A. Introduction

The term biomarker first appeared in scientific literature in the 1980s in the field of oncology and since that time, its presence has grown exponentially, expanding into virtually all-medical areas.

Biomarkers refer to a wide range of measureable parameters that are used as indicators or links to provide information about a complex biological characteristic or process. Any biological index, including key molecules (such as proteins, DNA, or RNA), or any form of scientific or optical imaging, can be considered a biomarker.

Biomarkers are an integral part of current medical practice and research; however, their full potential is likely still to be realized. It is obvious that the use of biomarkers greatly aids in diagnostic and prognostic processes, as well as in the discovery and development of new pharmaceutical approaches by furnishing surrogate endpoints. Although several biomarkers are already established in cardiovascular medicine, the development and evaluation of new biomarkers, in concert with technological advancements, constitutes a critical step in enhancing future medical and research applications. These developments usher us into an exciting era in which specific biomarkers, or biomarker combinations, will be used to understand, identify and predict pathologies with earlier, more specific and more sensitive results.

B. Biomarkers: Definition, Types and Clinical Use

A biological marker (biomarker) is defined by the NIH Biomarkers Definitions Working Group as “a biological substance, characteristic, or image that provides an indication of the biological state of an organism” (1). Therefore, biomarkers must be determined objectively, and should be considered as indicators of physiologic or pathologic biological processes, including responses to therapeutic interventions. A similar definition was also recently given for genomic biomarkers in the Note for Guidance ICH E15 (2). Biomarkers can thus be quantifiable biological parameters (e.g., specific enzyme or hormone concentrations, specific genetic phenotypes, the presence of biological substances) that serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, environmental exposure and its associated effects, disease diagnosis, metabolic processes, substance abuse, pregnancy, cell line development, epidemiologic studies, etc.

Several types of biomarkers can be distinguished according to the nature of information attained or the method of determination. For example, biomarkers may be classified as diagnostic, predictive (identifying patients likely to respond to a given therapy or having a particular safety profile), prognostic (identifying patients more likely to have specific course of disease), or as markers of efficacy and toxicity. Furthermore, these biomarkers can provide indications related to a variety of health or disease characteristics, including the level or type of exposure to an environmental factor, genetic susceptibility, genetic responses to exposures, markers of subclinical or clinical disease, or indicators of response to therapy. Biomarkers may also serve as surrogate endpoints for clinical endpoints by predicting clinical benefit (or harm, or lack of benefit/harm) on the basis of epidemiologic, therapeutic, pathophysiologic, or other scientific evidence. Distinctions may also be made on the method of analysis; biomarkers can be assessed in biological samples such as blood, urine, or tissues, directly obtained from a person, e.g. blood pressure or ECG, or determined from an imaging test, such as an echocardiogram or a CT scan.

In clinical settings, biomarkers are used in a variety of approaches. In clinical practice, biomarkers are used to identify risk for disease, diagnose disease and its severity, guide intervention strategies, and monitor patient responses to therapy. In clinical research, biomarkers may predict whether a drug or other intervention is safe and effective in a shorter time and at lower cost than clinical endpoints such as morbidity and mortality, and may thus contribute to reduce the size and duration of clinical trials.

C. Biomarker Development

A good biomarker must have high sensitivity and high specificity for the outcome, and is expected to identify and explain a reasonable proportion of the outcome independent of established predictors. For instance, in primary cardiovascular disease risk prediction, a marker should provide incremental information over and above existing algorithms, such as the Framingham risk score (3).

A new biomarker will be of clinical value only if it meets the following criteria:

• a) it is accurate, i.e. it has the ability to identify individuals at risk
• b) it is reliable, i.e. of the same results are obtained when repeated
• c) it provides a therapeutic impact by allowing early intervention or improved outcomes
• d) it is acceptable by the patients
• e) it is easy to interpret by clinicians

The process of biomarker discovery and validation has been well described in the field of cancer research (Table 1). In the first step, new target biomarkers are identified, or recognized biomarkers are refined, in a preclinical phase using standardized technology platforms. In a second step, selected candidates are characterized and validated in a clinical setting involving individuals with and without disease. Next, retrospective repository studies are used to determine how the biomarker deviates in case subjects compared with control subjects, and the information is used to establish a threshold for positive screening results. In a fourth step, prospective screening studies are applied to large cohorts. Finally, the biomarker is validated as a disease control tool in randomized controlled trials (4).

