation for Stroke Prevention Trial found that early rhythm control reduces cardiovascular events in patients with recently diagnosed atrial fibrillation (AF) compared with usual care. How genetic predisposition to AF and stroke interacts with early rhythm-control therapy is not known.

METHODS AND RESULTS

Array genotyping and imputation for common genetic variants were performed. Polygenic risk scores (PRS) were calculated for AF (PRS-AF) and ischaemic stroke risk (PRS-stroke). The effects of PRS-AF and PRS-stroke on the primary outcome (composite of cardiovascular death, stroke, and hospitalization for acute coronary syndrome or worsening heart failure), its components, and recurrent AF were determined.A total of 1567 of the 2789 trial patients were analysed [793 randomized to early rhythm control; 774 to usual care, median age 71 years (65-75), 704 (44%) women]. Baseline characteristics were similar between randomized groups. Early rhythm control reduced the primary outcome compared with usual care [HR 0.67, 95% CI: (0.53, 0.84), P < 0.001]. The randomized intervention, early rhythm control, did not interact with PRS-AF (interaction P = 0.806) or PRS-stroke (interaction P = 0.765). PRS-AF was associated with recurrent AF [HR 1.08 (01.0, 1.16), P = 0.047]. PRS-stroke showed an association with the primary outcome [HR 1.13 (1.0, 1.27), P = 0.048], driven by more heart failure events [HR 1.23 (1.05-1.43), P = 0.010] without differences in stroke [HR 1.0 (0.75, 1.34), P = 0.973] in this well-anticoagulated cohort. In a replication analysis, PRS-stroke was associated with incident AF [HR 1.16 (1.14, 1.67), P < 0.001] and with incident heart failure in the UK Biobank [HR 1.08 (1.06, 1.10), P < 0.001]. The association with heart failure was weakened when excluding AF patients [HR 1.03 (1.01, 1.05), P = 0.001].

CONCLUSIONS

Early rhythm control is effective across the spectrum of genetic AF and stroke risk. The association between genetic stroke risk and heart failure calls for research to understand the interactions between polygenic risk and treatment.

REGISTRATION

ISRCTN04708680, NCT01288352, EudraCT2010-021258-20, www.easttrial.org.

Population-Level Prevalence of Rare Variants Associated With Atrial Fibrillation and its Impact on Patient Outcomes

BACKGROUND

Whole exome sequencing may identify rare pathogenic/likely pathogenic variants (LPVs) that are linked to atrial fibrillation (AF). The impact of LPVs associated with AF on a population level on outcomes is unclear.

OBJECTIVES

This study sought to examine the association of LPVs with AF and their impact on clinical outcomes using the UK Biobank, a national repository of participants with available whole exome sequencing data.

METHODS

A total of 200,631 individuals in the UK Biobank were studied. Incident and prevalent AF, comorbidities, and outcomes were identified using self-reported assessments and hospital stay operative, and death registry records. LPVs were determined using arrhythmia and cardiomyopathy gene panels with LOFTEE and ClinVar to predict variants of functional significance.

RESULTS

Compared with control subjects, there was a modestly increased prevalence of LPVs among 9,585 patients with AF (2.0% vs 1.7%, respectively; P = 0.01). Among those with prevalent AF at <45 years of age, 4.2% were LPV carriers. LPVs in TTN and PKP2 were associated with AF with adjusted odds ratios of 2.69 (95% CI: 1.57-4.61) and 2.69 (95% CI: 1.54-4.68), respectively. There was no significant difference in combined ischemic stroke, heart failure hospitalization, and mortality among patients who have AF with and without LPVs (25.1% vs 23.8%; P = 0.49). Among participants with AF and available cardiac magnetic resonance imaging data, LPV carriers had lower left ventricular ejection fractions than non-LPV carriers (42% vs 52%; P = 0.027).

CONCLUSIONS

Patients with AF had a modestly increased prevalence of LPVs. Among reference arrhythmia and cardiomyopathy genes, the contribution of rare variants to AF risk at a population level is modest and its impact on outcomes appears to be limited, despite an association of LPVs with reduced left ventricular ejection fraction among patients with AF.

