Clinical Biochemistry 48 (2015) 329–333
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Usefulness of S100A12 as a prognostic biomarker for adverse events in patients with heart failure Yun-Yun He a,b, Wei Yan a, Chun-Lei Liu a, Xin Li a, Rui-Jun Li a, Yang Mu a,b, Qian Jia a,b, Fen-Fen Wu a, Li-Li Wang c,⁎, Kun-Lun He a,⁎⁎ a b c
Department of Cardiology, Chinese PLA General Hospital, Beijing China School of Medicine, Nankai University, Tianjin China Beijing Institute of Pharmacology and Toxicology, Beijing China
a r t i c l e
i n f o
Article history: Received 8 October 2014 Received in revised form 13 November 2014 Accepted 18 November 2014 Available online 29 November 2014 Keywords: Heart failure Inflammation S100A12 hs-CRP
a b s t r a c t Objectives: S100A12 has been proposed as a novel pivotal factor in inflammation produced by granulocytes. The purpose of this study was to investigate the relationship between S100A12 and chronic heart failure (CHF). Design and methods: One hundred and seventy-seven patients with CHF and 66 subjects without CHF were included in this study. Plasma levels of S100A12 and high-sensitivity C-reactive protein (hs-CRP) were measured in all participants. After a follow-up period of 18 months for CHF patients, major cardiovascular events (MCE), including cardiac death and rehospitalization for heart failure, were recorded. Results: Plasma levels of S100A12 were significantly higher in CHF patients than in control subjects (P b 0.001) and positively correlated with hs-CRP (r = 0.316, P b 0.001). S100A12 levels were also higher in MCE patients than in MCE-free patients. The occurrence of MCE increased with advancing plasma S100A12 levels by stratification according to quartiles (Q4 vs Q1, P = 0.015). Cox proportional hazards regression analysis revealed that S100A12 was an independent risk factor for MCE in CHF patients (P = 0.009). Conclusions: S100A12 is a potential biomarker of CHF that may provide important information regarding the prediction of MCE in patients with CHF. © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Introduction Chronic heart failure (CHF), the end stage of various cardiovascular diseases, is a public health problem with high morbidity and mortality. Rational use of biomarkers for diagnosis, prognosis, and therapeutic monitoring are critically important in the management of these patients. As a systemic illness, CHF activates the immune system and inflammation and is thus characterized by elevated levels of proinflammatory cytokines in both the heart and the circulation [1,2]. Therefore, markers of inflammation have become a major focus of interest in CHF research [3]. Neutrophils, monocytes, and macrophages are important inflammatory effector cells. S100A12, a member of S100 calcium-binding protein family, is mainly secreted from these cells [4] and is recognized as
⁎ Correspondence to: L.-L. Wang, Beijing Institute of Pharmacology and Toxicology, Taiping Road 27, Beijing 100850, China. ⁎⁎ Correspondence to: K.-L. He, Department of Cardiology, Chinese PLA General Hospital, Fuxing Road 28, Beijing, 100853, China. Fax: +86 10 66939236. E-mail addresses: [email protected] (L.-L. Wang), [email protected] (K.-L. He).
potentially playing a key role in inflammation [5]. It is a close homologue to two other S100 proteins, S100A8 and S100A9 [6], collectively termed calgranulins or myeloid-related proteins. The interaction between S100A12 and the receptor for advanced glycation end products (RAGE) mediates the proinflammatory properties of this protein. Thus, S100A12 is also known as extracellular newly identified RAGE-binding protein (EN-RAGE). Several studies have identified S100A12 as being markedly expressed in various inflammatory disorders such as Kawasaki disease [7], inflammatory bowel disease [8,9], atherosclerosis [10,11], and so on. Furthermore, it has been recently reported that S100A12 is an independent factor for predicting major cardiovascular events (MCE) in patients with stable coronary artery disease (CAD) [12]. In addition, S100A8/A9, a highly homologous inflammatory mediator with S100A12, provides significant predictive value for 1-year mortality in elderly patients with severe heart failure [13]. However, no information about the relationship between S100A12 and CHF is available. We hypothesized that S100A12 may provide important clinical prognostic significance for patients with CHF. In this study, we evaluated plasma S100A12 levels to determine whether S100A12 could be used as a biomarker for the prediction of MCE in these patients.
http://dx.doi.org/10.1016/j.clinbiochem.2014.11.016 0009-9120/© 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
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Methods
Results
Subjects
Baseline characteristics of subjects
One hundred and seventy-seven patients with CHF (New York Heart Association [NYHA] functional class II–IV) who were admitted to the Department of Cardiology, Chinese PLA General Hospital (Beijing, China), from April 2011 to October 2012 were included in the study. The diagnosis of CHF was made according to the criteria of the European Society of Cardiology [14] by symptoms or signs, electrocardiogram, chest radiograph, and echocardiography. All patients had stable clinical symptoms for at least 2 weeks. The comorbidities of heart failure were identified as coronary heart disease (67.2%), hypertension (60.5%), diabetes (29.4%), atrial fibrillation (27.7%), and dilated cardiomyopathy (22.6%). Sixty-six subjects without heart failure were enrolled as controls. Physical examinations, echocardiography, and biochemical markers were evaluated. The exclusion criteria were acute infections, severe renal dysfunction (estimated glomerular filtration rate [eGFR] b30 ml·min–1·1.73m–2, calculated by CKD-EPI formula), malignant tumors, acute coronary syndrome, and acute cerebrovascular diseases within 3 months, immunological diseases, and other patients received anti-inflammatory agents. After a follow-up period of 18 months, MCE, including cardiac death and rehospitalization for heart failure, were documented. The study was approved by the Ethical Committee for Medical Research of Chinese PLA General Hospital and was conducted in accordance with Helsinki Declaration. Informed consent was obtained from all subjects.
The baseline characteristics of all subjects are listed in Table 1. A total of 177 CHF participants and 66 controls were included in this study. The echocardiographic results showed that in CHF patients, left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), and left ventricular mass index (LVMI) significantly increased while ejection fraction (EF) and fractional shortening decreased, indicating changes in left ventricular structure and function. The mean values of plasma NT-proBNP, hs-CRP, and S100A12 in all CHF patients were 3320.3 pg/mL, 6.22 mg/L, and 49.70 ng/mL, respectively, significantly higher than those in controls (63.0 pg/mL, 2.81 mg/L, and 27.13 ng/mL) (P b 0.001). The eGFR was lower in the CHF group than in controls (P b 0.001).
Correlation of S100A12 levels with baseline characteristics The Kolmogorov–Smirnov test indicated that values of S100A12 did not comply with the normal distribution. A Spearman correlation test was carried out to analyze the correlation of S100A12 levels with other parameters in all subjects. The results with a correlation are
Table 1 Baseline characteristics of subjects. CHF patients
Laboratory measurements
Controls (n = 66)
P value
127/50 63.5 ± 13.9 25.3 ± 4.3 132.6 ± 22.4 76.3 ± 11.7 68/87/22
40/26 58.0 ± 11.1 24.6 ± 3.7 123.1 ± 14.9 71.5 ± 10.1
0.096 0.004 0.294 0.002 0.003 —
56.6 ± 11.0 44.1 ± 12.2 42.6 ± 12.2 23.0 ± 7.4 139.2 ± 43.0
43.5 29.2 60.7 32.3 83.3
b0.001 b0.001 b0.001 b0.001 b0.001
6.54 ± 1.90 0.620 ± 0.094 4.45 ± 0.61 6.45 ± 2.68 4.11 ± 1.05 1.42 ± 0.83 1.08 ± 0.34
5.85 ± 1.37 0.552 ± 0.089 4.43 ± 0.58 5.24 ± 1.13 4.38 ± 0.72 1.43 ± 1.01 1.17 ± 0.30
0.002 b0.001 0.782 b0.001 0.024 0.866 0.024
2.43 ± 0.87
2.66 ± 0.59
0.066
79.9 ± 21.1 3320.3 ± 4240.6 6.22 ± 4.57 49.7 ± 57.2
95.0 63.0 2.81 27.1
b0.001 b0.001 b0.001 b0.001
92 (52.0%) 99 (56.0%) 112 (63.3%) 47 (26.6%) 104 (58.8%) 101 (57.1%) 98 (55.4%) 57 (32.2%)
2 (3.0%) 4 (6.1%) 7 (10.6%) 4 (6.1%) 0 20 (30.3%) 0 0
(n = 177)
Peripheral blood samples from subjects were collected into EDTA anticoagulant tubes after an overnight fast on the second day of hospitalization. Blood samples were centrifuged immediately at 3000 ×g for 10 min at 4 °C to separate plasma from blood cells and stored at − 80 °C until measurement. The plasma concentrations of S100A12 were measured according to the manufacturer's instructions using commercially available enzyme-linked immunosorbent assay kits (CycLex, Nagano, Japan). The performance characteristics of the S100A12 assay showed that the minimum detectable dose was ranged from 0.043 to 0.068 ng/mL, with the mean value at 0.056 ng/mL. The coefficient of variation of intra-assay and inter-assay was 4.3% and 5.4%, respectively. High-sensitivity C-reactive protein (hs-CRP) was measured by latex-enhanced nephelometry (Jiancheng, Nanjing, China). Nterminal pro-brain natriuretic peptide (NT-proBNP) was measured by electrochemiluminescence.