Understanding the basics of statistics is critical for each of steps of biomarker development. Relative risk indicators, such as odds ratios or risk ratios, are the parameters most frequently reported to characterize a biomarker. These indicators measure the strength of association between a measurement and an outcome, but do not provide direct information as to whether a biomarker affects risk prediction. This is because the distribution of biomarker levels in cases and controls typically overlap substantially even when risk ratios are high, such that no cut-off value can achieve both high sensitivity and high specificity.

The ideal biomarker would have both perfect sensitivity and specificity. However, in practice, the increase of one comes at the expense of the other. The ability to differentiate between cases and controls is referred to as discrimination, which can be measured with the c-statistic, defined as the area under the receiver operating characteristic (ROC) curve. The ROC curve, a plot of sensitivity vs. 1-specificity (false-positive rate), offers a visual summary across all possible threshold values. The c-statistic, therefore, captures the trade-off between sensitivity and specificity of a prediction model into one statistic. It represents the probability that in a random case–control pair, the model will assign a higher predicted value to the case. Thus, the c-statistic ranges from 0.5 (no better than random guessing) to 1 (perfect discrimination) (5).

So far, with the exception of CRP, the development of biomarkers for cardiovascular disease risk prevention has been limited to the first three steps described in Table 1.

As described previously, the value of individual biomarkers may be limited. Conversely, combining them into a ‘multimarker’ score that enhances predictive value may make sense, especially if the biomarkers concern different (non-related) pathophysiological pathways. Practically, however, this approach has had only modest success in the few large studies that have examined this strategy (6).

D. Biomarkers in Cardiovascular Medicine

Cardiovascular disease is a field in which biomarkers have been extensively evaluated, especially circulating and imaging markers. Serum-based biomarkers such as the cardiac enzymes CK-MB and troponins, have been essential to the advancement of cardiology over the past half-century. With progressively increasing knowledge about their role in the pathophysiology of cardiovascular diseases, their utility has expanded from merely aiding in the diagnosis of diseases to being important in predicting risks and prognosis. Novel cardiovascular biomarkers continue to be evaluated, along with new lines of investigation, including genomic and metabolomic markers, which hold the potential for even greater insights into cardiovascular diseases and their treatment.

Biomarkers in cardiovascular disease are aimed at enhancing the ability of the clinician to provide optimal patient management. For example, among patients with chronic or atypical chest pain, biomarkers (chest pain, ECG changes) may facilitate identification of those with chest pain of ischemic etiology (angina) especially when combined with the use of treadmill stress testing or dobutamine stress echocardiography. In a patient presenting with acute severe chest pain (suspected acute coronary syndrome), biomarkers may help to differentiate patients with an acute myocardial infarction from those with unstable angina (e.g., troponin I or T), acute pulmonary embolism (e.g., D-dimer or ventilation perfusion scan), or an aortic dissection (e.g., transesophageal echocardiogram), thereby facilitating targeted management. In a patient with an established acute myocardial infarction, biomarkers may help to assess the following: necessity for therapeutic action (e.g., ECG ST-segment elevation indicating need for thrombolysis); extent of myocardial damage (e.g., troponin); severity of underlying coronary disease (e.g., coronary angiography); degree of left ventricular dysfunction (e.g., echocardiography); risk of future recurrence (e.g., exercise stress test); and progression to heart failure (e.g., B-type natriuretic peptide (BNP)).

The American College of Cardiology Foundation and the American Heart Association (ACCF/AHA) recently released guidelines on the use of existing markers (6). Table 2 provides an overview of selected cardiovascular biomarkers currently under investigation. Despite the large number of studies examining a host of candidate biomarkers, a class I recommendation, the highest possible level, was granted only for the assessment of family history of cardiovascular disease. Key biomarkers, such as C-reactive protein (CRP) and blood natriuretic protein (BNP), have been shown, in general, to improve discrimination and reclassification only modestly: approximately 0.02 increment in the c-statistic and 3% to 5% net reclassification improvement (NRI).

Since the publication of the 2010 ACCF/AHA guidelines, newer circulating biomarkers have been evaluated, including troponins (TnI and TnT). High-sensitivity troponin (hs-TnT) was detectable in up to one-quarter of middle-aged men and women (7). Increasing levels of circulating hs-TnT correlated with increases in cardiovascular mortality. Addition of this marker to a traditional risk factor model improved the c-statistic by about 0.04.

