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Circulation: Heart Failure. 2008;1:43-49
doi: 10.1161/CIRCHEARTFAILURE.107.746172
CLINICAL PERSPECTIVE
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Original Articles

Osteopontin, a New Prognostic Biomarker in Patients With Chronic Heart Failure

Mark Rosenberg, MD; Christian Zugck, MD; Manfred Nelles, MD; Claus Juenger, MD, MPH; Derk Frank, MD; Andrew Remppis, MD; Evangelos Giannitsis, MD; Hugo A. Katus, MD and Norbert Frey, MD

From the Department of Internal Medicine III (M.R., C.Z., M.N., D.F., A.R., E.G., H.A.K., N.F.), University of Heidelberg, Heidelberg, Germany, and Institut für Herzinfarktforschung an der Universität Heidelberg (C.J.), Ludwigshafen, Germany.

Correspondence to Norbert Frey, MD, Department of Internal Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany. E-mail norbert.frey{at}med.uni-heidelberg.de

Received October 18, 2007; accepted February 11, 2008.


    Abstract
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Background— Osteopontin, a glycoprotein that can be detected in plasma, was found to be upregulated in several animal models of cardiac failure and may thus represent a new biomarker that facilitates risk stratification in patients with heart failure. We therefore tested whether osteopontin plasma levels are elevated in patients with chronic heart failure and whether they provide independent prognostic information.

Methods and Results— We analyzed osteopontin plasma levels in 420 patients with chronic heart failure due to significantly impaired left ventricular systolic function and correlated the results with disease stage and prognostic information (median follow-up of 43 months). We found that osteopontin plasma levels were significantly elevated in patients with heart failure as compared with healthy control subjects (532 versus 382 ng/mL, P=0.008), irrespective of heart failure origin (ischemic versus dilated cardiomyopathy). Furthermore, osteopontin levels were higher in patients with moderate to severe heart failure than in patients with no or mild symptoms (672 ng/mL for New York Heart Association class III/IV versus 479 ng/mL for class I/II, P<0.0001). Estimated 4-year death rates in patients with osteopontin levels above or below a cutoff value derived from receiver operating characteristic analyses were 56.5% and 28.4%, respectively (hazard ratio 3.4, 95% confidence interval 2.2 to 5.3, P<0.0001). In a multivariable model that included demographic, clinical, and biochemical parameters such as N-terminal prohormone brain natriuretic peptide, osteopontin emerged as an independent predictor of death (hazard ratio 2.3, 95% confidence interval 1.4 to 3.5, P<0.001).

Conclusion— Our findings suggest that osteopontin might be useful as a novel prognostic biomarker in patients with chronic heart failure.

Key Words: heart failure • prognosis • biomarker


    Introduction
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Heart failure is a highly prevalent syndrome throughout the industrialized world and is associated with significant morbidity and mortality. In the United States, heart failure affects more than 5 million people and is responsible for nearly 50 000 deaths each year.1 Furthermore, annual hospitalizations for heart failure have increased over the past 20 years, from 377 000 to almost 1 million.2

Clinical Perspective p 49

Thus, in patients with heart failure, an accurate diagnosis and prognostic evaluation are critical to identify those at greatest risk for cardiac decompensation and death. Traditional risk stratification by clinical parameters and assessment of left ventricular ejection fraction has proved helpful in the clinical management of heart failure patients.3 More recently, the natriuretic peptides, in particular brain natriuretic peptide (BNP) or its fragment N-terminal prohormone BNP (NT-pro-BNP), have emerged as biomarkers that convey additional information for diagnosis and prognostication of death.4 However, even when clinical information is combined with BNP levels, there is considerable variation in the outcome.5 As a consequence, there is still great interest in new biomarkers that complement existing diagnostic tools and may facilitate risk stratification in patients with heart failure.

