Risk Factors for Atrial Fibrillation

Atrial fibrillation is a common cardiac arrhythmia that is characterized by rapid disorganized atrial electrical activity resulting in absence of atrial contractions. It is diagnosed on the basis of typical findings on an electrocardiogram (ECG). The characteristic ECG findings are absence of P-waves, and an irregular heart rate. Symptoms of atrial fibrillation include palpitations, dyspnea, reduced exercise capacity, chest pain and dizziness, but it often goes without symptoms. Although atrial fibrillation is often asymptomatic it has serious consequences for the health of affected individuals and is a substantial burden for the health care system. Atrial fibrillation is associated with a higher risk of several serious complications. It is associated with a three to five fold higher risk of stroke. Furthermore, it is associated with a higher risk of dementia, heart failure, and it is associated with increased mortality independent of age sex and other cardiovascular risk factors. Also, it is associated with lower quality of life, even patients without symptoms have a lower perceived general health and gobal life satisfaction than healthy subjects. The prevalence and incidence of atrial fibrillation increase with age. It is estimated that the lifetime risk for development of atrial fibrillation is one in every four adults over 40 years of age. As Western populations are projected to age in the coming decades it is likely that there will be an increase in the number of affected individuals with several types of chronic disease. Several studies projected that the future number of adults with atrial fibrillation in the United States will have doubled by the year 2050.13-15 Not much is known about the potential rise in the number of individuals with atrial fibrillation in the Netherlands and in the European Union but since these populations are projected to age, an increase in the number of patients can be expected

Non-steroidal anti-inflammatory drugs and the risk of atrial fibrillation: A population-based follow-up study

Objective: To investigate the association of non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of atrial fibrillation in a prospective community-based follow-up study of elderly individuals with uniform case assessment and data on potential confounders. Design: Data came from the population-based follow-up study, the Rotterdam Study. Participants: The study comprised 8423 participants without atrial fibrillation at baseline. Main outcome measures: Atrial fibrillation was ascertained from ECG assessments as well as medical records. Use of NSAIDs was obtained from automated prescription records by linkage with participating pharmacies. We used Cox proportional hazards models to study the association between NSAID drug use and atrial fibrillation. Use of NSAIDs was included in the model as a time-varying variable. Results: At baseline, the mean age of the study population was 68.5 years (SD: 8.7) and 58% were women. During a mean follow-up of 12.9 years, 857 participants developed atrial fibrillation. Current use of NSAIDs was associated with increased risk compared with never-use (HR 1.76, 95% CI 1.07 to 2.88). Also, recent use (within 30 days after discontinuation of NSAIDs) was associated with an increased risk of atrial fibrillation compared with never-use (HR 1.84, 95% CI 1.34 to 2.51) adjusted for age, sex and several potential confounders. Conclusions: In this study, use of NSAIDs was associated with an increased risk of atrial fibrillation. Further studies are needed to investigate the underlying mechanisms behind this association

Prevalence of pulmonary hypertension in the general population

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Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: A pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk ofmajor cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regressionmodels to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genom

Genetic Interactions with Age, Sex, Body Mass Index, and Hypertension in Relation to Atrial Fibrillation: The AFGen Consortium

It is unclear whether genetic markers interact with risk factors to influence atrial fibrillation (AF) risk. We performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index in the AFGen Consortium. Study-specific results were combined using meta-analysis (88,383 individuals of European descent, including 7,292 with AF). Variants with nominal interaction associations in the discovery analysis were tested for association in four independent studies (131,441 individuals, including 5,722 with AF). In the discovery analysis, the AF risk associated with the minor rs6817105 allele (at the PITX2 locus) was greater among subjects ≤ 65 years of age than among those > 65 years (interaction p-value = 4.0 × 10-5). The interaction p-value exceeded genome-wide significance in combined discovery and replication analyses (interaction p-value = 1.7 × 10-8). We observed one genome-wide significant interaction with body mass index and several suggestive interactions with age, sex, and body mass index in the discovery analysis. However, none was replicated in the independent sample. Our findings suggest that the pathogenesis of AF may differ according to age in individuals of European descent, but we did not observe evidence of statistically significant genetic interactions with sex, body mass index, or hypertension on AF risk

