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W2109689229 abstract "HomeCirculationVol. 125, No. 20Novel Risk Factors for Atrial Fibrillation Free AccessReview ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessReview ArticlePDF/EPUBNovel Risk Factors for Atrial FibrillationUseful for Risk Prediction and Clinical Decision Making? Michiel Rienstra, MD, PhD, David D. McManus, MD and Emelia J. Benjamin, MD, ScM Michiel RienstraMichiel Rienstra From the Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (M.R.); National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA (D.D.M., E.J.B.); Cardiac Electrophysiology Section, Department of Medicine, University of Massachusetts Medical School, Worcester, MA (D.D.M.); Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA (D.D.M.); Cardiology Section, Department of Medicine, Boston University School of Medicine, Boston, MA (E.J.B.); Preventive Medicine Section, Department of Medicine, Boston University School of Medicine, Boston, MA (E.J.B.); and Epidemiology Department, Boston University School of Public Health, Boston, MA (E.J.B.). Search for more papers by this author , David D. McManusDavid D. McManus From the Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (M.R.); National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA (D.D.M., E.J.B.); Cardiac Electrophysiology Section, Department of Medicine, University of Massachusetts Medical School, Worcester, MA (D.D.M.); Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA (D.D.M.); Cardiology Section, Department of Medicine, Boston University School of Medicine, Boston, MA (E.J.B.); Preventive Medicine Section, Department of Medicine, Boston University School of Medicine, Boston, MA (E.J.B.); and Epidemiology Department, Boston University School of Public Health, Boston, MA (E.J.B.). Search for more papers by this author and Emelia J. BenjaminEmelia J. Benjamin From the Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (M.R.); National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA (D.D.M., E.J.B.); Cardiac Electrophysiology Section, Department of Medicine, University of Massachusetts Medical School, Worcester, MA (D.D.M.); Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA (D.D.M.); Cardiology Section, Department of Medicine, Boston University School of Medicine, Boston, MA (E.J.B.); Preventive Medicine Section, Department of Medicine, Boston University School of Medicine, Boston, MA (E.J.B.); and Epidemiology Department, Boston University School of Public Health, Boston, MA (E.J.B.). Search for more papers by this author Originally published22 May 2012https://doi.org/10.1161/CIRCULATIONAHA.112.112920Circulation. 2012;125:e941–e946IntroductionAtrial fibrillation (AF) is the most common cardiac arrhythmia; the lifetime risk is 1 in 4 for persons over the age of 40 years in the United States.1 AF is associated with an increased risk of death, dementia, heart failure, and stroke.2–5 AF leads to high healthcare system utilization rates.6 Based on current US age- and sex-specific prevalence data, the national incremental AF cost in 2010 is estimated to range from $6.0 to $26.0 billion.7Risk factors for AF are diverse8 and include advancing age, male sex, diabetes mellitus, hypertension, valvular disease, myocardial infarction, heart failure, obesity, elevated inflammatory marker concentrations, and PR-interval prolongation, as recently reviewed elsewhere.9 Risk prediction models are important to define individual risk for AF, to identify novel risk factors for AF, to identify and assess potential targets of therapy, and to enhance the cost-effective implementation of therapies for both primary and secondary prevention of AF.10 A recently published risk score for the development of AF based on the established cardiovascular risk factors accounted for only part of the AF risk (C-statistic 0.76).11 Thus, although many risk factors for AF have been described, a substantial proportion of AF risk still remains unexplained.In the past years, multiple novel AF risk factors have been studied. In the present review, we aim to describe recently described risk factors and will underscore that substantial efforts are needed to incorporate novel markers of AF into risk prediction models. Efforts to optimize risk prediction models and prevention algorithms are useful for risk communication, patient motivation, and clinical decision making.10Familial Aggregation, Ethnic Differences, and Genetics of AFFamilial AggregationIn recent years, increasing data have been reported supporting the notion that AF in the general population is heritable. Diverse