Clinical Chemistry 62: (2016) Lipids, Lipoproteins, and Cardiovascular Risk Factors

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1 Clinical Chemistry 62: (2016) Lipids, Lipoproteins, and Cardiovascular Risk Factors Growth Differentiation Factor 15, Its 12-Month Relative Change, and Risk of Cardiovascular Events and Total Mortality in Patients with Stable Coronary Heart Disease: 10-Year Follow-up of the KAROLA Study Dhayana Dallmeier, 1,2 Hermann Brenner, 3 Ute Mons, 3 Wolfgang Rottbauer, 1 Wolfgang Koenig, 1,4,5* and Dietrich Rothenbacher 3,6 BACKGROUND: This study considered whether baseline concentrations and 12-month changes of growth differentiation factor 15 (GDF-15) are associated with subsequent cardiovascular events (CVEs) and total mortality in patients with stable coronary heart disease. METHODS: Baseline GDF-15 serum concentrations were measured in 1073 participants in a cardiac rehabilitation program (median follow-up 10 years). GDF-15 associations with subsequent CVE and total mortality were evaluated by Cox-proportional hazards models adjusting for well-established cardiovascular risk factors (Model 2), plus N-terminal probrain natriuretic peptide, highsensitivity (hs) CRP, and hs cardiac troponin T (Model 3). RESULTS: In our study population [84.7% men, mean age 59 years, median baseline GDF ng/l (interquartile range, 916, 1674)] we observed 190 CVE and 162 deaths. Compared to participants with GDF ng/l, increased risk for death was found in participants with GDF and 1800 ng/l [hazard ratio (HR) 1.68 (95% CI, )] and with GDF ng/l [HR 1.73 ( )], even in Model 3. The 12-month relative median change was 16.7%. As compared to participants with 12-month relative changes between 20% and 20%, GDF-15 increments 20% were associated with: a) an HR of 1.84 ( ) for CVE in Model 2, but found nonsignificant in Model 3; (b) an HR of 2.26 ( ) for death even in Model 3. CONCLUSIONS: GDF-15 at baseline is independently associated with subsequent CVE and 10-year total mortality. Twelve-month relative changes remained associated with subsequent CVE when adjusting for wellestablished cardiovascular risk factors, and with total mortality even after further adjustment for established cardiac biomarkers American Association for Clinical Chemistry Cardiovascular disease (CVD) 7 is the number one cause of death worldwide. About 17.5 million people died from CVD in 2012, 7.4 million due to coronary heart disease (CHD) and 6.7 million due to stroke (1). Based on the Framingham Heart Study, the Atherosclerosis Risk in Communities Study, and the Cardiovascular Health Study among those patients 45 years having a myocardial infarction (MI), about 19% of men and 26% of women will die within 1 year, whereby survivors will have a 1.5- to 15-times higher risk for illness and death compared to the general population (2). In such a scenario the evaluation of new biomarkers that could improve risk stratification and clinical decision making among patients with prevalent CHD becomes essential. Growth differentiation factor 15 (GDF-15) belongs to the transforming growth factor superfamily, and is involved in regulating inflammatory and apoptotic pathways (3). Different pathological conditions such as inflammation, cancer, cardiovascular, pulmonary and renal diseases, have been related to an increased GDF-15 ex- 1 Dept. of Internal Medicine II-Cardiology, University of Ulm Medical Center, Ulm, Germany; 2 Agaplesion Bethesda Hospital, Geriatric Research Unit, Ulm University and Geriatric Center Ulm/Alb-Donau, Ulm, Germany; 3 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany; 4 Deutsches Herzzentrum München, Technische Universität München, Munich, Germany; 5 DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany; 6 Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany. * Address correspondence to this author at: Klinik für Herz-& Kreislauferkrankungen, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, Munich, Germany. Fax ; koenig@dhm.mhn.de. Received January 12, 2016; accepted April 8, Previously published online at DOI: /clinchem American Association for Clinical Chemistry 7 Nonstandard abbreviations: CVD, cardiovascular disease; CHD, coronary heart disease; MI, myocardial infarction; GDF-15, Growth differentiation factor 15; ACS, acute coronary syndromes; CVE, cardiovascular event; CABG, coronary artery bypass graft; BMI, body mass index; NT-proBNP, N-terminal pro Brain Natriuretic Peptide; hs, high-sensitivity; CRP, C-reactive protein; LOD, lower limit of detection; ctnt, cardiac troponin T; ln, natural log; IQR, interquartile range; IR, incidence rate; HR, hazard ratio; IL, interleukin. 982

