Published online before print November 24, 2008, doi: 10.1161/CIRCULATIONAHA.108.814418
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(Circulation. 2008;118:2555-2562.)
© 2008 American Heart Association, Inc.
Stroke |
Plasma Fetuin-A Levels and the Risk of Myocardial Infarction and Ischemic Stroke
From the Departments of Epidemiology (C.W., M.B.S., T.P., H.B.) and Pharmacology (H.J.), German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; Institute for Social Medicine, Epidemiology, and Health Economics, Charité University Medicine Berlin, Berlin, Germany (C.W.); Department of Internal Medicine, Division of Endocrinology, Diabetology, Nephrology, Vascular Disease, and Clinical Chemistry, University of Tübingen, Tübingen, Germany (N.S., H.H., A.F.); Public Health Nutrition Unit, Technische Universität München, München, Germany (M.B.S.); and Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany (K.B.).
Correspondence to Cornelia Weikert, MD, MPH, Department of Epidemiology, German Institute of Human Nutrition, Arthur-Scheunert-Allee 114-116, D-14558 Nuthetal, Germany. E-mail Weikert{at}dife.de
Received May 29, 2008; accepted September 29, 2008.
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Abstract |
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Background— Fetuin-A, a protein almost exclusively secreted by the liver, induces insulin resistance and subclinical inflammation in rodents. Circulating fetuin-A levels are elevated in humans with metabolic syndrome and insulin resistance, conditions that are associated with increased risk of cardiovascular disease.
Methods and Results— We investigated the association between fetuin-A levels and the risk of future myocardial infarction (MI) and ischemic stroke (IS) in a case-cohort study based on the European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam Study comprising 27 548 middle-aged subjects of the general population. Fetuin-A levels were measured in plasma of 227 individuals who developed MI, in 168 who developed IS, and in 2198 individuals who remained free of cardiovascular events during a mean follow-up of 8.2±2.2 years. Individuals in the highest compared with the lowest quintile of plasma fetuin-A had significantly increased risks of MI (relative risk, 3.80; 95% confidence interval, 2.37 to 6.10; P for trend <0.0001) and IS (relative risk, 3.93; 95% confidence interval, 2.17 to 7.12; P for trend <0.0001) after adjustment for sex and age. Additional adjustment for smoking status, body mass index, waist circumference, alcohol consumption, educational attainment, physical activity, hypertension, diabetes mellitus, total and high-density lipoprotein cholesterol, and C-reactive protein only moderately attenuated these risks (MI: relative risk, 3.25; 95% confidence interval, 2.01 to 5.28; P for trend <0.0001; IS: relative risk, 3.78; 95% confidence interval, 2.06 to 6.94; P for trend <0.0001).
Conclusions— Our data provide evidence for a link between high plasma fetuin-A levels and an increased risk of MI and IS. Therefore, more research is warranted to determine the role of fetuin-A in the pathophysiology of cardiovascular disease.
