Monogenic and Polygenic Contributions to Atrial Fibrillation Risk: Results From a National Biobank

2024 HRS expert consensus statement on arrhythmias in the athlete: Evaluation, treatment, and return to play

Youth and adult participation in sports continues to increase, and athletes may be diagnosed with potentially arrhythmogenic cardiac conditions. This international multidisciplinary document is intended to guide electrophysiologists, sports cardiologists, and associated health care team members in the diagnosis, treatment, and management of arrhythmic conditions in the athlete with the goal of facilitating return to sport and avoiding the harm caused by restriction. Expert, disease-specific risk assessment in the context of athlete symptoms and diagnoses is emphasized throughout the document. After appropriate risk assessment, management of arrhythmias geared toward return to play when possible is addressed. Other topics include shared decision-making and emergency action planning. The goal of this document is to provide evidence-based recommendations impacting all areas in the care of athletes with arrhythmic conditions. Areas in need of further study are also discussed.

Clinical Genetic Testing for Atrial Fibrillation: Are We There Yet?

Important progress has been made toward unravelling the complex genetics underlying atrial fibrillation (AF). Initial studies were aimed to identify monogenic causes; however, it has become increasingly clear that the most common predisposing genetic substrate for AF is polygenic. Despite intensive investigations, there is robust evidence for rare variants for only a limited number of genes and cases. Although the current yield for genetic testing in early onset AF might be modest, there is an increasing appreciation that genetic culprits for potentially life-threatening ventricular cardiomyopathies and channelopathies might initially present with AF. The potential clinical significance of this recognition is highlighted by evidence that suggests that identification of a pathogenic or likely pathogenic rare variant in a patient with early onset AF is associated with an increased risk of death. These findings suggest that it might be warranted to screen patients with early onset AF for these potentially more sinister cardiac conditions. Beyond facilitating the early identification of genetic culprits associated with potentially malignant phenotypes, insight into underlying AF genetic substrates might improve the selection of patients for existing therapies and guide the development of novel ones. Herein, we review the evidence that links genetic factors to AF, then discuss an approach to using genetic testing for early onset AF patients in the present context, and finally consider the potential value of genetic testing in the foreseeable future. Although further work might be necessary before recommending uniform integration of genetic testing in cases of early onset AF, ongoing research increasingly highlights its potential contributions to clinical care.

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.

[Genetic basis of atrial fibrillation-on the road to precision medicine]

Atrial fibrillation (AF) is the most common cardiac arrhythmia and has complex genetic underpinnings. Despite advancements in treatment, mortality of AF patients remains high. This review discusses the genetic basis of AF and its implications for diagnosis and therapy. Although AF pathology has long been known to include a hereditary component, the first genes associated with AF were not identified until the early 2000s. Subsequent research with genome-wide association studies (GWAS) has implicated other genes and numerous genetic variants in AF. These studies have revealed nearly 140 different regions in the DNA with genome-wide significance associated with AF. In addition to common variants, rare variants with large effects have also been identified. The integration of these genetic findings into clinical practice holds promise for improving AF diagnosis and treatment, moving us closer to precision medicine. However, challenges remain, including the need for more diverse genetic data of non-European ancestry and improved genetic analyses of responses to AF therapy.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation.

METHODS

A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate.

STRUCTURE

Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Patients With Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation.

METHODS

A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate.

STRUCTURE

Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

Rare-variant and polygenic analyses of amyotrophic lateral sclerosis in the French-Canadian genome

PURPOSE

The genetic etiology of amyotrophic lateral sclerosis (ALS) includes few rare, large-effect variants and potentially many common, small-effect variants per case. The genetic risk liability for ALS might require a threshold comprised of a certain amount of variants. Here, we tested the degree to which risk for ALS was affected by rare variants in ALS genes, polygenic risk score, or both.

METHODS

335 ALS cases and 356 controls from Québec, Canada were concurrently tested by microarray genotyping and targeted sequencing of ALS genes known at the time of study inception. ALS genome-wide association studies summary statistics were used to estimate an ALS polygenic risk score (PRS). Cases and controls were subdivided into rare-variant heterozygotes and non-heterozygotes.

RESULTS

Risk for ALS was significantly associated with PRS and rare variants independently in a logistic regression model. Although ALS PRS predicted a small amount of ALS risk overall, the effect was most pronounced between ALS cases and controls that were not heterozygous for a rare variant in the ALS genes surveyed.

CONCLUSION

Both PRS and rare variants in ALS genes impact risk for ALS. PRS for ALS is most informative when rare variants are not observed in ALS genes.

Genetic Atrial Cardiomyopathies: Common Features, Specific Differences, and Broader Relevance to Understanding Atrial Cardiomyopathy

Atrial cardiomyopathy is a condition that causes electrical and contractile dysfunction of the atria, often along with structural and functional changes. Atrial cardiomyopathy most commonly occurs in conjunction with ventricular dysfunction, in which case it is difficult to discern the atrial features that are secondary to ventricular dysfunction from those that arise as a result of primary atrial abnormalities. Isolated atrial cardiomyopathy (atrial-selective cardiomyopathy [ASCM], with minimal or no ventricular function disturbance) is relatively uncommon and has most frequently been reported in association with deleterious rare genetic variants. The genes involved can affect proteins responsible for various biological functions, not necessarily limited to the heart but also involving extracardiac tissues. Atrial enlargement and atrial fibrillation are common complications of ASCM and are often the predominant clinical features. Despite progress in identifying disease-causing rare variants, an overarching understanding and approach to the molecular pathogenesis, phenotypic spectrum, and treatment of genetic ASCM is still lacking. In this review, we aim to analyze the literature relevant to genetic ASCM to understand the key features of this rather rare condition, as well as to identify distinct characteristics of ASCM and its arrhythmic complications that are related to specific genotypes. We outline the insights that have been gained using basic research models of genetic ASCM in vitro and in vivo and correlate these with patient outcomes. Finally, we provide suggestions for the future investigation of patients with genetic ASCM and improvements to basic scientific models and systems. Overall, a better understanding of the genetic underpinnings of ASCM will not only provide a better understanding of this condition but also promises to clarify our appreciation of the more commonly occurring forms of atrial cardiomyopathy associated with ventricular dysfunction.

