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Summary Background Comprehensive long-term data on atrial fibrillation trends in men and women are scant. Methods We investigated trends in atrial fibrillation incidence, prevalence, and risk factors, and in stroke and mortality following its onset in Framingham Heart Study participants (n=9511) from 1958 to 2007. To accommodate sex differences in atrial fibrillation risk factors and disease manifestations, sex-stratified analyses were performed. Findings During 50 years of observation (202,417 person-years), there were 1,544 new-onset atrial fibrillation cases (46.8% women). We observed about a fourfold increase in the age-adjusted prevalence and more than a tripling in age-adjusted incidence of atrial fibrillation (prevalence 20.4 versus 96.2 per 1000 person-years in men; 13.7 versus 49.4 in women; incidence rates in first versus last decade 3.7 versus 13.4 per 1000 person-years in men; 2.5 versus 8.6 in women, ptrend<0.0001). For atrial fibrillation diagnosed by ECG during routine Framingham examinations, age-adjusted prevalence increased (12.6versus 25.7 per 1000 person-years in men; 8.1 versus 11.8 in women, ptrend<0.0001). The age-adjusted incidence increased, but did not achieve statistical significance. Although the prevalence of most risk factors changed over time, their associated hazards for atrial fibrillation changed little. Multivariable-adjusted proportional hazards models revealed a 73.5% decline in stroke and a 25.4% decline in mortality following atrial fibrillation onset (ptrend=0.0001, ptrend=0.003, respectively). Interpretation Our data suggest that observed trends of increased incidence of atrial fibrillation in the community were partially due to enhanced surveillance. Stroke occurrence and mortality following atrial fibrillation onset declined over the decades, and prevalence increased approximately fourfold. The hazards for atrial fibrillation risk factors remained fairly constant. Our data indicate a need for measures to enhance early detection of atrial fibrillation through increased awareness coupled with targeted screening programs, and risk factor-specific prevention.

Background-Atrial fibrillation (AF) contributes to substantial increases in morbidity and mortality. Our aim was to develop a risk prediction model to assess individuals' absolute risk for

The use of a sensitive assay for troponin I improves early diagnosis of acute myocardial infarction and risk stratification, regardless of the time of chest-pain onset.

Chronic kidney disease (CKD) is a significant public health problem, and recent genetic studies have identified common CKD susceptibility variants. The CKDGen consortium performed a meta-analysis of genome-wide association data in 67,093 Caucasian individuals from 20 population-based studies to identify new susceptibility loci for reduced renal function, estimated by serum creatinine (eGFRcrea), cystatin C (eGFRcys), and CKD (eGFRcrea <60 ml/min/1.73m2; n = 5,807 CKD cases). Follow-up of the 23 genome-wide significant loci (p<5×10−8) in 22,982 replication samples identified 13 novel loci for renal function and CKD (in or near LASS2, GCKR, ALMS1, TFDP2, DAB2, SLC34A1, VEGFA, PRKAG2, PIP5K1B, ATXN2, DACH1, UBE2Q2, and SLC7A9) and 7 creatinine production and secretion loci (CPS1, SLC22A2, TMEM60, WDR37, SLC6A13, WDR72, BCAS3). These results further our understanding of biologic mechanisms of kidney function by identifying loci potentially influencing nephrogenesis, podocyte function, angiogenesis, solute transport, and metabolic functions of the kidney.

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.

Background-Digital pulse amplitude augmentation in response to hyperemia is a novel measure of peripheral vasodilator function that depends partially on endothelium-derived nitric oxide. Baseline digital pulse amplitude reflects local peripheral arterial tone. The relation of digital pulse amplitude and digital hyperemic response to cardiovascular risk factors in the community is unknown. Methods and Results-Using a fingertip peripheral arterial tonometry (PAT) device, we measured digital pulse amplitude in Framingham Third Generation Cohort participants (nϭ1957; mean age, 40Ϯ9 years; 49% women) at baseline and in 30-second intervals for 4 minutes during reactive hyperemia induced by 5-minute forearm cuff occlusion. To evaluate the vascular response in relation to baseline, adjusting for systemic effects and skewed data, we expressed the hyperemic response (called the PAT ratio) as the natural logarithm of the ratio of postdeflation to baseline pulse amplitude in the hyperemic finger divided by the same ratio in the contralateral finger that served as control. The relation of the PAT ratio to cardiovascular risk factors was strongest in the 90-to 120-second postdeflation interval (overall model R 2 ϭ0.159). In stepwise multivariable linear regression models, male sex, body mass index, ratio of total to high-density lipoprotein cholesterol, diabetes mellitus, smoking, and lipid-lowering treatment were inversely related to PAT ratio, whereas increasing age was positively related to PAT ratio (all PϽ0.01). Conclusions-Reactive

BackgroundVariability of gene expression in human may link gene sequence variability and phenotypes; however, non-genetic variations, alone or in combination with genetics, may also influence expression traits and have a critical role in physiological and disease processes.Methodology/Principal FindingsTo get better insight into the overall variability of gene expression, we assessed the transcriptome of circulating monocytes, a key cell involved in immunity-related diseases and atherosclerosis, in 1,490 unrelated individuals and investigated its association with >675,000 SNPs and 10 common cardiovascular risk factors. Out of 12,808 expressed genes, 2,745 expression quantitative trait loci were detected (P<5.78×10−12), most of them (90%) being cis-modulated. Extensive analyses showed that associations identified by genome-wide association studies of lipids, body mass index or blood pressure were rarely compatible with a mediation by monocyte expression level at the locus. At a study-wide level (P<3.9×10−7), 1,662 expression traits (13.0%) were significantly associated with at least one risk factor. Genome-wide interaction analyses suggested that genetic variability and risk factors mostly acted additively on gene expression. Because of the structure of correlation among expression traits, the variability of risk factors could be characterized by a limited set of independent gene expressions which may have biological and clinical relevance. For example expression traits associated with cigarette smoking were more strongly associated with carotid atherosclerosis than smoking itself.Conclusions/SignificanceThis study demonstrates that the monocyte transcriptome is a potent integrator of genetic and non-genetic influences of relevance for disease pathophysiology and risk assessment.