A metabonomic strategy based on LC-MS was employed to investigate the metabolic profile of urine samples from 20 athletes who had been tested positive for corticoids and anabolic steroids and 29 controls. In this aim, different sample preparations and chromatographic conditions were compared. The acquired LC-MS data of doped athletes and controls were subjected to analysis of variance (ANOVA) and principal component analysis (PCA). Using this approach, molecular signature of human urine was obtained showing that metabonomics could be a complementary tool to discriminate different urinary profiles and to track down metabolic changes in humans.
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