Genetic risk factors for postoperative atrial fibrillation-a nationwide genome-wide association study (GWAS)

Background

Atrial fibrillation (AF) is a major cause of morbidity with a high prevalence among the elderly and has an established genetic disposition. Surgery is a well-known risk factor for AF; however, it is currently not recognized how much common genetic variants influence the postoperative risk. The purpose of this study was to identify Single Nucleotide Polymorphisms associated with postoperative AF.

Methods

The UK Biobank was utilized to conduct a Genome-Wide Association Study (GWAS) to identify variants associated with AF after surgery. An initial discovery GWAS was performed in patients that had undergone surgery with subsequent replication in a unique non-surgical cohort. In the surgical cohort, cases were defined as newly diagnosed AF within 30 days after surgery. The threshold for significance was set at 5 × 10^-8.

Results

After quality control, 144,196 surgical patients with 254,068 SNPs were left for analysis. Two variants (rs17042171 (p = 4.86 × 10^-15) and rs17042081 (p = 7.12 × 10^-15)) near the PITX2-gene reached statistical significance. These variants were replicated in the non-surgical cohort (1.39 × 10^-101 and 1.27 × 10^-93, respectively). Several other loci were significantly associated with AF in the non-surgical cohort.

Conclusion

In this GWAS-analysis of a large national biobank, we identified 2 variants that were significantly associated with postoperative AF. These variants were subsequently replicated in a unique non-surgical cohort. These findings bring new insight in the genetics of postoperative AF and may help identify at-risk patients and guide management.

Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.

The Role of RYR2 in Atrial Fibrillation

Background. Atrial fibrillation (AF) is a common arrhythmia in elderly patients and is associated with increased risk of mortality. The pathogenesis of AF is complex and based on multiple genetic and environmental factors. Genome-wide association studies identified several loci in AF patients, indicating the complex genetic architecture of this disease. In rare cases, familial forms of AF have been described. Today, pathogenic variants in at least 11 different genes are associated with monogenic AF. Case presentation. The 37-year-old male patient presented to our emergency department with AF. At the age of 35, he had already been diagnosed with paroxysmal AF. Additionally, his 34-year-old brother had also been diagnosed with AF as well as nonobstructive hypertrophic cardiomyopathy. Moreover, the patient’s father was diagnosed with AF in his twenties. Transthoracic echocardiography and cardiac MRI revealed a reduced systolic left ventricular ejection without any signs of hypertrophic cardiomyopathy. Genetic testing identified the heterozygous missense variants c.3371C > T, p.(Pro1124Leu) in RYR2 (NM_001035.3) and c.2524C > A, p.(Pro842Thr) in HCN4 (NM_005477.3) in the patient’s and his brother’s DNA. Discussion. This case of familial AF helps to strengthen the role of RYR2 as a disease gene in the context of AF. Although the variant in RYR2 needs to be classified formally as variant of unknown significance, we regard it as probably disease-causing due to the previously published data. As RYR2 has already been identified as a possible target for prevention and therapy of AF, the knowledge of variants in RYR2 might become even more crucial for individual molecular therapies in the future.

Polygenic risk scores for the prediction of cardiometabolic disease

Cardiometabolic diseases contribute more to global morbidity and mortality than any other group of disorders. Polygenic risk scores (PRSs), the weighted summation of individually small-effect genetic variants, represent an advance in our ability to predict the development and complications of cardiometabolic diseases. This article reviews the evidence supporting the use of PRS in seven common cardiometabolic diseases: coronary artery disease (CAD), stroke, hypertension, heart failure and cardiomyopathies, obesity, atrial fibrillation (AF), and type 2 diabetes mellitus (T2DM). Data suggest that PRS for CAD, AF, and T2DM consistently improves prediction when incorporated into existing clinical risk tools. In other areas such as ischaemic stroke and hypertension, clinical application appears premature but emerging evidence suggests that the study of larger and more diverse populations coupled with more granular phenotyping will propel the translation of PRS into practical clinical prediction tools.

