Key result
Novel mass spectrometry profiling detects metabolic alterations within ~10 minutes of myocardial infarction.
Cohort
MOTIVATION: The discovery of new and unexpected biomarkers in cardiovascular disease is a highly data-driven process that requires the complementary power of modern metabolite profiling technologies, bioinformatics and biostatistics. Clinical biomarkers of early myocardial injury are lacking. A prospective biomarker cohort study was carried out to identify, categorize and profile kinetic patterns of early metabolic biomarkers of planned myocardial infarction (PMI) and spontaneous (SMI) myocardial infarction. We applied a targeted mass spectrometry (MS)-based metabolite profiling platform to serial blood samples drawn from carefully phenotyped patients undergoing alcohol septal ablation for hypertrophic obstructive cardiomyopathy serving as a human model of PMI. Patients with SMI and patients undergoing catheterization without induction of myocardial infarction served as positive and negative controls to assess generalizability of markers identified in PMI. RESULTS: To identify metabolites of high predictive value in tandem mass spectrometry data, we introduced a new feature selection method for the categorization of metabolic signatures into three classes of weak, moderate and strong predictors, which can be easily applied to both paired and unpaired samples. Our paradigm outperformed standard null-hypothesis significance testing and other popular methods for feature selection in terms of the area under the receiver operating curve and the product of sensitivity and specificity. Our results emphasize that this new method was able to identify, classify and validate alterations of levels in multiple metabolites participating in pathways associated with myocardial injury as early as 10 min after PMI. AVAILABILITY: The algorithm as well as supplementary material is available for download at: www.umit.at/page.cfm?vpath=departments/technik/iebe/tools/bi
No takes yet. Share an insight, caveat, or question.
Baumgärtner et al. (2010) conducted a cohort in Myocardial injury (planned and spontaneous myocardial infarction) in hypertrophic obstructive cardiomyopathy. Targeted mass spectrometry-based metabolite profiling and new feature selection method vs. Standard null-hypothesis significance testing and other popular feature selection methods was evaluated on Identification, classification, and validation of early metabolic biomarker alterations (evaluated by area under the ROC curve and product of sensitivity and specificity). A new feature selection method for mass spectrometry metabolite profiling identified and validated metabolic alterations as early as 10 min after planned myocardial infarction.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: