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Growth-Differentiation Factor-15 for Risk Stratification in Patients With Stable and Unstable Coronary Heart Disease Results From the AtheroGene Study Tibor Kempf, MD; Jan-Malte Sinning, MD; Anja Quint, BSc; Christoph Bickel, MD; Christoph Sinning, MD; Philipp S. Wild, MD; Renate Schnabel, MD; Edith Lubos, MD; Hans J. Rupprecht, MD; Thomas Münzel, MD; Helmut Drexler, MD; Stefan Blankenberg, MD; Kai C. Wollert, MD Downloaded from http://circgenetics.ahajournals.org/ by guest on June 14, 2017 Background—Growth-differentiation factor-15 (GDF-15) is a stress-responsive transforming growth factor--related cytokine that has emerged as a prognostic biomarker in acute coronary syndrome trial populations. Its predictive role in stable coronary heart disease (CHD) has never been assessed. Methods and Results—The circulating levels of GDF-15 were measured by immunoradiometric assay in patients with stable angina pectoris (n⫽1352) or acute coronary syndrome (n⫽877) who were followed up for a median of 3.6 years. Stable angina pectoris patients presenting with normal (⬍1200 ng/L), moderately elevated (1200 to 1800 ng/L), or markedly elevated (⬎1800 ng/L) GDF-15 levels had 3.6-year CHD mortality rates of 1.4%, 2.7%, and 15.0%, respectively (P⬍0.001). By backward stepwise Cox-regression analysis, which adjusted for age and gender, clinical variables, the number of diseased vessels, renal function, the levels of C-reactive protein, cardiac troponin I, and N-terminal pro–B-type natriuretic peptide, GDF-15 remained an independent predictor of CHD mortality (P⬍0.001). Addition of GDF-15 improved the prognostic accuracy of a clinical risk prediction model concerning CHD mortality (c-statistic, 0.84 versus 0.74; P⫽0.005). Analysis of the acute coronary syndrome part of the study population confirmed GDF-15 as an independent predictor of CHD mortality (P⬍0.001). The circulating levels of GDF-15 did not predict the future risk of nonfatal myocardial infarction in patients with stable angina pectoris or acute coronary syndrome. Conclusion—This study identifies GDF-15 as a strong and independent predictor of CHD mortality across the broad spectrum of patients with stable and unstable CHD. (Circ Cardiovasc Genet. 2009;2:286-292.) Key Words: growth-differentiation factor-15 䡲 coronary heart disease 䡲 biomarker 䡲 outcome G rowth-differentiation factor-15 (GDF-15) is a distant member of the transforming growth factor- cytokine superfamily. Although GDF-15 is weakly expressed in most tissues under physiological conditions,1,2 its expression levels may significantly increase in response to pathological stress associated with inflammation or tissue injury.3,4 Along that line, reactive oxygen species, proinflammatory cytokines, simulated ischemia, and mechanical stretch have been found to stimulate the expression of GDF-15 in cultured rat cardiomyocytes.4 – 6 Increased cardiac expression levels of GDF-15 have been observed in mouse models of myocardial infarction (MI), pressure overload, and cardiomyopathy,4,7,8 indicating that GDF-15 shares some of its upstream regulatory stimuli with B-type natriuretic peptide (BNP).9 In contrast to BNP, which is predominantly produced in the heart,10 GDF-15 is not a cardiac-specific factor, however. Endothelial cells, for example, have been shown to express GDF-15 when exposed to antiangiogenic stress.11,12 Moreover, GDF-15 has been detected in human atherosclerotic plaque macrophages, where it may be induced by oxidized low-density lipoprotein (LDL) and proinflammatory cytokines.1,13 Article on page 209 Clinical Perspective on p 292 Data on the prospective impact of GDF-15 plasma concentrations in patients are evolving. A nested case-control analysis of the Women’s Health Study found that the circulating level of GDF-15 is related to the risk of future cardiovascular (CV) events in elderly women with no previous evidence of CV disease. This effect was independent of traditional risk factors and C-reactive protein (CRP) levels.14 Retrospective analyses of randomized clinical trials have shown that the circulating levels of GDF-15 are elevated in patients with acute coronary syndrome (ACS).15–17 The levels of GDF-15 were strongly associated with the risk of all-cause Received September 28, 2008; accepted March 9, 2009. From the Department of Cardiology and Angiology (T.K., A.Q., H.D., K.C.W.), Hannover Medical School, Hannover, Germany; Federal Armed Forces Hospital (J.M.S., C.B.), Koblenz, Germany; and Department of Medicine II (C.S., P.S.W., R.S., E.L., H.J.R., T.M., S.B.), Johannes-Gutenberg University, Mainz, Germany. Correspondence to Kai C. Wollert, MD, Klinik für Kardiologie und Angiologie, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625 Hannover, Germany. E-mail [email protected] © 2009 American Heart Association, Inc. Circ Cardiovasc Genet is available at http://circgenetics.ahajournals.org 286 DOI: 10.1161/CIRCGENETICS.108.824870 Kempf et al mortality in these studies. Notably, the prognostic information provided by GDF-15 was independent of clinical variables and other risk markers, including renal dysfunction, CRP, cardiac troponin T, and N-terminal pro-B-type natriuretic peptide (NT-proBNP), suggesting that GDF-15 provides insight into a distinct pathophysiological process.15–17 Considering the relation of GDF-15 to stress signaling in different CV cell types, we hypothesized that GDF-15 may be associated with outcome across the broad spectrum of patients with stable and unstable coronary heart disease (CHD). To test this hypothesis, we measured the circulating level of GDF-15 and assessed its relation to clinical risk indicators, other biomarkers, and outcome in patients with angiographically proven CHD from the AtheroGene registry. Methods Patient Population and End Points Downloaded from http://circgenetics.ahajournals.org/ by guest on June 14, 2017 Between November 1996 and February 2004, patients with stable angina pectoris (SAP) or ACS who underwent coronary angiography at the Second Medical Department of the Johannes-Gutenberg University in Mainz or the German Federal Armed Forces Central Hospital in Koblenz, and who had at least 1 stenosis ⬎30% in a major coronary artery were enrolled in the AtheroGene registry. Details of the study design have been published.18,19 Exclusion criteria included significant valvular heart disease or known cardiomyopathy, clinical or echocardiographic signs of heart failure, a history of coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, pulmonary embolism, surgery, trauma, or use of oral anticoagulant therapy within the previous 4 weeks, febrile conditions or sepsis, and known cancer. Patients presenting after cardiopulmonary resuscitation were also excluded. For the current analyses, blood samples were available from 1352 patients with SAP and 877 patients with ACS (unstable angina according to Braunwald classes B and C, non–ST-elevation or ST-elevation MI). Patients who received antihypertensive treatment or who had blood pressure measurements ⬎140/90 mm Hg were considered to have hypertension. Patients were classified as current smokers, previous smokers (if they had stopped ⬎4 weeks and ⬍40 years earlier), or never smokers (if they had never smoked or had stopped ⬎40 years ago). Patients receiving dietary or drug treatment for diabetes or whose fasting blood glucose concentrations were ⬎125 mg/dL were considered to have diabetes mellitus. Left ventricular ejection fraction (LVEF) was determined by angiography and off-line analysis by the area-length method in 757 SAP and 439 ACS patients.18 Patients were followed for a median of 3.6 (maximum 6.9) years. All data were evaluated by an independent end point adjudication committee consisting of experienced physicians who were blinded to biomarker concentrations. CHD mortality (cardiac death, sudden cardiac death, fatal MI) and nonfatal MI were the end points of the present study. Information about the causes of death was obtained from hospital and general practitioner charts. Similarly, nonfatal MIs, as reported by the patients during follow-up, were validated using hospital and general practitioner charts and the ECG and biomarker criteria proposed by the European Society of Cardiology. The study was approved by the ethics committee at the University of Mainz. Participation was voluntary, and each subject provided written, informed consent. Laboratory Parameters and Biomarker Testing Blood samples were drawn in all patients immediately before coronary angiography, rapidly processed, and stored at ⫺80°C. Plasma concentrations of GDF-15 were determined by a recently developed and validated immunoradiometric assay with a linear range from 200 to 50000 ng/L.20 Two GDF-15 cutoff points, 1200 and 1800 ng/L, were prospectively validated in the present study. The 1200 ng/L cutoff point corresponds to the previously defined upper reference limit in a cohort of 429 apparently healthy elderly Table 