2 GDF-15, Secondary Cardiovascular Events and Mortality Fig. 1. Study design. pression (4). In patients with CVD atherosclerotic plaque macrophages and infarcted myocardium have been shown to express GDF-15 (5 6). GDF-15 has also been associated with mortality and disease progression in patients with acute coronary syndromes (ACS), angina pectoris, heart failure, and stroke (7 10). GDF-15 is weakly expressed in most tissues under physiological conditions and yet it is unclear whether high concentrations might just be a response to biologic stress or reflect directly a harmful pathway (3). The present study evaluated the association between baseline concentrations and 12-month changes of GDF-15 with the onset of subsequent cardiovascular events (CVE) and total mortality in patients with stable CHD during long-term follow-up. Materials and Methods STUDY POPULATION The KAROLA cohort is a prospective study including 1204 patients with CHD (30 70 years) who were admitted after an ACS or coronary artery bypass graft (CABG) to an in-hospital cardiac rehabilitation program at 2 cooperating hospitals in Southwest Germany between January 1999 and May For this study following exclusion criteria were applied: patients censored at baseline (n 83); missing values for GDF-15 at baseline (n 48); missing information for body mass index (BMI) (n 4), lipid profile (n 22), N-terminal pro brain natriuretic peptide (NT-proBNP) (n 3), highsensitivity (hs) C-reactive protein (CRP) (n 1), medications (n 2), history of diabetes (n 9), and history of hypertension (n 3). Thus, a total of 1029 participants were considered to evaluate GDF-15 baseline levels. For 12-month changes of GDF-15 we further excluded those patients with missing GDF-15 levels at 1-year follow-up (n 120) and with a CVE during the first year follow-up (n 28), so that a total of 909 and 881 participants were considered for the analyses with respect to total mortality, and the onset of a subsequent CVE (Fig. 1). The study was approved by the ethical committees of the Universities of Ulm and Heidelberg and by the Physicians Chambers of the States of Baden- Württemberg and Hessen. All participants gave written informed consent. DATA COLLECTION At the beginning of the rehabilitation program all participants filled out a standardized questionnaire containing socio-demographic information, medical history, and assessment of lifestyle factors. Participants were weighed, measured, and examined by a physician. BMI was defined as the individual s body weight divided by height square. Baseline fasting blood samples were obtained at the end of the rehabilitation phase. Serum samples underwent centrifugation (15 min at 2000g), were divided into aliquots and stored for up to 1 month at 20 C, and then transferred to a 80 C freezer until analysis. ElectroChemi-Luminescence Immunoassays (Fa. Roche) were used to measure GDF-15 [Cobas e411 (CV 5%), lower limit of detection (LOD) of 10 ng/l, measuring range ng/l], NT-proBNP (Elecsys 2010 Clinical Chemistry 62:7 (2016) 983

3 probnp II Test, CV 5%, LOD of 5 ng/l), and hs cardiac troponin T (ctnt) (Elecsys Troponin T hs Test, LOD of 5 ng/l, a 10% CV at 13 ng/l). Immunonephelometric assays (Fa. Siemens) were performed to measure hs-crp and cystatin C (BNII Analyzer (CV 5%)). The latter was standardized using the factor 1.17 as recommended by the manufacturer. Lipid levels were estimated using the same methods in both hospitals. All marker measurements were performed in a blinded fashion. ADVERSE CVD EVENTS Active follow-up of patients was conducted 1, 3, 4.5, 6, 8, and 10 years after discharge from the rehabilitation centers using mailed standardized questionnaires, with primary care physicians completed standardized questionnaires reporting any subsequent CVE (nonfatal MI and/or stroke) and new treatment and/or diagnoses. If a patient was deceased, the cause of death was extracted from death