Exploring the complex spectrum of dominance and recessiveness in genetic cardiomyopathies

Discrete categorization of Mendelian disease genes into dominant and recessive models often oversimplifies their underlying genetic architecture. Cardiomyopathies (CMs) are genetic diseases with complex etiologies for which an increasing number of recessive associations have recently been proposed. Here, we comprehensively analyze all published evidence pertaining to biallelic variation associated with CM phenotypes to identify high-confidence recessive genes and explore the spectrum of monoallelic and biallelic variant effects in established recessive and dominant disease genes. We classify 18 genes with robust recessive association with CMs, largely characterized by dilated phenotypes, early disease onset and severe outcomes. Several of these genes have monoallelic association with disease outcomes and cardiac traits in the UK Biobank, including LMOD2 and ALPK3 with dilated and hypertrophic CM, respectively. Our data provide insights into the complex spectrum of dominance and recessiveness in genetic heart disease and demonstrate how such approaches enable the discovery of unexplored genetic associations.

Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum

Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, that affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (p < 5×10-8). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes (MYBPC3, BAG3), as well as regulators of lipoprotein (LPL) and glucose metabolism (GIPR, GLP1R), and are enriched in cardiac, muscle, nerve, and vascular tissues, as well as myocyte and adipocyte cell types. Gene burden studies across three biobanks (PMBB, UKB, AOU) including 27,208 individuals with HF and 349,126 without uncover exome-wide significant (p < 3.15×10-6) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN, MYBPC3, FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, and is lower than heritability attributable to common variants (4.3%, 95% CI 3.9-4.7%) which is more diffusely spread throughout the genome. Finally, we demonstrate that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. These findings suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.

Decreased FAM13B Expression Increases Atrial Fibrillation Susceptibility by Regulating Sodium Current and Calcium Handling

A specific genetic variant associated with atrial fibrillation risk, rs17171731, was identified as a regulatory variant responsible for controlling FAM13B expression. The atrial fibrillation risk allele decreases FAM13B expression, whose knockdown alters the expression of many genes in stem cell-derived cardiomyocytes, including SCN2B, and led to pro-arrhythmogenic changes in the late sodium current and Ca2+ cycling. Fam13b knockout mice had increased P-wave and QT interval duration and were more susceptible to pacing-induced arrhythmias vs control mice. FAM13B expression, its regulation, and downstream effects are potential targets for investigation of patient-specific therapeutics.

Changes of ubiquitylated proteins in atrial fibrillation associated with heart valve disease: proteomics in human left atrial appendage tissue

Background

Correlations between posttranslational modifications and atrial fibrillation (AF) have been demonstrated in recent studies. However, it is still unclear whether and how ubiquitylated proteins relate to AF in the left atrial appendage of patients with AF and valvular heart disease.

Methods

Through LC-MS/MS analyses, we performed a study on tissues from eighteen subjects (9 with sinus rhythm and 9 with AF) who underwent cardiac valvular surgery. Specifically, we explored the ubiquitination profiles of left atrial appendage samples.

Results

In summary, after the quantification ratios for the upregulated and downregulated ubiquitination cutoff values were set at >1.5 and <1:1.5, respectively, a total of 271 sites in 162 proteins exhibiting upregulated ubiquitination and 467 sites in 156 proteins exhibiting downregulated ubiquitination were identified. The ubiquitylated proteins in the AF samples were enriched in proteins associated with ribosomes, hypertrophic cardiomyopathy (HCM), glycolysis, and endocytosis.

Conclusions

Our findings can be used to clarify differences in the ubiquitination levels of ribosome-related and HCM-related proteins, especially titin (TTN) and myosin heavy chain 6 (MYH6), in patients with AF, and therefore, regulating ubiquitination may be a feasible strategy for AF.

Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation

Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.

Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-Lead Electrocardiograms

BACKGROUND

Artificial intelligence (AI) models applied to 12-lead ECG waveforms can predict atrial fibrillation (AF), a heritable and morbid arrhythmia. However, the factors forming the basis of risk predictions from AI models are usually not well understood. We hypothesized that there might be a genetic basis for an AI algorithm for predicting the 5-year risk of new-onset AF using 12-lead ECGs (ECG-AI)-based risk estimates.

METHODS

We applied a validated ECG-AI model for predicting incident AF to ECGs from 39 986 UK Biobank participants without AF. We then performed a genome-wide association study (GWAS) of the predicted AF risk and compared it with an AF GWAS and a GWAS of risk estimates from a clinical variable model.

RESULTS

In the ECG-AI GWAS, we identified 3 signals (P<5×10-8) at established AF susceptibility loci marked by the sarcomeric gene TTN and sodium channel genes SCN5A and SCN10A. We also identified 2 novel loci near the genes VGLL2 and EXT1. In contrast, the clinical variable model prediction GWAS indicated a different genetic profile. In genetic correlation analysis, the prediction from the ECG-AI model was estimated to have a higher correlation with AF than that from the clinical variable model.

CONCLUSIONS

Predicted AF risk from an ECG-AI model is influenced by genetic variation implicating sarcomeric, ion channel and body height pathways. ECG-AI models may identify individuals at risk for disease via specific biological pathways.

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 Basis of Early Onset Atrial Fibrillation in Patients without Risk Factors

BACKGROUND

Atrial fibrillation (AF) is the most common arrhythmia and typically occurs in elderly patients with other cardiovascular and extracardiac diseases. However, up to 15% of AF develops without any related risk factors. Recently, the role of genetic factors has been highlighted in this particular form of AF.

AIMS

The aims of this study were to determine the prevalence of pathogenic variants in early-onset AF in patients without known disease-related risk factors and to identify any structural cardiac abnormalities in these patients.

MATERIALS AND METHODS

We conducted exome sequencing and interpretation in 54 risk factor-free early-onset AF patients and further validated our findings in a similar AF patient cohort from the UK Biobank.

RESULTS

Pathogenic/likely pathogenic variants were found in 13/54 (24%) patients. The variants were identified in cardiomyopathy-related and not arrhythmia-related genes. The majority of the identified variants were TTN gene truncating variants (TTNtvs) (9/13 (69%) patients). We also observed two TTNtvs founder variants in the analysed population-c.13696C>T p.(Gln4566Ter) and c.82240C>T p.(Arg27414Ter). Pathogenic/likely pathogenic variants were found in 9/107 (8%) individuals from an independent similar AF patient cohort from the UK Biobank. In correspondence with our Latvian patients, only variants in cardiomyopathy-associated genes were identified. In five (38%) of the thirteen Latvian patients with pathogenic/likely pathogenic variants, dilation of one or both ventricles was identified on a follow-up cardiac magnetic resonance scan.

