Despite advances in the management of heart disease, cardiovascular (CV) disease remains the leading cause of death. While a lot of effort has been dedicated to the treatment of diagnosed disease, there is increasing focus on screening biomarkers capable of differentiating at-risk individuals to better target preventive therapy. While discovery of novel CV biomarkers, including genetic markers, has garnered attention in recent years, to date proof of clinical utility lags. Biomarker Discovery CV biomarkers have been identified for a number of cardiac conditions including acute coronary syndrome, coronary artery disease (CAD), congestive heart failure (HF), and myocardial infarction (MI). Use of diagnostic biomarkers in patients with symptoms of disease is well-established clinically. But other than for cholesterol, screening biomarkers to assess future CV disease risk has not taken hold in routine practice. “The primary prevention of cardiovascular disease relies on the ability to identify at-risk individuals long before the development of overt events,” writes Thomas Wang, M.D., in a biomarker review piece published in the October 2012 issue of the Journal of Internal Medicine. “In the past decade, research into circulating, genetic, and imaging biomarkers to augment traditional methods of risk prediction has only achieved modest success.” In the 2010 American College of Cardiology Foundation and the American Heart Association guidelines on the use of existing markers, the group only recommended six circulating markers. While newer circulating biomarkers have been evaluated since that publication, leading candidates including C-reactive protein (CRP) and B-type natriuretic peptide (BNP) have only shown the ability to modestly improve discrimination and reclassification, Wang explained. He says that some have turned their hopes to multimarker combinations or scores, but there have only been a few large studies and they too have only had moderate success. Traditional risk factors (cigarette smoking, diabetes, high cholesterol, and hypertension) do not identify all individuals who will develop CV disease, and the current prevention strategy of lifestyle changes, lipid panel testing, and lipid-lowering drug therapy constitute the predominant prevention strategy for managing CV disease risk. In a meta-analysis published in Lancet in 2005 that included more than 90,000 patients from 14 randomized trials of statins, results showed that lipid-lowering therapy only reduced CV events by 21 percent. Some Promising Studies There are signs though that continued biomarker discovery efforts may be paying off. At the recent American College of Cardiology (ACC) Annual Scientific Session & Expo (March 9-11; San Francisco) there were a number of studies presenting evidence that efforts to use novel risk markers to improve identification of at-risk individuals for targeted preventive treatment may be working. Among the studies presented was the five-year STOP-HF study, which enrolled 1,374 asymptomatic patients (age 40 years and older) with risk factors for HF. Participants were randomized into either the control group, which received standard care, or the intervention group, which was screened at least annually for CV risks and blood level BNP. BNP is a hormone that indicates how well the heart is functioning. The researchers found that significantly fewer patients in the intervention group had new-onset HF requiring hospitalization or had left ventricular dysfunction. Additionally, intervention patients also had significantly lower rates of emergency hospitalization for major CV events, compared to the control group. “The results of this study indicated that use of BNP in the community may facilitate prevention strategies aimed at reducing heart failure, left ventricular dysfunction and cardiovascular events,” said co-author Kenneth McDonald, M.D., director of the Heart Failure Unit at St. Vincent’s University Hospital (Ireland), in a statement. “The STOP-HF project provides the first example of how a structured screening and intervention strategy can prevent heart failure.” Aside from identifying novel candidates, improvements in instrumentation technology may enable more sensitive exploration of established biomarkers. Such is the case with cardiac troponin I (cTnI). In another study presented at the ACC meeting, data showed that using a high-precision digital assay enabled the measurement of cTnI below traditional test measurements. With a highly sensitive assay, researchers from Brigham and Women’s Hospital (Boston) found that monitoring levels of cTnI over time can identify post-coronary syndrome patients who are at increased risk for future death from CV death or HF. Traditional tests can only measure cTnI levels above 30 pg/mL to 50 pg/mL. But using Singulex’s (Alameda, Calif.) digital single molecule counting “smart” enzyme-linked immunosorbent assay reader, the analytical measurement range is extended to 0.1 pg/mL. Serial measurements of cTnI levels taken in 2,664 patients with stable ischemic heart disease at 30 days and four months predicted likelihood of CV disease and death from heart failure at the two-year follow-up. Patients whose cTnI levels were elevated or newly rising above 9 