Statistical analysis All continuous variables are presented as mean ± standard deviation. All tests were carried out using SPSS version 15.0 statistical software. The normal distribution test for continuous variables was conducted using the Kolmogorov–Smirnov test. Statistical analysis of normal distribution data were performed using an unpaired Student t test between two groups and by one-way analysis of variance followed by a least-squares difference test for multiple comparisons. Non-normal distribution data were analyzed using the Mann–Whitney U test for continuous variables and the chi-square test for discrete variables. A linear correlation test was employed to study the association between S100A12 and other parameters. MCE-free survival curves were calculated by the Kaplan–Meier method and were compared using the log-rank test. Cox proportional hazards regression analysis was used to examine independent factors for predicting MCE in CHF patients. Differences were considered statistically significant at a two-tailed P value of less than 0.05.
Sex, male/female Age (years) BMI (kg/m2) SBP DBP NYHA class (II/III/IV) Echocardiography LVEDD (mm) LVESD (mm) EF (%) FS (%) LVMI (g/m2) Biochemical markers WBC (109/L) neutrophil ratio RBC (1012/L) Glucose (mmol/L) Total cholesterol (mmol/L) Triglyceride (mmol/L) Low-density lipoprotein cholesterol (mmol/L) High-density lipoprotein cholesterol (mmol/L) eGFR (ml · min−1 · 1.73 m−2) NT-proBNP (pg/ml) hs-CRP (mg/L) S100A12 (ng/ml) Medicine Aspirin ACEIs or ARBs β-Blockers Calcium-channel blockers Diuretics Statins Nitrates Digoxin
± ± ± ± ±
± ± ± ±
3.2 2.7 4.5 3.2 13.3
12.4 58.0 3.18 21.9
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; EF, ejection fraction; FS, shortening fraction; LVMI, left ventricular mass index; WBC, white blood cell; RBC, red blood cell; eGFR, estimated glomerular filtration rate; NT-proBNP, N-terminal pro-brain natriuretic peptide; hs-CRP, high-sensitivity C-reactive protein; ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers.
Y.-Y. He et al. / Clinical Biochemistry 48 (2015) 329–333
shown in Table 2. The S100A12 was not associated with age (r = 0.007, P = 0.920) or SBP (r = 0.007, P = 0.911) or DBP (r = 0.036, P =0.581). There was also no significant correlation between S100A12 and eGFR (r = 0.091, P = 0.180). However, plasma levels of S100A12 were positively correlated with white blood cell (WBC) count, neutrophil ratio, red blood cell count, glucose, NT-proBNP, hs-CRP, LVEDD, and LVESD. In particular, it correlated strongly with the inflammatory indicators neutrophil ratio (r = 0.351, P b 0.001), WBC (r = 0.339, P b 0.001), and hs-CRP (r = 0.316, P b 0.001). There was a negative correlation between S100A12 and EF (r = −0.182, P = 0.005).
Predictive value of S100A12 in CHF We followed up the CHF patients for 18 months. MCE occurred in 69 (38.98%) patients, consisting of 6 cardiac deaths and 63 readmissions. Clinical characteristics were compared between MCE and MCE-free patients (Table 3). MCE tended to occur in CHF patients who were older (P = 0.043). The plasma levels of hs-CRP in MCE patients (7.26 ± 4.95 mg/L) were significantly higher than those in MCE-free patients (5.57 ± 4.21 mg/L, P = 0.026). The same was observed with S100A12 levels, which were also significantly higher in MCE patients (61.33 ± 70.38 ng/mL) than that in MCE-free patients (42.27 ± 45.63 ng/mL, P = 0.004). CHF patients were stratified according to quartiles of S100A12 and hs-CRP, respectively (S100A12: Q1, 5.98 to b 21.07 ng/mL; Q2, 21.07 to b30.54 ng/mL; Q3, 30.54 to b 49.81 ng/mL; and Q4, 49.81 to 348.83 ng/mL; hs-CRP: Q1, 0.21 to b 2.50 mg/L; Q2, 2.50 to b4.83 mg/L; Q3, 4.83 to b8.26 mg/L; and Q4, 8.26 to 15.3 mg/L). Table 4 lists the baseline characteristics of CHF patients according to quartiles of S100A12. The frequency of males, body mass index (BMI), WBC, neutrophil ratio, and hs-CRP increased with increasing plasma S100A12 levels. The MCE-free survival rate was determined by Kaplan–Meier curve analysis (Fig. 1), which showed that MCE-free survival decreased along with increasing S100A12 or hs-CRP levels. There were significant differences between Q4 and Q1 in the S100A12-determined survival curve (75.0% vs 50.0%, P = 0.015). No difference was observed between the highest and lowest quartiles of hs-CRP levels (68.2% vs 50.0%, P = 0.077).
Independent factors for predicting MCE in CHF patients Cox proportional hazards regression analysis was performed to study the independent factors for predicting MCE in CHF patients. We analyzed age, sex, BMI, NYHA class, systolic blood pressure, diastolic blood pressure, LVEF, eGFR, hs-CRP, and S100A12 using univariate Cox regression analysis. Variables with a P value of less than 0.1 were entered into the multivariate Cox regression analysis, which was performed with the forward selection method. We found that among these variables, plasma eGFR and S100A12 were independent factors for predicting MCE, as reported in Table 5.
Table 2 Correlation between S100A12 and clinical characteristics of subjects.
WBC Neutrophil ratio RBC Glucose (mmol/L) NT-proBNP (pg/ml) hs-CRP (mg/L) LVEDD (mm) LVESD (mm) EF (%)
r
P value
0.339 0.351 0.169 0.153 0.214 0.316 0.170 0.189 −0.182
b0.001 b0.001 0.009 0.018 0.001 b0.001 0.009 0.004 0.005
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Table 3 Baseline characteristics in MCE and MCE-free CHF patients.
