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

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

Signature Activation: A Sparse Signal View for Holistic Saliency

The adoption of machine learning in healthcare calls for model transparency and explainability. In this work, we introduce Signature Activation, a saliency method that generates holistic and class-agnostic explanations for Convolutional Neural Network (CNN) outputs. Our method exploits the fact that certain kinds of medical images, such as angiograms, have clear foreground and background objects. We give theoretical explanation to justify our methods. We show the potential use of our method in clinical settings through evaluating its efficacy for aiding the detection of lesions in coronary angiograms

Potassium channel gene mutations rarely cause atrial fibrillation

BACKGROUND: Mutations in several potassium channel subunits have been associated with rare forms of atrial fibrillation. In order to explore the role of potassium channels in inherited typical forms of the arrhythmia, we have screened a cohort of patients from a referral clinic for mutations in the channel subunit genes implicated in the arrhythmia. We sought to determine if mutations in KCNJ2 and KCNE1-5 are a common cause of atrial fibrillation. METHODS: Serial patients with lone atrial fibrillation or atrial fibrillation with hypertension were enrolled between June 1, 2001 and January 6, 2005. Each patient underwent a standardized interview and physical examination. An electrocardiogram, echocardiogram and blood sample for genetic analysis were also obtained. Patients with a family history of AF were screened for mutations in KCNJ2 and KCNE1-5 using automated sequencing. RESULTS: 96 patients with familial atrial fibrillation were enrolled. Eighty-three patients had lone atrial fibrillation and 13 had atrial fibrillation and hypertension. Patients had a mean age of 56 years at enrollment and 46 years at onset of atrial fibrillation. Eighty-one percent of patients had paroxysmal atrial fibrillation at enrollment. Unlike patients with an activating mutation in KCNQ1, the patients had a normal QT(c )interval with a mean of 412 ± 42 ms. Echocardiography revealed a normal mean ejection fraction of 62.0 ± 7.2 % and mean left atrial dimension of 39.9 ± 7.0 mm. A number of common polymorphisms in KCNJ2 and KCNE1-5 were identified, but no mutations were detected. CONCLUSION: Mutations in KCNJ2 and KCNE1-5 rarely cause typical atrial fibrillation in a referral clinic population

Genetic Loci Associated With Atrial Fibrillation: Relation to Left Atrial Structure in the Framingham Heart Study

Background: Atrial fibrillation (AF) results in significant morbidity and mortality. Genome‐wide association studies (GWAS) have identified genetic variants associated with AF. Whether genetic variants associated with AF are also associated with atrial structure, an intermediate phenotype for AF, has had limited investigation. We sought to investigate associations between single nucleotide polymorphisms (SNPs) and atrial structure obtained by cardiovascular imaging in the Framingham Heart Study. Methods and Results: We selected 11 SNPs that have been associated with AF in GWAS. We examined the SNPs' relations to cross‐sectional left atrial (LA) dimensions (determined by transthoracic echocardiography) and LA volume (determined by cardiovascular magnetic resonance [CMR]) employing linear regression. The total sample included 1555 participants with CMR LA volume (age 60±9 years, 53% women) and 6861 participants with echocardiographic LA diameter (age 48±13 years, 52% women) measured. We employed a significance threshold of P<0.0023 to account for multiple testing of the 11 SNPs and 2 LA measures. In a primary analysis, no SNPs were significantly related to the LA measures. Likewise, in secondary analyses excluding individuals with prevalent AF (n=77, CMR sample; n=105, echocardiography sample) no SNPs were related to LA volume or diameter. Conclusion: In a community‐based cohort, we did not identify a statistically significant association between selected SNPs associated with AF and measures of LA anatomy. Further investigations with larger longitudinally assessed samples and a broader array of SNPs may be necessary to determine the relation between genetic loci associated with AF and atrial structure

Plasma microRNAs are Associated with Atrial Fibrillation (the miRhythm Study) and Change After Catheter-ablation

Background: Atrial fibrillation (AF) is the most common dysrhythmia in the U.S. and Europe. Few biomarkers exist to identify individuals at risk for AF. Cardiac microRNAs (miRNAs) have been implicated in susceptibility to AF and are detectable in the circulation. Nevertheless, data are limited on how circulating levels of miRNAs relate to AF or change over time after catheter- ablation. Methods: In 211 miRhythm participants (112 with paroxysmal or persistent AF; 99 without AF), we quantified plasma expression of 86 miRNAs associated with cardiac remodeling or disease by high-throughput quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR). We used qRT-PCR to examine change in plasma miRNA expression from baseline to 1-month after ablation in 47 participants. We also quantified expression of the 20 most variable miRNAs in atrial tissue in 31 participants undergoing cardiac surgery. Results: The mean age of the miRhythm cohort was 59 years and 58% of participants were men. 21 miRNAs differed significantly between participants with AF and those with no AF in regression models adjusting for known AF risk factors (p value of ≤ 0.0006). Several miRNAs associated with AF, including miR-21, miR-29a, miR-122, miR-150, miR-320, and miR-92a, regulate expression of genes implicated in the pathogenesis of AF. Levels of 33 miRNAs, including 14 associated with AF, changed significantly between baseline and 1-month after catheter ablation (p value of ≤ 0.0006). Although all AF-related plasma miRNAs were expressed in atrial tissue, only miR-21 and miR-411 differed significantly with respect to preoperative AF status. Conclusions: Plasma levels of miRNAs associated with heart disease and cardiac remodeling were related to AF and changed after catheter-ablation. Our study suggests that AF has a unique circulating miRNA profile and that this profile is influenced by catheter-ablation

