Introduction

Several diagnostic tools exist to clinically assess the prevalence and severity of coronary heart disease and to enhance the ability to identify the “vulnerable” patient at risk of developing cardiovascular events. In addition, the assessment of biomarkers is one option to improve the diagnosis of disease, to better identify high-risk individuals, to improve prognostication, and to optimize the selection of and response to chronic artery disease treatment. The major strength of biomarker assessment in chronic coronary artery disease (CAD) constitutes the improved prognostication and monitoring of disease.

The term biomarker (i.e., biologic marker) was introduced approximately 30 years ago indicating a measurable and quantifiable biological parameter (e.g. specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, environmental exposure and its effects, disease diagnosis, metabolic processes, substance abuse, pregnancy, cell line development, epidemiologic studies, etc.

This term was further developed and the definition standardized as

“a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.”

A biomarker can be determined as a biosample (blood-, urinary-, or tissue-borne); it may be a recording like blood pressure, electrocardiogram (ECG), stress test, or Holter; or it can constitute an imaging test (echocardiogram, magnetic resonance imaging [MRI], or computed tomography [CT] scan). This chapter focuses on the impact of blood-borne biomarkers in chronic CAD.

There are several main practical considerations for the use of blood-borne biomarkers in stable CAD ( Box 9.1 ). First, biomarkers might help to identify the prevalence of a disease in addition to clinical assessment, ECG, stress test, and imaging tests such as echocardiography or CT scan. However, the diagnostic accuracy of blood-borne biomarkers in identifying or validating chronic CAD is rather weak. Second, biomarkers may help to improve prognostication in diseased individuals as some biomarkers are strongly related to future cardiovascular events. Third, biomarkers may support treatment selection in CAD patients. Fourth, biomarkers might serve as indicators for disease progression and, finally, biomarkers might be used to monitor treatment success, although the use of biomarkers for the monitoring of disease progression and treatment success has not been successfully proven so far.

BOX 9.1
Biomarker Criteria: What Makes a Biomarker Useful?

  • 1.

    Provides additional information to already established clinical parameters

  • 2.

    Objectively measurable and quantifiable biologic parameter

  • 3.

    Measurable in an accurate and standardized way with low intra-individual variability

  • 4.

    Indicator of health and physiology-related assessments

  • 5.

    Tested in prospective studies to validate its prognostic and diagnostic efficacy

  • 6.

    Able to

    • identify individuals at high risk

    • identify disease prevalence in addition to clinical assessment

    • improve prognostication in healthy and diseased individuals

    • provide information that could lead to a change in therapeutic strategies and support treatment selection

    • monitor treatment success

    • assist the clinician for optimal patient management

    • assess response to therapy

  • 7.

    Easily accessible, measurable, cost-effective

The advent of new molecular technologies such as gene sequencing or reliable determination of noncoding RNAs allows the identification of novel biomarkers related to a disease. These novel biomarkers, which have not entered the clinical routine so far, might have the potential for more accurate disease-related application.

The overall expectation of a biomarker for chronic cardiovascular disease (CVD) is to enhance the ability of the clinician to optimally manage the patient ( Fig. 9.1 ). For instance, in a person with chronic or atypical chest pain, a biomarker may be expected to facilitate the identification of patients with chest pain of ischemic etiology leading to the clinical symptom of angina. In a patient with CAD, a biomarker may assess the likelihood of a future event and response to therapy.

FIG. 9.1, Workflow and qualification of establishing a biomarker for chronic coronary artery disease.

The clinical value of a biomarker is related to its accuracy, its standardized determination including reproducibility, its accessibility, and direct interpretation of the biomarker results for clinicians. The interpretation should include consistent prediction in multiple studies and the capacity to improve patient management. Changes in biomarker levels should lead to clinically relevant consequences (see Fig. 9.1 ).