Key Words: atherosclerosis • cerebral infarction • coronary disease • risk factors
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Introduction |
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Insulin resistance, abdominal obesity, and other components of the metabolic syndrome are established risk factors of cardiovascular diseases (CVD).1 Recent evidence suggests that nonalcoholic fatty liver disease adds independently of established cardiovascular risk factors to risk of atherosclerosis and CVD.2 Nonalcoholic fatty liver disease is present in the majority of patients with the metabolic syndrome, and it is increasingly common in the general population.3 The severity of nonalcoholic fatty liver disease is related to the extent of atherosclerosis.4–6
Clinical Perspective p 2562
Fatty liver status contributes to dyslipidemia, hyperglycemia, and subclinical inflammation,2 all known as risk factors of CVD,7,8 and may induce production and secretion of other factors involved in the pathophysiology of atherosclerosis. Such a candidate is the glycoprotein fetuin-A, also referred to as 
2-Heremans-Schmid glycoprotein, which is almost exclusively expressed and secreted by the liver, particularly under hepatic steatosis.9 Fetuin-A is a natural inhibitor of the insulin-stimulated insulin receptor tyrosine kinase and was shown to induce insulin resistance in rodents.10–13 Studies in humans have demonstrated that circulating fetuin-A levels are positively associated with fat accumulation in the liver, insulin resistance, and the metabolic syndrome.9,14,15 Recently, 2 independent prospective cohort studies have shown that fetuin-A is positively associated with risk of type 2 diabetes mellitus.16,17 Besides induction of insulin resistance, recent data suggest that fetuin-A is involved in subclinical inflammation. Circulating fetuin-A correlates positively with C-reactive protein (CRP) levels in humans.15,17 Furthermore, fetuin-A was recently found to induce cytokine expression in human monocytes and to reduce the expression of the atheroprotective adipokine adiponectin in animals.18 Taken together, fetuin-A may represent a pathway linking fatty liver with cardiovascular events by inducing insulin resistance and inflammation. However, it is unclear whether fetuin-A is a predictor of CVD in humans. Therefore, we investigated the relationship between plasma levels of fetuin-A and risk of myocardial infarction (MI) as well as ischemic stroke (IS) in the large prospective European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam Study.
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Methods |
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Study Population
The EPIC-Potsdam Study is part of the large-scale Europe-wide prospective cohort study EPIC and includes 27 548 individuals (16 644 women and 10 904 men). Participants were recruited between 1994 and 1998 from the general population with the preferred ages 35 to 65 years in women and 40 to 65 years in men. The recruitment process was based on addresses from general population registries.19 The baseline examination included standardized blood pressure measurements, anthropometric measurements, self-administered questionnaires on diet and lifestyle, PC-guided interviews including questions about prevalent diseases, and blood sampling. Blood was collected from 95% of participants at the Potsdam center. All participants gave written informed consent, and the Ethics Committee of the Federal State Brandenburg approved all study procedures. Information on incident diseases and changes in lifestyle is assessed biennially by self-administered questionnaires.20 Response rates for all follow-up rounds thus far have exceeded 90% at each occasion.
After exclusion of subjects with a history of MI or stroke at baseline, we identified 269 individuals with incident MI and 246 individuals with incident stroke (199 IS, 41 hemorrhagic strokes, and 6 strokes with undefined pathogenesis) during a mean follow-up of 8.2±2.2 years. Nonischemic strokes were not considered cases. Of 5 individuals who had both MI and IS, we considered only the first event, leaving 463 incident CVD (267 MI and 196 IS) cases. For the present analysis, 68 CVD (40 MI and 28 IS) cases had to be excluded because blood specimens were not available or follow-up data or biomarker measurements were missing. Excluded cases did not differ considerably from included cases in baseline characteristics (Table I in the online-only Data Supplement).
The association of fetuin-A levels with risk of MI and IS was analyzed with a case-cohort design.21,22 With this type of study design, the results are expected to be generalizable to the entire cohort without the need to measure biomarker levels in the entire cohort.21,23 For these purposes, we randomly selected a subcohort of 2500 individuals from the EPIC-Potsdam Study population. Of the subcohort, 149 participants with a self-reported diagnosis of MI or stroke at baseline, lacking blood samples, or missing follow-up data were excluded from the analysis. We further excluded 101 participants for whom not all biomarkers were available, leaving a final subcohort of 2250 subjects (including 52 cases with incident MI or IS during follow-up). Thus, the final case-cohort sample consisted of 395 incident cases (227 MI and 168 IS) and 2198 participants who remained free of MI or IS during follow-up.
Ascertainment of Incident MI and Stroke
Potential cases of incident MI or stroke were identified by self-report in 1 of the 4 follow-up questionnaires or by death certificate. To increase sensitivity, the questionnaire included additional questions about typical stroke symptoms.24 All self-reports for CVD incidences were verified by contacting the patients’ attending physicians or by review of death certificates according to World Health Organization Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) criteria.25 According to the International Statistical Classification of Diseases, 10th Revision (ICD-10), cases were classified as incident MI (ICD-10 I21), IS (ICD-10 I63.0 to I63.9), intracerebral (ICD-10 I61.0 to I61.9) or subarachnoid hemorrhage (ICD-10 I60.0 to I60.9), or undetermined stroke (ICD-10 I64.0-I64.9) by 2 physicians in the study center.26 Only confirmed cases were considered for analysis.