CONCLUSIONS

We observed a high prevalence of pathogenic/likely pathogenic variants in cardiomyopathy-associated genes in patients with risk factor-free early-onset AF. Moreover, our follow-up imaging data indicate that these types of patients are at risk of developing ventricular dilation. Furthermore, we identified two TTNtvs founder variants in our Latvian study population.

Genetics of atrial fibrillation

PURPOSE OF REVIEW

Atrial fibrillation is the most common cardiac arrhythmia worldwide. There is considerable interest in better understanding the molecular genetics and biology of atrial fibrillation to inform the development of new therapies and improve clinical management. This review summarizes recent advances in our understanding of the genetic basis of atrial fibrillation and new efforts to utilize genetics to inform clinical management.

RECENT FINDINGS

Genome-wide association studies in diverse populations have increased the number of genetic loci associated with atrial fibrillation and its specific subtypes. Large-scale biobanks with deep phenotyping have provided invaluable data to study the impact of both common and rare variants on atrial fibrillation, susceptibility, and prognosis. Polygenic risk scores help improve individual atrial fibrillation risk stratification and prognostication.

SUMMARY

Our understanding of atrial fibrillation genetics is rapidly improving with larger and more diverse genome-wide association studies. Translating genetic discoveries into molecular pathways and new therapeutic targets remains a bottleneck in the development of new therapies for atrial fibrillation. Genetic risk scores have shown early promise in improving atrial fibrillation risk stratification; however, their broader utility for the general population remains unclear.

A polygenic risk score predicts atrial fibrillation in cardiovascular disease

AIMS

Interest in targeted screening programmes for atrial fibrillation (AF) has increased, yet the role of genetics in identifying patients at highest risk of developing AF is unclear.

METHODS AND RESULTS

A total of 36,662 subjects without prior AF were analyzed from four TIMI trials. Subjects were divided into quintiles using a validated polygenic risk score (PRS) for AF. Clinical risk for AF was calculated using the CHARGE-AF model. Kaplan-Meier event rates, adjusted hazard ratios (HRs), C-indices, and net reclassification improvement were used to determine if the addition of the PRS improved prediction compared with clinical risk and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Over 2.3 years, 1018 new AF cases developed. AF PRS predicted a significant risk gradient for AF with a 40% increased risk per 1-SD increase in PRS [HR: 1.40 (1.32-1.49); P < 0.001]. Those with high AF PRS (top 20%) were more than two-fold more likely to develop AF [HR 2.45 (1.99-3.03), P < 0.001] compared with low PRS (bottom 20%). Furthermore, PRS provided an additional gradient of risk stratification on top of the CHARGE-AF clinical risk score, ranging from a 3-year incidence of 1.3% in patients with low clinical and genetic risk to 8.7% in patients with high clinical and genetic risk. The subgroup of patients with high clinical risk, high PRS, and elevated NT-proBNP had an AF risk of 16.7% over 3 years. The C-index with the CHARGE-AF clinical risk score alone was 0.65, which improved to 0.67 (P < 0.001) with the addition of NT-proBNP, and increased further to 0.70 (P < 0.001) with the addition of the PRS.

CONCLUSION

In patients with cardiovascular conditions, AF PRS is a strong independent predictor of incident AF that provides complementary predictive value when added to a validated clinical risk score and NT-proBNP.

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.

Association of Vascular Risk Factors and Genetic Factors With Penetrance of Variants Causing Monogenic Stroke

Importance

It is uncertain whether typical variants causing monogenic stroke are associated with cerebrovascular disease in the general population and why the phenotype of these variants varies so widely.

Objective

To determine the frequency of pathogenic variants in the 3 most common monogenic cerebral small vessel diseases (cSVD) and their associations with prevalent and incident stroke and dementia.

Design, Setting, and Participants

This cohort study is a multicenter population-based study of data from UK Biobank participants recruited in 2006 through 2010, with the latest follow-up in September 2021. A total of 9.2 million individuals aged 40 to 69 years who lived in the United Kingdom were invited to join UK Biobank, of whom 5.5% participated in the baseline assessment. Participants eligible for our study (n = 454 756, excluding 48 569 with incomplete data) had whole-exome sequencing and available data pertaining to lacunar stroke-related diseases, namely stroke, dementia, migraine, and epilepsy.

Exposures

NOTCH3, HTRA1, and COL4A1/2 pathogenic variants in monogenic stroke; Framingham cardiovascular risk; and ischemic stroke polygenic risk.

Main Outcomes and Measures

Primary outcomes were prevalent and incident stroke and dementia. Odds ratios (ORs) and hazard ratios (HRs) were adjusted for age, sex, ethnicity, exome sequencing batch, and top 10 genetic principal components.

Results

Of the 454 756 participants (208 027 [45.8%] men; mean [SD] age, 56.5 [8.1] years), 973 participants carried NOTCH3 variants, 546 carried HTRA1 variants, and 336 carried COL4A1/2 variants. Variant carriers were at least 66% more likely to have had stroke. NOTCH3 carriers had increased vascular dementia risk (OR, 5.42; 95% CI, 3.11-8.74), HTRA1 carriers an increased all-cause dementia risk (OR, 2.17; 95% CI, 1.28-3.41), and COL4A1/2 carriers an increased intracerebral hemorrhage risk (OR, 3.56; 95% CI, 1.34-7.53). NOTCH3 variants were associated with incident ischemic stroke and vascular dementia. NOTCH3 and HTRA1 variants were associated with magnetic resonance imaging markers of cSVD. Cardiovascular risk burden was associated with increased stroke risk in NOTCH3 and HTRA1 carriers. Variant location was also associated with risk.

Conclusions and Relevance

In this cohort study, pathogenic variants associated with rare monogenic stroke were more common than expected in the general population and associated with stroke and dementia. Cardiovascular risk burden is associated with the penetrance of such variants. Our results support the hypothesis that cardiovascular risk factor control may improve disease prognosis in individuals with monogenic cSVD variants. This lays the foundation for future studies to evaluate the effect of early identification before symptom onset on mitigating stroke and dementia risk.

Genetics of congenital arrhythmia syndromes: the challenge of variant interpretation

Congenital arrhythmia syndromes are rare genetic disorders that can cause a high risk of sudden cardiac death. Expert panels have affirmed 15 genes that are linked to congenital arrhythmias. These genes mostly encode cardiac ion channel proteins or associated regulatory proteins that generate the cardiac action potential. Common genetic variation modulates the risk of rare variants and partially explains the incomplete penetrance of these disorders. As genetic testing becomes more prevalent, a major challenge is that most detected variants are annotated as variants of uncertain significance. This review will highlight emerging methods that are refining our understanding of arrhythmia genetics, including phenotype risk scores, large cohorts, in vitro functional assays, structural models, and computational predictions.