certificates obtained from the local Public Health Department and coded according to the ICD (International Classification of Diseases) (ICD-9 pos until 2003, followed by ICD-10 pos. I0-I99 or R57.0). STATISTICAL ANALYSIS Discrete variables are presented as numbers and percentages, continuous variables as arithmetic means and SDs or medians and/or interquartile range (IQR) according to their distribution, and stratified according to the GDF-15 baseline concentrations based on the proposed cutoff points of 1200 and 1800 ng/l for patients with ACS or stable CHD (11 13). Differences in the distribution were tested using parametric and nonparametric methods. The median follow-up estimate was based on the reverse Kaplan Meier estimator. GDF-15, NTproBNP, hs-crp, and hs-ctnt concentrations showed a skewed distribution, and were natural log (ln) transformed for further analyses. We estimated the age and sex-adjusted Partial Spearman correlation coefficients between following variables measured at baseline: ln GDF- 15, ln NT-proBNP, ln hs-crp, ln cystatin C, ln hsctnt, BMI, smoking status, history of diabetes, history of hypertension, total cholesterol, HDL-cholesterol, and use of statins. We checked for collinearity between ln GDF-15, 12-month relative change of GDF-15, ln NTproBNP, ln hs-crp, ln cystatin C, and ln hs-ctnt. We evaluated single-predictor associations between the variables listed in Table 1 and ln GDF-15 using linear regression analysis. We identify those variables independently associated with baseline ln GDF-15 concentrations applying backwards selection in a multivariable linear regression. Cox-proportional hazards models evaluated the association of baseline ln GDF-15 (continuous and categorical) with the onset of an adverse CVE (MI, stroke, cardiovascular death), total mortality, and cardiovascular vs noncardiovascular mortality during a 10-year follow-up adjusting initially for age and sex (Model 1), followed by the addition of well-established cardiovascular risk factors measured at baseline: BMI, smoking, history of diabetes, history of hypertension, total cholesterol, HDL-cholesterol, use of statins, and cystatin C (Model 2), and by further adjustment for ln NTproBNP, ln hs-crp, and ln hs-ctnt (Model 3). The individual relative 12-month change of GDF-15 was defined as [(12-month ln GDF-15 baseline ln GDF-15)/baseline ln GDF-15] 100. A backward selection in a multivariable linear regression identified independent predictors of 12-month change among the following baseline covariates: age, sex, BMI, smoking, total cholesterol, HDL-cholesterol, history of hypertension, history of diabetes, cystatin C, NT-proBNP, hs- CRP, and hs-ctnt. We evaluated the correlation between 12-month changes of GDF-15 and the 12- month changes of NT-proBNP and hs-ctnt. The relationship between GDF-15 concentration with subsequent CVE and mortality were assessed by the Kaplan Meier and life-table method. Cox-proportional hazards models evaluated the association of 12-month relative change of ln GDF-15 (continuous and categorical) with a secondary CVE and total mortality during the subsequent 9 years of follow-up. Categorical analysis shows an upper category including those with a 12-month relative change 20%, a reference group including those with a relative change 20% but 20%, and a lower category for those with a relative change 20% (14). We adjusted initially for baseline levels of ln GDF-15, age and sex (Model 1), followed by additional adjustment for well-established cardiovascular risk factors (Model 2), and further adjustment for biomarkers representing specific pathogenetic pathways: ln NT-proBNP, ln hs-crp, and ln hs-ctnt (Model 3). For all Cox-proportional hazards models we checked the assumption of proportional hazards. We assessed discrimination in each model estimating the respective and its 95% CI. We considered 2-sided P 0.05 values as statistically significant. All analyses were performed using SAS software, version 9.2 (SAS Institute Inc.). Results Table 1 shows the baseline characteristics of the study sample (n 1029), as well as stratified according to GDF-15 baseline concentrations. The mean age was 59 (8) years, 84.7% were men; 57% were overweight, and 15.3% obese. Only 5% reported current smoking at baseline. History of diabetes and hypertension were present among 17.4% and 55.1% of participants respec- 984 Clinical Chemistry 62:7 (2016)