Assessment of Risk Factors and Covariates
Lifestyle characteristics, including regular physical exercise and smoking history, were documented at baseline by trained interviewers during a PC-guided interview. Sports activity was defined as the mean time spent on leisure time physical activities during the summer and winter seasons (hours per week). Educational attainment was expressed as "vocational school or less," "technical school," and "university." "Vocational school or less" is equal to a lower education of 10 years of school education with 2 years of additional professional training. "Technical school" describes 10 years of school followed by >2 years of professional training.
Anthropometric data and blood pressure were measured by trained and quality-monitored personnel.27 Prevalent hypertension was defined as systolic blood pressure 
140 mm Hg or diastolic blood pressure 90 mm Hg or self-reporting of a diagnosis or of use of antihypertensive medication. The prevalence of diabetes mellitus at baseline was evaluated by a physician using information on self-reported medical diagnosis, medication records, and dieting behavior. In ambiguous cases, the diagnosis was confirmed by personal communication with the participant and/or treating physician. Dietary habits including alcohol consumption during the preceding year were assessed by a validated self-administered food frequency questionnaire.
Blood Collection and Laboratory Analysis
A total of 30 mL of venous blood was collected at baseline from participants at the Potsdam center; it was fractionated into serum, plasma, buffy coat, and erythrocytes and was aliquoted into straws and stored in liquid nitrogen at –196°C for conservation until the time of analysis.
All plasmas included in this analysis were transferred to the Department of Internal Medicine, University of Tübingen, on dry ice for analyses of biomarkers. Analyses of all biomarkers were performed in 2007 with the exception of adiponectin and creatinine, which were measured in 2008. Plasma levels of glucose, high-density lipoprotein (HDL) cholesterol, total cholesterol, triglycerides, high-sensitivity CRP (hs-CRP), creatinine, 
-glutamyltransferase, and fetuin-A were measured with the automatic ADVIA 1650 analyzer (Siemens Medical Solutions, Erlangen, Germany). Adiponectin was determined with an enzyme-linked immunosorbent assay from Linco Research, St Charles, Mo (intra-assay coefficient of variation, 7.6%; interassay coefficient of variation, 2.4% to 8.4%). For determination of fetuin-A, an immunoturbidimetric method was used with specific polyclonal goat anti-human fetuin-A antibodies to human fetuin-A (BioVendor Laboratory Medicine, Modreci, Czech Republic). This method was evaluated in a side-by-side comparison with an enzyme-linked immunosorbent assay (intra-assay coefficient of variation, 3.5%; interassay coefficient of variation, 5.4%; BioVendor) showing a correlation of r=0.93.9,14
Statistical Analysis
Statistical analysis was performed with the use of SAS software package, release 9.1 (SAS Institute, Cary, NC). All tests performed were 2-sided, with P<0.05 considered statistically significant. Age- and sex-adjusted baseline characteristics and mean fetuin-A levels were compared between cases and noncases with ANCOVA. Correlations between fetuin-A levels and potential cardiovascular risk factors were assessed with the Spearman age- and sex-adjusted partial correlation coefficient.
