OBJECTIVES: IBIS-1 was a pilot study undertaken to correlate coronary imaging with circulating biomarker expression in patients with stable angina, unstable angina and acute myocardial infarction. We hypothesized that patients at high risk of future events could be identified in the future by a combination of high risk plaque features by plaque echogenicity and palpography and a set of circulating blood biomarkers. RESULTS AND METHODS: We assessed the expression of conventional biomarkers and novel marker protein microarray (170 analytes) over 6 months. There were no strong correlations observed between conventional biomarkers and coronary imaging in non-culprit artery. Proteomic microarray was performed in 66 patients. Seventy eight (45%) analytes showed dynamic changes over time. Using hierarchical clustering and principal component analysis two subsets of biomarkers were identified: initial up-regulation and decrease over time (D-dimer, hepatocyte growth factor, CXCL9/MIG, platelet factor 4/CXCL4, CTACK, C-6 Kine, follistatin, and FGF-7) and the opposite increase (PAI-1- anti-apoptotic protein and I-309--chemokine induced on the human endothelium by Lp(a)). CONCLUSIONS: Proteomic analysis identifies dynamic patterns in circulating biomarkers in a wide range of patients with coronary artery disease. Further large natural history studies are needed to better define multibiomarker sets for identification of patients at risk of future CV events.
OBJECTIVES: IBIS-1 was a pilot study undertaken to correlate coronary imaging with circulating biomarker expression in patients with stable angina, unstable angina and acute myocardial infarction. We hypothesized that patients at high risk of future events could be identified in the future by a combination of high risk plaque features by plaque echogenicity and palpography and a set of circulating blood biomarkers. RESULTS AND METHODS: We assessed the expression of conventional biomarkers and novel marker protein microarray (170 analytes) over 6 months. There were no strong correlations observed between conventional biomarkers and coronary imaging in non-culprit artery. Proteomic microarray was performed in 66 patients. Seventy eight (45%) analytes showed dynamic changes over time. Using hierarchical clustering and principal component analysis two subsets of biomarkers were identified: initial up-regulation and decrease over time (D-dimer, hepatocyte growth factor, CXCL9/MIG, platelet factor 4/CXCL4, CTACK, C-6 Kine, follistatin, and FGF-7) and the opposite increase (PAI-1- anti-apoptotic protein and I-309--chemokine induced on the human endothelium by Lp(a)). CONCLUSIONS: Proteomic analysis identifies dynamic patterns in circulating biomarkers in a wide range of patients with coronary artery disease. Further large natural history studies are needed to better define multibiomarker sets for identification of patients at risk of future CV events.