Scandinavian Cardiovascular Journal, 2015; 49: 213–219
ORIGINAL ARTICLE
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NGAL and ST2 levels in ambulatory patients with chronic heart failure. Clinical and echocardiographic correlates
IOANNIS VENTOULIS1, LILIAN MANTZIARI1, SOPHIA-ANASTASIA MOURATOGLOU1, VASILEIOS KAMPERIDIS1, GEORGE GIANNAKOULAS1, ANTONIOS ZIAKAS1, DIMITRIS TSALIKAKIS4, GREGORY GIAMOUZIS2, ARETI HITOGLOU-MAKEDOU3 & HARALAMBOS KARVOUNIS1 11st
Department of Cardiology, AHEPA University Hospital, Thessaloniki, Greece, 2Department of Cardiology, Larissa University Hospital, Larissa, Greece, 3Laboratory of Microbiology, AHEPA University Hospital, Thessaloniki, Greece, and 4Research & Analysis Laboratory, Department of Informatics and Telecommunication Engineering, University of Western Macedonia, Kozani, Greece
Abstract Aim. Neutrophil gelatinase-associated lipocalin (NGAL) and ST2 receptor, a member of the interleukin-1 receptor family, are novel biomarkers with a potential role in the diagnosis and risk stratification of patients with chronic heart failure (CHF). There is however scarce data on their relation with clinical characteristics and cardiac function in patients with CHF. Methods. Consecutive ambulatory patients with CHF were studied. All patients underwent clinical and echocardiographic assessment, and blood samples were collected for the estimation of ST2 and NGAL serum levels during the same assessment. Results. A total of 76 patients (79% male, mean age: 63 ⫾ 14 years), with CHF and left ventricular ejection fraction of 28 ⫾ 7% were included. Median NGAL was 0.16 (0.09–0.275) mg/L and median ST2 was 0.0125 (0.0071–0.0176) mg/L. No association between NGAL and ST2 was observed. Multivariate analysis revealed tissue Doppler-derived right ventricular systolic velocity as an independent predictor of ST2, and the duration of HF and serum creatinine levels as independent predictors of NGAL. Conclusions. NGAL levels depend on the renal function and the duration of HF, while ST2 levels are affected by the right but not the left ventricular function and show no association with clinical indices of HF. Key words: chronic heart failure, echocardiography, novel biomarkers
Introduction There is an increasing interest on the role of novel biomarkers in the diagnosis and management of chronic heart failure (CHF). Numerous biomarkers have been proposed to be related to various pathophysiological pathways associated with CHF, such as the neurohormonal activation, myocyte injury, extracellular matrix remodeling, inflammation, and renal dysfunction. However, with the exception of natriuretic peptides, the role of novel biomarkers is still controversial and their use in everyday practice is not embraced by the current guidelines (1). Neutrophil gelatinase-associated lipocalin (NGAL) is a glycoprotein found in activated neutrophils and
renal tubular cells and is associated with kidney damage (2). Subsequent studies revealed the role of NGAL in cell survival, inflammation, and matrix degradation, and its expression was found to be enhanced in clinical and experimental HF (3). Limited data from clinical studies indicate an association of increased serum levels of NGAL with worse prognosis in patients with HF (4,5). However, controversy exists whether this relation is attributed to worsening of renal function, commonly seen in patients with HF, or to complicated pathophysiological mechanisms related to myocardial dysfunction (3). ST2 receptor is a member of the interleukin-1 (IL-1) receptor family and consists of a membraneanchored and a soluble form. The soluble form of
The first two authors contributed equally to the manuscript. Correspondence: Sophia-Anastasia Mouratoglou, 1st Department of Cardiology, AHEPA University Hospital, St. Kyriakidi 1, 54636, Thessaloniki, Greece. Tel: ⫹302310994830. Fax: ⫹302310994673. E-mail: [email protected] (Received 23 February 2015 ; revised 8 April 2015 ; accepted 11 April 2015) ISSN 1401-7431 print/ISSN 1651-2006 online © 2015 Informa Healthcare DOI: 10.3109/14017431.2015.1043141
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ST2 can be measured in the serum and is considered as a biomarker of myocardial strain and a potential mediator of myocardial fibrosis (6). It has been evaluated in the diagnosis (7), prognosis (6,8–10), and risk stratification of HF (11), as well as in patients’ response to treatment (12), while its association with the cardiac function in acute HF and in patients referred for echocardiography has also been previously investigated (13,14). In the present study, we aimed to investigate the association between NGAL and ST2 levels and clinical and echocardiographic findings in a cohort of patients with stable CHF.