Several biomarkers have demonstrated potential utility in cardiovascular medicine (Table 2; (8)). However, heterogeneous methods for their evaluation, unclear associations with therapeutic implications, and the value added to natriuretic peptides limit the widespread application of these novel tests. Ultimately, however, it is possible to envision the use of biologically “orthogonal” markers such as NT-proBNP (stress), sST2 (myocardial fibrosis/remodeling), highly sensitive troponin (myocardial injury), MR-proADM (hemodynamic stress), copeptin (salt/water derangement), and renal biomarkers to provide a wide palette of biological information regarding the past, present, and future clinical state of patients suffering from heart failure. Thus, individualized therapeutic strategies developed from the use of such biomarkers may allow for a more personalized, biologically driven approach to heart failure care.

Today, troponins are considered the serum protein biomarkers of choice for monitoring potential drug induced myocardial injury. Troponins are highly sensitive indicators of myocardial injury and increase, when measured in its diagnostic window, is proportional to the extent of myocardial injury. They are detected as early, if not earlier, in the course of pathogenesis than other biomarkers of myocardial injury. The commercially available assays for cTnI and cTNT are simple, accurate, reproducible and inexpensive. Monitoring serum troponins can be useful when included in nonclinical studies to assess the potential for drug-induced myocardial injury (9).

E. Regulatory Considerations

Regulatory health authorities are increasingly aware of the benefits of biomarkers and how they may be used for drug approval, clinical trial design, and clinical care. The discovery and integration of new biomarkers in drug development, including genetic and genomic markers, and their appropriate use in clinical practice are encouraged by regulatory authorities. To provide assistance in their use and to clarify regulatory consequences, the FDA issued a Guidance for Industry: Pharmacogenomic Data Submissions in 2007 (10).

Obviously, biomarkers, either existing or new, must be qualified for a specific purpose prior to use in drug development and regulation. For this purpose, the FDA has set up a so-called biomarker qualification process that takes an exploratory biomarker through a series of scientific review processes (11). Similarly, the European Committee for Medicinal Products for Human Use (CHMP) can issue an opinion on the acceptability of a specific application of a method, such as the use of a novel methodology or an imaging method in the context of research and development. This qualification procedure should also be considered for the co-development of biomarker assays in the development of medicines. European EMA has also concluded a joint qualification process for biomarkers together with the FDA.

F. Conclusions

Biomarkers, defined as alterations in the constituents of tissues or body fluids that correlate with a specific diseases, provide powerful approaches to understanding the spectrum of cardiovascular disease with applications in at least 5 areas: screening, diagnosis, prognostics, therapeutic monitoring and prediction of recurrence. Advances in functional genomics, proteomics, metabolomics, and bioinformatics have revolutionized unbiased inquiries into numerous putative markers that may be informative with regard to the various stages of atherogenesis including overt cardiovascular disease and its sequelae. A prerequisite for the clinical use of biomarkers is elucidation of the specific indications, standardization of analytical methods, characterization of analytical features, assessment of performance characteristics, incremental yield with respect to different markers for a given clinical indication, and demonstration of cost-effectiveness. Technological advances will likely facilitate the use of multimarker profiling to individualize treatment of cardiovascular disease in the future.

References

1. Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001 Mar;69(3):89-95
2. ICH Topic E15. Definitions for genomic biomarkers, pharmacogenomics, pharmacogenetics, genomic data and sample coding categories. EMEA/CHMP/ICH/437986/2006, November 2007
3. Manolio T. Novel risk markers and clinical practice. N Engl J Med 2003; 349: 1587-9
4. Pepe MS, Etzioni R, Feng Z, Potter JD, Thompson ML, Thornquist M, Winget M, Yasui Y. Phases of biomarker development for early detection of cancer. J Natl Cancer Inst. 2001 Jul 18;93(14):1054-61
5. Ge Y, Wang TJ. Identifying novel biomarkers for cardiovascular disease risk prediction. J Int Med 2012, 272; 430-439
6. Greenland P, Alpert JS, Beller GA, et al. ACCF/AHA Guideline for Assessment of Cardiovascular Risk in Asymptomatic Adults. A Report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation 2010; 122; e584-636
7. de Lemos JA, Drazner MH, Omland T et al. Association of troponin T detected with a highly sensitive assay and cardiac structure and mortality risk in the general population. JAMA 2010; 304: 2503–12.
8. Van Kimmenade RRJ, Januzzi JL. Emerging Biomarkers in Heart Failure. Clin Chem 2012: 58: 127-138
9. FDA/NCSS Cardiotoxicity EWG August 2002
10. Guidance for Industry: Pharmacogenomic Data Submissions –Companion Guidance Draft Guidance 2007
11. Goodsaid F, Fruh F. Biomarker qualification pilot process for biomarker qualification at the FDA. Drug Discov. Today Technol 2007,;4(1): 9-11