4 GDF-15, Secondary Cardiovascular Events and Mortality Table 1. Sociodemographic, clinical, and laboratory characteristics of participants according to baseline GDF-15 levels (n = 1029). (n = 1029) <1200 ng/l (n = 496) ng/l (n = 321) >1800 ng/l (n = 212) P value a Age, years, mean ± SD 59 ± ± ± ± 5.3 <0.001 Male, n (%) 872 (84.7) 425 (85.7) 270 (84.1) 177 (83.5) BMI, kg/m 2, mean ± SD 26.9 ± ± ± ± BMI, n (%) Normal weight 284 (27.6) 129 (26.0) 84 (26.2) 71 (33.5) Overweight 587 (57.0) 297 (59.9) 194 (60.4) 96 (45.3) Obese 158 (15.3) 70 (14.1) 43 (13.4) 45 (21.2) Smoking, n (%) Never smoker 324 (31.5) 145 (29.2) 109 (34.0) 70 (33.0) Ex-smoker 653 (63.5) 326 (65.7) 197 (61.3) 130 (61.3) Current smoker 52 (5.0) 25 (5.0) 15 (4.7) 12 (5.7) History of MI, n (%) 600 (58.3) 287 (57.9) 182 (56.7) 131 (61.8) CABG, n (%) 488 (47.4) 179 (36.1) 178 (55.4) 131 (61.8) <0.001 History of diabetes, n (%) 179 (17.4) 49 (9.9) 52 (16.2) 78 (36.8) <0.001 History of hypertension, n (%) 567 (55.1) 236 (47.6) 197 (61.4) 134 (63.2) <0.001 History of cancer, n (%) 42 (4.1) 16 (3.2) 13 (4.0) 13 (6.1) Total cholesterol, mg/dl, mean ± SD b ± ± ± ± HDL cholesterol, mg/dl, mean ± SD b 39.6 ± ± ± ± Use of statins, n (%) 795 (77.3) 421 (84.9) 227 (70.7) 147 (69.3) <0.001 Days from acute event to blood sample collection, median (q1, q3) 44.0 (37.0, 52.0) 45.5 (38.0, 53.0) 42.0 (35.0, 50.0) 44.0 (36.0, 55.0) <0.001 Biomarkers at baseline, median (q1, q3) hs-crp, mg/l 3.5 (1.28, 8.37) 2.19 (0.89, 5.57) 4.68 (1.85, 9.44) 6.6 (2.92, 17.50) <0.001 Cystatin C, mg/l 1.20 (1.09, 1.39) 1.12 (1.04, 1.24) 1.27 (1.15, 1.39) 1.53 (1.30, 1.81) <0.001 NT-proBNP, ng/l 565 (277, 1096) 400 (202, 713) 625 (355, 1193) 1121 (538, 2310) <0.001 hs-ctnt, ng/l 14 (9, 22) 11 (7, 15) 16 (10, 23) 23 (15, 33) <0.001 a, ANOVA to test differences in the means among the groups;, Kruskall Wallis. b To convert cholesterol concentrations from mg/dl to mmol/l multiply by Clinical Chemistry 62:7 (2016) 985

5 Fig. 2. Survival distributions for (A) a secondary CVE, (B) 10-year total mortality according to the baseline levels of GDF-15, (C) a secondary CVE and (D) 9-year total mortality according to the 12-month relative change of GDF-15. tively. The median baseline GDF-15 was 1232 ng/l (IQR, ) without differences between sexes. We observed on average older patients with a higher proportion of CABG, history of diabetes and hypertension, and a lower proportion of statin users as well as higher concentrations of cystatin C, NT-proBNP, hs-crp, and hsctnt among those with GDF ng/l. We detected age- and sex-adjusted correlations between ln GDF-15 and ln NT-proBNP (0.37), ln CRP (0.26), and ln hs-ctnt (0.38) (all P values 0.001). Following variables were independently associated with higher baseline GDF-15 concentrations: age, current smoking, history of diabetes, nonuse of statins, and higher cystatin C, NT-proBNP, hs-crp, and hs-ctnt levels (R ). 13.7% of the variation was explained by cystatin C. Age and smoking explained 3.9 and 3.2% of this variation respectively after adjustment for all other predictors (see Table 1 in the Data Supplement that accompanies the online version of this article at During 10 years of follow-up we observed 190 subsequent CVEs and 162 deaths (82 cardiovascular and 80 noncardiovascular deaths). The incidence rate (IR) for an adverse CVE was 23.1 per 1000 patient-years (95% CI, ), with a mortality rate of 16.8 per 1000 patient-years (95% CI, ). BASELINE GDF-15 AND ASSOCIATION WITH SUBSEQUENT CVE Survival analysis showed a statistically significant difference with respect to a subsequent CVE among GDF-15 baseline concentrations (log-rank P value 0.001) (Fig. 2A). A 1 unit increment of ln GDF-15 was associated with an age- and sex-adjusted hazard ratio (HR) of 2.16 (95% CI, ) for a subsequent CVE (Table 3). In multivariable analysis this association was attenuated to an HR of 1.46 (95% CI, ). After addition of ln NT-proBNP, hs- CRP, and hs-ctnt the association was further attenuated and no longer statistically significant [HR of 986 Clinical Chemistry 62:7 (2016)