Materials and methods Patient population Consecutive patients with stable CHF followed up at a tertiary cardiac center were prospectively enrolled in this study. Inclusion criteria were age ⬎18 years, ejection fraction (EF) ⬍ 45%, and history of known HF due to ischemic or idiopathic dilated cardiomyopathy. Exclusion criteria were recent (ⱕ 30 days) acute coronary syndrome, pulmonary edema or decompensation of HF, permanent pacemakers or cardiac resynchronization devices, malignancies, connective tissue disease, and severe renal failure requiring hemofiltration. The study protocol was approved by the ethics committee of our institution and all enrolled patients gave written informed consent. Clinical evaluation Clinical evaluation included a detailed medical history, clinical examination, electrocardiogram, and review of all drug therapies. Functional capacity was assessed with Duke Activity Status Index (DASI) questionnaire. DASI is a 12-point scale based on the ability to perform everyday activities, previously validated in patients with HF for the assessment of their functional capacity (15). Biomarkers Blood samples were collected by venipuncture on the day of the echocardiographic study. Urea and creatinine levels were measured with the standard methods as per routine practice. Estimated glomerular filtration rate (eGFR) was calculated using both the Cockroft–Gault and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulae. Two extra vials of whole blood were centrifuged within 60 min and serum was frozen at ⫺ 70°C until
analyzed. Both ST2 and NGAL were estimated in the same serum sample. ST2 was measured using the Quantikine Human ST2/IL-1 R4 Immunoassay (R&D, Minneapolis, USA, assay range: 31.3*10 ⫺ 6 ⫺ 2,000*10 ⫺ 6 mg/L), and NGAL was measured using the Quantikine Human Lipocalin-2/NGAL Immunoassay (R&D, Minneapolis, USA, assay range: 1.56*10 ⫺ 3 – 0.01*10 ⫺ 3 mg/L). These assays employ the quantitative sandwich enzyme immunoassay technique (ELISA). Echocardiographic study A full echocardiographic study was performed by a single accredited echocardiographer (VK) to all study subjects using the same equipment (Vivid 7, GE Vingmed Ultrasound, Horten, Norway).The echocardiographer was blind on patients’ clinical details and all measurements were done off-line. Standard echocardiographic views were used. Left ventricular (LV) dimensions were measured in 2D images at the long parasternal axis. LV volumes and EF were calculated using the biplane Simpson’s method from 4- and 2-chamber views at the apical axis. Atrial volumes and right ventricular (RV) dimensions were calculated from the 4-chamber view according to established methods (16). Tricuspid annular plane systolic excursion (TAPSE) was measured by twodimensional difference of end-diastolic and endsystolic lines (in cm) traced between the center of the ultrasound fan origin and the junction of RV lateral tricuspid annulus, in apical four-chamber view. RV systolic pressure was estimated by calculating the maximal velocity of the tricuspid regurgitant jet and then, further using the Bernoulli equation, adding to this value an estimated right atrial pressure based on both the size of the inferior vena cava and its respiratory variation. Pulsed Doppler echocardiography for the assessment of the standard diastolic filling velocities of both ventricles was performed using the apical four-chamber view. Thus, the peak early diastolic filling velocity (E-wave), peak late diastolic filling velocity (A-wave), and the ratio (E/A) were recorded. Pulsed-wave tissue Doppler imaging (TDI) was used to assess mitral and tricuspid annular velocities. Filters were set to exclude high-frequency signals, and the Nyquist limit was adjusted to a velocity range of 15–20 cm/s. Gains were minimized in order to allow for a clear tissue signal with minimum background noise. All TDI recordings were obtained during normal respiration, in the apical four-chamber view. A 5-mm sample volume was placed at the septal and lateral corner of the mitral annulus and at the lateral corner of the tricuspid annulus. The peak myocardial velocities during systole (S’), early
LVEDD (cm) 6.6 ⫾ 0.8 LVESD (cm) 5.7 ⫾ 1.1 LVEDV (ml) 194 ⫾ 65 LVESV (ml) 141 ⫾ 54 LA diam (cm) 4.8 ⫾ 0.6 LA vol (ml) 95 ⫾ 44 RA diam (cm) 4.1 ⫾ 0.9 RA vol (ml) 56 ⫾ 29 RV area D (cm2) 18 ⫾ 6 RV area S (cm2) 11 ⫾ 5 RV mid (cm) 2.9 ⫾ 0.7 RV basal (cm) 4.0 ⫾ 0.9 TAPSE (cm) 1.8 ⫾ 0.5 Mitral E (cm/s) 0.86 ⫾ 0.33 Mitral A (cm/s) 0.63 ⫾ 0.30 Mitral DT (sec) 176 ⫾ 69
MI, myocardial infarction; BP, blood pressure; AA, aldosterone antagonists; DT, deceleration time; ACE/ARBs, angiotensin-converting enzyme/angiotensin receptor blockers.
Value Parameter N ⫽ 76
Serum NGAL levels were 0.16 (0.09–0.275) mg/L. All clinical and echocardiographic parameters were tested regarding their ability to predict NGAL levels (Table II). Among clinical characteristics, the significant predictors of NGAL were the duration of HF (r ⫽ 0.372, p ⫽ 0.013), the New York Heart Association (NYHA) class (r ⫽ 0.289, p ⫽ 0.019), DASI (r ⫽ -0.235, p ⫽ 0.048), serum urea levels (r ⫽ 0.482, p ⬍ 0.001), serum creatinine levels (r ⫽ 0.506, p ⬍ 0.001), serum cystatin C levels (r ⫽ 0.485, p ⬍ 0.001), and eGFR (r ⫽ -0.330, p ⫽ 0.011). No association between NGAL and N-terminal of the prohormone brain natriuretic peptide (NT-proBNP) serum levels was observed. Among echocardiographic measurements, only tissue Doppler RV systolic velocity was associated with NGAL levels (r ⫽ 0.277, p ⫽ 0.035). The
Value
NGAL
Parameter N ⫽ 76
A total of 76 patients (79% male, mean age: 63 ⫾ 14 years), with CHF (43% with ischemic heart disease) and mean LVEF of 28 ⫾ 7% were included in the study. Demographic, clinical, and echocardiographic data of the entire cohort are presented in Table I.
Parameter N ⫽ 76
Results
Medication QRS morphology Beta-blockers 91% Normal 33% ACE/ARBs 88% LBBB 61% Loop diuretics 92% RBBB 6% Thiazides 6% Blood examinations AA 70% Urea (mmol/L) 22.8 ⫾ 14.28 Amiodarone 17% Creatinine (μmol/L) 106.08 ⫾ 44.2 Digoxin 20% eGFR (ml/min/0.73 m2) 79 ⫾ 42 Vit K antagonist 27% NT-proBNP (ng/L) 2578 (1077–6139) Statin 44% Cystatin C (mg/L) 1.25 (1.0–1.8) Systolic BP NGAL (mg/L) 0.16 (0.09–0.275) 125 ⫾ 18 Diastolic BP ST2 (mg/L) 0.0125 (0.0071–0.0176) 75 ⫾ 11 Heart rate 74 ⫾ 13 Echo measurements Atrial fibrillation 16% EF % 28 ⫾ 7 QRS duration IVSd (cm) 126 ⫾ 43 1.0 ⫾ 0.3 LVPWd (cm) 1.0 ⫾ 0.2
Value
Parameter N ⫽ 76
Value
Statistical analysis was performed using SPSS v16.0 for windows (Chicago, IL, USA). NGAL and ST2 were not normally distributed and are expressed as median values (interquartile range), while a log transformation was performed to achieve normal distribution for further analysis. Univariate linear regression analysis was performed to identify association between clinical or echocardiographic variables and logNGAL or logST2. A stepwise multivariate regression analysis model including the variables found with significant univariate association (p ⬍ 0.1) was created for the determination of covariates independently associated with logNGAL or logST2. The strength of the association was determined using standardized beta coefficient (b) criterion. Colinearity between different markers of chronic kidney failure was assessed using the variance inflation factor and values ⱖ 10 were considered as indicators of multicollinearity. A p value ⬍ 0.05 was considered statistically significant.
Table I. Clinical and echocardiographic findings of the entire cohort.
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Statistical analysis
Age (years) 63 ⫾ 14 Female gender % 21 BMI (Kg/m2) 27.8 ⫾ 5.4 NYHA class 2.7 ⫾ 0.7 HF etiology Ischemic 43% Non-ischemic 57% Hypertension % 46% Diabetes % 31% Dyslipidemia % 36% CAD family history % 19% SCD family history % 12% Prior MI 31% Smoking % 17% DASI 21.2 ⫾ 15.7
Parameter N ⫽ 76
Value
diastole (E’), late diastole (A’), and the ratio (E’/A’) were recorded at a sweep speed of 100 mm/s. Furthermore, E to E’ ratio was calculated for both ventricles.
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Restrictive pattern 36% Tricuspid E (cm/s) 0.46 ⫾ 0.15 Tricuspid A (cm/s) 0.41 ⫾ 0.16 Tricuspid DT (sec) 216 ⫾ 81 Lateral S’ (mm/s) 5.1 ⫾ 1.7 Lateral E’ (mm/s) 7.1 ⫾ 3.5 Lateral A’ (mm/s) 5.7 ⫾ 2.4 Septal S’ (mm/s) 4.7 ⫾ 1.5 Septal E’ (mm/s) 4.8 ⫾ 2.0 Septal A’ (mm/s) 5.2 ⫾ 2.2 RV S’ (mm/s) 9.6 ⫾ 2.9 RV E’ (mm/s) 8.7 ⫾ 3.4 RV A’ (mm/s) 10.5 ⫾ 4.7 RVSP (mmHg) 46 ⫾ 21
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Table II. Univariable and multivariable linear regression between clinical and echocardiographic parameters and NGAL and ST2. NGAL
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Univariable
Duration of HF HF etiology NYHA class QRS duration DASI Diabetes ACE/ARBs Urea Creatinine eGFR (Cockroft–Gault formula) eGFR (CKD-EPI) Cystatin NT-proBNP Interventricular septum thickness RV area in diastole TAPSE RV S’ RV E’ RV A’
ST2 Multivariable
r
p
0.372 0.031 0.289 ⫺ 0.224 ⫺ 0.235 0.237 0.227 0.482 0.506 ⫺ 0.330 ⫺ 0.524 0.485 ⫺ 0.223 ⫺ 0.101 0.179 ⫺ 0.141 0.277 0.108 ⫺ 0.129
0.013 0.802 0.019 0.094 0.048 0.064 0.090 ⬍ 0.001 ⬍ 0.001 0.011 ⬍ 0.001 ⬍ 0.001 0.151 0.437 0.402 0.270 0.135 0.422 0.378
b
p
0.273
0.033
0.101 ⫺ 0.193 ⫺ 0.076 ⫺ 0.021 0.123 0.163 0.496 ⫺ 0.038 ⫺ 0.245 0.243
0.503 0.160 0.603 0.892 0.386 0.572 ⬍ 0.001 0.828 0.329 0.238
Univariable
Multivariable
r
p
0.034 0.269 0.002 0.194 ⫺ 0.108 ⫺ 0.166 0.054 0.203 0.124 ⫺ 0.014 ⫺ 0.021 0.185 0.435 0.253 0.443 ⫺ 0.251 ⫺ 0.523 ⫺ 0.271 ⫺ 0.324
0.826 0.029 0.985 0.147 0.388 0.197 0.691 0.108 0.329 0.918 0.872 0.140 0.004 0.048 0.030 0.047 ⬍ 0.001 0.040 0.023
b
p
0.118
0.549
0.285 0.206 0.313 0.055 ⫺ 0.523 0.089 ⫺ 0.129
0.147 0.268 0.101 0.808 0.009 0.711 0.532
HF, heart failure; GFR, glomerular filtration rate; ACE/ARBs, angiotensin converting enzyme/ angiotensin receptor blocker; TAPSE, tricuspid annular plane systolic excursion; b, standardized beta coefficient criterion. Bold letters indicate statistically significant correlations.