A novel murine model of atrial fibrillation by diphtheria toxin-induced injury

The treatment of atrial fibrillation (AF) continues to be a significant clinical challenge. While genome-wide association studies (GWAS) are beginning to identify AF susceptibility genes (Gudbjartsson et al., Nature, 2007, 448, 353-357; Choi et al., Circ. Res., 2020, 126, 200-209; van Ouwerkerk et al., Circ. Res., 2022, 127, 229-243), non-genetic risk factors including physical, chemical, and biological environments remain the major contributors to the development of AF. However, little is known regarding how non-genetic risk factors promote the pathogenesis of AF (Weiss et al., Heart Rhythm, 2016, 13, 1868-1877; Chakraborty et al., Heart Rhythm, 2020, 17, 1,398-1,404; Nattel et al., Circ. Res., 2020, 127, 51-72). This is, in part, due to the lack of a robust and reliable animal model induced by non-genetic factors. The currently available models using rapid pacing protocols fail to generate a stable AF phenotype in rodent models, often requiring additional genetic modifications that introduce potential sources of bias (Schüttler et al., Circ. Res., 2020, 127, 91-110). Here, we report a novel murine model of AF using an inducible and tissue-specific activation of diphtheria toxin (DT)-mediated cellular injury system. By the tissue-specific and inducible expression of human HB-EGF in atrial myocytes, we developed a reliable, robust and scalable murine model of AF that is triggered by a non-genetic inducer without the need for AF susceptibility gene mutations.

Habitual fish oil supplementation and the risk of incident atrial fibrillation: findings from a large prospective longitudinal cohort study

AIMS

Mixed effects of fish oil supplementation on the risks of atrial fibrillation (AF) were observed in several large-scale randomized controlled trials. Whether this relationship would be modified by genetic AF risk, baseline cardiovascular disease (CVD) status and background oily fish consumption are unknown.

METHODS AND RESULTS

We included 468 665 participants without AF at baseline from the UK Biobank cohort. The association between fish oil supplementation and the AF risk was assessed in the study cohort and in several subgroups, including genetic AF predisposition, baseline CVD status, and background oily fish consumption. During a median follow-up of 11.1 years, fish oil users had a higher rate of incident AF (6.2% vs. 5.2%, adjusted hazard ratio of 1.10, and 95% confidence interval of 1.07, 1.13). Compared with non-users, fish oil users had a higher rate of incident AF in the low (3.7% vs. 3.0%, P= 0.02), intermediate (5.8% vs. 4.8%, P &lt; 0.0001), and high (9.8% vs. 8.1%, P &lt; 0.0001) genetic AF risk groups. In participants without CVD at baseline, fish oil users had a higher rate of incident AF (5.3% vs. 4.1%, P &lt; 0.0001), which was not observed in participants with CVD at baseline (11.6% vs. 11.1%, P = 0.56), with significant interaction (P-interaction &lt; 0.0001). The association between fish oil supplementation and the AF risk was not modified by background oily fish consumption (P-interaction = 0.62).

CONCLUSION

Habitual fish oil supplementation was associated with the risk of incident AF, regardless of genetic AF predisposition and background oily fish consumption. This association was observed only in individuals without CVD at baseline.

Hidden Risk: Arrhythmogenic Genes in the General Population

The past 2 decades have seen the development of large-scale DNA biobanks associated with phenotypic information of the general population. Examples of these efforts are the UK Biobank, BioVU at Vanderbilt and MyCode. These repositories were designed to generate information to enable a precision medicine approach to diagnose, prevent, and treat human disease.

Endophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes

Accurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) provide evidence for variant pathogenicity. Effect sizes are associated with pathogenic ClinVar assertions (P < 0.001 for each trait) and discriminate pathogenic from non-pathogenic variants (area under the curve 0.82-0.84 across endophenotypes). An effect size threshold of ≥ 0.5 times the endophenotype standard deviation nominates up to 35% of rare variants of uncertain significance or not in ClinVar in disease susceptibility genes with pathogenic potential. We propose that variant associations with quantitative endophenotypes for monogenic diseases can provide evidence supporting pathogenicity.

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.

Loss-of-Function FLNC Variants Are Associated With Arrhythmogenic Cardiomyopathy Phenotypes When Identified Through Exome Sequencing of a General Clinical Population

BACKGROUND

The FLNC gene has recently garnered attention as a likely cause of arrhythmogenic cardiomyopathy, which is considered an actionable genetic condition. However, the association with disease in an unselected clinical population is unknown. We hypothesized that individuals with loss-of-function variants in FLNC (FLNC_LOF) would have increased odds for arrhythmogenic cardiomyopathy-associated phenotypes versus variant-negative controls in the Geisinger MyCode cohort.

METHODS

We identified rare, putative FLNC_LOF among 171 948 individuals with exome sequencing linked to health records. Associations with arrhythmogenic cardiomyopathy phenotypes from available diagnoses and cardiac evaluations were investigated.

RESULTS

Sixty individuals (0.03%; median age 58 years [47-70 interquartile range], 43% male) harbored 27 unique FLNC_LOF. These individuals had significantly increased odds ratios for dilated cardiomyopathy (odds ratio, 4.9 [95% CI, 2.6-7.6]; P<0.001), supraventricular tachycardia (odds ratio, 3.2 [95% CI, 1.1-5.6]; P=0.048), and left-dominant arrhythmogenic cardiomyopathy (odds ratio, 4.2 [95% CI, 1.4-7.9]; P=0.03). Echocardiography revealed reduced left ventricular ejection fraction (52±13% versus 57±9%; P=0.001) associated with FLNC_LOF. Overall, at least 9% of FLNC_LOF patients demonstrated evidence of penetrant disease.

CONCLUSIONS

FLNC_LOF variants are associated with increased odds of ventricular arrhythmia and dysfunction in an unselected clinical population. These findings support genomic screening of FLNC for actionable secondary findings.