Sex, male/female Age (years) BMI (kg/m2) SBP DBP NYHA (II/III/IV) Echocardiography LVEDD (mm) LVESD (mm) EF (%) LVMI (g/m2) Biochemical markers eGFR (ml·min−1·1.73 m−2) NT-proBNP (pg/ml) hs-CRP (mg/L) S100A12 (ng/ml) Comorbidities Coronary heart disease Hypertension Diabetes Dilated cardiomyopathy Atrial fibrillation Medicine Aspirin ACEIs or ARBs β-Blockers Calcium-channel blockers Diuretics Statins Nitrates Digoxin
MCE
MCE-free
(n = 69)
(n = 108)
P value
51/18 66.5 ± 13.1 25.3 ± 4.2 131.1 ± 23.1 74.7 ± 10.5 22/36/11
76/32 61.8 ± 14.1 25.3 ± 4.3 133.5 ± 21.9 77.4 ± 12.3 46/51/11
0.610 0.043 0.906 0.473 0.139 0.110
55.3 ± 11.7 43.4 ± 13.1 43.1 ± 13.1 135.1 ± 41.2
57.4 ± 10.5 44.6 ± 11.6 42.2 ± 11.5 142.0 ± 44.1
0.180 0.405 0.661 0.302
75.0 ± 22.0 3900.3 ± 5060.1 7.26 ± 4.95 61.3 ± 70.4
83.1 ± 20.0 2963.2 ± 3537.4 5.57 ± 4.21 42.3 ± 45.6
0.012 0.072 0.026 0.004
46 (66.7%) 42 (60.9%) 21 (30.4%) 16 (23.2%) 21 (30.4%)
73 (67.6%) 65 (60.2%) 31 (28.7%) 24 (22.2%) 28 (25.9%)
0.898 0.928 0.805 0.881 0.513
37 (53.6%) 39 (56.5%) 49 (71.0%) 15 (21.7%) 44 (63.8%) 40 (58.0%) 44 (63.8%) 23 (33.3%)
55 (50.9%) 60 (55.6%) 63 (58.3%) 32 (29.6%) 60 (55.6%) 61 (56.5%) 54 (50.0%) 34 (31.5%)
0.726 0.900 0.088 0.246 0.278 0.845 0.072 0.797
Discussion Our results indicated that plasma levels of S100A12 were significantly higher in CHF patients than in control subjects. S100A12 levels were significantly associated with neutrophil ratio, WBC, and hs-CRP, suggesting that S100A12 participated in the inflammatory response in CHF patients. S100A12 levels were also higher in patients with cardiac events than in those without cardiac events. Furthermore, we found that the occurrence of MCE increased along with increasing plasma S100A12 levels. S100A12 was an independent risk factor for MCE in patients with CHF by Cox proportional hazards regression analysis. To our knowledge, this is the first affirmation of a relationship between S100A12 and CHF. Our results demonstrated that this first-look analysis of the utility of S100A12 in heart failure patients may be contributory to prognostication. CHF, as a systemic illness, is recognized to activate inflammation in the pathological process. The role of inflammatory cytokines in CHF has aroused great interest among clinicians. There is considerable evidence to indicate that inflammatory markers are independent prognostic and risk factors in patients with CHF, particularly hs-CRP [15,16]. In the present study, the significantly increased plasma hs-CRP levels in CHF patients suggested the activation of inflammation in CHF. Our finding that hs-CRP levels in the MCE group were higher than MCE-free group further validated the association between hs-CRP and the prognosis of CHF patients. As a novel inflammatory marker, the mechanism of S100A12 in inflammation is complicated and not clearly elucidated. S100A12 is mainly distributed in the cytoplasm of granulocytes and translocates to membrane and cytoskeleton elements by interactions with calcium [17]. When secreted to extracellular space in an autocrine or paracrine manner, S100A12 contributes to the generation of immune responses. RAGE is the well-known natural target protein of S100A12. The ligation
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Table 4 Baseline characteristics in CHF patients according to quartiles of S100A12.
Sex, male/female Age (years) BMI (kg/m2) SBP DBP NYHA (II/III/IV) Echocardiography LVEDD (mm) LVESD (mm) EF (%) LVMI (g/m2) Biochemical markers WBC (109/L) Neutrophil ratio eGFR (ml·min−1·1.73 m−2) NT-proBNP (pg/ml) hs-CRP (mg/L) S100A12 (ng/ml)
Q1
Q2
Q3
Q4
(n = 44)
(n = 45)
(n = 44)
(n = 44)
27/17 64.7 ± 14.1 24.0 ± 3.4 130.2 ± 17.9 75.2 ± 10.4 19/20/5
29/16 63.7 ± 12.9 25.3 ± 3.5 135.8 ± 21.4 77.1 ± 13.08 15/26/4
36/8* 63.7 ± 14.1 26.0 ± 4.9* 128.0 ± 16.6 75.9 ± 11.1 14/27/3
35/9* 61.9 ± 14.5 25.9 ± 4.9* 136.3 ± 30.5 77.0 ± 12.2 20/14/10
55.2 ± 10.9 42.7 ± 12.4 43.4 ± 12.1 133.8 ± 40.7
57.3 ± 12.1 45.1 ± 13.4 42.9 ± 13.7 139.9 ± 48.6
58.2 ± 10.3 45.7 ± 11.0 40.8 ± 10.3 143.3 ± 43.7
55.7 ± 10.9 43.1 ± 12.1 43.2 ± 12.7 140.0 ± 39.5
5.84 ± 1.27 0.58 ± 0.09 81.0 ± 21.3 2891.9 ± 3536.1 4.65 ± 4.32 15.3 ± 3.69
6.49 ± 1.63 0.62 ± 0.10* 76.5 ± 20.4 3141.2 ± 3579.7 5.74 ± 4.33 25.3 ± 2.45†
6.55 ± 1.34 0.62 ± 0.08* 79.1 ± 21.0 2960.5 ± 3019.0 6.43 ± 4.13† 38.7 ± 5.73†
7.42 ± 2.81† 0.67 ± 0.09† 83.0 ± 21.9 4299.8 ± 6128.4 8.12 ± 4.93† 120.0 ± 79.4†
*P b 0.05, †P b 0.01 versus Q1.
of S100A12 with RAGE results in activation of NF-κB, a central transcription factor involved in inflammatory events, and thereby the production of proinflammatory cytokines and adhesion molecules [18–20]. It is reported that soluble RAGE is related to the risk stratification of heart failure and may be an independent prognostic factor in heart failure patients [21,22]. S100A12 is also an endogenous ligand of toll-like receptor 4 (TLR4), acting as a proinflammatory amplifier. During early inflammation, binding of S100A12 to TLR4 induces monocyte activation in a cross-talk with activated granulocytes [23]. It is reported that S100A12-mediated inflammation worsens the development of cardiac hypertrophy and ectopic cardiac calcification in chronic kidney disease [24]. Saito et al. [12] demonstrated that S100A12 is of clinical value in the evaluation of MCE occurrence in patients with stable CAD, especially in predicting the incidence of heart failure. In the present study, compared with controls, plasma S100A12 levels were significantly increased in CHF patients, suggesting an association between S100A12 and heart failure. This finding may reflect chronic inflammation in CHF patients. By Kaplan–Meier curve analysis, we found a significant difference between Q4 and Q1 in the survival curve determined by S100A12 but not by hs-CRP, indicating the superiority of plasma S100A12 as a prognostic factor of CHF. Apart from S100A12, S100A8/A9 and S100B are the best known ligands of RAGE. The benefits of S100A8/A9 and S100B in CHF are under investigation in clinical studies. Ma et al. [13] demonstrated that increased serum level of S100A8/A9 complex is an independent risk factor in elderly patients with severe heart failure. Li et al. [25] proved that S100B is
associated with the severity of cardiac dysfunction and provides significant information for the prediction of MCE in CHF patients. In the present study, we found that there was no significant difference between plasma S100A12 and eGFR levels, but they were both independent factors for predicting MCE by Cox proportional hazards regression analysis. This result was consistent with previous study reported by Kalousová et al. [26]. They pointed out that although S100A12 levels are slightly but nonsignificantly increased in patients with decreased kidney function, it is markedly correlated with inflammatory markers and related to the mortality of hemodialysis patients. However, Nakashima et al. [27] demonstrated that circulating S100A12 is significantly elevated in hemodialysis patients and associated with the prognosis, especially cardiovascular disease-related mortality. These findings suggest that further studies clarifying the relationship between S100A12 and kidney function are warranted. There are some limitations to our study. Some baseline characteristics of subjects did not match exactly among groups. The patients in the CHF group were older than the controls, although our results implied no association between S100A12 and age. Moreover, the relatively low mortality (6 cardiac deaths) of CHF patients in this study may be associated with the fact that patients with severe renal dysfunction were excluded, as eGFR is an independent prognostic factor. This may also be a reflection of good patient compliance. This study was on a small scale, with a limited number of patients and a short duration of follow-up, so the significance of S100A12 in CHF could not be definitively established. Nonetheless, our findings provide supporting evidence for S100A12 as a
Fig. 1. Kaplan–Meier curve analysis. (A) MCE-free survival in CHF patients according to quartile of plasma S100A12 level. There were significant differences between Q3 and Q1 (P = 0.046) as well as Q4 and Q1 (P = 0.015). (B) MCE-free survival in CHF patients according to quartile of plasma hs-CRP level. No difference was observed between Q4 and Q1 (P = 0.077).