Two Novel Functional Mutations in Promoter Region of SCN3B Gene Associated with Atrial Fibrillation

The sodium voltage-gated channel beta subunit 3 (SCN3B) plays a crucial role in electrically excitable cells and conduction tissue in the heart. Some previous studies have established that genetic modification in sodium voltage-channel genes encoding for the cardiac β-subunits, such as SCN1B, SCN2B, SCN3B and SCN4B, can result in atrial fibrillation (AF). In the current study, we identified two rare variants in 5′UTR (NM_018400.4: c.-324C>A, rs976125894 and NM_018400.4: c.-303C>T, rs1284768362) of SCN3B in two unrelated lone AF patients. Our further functional studies discovered that one of them, the A allele of c.-324C>A (rs976125894), can improve transcriptional activity and may raise SCN3B expression levels. The A allele of c.-324C>A (rs976125894) has higher transcriptional activity when it interacts with GATA4, as we confirmed transcription factor GATA4 is a regulator of SCN3B. To the best of our knowledge, the current study is the first to demonstrate that the gain-of-function mutation of SCN3B can produce AF and the first to link a mutation occurring in the non-coding 5′UTR region of SCN3B to lone AF. The work also offers empirical proof that GATA4 is a critical regulator of SCN3B gene regulation. Our findings may serve as an encyclopedia for AF susceptibility variants and can also provide insight into the investigation of the functional mechanisms behind AF variants discovered by genetic methods.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Genetically Based Atrial Fibrillation: Current Considerations for Diagnosis and Management

Atrial fibrillation (AF) is the most common atrial arrhythmia and is subcategorized into numerous clinical phenotypes. Given its heterogeneity, investigations into the genetic mechanisms underlying AF have been pursued in recent decades, with predominant analyses focusing on early onset or lone AF. Linkage analyses, genome wide association studies (GWAS), and single gene analyses have led to the identification of rare and common genetic variants associated with AF risk. Significant overlap with genetic variants implicated in dilated cardiomyopathy syndromes, including truncating variants of the sarcomere protein titin, have been identified through these analyses, in addition to other genes associated with cardiac structure and function. Despite this, widespread utilization of genetic testing in AF remains hindered by the unclear impact of genetic risk identification on clinical outcomes and the high prevalence of variants of unknown significance (VUS). However, genetic testing is a reasonable option for patients with early onset AF and in those with significant family history of arrhythmia. While many knowledge gaps remain, emerging data support genotyping to inform selection of AF therapeutics. In this review we highlight the current understanding of the complex genetic basis of AF and explore the overlap of AF with inherited cardiomyopathy syndromes. We propose a set of criteria for clinical genetic testing in AF patients and outline future steps for the integration of genetics into AF care. This article is protected by copyright. All rights reserved.

Whole-exome sequencing reveals a rare missense variant in DTNA in an Iranian pedigree with early-onset atrial fibrillation

Atrial fibrillation (AF) is a morbid and heritable irregular cardiac rhythm that affects about 2%–3% of the population. Patients with early-onset AF have a strong genetic association with the disease; nonetheless, the exact underlying mechanisms need clarification. We herein present our evaluation of a 2-generation Iranian pedigree with early-onset AF. Whole-exome sequencing was applied to elucidate the genetic predisposition. Direct DNA sequencing was utilized to confirm and screen the variants in the proband and his available family members. The pathogenicity of the identified nucleotide variations was scrutinized via either segregation analysis in the family or in silico predictive software. The comprehensive variant analysis revealed a missense variant (c.G681C, p.E227D, rs1477078144) in the human α-dystrobrevin gene (DTNA), which is rare in genetic databases. Most in silico analyses have predicted this variant as a disease-causing variant, and the variant is co-segregated with the disease phenotype in the family. Previous studies have demonstrated the association between the DTNA gene and left ventricular noncompaction cardiomyopathy. Taken together, we provide the first evidence of an association between a nucleotide variation in the DTNA gene and early-onset AF in an Iranian family. However, the genetic testing of AF in the Iranian population is still limited. This finding not only further confirms the significant role of genetics in the incidence of early-onset AF but also expands the spectrum of the gene variations that lead to AF. Additionally, it may have further implications for the treatment and prevention of AF.