multivariable analysis showed that serum creatinine levels and duration of HF were the only independent predictors of NGAL serum levels (Figure 1). ST2 Serum ST2 levels were 0.0125 (0.0071–0.0176) mg/L. No correlation was found between ST2 and NGAL levels. Table II presents the univariable and multivariable predictors of ST2 levels. No clinical
characteristic apart from HF etiology (r ⫽ 0.269, p ⫽ 0.029) correlated significantly with ST2 levels. Serum NT-proBNP showed strong correlation with ST2 (r ⫽ 0.435, p ⫽ 0.004). Among echocardiographic parameters, significant correlation was seen between ST2 and the interventricular septum thickness (r ⫽ 0.253, p ⫽ 0.048), RV area in diastole (r ⫽ 443, p ⫽ 0.030), TAPSE (r ⫽ -0.251, p ⫽ 0.047), tissue Doppler RV systolic velocity (r ⫽ -0.523, p ⬍ 0.001), tissue Doppler RV early diastolic velocity
Figure 1. Association between NGAL and duration of heart failure (panel A) as well as between NGAL and creatinine serum levels (panel B). NGAL, neutrophil gelatinase-associated lipocalin.
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Figure 2. Association between ST2 receptor serum levels and RV S’. ST2 receptor: a member of the Interleukin-1 receptor family, RV S’: tissue Doppler-derived right ventricular systolic velocity.
(RV E’) (r ⫽ -0.271, p ⫽ 0.040), and tissue Doppler RV late diastolic velocity (RV A’) (r ⫽ -0.324, p ⫽ 0.023). Multivariable analysis showed that only RV S’ could independently predict serum ST2 levels (r ⫽ -0.523, p ⫽ 0.009) (Figure 2). Discussion The present study explored the relation between NGAL and ST2 levels and clinical and echocardiographic parameters in patients with stable CHF. NGAL levels were associated with renal function and the duration of HF symptoms. Among all echocardiographic parameters, only RV systolic function was independently associated with ST2. No association between ST2 and NGAL was found. NGAL was first isolated in human activated neutrophils and was believed to play a role in inflammation (17). Subsequent studies revealed the presence of NGAL in renal tubular cells and led to its establishment as an early marker of renal dysfunction (18) and chronic renal damage (2), while its serum levels predict worsening of renal function in hospitalized patients with HF (19). In line with these observations we showed that NGAL levels strongly correlated with all markers of renal function (creatinine, urea, cystatin C, and GFR) in patients with stable CHF. A recent study showed increased levels of serum NGAL in patients after myocardial infarction or HF
(20). In addition, NGAL levels were associated with NYHA functional class in CHF (21) and with BNP (22) or NT-proBNP, but the latter was observed only in patients with ischemic HF (21). The lack of association between NGAL and NT-proBNP serum levels in our study population consisted of patients with stable CHF may be explained by the different biologic pathways leading to their expression, as NGAL expression is believed to be dysregulated in the setting of vascular damage and remodeling (3,20), while NT-proBNP is primarily expressed in the setting of myocardial strain (11). Another study that included both chronic and acute HF cohorts similarly showed that NGAL levels were associated with NYHA class, renal function, and indices of diastolic heart function, but not after adjustment for renal function (23). In our cohort, the duration of HF predicted NGAL levels independently of renal function in patients with stable CHF. There is however controversial data whether elevated serum NGAL levels are determined by underlying impairment of renal rather than myocardial function (23). In contrast to acute HF, we showed that there was no association between ST2 and indices of LV function in patients with stable CHF. Moreover, we confirmed the positive relation between indices of RV dysfunction and ST2 levels in line with previous studies in acute HF, in outpatients with dyspnea and normal EF (24,25) as well as in patients with RV
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dysfunction such as patients with pulmonary hypertension (26–29), in which the degree of RV dilatation and systolic dysfunction relate strictly to ST2 levels, supporting the notion that the secretion of ST2 may represent the epiphenomenon of complex pathophysiological paths associated with substantial myocardial wall stress (29). No correlation was found between ST2 and NGAL pointing that there are significant differences in the underlying pathophysiological mechanisms that lead to increased serum levels of these biomarkers.
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Limitations
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The small number of the patient population and the lack of control group are the main limitations of the present study, which prevented us from presenting associations between these biomarkers and clinical events on follow-up.
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Conclusions
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NGAL levels mainly depend on the renal function and the duration of HF syndrome, but remain independent from the myocardial function in patients with stable CHF. Serum ST2 levels, on the other hand, are affected by the right but not the LV function and show no association with clinical indices of HF.
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Source of funding The study was funded by the Hellenic Cardiology Society. LM was supported by grants by the European Heart Rhythm Association and the Hellenic Cardiology Society. For the remaining authors none were declared. Declaration of interest: The authors report no declarations of interest. The authors alone are responsible for the content and writing of the paper.