Management of Atrial Fibrillation Across the Spectrum of Heart Failure With Preserved and Reduced Ejection Fraction

Atrial fibrillation (AF) is the most common arrhythmia among patients with heart failure (HF), and HF is the most common cause of death for patients presenting with clinical AF. AF is frequently associated with pathological atrial myocardial dysfunction and remodeling, a triad that has been called atrial myopathy. AF can be the cause or consequence of clinical HF, and the directionality varies between individual patients and across the spectrum of HF. Although initial trials suggested no advantage for a systematic rhythm control strategy in HF with reduced ejection fraction, recent data suggest that select patients may benefit from attempts to maintain sinus rhythm with catheter ablation. Preliminary data also show a close relationship among AF, left atrial myopathy, mitral regurgitation, and HF with preserved ejection, with potential clinical benefits to catheter ablation therapy. The modern management of AF in HF also requires consideration of the degree of atrial myopathy and chronicity of AF, in addition to the pathogenesis and phenotype of the underlying left ventricular HF. In this review, we summarize the contemporary management of AF and provide practical guidance and areas in need of future investigation.

Hub Genes Identification, Small Molecule Compounds Prediction for Atrial Fibrillation and Diagnostic Model Construction Based on XGBoost Algorithm

Background

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and engenders significant global health care burden. The underlying mechanisms of AF is remained to be revealed and current treatment options for AF have limitations. Besides, a detection system can help identify those at risk of developing AF and will enable personalized management.

Materials and Methods

In this study, we utilized the robust rank aggregation method to integrate six AF microarray datasets from the Gene Expression Omnibus database, and identified a set of differentially expressed genes between patients with AF and controls. Potential compounds were identified by mining the Connectivity Map database. Functional modules and closely-interacted clusters were identified using weighted gene co-expression network analysis and protein–protein interaction network, respectively. The overlapped hub genes were further filtered. Subsequent analyses were performed to analyze the function, biological features, and regulatory networks. Moreover, a reliable Machine Learning-based diagnostic model was constructed and visualized to clarify the diagnostic features of these genes.

Results

A total of 156 upregulated and 34 downregulated genes were identified, some of which had not been previously investigated. We showed that mitogen-activated protein kinase and epidermal growth factor receptor inhibitors were likely to mitigate AF based on Connectivity Map analysis. Four genes, including CXCL12, LTBP1, LOXL1, and IGFBP3, were identified as hub genes. CXCL12 was shown to play an important role in regulation of local inflammatory response and immune cell infiltration. Regulation of CXCL12 expression in AF was analyzed by constructing a transcription factor-miRNA-mRNA network. The Machine Learning-based diagnostic model generated in this study showed good efficacy and reliability.

Conclusion

Key genes involving in the pathogenesis of AF and potential therapeutic compounds for AF were identified. The biological features of CXCL12 in AF were investigated using integrative bioinformatics tools. The results suggested that CXCL12 might be a biomarker that could be used for distinguishing subsets of AF, and indicated that CXCL12 might be an important intermediate in the development of AF. A reliable Machine Learning-based diagnostic model was constructed. Our work improved understanding of the mechanisms of AF predisposition and progression, and identified potential therapeutic avenues for treatment of AF.

LMNA Variants and Risk of Adult-Onset Cardiac Disease

BACKGROUND

Genetic variants in LMNA may cause cardiac disease, but population-level contributions of variants to cardiac disease burden are not well-characterized.

OBJECTIVES

We sought to determine the frequency and contribution of rare LMNA variants to cardiomyopathy and arrhythmia risk among ambulatory adults.

METHODS

We included 185,990 UK Biobank participants with whole-exome sequencing. We annotated rare loss-of-function and missense LMNA variants for functional effect using 30 in silico prediction tools. We assigned a predicted functional effect weight to each variant and calculated a score for each carrier. We tested associations between the LMNA score and arrhythmia (atrial fibrillation, bradyarrhythmia, ventricular arrhythmia) or cardiomyopathy outcomes (dilated cardiomyopathy and heart failure). We also examined associations for variants located upstream vs downstream of the nuclear localization signal.

RESULTS

Overall, 1,167 (0.63%) participants carried an LMNA variant and 15,079 (8.11%) had an arrhythmia or cardiomyopathy event during a median follow-up of 10.9 years. The LMNA score was associated with arrhythmia or cardiomyopathy (OR: 2.21; P < 0.001) and the association was more significant when restricted to variants upstream of the nuclear localization signal (OR: 5.05; P < 0.001). The incidence rate of arrhythmia or cardiomyopathy was 8.43 per 1,000 person-years (95% CI: 6.73-10.12 per 1,000 person-years) among LMNA variant carriers and 6.38 per 1,000 person-years (95% CI: 6.27-6.50 per 1,000 person-years) among noncarriers. Only 3 (1.2%) of the variants were reported as pathogenic in ClinVar.

CONCLUSIONS

Middle-aged adult carriers of rare missense or loss-of-function LMNA variants are at increased risk for arrhythmia and cardiomyopathy.

Rare and Common Genetic Variation Underlying the Risk of Hypertrophic Cardiomyopathy in a National Biobank

Importance

Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in young people. Although rare genetic variants are well-established contributors to HCM risk, common genetic variants have recently been implicated in disease pathogenesis.

Objective

To assess the contributions of rare and common genetic variation to risk of HCM in the general population.

Design, Setting, and Participants

This cohort study of the UK Biobank (data from 2006-2010) and the Mass General Brigham Biobank (2010-2019) assessed the relative and joint contributions of rare genetic variants and a common variant (polygenic) score to risk of HCM. Both rare and common variant predictors were then evaluated in the context of relevant clinical risk factors. Data analysis was conducted from May 2021 to February 2022.

Exposures

Pathogenic rare variants, common-variant (polygenic) score, and clinical risk factors.

Main Outcomes and Measures

Risk of HCM.

Results

The primary study population comprised 184 511 individuals from the UK Biobank. Mean (SD) age was 56 (8) years, 83 690 (45%) of participants were men, and 204 (0.1%) participants had HCM. Of 51 genes included in clinical genetic testing panels for HCM, pathogenic or likely pathogenic variants in 14 core genes (designated by the American College of Medical Genetics and Genomics [ACMG]) were associated with 55-fold higher odds (95% CI, 35-83) of HCM, while those in the remaining 37 non-ACMG genes were not significantly associated with HCM (OR, 1.8; 95% CI, 0.6-4.0). ClinVar pathogenic or likely pathogenic mutations in MYBPC3 (OR, 72; 95% CI, 39-124) and MYH7 (OR, 61; 95% CI, 26-121) were strongly associated with HCM, as were loss-of-function variants in ALPK3 (OR, 13; 95% CI, 4.4-28). A polygenic score was strongly associated with HCM (OR per SD increase in score, 1.6; 95% CI, 1.4-1.8), with concordant results in the Mass General Brigham Biobank. Genetic factors enhanced clinical risk prediction for HCM: addition of rare variant carrier status and the polygenic score to clinical risk factors (obesity, hypertension, atrial fibrillation, and coronary artery disease) improved the area under the receiver operator characteristic curve from 0.71 (95% CI, 0.65-0.77) to 0.82 (95% CI, 0.77-0.87).

