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Biofluids, like urine, form very complex matrixes containing a large number of potential biomarkers, that is, changes of endogenous metabolites in response to xenobiotic exposure. This paper describes a fast and sensitive method of screening biomarkers in rat urine. Biomarkers for phospholipidosis, induced by an antidepressant drug, were studied. Urine samples from rats exposed to citalopram were analyzed using solid-phase extraction (SPE) and liquid chromatography mass spectrometry (LC/MS) analysis detecting negative ions. A fast iterative method, called Gentle, was used for the automatic curve resolution, and metabolic fingerprints were obtained. After peak alignment principal component analysis (PCA) was performed for pattern recognition, PCA loadings were studied as a means of discovering potential biomarkers. In this study a number of potential biomarkers of phospholipidosis in rats are discussed. They are reported by their retention time and base peak, as their identification is not within the scope of the study. In addition to the fact that it was possible to differentiate control samples from dosed samples, the data were very easy to interpret, and signals from xenobiotic-related substances were easily removed without affecting the endogenous compounds. The proposed method is a complement or an alternative to NMR for metabolomic applications.
Idborg et al. (Wed,) studied this question.