Gender differences in clinical presentation and 1-year outcomes in atrial fibrillation

Objectives Our objective was to examine gender differences in clinical presentation, management and prognosis of atrial fibrillation (AF) in a contemporary cohort. Methods In 6412 patients, 39.7% women, of the PREvention oF thromboembolic events – European Registry in Atrial Fibrillation, we examined gender differences in symptoms, risk factors, therapies and 1-year incidence of adverse outcomes. Results Men with AF were on average younger than women (mean±SD: 70.1±10.7 vs 74.1±9.7 years, p<0.0001). Women more frequently had at least one AF-related symptom at least occasionally compared with men (95.4% in women, 89.8% in men, p<0.0001). Prescription of oral anticoagulation was similar, with an increase of non-vitamin K antagonist oral anticoagulants from 5.9% to 12.6% in women and from 6.2% to 12.6% in men, p<0.0001 for both. Men were more frequently treated with electrical cardioversion and ablation (20.6% and 6.3%, respectively) than women (14.9% and 3.3%, respectively), p<0.0001. Women had 65% (OR: 0.35; 95% CI (0.22 to 0.56)) lower age-adjusted and country-adjusted odds of coronary revascularisation, 40% (OR: 0.60; (0.38 to 0.93)) lower odds of acute coronary syndrome and 20% (OR: 0.80; (0.68 to 0.96)) lower odds of heart failure at 1 year. There were no statistically significant gender differences in 1-year stroke/transient ischaemic attack/arterial thromboembolism and major bleeding events. Conclusion In a ‘real-world’ European AF registry, women were more symptomatic but less likely to receive invasive rhythm control therapy such as electrical cardioversion or ablation. Further study is needed to confirm that these differences do not disadvantage women with AF

Risk Factors, Subsequent Disease Onset, and Prognostic Impact of Myocardial Infarction and Atrial Fibrillation

BACKGROUND: Although myocardial infarction (MI) and atrial fibrillation (AF) are frequent comorbidities and share common cardiovascular risk factors, the direction and strength of the association of the risk factors with disease onset, subsequent disease incidence, and mortality are not completely understood. METHODS AND RESULTS: In pooled multivariable Cox regression analyses, we examined temporal relations of disease onset and identified predictors of MI, AF, and all-cause mortality in 108 363 individuals (median age, 46.0 years; 48.2% men) free of MI and AF at baseline from 6 European population-based cohorts. During a maximum follow-up of 10.0 years, 3558 (3.3%) individuals were diagnosed exclusively with MI, 1922 (1.8%) with AF but no MI, and 491 (0.5%) individuals developed both MI and AF. Association of sex, systolic blood pressure, antihypertensive treatment, and diabetes appeared to be stronger with incident MI than with AF, whereas increasing age and body mass index showed a higher risk for incident AF. Total cholesterol and daily smoking were significantly related to incident MI but not AF. Combined population attributable fraction of cardiovascular risk factors was >70% for incident MI, whereas it was only 27% for AF. Subsequent MI after AF (hazard ratio [HR], 1.68; 95% CI, 1.03–2.74) and subsequent AF after MI (HR, 1.75; 95% CI, 1.31–2.34) both significantly increased overall mortality risk. CONCLUSIONS: We observed different associations of cardiovascular risk factors with both diseases indicating distinct pathophysiological pathways. Subsequent diagnoses of MI and AF significantly increased mortality risk

Comparison of Cardiovascular Risk Factors in European Population Cohorts for Predicting Atrial Fibrillation and Heart Failure, Their Subsequent Onset, and Death

