Download Growth-Differentiation Factor-15 for Risk Stratification in Patients

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
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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
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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)
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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
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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
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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
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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.
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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
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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,
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Copyright © 2009 American Heart Association, Inc. All rights reserved.
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