6 GDF-15, Secondary Cardiovascular Events and Mortality 1.20 (95% CI, )]. The addition from ln GDF-15 in both models was associated with an increment in the [from 0.65 (95% CI, ) to 0.66 (95% CI, ) in Model 2, and from 0.67 (95% CI, ) to 0.68 (95% CI, ) in Model 3]. Compared to the reference group ( 1200 ng/l) those with GDF ng/l had an age- and sexadjusted HR of 2.78 (95% CI, ) for a subsequent CVE. The multivariable analysis (Model 2) showed an attenuation of the risk [HR 1.72 (95% CI, )]. This association was further attenuated and became nonsignificant after additional adjustment for biomarkers (Model 3) [HR 1.54 (95% CI, )] (Table 3). BASELINE LEVELS OF GDF-15 AND ASSOCIATION WITH 10-YEAR TOTAL MORTALITY Survival analysis showed a statistically significant difference with respect to total mortality among GDF-15 baseline levels (log-rank P value 0.001) (Fig. 2B). A 1 unit increment of ln GDF-15 was associated with an age- and sex-adjusted HR of 2.80 (95% CI, ] with the onset of death (Table 3). In further analysis (Model 2) the association remained statistically significant with an HR of 1.60 (95% CI, ]. After inclusion of ln NTproBNP, ln hs-crp, and ln hs-ctnt (Model 3) the association was attenuated and became nonsignificant [HR 1.29 (95% CI, )]. The addition from ln GDF-15 in both Models was associated with an increment in the in only Model 2 from 0.72 (95% CI, ) to 0.73 (95% CI, ). Compared to the reference group those with moderate ( 1200 and 1800 ng/l) and high ( 1800 ng/l) concentrations of GDF-15 had an age- and sex-adjusted HR of 2.36 (95% CI, ) and of 4.07 (95% CI, ) for death respectively. These associations were attenuated but remained statistically significant in the multivariable analyses, so that after further adjustment for ln NT-proBNP, ln hs-crp and ln hs-ctnt (Model 3) those with moderate GDF-15 concentrations had 1.68 (95% CI, ), and those with high concentrations 1.73 (95% CI, ) times the hazard of dying (Table 3). Survival analysis showed a statistically significant difference for cardiovascular and noncardiovascular death according to GDF-15 baseline levels (both logrank P value 0.001) (see online Supplemental Fig. 1). The age- and sex adjusted analysis showed that a 1 unit increment of ln GDF-15 was associated with an HR of 3.19 (95% CI, ) for a cardiovascular death, and an HR of 1.98 (95% CI, ) could be observed for noncardiovascular death. When looking into the categories, those with a baseline level of GDF ng/l had an HR of 6.12 (95% CI, ) for cardiovascular death and an HR of 2.61 (95% ) for noncardiovascular death when compared to those with baseline levels of GDF ng/l (see online Supplemental Table 2). 12-MONTH RELATIVE CHANGE OF GDF-15 Overall, the median relative 12-month change of ln GDF-15 was 16.7% (IQR 28.97, 3.45). A total of 69 (7.6%) participants showed a change 20%. Smoking, total cholesterol, history of diabetes, cystatin C, hs- CRP, and hs-ctnt at baseline were identified as independent predictors of the relative change (see online Supplemental Table 1). We observed on average younger patients with a higher proportion of current smokers, history of diabetes, and a lower proportion of statin users as well as increased concentrations of NT-proBNP, hs- CRP, and hs-ctnt among those with a 12-month increment of GDF-15 20% (Table 2). The correlations between changes of GDF-15 and changes of NTproBNP and hs-ctnt were 0.21 and 0.24 respectively (all P values 0.001). Survival analysis showed a statistically significant difference with respect to a secondary CVE among the categories of relative change (log-rank P value 0.007) (Fig. 2C), with the highest IR [46.1 CVE per 1000 person-years (95% CI, 29.0, 69.8)] among those with a 12-month relative change 20%. A 10% increment of GDF-15 was associated with an age- and sexadjusted HR of 1.08 (95% CI, ) for the onset of an adverse secondary CVE. Those with a relative change 20% had an age- and sex-adjusted HR of 2.13 (95% CI, ) compared to the reference group ( 20%, 20%) (Model 1). In multivariable analysis (Model 2) those with a 12-month increment of GDF-15 20% had an increased hazard for an adverse secondary CVE when compared to the reference group [HR 1.84 (95% CI, )]. This association became nonsignificant after further adjustment for ln NT-proBNP, ln hs-crp, and ln hs-ctnt (Model 3) (Table 4). With respect to total mortality survival