Background: Differences in risk factors for atrial fibrillation (AF) and heart failure (HF) are incompletely understood. Aim of this study was to understand whether risk factors and biomarkers show different associations with incident AF and HF and to investigate predictors of subsequent onset and mortality. Methods and Results: In N=58 693 individuals free of AF/HF from 5 population-based European cohorts, Cox regressions were used to find predictors for AF, HF, subsequent onset, and mortality. Differences between associations were estimated using bootstrapping. Median follow-up time was 13.8 years, with a mortality of 15.7%. AF and HF occurred in 5.0% and 5.4% of the participants, respectively, with 1.8% showing subsequent onset. Age, male sex, myocardial infarction, body mass index, and NT-proBNP (N-terminal pro-B-type natriuretic peptide) showed similar associations with both diseases. Antihypertensive medication and smoking were stronger predictors of HF than AF. Cholesterol, diabetes mellitus, and hsCRP (high-sensitivity C-reactive protein) were associated with HF, but not with AF. No variable was exclusively associated with AF. Population-attributable risks were higher for HF (75.6%) than for AF (30.9%). Age, male sex, body mass index, diabetes mellitus, and NT-proBNP were associated with subsequent onset, which was associated with the highest all-cause mortality risk. Conclusions: Common risk factors and biomarkers showed different associations with AF and HF, and explained a higher proportion of HF than AF risk. As the subsequent onset of both diseases was strongly associated with mortality, prevention needs to be rigorously addressed and remains challenging, as conventional risk factors explained o:nly 31% of AF risk

Application of non-HDL cholesterol for population-based cardiovascular risk stratification: results from the Multinational Cardiovascular Risk Consortium.

BACKGROUND: The relevance of blood lipid concentrations to long-term incidence of cardiovascular disease and the relevance of lipid-lowering therapy for cardiovascular disease outcomes is unclear. We investigated the cardiovascular disease risk associated with the full spectrum of bloodstream non-HDL cholesterol concentrations. We also created an easy-to-use tool to estimate the long-term probabilities for a cardiovascular disease event associated with non-HDL cholesterol and modelled its risk reduction by lipid-lowering treatment. METHODS: In this risk-evaluation and risk-modelling study, we used Multinational Cardiovascular Risk Consortium data from 19 countries across Europe, Australia, and North America. Individuals without prevalent cardiovascular disease at baseline and with robust available data on cardiovascular disease outcomes were included. The primary composite endpoint of atherosclerotic cardiovascular disease was defined as the occurrence of the coronary heart disease event or ischaemic stroke. Sex-specific multivariable analyses were computed using non-HDL cholesterol categories according to the European guideline thresholds, adjusted for age, sex, cohort, and classical modifiable cardiovascular risk factors. In a derivation and validation design, we created a tool to estimate the probabilities of a cardiovascular disease event by the age of 75 years, dependent on age, sex, and risk factors, and the associated modelled risk reduction, assuming a 50% reduction of non-HDL cholesterol. FINDINGS: Of the 524 444 individuals in the 44 cohorts in the Consortium database, we identified 398 846 individuals belonging to 38 cohorts (184 055 [48·7%] women; median age 51·0 years [IQR 40·7-59·7]). 199 415 individuals were included in the derivation cohort (91 786 [48·4%] women) and 199 431 (92 269 [49·1%] women) in the validation cohort. During a maximum follow-up of 43·6 years (median 13·5 years, IQR 7·0-20·1), 54 542 cardiovascular endpoints occurred. Incidence curve analyses showed progressively higher 30-year cardiovascular disease event-rates for increasing non-HDL cholesterol categories (from 7·7% for non-HDL cholesterol <2·6 mmol/L to 33·7% for ≥5·7 mmol/L in women and from 12·8% to 43·6% in men; p<0·0001). Multivariable adjusted Cox models with non-HDL cholesterol lower than 2·6 mmol/L as reference showed an increase in the association between non-HDL cholesterol concentration and cardiovascular disease for both sexes (from hazard ratio 1·1, 95% CI 1·0-1·3 for non-HDL cholesterol 2·6 to <3·7 mmol/L to 1·9, 1·6-2·2 for ≥5·7 mmol/L in women and from 1·1, 1·0-1·3 to 2·3, 2·0-2·5 in men). The derived tool allowed the estimation of cardiovascular disease event probabilities specific for non-HDL cholesterol with high comparability between the derivation and validation cohorts as reflected by smooth calibration curves analyses and a root mean square error lower than 1% for the estimated probabilities of cardiovascular disease. A 50% reduction of non-HDL cholesterol concentrations was associated with reduced risk of a cardiovascular disease event by the age of 75 years, and this risk reduction was greater the earlier cholesterol concentrations were reduced. INTERPRETATION: Non-HDL cholesterol concentrations in blood are strongly associated with long-term risk of atherosclerotic cardiovascular disease. We provide a simple tool for individual long-term risk assessment and the potential benefit of early lipid-lowering intervention. These data could be useful for physician-patient communication about primary prevention strategies. FUNDING: EU Framework Programme, UK Medical Research Council, and German Centre for Cardiovascular Research