Fifteen Genetic Loci Associated with the Electrocardiographic P Wave

The P wave on an ECG is a measure of atrial electric function, and its characteristics may serve as predictors for atrial arrhythmias. Increased mean P-wave duration and P-wave terminal force traditionally have been used as markers for left atrial enlargement, and both have been associated with increased risk of atrial fibrillation. Here, we explore the genetic basis of P-wave morphology through meta-analysis of genome-wide association study results for P-wave duration and P-wave terminal force from 12 cohort studies. Methods and Results - We included 44 456 individuals, of which 6778 (16%) were of African ancestry. Genotyping, imputation, and genome-wide association study were performed at each study site. Summary-level results were meta-analyzed centrally using inverse-variance weighting. In meta-analyses of P-wave duration, we identified 6 significant (P<5×10-8) novel loci and replicated a prior association with SCN10A. We identified 3 loci at SCN5A, TBX5, and CAV1/CAV2 that were jointly associated with the PR interval, PR segment, and P-wave duration. We identified 6 novel loci in meta-analysis of P-wave terminal force. Four of the identified genetic loci were significantly associated with gene expression in 329 left atrial samples. Finally, we observed that some of the loci associated with the P wave were linked to overall atrial conduction, whereas others identified distinct phases of atrial conduction. Conclusions - We have identified 6 novel genetic loci associated with P-wave duration and 6 novel loci associated with P-wave terminal force. Future studies of these loci may aid in identifying new targets for drugs that may modify atrial conduction or treat atrial arrhythmias

Projections on the number of individuals with atrial fibrillation in the European Union, from 2000 to 2060

AimsSince atrial fibrillation (AF) is associated with increased risks of cardiovascular and cerebrovascular complications, estimations on the number of individuals with AF are relevant to healthcare plannin

Annotation of loci from genome-wide association studies using tissue-specifc quantitative interaction proteomics

Genome-wide association studies (GWAs) have identifed thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specifc quantitative interaction proteomics to map a network of fve genes involved in the mendelian disorder long Qt syndrome (lQts). We integrated the lQts network with GWAs loci from the corresponding common complex trait, Qt-interval variation, to identify candidate genes that were subsequently confrmed in Xenopus laevis oocytes and zebrafsh. We used the lQts protein network to flter weak GWAs signals by identifying single-nucleotide polymorphisms (snPs) in proximity to genes in the network supported by strong proteomic evidence. three snPs passing this flter reached genome-wide signifcance after replication genotyping. overall, we present a general strategy to propose candidates in GWAs loci for functional studies and to systematically flter subtle association signals using tissue-specifc quantitative interaction proteomics

B-type natriuretic peptide and C-reactive protein in the prediction of atrial fibrillation risk: the CHARGE-AF Consortium of community-based cohort studies

AIMS: B-type natriuretic peptide (BNP) and C-reactive protein (CRP) predict atrial fibrillation (AF) risk. However, their risk stratification abilities in the broad community remain uncertain. We sought to improve risk stratification for AF using biomarker information.METHODS AND RESULTS: We ascertained AF incidence in 18 556 Whites and African Americans from the Atherosclerosis Risk in Communities Study (ARIC, n=10 675), Cardiovascular Health Study (CHS, n = 5043), and Framingham Heart Study (FHS, n = 2838), followed for 5 years (prediction horizon). We added BNP (ARIC/CHS: N-terminal pr

Common variation in fatty acid metabolic genes and risk of incident sudden cardiac arrest

Background There is limited information on genetic factors associated with sudden cardiac arrest (SCA). Objective To assess the association of common variation in genes in fatty acid pathways with SCA risk. Methods We selected 85 candidate genes and 1155 single nucleotide polymorphisms (SNPs) tagging common variation in each gene. We investigated the SNP associations with SCA in a population-based case-control study. Cases (n = 2160) were from a repository of SCA in the greater Seattle area. Controls (n = 2615), frequency-matched on age and sex, were from the same area. We used linear logistic regression to examine SNP associations with SCA. We performed permutation-based p-min tests to account for multiple comparisons within each gene. The SNP associations with a corrected P value of <.05 were then examined in a meta-analysis of these SNP associations in 9 replication studies totaling 2129 SCA cases and 23,833 noncases. Results Eight SNPs in or near 8 genes were associated with SCA risk in the discovery study, one of which was nominally significant in the replication phase (rs7737692, minor allele frequency 36%, near the LPCAT1 gene). For each copy of the minor allele, rs7737692 was associated with 13% lower SCA risk (95% confidence interval -21% to -5%) in the discovery phase and 9% l