Abstract 16395: Metabolic Fingerprinting of Acute Coronary Syndrome Identifies Formate as a Biomarker
Clinical data, ECG and biomarkers, in particular troponins, have proven very useful in the diagnosis and risk stratification of ACS. However, the challenge of diagnosing myocardial ischemia in the everyday clinical setting remains. Available methods have suboptimal specificity. In this study we used NMR based metabolic fingerprinting in search of new biomarkers of ACS. Serum samples from a) patients diagnosed of ACS were obtained during the acute phase (n=48) and at 6 months (n=38), 15 Q wave AMI, 13 non Q wave AMI, 20 Unstable angina in the acute and 13 Q wave AMI, 12 non Q wave AMI and 13 unstable angina and b) patients with initially suspected ACS in whom this diagnosis was later ruled out (n=14). NMR spectra were obtained at 9,4T with a CPMG pulse sequence and pattern recognition analysis was performed on SIMCA-P software. 1H NMR spectra based metabolic fingerprinting was able to differentiate the acute phase of ACS from control or chronic phase ACS patients. Discriminant analysis showed that the most important metabolites in the discriminant model were relatively elevated lipid peaks at the acute phase and higher glucose in controls and at the chronic stage. When only the aromatic part of the spectra was used, the quality of the classification improved, and it was found that the peak corresponding to formic acid was responsible for the classification. Formate peak area was measured and was found to be different between acute phase of ACS and controls or chronic phase ACS (p < 10E-10); area under the ROC curve of 0,944 (p < 0,0001). In conclusion, 1H NMR based fingerprinting of serum samples is able to differentiate between acute and chronic phases of ACS. We have identified formic acid as a potential biomarker of ACS.
- © 2012 by American Heart Association, Inc.