1. GDF-15 in Coronary Heart Disease 287 Baseline Characteristics Stable Angina ACS No. patients 1352 877 Age, y 62⫾10 61⫾10 78.1 77.1 Male gender, % CV risk factors Body mass index, kg/m2 Hypertension, % 27.8⫾4.1 27.7⫾3.9 81.4 85.1 4.0 3.9 Medical treatment, % 10.5 7.6 Insulin treatment, % 9.1 7.5 Never, % 36.2 34.2 Previous, % 46.7 42.1 Current, % 17.0 23.5 Diabetes mellitus No or dietary treatment, % Cigarette smoking Lipid status LDL cholesterol, mg/dL HDL cholesterol, mg/dL Triglycerides, mg/dL 117 (90 to 146) 126 (102 to 152) 49 (41 to 58) 46 (39 to 54) 129 (95 to 182) 131 (96 to 183) CV disease Coronary artery disease 1-vessel disease, % 28.3 26.7 2-vessel disease, % 31.2 31.3 3-vessel disease, % 40.5 41.9 64⫾16 59⫾15 42.1 29.8 LVEF History of MI, % Medication at baseline -blocker, % 64.4 65.9 Statin, % 58.0 43.0 ACE-I and/or AT1-RA, % 61.9 53.4 Antiplatelet therapy, % 82.6 80.2 eGFR, mL/min 90 (72 to 111) 91 (74 to 114) CRP, mg/L 1.8 (0.9 to 4.4) 4.6 (1.6 to 12.9) Biomarker cTnI ⬎0.01 g/L, % NT-proBNP, ng/L GDF-15, ng/L 20.5 61.9 166 (79 to 435) 418 (163 to 1248) 1128 (850 to 1553) 1244 (962 to 1785) Data are reported as percentage, mean⫾SD, or median (interquartile range). In the stable angina cohort, CRP values were available from 1262 patients, cTnI from 1119, NT-proBNP from 1290, and LVEF from 757; in the ACS cohort, CRP was available from 834 patients, cTnI from 771, NT-proBNP from 853, and LVEF from 439. LDL indicates low-density lipoprotein; HDL, high-density lipoprotein; ACE-I, ACE-inhibitor; and AT1-RA, AT1 receptor antagonist. individuals (median age, 65 years; 67.1% men).20 A total of 1200 ng/L also correspond to the rounded lower tertile boundary in 2081 patients with non–ST-elevation ACS included in the Global Utilization of Strategies To Open occluded arteries (GUSTO) IV trial, whereas 1800 ng/L corresponds to the rounded upper tertile boundary in that patient population. These cutoff points were found to be useful for identifying patient subgroups at low risk (⬍1200 ng/L), intermediate risk (1200 to 1800 ng/L), or high risk (⬎1800 ng/L) of death in GUSTO IV and in another large non–ST-elevation ACS trial population.15,16 288 Circ Cardiovasc Genet Table 2. June 2009 Independent Association of GDF-15 With Clinical and Biochemical Variables Stable Angina B (95% CI) ACS P B (95% CI) P Age (per 5 y) 0.04 (0.03 to 0.06) ⬍0.001 0.06 (0.04 to 0.08) Male gender 0.12 (0.06 to 0.17) ⬍0.001 0.08 (0.00 to 0.16) 0.040 Body mass index 0.01 (0.01 to 0.02) ⬍0.001 0.02 (0.01 to 0.03) ⬍0.001 Hypertension 0.02 (⫺0.04 to 0.07) Diabetes mellitus* 0.20 (0.14 to 0.25) 0.57 ⬍0.001 0.04 (⫺0.03 to 0.11) 0.15 (0.06 to 0.24) ⬍0.001 0.23 ⬍0.001 Cigarette smoking† 0.07 (0.02 to 0.12) 0.003 0.03 (⫺0.04 to 0.09) 0.43 LDL/HDL ratio (per 1 SD) 0.01 (⫺0.01 to 0.04) 0.26 0.02 (⫺0.01 to 0.05) 0.26 ⫺0.01 (⫺0.04 to 0.02) 0.44 0.02 (⫺0.02 to 0.05) 0.43 0.01 (⫺0.04 to 0.05) 0.80 0.06 (⫺0.01 to 0.13) 0.08 ⫺0.16 (⫺0.19 to ⫺0.13) ⬍0.001 ⫺0.11 (⫺0.15 to ⫺0.06) ⬍0.001 No. diseased vessels History of MI ln eGFR (per 1 SD) Downloaded from http://circgenetics.ahajournals.org/ by guest on June 14, 2017 ln CRP (per 1 SD) 0.12 (0.09 to 0.15) cTnI ⬎0.01 g/L 0.00 (⫺0.05 to 0.05) ln NT-proBNP (per 1 SD) 0.12 (0.09 to 0.15) ⬍0.001 0.06 (0.03 to 0.10) ⬍0.001 0.97 ⫺0.01 (⫺0.08 to 0.07) 0.89 ⬍0.001 0.14 (0.10 to 0.17) ⬍0.001 Multiple linear regression analysis. Association with ln GDF-15 is shown. The models were also adjusted for baseline medication. CI indicates confidence interval; B, unstandardized B coefficient; LDL, low-density lipoprotein; and HDL, high-density lipoprotein. *Drug treated. †Previous or current. NT-proBNP was measured by a sandwich immunoassay (Roche Diagnostics), high-sensitivity CRP by a latex particle-enhanced immunoassay (Roche Diagnostics), and cardiac troponin I (cTnI) by the current version of the AccuTnI assay (Beckman Coulter). Based on previous investigations that showed that a cTnI level ⬎0.01 g/L was associated with CV high-risk features in elderly individuals21 and was prognostically useful in patients with stabilized CHD,22 this cutoff was used in the present analysis. Serum lipids and creatinine were measured by standard laboratory techniques. Estimated glomerular filtration rate (eGFR) was calculated according to the Cockcroft and Gault equation, and LDL cholesterol according to the Friedewald formula. Statistical Methods Baseline characteristics are shown as percentages or mean⫾SD. Skewed variables are presented as median with