analysis showed a statistically significant difference among the categories of relative change (log-rank P value 0.001) (Fig. 2D). Although nonsignificant, the HRs corresponding to a 12-month decrease of GDF-15 20% suggest a reduction of the risk for total mortality as high as 35% compared to the reference group ( 20%, 20%). A 10% increment of GDF-15 at 12 months remained associated with death even after adjustment for ln NTproBNP, ln hs-crp, and ln hs-ctnt [HR 1.13 (95% CI, )] (Table 4). We observed the lowest IR of death among those in the reference group [12.0 events per 1000 person-years, (95% CI, )], whereas those with a relative change 20% had the highest IR with 41.7 events per 1000 person-years (95% CI, 26.9 Clinical Chemistry 62:7 (2016) 987

7 Table 2. Sociodemographic, clinical, and laboratory characteristics of participants according to 12-month changes of GDF- 15 (n = 909). Total (n = 909) 20% (n = 393) Categories of 12-month change of GDF-15 ( 20%, 20%) (n = 447) 20% (n = 69) P value a Age, years, mean ± SD 59 ± ± ± ± Male, n (%) 774 (85.1) 329 (83.7) 382 (85.5) 63 (91.3) BMI, kg/m 2, mean ± SD 26.8 ± ± ± ± BMI, n (%) Normal weight 253 (27.8) 118 (30.0) 117 (26.2) 18 (26.1) Overweight 528 (58.1) 222 (56.5) 266 (59.5) 40 (58.0) Obese 128 (14.1) 53 (13.5) 64 (14.3) 11 (15.9) Smoking, n (%) Never smoker 291 (32.0) 140 (35.6) 136 (30.4) 15 (21.7) Ex-smoker 576 (63.4) 241 (61.3) 288 (64.4) 47 (68.1) Current smoker 42 (4.6) 12 (3.1) 23 (5.1) 7 (10.1) History of MI, n (%) 522 (57.4) 211 (53.7) 267 (59.7) 44 (63.8) CABG, n (%) 437 (48.1) 154 (39.2) 170 (38.0) 28 (40.6) History of diabetes, n (%) 152 (16.7) 72 (18.3) 59 (13.2) 21 (30.4) <0.001 History of hypertension, n (%) 506 (55.7) 226 (57.5) 247 (55.3) 33 (47.8) History of cancer, n (%) 42 (4.1) 23 (5.8) 18 (4.0) 1 (1.4) Total cholesterol, mg/dl, ± ± ± ± mean ± SD b HDL cholesterol, mg/dl, 39.7 ± ± ± ± mean ± SD b Use of statins, n (%) 704 (77.4) 286 (72.8) 367 (82.1) 51 (73.9) Biomarkers at baseline, median (q1, q3) hs-crp, mg/l 3.42 (1.22, 8.21) 4.36 (1.77, 9.85) 2.64 (1.02, 6.54) 3.95 (1.34, 9.44) <0.001 Cystatin C, mg/l 1.03 (0.93, 1.18) 1.08 (0.95, 1.26) 1.00 (0.92, 1.12) 1.06 (0.91, 1.20) <0.001 NT-proBNP, ng/l 544 (270, 1062) 648 (321, 1354) 477 (245, 834) 613 (207, 1252) <0.001 hs-ctnt, ng/l 14 (9, 22) 16 (11, 24) 12 (8, 19) 15 (11, 24) <0.001 a, ANOVA to test differences in the means among the groups;, Kruskall Wallis; Fisher exact test. b To convert cholesterol concentrations from mg/dl to mmol/l multiply by ). The latter also showed a 2.26 times the hazard for dying (95% CI, ) in Model 3. The models containing 12-month relative changes of GDF-15 provided a better discrimination with respect to death compared to the subsequent onset of an adverse secondary CVE [ of 0.76 (95% CI, ) vs 0.65 (95% CI, ) in Model 2, and 0.77 (95% CI, ) vs 0.65 (95% CI, ) in Model 3]. Discussion The present study of patients with stable CHD and 10- year follow-up showed that baseline GDF-15 is associated with the onset of a subsequent CVE and total mortality after adjustment for well-established cardiovascular risk factors. The association with death remained even after further adjustment for the established cardiovascular biomarkers NT-proBNP, hs-crp, and hs-ctnt. In addition, a 12-month relative change 20.0% was associated with the risk of a subsequent CVE and with total mortality when adjusting for well-established cardiovascular risk factors. However, after further adjustment for NT-proBNP, hs-crp, and hs-ctnt only the association with total mortality persisted. The models containing GDF-15 were noted to provide better discrimination with respect to death in comparison to the risk for a subsequent CVE. Therefore, baseline GDF-15 concentration and GDF-15 changes over 12-month may carry 988 Clinical Chemistry 62:7 (2016)