To date, cardiovascular risk assessment has been predominantly based on classic risk factors. However, particularly in diseased individuals, the classic risk factors do not fully explain the risk of repeated events. Most of these factors are modifiable, and intervention is likely to reduce the risk of CVD. To improve risk estimation beyond what is possible with classic risk factors, many biomarkers have now been related to cardiovascular risk in secondary prevention. It seems that biomarkers of inflammation like C-reactive protein (CRP), biomarkers of hemodynamics like B-type natriuretic peptide (BNP) and the N-terminal fragment of its prohormone, NT-proBNP, and—most recently—markers reflecting cardiac micronecrosis such as cardiac troponins measured with high-sensitivity assays have most consistently improved risk estimates and led to interventions.

Various biomarkers have been postulated to improve risk prediction and patient care in stable CAD patients. Only a few biomarkers have undergone rigorous evaluation regarding whether or not they add prognostic information beyond that which is already obtained by simpler clinical methods and classic risk factors (see Fig. 9.1 ). These extensively studied biomarkers are cardiac troponin I or T, CRP, and BNP. In addition, multiple studies have tested their interaction with different therapeutic strategies.

In general, biomarkers that are currently discussed to support management in chronic CAD reflect different pathophysiologic processes such as cardiac micronecrosis and hemodynamics, as well as more general processes such as inflammation, vascular function, renal function, and lipid disorders.

This chapter provides an overview about established and novel biomarkers in chronic CAD and describes the molecular basis of biomarker discovery and selection and the practical considerations that are a prerequisite to their clinical use.

Biomarkers of Myocardial Injury

Cardiac Troponin

Myocardial injury occurs when there is a disruption of normal cardiac myocyte membrane integrity. This results in the release of intracellular components into the extracellular space, including detectable levels of a variety of biologically active cytosolic and structural proteins, such as cardiac troponins. Myocardial injury has traditionally been considered to be an irreversible process (cell death), occurring mainly during an acute pathologic cardiac condition like an acute coronary ischemic event or acute myocarditis. The advent of more sensitive methods allows troponin determination in apparently stable cardiac healthy conditions.

Cardiac troponins I and T are regulatory proteins that control the calcium-mediated interaction of actin and myosin during contraction. These proteins are products of specific genes and therefore have the potential to be unique for the heart. Studies performed with cardiac troponin I have failed to locate any troponin I outside of the heart at any stage of neonatal development. In contrast, cardiac troponin T is expressed to a minor extent in skeletal muscle. Data indicate that there are at least some patients with skeletal muscle disease who have detectable levels of cardiac troponins. This implies that skeletal muscle injury can, in some patients, be the source for elevations of troponin detected in the blood, even in a healthy state.

Assays to Measure Cardiac Troponins

Cardiac troponins I and T are specific markers for myocardial injury. However, there are variations in the sensitivity and specificity of various immunoassays. This is related to a lack of standardization, the presence of modified cardiac troponin I and troponin T in plasma, and variations in antibody cross-reactivities to the various detectable forms of troponin I that result from their degradation. Because each assay relies on specific conditions, one cannot extrapolate a value from one assay to another. Older assays are less sensitive than newer assays. The former are referred to as conventional or sensitive assays and the latter are referred to as high-sensitivity assays. One criterion for calling an assay high sensitivity is the proportion of apparently healthy individuals in whom the assay is capable of detecting troponin. All individuals have small amounts of measurable troponin levels in their blood. Most conventional or sensitive assays detect troponin levels only in very few normal individuals, whereas some high-sensitivity assays detect troponin in nearly 100% of normal individuals. Both the analytical performance of the assay and instrumentation and differences in the reference populations likely contribute to reported variability between assays (as reviewed by Jaffe ).

The highly sensitive assays have tremendous potential for clinical practice. Compared with sensitive troponin assays, high-sensitivity troponin assays enhance the accuracy and speed of the diagnosis, improve outcome, and are cost-effective. High-sensitivity assays that allow the measurement of very low cardiac troponin levels in patients with stable heart disease are now available for clinical and research use. These low, previously undetectable troponin levels have shown strong associations with incidents, i.e., future myocardial infarction (MI), stroke, and death, in a variety of primary and secondary prevention populations, including in patients with stable ischemic heart disease or stable CAD.