Genome-wide association studies of cardiac electrical phenotypes

The genetic basis of cardiac electrical phenotypes has in the last 25 years been the subject of intense investigation. While in the first years, such efforts were dominated by the study of familial arrhythmia syndromes, in recent years, large consortia of investigators have successfully pursued genome-wide association studies (GWAS) for the identification of single-nucleotide polymorphisms that govern inter-individual variability in electrocardiographic parameters in the general population. We here provide a review of GWAS conducted on cardiac electrical phenotypes in the last 14 years and discuss the implications of these discoveries for our understanding of the genetic basis of disease susceptibility and variability in disease severity. Furthermore, we review functional follow-up studies that have been conducted on GWAS loci associated with cardiac electrical phenotypes and highlight the challenges and opportunities offered by such studies.

New biomarkers from multiomics approaches: improving risk prediction of atrial fibrillation

Atrial fibrillation (AF) is a common cardiac arrhythmia leading to many adverse outcomes and increased mortality. Yet the molecular mechanisms underlying AF remain largely unknown. Recent advances in high-throughput technologies make large-scale molecular profiling possible. In the past decade, multiomics studies of AF have identified a number of potential biomarkers of AF. In this review, we focus on the studies of multiomics profiles with AF risk. We summarize recent advances in the discovery of novel biomarkers for AF through multiomics studies. We also discuss limitations and future directions in risk assessment and discovery of therapeutic targets for AF.

Heritability estimates of atrial fibrillation in Thoroughbred racehorses in Hong Kong and Australia

INTRODUCTION

Atrial fibrillation (AF) is the most common performance-limiting arrhythmia of racehorses. A genetic contribution has been suggested in Standardbred racehorses but has not been investigated in Thoroughbreds. The objective of this study was to determine the heritability of AF in Thoroughbred racehorses.

ANIMALS, MATERIALS AND METHODS

Horses racing between 2007 and 2019 in Hong Kong and Australia that had AF detected postrace via auscultation (n = 463 cases) were compared with five randomly selected racing contemporaries (n = 2,315 controls). The ASReml-R programme was used to fit an animal model to the AF data to estimate heritability using the entire data set and a subset of horses (n = 106 cases) that had electrocardiographic confirmation of AF. Variance components were estimated assuming AF was normally distributed and on the logit-transformed scale. The risk of producing AF-affected offspring was calculated using Fisher's exact test for stallions that sired ≥10 individuals in the case-control population.

RESULTS

Heritability on the underlying scale was 0.064 ± 0.04 (logit animal) and 0.071 ± 0.04 (normal animal) for the entire population and 0.065 ± 0.097 (logit animal) and 0.058 ± 0.11 (normal animal) for electrocardiographic-confirmed AF cases. Of 71 stallions that sired ≥10 individuals, three were more likely to produce affected offspring (odds ratio: 4.05-7.57; p < 0.01). Age (p = 0.991), sex (p = 0.830), and year of birth (p = 0.547) did not contribute to expression.

CONCLUSIONS

Although some stallions were overrepresented amongst affected horses, the heritability of AF in this population of Thoroughbreds was low. Environmental and individual factors contributing to AF development require further investigation.

Genetics of atrial fibrillation-practical applications for clinical management: if not now, when and how?

The prevalence and economic burden of atrial fibrillation (AF) are predicted to more than double over the next few decades. In addition to anticoagulation and treatment of concomitant cardiovascular conditions, early and standardized rhythm control therapy reduces cardiovascular outcomes as compared with a rate control approach, favouring the restoration, and maintenance of sinus rhythm safely. Current therapies for rhythm control of AF include antiarrhythmic drugs (AADs) and catheter ablation (CA). However, response in an individual patient is highly variable with some remaining free of AF for long periods on antiarrhythmic therapy, while others require repeat AF ablation within weeks. The limited success of rhythm control therapy for AF is in part related to incomplete understanding of the pathophysiological mechanisms and our inability to predict responses in individual patients. Thus, a major knowledge gap is predicting which patients with AF are likely to respond to rhythm control approach. Over the last decade, tremendous progress has been made in defining the genetic architecture of AF with the identification of rare mutations in cardiac ion channels, signalling molecules, and myocardial structural proteins associated with familial (early-onset) AF. Conversely, genome-wide association studies have identified common variants at over 100 genetic loci and the development of polygenic risk scores has identified high-risk individuals. Although retrospective studies suggest that response to AADs and CA is modulated in part by common genetic variation, the development of a comprehensive clinical and genetic risk score may enable the translation of genetic data to the bedside care of AF patients. Given the economic impact of the AF epidemic, even small changes in therapeutic efficacy may lead to substantial improvements for patients and health care systems.