Osteopontin is a glycoprotein that is expressed in various cell types, including cardiomyocytes and fibroblasts. Osteopontin can exist as an immobilized extracellular matrix molecule or as a soluble cytokine and contains an RGD (arginine-glycine-aspartate) binding sequence that mediates interaction with several integrins, including β1-integrin, which is predominantly expressed in the myocardium.6 Because of its localization and molecular properties, osteopontin has been suggested to be involved in the communication between the extracellular matrix and cardiomyocytes (reviewed in Okamoto7). Moreover, we and others have shown that osteopontin is markedly upregulated in several animal models of cardiac hypertrophy and failure (Data Supplement Figure I),8,9 which implies a role in myocardial remodeling in response to biomechanical stress. Initial clinical studies also indicate that osteopontin could be upregulated in patients with cardiovascular disease. Stawowy et al10 analyzed the expression of osteopontin in myocardial biopsy samples obtained from 10 patients with dilated cardiomyopathy (DCM) and found significant upregulation compared with control tissue. Likewise, Satoh and coworkers11 reported a correlation of osteopontin content and left ventricular diameters in myocardial biopsy samples from DCM patients. Another study evaluated the relationship of osteopontin plasma levels during the course of an acute myocardial infarction. Again, osteopontin plasma levels were found to be elevated and correlated with left ventricular dysfunction and volume in 18 patients with myocardial infarction.12 Finally, in a small series of stable heart failure patients, osteopontin and aldosterone were demonstrated to be increased.13

On the basis of these experimental and clinical findings, we postulated that osteopontin levels might not only be elevated in patients with heart failure but could also be associated with the severity of heart failure and an adverse prognosis. Therefore, we analyzed osteopontin plasma levels in a large series of patients with chronic heart failure due to dilated or ischemic cardiomyopathy.


    Methods
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Study Population
Heart Failure Patients
In a retrospective analysis, heart failure patients were recruited from the specialized heart failure clinic of a large university hospital that serves as a tertiary referral center in southern Germany. Eligible patients were ≥18 years of age and revealed significantly reduced left ventricular systolic function with an ejection fraction <40%. Both patients with DCM and those with ischemic heart failure were included. Because angiotensin II extensively stimulates osteopontin expression in the heart, all patients had to be taking an angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker. All examinees enrolled in the present study had to have been taking stable medication 1 month before inclusion. Patients with malignant or inflammatory diseases, history of organ transplantation, or significant acute/chronic renal failure (serum creatinine >2 mg/dL) were excluded.

According to these inclusion and exclusion criteria, we performed a database inquiry of our heart failure clinic biobank, which collects blood samples of all heart failure patients seen in the clinic. From this query, 828 eligible plasma samples were identified that could be allocated to 420 individual patients. In patients with >1 plasma sample available, osteopontin was measured from the sample from which an NT-pro-BNP measurement had also been performed and/or which allowed complete analysis of 48 months’ follow-up. Osteopontin plasma levels were determined by enzyme-linked immunosorbent assay (ELISA) (see below) in all 420 patients. In a subgroup of 327 patients, NT-pro-BNP levels measured from the same plasma sample were available. To assess the potential prognostic significance of osteopontin, we analyzed all-cause deaths within 48 months of follow-up. Four-year event rates in heart failure patients in the present study were registered by yearly outpatient visits and telephone calls. Until January 2006, follow-up information for 410 patients (97.6%) was available; 10 examinees (2.4%) were lost to follow-up. A total of 290 of the 410 patients completed the observation period of 48 months by January 2006. In 223 of these 290 patients, NT-pro-BNP measurements were conducted and subsequently used for analysis of the additive value of osteopontin in the risk stratification of heart failure patients.

Control Group
EDTA plasma samples were also obtained from apparently healthy individuals. Forty-three subjects without signs of significant heart disease were included and served as the control group. Patients were recruited in our catheterization laboratory after undergoing coronary angiography for suspected coronary artery disease. Patients were only considered if invasive testing and echocardiography excluded (1) significant coronary artery disease and (2) systolic or diastolic dysfunction (defined as left ventricular ejection fraction ≥55% and left ventricular end-diastolic pressure ≤12 mm Hg). Individuals who fulfilled these criteria were still excluded if valvular heart disease or myocardial hypertrophy was evident on echocardiography. Further requirements for study enrollment were the absence of other acute or chronic diseases and normal results on routine laboratory testing.

The study conformed to the principles outlined in the Declaration of Helsinki and was approved by the local ethics committee of the University of Heidelberg. All subjects included in the study provided written informed consent.