interquartile range. The Kolmogorov-Smirnov test was used to test for a normal distribution of continuous variables. Multiple linear regression analysis was applied to identify factors that were independently associated with GDF-15. The Kaplan–Meier method was used to illustrate the timing of events during follow-up; statistical assessment was performed by the log-rank test. The relations of GDF-15 to outcome were assessed by backward stepwise Cox regression analyses, first adjusting for age and gender (model 1), and then adjusting also for classical risk factors (hypertension, smoking [never, previous, current], diabetes [no or dietary treatment, medical treatment, insulin treatment], LDL/HDL ratio), number of diseased vessels (left main stenosis was classified as 2-vessel disease), history of MI, eGFR, CRP, cTnI (ⱕ0.01 versus ⬎0.01 g/L), and NT-proBNP (model 2); variables were entered one at a time; variables with a significant partial regression coefficient of P⬍0.10 were added to the model, and those with P⬍0.10 in the stepwise procedure were retained. The prognostic performance of the 2 prespecified GDF-15 cutoff values was assessed in the same age-adjusted, gender-adjusted and fully adjusted Cox regression models. Variables that were not normally distributed (eGFR, CRP, NT-proBNP, and GDF-15) were transformed to their natural logarithm for all regression analyses. To compare the prognostic information provided by a clinical risk model, which included information about age, gender, hypertension, diabetes (categorical), smoking (categorical), LDL/HDL ratio, number of diseased vessels, history of MI, and eGFR, alone and in combination with GDF-15, receiver operating characteristic curves were generated, and the area under the receiver operator characteristic curves were calculated and compared.23 Probability values ⬍0.05 were considered to indicate statistical significance. All analyses were performed using SPSS version 15.0.1 (SPSS Inc, Chicago, Ill) and MedCalc version 9.3.2.0 (MedCalc Software, Mariakerke, Belgium). Results GDF-15 Levels in Patients With Stable Angina and ACS Baseline characteristics are shown in Table 1. The SAP population consisted of 1352 patients (78.1% men) with a mean age of 62⫾10 years. GDF-15 levels in this cohort ranged from 376 to 11365 ng/L with a median (interquartile range) of 1128 (850 to 1553) ng/L; 55.8%, 26.3%, and 17.9% of the patients presented with GDF-15 levels ⬍1200 ng/L, between 1200 and 1800 ng/L, and ⬎1800 ng/L, respectively. The ACS population included 877 patients (77.1% men) with a mean age of 61⫾10 years. GDF-15 levels ranged from 300 to 18660 ng/L, with a median (interquartile range) of 1244 (962 to 1785) ng/L; 46.6%, 29.1%, and 24.3% of these individuals presented with GDF-15 levels ⬍1200 ng/L, between 1200 and 1800 ng/L, and ⬎1800 ng/L, respectively. Patients with ACS had significantly higher GDF-15 levels as compared to patients with SAP (P⬍0.001). GDF-15 in Relation to Baseline Characteristics and Clinical and Biochemical Risk Markers By multiple regression analysis that used the natural logarithm of GDF-15 as the dependent variable, GDF-15 was independently associated with age, male gender, body mass index, drug-treated diabetes, low eGFR, and the levels of CRP and NT-proBNP, both in patients with SAP or with ACS (Table 2). In SAP, a relation to previous or current smoking was also noted. The r2 values of these multiple regression models were 0.48 in SAP and 0.39 in ACS. Kempf et al GDF-15 in Coronary Heart Disease 289 Table 3. Backward Stepwise Cox Regression Analyses of the Association Between Biomarker Measurements and Coronary Heart Disease Mortality in Patients With Stable Angina Model 1 (Age and Gender Adjusted) eGFR Model 2 (Fully Adjusted*) HR (95% CI) P HR (95% CI) P 0.7 (0.6 to 0.8) ⬍0.001 1.1 (0.7 to 1.8) 0.68 CRP 1.9 (1.4 to 2.6) ⬍0.001 1.0 (0.7 to 1.6) 0.88 cTnI ⬎0.01 g/L 4.8 (2.6 to 9.1) ⬍0.001 2.5 (1.1 to 5.7) 0.033 NT-proBNP 3.3 (2.5 to 4.4) ⬍0.001 1.7 (1.1 to 2.6) 0.011 GDF-15 2.7 (2.2 to 3.3) ⬍0.001 2.4 (1.7 to 3.4) ⬍0.001 Downloaded from http://circgenetics.ahajournals.org/ by guest on June 14, 2017 High-sensitivity CRP, eGFR, NT-proBNP, and GDF-15 were not normally distributed and ln transformed; hazard ratios refer to 1 SD in the ln scale in these variables. CI indicates confidence interval; HR, hazard ratio; NT-proBNP, N-terminal pro-B-type natriuretic peptide; LDL, low-density lipoprotein; and HDL, high-density lipoprotein. *Adjusted for age, gender, hypertension, diabetes (categorical), smoking (categorical), LDL/HDL-ratio, number of diseased vessels, history of myocardial infarction, and all indicated biomarkers. Figure 1. CHD mortality according to the levels of GDF-15 at baseline. Kaplan–Meier curves showing the cumulative incidence of CHD mortality in 1352 patients with stable angina (A) and 877 patients with acute coronary syndrome (B). The number of patients at risk is indicated at the bottom of each panel. GDF-15 and the Risk of CHD Mortality and Nonfatal MI In the SAP cohort, 50 CHD deaths (3.7% of the study population) and 37 nonfatal MIs (2.7%) were observed. The levels of GDF-15 were closely associated with the risk of CHD mortality (P⬍0.001; Figure 1A). At 3.6 years (median follow-up), patients presenting with GDF-15 levels ⬍1200 ng/L, between 1200 and 1800 ng/L, and ⬎1800 ng/L had CHD mortality rates of 1.4%, 2.7%, and 15.0%, respectively (P⬍0.001). The levels of GDF-15 were not associated with the risk of nonfatal MI in our patients with SAP (P⫽0.16). In the ACS cohort, 49 CHD deaths (5.6%) and 52 nonfatal MIs (5.9%) occurred during follow-up. Increasing levels of GDF-15 were closely associated with the risk of CHD mortality (P⬍0.001; Figure 1B). At 3.6 years, CHD mortality rates were 1.7%, 4.6%, and 14.6% in the 3 strata of GDF-15. No significant relation was observed between the levels of GDF-15 and the risk of nonfatal MI (P⫽0.28). GDF-15 in the Context of Other Biomarkers of Cardiovascular Risk In the SAP cohort, a reduced eGFR and the levels of CRP, cTnI, NT-proBNP, and GDF-15 were all significantly related to the risks of CHD mortality in an age- and gender-adjusted analysis (Table 3). To assess the independent strength of GDF-15 for CV risk prediction in comparison with established biomarkers, a backward stepwise Cox regression model was developed. In this analysis, GDF-15 (P⬍0.001), NT-proBNP (P⫽0.011), and a cTnI level ⬎0.01 g/L (P⫽0.033) remained independently predictive for CHD mortality after full adjustment for age and gender, clinical variables, classical risk factors, the number of diseased vessels, and biomarker levels (Table 3). After further adjustment for LVEF (data available from 757 SAP patients), GDF-15 remained independently associated with the risk of CHD mortality (P⬍0.001). Patients with ACS, CRP, NT-proBNP, and GDF-15 predicted the risk of CHD mortality after adjustment for age and gender (Table 4). After full adjustment, only GDF-15 remained independently related to the risk of CHD mortality (P⬍0.001). After further adjustment for LVEF, GDF-15 lost its independent relation to CHD mortality (P⫽0.18); howTable 4. Backward Stepwise Cox Regression Analyses of the Association Between Biomarker Measurements and Coronary Heart Disease Mortality in Patients With Acute Coronary Syndrome Model 1 (Age and Gender Adjusted) Model 2 (Fully Adjusted*) HR (95% CI) P HR (95% CI) P 0.7 (0.5 to 1.1) 0.07 1.0 (0.6 to 1.5) 0.85 CRP 1.6 (1.2 to 2.1) ⬍0.001 1.2 (0.9 to 1.7) 0.31 cTnI ⬎0.01 g/L 1.7 (0.8 to 3.4) 0.18 0.7 (0.3 to 1.7) 0.35 NT-proBNP 1.9 (1.4 to 2.6) ⬍0.001 1.4 (1.0 to 2.0) 0.08 GDF-15 2.0 (1.6 to 2.5) ⬍0.001 1.6 (1.2 to 2.1) ⬍0.001 eGFR High-sensitivity CRP, eGFR, NT-proBNP, and GDF-15 were not normally distributed and ln transformed; HRs refer to 1 SD in the ln scale in these variables. CI indicates confidence interval; HR, hazard ratio; NT-proBNP, N-terminal pro-B-type natriuretic peptide; LDL, low-density lipoprotein; and HDL, high-density lipoprotein. *Adjusted for age, gender, hypertension, diabetes (categorical), smoking (categorical), LDL/HDL-ratio, number of diseased vessels, history of myocardial infarction, and all indicated biomarkers. 290 Circ Cardiovasc Genet June 2009 Table 5. Incremental Prognostic Value of GDF-15 Concerning Coronary Heart Disease Mortality A HR (95% CI) P value GDF-15 [ng/L] Stable Angina ACS <1200 AUC (95% CI) 1200-1800 2.0 (0.8 to 5.1) 1.3 (0.4 to 4.3) 0.17 0.69 >1800 14 (6.4 to 29) 6.3 (2.2 to 18) <0.001 0.001 0.1 0.5 1 5 10 50 [Hazard ratio] B HR (95% CI) P value GDF-15 [ng/L] <1200 Downloaded from http://circgenetics.ahajournals.org/ by guest on June 14, 2017 1200-1800 1.8 (0.6 to 5.2) 2.0 (0.6 to 6.3) 0.28 0.24 >1800 5.5 (2.1 to 15) 4.9 (1.7 to 15) 0.001 0.004 0.1 0.5 1 5 10 50 [Hazard ratio] Figure 2. Application of GDF-15 cutoffs for risk stratification. Risk of CHD mortality during follow-up associated with GDF-15 levels between 1200 and 1800 ng/L, and ⬎1800 ng/L as compared to a GDF-15 level ⬍1200 ng/L in patients