We examined the association of plasma fetuin-A levels with risk of MI, IS, and total CVD (including both end points) by calculating relative risks (RRs) using Cox proportional hazards regression, modified according to the Prentice method to account for the case-cohort design.21 With the use of this approach, participants within the subcohort are given a weight of 1 at all times, and cases outside the subcohort are assigned a weight of 1 at time of event and have weight 0 at all other times. Age was used as the underlying time variable in the counting process with entry and exit time defined as the subject’s age at recruitment and age at MI or IS diagnosis or censoring, respectively. Sex- and multivariable-adjusted RRs were calculated for quintiles of fetuin-A levels on the basis of the subcohort and for increases in fetuin-A by 1 SD. The first, crude model included age, sex, and fetuin-A levels. The second model also included smoking status (never smoker, former smoker, current smoker <20 cigarettes per day, current smoker 20 cigarettes per day), sports activity (<2 h/wk versus 2 h/wk), educational attainment (vocational school or less, technical school, university), body mass index (BMI) (continuously), waist circumference (continuously), and alcohol consumption (men: <2 g/d, 2 to 15 g/d, >15 g/d; women: <1 g/d, 1 to 7.5 g/d, >7.5 g/d), prevalent diabetes mellitus, and prevalent hypertension. The third model additionally included HDL cholesterol, total cholesterol, and log-transformed hs-CRP. The significance of linear trends across quintiles of fetuin-A was tested by assigning the median value within quintiles to each participant and modeling this value as a continuous variable. To test whether the associations of fetuin-A levels with cardiovascular events differ between MI and IS, we evaluated these relationships for fetuin-A levels on a continuous scale in a common regression model using the data augmentation method described by Lunn and McNeil.28
To further investigate the impact of important risk factors on the associations between fetuin-A levels and cardiovascular risk, we performed stratified analyses for subgroups defined by risk factor prevalence. We calculated multivariable-adjusted RR associated with an increase in fetuin-A by 1 SD according to important risk factors including the metabolic syndrome. The metabolic syndrome was defined according to the American Heart Association/National Heart, Lung, and Blood Institute definition.29 Interactions between fetuin-A and subgroups were tested with cross-product terms (subgroupxfetuin-A levels) in the fully adjusted models.
We also evaluated discrimination between subjects who did and who did not experience CVD events through receiver operating characteristic curve analysis based on logistic regression models with the area under the curve being a measure of the predictive ability.30 The difference in C statistics (with 95% confidence intervals [CIs]) after the addition of fetuin-A to a model with established risk factors was estimated with the method described by de Long et al31 with the use of SAS Macro (http://support.sas.com/kb/25/017.html).
The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.
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Results |
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Mean fetuin-A levels at baseline were higher in subjects with incident MI (mean, 246.6; SD 47.0 µg/mL; P<0.0001) or IS (mean, 242.7; SD 48.9 µg/mL; P=0.0005) than in individuals who did not develop cardiovascular events during the follow-up period (mean, 228.1; SD 52.2 µg/mL). Individuals with incident MI or IS were older and more likely to be male than individuals who remained free of CVD during follow-up. In age- and sex-adjusted analyses, individuals who developed MI or IS more often had a history of diabetes mellitus and hypertension than individuals who remained free of disease (Table 1). In contrast, differences in the incidence of diabetes mellitus did not reach statistical significance between cases of MI (4.8%; P=0.26) or cases of IS (5.5%; P=0.16) compared with subjects without cardiovascular events (3.3%) (data not shown). Individuals with MI or stroke had higher levels of triglycerides and hs-CRP and lower levels of HDL cholesterol than subjects without a cardiovascular event (Table 1).
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In sex-adjusted analyses, a weak inverse correlation was observed between fetuin-A and age. Adjusted for age and sex, fetuin-A was weakly positively correlated with total cholesterol, hs-CRP, triglycerides, and -glutamyltransferase. BMI, waist circumference, HDL cholesterol, glucose, adiponectin, and blood pressure were also significantly correlated with fetuin-A, but correlation coefficients were <0.1 (Table 2).