8 GDF-15, Secondary Cardiovascular Events and Mortality Table 3. Cox-proportional hazards models for baseline levels of GDF15 with respect to adverse secondary CVE and mortality. Model 1* Model 2 a Model 3 a Adverse secondary event (n = 1029, 190 CVE) HR P value HR P value ln-transformed GDF ( ) < ( ) ( ) 1.20 ( ) ( ) GDF-15 ng/l CVE/n IR per 1000 person-years HR P value HR P value < / ( ) Ref Ref 0.66 ( ) Ref 0.68 ( ) / ( ) 1.46 ( ) ( ) ( ) > / ( ) 2.78 ( ) < ( ) ( ) Model 1* Model 2 b Model 3 b Mortality (n = 1029, 162 deaths) HR P value HR P value ln-transformed GDF ( ) < ( ) ( ) 1.29 ( ) ( ) GDF-15 ng/l CVE/n IR per 1000 person-years HR P value HR P value < / ( ) Ref Ref 0.73 ( ) Ref 0.75 ( ) / ( ) 2.36 ( ) < ( ) ( ) > / ( ) 4.07 ( ) < ( ) ( ) * Adjusted for age and sex;, adjusted for age, sex, BMI, smoking, diabetes, hypertension, total cholesterol, HDL-cholesterol, use of statins, cystatin C;, adjusted for age, sex, BMI, smoking, diabetes, hypertension, total cholesterol, HDL-cholesterol, use of statins, cystatin C, NT-proBNP, hs-crp, and hs-ctnt; log-rank test P value < a c-statistics without GDF-15 with respect to adverse secondary CVE for Model ( ) and for Model ( ). b c-statistics without GDF-15 with respect to mortality for Model ( ) and for Model ( ). Clinical Chemistry 62:7 (2016) 989

9 Table 4. Cox-proportional hazards models for 12-month relative change of GDF-15 with respect to adverse secondary CVE and mortality. Model 1* Model 2 Model 3 Adverse secondary event (n = 899, 129 CVE) HR P value HR P value 10% Relative change of ln GDF a ( ) b ( ) ( ) 1.05 c ( ) ( ) Relative change of ln GDF-15 (%) CVE/n IR per 1000 person-years HR P value HR P value 20 66/ ( ) 0.80 ( ) ( ) ( ) 0.87 ( ) ( ) ( 20, 20) 71/ ( ) Ref. Ref. Ref / ( ) 2.13 ( ) ( ) ( ) Model 1 Model 2 Model 3 Mortality (n = 909, 114 deaths) HR P value HR P value 10% Relative change of ln GDF d ( ) < e ( ) < ( ) 1.13 f ( ) < ( ) Relative change of ln GDF-15 (%) CVE/n IR per 1000 person-years HR P value HR P value 20 46/ ( ) 0.65 ( ) ( ) ( ) 0.65 ( ) ( ) ( 20, 20) 46/ ( ) Ref. Ref. Ref / ( ) 2.87 ( ) < ( ) ( ) * Adjusted for age and sex; adjusted for age, sex, BMI, smoking, diabetes, hypertension, total cholesterol, HDL-cholesterol, use of statins, cystatin C. adjusted for age, sex, BMI, smoking, diabetes, hypertension, total cholesterol, HDL-cholesterol, use of statins, cystatin C, NT-proBNP, hs-crp, hs-ctnt. A 20% increment of GDF15 is associated with a, an HR 1.16 ( ); b, an HR 1.11 ( ); and c, an HR 1.11 ( ) with the occurrence of a secondary CVE. A 20% increment of GDF-15 is associated with d, an HR 1.34 ( ); e, an HR 1.27 ( ); and f, an HR 1.27 ( ) with the occurrence of death., Log-rank test P value = 0.007;, log-rank test P value < Clinical Chemistry 62:7 (2016)

10 GDF-15, Secondary Cardiovascular Events and Mortality important prognostic information for the identification of patients at high risk for death. Animal studies have demonstrated an up-regulation of GDF-15 expression induced by different stressors such as ischemia/reperfusion, pressure overload, heart failure, and atherosclerosis (15) associated with a cardiac protection from hypertrophy and ischemia-reperfusion injury (5, 16). Consistent with this observation we detected a correlation with NT-proBNP and hs-ctnt. So far, epidemiologic studies have also shown an association with biomarkers for endothelial activation, left ventricle mass index and concentric hypertrophy, reduced left ventricle ejection fraction, and heart failure even after adjustment for traditional CV risk factors (17 18). GDF-15 concentrations are known to be increased in patients with ACS without the typical rise and/or fall pattern seen with markers of myonecrosis (19), with high circulating GDF-15 being detected even 5 days after initial presentation (10). This could suggest an involvement of GDF-15 in the later stages of postinfarct healing and wound repair (20). A 72 h stability of GDF-15 concentrations has also been reported for patients admitted with non ST-elevation ACS, for which GDF-15 has been independently related to age, current smoking, diabetes, impaired renal function, CRP, interleukin (IL)-6, and NT-proBNP, indicating its role as a biomarker of cardiovascular risk, inflammation, and end-organ damage (20) reflecting at the same time chronic underlying pathologies such as atherosclerosis and coronary artery disease. GDF-15 was also identified as an important risk factor for death in patient with heart failure independently of NT-proBNP, and novel biomarkers such as hepatocyte growth factor, and soluble apoptosisstimulating fragment (21). In patients with atrial fibrillation GDF-15 was also shown to be associated with death independently of NT-proBNP and cardiac