Conclusions and Relevance

Both rare and common genetic variants contribute substantially to HCM susceptibility in the general population and improve HCM risk prediction beyond that achieved with clinical factors.

Genetic and non-genetic risk factors associated with atrial fibrillation

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

Monogenic and Polygenic Contributions to QTc Prolongation in the Population

BACKGROUND

Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population.

METHODS

We performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed.

RESULTS

Fifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/decile of PRS=1.4 ms [95% CI, 1.3 to 1.5]; P=1.1×10-196). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms [95% CI, 7.4 to 14.4]). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS).

CONCLUSIONS

QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.

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.

Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank

Cardiometabolic diseases are the leading cause of death worldwide. Despite a known genetic component, our understanding of these diseases remains incomplete. Here, we analyzed the contribution of rare variants to 57 diseases and 26 cardiometabolic traits, using data from 200,337 UK Biobank participants with whole-exome sequencing. We identified 57 gene-based associations, with broad replication of novel signals in Geisinger MyCode. There was a striking risk associated with mutations in known Mendelian disease genes, including MYBPC3, LDLR, GCK, PKD1 and TTN. Many genes showed independent convergence of rare and common variant evidence, including an association between GIGYF1 and type 2 diabetes. We identified several large effect associations for height and 18 unique genes associated with blood lipid or glucose levels. Finally, we found that between 1.0% and 2.4% of participants carried rare potentially pathogenic variants for cardiometabolic disorders. These findings may facilitate studies aimed at therapeutics and screening of these common disorders.

Genome-wide association analyses identify new Brugada syndrome risk loci and highlight a new mechanism of sodium channel regulation in disease susceptibility

Brugada syndrome (BrS) is a cardiac arrhythmia disorder associated with sudden death in young adults. With the exception of SCN5A, encoding the cardiac sodium channel Na_V1.5, susceptibility genes remain largely unknown. Here we performed a genome-wide association meta-analysis comprising 2,820 unrelated cases with BrS and 10,001 controls, and identified 21 association signals at 12 loci (10 new). Single nucleotide polymorphism (SNP)-heritability estimates indicate a strong polygenic influence. Polygenic risk score analyses based on the 21 susceptibility variants demonstrate varying cumulative contribution of common risk alleles among different patient subgroups, as well as genetic associations with cardiac electrical traits and disorders in the general population. The predominance of cardiac transcription factor loci indicates that transcriptional regulation is a key feature of BrS pathogenesis. Furthermore, functional studies conducted on MAPRE2, encoding the microtubule plus-end binding protein EB2, point to microtubule-related trafficking effects on Na_V1.5 expression as a new underlying molecular mechanism. Taken together, these findings broaden our understanding of the genetic architecture of BrS and provide new insights into its molecular underpinnings.

Tissue-specific multi-omics analysis of atrial fibrillation

Genome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, refined multi-omics approaches are needed for deciphering the underlying molecular networks. Here, we integrate genomics, transcriptomics, and proteomics of human atrial tissue in a cross-sectional study to identify widespread effects of genetic variants on both transcript (cis-eQTL) and protein (cis-pQTL) abundance. We further establish a novel targeted trans-QTL approach based on polygenic risk scores to determine candidates for AF core genes. Using this approach, we identify two trans-eQTLs and five trans-pQTLs for AF GWAS hits, and elucidate the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multi-omics method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization.

A novel PRRX1 loss-of-function variation contributing to familial atrial fibrillation and congenital patent ductus arteriosus

Atrial fibrillation (AF) represents the most common type of sustained cardiac arrhythmia in humans and confers a significantly increased risk for thromboembolic stroke, congestive heart failure and premature death. Aggregating evidence emphasizes the predominant genetic defects underpinning AF and an increasing number of deleterious variations in more than 50 genes have been involved in the pathogenesis of AF. Nevertheless, the genetic basis underlying AF remains incompletely understood. In the current research, by whole-exome sequencing and Sanger sequencing analysis in a family with autosomal-dominant AF and congenital patent ductus arteriosus (PDA), a novel heterozygous variation in the PRRX1 gene encoding a homeobox transcription factor critical for cardiovascular development, NM_022716.4:c.373G>T;p.(Glu125^*), was identified to be in co-segregation with AF and PDA in the whole family. The truncating variation was not detected in 306 unrelated healthy individuals employed as controls. Quantitative biological measurements with a reporter gene analysis system revealed that the Glu125^*-mutant PRRX1 protein failed to transactivate its downstream target genes SHOX2 and ISL1, two genes that have been causally linked to AF. Conclusively, the present study firstly links PRRX1 loss-of-function variation to AF and PDA, suggesting that AF and PDA share a common abnormal developmental basis in a proportion of cases.

PRRX1 Loss-of-Function Mutations Underlying Familial Atrial Fibrillation

Background

Atrial fibrillation (AF) is the most common form of clinical cardiac dysrhythmia responsible for thromboembolic cerebral stroke, congestive heart failure, and death. Aggregating evidence highlights the strong genetic basis of AF. Nevertheless, AF is of pronounced genetic heterogeneity, and in an overwhelming majority of patients, the genetic determinants underpinning AF remain elusive.

Methods and Results

By genome‐wide screening with polymorphic microsatellite markers and linkage analysis in a 4‐generation Chinese family affected with autosomal‐dominant AF, a novel locus for AF was mapped to chromosome 1q24.2–q25.1, a 3.20‐cM (≈4.19 Mbp) interval between markers D1S2851 and D1S218, with the greatest 2‐point logarithm of odds score of 4.8165 for the marker D1S452 at recombination fraction=0.00. Whole‐exome sequencing and bioinformatics analyses showed that within the mapping region, only the mutation in the paired related homeobox 1 (PRRX1) gene, NM_022716.4:c.319C>T;(p.Gln107*), cosegregated with AF in the family. In addition, sequencing analyses of PRRX1 in another cohort of 225 unrelated patients with AF revealed a new mutation, NM_022716.4:c.437G>T; (p.Arg146Ile), in a patient. The 2 mutations were absent in 908 control subjects. Biological analyses in HeLa cells demonstrated that the 2 mutants had significantly diminished transactivation on the target genes ISL1 and SHOX2 and markedly decreased ability to bind the promoters of ISL1 and SHOX2 (2 genes causally linked to AF), although with normal intracellular distribution.

