Quantitative profiling of a large number of metabolic compounds is a promising method to detect biomarkers in inflammatory bowel diseases (IBD), such as ulcerative colitis (UC). We induced an experimental form of UC in mice by treatment with dextran sulfate sodium (DSS) and characterized 53 serum and 69 urine metabolites by use of (1)H NMR spectroscopy and quantitative ("targeted") analysis to distinguish between diseased and healthy animals. Hierarchical multivariate orthogonal partial least-squares (OPLS) models were developed to detect and predict separation of control and DSS-treated mice. DSS treatment resulted in weight loss, colonic inflammation, and increase in myeloperoxidase activity. Metabolomic patterns generated from the OPLS data clearly separated DSS-treated from control mice with a slightly higher predictive power (Q(2)) for serum (0.73) than urine (0.71). During DSS colitis, creatine, carnitine, and methylamines increased in urine while in serum, maximal increases were observed for ketone bodies, hypoxanthine, and tryptophan. Antioxidant metabolites decreased in urine whereas in serum, glucose and Krebs cycle intermediates decreased strongly. Quantitative metabolic profiling of serum and urine thus discriminates between healthy and DSS-treated mice. Analysis of serum or urine seems to be equally powerful for detecting experimental colitis, and a combined analysis offers only a minor improvement.