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.
- 1.
Provides additional information to already established clinical parameters
- 2.
Objectively measurable and quantifiable biologic parameter
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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
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identify individuals at high risk
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identify disease prevalence in addition to clinical assessment
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improve prognostication in healthy and diseased individuals
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provide information that could lead to a change in therapeutic strategies and support treatment selection
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monitor treatment success
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assist the clinician for optimal patient management
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assess response to therapy
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- 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.
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.
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.
Cystatin C
As serum creatinine measurements have limitations due to variations in creatinine production, secretion, and extra-renal excretion influenced by age, gender, muscle metabolism, and renal reserve, potentially more robust renal markers have been evaluated. Of these, cystatin C is the best validated and most widespread renal marker beside serum creatinine. Cystatin C is produced by all nucleated cells at a relatively constant rate, is filtered at the glomerulus, and is not reabsorbed in the tubules. Due to fewer variations influenced by age, gender, muscle mass, diet, or other factors, impaired cystatin C concentration better detects particularly mild decreases of renal function. In a large cohort of patients with CAD and normal or only mildly reduced renal function, cystatin C was a potent predictor of cardiovascular mortality beyond classic risk factors.
In terms of GFR prediction, the use of cystatin C for estimation of eGFR with cystatin C–based eGFR equations has similar accuracy compared to the use of creatinine-based eGFR equations. The combined CKD-EPI eGFR equation using both serum creatinine and cystatin C has been shown to be more exact for estimation of GFR than eGFR equations based on either of these markers alone. In terms of cardiovascular risk prediction, eGFR calculated with the cystatin C–based or combined CKD-EPI equation was shown to be more strongly associated with the cardiovascular prognosis than eGFR calculated with serum creatinine–based equations both in a cohort of HF patients and in a cohort of patients with CAD.
Measurement of cystatin C in addition to serum creatinine and assessment of eGFR with the combined CKD-EPI equation can be helpful as a confirmatory test in patients with a creatinine-based GFR estimation of 45 to 75 mL/min per 1.73 m 2 to identify, or exclude more accurately, the cardiovascular high-risk setting of reduced renal function with a GFR less than 60 mL/min per 1.73 m 2 , which requires the most intensive treatment of cardiovascular risk factors.
Lipid Biomarkers
More than a century ago the German chemist Adolf Windaus described a far higher amount of cholesterol in atherogenic plaques of human aortas compared to healthy aortas. Since then, numerous studies have demonstrated a key role of atherogenic cholesterol-containing lipoprotein particles, particularly low-density lipoprotein cholesterol (LDL-C), for the development of CAD.
Although there is a large diversity of measurable lipoproteins and various lipoprotein ratios have been evaluated, the strong evidence of lipid-lowering therapy established through many randomized controlled trials is almost entirely based on total cholesterol and LDL-C. (See Chapter 8 for more on lipid biomarkers.)
Recommendations for Lipid Profile Measurement
A lipid profile including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), LDL-C, and triglycerides (TGs) should be assessed in all patients with suspected or known stable CAD. In those patients with established diagnosis of CAD the lipid profile should be reassessed in an intervallic manner in order to control the efficacy of lipid-lowering therapy and to evaluate dose adjustments in the case of LDL-C goal-directed therapy. Without clear evidence for the duration of intervals of reassessment, annual measurements of the lipid profile are recommended.
Whereas measurement of lipids at a fasting status was common for decades, the 2016 joint consensus statement from the European Atherosclerosis Society and European Federation of Clinical Chemistry and Laboratory Medicine recommended the routine use of nonfasting lipid profiles to improve patient compliance and simplify the processes of lipid testing. This recommendation is based on well-proven data indicating that the changes of lipid parameters 1 to 6 hours after a common meal are not clinically relevant. A fasting measurement of the lipid profile is only recommended in the case of very high nonfasting TG levels (> 440 mg/dL according to ESC recommendations, > 500 mg/dL according to American Heart Association [AHA]/American College of Cardiology [ACC] recommendations).
Low-Density Lipoprotein Cholesterol
Epidemiologic, genetic, mechanistic, and intervention studies have proven the causal role of LDL-C in the genesis of CAD. In patients with CAD, an LDL-C reduction with statins of 1 mmol/L (38.7 mg/dL) results in a 20% to 25% relative risk reduction of major vascular events irrespective of baseline LDL-C. Furthermore, several studies have shown a lower progression and even regression of CAD with significant percent diameter stenosis decrease and minimum lumen diameter increase under intensive LDL-C reduction by high-dose statin therapy.