troponin (22). In the general population GDF-15 has been associated with all-cause mortality independent of age, BMI, smoking, IL-6, hs-crp, NT-proBNP, hs-ctnt, and telomere length (23 24). Stratified analyses have also demonstrated an association with mortality from CVD, cancer, and other causes, which suggest that increased GDF-15 reflects multiple different pathophysiological pathways (23, 25). In relatively healthy individuals GDF-15 concentrations have been more strongly associated with mortality than with nonfatal CVE (23), and among those with ACS the association with mortality was also stronger than with recurrent MI (20, 26, 27). This observed association with total mortality could be related to the process of aging, which is known to be associated with cumulative oxidative stress, protein glycosylation, and inflammation; processes which also induce GDF-15 expression (28). Further studies evaluating the underlying pathophysiological mechanisms and the involving signaling pathways are urgently needed to understand whether GDF-15 should be seen as a messenger of a poor outcome without specific therapeutic implications (25), whether GDF-15 concentrations can be modified through new intervention modalities with a subsequent reduction of the risk for a CVE and mortality, or whether GDF-15 concentrations could further help to stratify patients for specific treatment options according to their overall risk. With respect to the observed associations between 12-month change of GDF-15 concentrations and the onset of a subsequent CVE and total mortality, our data are consistent with the available literature. A nested study within the FRISC II Trial reported that GDF-15 concentrations measured even 6 months after the initial event are still associated with a secondary CVE during the subsequent 4.5 years of follow-up (29). Additionally a cohort study among older people showed that single GDF-15 concentrations, but also 5-year changes in GDF-15 may be important for the assessment of risk to death in this population (30). However, more studies evaluating GDF-15 longitudinal changes are needed to better elucidate their significance with respect to these outcomes. Strengths in our study include the long-term follow-up over 10 years and the high degree of complete data collection. However, some limitations warrant mention. Our analyses were based on single GDF-15 measurements for both time points, with adjustment using baseline levels of covariates. As an observational study, residual confounding has to be kept in mind. Our study consisted mostly of male, Caucasian patients. Case numbers were insufficient to perform separate analyses by sex and other ethnic/racial groups, as well as for each of the single adverse CVE owing to the low number of events in each group. Also, not all patients may have participated in cardiac rehabilitation, so that we could be missing the most severe cases, affecting the generalizability of the results. Nevertheless this should not affect the internal validity of our data. In conclusion, among patients with CHD, GDF-15 baseline concentrations are associated with subsequent CVE and total mortality after adjustment for wellestablished cardiovascular risk factors. The latter association remained stable even after further adjustment for cardiac and inflammatory biomarkers. In addition, 12- month longitudinal changes of GDF-15 were associated with subsequent CVE after adjustment for wellestablished cardiovascular risk factors, as well as with total mortality even after further adjustment for additional cardiac and inflammatory biomarkers. Our study thus provides evidence for the association of GDF-15 and its 12-month changes with total mortality in patients with Clinical Chemistry 62:7 (2016) 991

11 CHD, supporting its further evaluation as a prognostic biomarker. Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article. Authors Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest: Employment or Leadership: None declared. Consultant or Advisory Role: None declared. References Stock Ownership: None declared. Honoraria: None declared. Research Funding: H. Brenner, the German Federal Ministry of Education and Research [#01GD9820/0] and the Pitzer Foundation; W. 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