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Table 3 depicts the estimated RRs of MI, IS, and total CVD (including both MI and IS) across quintiles of fetuin-A levels at baseline. After adjustment for age and sex, individuals in the highest compared with the lowest quintile of fetuin-A levels had a significantly increased risk of MI (RR, 3.80; 95% CI, 2.37 to 6.10; P for trend <0.0001) and IS (RR, 3.93; 95% CI, 2.17 to 7.12; P for trend <0.0001). Further adjustment for smoking status, BMI, waist circumference, alcohol consumption, education, physical activity, hypertension, diabetes mellitus, and plasma levels of total and HDL cholesterol and hs-CRP did not appreciably change the risk estimates (MI: RR, 3.25; 95% CI, 2.01 to 5.28; P for trend <0.0001; IS: RR, 3.78; 95% CI, 2.06 to 6.94; P for trend <0.0001). We further evaluated these associations on a continuous scale. Similar to the analyses by quintiles, fetuin-A was positively related to risk of MI (fully adjusted RR per 1 SD higher fetuin-A levels, 1.59; 95% CI, 1.38 to 1.84) and risk of IS (RR, 1.49; 95% CI, 1.27 to 1.74). The additional adjustment for incident diabetes mellitus also did not change the results (data not shown). The strengths of the associations did not appreciably differ by type of cardiovascular event (MI versus IS, P for difference=0.22). Therefore, the relationship of fetuin-A levels with total CVD, including both MI and IS, was investigated further (fully adjusted RR per 1 SD higher fetuin-A levels, 1.51; 95% CI, 1.36 to 1.68) (Table 3). Further adjustment for triglycerides, glucose, -glutamyltransferase, adiponectin, or creatinine or mutual adjustment for all these biomarkers did not appreciably affect this result (Figure I in the online-only Data Supplement).
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Furthermore, we investigated whether the association of fetuin-A with risk of total CVD differed across strata of important risk factors, such as prevalence of hypertension, diabetes mellitus, or the metabolic syndrome. Table 4 shows RRs of CVD for a difference of fetuin-A levels of 1 SD in specific subgroups defined by the presence or absence of selected cardiovascular risk factors. The risk estimates remained the same across most strata. The stratified analysis for sex revealed a somewhat higher risk of CVD per increase in fetuin-A levels in women compared with men (Figure). However, the interaction term was not statistically significant (P=0.059). A significant interaction was observed between total cholesterol levels and fetuin-A (P=0.028), with stronger associations of fetuin-A with risk of CVD in subjects with cholesterol levels <200 mg/dL compared with 200 mg/dL (Table 4).
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Finally, we evaluated discrimination between subjects who did and who did not experience CVD events through receiver operating characteristic curve analysis. The C statistic for a model that included age, sex, smoking status, BMI, waist circumference, prevalent hypertension and diabetes mellitus, physical activity, alcohol intake, education, total and HDL cholesterol, and CRP was 0.7918 (95% CI, 0.7683 to 0.8154). Adding fetuin-A to the model improved the C statistic significantly to 0.8142 (95% CI, 0.7927 to 0.8357; P for difference <0.0001).
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Discussion |
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In the present study, we found that plasma fetuin-A levels predict the risk of MI and IS. This association was independent of lifestyle risk factors for CVD, such as smoking and physical activity, as well as independent of other important risk factors including diabetes mellitus, hypertension, dyslipidemia, and hs-CRP. These data support the hypothesis that fetuin-A may have a role in the pathophysiology of CVD, possibly representing a novel pathway in the development of MI and IS, that may be independent of the classic risk factors.
Our hypothesis is in agreement with previous studies showing that fetuin-A is elevated in humans with fatty liver and the metabolic syndrome.9,14,15 These conditions are strongly associated with insulin resistance.32 Fetuin-A itself was found to inhibit the insulin receptor kinase, thus inducing insulin resistance in animals.11–13 In humans, fetuin-A plasma levels predicted insulin resistance, measured by the euglycemic hyperinsulinemic clamp,9,14 and were positively associated with risk of type 2 diabetes mellitus in the EPIC-Potsdam Study and another prospective cohort study.16,17 Thus, fetuin-A may promote atherosclerosis via induction of insulin resistance. However, in the present study, the association between fetuin-A and CVD risk was largely independent of prevalent or incident diabetes mellitus and of blood glucose levels. Fetuin-A may play also a role in the pathophysiology of subclinical inflammation, thereby affecting CVD risk. This hypothesis is supported by recent findings that fetuin-A promotes cytokine expression in human monocytes.18 Interestingly, in the present study, the association between fetuin-A and the risk of MI and IS was also independent of plasma CRP and adiponectin levels. These findings indicate that at least some of the potential effects of fetuin-A on vascular function may not be mediated by these factors.