population-based studies have demonstrated that familial clustering of AF is common. In 1 such study, Framingham Heart Study investigators reported that a parental history of AF doubled the risk of AF in offspring,12 and that a family history of AF improved risk prediction of AF.13 An analysis of 1137 same-sex twin pairs (356 monozygotic and 781 dizygotic pairs) in which one or both members were diagnosed with AF from the Danish Twin Registry found that concordance rates were twice as high for monozygotic pairs as for dizygotic pairs (22.0% versus 11.6%, P<0.0001).14Ethnic DifferencesDespite having a higher burden of traditional AF risk factors, blacks appear to be at lower risk of AF than whites.15 To determine whether genetic differences were responsible, Marcus et al16 investigated European ancestry as an independent risk factor for AF. The authors compared AF risk in whites (n=4543) and blacks (n=822) in the Cardiovascular Health Study, and in whites (n=10 902) and blacks (n=3517) in the Atherosclerosis Risk in Communities Study, as well. Percentage of European ancestry in blacks was estimated with ancestry-informative markers from the 2 different genetic analysis arrays. After adjustment for potential confounders, European ancestry remained a predictor of incident AF in each cohort alone, with a combined estimated hazard ratio (HR) for AF of 1.17 (95% CI, 1.07–1.29; P=0.001) for each 10% increase in European ancestry.16Common Genetic VariantsBy building on data showing that AF was heritable, several published investigations have convincingly demonstrated a genetic component to AF. Before high-throughput genotyping techniques and genome-wide association studies, candidate-gene studies screened genes for causative mutations based on assumptions regarding their pathophysiological role and found several single-nucleotide polymorphisms in ion channels, gap junction proteins, atrial natriuretic peptide, inflammatory mediators, and renin-angiotensin-aldosterone system genes that appeared to relate to AF. Perhaps because of the relatively small sample sizes and heterogeneous nature of the candidate gene studies, only a few of the single-nucleotide polymorphisms associated with AF in candidate-gene studies could be replicated in additional independent cohorts.17,18Genome-wide association studies have successfully identified 3 genetic loci (4q25 near transcription factor PITX2,19,20 and 16q22 near ZFHX3,21 and 1q21 at the small-conductance calcium-activated potassium channel KCNN322), all pointing toward novel pathways not previously known to be involved in AF. The PITX2 locus encodes a homeobox transcription factor of the paired type, previously identified to be of importance for the formation of embryonic pulmonary myocardial cells, necessary for pulmonary myocardial sleeves development, and for the formation of a sinus node in the left atrium.23,24As follow-up of genome-wide association studies, Lubitz and colleagues did fine mapping of the 4q25 locus near PITX2 and genotyped 34 haplotype-tagging single-nucleotide polymorphisms in 790 case and 1177 control subjects from Massachusetts General Hospital and tested for association with AF.25 Results were replicated in 5066 cases and 30 661 controls from the German Competence Network for Atrial Fibrillation, Atherosclerosis Risk In Communities Study, Cleveland Clinic Lone AF Study, Cardiovascular Health Study, and Rotterdam Study. Lubitz et al25 found 2 novel AF susceptibility signals on chromosome 4q25. Considering the multiple susceptibility signals at the chromosome 4q25 locus identified individuals with increased risk of AF.In the past 2 years, experimental and human studies have increased the understanding of PITX2 in adult hearts and its relation with AF. Wang et al26 studied postnatal mice and found that PITX2c is expressed in left atria, pulmonary veins, and right ventricles and that PITX2c-deficient mice are predisposed to atrial arrhythmias. Kirchhof et al27 studied human atrial tissues and found higher PITX2 expression levels in the left atrium than in the right atrium or ventricles. Compared with the wild type, PITX2c heterozygous mice had shorter atrial action potential durations in comparison with the wild type and were susceptible to AF induced by pacing, whereas no differences in cardiac morphology were observed.27 Chinchilla et al28 used atrial tissue samples of 47 permanent AF patients, and 100 controls undergoing cardiac surgery, and found PITX2c expression significantly decreased in human patients with permanent AF. Additional characterization of chamber-specific Pitx2 conditional