Novel biomarker panel measuring endothelial injury identifies patients at risk of coronary artery syndrome and discordance with low-density lipoprotein cholesterol.

BACKGROUND: Individuals with no history of coronary artery disease can develop acute coronary syndrome (ACS), often in the absence of major risk factors including low-density lipoprotein cholesterol (LDL-C). We identified risk factors and biomarkers that can help identify those at discordantly high risk of ACS with normal LDL-C using a novel validated coronary artery disease predictive algorithm (CADPA) incorporating biomarkers of endothelial injury. METHODS: Five-year predicted ACS risk was calculated for 6392 persons using CADPA. Persons were classified as low (<3.5%), intermediate (3.5-<7.5%) or high (≥7.5%) CADPA risk and by LDL-C levels <130 mg/dL (low) and ≥130 mg/dL (high) and whether in the discordantly low LDL-C (but high CADPA risk) or high LDL-C (but low/intermediate CADPA risk) group. Multiple logistic regression identified risk factors and biomarkers that predicted discordance. RESULTS: 31% were classified as low (<3.5%), 27% at intermediate (3.5-<7.5%) and 42% were at high risk (≥7.5%). 28% of subjects were identified in the low LDL discordant risk group (LDL-C< 130 mg/dL but 5-year CADPA predicted risk ≥7.5%) and 19% in the high LDL discordant risk group (LDL-C ≥ 130 mg/dL but 5-year CADPA risk of <7.5%). Diabetes (odds ratio [OR], 2.84 [2.21-3.66]), male sex (OR, 2.83 [2.40-3.35]), family history (OR, 2.23 [1.88-2.64]) and active smoking (OR, 1.99 [1.50-2.62]) predicted low LDL risk discordance more than other risk factors (all P < 0.01). Increased serum soluble FAS, hemoglobin A1c and interleukin-16 were the biomarkers most independently associated with increased risk. CONCLUSIONS: Discordance between LDL-C levels and ACS risk is common. Males with diabetes and a family history of myocardial infarction who are actively smoking may be at highest risk of developing ACS despite controlled LDL-C. Future studies should examine whether using the CADPA can help identify individuals that could benefit from earlier targeting of risk factor modification for the prevention of ACS.

Usefulness of a Coronary Artery Disease Predictive Algorithm to Predict Global Risk for Cardiovascular Disease and Acute Coronary Syndrome.

Traditional global risk assessment for cardiovascular disease fails to identify a significant percentage of the population initially classified at low or intermediate risk of cardiovascular disease that are actually at high risk for acute coronary syndrome (ACS). We examined a coronary artery disease predictive algorithm (CADPA) that includes 9 biomarkers involved in the pathogenesis of atherosclerosis initiated by endothelial damage and repair (hepatocyte growth factor, soluble FAS, Fas ligand, eotaxin, cutaneous T cell-attracting chemokine, monocyte chemotactic protein-3, interleukin-16, hemoglobin A1c, high-density lipoprotein-cholesterol), in addition to age, gender, diabetes, and family history of myocardial infarction that more accurately predicts 5-year risk of ACS to identify the patient population at discordantly high risk. We found that 34% of patients at low risk by global risk assessment and 72% of patients at intermediate risk by global risk assessment were actually at discordantly high risk for ACS. This patient population was disproportionately male and older in age. The biomarkers (per standard deviation) that most predicted the odds (95% confidence levels) of discordance were interleukin-16 (2.59 [2.21 to 3.03]), Fas Ligand (0.50 [0.43 to 0.57]), hepatocyte growth factor (1.72 [1.50 to 1.98]), soluble FAS (2.19 [1.86 to 2.58]), cutaneous T cell-attracting chemokine (0.46 [0.40 to 0.53]), and eotaxin (1.78 [1.56 to 2.03]), in addition to age, HbA1c, low-density lipoprotein-cholesterol, and glycated hemoglobin. In conclusion, although future prospective study validation is needed to establish a causal relation between CADPA and cardiovascular events, our study defines a patient population considered low to intermediate risk by conventional clinical evaluation, but who is at discordantly high risk indicated by the endothelial injury serum biomarker algorithm CADPA and may benefit from further evaluation and medical management.

Clinical utility of a novel coronary heart disease risk-assessment test to further classify intermediate-risk patients.

BACKGROUND: Current coronary heart disease (CHD) risk assessments inadequately assess intermediate-risk patients, leaving many undertreated and vulnerable to heart attacks. A novel CHD risk-assessment (CHDRA) tool was developed for intermediate-risk stratification using biomarkers and established risk factors to significantly improve CHD risk discrimination. HYPOTHESIS: Physicians will change their treatment plan in response to more information about a patient's CHD risk level provided by the CHDRA test. METHODS: A Web-based survey of cardiology, internal medicine, family practice, and obstetrics/gynecology physicians (n = 206) was conducted to assess the CHDRA clinical impact. Each physician was shown 3 clinical vignettes representing community-based cohort participants randomly selected from 8 total vignettes. For each, the physicians assessed the individual's CHD risk and selected preferred therapies based on the individual's comorbidities, physical examination, and laboratory results. The individual's CHDRA score was then provided and the physicians were queried for changes to their initial treatment plans. RESULTS: After obtaining the CHDRA result, 70% of the physician responses indicated a change to the patient's treatment plan. The revised lipid-management plans agreed more often (74.6% of the time) with the current Adult Treatment Panel III guidelines than did the original plans (57.6% of the time). Most physicians (71.3%) agreed with the statement that the CHDRA result provided information that would impact their current treatment decisions. CONCLUSIONS: The CHDRA test provided additional information to which physicians responded by more often applying appropriate therapy and actions aligned with guidelines, thus demonstrating the clinical utility of the test.

Analytical performance validation of a coronary heart disease risk assessment multi-analyte proteomic test.

BACKGROUND: Coronary heart disease (CHD) remains prevalent despite efforts to improve CHD risk assessment. The authors developed a multi-analyte immunoassay-based CHD risk assessment (CHDRA) algorithm, clinically validated in a multicenter study, to improve CHDRA in intermediate risk individuals. OBJECTIVE: Clinical laboratory validation of the CHDRA biomarker assays' analytical performance. METHODS: Multiplexed immunoassay panels developed for the seven CHDRA assays were evaluated with donor sera in a clinical laboratory. Specificity, sensitivity, interfering substances and reproducibility of the CHDRA assays, along with the effects of pre-analytical specimen processing, were evaluated. RESULTS: Analytical measurements of the CHDRA panel proteins (CTACK, Eotaxin, Fas Ligand, HGF, IL-16, MCP-3 and sFas) exhibited acceptable accuracy (80 - 120%), cross-reactivity (< 1%), interference (< 30% at high concentrations of bilirubin, lipids, hemoglobin and HAMA), sensitivity and reproducibility (< 20% CV across multiple runs, operators and instruments). Recoveries from donor sera subjected to typical clinical laboratory pre-analytical conditions were within 80 - 120%. The pre-analytical variables did not substantively impact the CHDRA scores. CONCLUSIONS: The CHDRA panel analytical validation in a clinical laboratory meets or exceeds the specifications established during the clinical utility studies. Risk score reproducibility across multiple test scenarios suggests the assays are not susceptible to clinical laboratory pre-analytical and analytical variation.