Biochemical Analyses
Osteopontin Plasma Levels
Blood samples were drawn from control subjects and heart failure patients into an evacuated tube coated with EDTA. Plasma samples were generated within 30 minutes of collection by centrifugation at 1000g for 10 minutes at 4°C. To avoid repetitive freeze-and-thaw cycles, different aliquots of 1 sample were generated, immediately frozen, and stored at –80°C until analysis, because osteopontin is highly sensitive to proteolytic degradation at higher temperatures. Plasma osteopontin levels were determined with a sandwich ELISA by use of a commercially available kit (Immuno Biological Laboratories, Hamburg, Germany) according to the manufacturer’s instructions. Human osteopontin is detected with this kit at a threshold of ≥5 ng/mL. Briefly, a 1:10 diluted test sample was incubated for 1 hour at 37°C in wells precoated with an anti-human osteopontin antibody. After washing, 100 µL of horseradish peroxidase–conjugated anti-human osteopontin antibody was added to each well and incubated for 30 minutes at 4°C. After an additional washing step, tetramethylbenzidine was used as a substrate, and absorbance was measured at 450 nm with an automatic ELISA reader (Tecan Spectra, Crailsheim, Germany). Intra-assay and interassay coefficients of variation were <5% and 10%, respectively. Osteopontin measurements were performed in duplicate by an investigator unaware of patients’ characteristics and outcome.

NT-Pro-BNP Plasma Levels
NT-pro-BNP was measured from different aliquots of the same plasma sample. Measurements were performed at the clinical core laboratory of the University Hospital Heidelberg with an ELISA (Roche Diagnostics, Mannheim, Germany).

Statistical Analysis
Data are presented as mean±SD, median (interquartile range), or count and percentages. Continuous and categorical variables for heart failure patients and healthy control subjects were compared with the nonparametric Mann-Whitney U test or Fisher exact test, respectively. Linearity of categorical variables such as New York Heart Association (NYHA) classification was confirmed and assessed by a method described by Hosmer and Lemeshow.14 The optimal plasma osteopontin and NT-pro-BNP cutoff value to predict an adverse outcome in the present study population was calculated by a receiver operating characteristic (ROC) curve–driven analysis. Estimates of the cumulative event rate were evaluated by the Kaplan-Meier method. Heart failure patients were compared according to the osteopontin cutoff value with the use of log-rank tests of the 4-year survival curves. Because the influence of other factors cannot be excluded by the univariate Kaplan-Meier analysis, univariate and multivariable analyses by Cox proportional hazards regression were performed as well, to identify independent predictors of 4-year death in the present patient cohort. These models included all demographic, clinical, and biochemical parameters of the study population. Only parameters with significant differences in univariate and multivariable testing are presented.

To rule out the possibility that the predictive power of osteopontin is restricted to an "optimal" cutoff point derived from ROC analysis, we additionally calculated the univariate and multivariate Cox proportional hazards regression test with osteopontin either dichotomized according to median values or considered as a continuous variable. To test whether osteopontin is of additive value in the risk stratification of patients with significantly impaired left ventricular function and known NT-pro-BNP levels, a subgroup of 327 (of a total of 420) patients were analyzed for whom both NT-pro-BNP and osteopontin measurements from the same plasma sample were available. Patients were categorized according to osteopontin and NT-pro-BNP cutoff values derived from the ROC analysis. Cumulative survival plots of the different groups were again calculated by the Kaplan-Meier method and compared with the use of the log-rank test. Additionally, we performed the likelihood ratio test to confirm the additive value of osteopontin in the risk stratification of patients with chronic heart failure. The reduced model consisted only of NT-pro-BNP (as a continuous variable), whereas the full model included NT-pro-BNP and osteopontin (each as continuous variable).

All statistical comparisons were 2 tailed, and probability values <0.05 were considered statistically significant. All statistical analyses were performed with Prism 5.0 (GraphPad Software, San Diego, Calif) and MedCalc 9.3.0.0 (MedCalc, Mariakerke, Belgium) software.

The authors had full access to the data and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.


    Results
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Clinical Characteristics of Patient Cohort and Control Subjects
Among 420 patients, 267 had DCM (64%), and 153 an ischemic origin of heart failure (36%). The median age of the heart failure group was 57 years and included 342 men (81%) and 78 women (19%). The control group consisted of 17 men (39.5%) and 26 women (60.5%) with a median age of 59 years. The distribution of cardiovascular risk factors was similar in heart failure patients and controls (Data Supplement Table I).