Omland et al. showed that very low circulating levels of cardiac troponin T are detectable in the great majority of patients with stable CAD and preserved left ventricular function. Multiple conventional risk factors were associated with higher troponin T levels in this population, and very low circulating levels of troponin T had a graded relationship with the incidence of cardiovascular death and heart failure (HF). Moreover, the authors presented insights into the levels well below the limit of detection of previous assays and below the 99th percentile in apparently healthy blood donors. Even in this range, troponin levels were strongly associated with the incidence of cardiovascular death and HF; however, the levels were not independently associated with the incidence of MI.

When applying a high-sensitivity troponin I test in the same study population, Omland et al. demonstrated that small elevations were associated with the incidence of cardiovascular death or HF in patients with stable CAD and provide additional prognostic information to conventional risk markers and prognostic cardiovascular biomarkers, including troponin T. Interestingly, the correlation between troponin I and troponin T levels was of only moderate strength, suggesting that mechanisms of release and/or degradation may potentially differ between the troponins in the chronic setting. Furthermore, troponin I, but not troponin T, was significantly and independently associated with both prior acute MI (AMI) and the incidence of subsequent AMI. Chronic, low-grade elevation of troponin I and troponin T in patients with stable CAD may potentially reflect different pathophysiologic determinants and suggest different therapeutic responses.

Everett et al. showed in their study involving patients with both type 2 diabetes and stable ischemic heart disease that baseline cardiac troponin T levels above the upper limit of normal were associated with approximately a doubling of the risks of MI, stroke, HF, death from cardiovascular causes, and death from any cause. Nearly 40% of the patients had high-sensitivity cardiac troponin T levels at baseline that were above the upper reference limit used to define myocardial injury. The incidence of the primary composite endpoint of death from cardiovascular causes, MI, or stroke at 5 years in this group was 27%, which was double the rate in the group with normal baseline troponin T levels. Similar results were seen with respect to other important outcomes, such as the secondary composite outcome of death from any cause, MI, stroke, or HF. The relationship between troponin T levels and the subsequent risk of MI, stroke, HF, death from cardiovascular causes, and death from any cause suggests that high-sensitivity cardiac troponin T level is a powerful prognostic marker in patients who have both type 2 diabetes and stable ischemic heart disease.

The newly established technologies allow precise measurement of low circulating troponin levels even in the general population. This biomarker is of particular importance, as it is cardiac specific and directly reflects pathologic cardiac conditions. Cardiac troponin concentrations also correlate with the prevalence of cardiovascular risk factors. Assessment of circulating troponin levels using a robust, highly sensitive assay might therefore be suitable to predict first and subsequent adverse events. Whether the measurement of troponin in addition to risk scoring systems is useful for cardiovascular risk assessment will be subject to further research.

The first steps in this direction have been analysed by using the harmonized database and biobank of the Biomarker for Cardiovascular Risk Assessment in Europe (BiomarCaRE). The distribution of troponin I levels was evaluated on an individual level, assayed using a highly sensitive method in population cohorts across Europe. The association with cardiovascular mortality, first nonfatal and fatal cardiovascular events, and overall mortality has been characterized, and the predictive value beyond the variables used in the European Society of Cardiology Systematic COronary Risk Evaluation (ESC SCORE) has been determined. The application of high-sensitivity cardiac troponin I has the potential to improve risk prediction of cardiac death in the general population. A potentially clinically relevant cut-off value was applied. The results of the BiomarCaRE study indicate conditions in which the determination of troponin I concentrations provides additional prognostic information to established risk models. Troponin I determination might support the selection of those individuals who would benefit most from preventive strategies. However, the direct interaction between troponin elevation and preventive treatment strategies in particular in diseased individuals still has to be proven.