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ORIGINAL ARTICLE
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NGAL and ST2 levels in ambulatory patients with chronic heart failure. Clinical and echocardiographic correlates
IOANNIS VENTOULIS1, LILIAN MANTZIARI1, SOPHIA-ANASTASIA MOURATOGLOU1, VASILEIOS KAMPERIDIS1, GEORGE GIANNAKOULAS1, ANTONIOS ZIAKAS1, DIMITRIS TSALIKAKIS4, GREGORY GIAMOUZIS2, ARETI HITOGLOU-MAKEDOU3 & HARALAMBOS KARVOUNIS1 11st
Department of Cardiology, AHEPA University Hospital, Thessaloniki, Greece, 2Department of Cardiology, Larissa University Hospital, Larissa, Greece, 3Laboratory of Microbiology, AHEPA University Hospital, Thessaloniki, Greece, and 4Research & Analysis Laboratory, Department of Informatics and Telecommunication Engineering, University of Western Macedonia, Kozani, Greece
Abstract Aim. Neutrophil gelatinase-associated lipocalin (NGAL) and ST2 receptor, a member of the interleukin-1 receptor family, are novel biomarkers with a potential role in the diagnosis and risk stratification of patients with chronic heart failure (CHF). There is however scarce data on their relation with clinical characteristics and cardiac function in patients with CHF. Methods. Consecutive ambulatory patients with CHF were studied. All patients underwent clinical and echocardiographic assessment, and blood samples were collected for the estimation of ST2 and NGAL serum levels during the same assessment. Results. A total of 76 patients (79% male, mean age: 63 ⫾ 14 years), with CHF and left ventricular ejection fraction of 28 ⫾ 7% were included. Median NGAL was 0.16 (0.09–0.275) mg/L and median ST2 was 0.0125 (0.0071–0.0176) mg/L. No association between NGAL and ST2 was observed. Multivariate analysis revealed tissue Doppler-derived right ventricular systolic velocity as an independent predictor of ST2, and the duration of HF and serum creatinine levels as independent predictors of NGAL. Conclusions. NGAL levels depend on the renal function and the duration of HF, while ST2 levels are affected by the right but not the left ventricular function and show no association with clinical indices of HF. Key words: chronic heart failure, echocardiography, novel biomarkers
Introduction There is an increasing interest on the role of novel biomarkers in the diagnosis and management of chronic heart failure (CHF). Numerous biomarkers have been proposed to be related to various pathophysiological pathways associated with CHF, such as the neurohormonal activation, myocyte injury, extracellular matrix remodeling, inflammation, and renal dysfunction. However, with the exception of natriuretic peptides, the role of novel biomarkers is still controversial and their use in everyday practice is not embraced by the current guidelines (1). Neutrophil gelatinase-associated lipocalin (NGAL) is a glycoprotein found in activated neutrophils and
renal tubular cells and is associated with kidney damage (2). Subsequent studies revealed the role of NGAL in cell survival, inflammation, and matrix degradation, and its expression was found to be enhanced in clinical and experimental HF (3). Limited data from clinical studies indicate an association of increased serum levels of NGAL with worse prognosis in patients with HF (4,5). However, controversy exists whether this relation is attributed to worsening of renal function, commonly seen in patients with HF, or to complicated pathophysiological mechanisms related to myocardial dysfunction (3). ST2 receptor is a member of the interleukin-1 (IL-1) receptor family and consists of a membraneanchored and a soluble form. The soluble form of
The first two authors contributed equally to the manuscript. Correspondence: Sophia-Anastasia Mouratoglou, 1st Department of Cardiology, AHEPA University Hospital, St. Kyriakidi 1, 54636, Thessaloniki, Greece. Tel: ⫹302310994830. Fax: ⫹302310994673. E-mail: [email protected] (Received 23 February 2015 ; revised 8 April 2015 ; accepted 11 April 2015) ISSN 1401-7431 print/ISSN 1651-2006 online © 2015 Informa Healthcare DOI: 10.3109/14017431.2015.1043141
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ST2 can be measured in the serum and is considered as a biomarker of myocardial strain and a potential mediator of myocardial fibrosis (6). It has been evaluated in the diagnosis (7), prognosis (6,8–10), and risk stratification of HF (11), as well as in patients’ response to treatment (12), while its association with the cardiac function in acute HF and in patients referred for echocardiography has also been previously investigated (13,14). In the present study, we aimed to investigate the association between NGAL and ST2 levels and clinical and echocardiographic findings in a cohort of patients with stable CHF.