Age-specific atrial fibrillation incidence, attributable risk factors and risk of stroke and mortality: results from the MORGAM Consortium

BackgroundThe main aim was to examine age-specific risk factor associations with incident atrial fibrillation (AF) and their attributable fraction in a large European cohort. Additionally, we aimed to examine risk of stroke and mortality in relation to new-onset AF across age.MethodsWe used individual-level data (n=66 951, 49.1% men, age range 40–98 years at baseline) from five European cohorts of the MOnica Risk, Genetics, Archiving and Monograph Consortium. The participants were followed for incident AF for up to 10 years and the association with modifiable risk factors from the baseline examinations (body mass index (BMI), hypertension, diabetes, daily smoking, alcohol consumption and history of stroke and myocardial infarction (MI)) was examined. Additionally, the participants were followed up for incident stroke and all-cause mortality after new-onset AF.ResultsAF incidence increased from 0.9 per 1000 person-years at baseline age 40–49 years, to 17.7 at baseline age ≥70 years. Multivariable-adjusted Cox models showed that higher BMI, hypertension, high alcohol consumption and a history of stroke or MI were associated with increased risk of AF across age groups (pConclusionIn this large European cohort aged 40 years and above, risk of AF was largely attributed to BMI, high alcohol consumption and a history MI or stroke from middle age. Thus, preventive measures for AF should target risk factors such as obesity and hypertension from early age and continue throughout life.Data availability statementThe data are not available in a public repository. Access to the data is restricted by the ethical approvals and the legislation of the European Union and the countries of each MORGAM study. Approval by the Principal Investigator of each cohort study and the MORGAM/BiomarCaRE Steering Group will be required for release of the data. The MORGAM Manual at https://www.thl.fi/publications/morgam/manual/contents.htm gives more information on access to the data.</p

Candidate gene prioritization by network analysis of differential expression using machine learning approaches

<p>Abstract</p> <p>Background</p> <p>Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals.</p> <p>To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network.</p> <p>Results</p> <p>We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (<it>Simple Expression Ranking</it>). Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the <it>Heat Kernel Diffusion Ranking </it>leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%.</p> <p>Conclusion</p> <p>In this study we could identify promising candidate genes using network based machine learning approaches even if no knowledge is available about the disease or phenotype.</p

Cross-Sectional Associations between Homoarginine, Intermediate Phenotypes, and Atrial Fibrillation in the CommunityThe Gutenberg Health Study

Homoarginine has come into the focus of interest as a biomarker for cardiovascular disease. Atrial fibrillation (AF) causes a substantial increase in morbidity and mortality. Whether circulating homoarginine is associated with occurrence or persistence of AF and may serve as a new predictive biomarker remains unknown. We measured plasma levels of homoarginine in the population-based Gutenberg health study (3761 patients included, of them 51.7% males), mean age 55.6 +/- 10.9 years-old. Associations between homoarginine and intermediate electrocardiographic and echocardiographic phenotypes and manifest AF were examined. Patients with AF (124 patients, of them 73.4% males) had a mean age 64.8 +/- 8.6 years-old compared to a mean age of 55.3 +/- 10.9 in the population without AF (p-value < 0.001) and showed a less beneficial risk factor profile. The median homoarginine levels in individuals with and without AF were 1.9 mol/L (interquartile range (IQR) 1.5-2.5) and 2.0 mol/L (IQR 1.5-2.5), respectively, p = 0.56. In multivariable-adjusted regression analyses homoarginine was not statistically significantly related to electrocardiographic variables. Among echocardiographic variables beta per standard deviation increase was -0.12 (95% confidence interval (CI) -0.23-(-0.02);p = 0.024) for left atrial area and -0.01 (95% CI -0.02-(-0.003);p = 0.013) for E/A ratio. The odds ratio between homoarginine and AF was 0.91 (95% CI 0.70-1.16;p = 0.45). In our large, population-based cross-sectional study, we did not find statistically significant correlations between lower homoarginine levels and occurrence or persistence of AF or most standard electrocardiographic phenotypes, but some moderate inverse associations with echocardiographic left atrial size and E/A. Homoarginine may not represent a strong biomarker to identify individuals at increased risk for AF. Further investigations will be needed to elucidate the role of homoarginine and cardiac function