Atrial fibrillation without comorbidities: Prevalence, incidence and prognosis (from the Framingham Heart Study)

BACKGROUND: The epidemiology of atrial fibrillation (AF) without comorbidities, known as \u27lone AF\u27, is uncertain. Although it has been considered a benign condition, we hypothesized that it confers a worse prognosis compared with a matched sample without AF. METHODS: We described the proportion of AF without comorbidities (clinical, subclinical cardiovascular disease and triggers) among the entire AF sample in Framingham Heart Study (FHS). We compared AF without comorbidities with typical AF, and age-, sex- and cohort-matched individuals without AF, using Cox proportional hazards analysis in relation to combined cardiovascular events (stroke, heart failure, myocardial infarction), and mortality. RESULTS: Of 10,311 FHS participants, 1,961 were diagnosed with incident AF, among which 173 individuals had AF without comorbidities (47% women, mean age 71+/-12 years). AF without comorbidities had a prevalence of 1.7% of the entire cohort, and an annual incidence of 0.5 per 1000 person-years. During a median follow-up of 9.7 years after initial AF, 137 individuals with AF without comorbidities (79.2%) died and 141 individuals developed cardiovascular events (81.5%). AF without comorbidities had significantly lower mortality (HR 0.67, 95%CI 0.55-0.81, P \u3c .001) and total cardiovascular events (HR 0.66, 95% CI 0.55-0.80, P \u3c .001) compared with typical AF. However, mortality (HR1.43, 95% CI 1.18-1.75, P \u3c .001) and risk of total cardiovascular events (HR 1.73, 95% CI 1.39-2.16, P \u3c .001) were higher than age-, sex-, and cohort-matched individuals without AF. CONCLUSIONS: The risk of cardiovascular outcomes and mortality among individuals with AF without comorbidities is lower than typical AF, but is significantly elevated compared with matched individuals without AF

Lifetime risk of atrial fibrillation according to optimal, borderline, or elevated levels of risk factors: cohort study based on longitudinal data from the Framingham Heart Study

OBJECTIVE: To examine the association between risk factor burdens-categorized as optimal, borderline, or elevated-and the lifetime risk of atrial fibrillation. DESIGN: Community based cohort study. SETTING: Longitudinal data from the Framingham Heart Study. PARTICIPANTS: Individuals free of atrial fibrillation at index ages 55, 65, and 75 years were assessed. Smoking, alcohol consumption, body mass index, blood pressure, diabetes, and history of heart failure or myocardial infarction were assessed as being optimal (that is, all risk factors were optimal), borderline (presence of borderline risk factors and absence of any elevated risk factor), or elevated (presence of at least one elevated risk factor) at index age. MAIN OUTCOME MEASURE: Lifetime risk of atrial fibrillation at index age up to 95 years, accounting for the competing risk of death. RESULTS: At index age 55 years, the study sample comprised 5338 participants (2531 (47.4%) men). In this group, 247 (4.6%) had an optimal risk profile, 1415 (26.5%) had a borderline risk profile, and 3676 (68.9%) an elevated risk profile. The prevalence of elevated risk factors increased gradually when the index ages rose. For index age of 55 years, the lifetime risk of atrial fibrillation was 37.0% (95% confidence interval 34.3% to 39.6%). The lifetime risk of atrial fibrillation was 23.4% (12.8% to 34.5%) with an optimal risk profile, 33.4% (27.9% to 38.9%) with a borderline risk profile, and 38.4% (35.5% to 41.4%) with an elevated risk profile. Overall, participants with at least one elevated risk factor were associated with at least 37.8% lifetime risk of atrial fibrillation. The gradient in lifetime risk across risk factor burden was similar at index ages 65 and 75 years. CONCLUSIONS: Regardless of index ages at 55, 65, or 75 years, an optimal risk factor profile was associated with a lifetime risk of atrial fibrillation of about one in five; this risk rose to more than one in three a third in individuals with at least one elevated risk factor

Whole Blood Gene Expression and Atrial Fibrillation: The Framingham Heart Study

Background: Atrial fibrillation (AF) involves substantial electrophysiological, structural and contractile remodeling. We hypothesize that characterizing gene expression might uncover important pathways related to AF. Methods and Results: We performed genome-wide whole blood transcriptomic profiling (Affymetrix Human Exon 1.0 ST Array) of 2446 participants (mean age 66±9 years, 55% women) from the Offspring cohort of Framingham Heart Study. The study included 177 participants with prevalent AF, 143 with incident AF during up to 7 years follow up, and 2126 participants with no AF. We identified seven genes statistically significantly up-regulated with prevalent AF. The most significant gene, PBX1 (P = 2.8×10−7), plays an important role in cardiovascular development. We integrated differential gene expression with gene-gene interaction information to identify several signaling pathways possibly involved in AF-related transcriptional regulation. We did not detect any statistically significant transcriptomic associations with incident AF. Conclusion: We examined associations of gene expression with AF in a large community-based cohort. Our study revealed several genes and signaling pathways that are potentially involved in AF-related transcriptional regulation