Osteopontin Plasma Levels Are Significantly Increased in Patients With Heart Failure Irrespective of the Underlying Cause
The median osteopontin plasma level in the control sample was 382 ng/mL (interquartile range 257 to 540 ng/mL). Patients with systolic heart failure displayed a significantly higher (P=0.008) median osteopontin plasma level of 532 ng/mL (232 to 875 ng/mL; Table 1; Data Supplement Figure II). The upregulation of osteopontin plasma levels was independent of the underlying cause of heart failure. Patients with DCM revealed a median osteopontin plasma level of 577 ng/mL (151 to 954 ng/mL) that did not differ significantly from the median level of patients with ischemic cardiomyopathy (508 ng/mL, range 310 to 791 ng/mL; Table 1). No significant difference between male and female subjects was observed in either heart failure patients or control subjects (data not shown).


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Table 1. Osteopontin Plasma Levels in Patients With DCM or Ischemic Cardiomyopathy Compared With Healthy Control Subjects
 
Osteopontin Plasma Levels Correlate With the Severity of Heart Failure
Next, we analyzed whether osteopontin plasma levels correlate with the severity of heart failure. Because plasma samples were obtained from patients treated in our outpatient clinic, the vast majority of the examinees had symptoms that placed them in NYHA functional class II (195; 46.5%) or III (161; 38.5%). Only a minority of the included patients were classified as NYHA class I (56; 13%) or IV (8; 2%). Thus, patients with no or mild symptoms (NYHA I or II) were compared with patients with moderate to severe heart failure (NYHA III or IV). Baseline characteristics of the 2 patient cohorts are illustrated in Table I of the Data Supplement and revealed no significant differences with regard to demographic parameters, cardiovascular risk factors, current medication, or left ventricular function; however, patients with ischemic cardiomyopathy were more likely to have advanced heart failure.

Median osteopontin in patients with no or mild symptoms was 479 ng/mL (range 179 to 786 ng/mL), whereas patients with moderate to severe disease revealed a median osteopontin level of 672 ng/mL (299 to 1145 ng/mL, P<0.0001; Table 2). Multigroup analyses by ANOVA revealed significant differences for both NYHA III and IV compared with all other groups (Data Supplement Figure III). There was no significant difference between NYHA class I and II. These findings suggest that osteopontin plasma levels are not only elevated in the presence of heart failure but are also associated with disease severity, in particular with advanced heart failure.


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Table 2. Osteopontin Plasma Levels According to NYHA Classification
 
Osteopontin Predicts Death in Patients With Heart Failure
Given that osteopontin levels were elevated significantly in patients with heart failure and also correlated with functional status, we sought to evaluate whether osteopontin could also provide prognostic information in the present patient cohort. Therefore, an ROC analysis was conducted to identify the optimal osteopontin plasma level for potential prediction of death within 48 months of follow-up. The best cutoff value of osteopontin for the prediction of all-cause death within 48 months in the present study group was 929 ng/mL, with a sensitivity of 46% and a specificity of 83% (Data Supplement Figure IV). The area under the curve was 0.65 (95% CI 0.57 to 0.73, P<0.001). Subsequent survival analyses were performed according to this optimized threshold.

Baseline characteristics of patients above or below the optimized osteopontin cutoff defined by ROC analysis are illustrated in Table 3. No significant differences were observed between patients with low and high osteopontin plasma levels with respect to demographic factors, cardiovascular risk factors, or medication, with the exception of a higher prevalence of dyslipidemia in the low-osteopontin group. Moreover, neither the underlying cause of heart failure (ischemic versus DCM) nor the degree of left ventricular dysfunction was different in patients with low or high osteopontin levels, respectively, yet patients with NYHA class III and IV were significantly overrepresented in the high-osteopontin group (NYHA class III 51.0% versus 34.7%, P<0.01; NYHA class IV 7.0% versus 0.3%, P<0.001), whereas functional NYHA class II was more prevalent in the group with an osteopontin level below the cutoff value of 929 ng/mL (51.0% versus 31.0%, P<0.001).