We also examined the association of fetuin-A levels with risk of CVD in several subgroups of our population. Our results suggest that especially in the group of subjects with low cholesterol levels, fetuin-A may be more strongly associated with CVD. In addition, a borderline significant interaction was found between gender and fetuin-A levels for CVD risk. Higher fetuin-A levels might be more strongly associated with a higher CVD risk in women than in men. Therefore, fetuin-A may be a promising biomarker in individuals who are traditionally regarded to have a lower risk for CVD.
Some previous studies investigating the role of fetuin-A in CVD had conflicting results. Low fetuin-A levels were found to be associated with increased cardiovascular mortality in patients with end-stage renal disease and renal replacement therapy.33 These findings seem to contradict our data. However, a single hemodialysis session has been shown to reduce fetuin-A levels,34 indicating that the observed inverse association in this group of patients may reflect the renal replacement therapy. In addition, data from a recent study including a larger number of patients with less severe impairment of renal function do not support the conclusion that low fetuin-A levels are associated with increased all-cause or cardiovascular mortality.35 Notably, adjustment for creatinine levels (that were essentially in the normal range in this study) did not influence the association between fetuin-A and risk of CVD.
Because circulating fetuin-A is a well-described inhibitor of calcification,33,36 increased vascular calcification in patients with renal disease who display low fetuin-A levels is likely to be the mechanism for increased mortality. Two additional studies mainly or exclusively performed in coronary heart disease patients suggest a relationship between low fetuin-A levels and mitral and aortic calcification and stenosis.37,38 On the other hand, an association of increased fetuin-A levels with coronary artery calcification was reported in patients with diabetic nephropathy.39 Altogether, these data indicate that the role of fetuin-A in CVD seems to be complex and modulated by various independent pathogenetic mechanisms such as calcification, inflammation, and insulin resistance.15,33
Among the strengths of our study are the prospective study design, the measurements of biomarkers that were blinded with respect to case status, and the comprehensive data on study participants allowing for adjustment for other risk factors. All cases of MI and stroke were validated by medical records. Nevertheless, some limitations of our study should be discussed. Our results are based on fetuin-A measurements from single blood samples, which might have introduced random measurement errors in determining biochemical variables. However, if anything, such random error would bias the results toward the null. The potential of residual confounding applies to our study as it does to observational studies in general. Although we adjusted for a large variety of known risk factors and biochemical variables, we cannot rule out that unmeasured factors explain our observation. The association between fetuin-A plasma levels and CVD risk was surprisingly strong. Future prospective cohort studies should evaluate whether the results can be generalized to other populations.
In conclusion, our data suggest that plasma fetuin-A levels are associated with risk of both MI and IS independently of established risk factors. Thus, fetuin-A may play a role in the pathophysiology of CVD.
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Acknowledgments |
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The authors thank all study participants for their cooperation. We gratefully acknowledge the excellent technical assistance of Anna Bury, Sabina Herbert, Albrecht Pfäfflin, and Ingo Besenthal, who were involved in the biochemical analyses. We are indebted to Manuela Bergmann and Wolfgang Fleischhauer for case ascertainment and to Ellen Kohlsdorf for data management.
Sources of Funding
The recruitment phase of the EPIC-Potsdam Study was supported by the Federal Ministry of Science, Germany (01 EA 9401), and the European Union (SOC 95201408 05F02). The follow-up of the EPIC-Potsdam Study was supported by the German Cancer Aid (70-2488-Ha I) and the European Community (SOC 98200769 05F02). Dr Stefan is currently supported by a Heisenberg grant from the Deutsche Forschungsgemeinschaft (STE 1096/1-1).
Disclosures
None.
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The online-only Data Supplement is available with this article at http://circ.ahajournals.org/cgi/content/full/CIRCULATIONAHA.108.814418/DC1.
Related Article:
Circulation 2008 118: 2485-2487.
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