mouse mutants, displaying a ≈60% reduction of Pitx2 expression, provided an illuminating experimental model of Pitx2 insufficiency. Studies using this mouse model revealed that atrial, but not ventricular, chamber-specific deletion of Pitx2 results in differences in the action potential amplitude and resting membrane potential in the adult heart, and ECG characteristics consistent with atrioventricular block, as well. Lack of Pitx2 in atrial myocardium impairs sodium channel and potassium channel expression, mediated in part by miRNA misexpression.28Experimental analysis of the small-conductance calcium-activated potassium channels, previously not considered as important cardiac ion channels, demonstrated that these channels are expressed in human hearts and are more important in atria than in ventricles.29 Previous investigations suggested that the small-conductance calcium-activated potassium channels are of importance for atrial repolarization and AF.30 Diness and colleagues31 demonstrated that using 3 different inhibitors of the small-conductance calcium-activated potassium channels prolongs atrial effective refractory period without affecting QT interval and prevents and terminates AF in both ex vivo and in vivo experiments.Early-Life Antecedents of AFEarly-life antecedents such as low birth weight32 and childhood socioeconomic status,33 have been related to hypertension, diabetes mellitus, obesity, heart failure, coronary artery disease, stroke, and overall mortality. A recent analysis of the Women's Health Study included 27 982 healthy women.34 Information on birth weight was categorized into 5 different categories. They observed that increasing birth weight category was significantly associated with incident AF.34Subclinical Risk Factors for AFPericardial FatObesity is an important risk factor for AF. Pericardial fat is an ectopic fat deposit in close proximity of the heart and shares blood supply with the cardiac microcirculation.35 Pericardial fat is highly metabolically active36 and may be a pathway by which obesity increases the risk of AF. Framingham Heart Study investigators studied 3217 participants with multislice computed tomography and quantified adipose tissue volumes.37 Pericardial fat, in contrast to intrathoracic or visceral abdominal fat, was associated with prevalent AF, even after adjustment for AF risk factors, including body mass index.37 Batal and colleagues38 specifically studied left atrium epicardial fat pad thickness by multislice computed tomography in 73 individuals without AF, 60 with paroxysmal AF, and 36 with persistent AF. They reported that increased posterior left atrial fat thickness appears to be associated with AF burden independent of age, body mass index, or left atrial area.38Blood Pressure in Nonhypertensive RangeHypertension, defined as use of antihypertensive medication or blood pressures >140/90 mm Hg, is the most prevalent risk factor for AF, but data regarding the risk of AF at lower blood pressure levels are sparse. An analysis of 34 221 women participating in the Women's Health Study showed that blood pressure was strongly associated with incident AF, and systolic blood pressure was more strongly related to AF incidence than diastolic blood pressure.39 Systolic blood pressure levels within the nonhypertensive range were associated with incident AF, even after accounting for blood pressure changes over time.39Left Ventricular Diastolic DysfunctionAtrial fibrillation and left ventricular diastolic dysfunction share multiple risk factors, including aging and hypertension.40 Because diastolic dysfunction causes atrial pressure and volume overload, atrial structural remodeling is common among patients with abnormal diastolic parameters. An early Framingham Heart Study report demonstrated that the ratio of echocardiographically measured velocity-time integrals of the Doppler mitral valve inflow early (E-wave) and late (A-wave) diastolic filling waves, and the E-wave deceleration time, were markers of increased risk of AF.41 More recently, investigators of the Cardiovascular Health Study examined echocardiographic parameters of diastolic function in 4480 older adults and reported that Doppler peak E-wave velocity and left atrial diameter were positively and nonlinearly associated, and Doppler A-wave velocity time integral displayed a U-shaped relationship with the risk of AF.42 Vogel et al43 described the natural history of 388 participants of the Rochester Epidemiology Project with diastolic dysfunction without signs or symptoms of heart failure. Over the course mean 3.9 years, 52 participants developed