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Table 3. Patient Characteristics According to Osteopontin Plasma Levels
 
The mean follow-up (±SE) of all 420 patients analyzed was 43±2 months. Death rates were calculated by Kaplan-Maier analysis according to the osteopontin cutoff value determined by the ROC curve (Figure 1). Estimated 4-year death rates in heart failure patients with osteopontin levels above the cutoff value of 929 ng/mL were 56.5% versus 28.4% in the population with lower osteopontin levels (hazard ratio [HR] 3.4, 95% CI 2.2 to 5.3, P<0.0001). Median survival duration of patients whose osteopontin values were high was only 34 months, whereas median survival duration in patients with lower osteopontin levels was >48 months (Figure 1). For 223 patients (53%), 48 months of follow-up were complete, and information on osteopontin and NT-pro-BNP levels was available. Of these, 162 patients had osteopontin levels <929 ng/mL, whereas 61 examinees had levels above the cutoff value. Death due to any cause occurred in 43 patients with low osteopontin levels and 36 individuals with values above the cutoff, which corresponded to significant differences in the 4-year event rate of 27% and 59%, respectively (HR 2.9, 95% CI 1.8 to 4.5, P<0.001).


Figure 1746172
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Figure 1. Estimated 4-year death rate according to osteopontin (OPN) cutoff value. Estimated 4-year death rates in patients with osteopontin levels above or below the cutoff value were 56.5% and 28.4%, respectively. Median survival duration of patients measured with osteopontin values above the cutoff was only 34 months, whereas median survival duration in patients with osteopontin levels below the cutoff could not be calculated within 48 months of follow-up.

 
Other factors significantly associated with risk of death at 4 years in the present study included NT-pro-BNP, NYHA classification, creatinine, and age (Table 4). Subsequent multivariable analysis by Cox proportional hazards regression with osteopontin dichotomized according to an optimal cutoff value derived from ROC analysis revealed that osteopontin independently predicted death (HR 2.3, 95% CI 1.4 to 3.5, P<0.001). Besides osteopontin, NT-pro-BNP, serum creatinine, and NYHA classification stage emerged as independent predictors in the multiple model (Table 4). Similar results were obtained when the median osteopontin level (618 ng/mL) was used as a cutoff point (Data Supplement Table IIa) or when osteopontin was included as a continuous variable in the multivariable Cox proportional hazards regression analysis (Data Supplement Table IIb).


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Table 4. Cox Proportional Hazards Regression for 4-Year Death Rate in Relation to Biochemical, Demographic, and Clinical Factors
 
Additive Value of Osteopontin in Predicting Death of Heart Failure Patients
To test for a potential additive value of osteopontin in the prediction of death, patients were classified according to their NT-pro-BNP and osteopontin values. As mentioned above, we determined the optimal osteopontin and NT-pro-BNP plasma levels for the prediction of 4-year death by means of an ROC-driven analysis. Death rates for the 327 patients for whom a simultaneous measurement of osteopontin and NT-pro-BNP was available were calculated by the Kaplan-Meier method according to combined osteopontin and NT-pro-BNP cutoff values and compared with the log-rank test. The estimated 4-year death rates in patients with both biomarkers below the cutoff was only 12%, compared with 73% when both markers were elevated above the cutoff (HR 98, 95% CI 39 to 246, P<0.0001; Figure 2). In the lower BNP group, an osteopontin level ≥929 ng/mL raised the estimated 4-year death rate to 39%, compared with 12% in patients with low osteopontin (HR 6.5, 95% CI 2.4 to 17.4, P<0.001). Similarly, high osteopontin values in patients with BNP levels above the cutoff increased the estimated 4-year death rate from 50% to 73% (HR 2.2, 95% CI 1.2 to 3.9, P=0.007; Figure 2).


Figure 2746172
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Figure 2. Additive value of osteopontin (OPN) in 4-year death prediction. Variation of osteopontin levels in a patient population with NT-pro-BNP values below the cutoff defined by ROC analysis leads to a rise in estimated 4-year death rates from 12% to 39%. Similar results were obtained for the patient group with markedly elevated NT-pro-BNP values. Depending on the osteopontin level, death rates rose from 50% to 73% in these patients. Median survival duration in the group of patients with values for both biomarkers above the cutoff level was only 18 months. Subjects with high NT-pro-BNP and low osteopontin had a median survival duration of 46 months. Calculation of median survival duration in the low-risk groups was not possible within 48 months of follow-up.