Neither treatment to a specific LDL-C target nor comparison of different LDL-C treatment targets has been investigated by randomized controlled trials. The vast majority of randomized controlled trials proving a risk reduction in patients with CAD used a fixed-dose statin therapy. Based on this evidence the latest ACC/AHA guidelines do not recommend any specific LDL-C targets or titrating lipid-lowering therapy to LDL-C goals, but do recommend high-intensity statin therapy in all patients with known CAD regardless of specific LDL-C targets. In contrast, the ESC guidelines recommend statin therapy for all patients with CAD with a treatment target of LDL-C less than 1.8 mmol/L (< 70 mg/dL) or at least 50% reduction from baseline LDL-C if the target level cannot be achieved. Despite different recommendations regarding the strategies of lipid-lowering therapy for patients with known CAD, both the ESC guidelines and ACC/AHA guidelines recommend at least annual measurements of LDL-C to evaluate the adherence and response to lipid-lowering therapy. LDL-C can be determined using the Friedewald formula, if TGs are less than 400 mg/dL, or measured directly irrespective of TG levels.
High-Density Lipoprotein Cholesterol
An inverse correlation of HDL-C levels and the risk of CAD has been found by numerous epidemiologic studies. Several protective mechanisms of HDL-C have been described. Despite the strong correlation of HDL-C levels and CAD, no causation between HDL-C and the genesis of CAD or atherosclerosis has been established. Of particular importance, Mendelian randomization studies have not shown an association between genetic mechanisms that raise HDL-C levels and the risk of CVD. Furthermore, clinical trials investigating HDL-C-raising therapies such as niacin or cholesteryl ester transfer protein inhibitors have failed to improve cardiovascular outcomes. In the setting of secondary prevention, both the AHA/ACC and ESC guidelines do not specify HDL-C levels as treatment targets for patients with CAD. In the setting of primary prevention or suspected CAD, measurement of HDL-C is recommended for risk estimation and can be used for decision-making in individuals with a cardiovascular risk at the threshold for intensive risk factor modification, where these individuals qualify for more intensive advice in the case of low HDL-C levels. Low HDL-C levels are defined as less than 1.0 mmol/L (< 40 mg/dL) in men and less than 1.2 mmol/L (< 45 mg/dL) in women.
Markers of functional properties of HDL as cholesterol efflux capacity and not solely HDL-C levels are promising and might be established as relevant biomarkers and treatment targets.
Triglycerides
Elevated levels of TGs are associated with CVD with an increased risk for fasting levels of greater than 1.7 mmol/L (> 150 mg/dL). Compared to hypercholesterolemia as a cardiovascular risk factor, the association of TGs and CVD is far weaker. However, evidence suggesting a causal role of TGs in the genesis of coronary heart disease was recently presented. Because clinical trials with triglyceride-reducing therapies such as fibrates, nicotinic acid, and fish oil have failed to show a cardiovascular risk reduction, guidelines do not specify treatment targets for patients with CAD. Irrespective of the presence of CVD the ACC/AHA guidelines recommend an evaluation for secondary causes of hyperlipidemia in the case of very high TG levels (≥ 500 mg/dL [≥ 5.7 mmol/L]), e.g., high alcohol intake, nephrotic syndrome, hypothyroidism, or poorly controlled diabetes.
Lipoprotein(a)
Beyond the role of a cardiovascular risk factor, genetic studies indicate a causal role of lipoprotein(a) (Lp[a]) for CVD, particularly CAD. Plasma levels of Lp(a) are genetically determined, remain relatively constant throughout life without significant response to lifestyle changes, and vary strongly between ethnicities, with the lowest levels in Caucasians and highest levels in African Americans. A strong inverse correlation between the size of the apo(a) isoforms and Lp(a) levels has been shown. Therefore, assays for Lp(a) measurements are recommended to be isoform insensitive. Several substances, such as some fibrates or niacin, have been shown to moderately reduce Lp(a) levels by a maximum of 30% to 35%. However, no clinical trials have shown cardiovascular risk reduction for selective Lp(a) reduction. Instead of broad screening for elevated Lp(a) levels in the general population, Lp(a) should be measured once only in selected individuals. For patients with CAD, measurement of Lp(a) is recommended in those with a premature CAD, in those with a family history of premature CVD and/or elevated Lp(a), and in those with recurrent vascular events despite intensive statin treatment. Reassessment of Lp(a) levels is only necessary in patients who receive Lp(a)-reducing treatment such as niacin or lipid apheresis.