Functional genomics and epigenomics of atrial fibrillation

Atrial fibrillation is a progressive cardiac arrhythmia that increases the risk of hospitalization and adverse cardiovascular events. Despite years of study, we still do not have a full comprehension of the molecular mechanism responsible for the disease. The recent implementation of large-scale approaches in both patient samples, population studies and animal models has helped us to broaden our knowledge on the molecular drivers responsible for AF and on the mechanisms behind disease progression. Understanding genomic and epigenomic changes that take place during chronification of AF will prove essential to design novel treatments leading to improved patient care.

Atrial fibrillation and left atrial size and function: a Mendelian randomization study

Atrial fibrillation (AF) patients have enlarged left atria (LA), but prior studies suggested enlarged atria as both cause and consequence of AF. The aim of this study is to investigate the causal association between AF and LA size and function. In the UK Biobank, all individuals with contoured cardiovascular magnetic resonance data were selected. LA maximal volume (LA max), LA minimal volume (LA min), LA stroke volume and LA ejection fraction were measured and indexed to body surface area (BSA). Two-sample Mendelian randomization analyses were performed using 84 of the known genetic variants associated with AF to assess the association with all LA size and function in individuals without prevalent AF. A total of 4274 individuals (mean age 62.0 ± 7.5 years, 53.2% women) were included. Mendelian randomization analyses estimated a causal effect between genetically determined AF and BSA-indexed LA max, LA min, and LA ejection fraction, but not between AF and LA stroke volume. Leave-one-out analyses showed that the causal associations were attenuated after exclusion of rs67249485, located near PITX2 gene. Our results suggest that AF causally increases LA size and decreases LA ejection fraction. The AF risk allele of rs67249485, located near the PITX2 gene, contributes strongly to these associations.

Role of genetics in atrial fibrillation management

Atrial fibrillation (AF) management has significantly improved during the career of professor Crijns. Research was implemented into guidelines and clinical practice. However, despite advances in AF management, large differences between individual treatment responses still exist and the mechanisms underlying initiation and perpetuation of AF are not completely understood. International collaborations have revealed the genetic contribution to AF and steps towards improving AF management are being made. In this short review, the most important paradigms shifts in the field of AF genetics are recognized and the future role of genetics in personalized management of AF is discussed.

Effect of family history of atrial fibrillation on recurrence after atrial fibrillation ablation: A report from the Chinese Atrial Fibrillation Registry Study

BACKGROUND

To evaluate the impact of family history of atrial fibrillation (FAF) on postablation atrial tachyarrhythmia (AT) recurrence.

METHODS

All the 8198 patients undergoing initial AF ablation registered in the Chinese Atrial Fibrillation Registry study were analyzed. FAF was defined as having first-degree relatives diagnosed as AF at age 65 years or younger, and before the time the case in this study was diagnosed. Cox proportional hazards models were used to evaluate the impact of FAF on postablation AT recurrence. Age, sex, body mass index, AF type, history of congestive heart failure, hypertension, diabetes mellitus, prior stroke/transient ischemic attack/systemic embolism, vascular diseases, use of contact force-sensing catheter, and completion of high school were adjusted. The definition of AT recurrence was any documented AF, atrial flutter, or AT lasting more than or equal to 30 s after 3 months blanking period.

RESULTS

After a mean follow-up of 26.2 ± 19.6 months, 318 out of the 645 patients (49.3%) with FAF and 3339 out of the 7553 patients (44.2%) without FAF experienced AT recurrence, corresponding to annual recurrence rates of 22.8% and 20.2%, respectively. Patients with FAF had a significant higher risk of AT recurrence (adjusted hazard ratio 1.129, 95% confidence interval 1.005-1.267) in multivariable analysis. Moreover, FAF had a significant higher impact on AT recurrence in the subgroup of patients diagnosed with AF at age 50 years or younger (p for interaction = .036).

CONCLUSION

FAF is a risk factor for postablation AT recurrence. This is especially true in those with AF diagnosed at 50 years or younger.