 
Because not all patients had the same follow-up range, we used a Cox proportional-hazards regression model to evaluate the prognostic information provided by osteopontin in chronic heart failure. A comparison of the reduced model with only NT-pro-BNP (as a continuous variable) and the full model with both NT-pro-BNP (as a continuous variable) and osteopontin (as a continuous variable) was made by the likelihood ratio test: For the reduced model (NT-pro-BNP), a likelihood ratio of G=17.94 was determined. P[{chi}2(1)>17.94]=0.00002 was calculated, which indicates that osteopontin provides additional prognostic information beyond that provided by NT-pro-BNP. Taken together, these results suggest that osteopontin provides additional and independent prognostic information for the risk stratification of patients with heart failure and impaired left ventricular function.


    Discussion
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Chronic congestive heart failure is a growing major public health problem. Successful management depends on an accurate and rapid diagnosis and an appropriate risk stratification to identify the patients at highest risk for subsequent decompensation and death. We therefore tested the hypothesis that plasma levels of a novel potential biomarker, osteopontin, are elevated in heart failure patients and, if so, whether such elevation might also correlate with disease severity and prognosis.

The present study demonstrated that osteopontin plasma levels are significantly elevated in patients with systolic heart failure. Moreover, osteopontin plasma levels also provide prognostic information independent of established clinical and biochemical markers, including NYHA stage and NT-pro-BNP.

Role of Osteopontin in Heart Failure
Osteopontin is an extracellular matrix protein that plays an important role in cardiac remodeling and fibrosis. In animal models, its expression is significantly upregulated after increased mechanical stress due to pressure overload,15 genetic cardiomyopathy,16 and myocardial infarction.17 Angiotensin II, which itself is increased in heart failure,18 potently induces osteopontin expression in cardiac cells, such as fibroblasts or cardiomyocytes.9,19 Conversely, experimental studies with osteopontin-knockout mice revealed that osteopontin deficiency abolished angiotensin II–induced cardiac fibrosis,20,21 In addition, it has been shown that the lack of osteopontin blunted myocardial hypertrophy due to experimental transthoracic aortic constriction yet promoted impairment of contractile function.15 Consistently, exaggerated left ventricular dilation in response to myocardial infarction was reported in mice lacking osteopontin.22 Finally, impaired angiogenesis was observed in these animals, which may further contribute to the adverse cardiac remodeling process.23

Taken together, these data suggest that osteopontin is a novel marker protein that is critically involved in cardiac adaptation to biomechanical strain and myocardial injury. Moreover, we found that osteopontin plasma levels were increased irrespective of the underlying cause of heart failure, which suggests that osteopontin may be part of the general neurohormonal response to chronic heart failure. Although at present, the precise functional significance of increased osteopontin in humans remains unclear, it appears that the elevated osteopontin levels observed in heart failure patients represent an unsuccessful attempt to ameliorate adverse ventricular remodeling.

Osteopontin as a Potential Novel Biomarker in Heart Failure
Risk stratification with clinical parameters such as symptom severity and left ventricular ejection fraction is critical to identify those patients with heart failure at greatest risk for subsequent decompensation and death. Recently, biomarkers such as BNP have been shown to add clinically useful information in the management of heart failure patients.24 However, even when clinical findings are combined with BNP levels, there is still considerable variation in the outcome.5 Thus, it is highly unlikely that a single marker will provide all the information needed for clinical decision making, and an integrated "multimarker strategy" may be preferable.25 As a consequence, there is still great interest in new biomarkers that complement existing diagnostic tools and may facilitate risk stratification in patients with heart failure. In this regard, we show that increased plasma levels of osteopontin are significantly associated with heart failure severity. Although patients with significantly impaired systolic function and NYHA class I or II symptoms revealed only mild increases in osteopontin levels, patients in NYHA class III or IV revealed a marked induction, which suggests that osteopontin is a marker for advanced heart failure. Moreover, osteopontin emerged as an independent predictor of 4-year death and added significant information for the risk assessment of patients with heart failure. We also provide evidence that even in patients with a given NT-pro-BNP level, osteopontin levels markedly altered the prediction of 4-year death. The risk of death within 48 months was almost 6-fold greater in patients assigned to a low-risk group according to their NT-pro-BNP levels and whose osteopontin levels were above the cutoff value. Even in the setting of an already significantly elevated NT-pro-BNP, a high osteopontin level still conferred an additional increase in the 4-year death risk, which reached 73% when both markers were combined. In contrast, the death rate was only 12% when both markers were measured below their respective cutoff values. Taken together, it appears that osteopontin provides complementary prognostic information beyond that of traditional markers and could thus improve risk stratification in patients with heart failure.