Y.-Y. He et al. / Clinical Biochemistry 48 (2015) 329–333 Table 5 Independent factors for predicting MCE in CHF patients at 18 months. Univariate
Age NYHA eGFR hs-CRP S100A12
Multivariable
HR (95% CI)
P value
1.019 (1.000–1.038) 1.361 (0.985–1.934) 0.986 (0.975–0.997) 1.065 (1.014–1.118) 1.004 (1.001–1.008)
0.047 0.085 0.013 0.011 0.010
HR (95% CI)
P value
0.985 (0.974–0.996)
0.417 0.219 0.009 0.102 0.009
1.004 (1.001–1.008)
potential prognostic indicator of CHF. A large-scale investigation of patients with CHF needs to be undertaken to further confirm the importance of S100A12. Conclusions In conclusion, our results demonstrated that S100A12 has potential as a novel biomarker to predict MCE in patients with heart failure and that more studies are needed to provide further evidence to support or refute this hypothesis. Funding sources This study was supported by the Ministry Science Foundation of the Chinese People's Liberation Army during the 12th Five-Year Plan Period (grant no. BWS12J048) and the Major International Science and Technology Cooperation Projects (grant no. 2013DFA31170). Disclosures The authors have no conflicts of interest to disclose. References [1] Diwan A, Tran T, Misra A, Mann DL. Inflammatory mediators and the failing heart: a translational approach. Curr Mol Med 2003;3:161–82. [2] Yndestad A, Damås JK, Øie E, Ueland T, Gullestad L, Aukrust P. Role of inflammation in the progression of heart failure. Curr Cardiol Rep 2007;9:236–41. [3] Braunwald E. Biomarkers in heart failure. N Engl J Med 2008;358:2148–59. [4] Vogl T, Pröpper C, Hartmann M, Strey A, Strupat K, van den Bos C, et al. S100A12 is expressed exclusively by granulocytes and acts independently from MRP8 and MRP14. J Biol Chem 1999;274:25291–6. [5] Pietzsch J, Hoppmann S. Human S100A12: a novel key player in inflammation. Amino Acids 2009;36:381–9. [6] Ilg EC, Troxler H, Bürgisser DM, Kuster T, Markert M, Guignard F, et al. Amino acid sequence determination of human S100A12 (P6, Calgranulin C, CGRP, CAAF1) by tandem mass spectrometry. Biochem Biophys Res Commun 1996;225:146–50. [7] Foell D, Ichida F, Vogl T, Yu X, Chen R, Miyawaki T, et al. S100A12 (EN-RAGE) in monitoring Kawasaki disease. Lancet 2003;361:1270–2. [8] Brinar M, Cleynen I, Coopmans T, Van Assche G, Rutgeerts P, Vermeire S. Serum S100A12 as a new marker for inflammatory bowel disease and its relationship with disease activity. Gut 2010;59:1728–9. [9] van de Logt F, Day AS. S100A12: a noninvasive marker of inflammation in inflammatory bowel disease. J Dig Dis 2013;14:62–7.
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[10] Kim JK, Park S, Lee MJ, Song YR, Han SH, Kim SG, et al. Plasma levels of soluble receptor for advanced glycation end products (sRAGE) and proinflammatory ligand for RAGE (EN-RAGE) are associated with carotid atherosclerosis in patients with peritoneal dialysis. Atherosclerosis 2012;220:208–14. [11] Goyette J, Yan WX, Yamen E, Chung YM, Lim SY, Hsu K, et al. Pleiotropic roles of S100A12 in coronary atherosclerotic plaque formation and rupture. J Immunol 2009;183:593–603. [12] Saito T, Hojo Y, Ogoyama Y, Hirose M, Ikemoto T, Katsuki T, et al. S100A12 as a marker to predict cardiovascular events in patients with chronic coronary artery disease. Circ J 2012;76:2647–52. [13] Ma LP, Haugen E, Ikemoto M, Fujita M, Terasaki F, Fu M. S100A8/A9 complex as a new biomarker in prediction of mortality in elderly patients with severe heart failure. Int J Cardiol 2012;155:26–32. [14] Dickstein K, Cohen-Solal A, Filippatos G, McMurray JJ, Ponikowski P, Poole-Wilson PA, et al. ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure 2008: the Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure 2008 of the European Society of Cardiology. Developed in collaboration with the Heart Failure Association of the ESC (HFA) and endorsed by the European Society of Intensive Care Medicine (ESICM). Eur Heart J 2008;29: 2388–442. [15] Yin WH, Chen JW, Jen HL, Chiang MC, Huang WP, Feng AN, et al. Independent prognostic value of elevated high-sensitivity C-reactive protein in chronic heart failure. Am Heart 2004;J147:931–8. [16] Araújo JP, Lourenço P, Azevedo A, Friões F, Rocha-Gonçalves F, Ferreira A, et al. Prognostic value of high-sensitivity C-reactive protein in heart failure: a systematic review. J Card Fail 2009;15:256–66. [17] Garcia AF, Lopes JL, Costa-Filho AJ, Wallace BA, Araujo AP. Membrane interactions of S100A12 (Calgranulin C). PLoS One 2013;8:e82555. [18] Hofmann MA, Drury S, Fu C, Qu W, Taguchi A, Lu Y, et al. RAGE mediates a novel proinflammatory axis: a central cell surface receptor for S100/calgranulin polypeptides. Cell 1999;97:889–901. [19] Yang Z, Yan WX, Cai H, Tedla N, Armishaw C, Di Girolamo N, et al. S100A12 provokes mast cell activation: a potential amplification pathway in asthma and innate immunity. J Allergy Clin Immunol 2007;119:106–14. [20] Chavakis T, Bierhaus A, Nawroth PP. RAGE (receptor for advanced glycation end products): a central player in the inflammatory response. Microbes Infect 2004;6: 1219–25. [21] Koyama Y, Takeishi Y, Niizeki T, Suzuki S, Kitahara T, Sasaki T, et al. Soluble receptor for advanced glycation end products (RAGE) is a prognostic factor for heart failure. J Card Fail 2008;14:133–9. [22] Raposeiras-Roubín S, Rodiño-Janeiro BK, Grigorian-Shamagian L, Moure-González M, Seoane-Blanco A, Varela-Román A, et al. Relation of soluble receptor for advanced glycation end products to predict mortality in patients with chronic heart failure independently of Seattle Heart Failure Score. Am J Cardiol 2011;107:938–44. [23] Foell D, Wittkowski H, Kessel C, Lüken A, Weinhage T, Varga G, et al. Proinflammatory S100A12 can activate human monocytes via Toll-like receptor 4. Am J Respir Crit Care Med 2013;187:1324–34. [24] Yan L, Mathew L, Chellan B, Gardner B, Earley J, Puri TS, et al. S100/Calgranulinmediated inflammation accelerates left ventricular hypertrophy and aortic valve sclerosis in chronic kidney disease in a receptor for advanced glycation end products-dependent manner. Arterioscler Thromb Vasc Biol 2014;34:1399–411. [25] Li JP, Lu L, Wang LJ, Zhang FR, Shen WF. Increased serum levels of S100B are related to the severity of cardiac dysfunction, renal insufficiency and major cardiac events in patients with chronic heart failure. Clin Biochem 2011;44:984–8. [26] Kalousová M, Kuběna AA, Benáková H, Dusilová-Sulková S, Tesař V, Zima T. ENRAGE (extracellular newly identified receptor for advanced glycation endproducts binding protein) and mortality of long-term hemodialysis patients: a prospective observational cohort study. Clin Biochem 2012;45:556–60. [27] Nakashima A, Carrero JJ, Qureshi AR, Miyamoto T, Anderstam B, Bárány P, et al. Effect of circulating soluble receptor for advanced glycation end products (sRAGE) and the proinflammatory RAGE ligand (EN-RAGE, S100A12) on mortality in hemodialysis patients. Clin J Am Soc Nephrol 2010;5:2213–9.