Inflammatory Biomarkers
High-Sensitivity C-Reactive Protein
CRP is a sensitive marker of inflammation and tissue damage. Phylogenetically conserved, CRP plays a role in the response to inflammation. Produced in the liver, levels of CRP rapidly rise nonspecifically during acute phase reactions, such as infections. CRP directly binds highly atherogenic oxidized LDL-C and is present within lipid-laden plaques, thereby triggering the immune response.
CRP has received widespread interest in CVD, although controversy remains regarding its clinical value as a potential proinflammatory mediator. Data from several epidemiologic studies indicate a significant association between elevated serum or plasma levels of CRP and the prevalence of underlying atherosclerosis, the risk of recurrent cardiovascular events among patients with established disease, and the incidence of first cardiovascular events among individuals at risk for atherosclerosis.
In addition, a number of drugs used in the treatment of CVD, such as statins, reduce serum CRP levels. The potential interaction of CRP levels with statin therapy has been retrospectively and prospectively tested in various clinical trials. The Pravastatin or Atorvastatin Evaluation and Infection Therapy–Thrombolysis in Myocardial Infarction 22 (PROVE-IT–TIMI 22) and Reversal of Atherosclerosis with Aggressive Lipid Lowering (REVERSAL) trials showed that intensive statin therapy achieved a greater reduction in high-sensitivity C-reactive protein (hs-CRP) levels and, together with LDL-C, were associated with a greater reduction in the number of clinical events and progression of atherosclerotic plaque burden. Statins reduced hs-CRP and LDL-C levels by 38% and 35%, respectively. Confirmation of these data could be shown in the Aggrastat to Zocor (A to Z) trial, in which on-treatment hs-CRP levels were independently associated with long-term survival. The Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) study prospectively tested the impact of rosuvastatin therapy in cardiovascular risk individuals with LDL levels below 130 mg/dL and CRP above 2 mg/L. In this trial of apparently healthy individuals without hyperlipidemia but with elevated hs-CRP levels, rosuvastatin significantly reduced the incidence of major cardiovascular events. These data provide the possibility that reduced inflammation contributes to the beneficial effects of these medications.
The question of whether CRP is causally linked with CAD (and thus lowering CRP should also reduce CAD risk), or just a marker of underlying atherosclerosis, has been investigated in Mendelian randomization studies. These approaches allow the drawing of conclusions about the causality underlying the relationship between biomarker and diseases. Mendelian randomization studies investigate the impact of genetic variations, which influence circulating biomarker levels like CRP concentration, on future cardiovascular events. Several such Mendelian randomization studies investigating CRP and cardiovascular events have convincingly excluded a causal role of CRP for CAD. In contrast, Mendelian randomization studies targeting the LDL hypothesis have proven the causal role of LDL-C for incident cardiovascular events. Despite the consistent epidemiologic evidence, there is, at present, no established role for routine measurement of hs-CRP in patients with CVD.89
Various studies described the association between CRP and outcome in patients with stable angina and chronic CAD. Hs-CRP levels were, among other inflammatory markers, significantly higher in those patients who died of cardiac events during follow-up and were predictive of death. This association was not observed in statin-treated individuals. However, in patients without statin medication, cardiac mortality was low when the patients had low hs-CRP levels but was high in individuals with elevated hs-CRP levels. These patients had a 2.3-fold risk increase for fatal coronary events, independent of LDL-C levels. In the PEACE trial, the ability of hs-CRP to predict outcomes in patients with stable CAD and a preserved ejection fraction was further tested. In over 3700 patients, hs-CRP levels were measured and patients were followed up over a median of 4.8 years for cardiovascular death, MI, or stroke. Higher hs-CRP levels were associated with a significantly increased risk of cardiovascular death, MI, and stroke, even at average levels > 1 mg/L. Elevated hs-CRP levels were also found to be an independent predictor for incident HF and diabetes. Thus, in patients with stable CAD, hs-CRP levels were a strong predictor of cardiovascular death, MI, stroke, new HF, and new diabetes, independent of baseline characteristics and treatments.
Despite being associated with incident cardiovascular events in patients with chronic CAD, the strength of the CRP association is not comparable to that of cardiac specific biomarkers such as troponin or NT-proBNP. For example, in the Heart Outcomes Prevention Evaluation (HOPE) Study, which evaluated several biomarkers in a setting of high-risk individuals, data showed that classic risk factor models do not gain accuracy by including inflammatory markers for the prediction of future cardiovascular events. The value for risk prediction attributable to CRP was modest, whereas plasma NT-proBNP levels strongly predicted future fatal and nonfatal cardiac events and, significantly, added information above classic risk factors. Furthermore, no interaction between CRP levels and ramipril therapy was observed.