Epidemiology of Atrial Fibrillation: Geographic/Ecological Risk Factors, Age, Sex, Genetics

Atrial fibrillation is the most common arrhythmia globally. The global prevalence of atrial fibrillation is positively correlated with the sociodemographic index of different regions. Advancing age, male sex, and Caucasian race are risk factors; female sex is correlated with higher atrial fibrillation mortality worldwide likely owing to thromboembolic risk. African American ethnicity is associated with lower atrial fibrillation risk, same as Asian and Hispanic/Latino ethnicities compared with Caucasians. Atrial fibrillation may be heritable, and more than 100 genetic loci have been identified. A polygenic risk score and clinical risk factors are feasible and effective in risk stratification of incident disease.

Atrial fibrillation-a complex polygenetic disease

Atrial fibrillation (AF) is the most common type of arrhythmia. Epidemiological studies have documented a substantial genetic component. More than 160 genes have been associated with AF during the last decades. Some of these were discovered by classical linkage studies while the majority relies on functional studies or genome-wide association studies. In this review, we will evaluate the genetic basis of AF and the role of both common and rare genetic variants in AF. Rare variants in multiple ion-channel genes as well as gap junction and transcription factor genes have been associated with AF. More recently, a growing body of evidence has implicated structural genes with AF. An increased burden of atrial fibrosis in AF patients compared with non-AF patients has also been reported. These findings challenge our traditional understanding of AF being an electrical disease. We will focus on several quantitative landmark papers, which are transforming our understanding of AF by implicating atrial cardiomyopathies in the pathogenesis. This new AF research field may enable better diagnostics and treatment in the future.

The 2020 Canadian Cardiovascular Society/Canadian Heart Rhythm Society Comprehensive Guidelines for the Management of Atrial Fibrillation

The Canadian Cardiovascular Society (CCS) atrial fibrillation (AF) guidelines program was developed to aid clinicians in the management of these complex patients, as well as to provide direction to policy makers and health care systems regarding related issues. The most recent comprehensive CCS AF guidelines update was published in 2010. Since then, periodic updates were published dealing with rapidly changing areas. However, since 2010 a large number of developments had accumulated in a wide range of areas, motivating the committee to complete a thorough guideline review. The 2020 iteration of the CCS AF guidelines represents a comprehensive renewal that integrates, updates, and replaces the past decade of guidelines, recommendations, and practical tips. It is intended to be used by practicing clinicians across all disciplines who care for patients with AF. The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) system was used to evaluate recommendation strength and the quality of evidence. Areas of focus include: AF classification and definitions, epidemiology, pathophysiology, clinical evaluation, screening and opportunistic AF detection, detection and management of modifiable risk factors, integrated approach to AF management, stroke prevention, arrhythmia management, sex differences, and AF in special populations. Extensive use is made of tables and figures to synthesize important material and present key concepts. This document should be an important aid for knowledge translation and a tool to help improve clinical management of this important and challenging arrhythmia.

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

Generation of patient-specific induced pluripotent stem cells (ZZUSAHi001-A) derived from a familial atrial fibrillation patient carrying KCNA5 c.775G>A mutation

Peripheral blood mononuclear cells (PBMCs) were isolated from a 57-year-old female who was clinically diagnosed as familial atrial fibrillation and were reprogrammed using non-integrative Sendai viral vectors containing reprogramming factors OCT4, SOX2, KLF4 and cMYC. The generated human induced pluripotent stem cell (hiPSC) line, ZZUSAHi001-A, exhibited a normal karyotype, showed robust expression of pluripotency markers and differentiated towards three germ layers in vivo.

The molecular genetic basis of atrial fibrillation

As the most common cardiac arrhythmia, atrial fibrillation (AF) is a major risk factor for stroke, heart failure, and premature death with considerable associated costs. However, no available treatment options have optimal benefit-harm profiles currently, reflecting an incomplete understanding of the biological mechanisms underlying this complex arrhythmia. Recently, molecular epidemiological studies, especially genome-wide association studies, have emphasized the substantial genetic component of AF etiology. A comprehensive mapping of the genetic underpinnings for AF can expand our knowledge of AF mechanism and further facilitate the process of locating novel therapeutics for AF. Here we provide a state-of-the-art review of the molecular genetics of AF incorporating evidence from linkage analysis and candidate gene, as well as genome-wide association studies of common variations and rare copy number variations; potential epigenetic modifications (e.g., DNA methylation, histone modification, and non-coding RNAs) are also involved. We also outline the challenges in mechanism investigation and potential future directions in this article.

