BackgroundTools for the prediction of atrial fibrillation (AF) may identify high‐risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors.Methods and ResultsIndividual‐level data from 3 large cohorts in the United States (Atherosclerosis Risk in Communities [ARIC] study, the Cardiovascular Health Study [CHS], and the Framingham Heart Study [FHS]), including 18 556 men and women aged 46 to 94 years (19% African Americans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment—Reykjavik study (AGES) and the Rotterdam Study (RS). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5‐year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C‐statistic, 0.765; 95% CI, 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C‐statistic, 0.767; 95% CI, 0.750 to 0.783; categorical net reclassification improvement, −0.0032; 95% CI, −0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable (AGES C‐statistic, 0.664; 95% CI, 0.632 to 0.697 and RS C‐statistic, 0.705; 95% CI, 0.664 to 0.747) and calibration was adequate.ConclusionA risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the United States and Europe.

We estimate that from 2010 to 2060, the number of adults 55 years and over with AF in the European Union will more than double. As AF is associated with significant morbidities and mortality, this increasing number of individuals with AF may have major public health implications.

Atrial fibrillation is a highly prevalent arrhythmia and a major risk factor for stroke, heart failure and death1. We conducted a genome-wide association study (GWAS) in individuals of European ancestry, including 6,707 with and 52,426 without atrial fibrillation. Six new atrial fibrillation susceptibility loci were identified and replicated in an additional sample of individuals of European ancestry, including 5,381 subjects with and 1 0,030 subjects without atrial fibrillation (P < 5 × 10−8). Four of the loci identified in Europeans were further replicated in silico in a GWAS of Japanese individuals, including 843 individuals with and 3,350 individuals without atrial fibrillation. The identified loci implicate candidate genes that encode transcription factors related to cardiopulmonary development, cardiac-expressed ion channels and cell signaling molecules.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.

Background Atrial fibrillation (AF) affects over 30 million individuals worldwide and is associated with an increased risk of stroke, heart failure, and death. AF is highly heritable, yet the genetic basis for the arrhythmia remains incompletely understood. Methods & Results To identify new AF-related genes, we utilized a multifaceted approach, combining large-scale genotyping in two ethnically distinct populations, cis-eQTL mapping, and functional validation. Four novel loci were identified in individuals of European descent near the genes NEURL (rs12415501, RR=1.18, 95%CI 1.13 – 1.23, p=6.5×10−16), GJA1 (rs13216675, RR=1.10, 95%CI 1.06 – 1.14, p=2.2×10−8), TBX5 (rs10507248, RR=1.12, 95%CI 1.08 – 1.16, p=5.7×10−11), and CAND2 (rs4642101, RR=1.10, 95%CI 1.06 – 1.14, p=9.8×10−9). In Japanese, novel loci were identified near NEURL (rs6584555, RR=1.32, 95%CI 1.26–1.39, p=2.0×10−25) and CUX2 (rs6490029, RR=1.12, 95%CI 1.08–1.16, p=3.9×10−9). The top SNPs or their proxies were identified as cis-eQTLs for the genes CAND2 (p=2.6×10−19), GJA1 (p=2.66×10−6), and TBX5 (p=1.36×10−05). Knockdown of the zebrafish orthologs of NEURL and CAND2 resulted in prolongation of the atrial action potential duration (17% and 45%, respectively). Conclusions We have identified five novel loci for AF. Our results further expand the diversity of genetic pathways implicated in AF and provide novel molecular targets for future biological and pharmacological investigation.