Study Limitations and Future Directions
We show here that osteopontin levels add significant information in the risk assessment of a cohort of patients with chronic heart failure; however, it remains to be determined whether osteopontin can also aid in clinical decision making in the management of individual patients. For example, it will be interesting to see whether osteopontin levels can predict the response to specific heart failure therapies such as aldosterone antagonists, which have been implicated in attenuation of cardiac fibrosis.26 Moreover, patients were recruited from a heart failure clinic of a large university hospital that serves as a tertiary referral center. Therefore, the present study population comprised relatively young patients, who more often have a nonischemic origin of heart failure. To generalize our findings, it will be important to confirm and extend the results in other heart failure populations and in patients with acute heart failure. Finally, osteopontin is not specific for the heart and has been shown to be elevated in other conditions, including mesothelioma and ovarian cancer.27,28 Thus, it will be critical to interpret elevated osteopontin levels in the appropriate clinical context and likely in concert with other biomarkers, such as NT-pro-BNP.

Summary
In summary, the present study shows for the first time that osteopontin plasma levels are not only elevated in heart failure patients with left ventricular dysfunction but also correlate with disease severity and the risk for subsequent death. The present data demonstrate that osteopontin can expand the prognostic power of established biomarkers in heart failure, such as NT-pro-BNP. Future studies should focus on the evaluation of its potential in advancing the clinical management of patients with heart failure.


    Acknowledgments
 
The authors thank Maike Hornig and Jutta Krebs for their excellent technical support.

Sources of Funding

This work was supported by internal funds from the University of Heidelberg.

Disclosures

Drs Rosenberg, Katus, and Frey have filed a patent application for osteopontin testing in heart failure patients.


    References
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

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CLINICAL PERSPECTIVE

In heart failure, prognostic evaluation is critical to identify patients at highest risk for subsequent decompensation and death. Despite the availability of clinical criteria and the biomarker brain natriuretic peptide, there is still considerable uncertainty in the prediction of prognosis. Consequently, there is great interest in new biomarkers that could improve risk stratification. Osteopontin, a glycoprotein that can be detected in plasma, is an extracellular matrix protein that interacts with several integrins and thereby mediates signals in cell–cell and cell–matrix interaction. Additionally, osteopontin was found to be upregulated in several animal models of cardiac failure and may thus represent an attractive candidate molecule. We therefore tested the hypothesis that osteopontin levels are significantly elevated in patients with chronic heart failure and could provide independent prognostic information. Here, we show that osteopontin plasma levels are readily detectable and significantly elevated in patients with chronic heart failure. Furthermore, osteopontin reliably predicted clinical severity and 4-year death rates irrespective of established demographic, clinical, and biochemical risk factors such as N-terminal prohormone brain natriuretic peptide. For example, patients with a left ventricular ejection fraction ≤40% stratified by an osteopontin and N-terminal prohormone brain natriuretic peptide cutoff value derived from receiver operating characteristic analyses revealed 4-year death rates of only 12% when both biomarkers were measured below the cutoff value, compared with 73% when both biomarkers were elevated above the cutoff (hazard ratio 98, 95% confidence interval [CI] 39 to 246, P<0.0001). We therefore believe that osteopontin will be useful as a new prognostic biomarker in the risk stratification of patients with chronic heart failure.


    Footnotes
 
The online-only Data Supplement, which contains additional figures and tables, can be found at http://circheartfailure.ahajournals.org/cgi/content/full/1/1/43/DC1.





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