pg/mL at four months experienced more than three times the rate of CV disease or death from heart failure within two years compared with those with low cTnI levels (below 9 pg/mL). The findings potentially expand the clinical applications of cTnI beyond diagnosing MI in acute-care settings due to improved sensitivity in testing. A previous study showed that patients with cTnI levels of 9 pg/mL or greater benefited from intensive statin therapy versus moderate dose therapy. Genetic Markers While hopes are high that incorporating genetic markers into CV disease risk profiling will ultimately improve identification of patients most likely to benefit from targeted preventive therapy, many clinicians don’t feel routine genetic screening for CV disease is ready yet. Routine genetic screening is unlikely until management is improved by genetic testing. Currently, they say, risk variants are less potent predictors of common CV disease, like CAD, compared with biomarkers. To date, 33 genetic variants of genomewide significance have been identified and replicated. However, these genetic variants have only been found to have modest to minimal risk effect, experts say. Based on an evidence report on the use of genomic profiling to assess risk for CV disease, the Evaluation of Genomic Applications in Practice and Prevention group (EGAPP; commissioned by the U.S. Centers for Disease Control and Prevention’s Office of Public Health Genomics) made the recommendation in 2010 that there was insufficient evidence to recommend testing in the general population for 58 variants (including 9p21) in 29 genes encompassed in eight available genomic tests. The group said the magnitude of any health benefit from use of any of the tests, either alone or combined, is negligible. “It is fair to say that the human genome turned out to be more complicated than people thought, and its clinical usefulness less than people thought,” says Doug Campos-Outcalt M.D., a member of the EGAPP group and chair of family, community, and preventive medicine at the University of Arizona College of Medicine, Phoenix. “The real problem is these genomic-based cardiovascular risk panels are not very predictive beyond common clinical factors—age, gender, family history, blood pressure, weight.” Among EGAPP’s unresolved questions related to the clinical utility of such tests are the biological mechanism underlying the most convincing marker’s (9p21) association with CVD, the level of risk that changes intervention, whether long-term disease outcomes will improve, how individuals ordering direct-to-consumer tests will understand and respond to test results and interact with the health care system, and whether testing will actually stimulate behavior change. “It is a tall order to develop a screening test accurate enough to identify those who will get disease in a low-risk population. The test performance characteristics have to be great,” Wang, who is now chief of cardiovascular medicine at Vanderbilt University (Nashville), tells DTTR. “It is useful to remember we are early in discovery. I still think there is reason for optimism, but it will take time.” Among those who are optimistic about the prospects that a genetic-based score can predict CV risk are researchers from CardioDx (Palo Alto, Calif.). The company has developed a gene expression score (GES) based on an algorithm incorporating 23 genes, age, and sex that delivers a score on a 1 to 40 scale. In a study published online Feb. 15 in Circulation: Cardiovascular Genetics, the gene expression score outperformed clinical factors and myocardial perfusion imaging in identifying CAD in symptomatic patients referred for nuclear imaging. In the multicenter study, of 431 patients, the researchers found that GES has high sensitivity and negative predictive value (NPV) for obstructive CAD, with an area under the curve of 0.79. The GES had a sensitivity, specificity, and NPV of 89 percent, 52 percent, and 96 percent respectively. Over six months of follow-up, 27 of 28 patients with adverse cardiovascular events or revascularization had GES scores higher than 15. The authors said the test is most suitable as a “rule-out” test, but 54 percent of patients had scores above 15. Gregory Thomas, M.D., lead author of the study, who is a paid consultant for CardioDx, tells DTTR he believes such a gene expression test is complimentary to existing diagnostic methods, like nuclear stress tests, and the combination of the two “may optimize diagnostic performance and utilization of health care resources.” He acknowledges though that widespread clinical utilization of new screening tests of CV risk will be a challenge. “Medicine changes very slowly. With guidelines it takes five years for predominate acceptance and 10 years for substantial acceptance,” says Thomas, who is medical director of the MemorialCare Heart and Vascular Institute at Long Beach Memorial Medical Center in Long Beach, Calif. “The challenge is physician comfort. They are very comfortable with a stress test developed 60 years ago. Labs can put their toe in the water with testing, but they must show each doctor. It is a stretch to understand how a blood test can show blockages.”

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