The contribution of non-coding regulatory elements to cardiovascular disease

Cardiovascular disease collectively accounts for a quarter of deaths worldwide. Genome-wide association studies across a range of cardiovascular traits and pathologies have highlighted the prevalence of common non-coding genetic variants within candidate loci. Here, we review genetic, epigenomic and molecular approaches to investigate the contribution of non-coding regulatory elements in cardiovascular biology. We then discuss recent insights on the emerging role of non-coding variation in predisposition to cardiovascular disease, with a focus on novel mechanistic examples from functional genomics studies. Lastly, we consider the clinical significance of these findings at present, and some of the current challenges facing the field.

Genetics of Atrial Fibrillation in 2020: GWAS, Genome Sequencing, Polygenic Risk, and Beyond

Atrial fibrillation is a common heart rhythm disorder that leads to an increased risk for stroke and heart failure. Atrial fibrillation is a complex disease with both environmental and genetic risk factors that contribute to the arrhythmia. Over the last decade, rapid progress has been made in identifying the genetic basis for this common condition. In this review, we provide an overview of the primary types of genetic analyses performed for atrial fibrillation, including linkage studies, genome-wide association studies, and studies of rare coding variation. With these results in mind, we aim to highlighting the existing knowledge gaps and future directions for atrial fibrillation genetics research.

Unraveling the Genetics Behind Equid Cardiac Disease

There have been some advances in understanding the genetic contribution to ventricular septal defects in Arabians, sudden death in racehorses, and atrial fibrillation in racehorses. No genetic analyses have been published for aortic rupture in Friesians or atrioventricular block in donkeys despite strong evidence for a genetic cause. To date, no genetic mutation has been identified for any equid cardiac disease. With the advancement of genetic tools and resources, we are moving closer to discoveries that may explain the heritable basis of inherited equid cardiac disease.

The Genetic Puzzle of Familial Atrial Fibrillation

Atrial fibrillation (AF) is the most common clinical tachyarrhythmia. In Europe, AF is expected to reach a prevalence of 18 million by 2060. This estimate will increase hospitalization for AF to 4 million and 120 million outpatient visits. Besides being an independent risk factor for mortality, AF is also associated with an increased risk of morbidities. Although there are many well-defined risk factors for developing AF, no identifiable risk factors or cardiac pathology is seen in up to 30% of the cases. The heritability of AF has been investigated in depth since the first report of familial atrial fibrillation (FAF) in 1936. Despite the limited value of animal models, the advances in molecular genetics enabled identification of many common and rare variants related to FAF. The importance of AF heritability originates from the high prevalence of lone AF and the lack of clear understanding of the underlying pathophysiology. A better understanding of FAF will facilitate early identification of people at high risk of developing FAF and subsequent development of more effective management options. In this review, we reviewed FAF epidemiological studies, identified common and rare variants, and discussed their clinical implications and contributions to developing new personalized therapeutic strategies.

Predicting atrial fibrillation using a combination of genetic risk score and clinical risk factors

BACKGROUND

Atrial fibrillation (AF) has a genetic basis, and environmental factors can modify its actual pathogenesis.

OBJECTIVE

The purpose of this study was to construct a combined risk assessment method including both genetic and clinical factors in the Japanese population.

METHODS

We screened a cohort of 540 AF patients and 520 non-AF controls for single nucleotide polymorphisms (SNPs) previously associated with AF by genome-wide association studies. The most strongly associated SNPs after propensity score analysis were then used to calculate a weighted genetic risk score (WGRS). We also enrolled 1018 non-AF Japanese subjects as a validation cohort and monitored AF emergence over several years. Finally, we constructed a logistic model for AF prediction combining WGRS and clinical risk factors.