Biomarkers of Vascular Function and Neurohumoral Activity

B-Type Natriuretic Peptide

BNP is a natriuretic peptide hormone with vasoactive functions and is involved in volume homeostasis and cardiovascular remodeling. Both BNP and NT-proBNP are robust markers of neurohormonal activation. BNP is produced from larger precursor molecules, prepro-BNP(1-134) and pro-BNP(1-108), pro-BNP is then cleaved into the active moiety BNP(1-32) and an inactive part, NT-proBNP(1-76). Although this simple model of the cleavage pattern is widely described, the cleavage mechanisms seem to be more complex and dependent on different factors. A number of reports have demonstrated high-molecular-weight material, apparently unprocessed proBNP forms, circulating in healthy as well as in diseased individuals, even in almost equal amounts as processed BNP. proBNP is a glycoprotein including several glycosylation sites within the protein. The glycosylation status seems to be crucial for further proBNP processing, in particular at the glycosylation sites near the region of cleavage. Molecular studies have shown an O-glycosylation-dependent inhibition of proBNP processing, which could be one possible explanation for the presence of higher levels of unprocessed proBNP in biologic samples. In addition, NT-proBNP in human blood is also glycosylated, which can negatively influence the recognition of NT-proBNP by antibodies targeting the central part of the molecule and thus might not be easily accessible by standard assays. These data are of clinical interest, as they indicate the existence of different high-molecular-weight and low-molecular-weight forms of BNP in biologic material. Consequently, assays to detect BNP/NT-proBNP need to be able to clearly distinguish between these various circulating forms of BNP.

Several other mechanisms also contribute to an increase in BNP levels such as cardiac hypertrophy, or increased muscle mass in left ventricular hypertrophy. By binding to its receptor (natriuretic peptide A receptor), BNP mediates natriuresis, vasodilatation, and renin inhibition, as well as anti-ischemic effects. Clearance of BNP is mediated mainly via the natriuretic peptide C (clearance) receptor and the widely distributed enzyme neprilysin. Although functionally inactive, NT-proBNP has a longer half-life compared to BNP (1–2 h vs. 20 min), resulting in higher circulating levels. The longer in vivo half-life and enhanced in vitro stability are clear advantages, particularly in settings such as general practice where samples are shipped to hospital laboratories for analysis.

The main source of circulating BNP is the ventricular myocardium where it is produced in response to dilatation and pressure overload, and released into the circulation. This reflection of myocardial stretch makes BNP an excellent marker for diagnosis and an important surrogate for severity of HF. As markers for myocardial stretch, and the fact that therapy of HF modulates levels of BNP and NT-proBNP, these biomarkers are recommended for the assessment of diagnosis, prognosis, and treatment success in HF by all major cardiovascular societies.

A large body of data provide evidence that BNP production is stimulated by hypoxia and ischemia itself, processes which may result in myocyte stress under ischemic conditions despite constancy in measurable hemodynamic parameters.

For patients with HF with reduced ejection fraction (HFrEF), impressive data have been generated for BNP in the prediction of outcome. In particular, patients with persistently high BNP levels are at high risk for adverse outcomes. In chronic HF, higher levels of BNP are associated with increased cardiovascular and all-cause mortality, independent of age, New York Heart Association class, previous MI, and left ventricular ejection fraction (LVEF). BNP is also associated with re-admission for HF and outcomes after presentation to the emergency department for HF, a setting in which traditional risk factors do not have any prognostic value. In HF with preserved ejection fraction (HFpEF), BNP has also been shown to be an important prognostic marker in patients for predicting mortality.