with stable angina (A) or ACS (B). Closed squares indicate hazard ratios (HRs) adjusted for age and gender; open squares represent HRs adjusted for age, gender, hypertension, diabetes (categorical), smoking (categorical), LDL/high-density lipoprotein ratio, number of diseased vessels, history of MI, estimated GFR, CRP, and NT-proBNP and cTnI (ⱕ0.01 versus ⬎0.01 g/L). CI denotes confidence interval. ever, data on LVEF were available from only 439 ACS patients, thus greatly reducing the stability of this model. None of the tested biomarkers (eGFR, CRP, cTnI, NTproBNP, GDF-15) was associated with the risk of nonfatal MI in SAP or ACS in age- and gender-adjusted Cox regression analyses (data not shown). Application of the 1200 and 1800 ng/L Cutoff Points for Risk Prediction In an age- and gender-adjusted Cox regression analysis, SAP patients presenting with a GDF-15 level ⬎1800 ng/L had a 14-fold increase in the risk of CHD mortality (P⬍0.001) as compared to patients with a GDF-15 level ⬍1200 ng/L (Figure 2A). After adjustment for clinical variables and classical risk factors, the number of diseased vessels, and biomarker levels, a GDF-15 level ⬎1800 ng/L remained associated with a 6.3-fold (P⫽0.001) increase in the risk of CHD mortality. GDF-15 levels between 1200 and 1800 ng/L were not associated with a significant increase in the risk of CHD mortality in SAP patients after adjustment for age and gender (Figure 2A). In patients with ACS, a GDF-15 level ⬎1800 ng/L was associated with a 5.5-fold (P⫽0.001) increase in the risk of CHD mortality in the age- and gender-adjusted model, and a 4.9-fold (P⫽0.004) increase in the risk of CHD mortality in the fully adjusted model (Figure 2B). GDF-15 levels between 1200 and 1800 ng/L did not predict an increase in CHD mortality in ACS patients after adjustment for age and gender (Figure 2B). P* AUC (95% CI) P* Clinical model 0.74 (0.71 to 0.78) ... 0.82 (0.78 to 0.85) ... GDF-15 0.80 (0.77 to 0.83) 0.21 0.77 (0.73 to 0.81) 0.29 Clinical model⫹ GDF-15 0.84 (0.81 to 0.86) 0.005 0.85 (0.81 to 0.88) 0.17 Data are from a receiver operator characteristic curve analysis concerning coronary heart disease mortality at 3.6 years. The clinical model includes information on age, gender, hypertension, diabetes (categorical), smoking (categorical), LDL/HDL ratio, number of diseased vessels, history of myocardial infarction, and ln transformed estimated GFR (per 1 SD). GDF-15 was treated as an ln-transformed continuous variable. CI indicates confidence interval; LDL, low-density lipoprotein; and HDL, high-density lipoprotein. *Versus clinical model. Incremental Prognostic Value of GDF-15 for Risk Stratification in Stable Angina and ACS Receiver operating characteristic curve analyses were performed to explore if GDF-15 can add to the predictive value of a clinical model, which included all information that was readily available in our patients (age, gender, classical risk factors, lipid status, eGFR, and number of diseased vessels). The optimal GDF-15 levels for predicting 3.6-year CHD mortality were 1984 ng/L (sensitivity 60.9%, specificity 91.6%) in the SAP cohort and 1548 ng/L (sensitivity 77.3, specificity 72.3%) in the ACS cohort. In SAP, addition of GDF-15 improved the predictive accuracy of the clinical model concerning CHD mortality, as reflected by an increase in the c-statistic from 0.74 for the clinical model to 0.84 after addition of GDF-15 (P⫽0.005) (Table 5). GDF-15 did not add significantly to the clinical model in ACS (c-statistic, 0.82 versus 0.85; P⫽0.17; Table 5). Discussion A New Biomarker in Stable CHD This study identifies GDF-15 as an independent predictor of CHD mortality in patients with SAP. The main findings are 1) a single measurement of GDF-15 provides independent prognostic information regarding the long-term risks of CHD mortality in patients with SAP and at least 1 documented coronary artery stenosis ⬎30%; 2) GDF-15 cutoff levels that have been used to identify ACS patients at low (⬍1200 ng/L) or very high risk (⬎1800 ng/L) appear to be also helpful for risk stratification in SAP; 3) addition of GDF-15 significantly improves the prognostic accuracy of a clinical risk prediction model. Several biomarkers have been shown to improve risk stratification beyond traditional risk factors in patients with stable CHD. The data are especially strong for BNP and NT-proBNP that have been linked to adverse CV outcomes in a number of studies.18,24,25 Renal dysfunction,26,27 inflammatory