RESULTS

We identified 5 SNPs (in PRRX1, ZFHX3, PITX2, HAND2, and NEURL1) associated with AF after Bonferroni correction. There was a 4.92-fold difference in AF risk between the highest and lowest WGRS calculated using these 5 SNPs (P = 2.32 × 10^-10). Receiver operating characteristic analysis of WGRS yielded an area under the curve (AUC) of 0.73 for the screening cohort and 0.72 for the validation cohort. The predictive logistic model constructed using a combination of WGRS and AF clinical risk factors (age, body mass index, sex, and hypertension) demonstrated better discrimination of AF than WGRS alone (AUC = 0.84; sensitivity 75.4%; specificity 80.2%).

CONCLUSION

This novel predictive model of combined AF-associated SNPs and known clinical risk factors can accurately stratify AF risk in the Japanese population.

Pedigree analysis of atrial fibrillation in Irish wolfhounds supports a high heritability with a dominant mode of inheritance

Background

Atrial fibrillation (AF) is the most common arrhythmia in dogs. The Irish Wolfhound breed has a high prevalence of AF making them an ideal breed to investigate possible genetic contributions to this disease. The aim of this study was to perform a heritability analysis in North American Irish Wolfhounds using phenotype data from cardiac screenings performed between 2000 and 2019 in order to determine how much of this disease can be attributed to genetics compared to environmental causes. The second aim was to determine the disease mode of inheritance to help inform prevention and breeding practices.

Results

There were 327 Irish Wolfhounds diagnosed with AF and 136 Irish Wolfhounds over 8 years of age without AF. The estimated mean (95% confidence interval) heritability of AF in Irish Wolfhounds was 0.69 (0.50–0.86). The pedigree was consistent with a dominant mode of inheritance.

Conclusion

Results of this study indicate a strong genetic contribution to AF in Irish Wolfhounds and suggest that future research to identify causative genetic mutations is warranted.

Characteristics of Atrial Fibrillation Patients with a Family History of Atrial Fibrillation

Background

Family history has been shown to be associated with increased risk of atrial fibrillation (AF). However, the specific AF characteristics that travel with a family history have not yet been elucidated. The purpose of this study was to determine whether a family history of AF is associated with specific patient characteristics in a worldwide, remote cohort.

Methods

From the Health eHeart Study, an internet-based prospective cohort, we performed a cross-sectional analysis of AF participants who reported their family history and completed questionnaires regarding their medical conditions and AF symptoms. We assessed demographics, cardiovascular comorbidities, and AF symptom characteristics in AF participants with and without a family history of AF.

Results

In multivariable analysis of 5,884 participants with AF (mean age 59.9 ± 14.5, 59% male, 92% white), female sex (odds ratio [OR]=1.35, 95% CI, 1.17-1.54, p<0.0001) and birth in the U.S. (OR=2.54, 95% CI, 2.12-3.05, p<0.0001) were independently associated with having a family history of AF. Having a family history of AF was also more commonly associated with symptoms of shortness of breath (OR=1.40, 95% CI, 1.07-1.82, p=0.014), chest pain, pressure, or discomfort (OR=1.95, 95% CI, 1.22-3.13, p=0.0052), and feeling generally "off" about oneself (OR=1.84, 95% CI, 1.27-2.67, p=0.0013).

Conclusions

Patients with a family history of AF are more likely to be female, be US-born, and experience symptoms of AF, suggesting underlying mechanistic differences between those with and without family history of AF.

Atrial Fibrillation Genetics Update: Toward Clinical Implementation

Atrial fibrillation (AF) is the most common heart rhythm disorder worldwide and may have serious cardiovascular health consequences. AF is associated with increased risk of stroke, dementia, heart failure, and death. There are several known robust, clinical risk predictors for AF, such as male sex, increasing age, and hypertension; however, during the last couple of decades, a substantive genetic component has also been established. Over the last 10 years, the discovery of novel AF-related genetic variants has accelerated, increasing our understanding of mechanisms behind AF. Current studies are focusing on mapping the polygenic structure of AF, improving risk prediction, therapeutic development, and patient-specific management. Nevertheless, it is still difficult for clinicians to interpret the role of genetics in AF prediction and management. Here, we provide an overview of relevant topics within the genetics of AF and attempt to provide some guidance on how to interpret genetic advances and their implementation into clinical decision-making.