In addition to its use for HF diagnosis and prognosis, NT-proBNP has also been recognized as a marker of long-term mortality in patients with stable coronary disease. Kragelund et al. showed, in over 1000 coronary heart disease (CHD) patients, including a high proportion of patients with suspected HF, that NT-proBNP levels were significantly higher in patients who died from any cause after a median follow-up of 9 years. Patients with high NT-pro-BNP levels were older, had a lower LVEF and a lower creatinine clearance rate, and were more likely to have a history of MI, clinically significant CAD, and diabetes. In another large study whose aim was to examine the predictive value of BNP in CAD for long-term cardiovascular outcome, Schnabel et al. prospectively analyzed BNP levels in patients with stable angina. BNP levels were significantly increased in patients with future cardiovascular events. Patients with high levels of BNP had an elevated risk for cardiovascular events, even after adjustment for potential confounders such as age, gender, body mass index (BMI), CRP, and HDL-C ( Fig. 9.2 ). These data provide clear and independent evidence that BNP is a strong prognostic marker that provides additional information above and beyond that provided by classic risk factors.

FIG. 9.2, Evidence for the predictive value of B-type natriuretic peptide in coronary artery disease for long-term cardiovascular outcome.

In the studies of Kargelund and Schnabel, a high proportion of clinically suspected HF patients—and thus high-risk stable CAD patients—were present. Thus, the association between BNP and mortality might be explained mainly by the ability of BNP to predict HF. To further examine whether BNP can act as a prognostic indicator in patients with low-risk stable CAD and to investigate whether BNP levels might also relate to incidence of coronary ischemic events, plasma BNP and NT-proBNP levels were measured in a subcohort of the Prevention of Events with Angiotensin-Converting Enzyme Inhibition (PEACE) trial, including patients with stable CAD and preserved systolic function. Both BNP and NT-proBNP showed predictive value for incidence of cardiovascular death, congestive HF, and stroke, but not for MI. After adjustment for classic risk factors, both peptides were still predictive for HF but only NT-proBNP remained predictive for cardiovascular death and stroke. Importantly, even after adjustment for the incidence of HF, NT-proBNP remained a significant predictor of cardiovascular mortality. Accordingly, both BNP peptides added strong prognostic information to classic risk factors in both high- and low-risk patients with stable CAD.

Although persuasive evidence exists that NT-proBNP and BNP strongly predict outcome in individuals with chronic CAD, the determination of these natriuretic markers is currently not established in the clinical routine of stable ischemic heart disease assessment. This is explained by the lack of treatment consequences in individuals with chronic CAD who have elevated NT-proBNP or BNP levels. Nevertheless, elevated natriuretic peptide levels in these patients should prompt detailed diagnostic efforts to exclude the presence of HF.

Atrial Natriuretic Peptide

Similar to BNP, atrial or A-type natriuretic peptide (ANP) is a hormone that is released from myocardial cells in response to volume expansion and increased wall stress. ANP circulates primarily as a 28–amino acid polypeptide predominately synthesized and secreted by atrial cardiomyocytes in healthy individuals. In HF, ANP is also produced by ventricular cardiomyocytes. ANP is derived from a precursor molecule of 126 amino acids, called proANP, and is cleaved into a 98–amino acid N-terminal fragment (NT-proANP) and the active ANP. NT-proANP has a much longer half-life than active ANP and has therefore been proposed as a more reliable analyte for measurement than ANP. Further fragmentation of proANP results in a mid-regional ANP molecule (MR-proANP), which is even more stable than the N- or C-terminal part of the precursor.

Just like the related B-type natriuretic peptides, an increase in ANP and its cleavage associates with HF. The Leicester Acute Myocardial Infarction Peptide (LAMP) study demonstrated that MR-proANP is a powerful predictor of death in post-MI patients. This was especially evident in patients with an elevated NT-proBNP, indicating that the combination of both A- and B-type natriuretic peptides gives added prognostic information above existing clinical characteristics. The Gruppo Italiano per lo Studio della Sopravvivenza nell’Infarto Miocardico Heart Failure (GISSI-HF) trial provided evidence that measurement of MR-proANP provided prognostic information independently of NT-proBNP. Natriuretic peptides and other vasoactive peptides were measured in 1237 patients with chronic stable HF at randomization and at 3 months. The addition of MR-proANP improved classification for mortality when added to models based on clinical risk factors alone (net reclassification improvement [NRI] = 0.12) or together with NT-proBNP (NRI = 0.06). Increases in MR-proANP levels were associated with mortality (hazard ratio 1.38, 95% confidence interval [CI] 0.99–1.93 and hazard ratio 1.58, 95% CI 1.13–2.21, in the middle and highest versus the lowest tertiles, respectively).