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Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Usefulness of S100A12 as a prognostic biomarker for adverse events in patients with heart failure Yun-Yun He a,b, Wei Yan a, Chun-Lei Liu a, Xin Li a, Rui-Jun Li a, Yang Mu a,b, Qian Jia a,b, Fen-Fen Wu a, Li-Li Wang c,⁎, Kun-Lun He a,⁎⁎ a b c
Department of Cardiology, Chinese PLA General Hospital, Beijing China School of Medicine, Nankai University, Tianjin China Beijing Institute of Pharmacology and Toxicology, Beijing China
a r t i c l e
i n f o
Article history: Received 8 October 2014 Received in revised form 13 November 2014 Accepted 18 November 2014 Available online 29 November 2014 Keywords: Heart failure Inflammation S100A12 hs-CRP
a b s t r a c t Objectives: S100A12 has been proposed as a novel pivotal factor in inflammation produced by granulocytes. The purpose of this study was to investigate the relationship between S100A12 and chronic heart failure (CHF). Design and methods: One hundred and seventy-seven patients with CHF and 66 subjects without CHF were included in this study. Plasma levels of S100A12 and high-sensitivity C-reactive protein (hs-CRP) were measured in all participants. After a follow-up period of 18 months for CHF patients, major cardiovascular events (MCE), including cardiac death and rehospitalization for heart failure, were recorded. Results: Plasma levels of S100A12 were significantly higher in CHF patients than in control subjects (P b 0.001) and positively correlated with hs-CRP (r = 0.316, P b 0.001). S100A12 levels were also higher in MCE patients than in MCE-free patients. The occurrence of MCE increased with advancing plasma S100A12 levels by stratification according to quartiles (Q4 vs Q1, P = 0.015). Cox proportional hazards regression analysis revealed that S100A12 was an independent risk factor for MCE in CHF patients (P = 0.009). Conclusions: S100A12 is a potential biomarker of CHF that may provide important information regarding the prediction of MCE in patients with CHF. © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Introduction Chronic heart failure (CHF), the end stage of various cardiovascular diseases, is a public health problem with high morbidity and mortality. Rational use of biomarkers for diagnosis, prognosis, and therapeutic monitoring are critically important in the management of these patients. As a systemic illness, CHF activates the immune system and inflammation and is thus characterized by elevated levels of proinflammatory cytokines in both the heart and the circulation [1,2]. Therefore, markers of inflammation have become a major focus of interest in CHF research [3]. Neutrophils, monocytes, and macrophages are important inflammatory effector cells. S100A12, a member of S100 calcium-binding protein family, is mainly secreted from these cells [4] and is recognized as
⁎ Correspondence to: L.-L. Wang, Beijing Institute of Pharmacology and Toxicology, Taiping Road 27, Beijing 100850, China. ⁎⁎ Correspondence to: K.-L. He, Department of Cardiology, Chinese PLA General Hospital, Fuxing Road 28, Beijing, 100853, China. Fax: +86 10 66939236. E-mail addresses: [email protected] (L.-L. Wang), [email protected] (K.-L. He).
potentially playing a key role in inflammation [5]. It is a close homologue to two other S100 proteins, S100A8 and S100A9 [6], collectively termed calgranulins or myeloid-related proteins. The interaction between S100A12 and the receptor for advanced glycation end products (RAGE) mediates the proinflammatory properties of this protein. Thus, S100A12 is also known as extracellular newly identified RAGE-binding protein (EN-RAGE). Several studies have identified S100A12 as being markedly expressed in various inflammatory disorders such as Kawasaki disease [7], inflammatory bowel disease [8,9], atherosclerosis [10,11], and so on. Furthermore, it has been recently reported that S100A12 is an independent factor for predicting major cardiovascular events (MCE) in patients with stable coronary artery disease (CAD) [12]. In addition, S100A8/A9, a highly homologous inflammatory mediator with S100A12, provides significant predictive value for 1-year mortality in elderly patients with severe heart failure [13]. However, no information about the relationship between S100A12 and CHF is available. We hypothesized that S100A12 may provide important clinical prognostic significance for patients with CHF. In this study, we evaluated plasma S100A12 levels to determine whether S100A12 could be used as a biomarker for the prediction of MCE in these patients.
http://dx.doi.org/10.1016/j.clinbiochem.2014.11.016 0009-9120/© 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
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Y.-Y. He et al. / Clinical Biochemistry 48 (2015) 329–333
Methods
Results
Subjects
Baseline characteristics of subjects
One hundred and seventy-seven patients with CHF (New York Heart Association [NYHA] functional class II–IV) who were admitted to the Department of Cardiology, Chinese PLA General Hospital (Beijing, China), from April 2011 to October 2012 were included in the study. The diagnosis of CHF was made according to the criteria of the European Society of Cardiology [14] by symptoms or signs, electrocardiogram, chest radiograph, and echocardiography. All patients had stable clinical symptoms for at least 2 weeks. The comorbidities of heart failure were identified as coronary heart disease (67.2%), hypertension (60.5%), diabetes (29.4%), atrial fibrillation (27.7%), and dilated cardiomyopathy (22.6%). Sixty-six subjects without heart failure were enrolled as controls. Physical examinations, echocardiography, and biochemical markers were evaluated. The exclusion criteria were acute infections, severe renal dysfunction (estimated glomerular filtration rate [eGFR] b30 ml·min–1·1.73m–2, calculated by CKD-EPI formula), malignant tumors, acute coronary syndrome, and acute cerebrovascular diseases within 3 months, immunological diseases, and other patients received anti-inflammatory agents. After a follow-up period of 18 months, MCE, including cardiac death and rehospitalization for heart failure, were documented. The study was approved by the Ethical Committee for Medical Research of Chinese PLA General Hospital and was conducted in accordance with Helsinki Declaration. Informed consent was obtained from all subjects.
The baseline characteristics of all subjects are listed in Table 1. A total of 177 CHF participants and 66 controls were included in this study. The echocardiographic results showed that in CHF patients, left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), and left ventricular mass index (LVMI) significantly increased while ejection fraction (EF) and fractional shortening decreased, indicating changes in left ventricular structure and function. The mean values of plasma NT-proBNP, hs-CRP, and S100A12 in all CHF patients were 3320.3 pg/mL, 6.22 mg/L, and 49.70 ng/mL, respectively, significantly higher than those in controls (63.0 pg/mL, 2.81 mg/L, and 27.13 ng/mL) (P b 0.001). The eGFR was lower in the CHF group than in controls (P b 0.001).
Correlation of S100A12 levels with baseline characteristics The Kolmogorov–Smirnov test indicated that values of S100A12 did not comply with the normal distribution. A Spearman correlation test was carried out to analyze the correlation of S100A12 levels with other parameters in all subjects. The results with a correlation are
Table 1 Baseline characteristics of subjects. CHF patients
Laboratory measurements
Controls (n = 66)
P value
127/50 63.5 ± 13.9 25.3 ± 4.3 132.6 ± 22.4 76.3 ± 11.7 68/87/22
40/26 58.0 ± 11.1 24.6 ± 3.7 123.1 ± 14.9 71.5 ± 10.1
0.096 0.004 0.294 0.002 0.003 —
56.6 ± 11.0 44.1 ± 12.2 42.6 ± 12.2 23.0 ± 7.4 139.2 ± 43.0
43.5 29.2 60.7 32.3 83.3
b0.001 b0.001 b0.001 b0.001 b0.001
6.54 ± 1.90 0.620 ± 0.094 4.45 ± 0.61 6.45 ± 2.68 4.11 ± 1.05 1.42 ± 0.83 1.08 ± 0.34
5.85 ± 1.37 0.552 ± 0.089 4.43 ± 0.58 5.24 ± 1.13 4.38 ± 0.72 1.43 ± 1.01 1.17 ± 0.30
0.002 b0.001 0.782 b0.001 0.024 0.866 0.024
2.43 ± 0.87
2.66 ± 0.59
0.066
79.9 ± 21.1 3320.3 ± 4240.6 6.22 ± 4.57 49.7 ± 57.2
95.0 63.0 2.81 27.1
b0.001 b0.001 b0.001 b0.001
92 (52.0%) 99 (56.0%) 112 (63.3%) 47 (26.6%) 104 (58.8%) 101 (57.1%) 98 (55.4%) 57 (32.2%)
2 (3.0%) 4 (6.1%) 7 (10.6%) 4 (6.1%) 0 20 (30.3%) 0 0
(n = 177)
Peripheral blood samples from subjects were collected into EDTA anticoagulant tubes after an overnight fast on the second day of hospitalization. Blood samples were centrifuged immediately at 3000 ×g for 10 min at 4 °C to separate plasma from blood cells and stored at − 80 °C until measurement. The plasma concentrations of S100A12 were measured according to the manufacturer's instructions using commercially available enzyme-linked immunosorbent assay kits (CycLex, Nagano, Japan). The performance characteristics of the S100A12 assay showed that the minimum detectable dose was ranged from 0.043 to 0.068 ng/mL, with the mean value at 0.056 ng/mL. The coefficient of variation of intra-assay and inter-assay was 4.3% and 5.4%, respectively. High-sensitivity C-reactive protein (hs-CRP) was measured by latex-enhanced nephelometry (Jiancheng, Nanjing, China). Nterminal pro-brain natriuretic peptide (NT-proBNP) was measured by electrochemiluminescence.