Conclusions

This study first indicates that PRRX1 loss‐of‐function mutations predispose to AF, which provides novel insight into the molecular pathogenesis underpinning AF, implying potential implications for precisive prophylaxis and management of AF.

A Higher Polygenic Risk Score Is Associated with a Higher Recurrence Rate of Atrial Fibrillation in Direct Current Cardioversion-Treated Patients

Background and Objectives: Recurrence of atrial fibrillation (AF) within six months after sinus rhythm restoration with direct current cardioversion (DCC) is a significant treatment challenge. Currently, the factors influencing outcome are mostly unknown. Studies have found a link between genetics and the risk of AF and efficacy of rhythm control. The aim of this study was to examine the association between eight single-nucleotide variants (SNVs) and the risk of AF development and recurrence after DCC. Materials and Methods: Regarding the occurrence of AF, 259 AF cases and 108 controls were studied. Genotypes for the eight SNVs located in the genes CAV1, MYH7, SOX5, KCNN3, ZFHX3, KCNJ5 and PITX2 were determined using high-resolution melting analysis and confirmed with Sanger sequencing. Six months after DCC, a telephone interview was conducted to determine whether AF had recurred. A polygenic risk score (PRS) was calculated as the unweighted sum of risk alleles. Multivariate regression analyses were performed to assess SNV and PRS association with AF occurrence and recurrence after DCC. Results: The risk allele of rs2200733 (PITX2) was significantly associated with the development of AF (p = 0.012, OR = 2.31, 95% CI = 1.206–4.423). AF recurred in 60% of patients and the allele generally associated with a decreased risk of AF of rs11047543 (SOX5) was associated with a greater risk of AF recurrence (p = 0.014, OR = 0.223, 95% CI = 0.067–0.738). A PRS of greater than 7 was significantly associated (p = 0.008) with a higher likelihood of developing AF after DCC (OR = 4.174, 95% CI = 1.454–11.980). Conclusions: A higher PRS is associated with increased odds of AF recurrence after treatment with DCC. PITX2 (rs2200733) is significantly associated with an increased risk of AF. The protective allele of rs11047543 (SOX5) is associated with a greater risk of AF recurrence. Further studies are needed to predict the success of rhythm control and guide patient selection towards the most efficacious treatment.

Towards precision medicine in heart failure

The number of therapies for heart failure (HF) with reduced ejection fraction has nearly doubled in the past decade. In addition, new therapies for HF caused by hypertrophic and infiltrative disease are emerging rapidly. Indeed, we are on the verge of a new era in HF in which insights into the biology of myocardial disease can be matched to an understanding of the genetic predisposition in an individual patient to inform precision approaches to therapy. In this Review, we summarize the biology of HF, emphasizing the causal relationships between genetic contributors and traditional structure-based remodelling outcomes, and highlight the mechanisms of action of traditional and novel therapeutics. We discuss the latest advances in our understanding of both the Mendelian genetics of cardiomyopathy and the complex genetics of the clinical syndrome presenting as HF. In the phenotypic domain, we discuss applications of machine learning for the subcategorization of HF in ways that might inform rational prescribing of medications. We aim to bridge the gap between the biology of the failing heart, its diverse clinical presentations and the range of medications that we can now use to treat it. We present a roadmap for the future of precision medicine in HF.

Early-Onset Atrial Fibrillation and the Prevalence of Rare Variants in Cardiomyopathy and Arrhythmia Genes

Question

In patients diagnosed with atrial fibrillation before 66 years of age, what is the prevalence of disease-associated variants in susceptibility genes for inherited cardiomyopathy and arrhythmia syndromes?

Findings

In this cohort study, among 1293 participants who underwent whole genome sequencing, disease-associated rare variants in cardiomyopathy and arrhythmia genes were identified in 10.1% of participants younger than 66 years and 16.8% of those younger than 30 years. Disease-associated rare variants were more prevalent in genes associated with inherited cardiomyopathy syndromes than inherited arrhythmia syndromes.

Meaning

The results of this study suggest that genetic testing in patients with early-onset atrial fibrillation identifies pathogenic variants associated with more serious inherited cardiomyopathy and arrhythmia syndromes.

Importance

Early-onset atrial fibrillation (AF) can be the initial manifestation of a more serious underlying inherited cardiomyopathy or arrhythmia syndrome.

Objective

To examine the results of genetic testing for early-onset AF.

Design, Setting, and Participants

This prospective, observational cohort study enrolled participants from an academic medical center who had AF diagnosed before 66 years of age and underwent whole genome sequencing through the National Heart, Lung, and Blood Institute’s Trans-Omics for Precision Medicine program. Participants were enrolled from November 23, 1999, to June 2, 2015. Data analysis was performed from October 24, 2020, to March 11, 2021.

Exposures

Rare variants identified in a panel of 145 genes that are included on cardiomyopathy and arrhythmia panels used by commercial clinical genetic testing laboratories.

Main Outcomes and Measures

Sequencing data were analyzed using an automated process followed by manual review by a panel of independent, blinded reviewers. The primary outcome was classification of rare variants using American College of Medical Genetics and Genomics criteria: benign, likely benign, variant of undetermined significance, likely pathogenic, or pathogenic. Disease-associated variants were defined as pathogenic/likely pathogenic variants in genes associated with autosomal dominant or X-linked dominant disorders.

Results

Among 1293 participants (934 [72.2%] male; median [interquartile range] age at enrollment, 56 [48-61] years; median [interquartile range] age at AF diagnosis, 50 [41-56] years), genetic testing identified 131 participants (10.1%) with a disease-associated variant, 812 (62.8%) with a variant of undetermined significance, 92 (7.1%) as heterozygous carriers for an autosomal recessive disorder, and 258 (20.0%) with no suspicious variant. The likelihood of a disease-associated variant was highest in participants with AF diagnosed before the age of 30 years (20 of 119 [16.8%; 95% CI, 10.0%-23.6%]) and lowest after the age of 60 years (8 of 112 [7.1%; 95% CI, 2.4%-11.9%]). Disease-associated variants were more often associated with inherited cardiomyopathy syndromes compared with inherited arrhythmias. The most common genes were TTN (n = 38), MYH7 (n = 18), MYH6 (n = 10), LMNA (n = 9), and KCNQ1 (n = 8).