Although data on the value of ANP and its amino- and mid-terminal fragments in chronic coronary disease are available, more data are needed to define the clinical utility of MR-proANP measurements in patients with stable angina pectoris and chronic CAD.

Adrenomedullin

Adrenomedullin (ADM) is a peptide that was originally isolated from human pheochromocytoma cells; it has an amino acid sequence that is similar to human calcitonin gene-related peptide, a potent vasodilator. In addition to the strong vasodilatory effects on the vasculature, ADM enhances myocardial contractility via a cyclic adenosine monophosphate-independent mechanism (reviewed by Colucci ). Although not cardiac-specific, ADM exerts various effects on the cardiovascular system, i.e., induction of hypotension and bronchodilatation or enhancement of renal perfusion.

ADM is derived from a 185–amino acid precursor peptide (preproADM), which is processed into another biologically active peptide termed proadrenomedullin N-terminal 20 peptide (PAMP). This peptide fragment has a suggested hypotensive effect and two peptides flanking ADM: one mid-regional part of proADM (proADM 45–92) and the COOH terminus of the molecule (proADM 153–185).

Earlier studies investigating the active form of ADM showed that ADM plasma levels are elevated in patients with chronic HF and increase with disease severity. Because active ADM immediately binds to receptors in the vicinity of its production and has a short half-life (22 min), reliable measurement of active ADM in the circulation is difficult. Therefore, novel immunoassays measuring the stable mid-regional part of proADM (MR-proADM) have been developed and are currently used to assess MR-proADM levels.

In hypertensive African Americans, MR-proADM is correlated with pulse pressure, left ventricular (LV) mass, and albuminuria (reviewed by Neumann et al. ). In patients with HF, ADM was an independent predictor of mortality and added further prognostic value to established biomarkers, e.g., NT-proBNP. In the Biomarkers in Acute Heart Failure (BACH) trial, which investigated the prognostic value of MR-proADM in patients with acute HF, the peptide predicted survival over a period of 90 days superior to BNP and NT-proBNP. Using cut-off values, the accuracy to predict 90-day survival was 73% for MR-proADM, 62% for BNP, and 64% for NT-proBNP (difference p < 0.001). Even in the adjusted multivariable Cox regression, MR-proADM carried independent prognostic value.

The prognostic impact of MR-proADM on future fatal and nonfatal cardiovascular events in patients with symptomatic CAD was assessed in the AtheroGene study. Individuals presenting with stable angina pectoris had comparable MR-proADM levels to levels in those with acute coronary events. Individuals who suffered a subsequent cardiovascular event had elevated MR-proADM levels at baseline in both groups. Baseline MR-proADM levels were independently associated with future cardiovascular events, and MR-proADM added information beyond that obtained from classic risk models. The additional use of MR-proADM for risk stratification in patients with known stable coronary heart disease was also shown in the Long-Term Intervention with Pravastatin in Ischemic Disease (LIPID) study. Here, baseline levels of MR-proADM predicted major CHD events (nonfatal MI or CHD death and all-cause mortality) after 1 year. An increase in MR-proADM levels after 1 year was associated with an increased risk of subsequent CHD events, nonfatal MI, HF, and all-cause mortality. Adjustment for baseline BNP levels did not change the significance of these associations.

Concerning its prognostic value in post-MI patients, MR-proADM was also a powerful predictor of adverse outcome and was correlated with future cardiovascular events in patients with symptomatic CAD and acute chest pain. In the LAMP Study, MR-proADM was increased in post-MI patients who suffered death or HF, and MR-proADM levels were significant independent predictors of death and HF in these patients. MR-proADM levels provided even stronger risk stratification in those patients who had NT-proBNP levels above the median, indicating that MR-proADM represents a powerful and clinically useful marker for prognosis of death and HF after AMI, comparable to or in combination with NT-proBNP.