Statistical analysis All continuous variables are presented as mean ± standard deviation. All tests were carried out using SPSS version 15.0 statistical software. The normal distribution test for continuous variables was conducted using the Kolmogorov–Smirnov test. Statistical analysis of normal distribution data were performed using an unpaired Student t test between two groups and by one-way analysis of variance followed by a least-squares difference test for multiple comparisons. Non-normal distribution data were analyzed using the Mann–Whitney U test for continuous variables and the chi-square test for discrete variables. A linear correlation test was employed to study the association between S100A12 and other parameters. MCE-free survival curves were calculated by the Kaplan–Meier method and were compared using the log-rank test. Cox proportional hazards regression analysis was used to examine independent factors for predicting MCE in CHF patients. Differences were considered statistically significant at a two-tailed P value of less than 0.05.
Sex, male/female Age (years) BMI (kg/m2) SBP DBP NYHA class (II/III/IV) Echocardiography LVEDD (mm) LVESD (mm) EF (%) FS (%) LVMI (g/m2) Biochemical markers WBC (109/L) neutrophil ratio RBC (1012/L) Glucose (mmol/L) Total cholesterol (mmol/L) Triglyceride (mmol/L) Low-density lipoprotein cholesterol (mmol/L) High-density lipoprotein cholesterol (mmol/L) eGFR (ml · min−1 · 1.73 m−2) NT-proBNP (pg/ml) hs-CRP (mg/L) S100A12 (ng/ml) Medicine Aspirin ACEIs or ARBs β-Blockers Calcium-channel blockers Diuretics Statins Nitrates Digoxin
± ± ± ± ±
± ± ± ±
3.2 2.7 4.5 3.2 13.3
12.4 58.0 3.18 21.9
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; EF, ejection fraction; FS, shortening fraction; LVMI, left ventricular mass index; WBC, white blood cell; RBC, red blood cell; eGFR, estimated glomerular filtration rate; NT-proBNP, N-terminal pro-brain natriuretic peptide; hs-CRP, high-sensitivity C-reactive protein; ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers.
Y.-Y. He et al. / Clinical Biochemistry 48 (2015) 329–333
shown in Table 2. The S100A12 was not associated with age (r = 0.007, P = 0.920) or SBP (r = 0.007, P = 0.911) or DBP (r = 0.036, P =0.581). There was also no significant correlation between S100A12 and eGFR (r = 0.091, P = 0.180). However, plasma levels of S100A12 were positively correlated with white blood cell (WBC) count, neutrophil ratio, red blood cell count, glucose, NT-proBNP, hs-CRP, LVEDD, and LVESD. In particular, it correlated strongly with the inflammatory indicators neutrophil ratio (r = 0.351, P b 0.001), WBC (r = 0.339, P b 0.001), and hs-CRP (r = 0.316, P b 0.001). There was a negative correlation between S100A12 and EF (r = −0.182, P = 0.005).
Predictive value of S100A12 in CHF We followed up the CHF patients for 18 months. MCE occurred in 69 (38.98%) patients, consisting of 6 cardiac deaths and 63 readmissions. Clinical characteristics were compared between MCE and MCE-free patients (Table 3). MCE tended to occur in CHF patients who were older (P = 0.043). The plasma levels of hs-CRP in MCE patients (7.26 ± 4.95 mg/L) were significantly higher than those in MCE-free patients (5.57 ± 4.21 mg/L, P = 0.026). The same was observed with S100A12 levels, which were also significantly higher in MCE patients (61.33 ± 70.38 ng/mL) than that in MCE-free patients (42.27 ± 45.63 ng/mL, P = 0.004). CHF patients were stratified according to quartiles of S100A12 and hs-CRP, respectively (S100A12: Q1, 5.98 to b 21.07 ng/mL; Q2, 21.07 to b30.54 ng/mL; Q3, 30.54 to b 49.81 ng/mL; and Q4, 49.81 to 348.83 ng/mL; hs-CRP: Q1, 0.21 to b 2.50 mg/L; Q2, 2.50 to b4.83 mg/L; Q3, 4.83 to b8.26 mg/L; and Q4, 8.26 to 15.3 mg/L). Table 4 lists the baseline characteristics of CHF patients according to quartiles of S100A12. The frequency of males, body mass index (BMI), WBC, neutrophil ratio, and hs-CRP increased with increasing plasma S100A12 levels. The MCE-free survival rate was determined by Kaplan–Meier curve analysis (Fig. 1), which showed that MCE-free survival decreased along with increasing S100A12 or hs-CRP levels. There were significant differences between Q4 and Q1 in the S100A12-determined survival curve (75.0% vs 50.0%, P = 0.015). No difference was observed between the highest and lowest quartiles of hs-CRP levels (68.2% vs 50.0%, P = 0.077).
Independent factors for predicting MCE in CHF patients Cox proportional hazards regression analysis was performed to study the independent factors for predicting MCE in CHF patients. We analyzed age, sex, BMI, NYHA class, systolic blood pressure, diastolic blood pressure, LVEF, eGFR, hs-CRP, and S100A12 using univariate Cox regression analysis. Variables with a P value of less than 0.1 were entered into the multivariate Cox regression analysis, which was performed with the forward selection method. We found that among these variables, plasma eGFR and S100A12 were independent factors for predicting MCE, as reported in Table 5.
Table 2 Correlation between S100A12 and clinical characteristics of subjects.
WBC Neutrophil ratio RBC Glucose (mmol/L) NT-proBNP (pg/ml) hs-CRP (mg/L) LVEDD (mm) LVESD (mm) EF (%)
r
P value
0.339 0.351 0.169 0.153 0.214 0.316 0.170 0.189 −0.182
b0.001 b0.001 0.009 0.018 0.001 b0.001 0.009 0.004 0.005
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Table 3 Baseline characteristics in MCE and MCE-free CHF patients.