Materials and methods Patient population Consecutive patients with stable CHF followed up at a tertiary cardiac center were prospectively enrolled in this study. Inclusion criteria were age ⬎18 years, ejection fraction (EF) ⬍ 45%, and history of known HF due to ischemic or idiopathic dilated cardiomyopathy. Exclusion criteria were recent (ⱕ 30 days) acute coronary syndrome, pulmonary edema or decompensation of HF, permanent pacemakers or cardiac resynchronization devices, malignancies, connective tissue disease, and severe renal failure requiring hemofiltration. The study protocol was approved by the ethics committee of our institution and all enrolled patients gave written informed consent. Clinical evaluation Clinical evaluation included a detailed medical history, clinical examination, electrocardiogram, and review of all drug therapies. Functional capacity was assessed with Duke Activity Status Index (DASI) questionnaire. DASI is a 12-point scale based on the ability to perform everyday activities, previously validated in patients with HF for the assessment of their functional capacity (15). Biomarkers Blood samples were collected by venipuncture on the day of the echocardiographic study. Urea and creatinine levels were measured with the standard methods as per routine practice. Estimated glomerular filtration rate (eGFR) was calculated using both the Cockroft–Gault and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulae. Two extra vials of whole blood were centrifuged within 60 min and serum was frozen at ⫺ 70°C until
analyzed. Both ST2 and NGAL were estimated in the same serum sample. ST2 was measured using the Quantikine Human ST2/IL-1 R4 Immunoassay (R&D, Minneapolis, USA, assay range: 31.3*10 ⫺ 6 ⫺ 2,000*10 ⫺ 6 mg/L), and NGAL was measured using the Quantikine Human Lipocalin-2/NGAL Immunoassay (R&D, Minneapolis, USA, assay range: 1.56*10 ⫺ 3 – 0.01*10 ⫺ 3 mg/L). These assays employ the quantitative sandwich enzyme immunoassay technique (ELISA). Echocardiographic study A full echocardiographic study was performed by a single accredited echocardiographer (VK) to all study subjects using the same equipment (Vivid 7, GE Vingmed Ultrasound, Horten, Norway).The echocardiographer was blind on patients’ clinical details and all measurements were done off-line. Standard echocardiographic views were used. Left ventricular (LV) dimensions were measured in 2D images at the long parasternal axis. LV volumes and EF were calculated using the biplane Simpson’s method from 4- and 2-chamber views at the apical axis. Atrial volumes and right ventricular (RV) dimensions were calculated from the 4-chamber view according to established methods (16). Tricuspid annular plane systolic excursion (TAPSE) was measured by twodimensional difference of end-diastolic and endsystolic lines (in cm) traced between the center of the ultrasound fan origin and the junction of RV lateral tricuspid annulus, in apical four-chamber view. RV systolic pressure was estimated by calculating the maximal velocity of the tricuspid regurgitant jet and then, further using the Bernoulli equation, adding to this value an estimated right atrial pressure based on both the size of the inferior vena cava and its respiratory variation. Pulsed Doppler echocardiography for the assessment of the standard diastolic filling velocities of both ventricles was performed using the apical four-chamber view. Thus, the peak early diastolic filling velocity (E-wave), peak late diastolic filling velocity (A-wave), and the ratio (E/A) were recorded. Pulsed-wave tissue Doppler imaging (TDI) was used to assess mitral and tricuspid annular velocities. Filters were set to exclude high-frequency signals, and the Nyquist limit was adjusted to a velocity range of 15–20 cm/s. Gains were minimized in order to allow for a clear tissue signal with minimum background noise. All TDI recordings were obtained during normal respiration, in the apical four-chamber view. A 5-mm sample volume was placed at the septal and lateral corner of the mitral annulus and at the lateral corner of the tricuspid annulus. The peak myocardial velocities during systole (S’), early
LVEDD (cm) 6.6 ⫾ 0.8 LVESD (cm) 5.7 ⫾ 1.1 LVEDV (ml) 194 ⫾ 65 LVESV (ml) 141 ⫾ 54 LA diam (cm) 4.8 ⫾ 0.6 LA vol (ml) 95 ⫾ 44 RA diam (cm) 4.1 ⫾ 0.9 RA vol (ml) 56 ⫾ 29 RV area D (cm2) 18 ⫾ 6 RV area S (cm2) 11 ⫾ 5 RV mid (cm) 2.9 ⫾ 0.7 RV basal (cm) 4.0 ⫾ 0.9 TAPSE (cm) 1.8 ⫾ 0.5 Mitral E (cm/s) 0.86 ⫾ 0.33 Mitral A (cm/s) 0.63 ⫾ 0.30 Mitral DT (sec) 176 ⫾ 69
MI, myocardial infarction; BP, blood pressure; AA, aldosterone antagonists; DT, deceleration time; ACE/ARBs, angiotensin-converting enzyme/angiotensin receptor blockers.
Value Parameter N ⫽ 76
Serum NGAL levels were 0.16 (0.09–0.275) mg/L. All clinical and echocardiographic parameters were tested regarding their ability to predict NGAL levels (Table II). Among clinical characteristics, the significant predictors of NGAL were the duration of HF (r ⫽ 0.372, p ⫽ 0.013), the New York Heart Association (NYHA) class (r ⫽ 0.289, p ⫽ 0.019), DASI (r ⫽ -0.235, p ⫽ 0.048), serum urea levels (r ⫽ 0.482, p ⬍ 0.001), serum creatinine levels (r ⫽ 0.506, p ⬍ 0.001), serum cystatin C levels (r ⫽ 0.485, p ⬍ 0.001), and eGFR (r ⫽ -0.330, p ⫽ 0.011). No association between NGAL and N-terminal of the prohormone brain natriuretic peptide (NT-proBNP) serum levels was observed. Among echocardiographic measurements, only tissue Doppler RV systolic velocity was associated with NGAL levels (r ⫽ 0.277, p ⫽ 0.035). The
Value
NGAL
Parameter N ⫽ 76
A total of 76 patients (79% male, mean age: 63 ⫾ 14 years), with CHF (43% with ischemic heart disease) and mean LVEF of 28 ⫾ 7% were included in the study. Demographic, clinical, and echocardiographic data of the entire cohort are presented in Table I.