biomarkers, including CRP,28,29 and minor cTnI elevations,22 may also help in identifying patients at increased risk. In the present data set, all of these markers, and GDF-15, were significantly related to the risk of CHD mortality in an age- and gender-adjusted analysis. After further adjustment Kempf et al GDF-15 in Coronary Heart Disease 291 Downloaded from http://circgenetics.ahajournals.org/ by guest on June 14, 2017 for clinical variables, the number of diseased vessels, biomarker levels, and even LVEF, GDF-15 remained independently predictive for CHD mortality. It should be mentioned that GDF-15 was similarly predictive for CV mortality (CHD mortality, vascular death, stroke death) and all-cause mortality in SAP (data not shown). The associations of these biomarkers with the specific risk of (nonfatal) MI in SAP have been less well studied and appear to be somewhat less consistent.24,25,28,29 We found no significant association between the levels of GDF-15 and the risk of nonfatal MI in our SAP cohort. avoid overadjustment, backward stepwise Cox regression analyses were performed to build the multivariable models in our study. Still, the association of some biomarkers with CHD death may not be statistically significant due to a type II error. Second, our patients were recruited in a small area in Germany, which limits the generalizability of our findings. Third, the nonrandomized design of the AtheroGene registry did not allow us to study the influence of drugs (eg, heparin) on the circulating levels of GDF-15. Before introducing GDF-15 into clinical practice, the influence of common medications on the circulating levels of this biomarker should be explored. GDF-15 as a Biomarker in ACS Clinical Implications Patients with ACS had significantly higher levels of GDF-15 as compared to patients with SAP; the difference was small, however. Moreover, no independent relation between the levels of GDF-15 and cTnI was observed in the ACS patient cohort, thus supporting the conclusion that GDF-15 does not reflect myocardial ischemia and infarction during an episode of ACS.15–17 GDF-15 did not predict the risk of nonfatal MI in our ACS population. However, confirming and extending previous observations from ACS trial populations,15–17 GDF-15 was a strong and independent predictor of CHD mortality in the AtheroGene ACS population. GDF-15 was similarly predictive for CV mortality and all-cause mortality (data not shown). This study identifies GDF-15 as a promising new biomarker for risk stratification of patients with SAP and confirms GDF-15 as an independent prognostic marker in ACS. Pathophysiology and Predictive Value of GDF-15 We are only beginning to understand the pathobiology of GDF-15 in CV disease and the basis of its strong association with adverse CV outcomes. The predictive capacity of GDF-15 may be explained in part by the relation of GDF-15 to inflammation, which is reflected by its independent association to CRP in the present study and in ACS trial populations,15,16 the expression of GDF-15 in human atherosclerotic plaque macrophages,13 and the upregulation of GDF-15 in other chronic inflammatory conditions.30 The independent relation of GDF-15 to NT-proBNP, which has also been observed in ACS trial populations15–17 and in patients with chronic heart failure,31 suggests that GDF-15 may reflect, to some extent, cardiac pathologies. Supporting this hypothesis, BNP and GDF-15 are similarly induced by biomechanical stress in isolated rat cardiomyocytes and in the murine heart.6 – 8 In addition, GDF-15 appears to combine information from several CV risk factors, including age, male gender, body mass index, diabetes, and renal dysfunction. The positive correlation of GDF-15 to body mass index may be of particular interest, especially because a negative correlation to body mass index has been observed for the natriuretic peptides.32 It is interesting to note in this regard that human adipocytes express and secrete GDF-15 on exposure to oxidative stress.33 Together, these clinical variables and biomarkers explained ⬍50% of the variation in the GDF-15 levels (as judged by the multiple regression r2 values), indicating that GDF-15 carries unique additional information. Study Limitations First, the relatively small numbers of end points introduces a problem of low statistical power. To address this problem and Sources of Funding AtheroGene is supported by the Stiftung Rheinland-Pfalz für Innovation (Aktenzeichen 15202-386261/545); Dr. Wollert