Sex, male/female Age (years) BMI (kg/m2) SBP DBP NYHA (II/III/IV) Echocardiography LVEDD (mm) LVESD (mm) EF (%) LVMI (g/m2) Biochemical markers eGFR (ml·min−1·1.73 m−2) NT-proBNP (pg/ml) hs-CRP (mg/L) S100A12 (ng/ml) Comorbidities Coronary heart disease Hypertension Diabetes Dilated cardiomyopathy Atrial fibrillation Medicine Aspirin ACEIs or ARBs β-Blockers Calcium-channel blockers Diuretics Statins Nitrates Digoxin
MCE
MCE-free
(n = 69)
(n = 108)
P value
51/18 66.5 ± 13.1 25.3 ± 4.2 131.1 ± 23.1 74.7 ± 10.5 22/36/11
76/32 61.8 ± 14.1 25.3 ± 4.3 133.5 ± 21.9 77.4 ± 12.3 46/51/11
0.610 0.043 0.906 0.473 0.139 0.110
55.3 ± 11.7 43.4 ± 13.1 43.1 ± 13.1 135.1 ± 41.2
57.4 ± 10.5 44.6 ± 11.6 42.2 ± 11.5 142.0 ± 44.1
0.180 0.405 0.661 0.302
75.0 ± 22.0 3900.3 ± 5060.1 7.26 ± 4.95 61.3 ± 70.4
83.1 ± 20.0 2963.2 ± 3537.4 5.57 ± 4.21 42.3 ± 45.6
0.012 0.072 0.026 0.004
46 (66.7%) 42 (60.9%) 21 (30.4%) 16 (23.2%) 21 (30.4%)
73 (67.6%) 65 (60.2%) 31 (28.7%) 24 (22.2%) 28 (25.9%)
0.898 0.928 0.805 0.881 0.513
37 (53.6%) 39 (56.5%) 49 (71.0%) 15 (21.7%) 44 (63.8%) 40 (58.0%) 44 (63.8%) 23 (33.3%)
55 (50.9%) 60 (55.6%) 63 (58.3%) 32 (29.6%) 60 (55.6%) 61 (56.5%) 54 (50.0%) 34 (31.5%)
0.726 0.900 0.088 0.246 0.278 0.845 0.072 0.797
Discussion Our results indicated that plasma levels of S100A12 were significantly higher in CHF patients than in control subjects. S100A12 levels were significantly associated with neutrophil ratio, WBC, and hs-CRP, suggesting that S100A12 participated in the inflammatory response in CHF patients. S100A12 levels were also higher in patients with cardiac events than in those without cardiac events. Furthermore, we found that the occurrence of MCE increased along with increasing plasma S100A12 levels. S100A12 was an independent risk factor for MCE in patients with CHF by Cox proportional hazards regression analysis. To our knowledge, this is the first affirmation of a relationship between S100A12 and CHF. Our results demonstrated that this first-look analysis of the utility of S100A12 in heart failure patients may be contributory to prognostication. CHF, as a systemic illness, is recognized to activate inflammation in the pathological process. The role of inflammatory cytokines in CHF has aroused great interest among clinicians. There is considerable evidence to indicate that inflammatory markers are independent prognostic and risk factors in patients with CHF, particularly hs-CRP [15,16]. In the present study, the significantly increased plasma hs-CRP levels in CHF patients suggested the activation of inflammation in CHF. Our finding that hs-CRP levels in the MCE group were higher than MCE-free group further validated the association between hs-CRP and the prognosis of CHF patients. As a novel inflammatory marker, the mechanism of S100A12 in inflammation is complicated and not clearly elucidated. S100A12 is mainly distributed in the cytoplasm of granulocytes and translocates to membrane and cytoskeleton elements by interactions with calcium [17]. When secreted to extracellular space in an autocrine or paracrine manner, S100A12 contributes to the generation of immune responses. RAGE is the well-known natural target protein of S100A12. The ligation
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Table 4 Baseline characteristics in CHF patients according to quartiles of S100A12.
Sex, male/female Age (years) BMI (kg/m2) SBP DBP NYHA (II/III/IV) Echocardiography LVEDD (mm) LVESD (mm) EF (%) LVMI (g/m2) Biochemical markers WBC (109/L) Neutrophil ratio eGFR (ml·min−1·1.73 m−2) NT-proBNP (pg/ml) hs-CRP (mg/L) S100A12 (ng/ml)
Q1
Q2
Q3
Q4
(n = 44)
(n = 45)
(n = 44)
(n = 44)
27/17 64.7 ± 14.1 24.0 ± 3.4 130.2 ± 17.9 75.2 ± 10.4 19/20/5
29/16 63.7 ± 12.9 25.3 ± 3.5 135.8 ± 21.4 77.1 ± 13.08 15/26/4
36/8* 63.7 ± 14.1 26.0 ± 4.9* 128.0 ± 16.6 75.9 ± 11.1 14/27/3
35/9* 61.9 ± 14.5 25.9 ± 4.9* 136.3 ± 30.5 77.0 ± 12.2 20/14/10
55.2 ± 10.9 42.7 ± 12.4 43.4 ± 12.1 133.8 ± 40.7
57.3 ± 12.1 45.1 ± 13.4 42.9 ± 13.7 139.9 ± 48.6
58.2 ± 10.3 45.7 ± 11.0 40.8 ± 10.3 143.3 ± 43.7
55.7 ± 10.9 43.1 ± 12.1 43.2 ± 12.7 140.0 ± 39.5
5.84 ± 1.27 0.58 ± 0.09 81.0 ± 21.3 2891.9 ± 3536.1 4.65 ± 4.32 15.3 ± 3.69
6.49 ± 1.63 0.62 ± 0.10* 76.5 ± 20.4 3141.2 ± 3579.7 5.74 ± 4.33 25.3 ± 2.45†
6.55 ± 1.34 0.62 ± 0.08* 79.1 ± 21.0 2960.5 ± 3019.0 6.43 ± 4.13† 38.7 ± 5.73†
7.42 ± 2.81† 0.67 ± 0.09† 83.0 ± 21.9 4299.8 ± 6128.4 8.12 ± 4.93† 120.0 ± 79.4†
*P b 0.05, †P b 0.01 versus Q1.
of S100A12 with RAGE results in activation of NF-κB, a central transcription factor involved in inflammatory events, and thereby the production of proinflammatory cytokines and adhesion molecules [18–20]. It is reported that soluble RAGE is related to the risk stratification of heart failure and may be an independent prognostic factor in heart failure patients [21,22]. S100A12 is also an endogenous ligand of toll-like receptor 4 (TLR4), acting as a proinflammatory amplifier. During early inflammation, binding of S100A12 to TLR4 induces monocyte activation in a cross-talk with activated granulocytes [23]. It is reported that S100A12-mediated inflammation worsens the development of cardiac hypertrophy and ectopic cardiac calcification in chronic kidney disease [24]. Saito et al. [12] demonstrated that S100A12 is of clinical value in the evaluation of MCE occurrence in patients with stable CAD, especially in predicting the incidence of heart failure. In the present study, compared with controls, plasma S100A12 levels were significantly increased in CHF patients, suggesting an association between S100A12 and heart failure. This finding may reflect chronic inflammation in CHF patients. By Kaplan–Meier curve analysis, we found a significant difference between Q4 and Q1 in the survival curve determined by S100A12 but not by hs-CRP, indicating the superiority of plasma S100A12 as a prognostic factor of CHF. Apart from S100A12, S100A8/A9 and S100B are the best known ligands of RAGE. The benefits of S100A8/A9 and S100B in CHF are under investigation in clinical studies. Ma et al. [13] demonstrated that increased serum level of S100A8/A9 complex is an independent risk factor in elderly patients with severe heart failure. Li et al. [25] proved that S100B is
associated with the severity of cardiac dysfunction and provides significant information for the prediction of MCE in CHF patients. In the present study, we found that there was no significant difference between plasma S100A12 and eGFR levels, but they were both independent factors for predicting MCE by Cox proportional hazards regression analysis. This result was consistent with previous study reported by Kalousová et al. [26]. They pointed out that although S100A12 levels are slightly but nonsignificantly increased in patients with decreased kidney function, it is markedly correlated with inflammatory markers and related to the mortality of hemodialysis patients. However, Nakashima et al. [27] demonstrated that circulating S100A12 is significantly elevated in hemodialysis patients and associated with the prognosis, especially cardiovascular disease-related mortality. These findings suggest that further studies clarifying the relationship between S100A12 and kidney function are warranted. There are some limitations to our study. Some baseline characteristics of subjects did not match exactly among groups. The patients in the CHF group were older than the controls, although our results implied no association between S100A12 and age. Moreover, the relatively low mortality (6 cardiac deaths) of CHF patients in this study may be associated with the fact that patients with severe renal dysfunction were excluded, as eGFR is an independent prognostic factor. This may also be a reflection of good patient compliance. This study was on a small scale, with a limited number of patients and a short duration of follow-up, so the significance of S100A12 in CHF could not be definitively established. Nonetheless, our findings provide supporting evidence for S100A12 as a
Fig. 1. Kaplan–Meier curve analysis. (A) MCE-free survival in CHF patients according to quartile of plasma S100A12 level. There were significant differences between Q3 and Q1 (P = 0.046) as well as Q4 and Q1 (P = 0.015). (B) MCE-free survival in CHF patients according to quartile of plasma hs-CRP level. No difference was observed between Q4 and Q1 (P = 0.077).