Growth Differentiation Factor-15

Growth differentiation factor-15 (GDF-15), also known as serum macrophage inhibitory cytocine-1 (MIC-1), is a member of the transforming growth factor (TGF-ß) cytokine superfamily, which has been discussed in the last decade as a novel emerging biomarker for CVD and other diseases such as cancer. Under physiologic conditions, GDF-15 is solely expressed in the placenta, but its expression pattern is increased under various pathophysiologic conditions. GDF-15 has been shown to be associated with oxidative stress, inflammation, and stress induced by biomechanical stretching of the heart. In an experimental mouse model, Kempf et al. showed endogenous GDF-15 to be significantly involved in cardiac protection in ischemia or reperfusion injury. However, the pathophysiologic role of GDF-15 in different pathologic disease states and its regulatory mechanism are still controversial.

In diseased patients suffering from HF, GDF-15 measurement improved the prediction of mortality and an adverse outcome. Interestingly, GDF-15 levels seem to better correlate with diastolic dysfunction than NT-proBNP levels and thus add incremental information to NT-proBNP in a population at risk. Brown et al. described increased plasma levels of GDF-15 as a predictor for cardiovascular events in patients in a case-control study in healthy women. Interestingly, GDF-15 was also reported to be a prognostic marker in non-ST-segment elevation MI (NSTEMI) or ST-segment elevation MI (STEMI). GDF-15 has also been evaluated as a prognostic tool in stable CAD. In the AtheroGene study, GDF-15 was associated with coronary heart disease mortality, but not MI, after adjustment for confounders. In the Heart and Soul study, GDF-15 was independently associated with increased risk of cardiovascular events. GDF-15 levels have also been implicated as a marker for patients at risk of death and HF rehospitalization in both HFrEF and HFpEF. To date, this marker constitutes a powerful risk predictor in various clinical conditions, but without direct clinical applicability. Whether the determination of GDF-15 in chronic CAD might help to improve treatment strategies has not yet been tested.

Biomarkers of Renal Function

It has been well proven that impairment of renal function is strongly associated with CAD and cardiovascular mortality. Beyond shared risk factors, decreased renal function affects the cardiovascular system through numerous mechanisms, e.g., increased aldosterone activity, enhanced proinflammation, and platelet activation. These mechanisms lead to an acceleration of the development and progression of CAD, resulting in a poor prognosis of patients with decreased renal function. In addition to manifest chronic kidney disease, slight impairment of renal function is also associated with increased coronary risk. Therefore, biomarkers for the identification and exact quantification of different stages of renal dysfunction are essential for risk stratification, prevention, and therapies of CAD.

Estimated Glomerular Filtration Rate

The estimated glomerular filtration rate (eGFR) is the most relevant parameter for assessment of renal function in clinical practice. Different equations for the estimation of GFR have been developed during the past decades. Today, the eGFR equation of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) is the best validated equation in terms of accuracy and risk prediction, especially in individuals with normal or only mildly reduced GFR. Thus, the CKD-EPI equation is currently replacing other eGFR equations such as the Cockcroft-Gault equation or the Modification of Diet in Renal Disease (MDRD) equation. Despite several limitations, serum creatinine remains the most commonly used renal marker for estimation of GFR.

Numerous large studies have shown a substantial increase of cardiovascular risk in relation to eGFR decline toward 60 mL/min per 1.73 m 2 or below. Individuals with an eGFR less than 60 mL/min per 1.73 m 2 are defined as high cardiovascular risk. Although those individuals are exposed to more adverse effects by the use of cardiovascular drugs or iodinated contrast agents compared to individuals with a preserved renal function, the benefit of an intensive treatment of CVD outweighs this substantially in patients with decreased renal function. Therefore, a baseline and annual measurement of creatinine and assessment of renal function with eGFR is recommended for all patients with known or suspected CAD.

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