An arrhythmogenic metabolite in atrial fibrillation

Abstract Background Long-chain acyl-carnitines (ACs) are potential arrhythmogenic metabolites. Their role in atrial fibrillation (AF) remains incompletely understood. Using a systems medicine approach, we assessed the contribution of C18:1AC to AF by analysing its in vitro effects on cardiac electrophysiology and metabolism, and translated our findings into the human setting. Methods and results Human iPSC-derived engineered heart tissue was exposed to C18:1AC. A biphasic effect on contractile force was observed: short exposure enhanced contractile force, but elicited spontaneous contractions and impaired Ca2+ handling. Continuous exposure provoked an impairment of contractile force. In human atrial mitochondria from AF individuals, C18:1AC inhibited respiration. In a population-based cohort as well as a cohort of patients, high C18:1AC serum concentrations were associated with the incidence and prevalence of AF. Conclusion Our data provide evidence for an arrhythmogenic potential of the metabolite C18:1AC. The metabolite interferes with mitochondrial metabolism, thereby contributing to contractile dysfunction and shows predictive potential as novel circulating biomarker for risk of AF

Risk Factors, Subsequent Disease Onset, and Prognostic Impact of Myocardial Infarction and Atrial Fibrillation

Background Although myocardial infarction (MI) and atrial fibrillation (AF) are frequent comorbidities and share common cardiovascular risk factors, the direction and strength of the association of the risk factors with disease onset, subsequent disease incidence, and mortality are not completely understood.Methods and Results In pooled multivariable Cox regression analyses, we examined temporal relations of disease onset and identified predictors of MI, AF, and all-cause mortality in 108 363 individuals (median age, 46.0 years; 48.2% men) free of MI and AF at baseline from 6 European population-based cohorts. During a maximum follow-up of 10.0 years, 3558 (3.3%) individuals were diagnosed exclusively with MI, 1922 (1.8%) with AF but no MI, and 491 (0.5%) individuals developed both MI and AF. Association of sex, systolic blood pressure, antihypertensive treatment, and diabetes appeared to be stronger with incident MI than with AF, whereas increasing age and body mass index showed a higher risk for incident AF. Total cholesterol and daily smoking were significantly related to incident MI but not AF. Combined population attributable fraction of cardiovascular risk factors was >70% for incident MI, whereas it was only 27% for AF. Subsequent MI after AF (hazard ratio [HR], 1.68; 95% CI, 1.03-2.74) and subsequent AF after MI (HR, 1.75; 95% CI, 1.31-2.34) both significantly increased overall mortality risk.Conclusions We observed different associations of cardiovascular risk factors with both diseases indicating distinct pathophysiological pathways. Subsequent diagnoses of MI and AF significantly increased mortality risk.</p

Temporal relations between atrial fibrillation and ischaemic stroke and their prognostic impact on mortality

AimsLimited evidence is available on the temporal relationship between atrial fibrillation (AF) and ischaemic stroke and their impact on mortality in the community. We sought to understand the temporal relationship of AF and ischaemic stroke and to determine the sequence of disease onset in relation to mortality.Methods and resultsAcross five prospective community cohorts of the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) project we assessed baseline cardiovascular risk factors in 100 132 individuals, median age 46.1 (25th–75th percentile 35.8–57.5) years, 48.4% men. We followed them for incident ischaemic stroke and AF and determined the relation of subsequent disease diagnosis with overall mortality. Over a median follow-up of 16.1 years, N = 4555 individuals were diagnosed solely with AF, N = 2269 had an ischaemic stroke but no AF diagnosed, and N = 898 developed both, ischaemic stroke and AF. Temporal relationships showed a clustering of diagnosis of both diseases within the years around the diagnosis of the other disease. In multivariable-adjusted Cox regression analyses with time-dependent covariates subsequent diagnosis of AF after ischaemic stroke was associated with increased mortality [hazard ratio (HR) 4.05, 95% confidence interval (CI) 2.17–7.54; P P ConclusionThe temporal relations of ischaemic stroke and AF appear to be bidirectional. Ischaemic stroke may precede detection of AF by years. The subsequent diagnosis of both diseases significantly increases mortality risk. Future research needs to investigate the common underlying systemic disease processes.</p