Y.-Y. He et al. / Clinical Biochemistry 48 (2015) 329–333 Table 5 Independent factors for predicting MCE in CHF patients at 18 months. Univariate
Age NYHA eGFR hs-CRP S100A12
Multivariable
HR (95% CI)
P value
1.019 (1.000–1.038) 1.361 (0.985–1.934) 0.986 (0.975–0.997) 1.065 (1.014–1.118) 1.004 (1.001–1.008)
0.047 0.085 0.013 0.011 0.010
HR (95% CI)
P value
0.985 (0.974–0.996)
0.417 0.219 0.009 0.102 0.009
1.004 (1.001–1.008)
potential prognostic indicator of CHF. A large-scale investigation of patients with CHF needs to be undertaken to further confirm the importance of S100A12. Conclusions In conclusion, our results demonstrated that S100A12 has potential as a novel biomarker to predict MCE in patients with heart failure and that more studies are needed to provide further evidence to support or refute this hypothesis. Funding sources This study was supported by the Ministry Science Foundation of the Chinese People's Liberation Army during the 12th Five-Year Plan Period (grant no. BWS12J048) and the Major International Science and Technology Cooperation Projects (grant no. 2013DFA31170). Disclosures The authors have no conflicts of interest to disclose. References [1] Diwan A, Tran T, Misra A, Mann DL. Inflammatory mediators and the failing heart: a translational approach. Curr Mol Med 2003;3:161–82. [2] Yndestad A, Damås JK, Øie E, Ueland T, Gullestad L, Aukrust P. Role of inflammation in the progression of heart failure. Curr Cardiol Rep 2007;9:236–41. [3] Braunwald E. Biomarkers in heart failure. N Engl J Med 2008;358:2148–59. [4] Vogl T, Pröpper C, Hartmann M, Strey A, Strupat K, van den Bos C, et al. S100A12 is expressed exclusively by granulocytes and acts independently from MRP8 and MRP14. J Biol Chem 1999;274:25291–6. [5] Pietzsch J, Hoppmann S. Human S100A12: a novel key player in inflammation. Amino Acids 2009;36:381–9. [6] Ilg EC, Troxler H, Bürgisser DM, Kuster T, Markert M, Guignard F, et al. Amino acid sequence determination of human S100A12 (P6, Calgranulin C, CGRP, CAAF1) by tandem mass spectrometry. Biochem Biophys Res Commun 1996;225:146–50. [7] Foell D, Ichida F, Vogl T, Yu X, Chen R, Miyawaki T, et al. S100A12 (EN-RAGE) in monitoring Kawasaki disease. Lancet 2003;361:1270–2. [8] Brinar M, Cleynen I, Coopmans T, Van Assche G, Rutgeerts P, Vermeire S. Serum S100A12 as a new marker for inflammatory bowel disease and its relationship with disease activity. Gut 2010;59:1728–9. [9] van de Logt F, Day AS. S100A12: a noninvasive marker of inflammation in inflammatory bowel disease. J Dig Dis 2013;14:62–7.
333
[10] Kim JK, Park S, Lee MJ, Song YR, Han SH, Kim SG, et al. Plasma levels of soluble receptor for advanced glycation end products (sRAGE) and proinflammatory ligand for RAGE (EN-RAGE) are associated with carotid atherosclerosis in patients with peritoneal dialysis. Atherosclerosis 2012;220:208–14. [11] Goyette J, Yan WX, Yamen E, Chung YM, Lim SY, Hsu K, et al. Pleiotropic roles of S100A12 in coronary atherosclerotic plaque formation and rupture. J Immunol 2009;183:593–603. [12] Saito T, Hojo Y, Ogoyama Y, Hirose M, Ikemoto T, Katsuki T, et al. S100A12 as a marker to predict cardiovascular events in patients with chronic coronary artery disease. Circ J 2012;76:2647–52. [13] Ma LP, Haugen E, Ikemoto M, Fujita M, Terasaki F, Fu M. S100A8/A9 complex as a new biomarker in prediction of mortality in elderly patients with severe heart failure. Int J Cardiol 2012;155:26–32. [14] Dickstein K, Cohen-Solal A, Filippatos G, McMurray JJ, Ponikowski P, Poole-Wilson PA, et al. ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure 2008: the Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure 2008 of the European Society of Cardiology. Developed in collaboration with the Heart Failure Association of the ESC (HFA) and endorsed by the European Society of Intensive Care Medicine (ESICM). Eur Heart J 2008;29: 2388–442. [15] Yin WH, Chen JW, Jen HL, Chiang MC, Huang WP, Feng AN, et al. Independent prognostic value of elevated high-sensitivity C-reactive protein in chronic heart failure. Am Heart 2004;J147:931–8. [16] Araújo JP, Lourenço P, Azevedo A, Friões F, Rocha-Gonçalves F, Ferreira A, et al. Prognostic value of high-sensitivity C-reactive protein in heart failure: a systematic review. J Card Fail 2009;15:256–66. [17] Garcia AF, Lopes JL, Costa-Filho AJ, Wallace BA, Araujo AP. Membrane interactions of S100A12 (Calgranulin C). PLoS One 2013;8:e82555. [18] Hofmann MA, Drury S, Fu C, Qu W, Taguchi A, Lu Y, et al. RAGE mediates a novel proinflammatory axis: a central cell surface receptor for S100/calgranulin polypeptides. Cell 1999;97:889–901. [19] Yang Z, Yan WX, Cai H, Tedla N, Armishaw C, Di Girolamo N, et al. S100A12 provokes mast cell activation: a potential amplification pathway in asthma and innate immunity. J Allergy Clin Immunol 2007;119:106–14. [20] Chavakis T, Bierhaus A, Nawroth PP. RAGE (receptor for advanced glycation end products): a central player in the inflammatory response. Microbes Infect 2004;6: 1219–25. [21] Koyama Y, Takeishi Y, Niizeki T, Suzuki S, Kitahara T, Sasaki T, et al. Soluble receptor for advanced glycation end products (RAGE) is a prognostic factor for heart failure. J Card Fail 2008;14:133–9. [22] Raposeiras-Roubín S, Rodiño-Janeiro BK, Grigorian-Shamagian L, Moure-González M, Seoane-Blanco A, Varela-Román A, et al. Relation of soluble receptor for advanced glycation end products to predict mortality in patients with chronic heart failure independently of Seattle Heart Failure Score. Am J Cardiol 2011;107:938–44. [23] Foell D, Wittkowski H, Kessel C, Lüken A, Weinhage T, Varga G, et al. Proinflammatory S100A12 can activate human monocytes via Toll-like receptor 4. Am J Respir Crit Care Med 2013;187:1324–34. [24] Yan L, Mathew L, Chellan B, Gardner B, Earley J, Puri TS, et al. S100/Calgranulinmediated inflammation accelerates left ventricular hypertrophy and aortic valve sclerosis in chronic kidney disease in a receptor for advanced glycation end products-dependent manner. Arterioscler Thromb Vasc Biol 2014;34:1399–411. [25] Li JP, Lu L, Wang LJ, Zhang FR, Shen WF. Increased serum levels of S100B are related to the severity of cardiac dysfunction, renal insufficiency and major cardiac events in patients with chronic heart failure. Clin Biochem 2011;44:984–8. [26] Kalousová M, Kuběna AA, Benáková H, Dusilová-Sulková S, Tesař V, Zima T. ENRAGE (extracellular newly identified receptor for advanced glycation endproducts binding protein) and mortality of long-term hemodialysis patients: a prospective observational cohort study. Clin Biochem 2012;45:556–60. [27] Nakashima A, Carrero JJ, Qureshi AR, Miyamoto T, Anderstam B, Bárány P, et al. Effect of circulating soluble receptor for advanced glycation end products (sRAGE) and the proinflammatory RAGE ligand (EN-RAGE, S100A12) on mortality in hemodialysis patients. Clin J Am Soc Nephrol 2010;5:2213–9.