At this stage, the clinical use of CRP determination in patients with established chronic CAD is not fully proven and has not been included in guideline recommendations.
Interleukin-6
Whereas the association between inflammation and the development of atherosclerotic disease is well known, proving causation for any particular biomarker of inflammation has been difficult. Interleukin (IL)-6 signals a downstream proinflammatory response by activating membrane-bound IL-6 receptors on the cell surface. IL-6 receptors appear to play a direct causal role in the development of CHD and have been discussed as a target for therapeutic interventions to prevent CHD. Two large meta-analyses have confirmed the crucial role of IL-6 in the generation of inflammation and the associated risk of CHD. These studies demonstrated an association between IL-6 levels and CHD in a dose-dependent manner. Taken together, these results provide evidence supporting a causal role of IL-6 in the development of CHD and suggest it as a target for therapeutic interventions to prevent CHD.
Multiple Marker Strategies
The simultaneous measurement and analysis of several biomarkers might add more clinically useful information, as a broader picture of the different pathophysiologic aspects could be reflected upon and thus would be more informative. Several studies have evaluated the performance of these multimarker strategies in individuals with chronic CAD.
The incremental value of simultaneously measured markers reflecting acute-phase reaction, proinflammatory pathways, endothelial cell activation, and vascular function, compared to classic risk factors, was assessed in the secondary prevention setting of the HOPE Study. Among others, hs-CPR, IL-6, and NT-proBNP were analyzed with regard to the endpoints of MI, stroke, and cardiovascular death. Inflammatory markers such as CRP and IL-6 added only limited additional prognostic information above classic risk factors (although individually significantly related to cardiovascular risk), whereas the inclusion of NT-proBNP improved the prediction of future cardiac events, resulting in significant incremental prognostic information.
Another multimarker approach for risk prediction in CAD selected more novel biomarkers reflecting inflammation (CRP, GDF-15), lipid metabolism (apolipoproteins), renal function (cystatin C and creatinine), and cardiovascular function and remodeling (including natriuretic peptides and MR-proADM), representing multiple pathways of CAD. This comparative analysis revealed Nt-proBNP, MR-proADM, cystatin C, and MR-proANP as the most informative biomarkers offering incremental predictive ability over classic risk factors. The combination of these biomarkers was most strongly related to outcome, and added incremental risk information to classic risk factor models. However, the combination did not enhance risk stratification or reclassification compared to the strongest single biomarkers, NT-proBNP and GDF-15. Supporting these data, a multimarker approach in the PEACE trial including stable CAD patients at low risk assessed the markers MR-proANP and MR-proADM, as well as endothelin and copeptin. After adjustment for clinical cardiovascular risk predictors and LVEF, elevated levels of MR-proANP, MR-proADM, and CT-proET-1 were independently associated with the risk of cardiovascular death or HF. These three biomarkers also significantly improved metrics of discrimination when added to a clinical model.
In the LIPID study the predictive power of biomarkers reflecting hemodynamics, micronecrosis, inflammation, coagulation, lipids, neurohumoral activity, and renal function was examined beyond classic risk factor models. Furthermore, the investigators addressed whether changes in concentrations of these biomarkers over 12 months affected the risk of subsequent CHD events. All baseline biomarkers measured—except lipoprotein-associated phospholipase A2 (Lp-PLA2) activity and Lp(a)—were associated with outcome. The strongest prediction was observed for BNP and sensitive troponin I baseline concentrations. The prediction strength of these biomarkers was also strong compared with classic risk factors and other clinical features. Of all variables assessed, only a history of MI was a stronger predictor than troponin I or BNP. The other biomarkers—cystatin C, MR-proADM, D-dimer, and CRP—had significant but lesser prognostic value. The major finding was that changes in levels of troponin I and BNP in addition to their baseline levels predicted higher or lower CHD risk. These associations were observed irrespective of whether patients were randomized to pravastatin or placebo. Thus, both of these markers can be considered to reflect aggregate therapeutic and environmental effects. Despite evidence that some biomarkers can add information concerning prediction of the risk of CVD and associated events, apart from their diagnostic value in acute MI (troponin) and HF (particularly BNP) the direct clinical benefit of their assessment in usual clinical practice has not been well defined.
In summary, the data of most multiple marker studies suggest that combining biomarkers reflecting different cardiovascular processes in a panel can be helpful for improved risk prediction in chronic CAD and repeated biomarker measures such as troponin or BNP, and their level changes might directly translate into risk prediction.
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