Conclusions and Relevance

In this cohort study, genetic testing identified a disease-associated variant in 10% of patients with early-onset AF (the percentage was higher if diagnosed before the age of 30 years and lower if diagnosed after the age of 60 years). Most pathogenic/likely pathogenic variants are in genes associated with cardiomyopathy. These results support the use of genetic testing in early-onset AF.

NOTCH3 variants are more common than expected in the general population and associated with stroke and vascular dementia: an analysis of 200 000 participants

BACKGROUND

Cysteine-altering NOTCH3 variants identical to those causing the rare monogenic form of stroke, CADASIL (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy), have been reported more common than expected in the general population, but their clinical significance and contribution to stroke and dementia risk in the community remain unclear.

METHODS

Cysteine-altering NOTCH3 variants were identified in UK Biobank whole-exome sequencing data (N=200 632). Frequency of stroke, vascular dementia and other clinical features of CADASIL, and MRI white matter hyperintensity volume were compared between variant carriers and non-carriers. MRIs from those with variants were visually rated, each matched with three controls.

RESULTS

Of 200 632 participants with exome sequencing data available, 443 (~1 in 450) carried 67 different cysteine-altering NOTCH3 variants. After adjustment for various covariates, NOTCH3 variant carriers had increased risk of stroke (OR: 2.33, p=0.0004) and vascular dementia (OR: 5.00, p=0.007), and increased white matter hyperintensity volume (standardised difference: 0.52, p<0.001) and white matter ultrastructural damage on diffusion MRI (standardised difference: 0.72, p<0.001). On visual analysis of MRIs from 47 carriers and 148 matched controls, variants were associated with presence of lacunes (OR: 5.97, p<0.001) and cerebral microbleeds (OR: 4.38, p<0.001). White matter hyperintensity prevalence was most increased in the anterior temporal lobes (OR: 7.65, p<0.001) and external capsule (OR: 13.32, p<0.001).

CONCLUSIONS

Cysteine-changing NOTCH3 variants are more common in the general population than expected from CADASIL prevalence and are risk factors for apparently 'sporadic' stroke and vascular dementia. They are associated with MRI changes of small vessel disease, in a distribution similar to that seen in CADASIL.

Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care

Despite significant advances in its detection, understanding and management, atrial fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on morbidity and mortality of millions of patients. AF results from complex, dynamic interactions between risk factors and comorbidities that induce diverse atrial remodelling processes. Atrial remodelling increases AF vulnerability and persistence, while promoting disease progression. The variability in presentation and wide range of mechanisms involved in initiation, maintenance and progression of AF, as well as its associated adverse outcomes, make the early identification of causal factors modifiable with therapeutic interventions challenging, likely contributing to suboptimal efficacy of current AF management. Computational modelling facilitates the multilevel integration of multiple datasets and offers new opportunities for mechanistic understanding, risk prediction and personalized therapy. Mathematical simulations of cardiac electrophysiology have been around for 60 years and are being increasingly used to improve our understanding of AF mechanisms and guide AF therapy. This narrative review focuses on the emerging and future applications of computational modelling in AF management. We summarize clinical challenges that may benefit from computational modelling, provide an overview of the different in silico approaches that are available together with their notable achievements, and discuss the major limitations that hinder the routine clinical application of these approaches. Finally, future perspectives are addressed. With the rapid progress in electronic technologies including computing, clinical applications of computational modelling are advancing rapidly. We expect that their application will progressively increase in prominence, especially if their added value can be demonstrated in clinical trials.

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.

Genetics of atrial fibrillation

PURPOSE OF REVIEW

Atrial fibrillation is the most common sustained cardiac arrhythmia. In addition to traditional risk factors, it is increasingly recognized that a genetic component underlies atrial fibrillation development. This review aims to provide an overview of the genetic cause of atrial fibrillation and clinical applications, with a focus on recent developments.

RECENT FINDINGS

Genome-wide association studies have now identified around 140 genetic loci associated with atrial fibrillation. Studies into the effects of several loci and their tentative gene targets have identified novel pathways associated with atrial fibrillation development. However, further validations of causality are still needed for many implicated genes. Genetic variants at identified loci also help predict individual atrial fibrillation risk and response to different therapies.

SUMMARY

Continued advances in the field of genetics and molecular biology have led to significant insight into the genetic underpinnings of atrial fibrillation. Potential clinical applications of these studies include the identification of new therapeutic targets and development of genetic risk scores to optimize management of this common cardiac arrhythmia.

KLF15 Loss-of-Function Mutation Underlying Atrial Fibrillation as well as Ventricular Arrhythmias and Cardiomyopathy

Atrial fibrillation (AF) represents the most common type of clinical cardiac arrhythmia and substantially increases the risks of cerebral stroke, heart failure and death. Accumulating evidence has convincingly demonstrated the strong genetic basis of AF, and an increasing number of pathogenic variations in over 50 genes have been causally linked to AF. Nevertheless, AF is of pronounced genetic heterogeneity, and the genetic determinants underpinning AF in most patients remain obscure. In the current investigation, a Chinese pedigree with AF as well as ventricular arrhythmias and hypertrophic cardiomyopathy was recruited. Whole exome sequencing and bioinformatic analysis of the available family members were conducted, and a novel heterozygous variation in the KLF15 gene (encoding Krüppel-like factor 15, a transcription factor critical for cardiac electrophysiology and structural remodeling), NM_014079.4: c.685A>T; p.(Lys229*), was identified. The variation was verified by Sanger sequencing and segregated with autosomal dominant AF in the family with complete penetrance. The variation was absent from 300 unrelated healthy subjects used as controls. In functional assays using a dual-luciferase assay system, mutant KLF15 showed neither transcriptional activation of the KChIP2 promoter nor transcriptional inhibition of the CTGF promoter, alone or in the presence of TGFB1, a key player in the pathogenesis of arrhythmias and cardiomyopathies. The findings indicate KLF15 as a new causative gene responsible for AF as well as ventricular arrhythmias and hypertrophic cardiomyopathy, and they provide novel insight into the molecular mechanisms underlying cardiac arrhythmias and hypertrophic cardiomyopathy.