AF.Subclinical Coronary Artery DiseaseMyocardial infarction is a risk factor for AF. Diagnosis of coronary artery disease is generally based on the presence or history of acute coronary syndrome or myocardial infarction. Nucifora et al,44 however, used multislice computed tomography to detect asymptomatic coronary artery disease. They compared 150 patients with AF without known coronary artery disease with 148 patients without AF but with similar demographic and clinical characteristics, including pretest likelihood for coronary artery disease. Eighteen percent of patients with AF were classified as having no coronary artery disease by multislice computed tomography, whereas 41% showed nonobstructive coronary artery disease, and the remaining 41% had obstructive coronary artery disease (P=0.01 compared with patients without AF).44Clinical Risk Factors for AFPhysical ActivityRegular physical activity is well known to have a beneficial effect on many cardiovascular risk factors. Physical activity is associated with a 3 to 5 mm Hg reduction in systolic blood pressure,45 a reduction in body weight and body mass index,46 and the prevention of coronary heart disease,47 suggesting that exercise may reduce the incidence of AF. On the other hand, data suggest that excessive exercise may increase the risk for AF.48 Investigators from the Women's Health Study followed 34 759 women who reported their leisure-time physical activity for the occurrence of AF. They found that women who achieved the federal government's recommendation of 7.5 metabolic equivalent-hour/wk of physical activity were at reduced risk of AF in comparison with those who did not (hazard ratio [HR], 0.86; 95% confidence interval [CI], 0.75–0.98; P=0.03), but this association was attenuated by body mass index.49 Comparable results were published by the Cardiovascular Health study in older adults.50Chronic Kidney DiseasePatients with chronic kidney disease are at higher risk for coronary heart disease and heart failure.51 Chronic kidney disease is associated hypertension, left ventricular hypertrophy, and systemic inflammation.51 Because many of these cardiovascular risk factors and diseases have been associated with AF, Alonso et al52 sought to examine the risk between chronic kidney disease and AF in 10 328 men and women from the Atherosclerosis Risk in Communities study. They found that reduced kidney function and presence of albuminuria were strongly associated with the incidence of AF, during 10 years follow-up, accounting for other risk factors. Baber et al53 followed 26 917 participants in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study and found similar results; regardless of severity, chronic kidney disease was associated with an increased prevalence of AF.Biomarkers of AFBiomarkers are potential novel instruments to enhance AF risk prediction and to provide insights into the pathophysiology of the disease, and may help to identify novel targets for therapy. Recently, B-type natriuretic peptide (BNP) was investigated as a biomarker for incident AF. Although most widely used as a marker of heart failure, elevated BNP levels have been reported in patients with AF.54,55 In the Cardiovascular Health Study, a community-based population of 5445 older adults, N-terminal proBNP was a strong predictor of incident AF, adjusting for other risk factor (adjusted HR, 4.0; 95% CI, 3.2–5.0; P<0.001).56Previously, multiple biomarkers have been studied in relation to AF, but their predictive ability remains uncertain. Schnabel et al57 chose a panel of 10 candidate AF biomarkers aiming to represent distinct pathophysiological pathways, including inflammation (C-reactive protein and fibrinogen), neurohormonal activation (BNP and N-terminal proatrial natriuretic peptide), oxidative stress and endothelial dysfunction (homocysteine), the renin-angiotensin-aldosterone system (renin and aldosterone), thrombosis and endothelial function (d-dimer and plasminogen activator inhibitor type 1), and microvascular damage (urinary albumin excretion). In 3120 Framingham Heart Study participants, they found that the biomarker panel was associated with incident AF (P<0.0001). In stepwise-selection models, log-transformed BNP (HR per SD, 1.62, 95% CI, 1.41–1.85, P<0.0001) and C-reactive protein (HR, 1.25, 95% CI, 1.07–1.45, P=0.004) remained associated with AF after multivariable adjustment. Adding BNP and C-reactive protein, separately and together, to an AF risk score based on clinical covariates revealed that only BNP improved risk stratification beyond well-established clinical risk factors.57Blood lipids