Parameter N ⫽ 76
Results
Medication QRS morphology Beta-blockers 91% Normal 33% ACE/ARBs 88% LBBB 61% Loop diuretics 92% RBBB 6% Thiazides 6% Blood examinations AA 70% Urea (mmol/L) 22.8 ⫾ 14.28 Amiodarone 17% Creatinine (μmol/L) 106.08 ⫾ 44.2 Digoxin 20% eGFR (ml/min/0.73 m2) 79 ⫾ 42 Vit K antagonist 27% NT-proBNP (ng/L) 2578 (1077–6139) Statin 44% Cystatin C (mg/L) 1.25 (1.0–1.8) Systolic BP NGAL (mg/L) 0.16 (0.09–0.275) 125 ⫾ 18 Diastolic BP ST2 (mg/L) 0.0125 (0.0071–0.0176) 75 ⫾ 11 Heart rate 74 ⫾ 13 Echo measurements Atrial fibrillation 16% EF % 28 ⫾ 7 QRS duration IVSd (cm) 126 ⫾ 43 1.0 ⫾ 0.3 LVPWd (cm) 1.0 ⫾ 0.2
Value
Parameter N ⫽ 76
Value
Statistical analysis was performed using SPSS v16.0 for windows (Chicago, IL, USA). NGAL and ST2 were not normally distributed and are expressed as median values (interquartile range), while a log transformation was performed to achieve normal distribution for further analysis. Univariate linear regression analysis was performed to identify association between clinical or echocardiographic variables and logNGAL or logST2. A stepwise multivariate regression analysis model including the variables found with significant univariate association (p ⬍ 0.1) was created for the determination of covariates independently associated with logNGAL or logST2. The strength of the association was determined using standardized beta coefficient (b) criterion. Colinearity between different markers of chronic kidney failure was assessed using the variance inflation factor and values ⱖ 10 were considered as indicators of multicollinearity. A p value ⬍ 0.05 was considered statistically significant.
Table I. Clinical and echocardiographic findings of the entire cohort.
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Statistical analysis
Age (years) 63 ⫾ 14 Female gender % 21 BMI (Kg/m2) 27.8 ⫾ 5.4 NYHA class 2.7 ⫾ 0.7 HF etiology Ischemic 43% Non-ischemic 57% Hypertension % 46% Diabetes % 31% Dyslipidemia % 36% CAD family history % 19% SCD family history % 12% Prior MI 31% Smoking % 17% DASI 21.2 ⫾ 15.7
Parameter N ⫽ 76
Value
diastole (E’), late diastole (A’), and the ratio (E’/A’) were recorded at a sweep speed of 100 mm/s. Furthermore, E to E’ ratio was calculated for both ventricles.
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Restrictive pattern 36% Tricuspid E (cm/s) 0.46 ⫾ 0.15 Tricuspid A (cm/s) 0.41 ⫾ 0.16 Tricuspid DT (sec) 216 ⫾ 81 Lateral S’ (mm/s) 5.1 ⫾ 1.7 Lateral E’ (mm/s) 7.1 ⫾ 3.5 Lateral A’ (mm/s) 5.7 ⫾ 2.4 Septal S’ (mm/s) 4.7 ⫾ 1.5 Septal E’ (mm/s) 4.8 ⫾ 2.0 Septal A’ (mm/s) 5.2 ⫾ 2.2 RV S’ (mm/s) 9.6 ⫾ 2.9 RV E’ (mm/s) 8.7 ⫾ 3.4 RV A’ (mm/s) 10.5 ⫾ 4.7 RVSP (mmHg) 46 ⫾ 21
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Table II. Univariable and multivariable linear regression between clinical and echocardiographic parameters and NGAL and ST2. NGAL
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Univariable
Duration of HF HF etiology NYHA class QRS duration DASI Diabetes ACE/ARBs Urea Creatinine eGFR (Cockroft–Gault formula) eGFR (CKD-EPI) Cystatin NT-proBNP Interventricular septum thickness RV area in diastole TAPSE RV S’ RV E’ RV A’
ST2 Multivariable
r
p
0.372 0.031 0.289 ⫺ 0.224 ⫺ 0.235 0.237 0.227 0.482 0.506 ⫺ 0.330 ⫺ 0.524 0.485 ⫺ 0.223 ⫺ 0.101 0.179 ⫺ 0.141 0.277 0.108 ⫺ 0.129
0.013 0.802 0.019 0.094 0.048 0.064 0.090 ⬍ 0.001 ⬍ 0.001 0.011 ⬍ 0.001 ⬍ 0.001 0.151 0.437 0.402 0.270 0.135 0.422 0.378
b
p
0.273
0.033
0.101 ⫺ 0.193 ⫺ 0.076 ⫺ 0.021 0.123 0.163 0.496 ⫺ 0.038 ⫺ 0.245 0.243
0.503 0.160 0.603 0.892 0.386 0.572 ⬍ 0.001 0.828 0.329 0.238
Univariable
Multivariable
r
p
0.034 0.269 0.002 0.194 ⫺ 0.108 ⫺ 0.166 0.054 0.203 0.124 ⫺ 0.014 ⫺ 0.021 0.185 0.435 0.253 0.443 ⫺ 0.251 ⫺ 0.523 ⫺ 0.271 ⫺ 0.324
0.826 0.029 0.985 0.147 0.388 0.197 0.691 0.108 0.329 0.918 0.872 0.140 0.004 0.048 0.030 0.047 ⬍ 0.001 0.040 0.023
b
p
0.118
0.549
0.285 0.206 0.313 0.055 ⫺ 0.523 0.089 ⫺ 0.129
0.147 0.268 0.101 0.808 0.009 0.711 0.532
HF, heart failure; GFR, glomerular filtration rate; ACE/ARBs, angiotensin converting enzyme/ angiotensin receptor blocker; TAPSE, tricuspid annular plane systolic excursion; b, standardized beta coefficient criterion. Bold letters indicate statistically significant correlations.
