Screening of Biomarkers in Rat Urine Using LC/ Electrospray Ionization-MS and Two-Way Data Analysis Helena Idborg-Bjo 1 rkman, † Per-Olof Edlund, † Olav M. Kvalheim, ‡ Ina Schuppe-Koistinen, § and Sven P. Jacobsson* ,† Department of Analytical Chemistry, Stockholm University, SE-106 91 Stockholm, Sweden, Department of Chemistry, University of Bergen, NO-5007 Bergen, Norway, and Molecular Toxicology, Safety Assessment, AstraZeneca R&D, SE-151 85 So ¨ derta ¨ lje, Sweden Biofluids, like urine, form very complex matrixes contain- ing a large number of potential biomarkers, that is, changes of endogenous metabolites in response to xeno- biotic 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 citalo- pram 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 resolu- tion, and metabolic fingerprints were obtained. After peak alignment principal component analysis (PCA) was per- formed for pattern recognition, PCA loadings were studied as a means of discovering potential biomarkers. In this study a number of potential biomarkers of phospho- lipidosis 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 pro- posed method is a complement or an alternative to NMR for metabolomic applications. The use of biomarkers in toxicology is becoming increasingly important in assessing the health risks of exposure to potentially toxic drugs and chemicals. Biomarkers are used to measure effects on the catabolism after exposure of a toxic compound and the extent of a toxic response that should be easy to measure and quantify with high sensitivity and specificity, and they should furthermore relate to the biochemical mechanism of a compound. The ultimate biomarker should be species-independent and noninvasive and should predict a toxic effect at realistic doses. 1 There are high expectations that the use of molecular profiling methods such as genomics, proteomics, and metabolomics will improve risk assessment and the identification of biomarkers for drug effects and toxicity. 2 Using these techniques, the expression of thousands of genes, proteins, and endogenous metabolites can be investigated simultaneously following exposure to a toxic compound. The challenge for the toxicologist is to distinguish physiological effects, such as age, gender, diet, etc., and pharma- cological effects (induction, diuresis, renal xenobiotic clearance) from toxicity and to offer a valid interpretation of their meaning. In this study, drug-induced phospholipidosis is used as an example to illustrate the development of a method using LC/ MS and two-way analysis, that is, multivariate analysis, for biomarker identification. Phospholipidosis is a phospholipid storage disorder resulting in an excessive accumulation of phospholipids in the tissues and has been observed as a recurrent pathological feature in toxicity studies in both animals and humans. 3,4 To date, the determination of phospholipidosis has relied on the use of histopathology and electron microscopy or the examination of peripheral blood lymphocytes. 5 Accordingly, drug candidates causing phospholipidosis are in general identified at a late stage in drug development, and there is a great need to identify biomarkers for early identification of the insult. In this report, the antidepressant citalopram, a selective serotonin reuptake inhibitor, has been used as a model compound to induce phospholipidosis. Recently, the use of nuclear magnetic resonance (NMR) as an analytical technique in the screening of biomarkers has gained attention. NMR metabonomics and pattern recognition analysis have been used in several metabolic studies to identify potential biomarkers. 6 NMR has been proven to be a fast and information- rich technique, giving rise to very complex spectra that mainly have to be analyzed by multivariate methods. Owing to sensitivity reasons and the complexity of the data, the proportion of potential biomarkers that can be identified is limited. Thus, there is a need for alternative methods that can fulfill the aim of screening with high capacity and provide a means of identification. The use of † Stockholm University. ‡ University of Bergen. § AstraZeneca R&D So ¨ derta ¨ lje. (1) Timbrell, J. Toxicology 1998 , 129,1-12. (2) Hellmold, H.; Nilsson, C. B.; Schuppe-Koistinen, I.; Kenne, K.; Warngard, L. Toxicol. Lett. 2002 , 127, 239-243. (3) Kodavanti, U. P.; Mehendale, H. M. Pharmacol. Rev. 1990 , 42, 327-54. (4) Halliwell, H. Toxicol. Pathol. 1997 , 25, 53-60. (5) Luellmann, H.; Luellmann-Rauch, R.; Wassermann, O. Crit. Rev. Toxicol. 1975 , 4, 185-218. (6) Nicholls, A. W.; Nicholson, J. K.; Haselden, J. N.; Waterfield, C. J. Biomarkers 2000 , 5, 410-423. Anal. Chem. 2003, 75, 4784-4792 4784 Analytical Chemistry, Vol. 75, No. 18, September 15, 2003 10.1021/ac0341618 CCC: $25.00 © 2003 American Chemical Society Published on Web 08/20/2003