are established risk factors for coronary artery disease, which may precede incident AF. Limited and inconsistent data exist on the association of triglycerides, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with incident AF. Recently, investigators of the Atherosclerosis Risk in Communities study reported that higher concentrations of low-density lipoprotein cholesterol and total cholesterol were associated with a lower incidence of AF, although the mechanisms linking lipids to AF remain uncertain. No association between high-density lipoprotein cholesterol and triglycerides with incident AF was found.58Long-chain n-3 polyunsaturated fatty acids may reduce the risk of AF as was previously shown in experimental studies. Prior human studies evaluating fish or n-3 polyunsaturated fatty acids consumption from dietary questionnaires and incident AF have reported conflicting results. The Cardiovascular Health Study investigated the association of circulating levels of n-3 polyunsaturated fatty acids (eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid) and incident AF. They found that higher circulating total long-chain n-3 polyunsaturated fatty acids and docosahexaenoic acid levels were associated with lower risk of incident AF.59ConclusionsAs with other forms of cardiovascular disease, more than half of the AF burden is potentially preventable.60 Adequate risk assessment is therefore of utmost importance to improve primary and secondary prevention of AF and its consequences.61 However, the traditional risk factors for AF do not explain all cases of AF. Present risk stratification tools for AF are an important step forward, but are far from optimal. In recent years, investigators have learned more about the pathophysiology of AF, and multiple studies have demonstrated a role for heritability and genetics, early antecedents, preclinical risk factors, and circulating biomarkers in the development of AF. Future research is needed to determine the extent to which novel risk factors are associated with AF in racial and ethnic minorities. Data are also needed as to the extent to which novel risk factors improve existing AF risk prediction models over traditional cardiovascular disease risk factors to better identify patients at risk for AF to target for disease prevention.62 We are embarking on an exciting chapter in AF risk prediction and prevention, because novel AF biomarkers better identify patients at risk for AF and identify potential targets of therapy, enabling more personalized and targeted AF risk reduction.10Sources of FundingThis work was supported by grants from the NIH to Dr Benjamin (1R01HL092577; 1R01HL102214; 1RC1HL101056).DisclosuresNone.FootnotesCorrespondence to Michiel Rienstra, MD, PhD, Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, The Netherlands. E-mail m.[email protected]nlReferences1. Lloyd-Jones DM, Wang TJ, Leip EP, Larson MG, Levy D, Vasan RS, D'Agostino RB, Massaro JM, Beiser A, Wolf PA, Benjamin EJ. Lifetime risk for development of atrial fibrillation: the Framingham heart study. Circulation.2004; 110: 1042– 1046. LinkGoogle Scholar2. Kannel WB, Wolf PA, Benjamin EJ, Levy D. Prevalence, incidence, prognosis, and predisposing conditions for atrial fibrillation: population-based estimates. Am J Cardiol.1998; 82: 2N–9N. CrossrefMedlineGoogle Scholar3. Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham study. Stroke.1991; 22: 983– 988. LinkGoogle Scholar4. Benjamin EJ, Wolf PA, D'Agostino RB, Silbershatz H, Kannel WB, Levy D. Impact of atrial fibrillation on the risk of death: the Framingham heart study. Circulation.1998; 98: 946– 952. LinkGoogle Scholar5. Piccini JP, Hammill BG, Sinner MF, Jensen PN, Hernandez AF, Heckbert SR, Benjamin EJ, Curtis LH. Incidence and prevalence of atrial fibrillation and associated mortality among Medicare beneficiaries, 1993–2007.Circ Cardiovasc Qual Outcomes. 2012; 5: 85– 93. 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Ellinor PT, Lunetta KL, Glazer NL, Pfeufer A, Alonso A, Chung MK, Sinner MF, de Bakker PI, Mueller M, Lubitz SA, Fox E, Darbar D, Smith NL, Smith JD, Schnabel RB, Soliman EZ, Rice KM, Van Wagoner DR, Beckmann BM, van Noord C, Wang K, Ehret GB, Rotter JI, Hazen SL, Steinbeck G, Smith AV, Launer LJ, Harris TB, Makino S, Nelis M, Milan DJ," @default.
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W2109689229 title "Novel Risk Factors for Atrial Fibrillation" @default.
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W2109689229 doi "https://doi.org/10.1161/circulationaha.112.112920" @default.
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