36 research outputs found

    Variable Nav1.5 Protein Expression from the Wild-Type Allele Correlates with the Penetrance of Cardiac Conduction Disease in the Scn5a+/− Mouse Model

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    BACKGROUND: Loss-of-function mutations in SCN5A, the gene encoding Na(v)1.5 Na+ channel, are associated with inherited cardiac conduction defects and Brugada syndrome, which both exhibit variable phenotypic penetrance of conduction defects. We investigated the mechanisms of this heterogeneity in a mouse model with heterozygous targeted disruption of Scn5a (Scn5a(+/-) mice) and compared our results to those obtained in patients with loss-of-function mutations in SCN5A. METHODOLOGY/PRINCIPAL FINDINGS: Based on ECG, 10-week-old Scn5a(+/-) mice were divided into 2 subgroups, one displaying severe ventricular conduction defects (QRS interval>18 ms) and one a mild phenotype (QRS53 weeks), ajmaline effect was larger in the severely affected subgroup. These data matched the clinical observations on patients with SCN5A loss-of-function mutations with either severe or mild conduction defects. Ventricular tachycardia developed in 5/10 old severely affected Scn5a(+/-) mice but not in mildly affected ones. Correspondingly, symptomatic SCN5A-mutated Brugada patients had more severe conduction defects than asymptomatic patients. Old severely affected Scn5a(+/-) mice but not mildly affected ones showed extensive cardiac fibrosis. Mildly affected Scn5a(+/-) mice had similar Na(v)1.5 mRNA but higher Na(v)1.5 protein expression, and moderately larger I(Na) current than severely affected Scn5a(+/-) mice. As a consequence, action potential upstroke velocity was more decreased in severely affected Scn5a(+/-) mice than in mildly affected ones. CONCLUSIONS: Scn5a(+/-) mice show similar phenotypic heterogeneity as SCN5A-mutated patients. In Scn5a(+/-) mice, phenotype severity correlates with wild-type Na(v)1.5 protein expression

    Simple Risk Model Predicts Incidence of Atrial Fibrillation in a Racially and Geographically Diverse Population: the CHARGE-AF Consortium

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    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

    Use of anticoagulants and antiplatelet agents in stable outpatients with coronary artery disease and atrial fibrillation. International CLARIFY registry

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    PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity

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    Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genomewide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are overrepresented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of similar to 105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ionchannel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development

    ExomeChip-Wide Analysis of 95 626 Individuals Identifies 10 Novel Loci Associated With QT and JT Intervals

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    Common Fund of the Office of the Director of the National Institutes of Health. Additional funds were provided by the National Cancer Institute (NCI), National Human Genome Research Institute (NHGRI), National Heart, Lung, and Blood Institute (NHLBI), National Institute on Drug Abuse (NIDA), National Institute of Mental Health (NIMH), and National Institute of Neurological Disorders and Stroke (NINDS)

    Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6

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    Background: Genome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear.Results: Here, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction.Conclusions: Our approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes

    Genetic loci associated with heart rate variability and their effects on cardiac disease risk

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    Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74 < r(g) < -0.55) and blood pressure (-0.35 < r(g) < -0.20). These findings provide clinically relevant biological insight into heritable variation in vagal heart rhythm regulation, with a key role for genetic variants (GNG11, RGS6) that influence G-protein heterotrimer action in GIRK-channel induced pacemaker membrane hyperpolarization

    Erratum: Genetic loci associated with heart rate variability and their effects on cardiac disease risk

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    Correction to article number 15805 published in June 2017 in Nature Communications, vol 8

    Erratum: Genetic loci associated with heart rate variability and their effects on cardiac disease risk

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    Correction to article number 15805 published in June 2017 in Nature Communications, vol 8
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