Plasma fingerprinting with GC-MS in acute coronary syndrome

Abstract

New biomarkers of cardiovascular disease are needed to augment the information obtained from traditional indicators and to illuminate disease mechanisms. One of the approaches used in metabolomics/metabonomics for that purpose is metabolic fingerprinting aiming to profile large numbers of chemically diverse metabolites in an essentially nonselective way. In this study, gas chromatography-mass spectrometry was employed to evaluate the major metabolic changes in low molecular weight plasma metabolites of patients with acute coronary syndrome (n = 9) and with stable atherosclerosis (n = 10) vs healthy subjects without significant differences in age and sex (n = 10). Reproducible differences between cases and controls were obtained with pattern recognition techniques, and metabolites accounting for higher weight in the classification have been identified through their mass spectra. On this basis, it seems inherently plausible that even a simple metabolite profile might be able to offer improved clinical diagnosis and prognosis, but in addition, specific markers are being identified.

Evaluation of automated sample preparation, retention time locked gas chromatography–mass spectrometry and data analysis methods for the metabolomic study of Arabidopsis species

“…Gas chromatography combined with mass spectrometry (GC-MS) is suitable for the analysis of small molecules such as amino acids, amines, sugars, organic acids, fatty acids, and sterols, in metabolomic studies [1][2][3][4][5][6][7][8][9][10]. For the analysis of these polar molecules, derivatisation is however needed and, to this, oximation combined with silylation is often selected [11,12].…”

Metabotype Concept: Flexibility, Usefulness and Meaning in Different Biological Populations

“…In patients suffering from non-ST-segment elevation acute coronary syndrome, plasma samples showed decrease in citric acid, 4-hydroxyproline, aspartic acid and fructose versus increase in lactate, urea, glucose and valine, compared to control healthy subjects (Vallejo et al, 2009). …”

Mass Spectrometry for Metabolomics

“…The main advantage of this approach is that annotation of the analytical data is not required, and therefore data analysis is quick and relatively simple. There are numerous examples in the literature utilizing fingerprinting techniques using a variety of analytical approaches such as NMR spectroscopy [15][16][17], infrared (IR) and Raman spectroscopy [18][19][20][21], and CE-MS [22,23], atmospheric pressure desorption-MS [24], direct injection [25][26][27][28], lC-MS [29][30][31][32], and gC-MS [33][34][35].…”