is supported by the Deutsche Forschungsgemeinschaft (Sonderforschungsbereich 566) and the Bundesministerium für Bildung und Forschung (BioChancePlus). Disclosures Drs Kempf, Drexler, and Wollert have filed a patent and have a contract with Roche Diagnostics to develop a GDF-15 assay for cardiovascular applications. The other authors have nothing to disclose in relation to this work. References 1. Bootcov MR, Bauskin AR, Valenzuela SM, Moore AG, Bansal M, He XY, Zhang HP, Donnellan M, Mahler S, Pryor K, Walsh BJ, Nicholson RC, Fairlie WD, Por SB, Robbins JM, Breit SN. MIC-1, a novel macrophage inhibitory cytokine, is a divergent member of the TGF- superfamily. Proc Natl Acad Sci USA. 1997;94:11514 –11519. 2. 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Sabatine MS, Morrow DA, Jablonski KA, Rice MM, Warnica JW, Domanski MJ, Hsia J, Gersh BJ, Rifai N, Ridker PM, Pfeffer MA, Braunwald E. Prognostic significance of the Centers for Disease Control/ American Heart Association high-sensitivity C-reactive protein cut points for cardiovascular and other outcomes in patients with stable coronary artery disease. Circulation. 2007;115:1528 –1536. 30. Brown DA, Moore J, Johnen H, Smeets TJ, Bauskin AR, Kuffner T, Weedon H, Milliken ST, Tak PP, Smith MD, Breit SN. Serum macrophage inhibitory cytokine 1 in rheumatoid arthritis: a potential marker of erosive joint destruction. Arthritis Rheum. 2007;56:753–764. 31. Kempf T, von Haehling S, Peter T, Allhoff T, Cicoira M, Doehner W, Ponikowski P, Filippatos GS, Rozentryt P, Drexler H, Anker SD, Wollert KC. Prognostic utility of growth differentiation factor-15 in patients with chronic heart failure. J Am Coll Cardiol. 2007;50:1054 –1060. 32. Bayes-Genis A, DeFilippi C, Januzzi JL Jr. Understanding aminoterminal pro-B-type natriuretic peptide in obesity. Am J Cardiol. 2008; 101(3A):89 –94. 33. Ding Q, Mracek T, Gonzalez-Muniesa P, Kos K, Wilding J, Trayhurn P, Bing C. Identification of macrophage inhibitory cytokine-1 (MIC-1) in adipose tissue and its secretion as an adipokine by human adipocytes. Endocrinology. 2009;150:1688 –1696. CLINICAL PERSPECTIVE The clinical presentation of patients with coronary heart disease (CHD) ranges from chronic stable angina to acute coronary syndrome (ACS). Within these broad patient categories, the future risk of adverse coronary events may vary considerably in individual patients. Growth-differentiation factor-15 (GDF-15) is a stress-responsive cytokine that is produced in the heart and in extracardiac tissues. Previous studies in highly selected ACS trial populations have documented a close association between the circulating levels of GDF-15 and mortality risk. We measured the circulating levels of GDF-15 in 2229 unselected, real-life CHD patients undergoing coronary angiography in 2 hospitals in Germany. Patients were followed for a median of 3.6 years. GDF-15 levels within the normal range (⬍1200 ng/L) were associated with a very low risk of CHD mortality at 3.6 years (1.4% in stable angina patients; 1.7% in ACS). Conversely, GDF-15 levels ⬎1800 ng/L identified a patient subgroup at high risk of CHD mortality (15.0% in stable angina; 14.6% in ACS). After adjustment for age and gender, clinical variables, the number of diseased vessels, renal function, the levels of C-reactive protein, cardiac troponin I, and N-terminal pro–B-type natriuretic peptide, GDF-15 levels ⬎1800 ng/L remained associated with 6.3- and 4.9-fold increases in the risk of CHD mortality in stable angina and ACS, respectively. Our study identifies GDF-15 as a promising new biomarker for risk stratification across a broad spectrum of patients with stable and unstable coronary heart disease. Growth-Differentiation Factor-15 for Risk Stratification in Patients With Stable and Unstable Coronary Heart Disease: Results From the AtheroGene Study Tibor Kempf, Jan-Malte Sinning, Anja Quint, Christoph Bickel, Christoph Sinning, Philipp S. Wild, Renate Schnabel, Edith Lubos, Hans J. Rupprecht, Thomas Münzel, Helmut Drexler, Stefan Blankenberg and Kai C. Wollert Downloaded from http://circgenetics.ahajournals.org/ by guest on June 14, 2017 Circ Cardiovasc Genet. 2009;2:286-292; originally published online March 31, 2009; doi: 10.1161/CIRCGENETICS.108.824870 Circulation: Cardiovascular Genetics is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231 Copyright © 2009 American Heart Association, Inc. All rights reserved. Print ISSN: 1942-325X. 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