multivariable analysis showed that serum creatinine levels and duration of HF were the only independent predictors of NGAL serum levels (Figure 1). ST2 Serum ST2 levels were 0.0125 (0.0071–0.0176) mg/L. No correlation was found between ST2 and NGAL levels. Table II presents the univariable and multivariable predictors of ST2 levels. No clinical
characteristic apart from HF etiology (r ⫽ 0.269, p ⫽ 0.029) correlated significantly with ST2 levels. Serum NT-proBNP showed strong correlation with ST2 (r ⫽ 0.435, p ⫽ 0.004). Among echocardiographic parameters, significant correlation was seen between ST2 and the interventricular septum thickness (r ⫽ 0.253, p ⫽ 0.048), RV area in diastole (r ⫽ 443, p ⫽ 0.030), TAPSE (r ⫽ -0.251, p ⫽ 0.047), tissue Doppler RV systolic velocity (r ⫽ -0.523, p ⬍ 0.001), tissue Doppler RV early diastolic velocity
Figure 1. Association between NGAL and duration of heart failure (panel A) as well as between NGAL and creatinine serum levels (panel B). NGAL, neutrophil gelatinase-associated lipocalin.
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Figure 2. Association between ST2 receptor serum levels and RV S’. ST2 receptor: a member of the Interleukin-1 receptor family, RV S’: tissue Doppler-derived right ventricular systolic velocity.
(RV E’) (r ⫽ -0.271, p ⫽ 0.040), and tissue Doppler RV late diastolic velocity (RV A’) (r ⫽ -0.324, p ⫽ 0.023). Multivariable analysis showed that only RV S’ could independently predict serum ST2 levels (r ⫽ -0.523, p ⫽ 0.009) (Figure 2). Discussion The present study explored the relation between NGAL and ST2 levels and clinical and echocardiographic parameters in patients with stable CHF. NGAL levels were associated with renal function and the duration of HF symptoms. Among all echocardiographic parameters, only RV systolic function was independently associated with ST2. No association between ST2 and NGAL was found. NGAL was first isolated in human activated neutrophils and was believed to play a role in inflammation (17). Subsequent studies revealed the presence of NGAL in renal tubular cells and led to its establishment as an early marker of renal dysfunction (18) and chronic renal damage (2), while its serum levels predict worsening of renal function in hospitalized patients with HF (19). In line with these observations we showed that NGAL levels strongly correlated with all markers of renal function (creatinine, urea, cystatin C, and GFR) in patients with stable CHF. A recent study showed increased levels of serum NGAL in patients after myocardial infarction or HF
(20). In addition, NGAL levels were associated with NYHA functional class in CHF (21) and with BNP (22) or NT-proBNP, but the latter was observed only in patients with ischemic HF (21). The lack of association between NGAL and NT-proBNP serum levels in our study population consisted of patients with stable CHF may be explained by the different biologic pathways leading to their expression, as NGAL expression is believed to be dysregulated in the setting of vascular damage and remodeling (3,20), while NT-proBNP is primarily expressed in the setting of myocardial strain (11). Another study that included both chronic and acute HF cohorts similarly showed that NGAL levels were associated with NYHA class, renal function, and indices of diastolic heart function, but not after adjustment for renal function (23). In our cohort, the duration of HF predicted NGAL levels independently of renal function in patients with stable CHF. There is however controversial data whether elevated serum NGAL levels are determined by underlying impairment of renal rather than myocardial function (23). In contrast to acute HF, we showed that there was no association between ST2 and indices of LV function in patients with stable CHF. Moreover, we confirmed the positive relation between indices of RV dysfunction and ST2 levels in line with previous studies in acute HF, in outpatients with dyspnea and normal EF (24,25) as well as in patients with RV
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dysfunction such as patients with pulmonary hypertension (26–29), in which the degree of RV dilatation and systolic dysfunction relate strictly to ST2 levels, supporting the notion that the secretion of ST2 may represent the epiphenomenon of complex pathophysiological paths associated with substantial myocardial wall stress (29). No correlation was found between ST2 and NGAL pointing that there are significant differences in the underlying pathophysiological mechanisms that lead to increased serum levels of these biomarkers.
3.
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Limitations
6.
The small number of the patient population and the lack of control group are the main limitations of the present study, which prevented us from presenting associations between these biomarkers and clinical events on follow-up.
7.
Conclusions
8.
NGAL levels mainly depend on the renal function and the duration of HF syndrome, but remain independent from the myocardial function in patients with stable CHF. Serum ST2 levels, on the other hand, are affected by the right but not the LV function and show no association with clinical indices of HF.
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10.
Source of funding The study was funded by the Hellenic Cardiology Society. LM was supported by grants by the European Heart Rhythm Association and the Hellenic Cardiology Society. For the remaining authors none were declared. Declaration of interest: The authors report no declarations of interest. The authors alone are responsible for the content and writing of the paper.
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