title: Comparative urine analysis by liquid chromatography-mass spectrometry and multivariate statistics: method development, evaluation, and application to proteinuria.
abstract: We describe a platform for the comparative profiling of urine using reversed-phase liquid chromatography-mass spectrometry (LC-MS) and multivariate statistical data analysis. Urinary compounds were separated by gradient elution and subsequently detected by electrospray Ion-Trap MS. The lower limit of detection (5.7-21 nmol/L), within-day (2.9-19%) and between-day (4.8-19%) analytical variation of peak areas, linearity (R2: 0.918-0.999), and standard deviation for retention time (<0.52 min) of the method were assessed by means of addition of seven 3-8 amino acid peptides (0-500 nmol/L). Relating the amount of injected urine to the area under the curve (AUC) of the chromatographic trace at 214 nm better reduced the coefficient of variation (CV) of the AUC of the total ion chromatogram (CV = 10.1%) than relating it to creatinine (CV = 38.4%). LC-MS data were processed, and the common peak matrix was analyzed by principal component analysis (PCA) after supervised classification by the nearest shrunken centroid algorithm. The feasibility of the method to discriminate urine samples of differing compositions was evaluated by (i) addition of seven peptides at nanomolar concentrations to blank urine samples of different origin and (ii) a study of urine from kidney patients with and without proteinuria. (i) The added peptides were ranked as highly discriminatory peaks despite significant biological variation. (ii) Ninety-two peaks were selected best discriminating proteinuric from nonproteinuric samples, of which 6 were more intense in the majority of the proteinuric samples. Two of these 6 peaks were identified as albumin-derived peptides, which is in accordance with the early rise of albumin during glomerular proteinuria. Interestingly, other albumin-derived peptides were nondiscriminatory indicating preferential proteolysis at some cleavage sites.
authors.affiliation: Department of Analytical Biochemistry, University Centre for Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV Groningen, The Netherlands.
authors.forename: Ramses F J
authors.initials: RF
authors.lastname: Kemperman
authors.forename: Peter L
authors.initials: PL
authors.lastname: Horvatovich
authors.forename: Berend
authors.initials: B
authors.lastname: Hoekman
authors.forename: Theo H
authors.initials: TH
authors.lastname: Reijmers
authors.forename: Frits A J
authors.initials: FA
authors.lastname: Muskiet
authors.forename: Rainer
authors.initials: R
authors.lastname: Bischoff
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D019540:Area Under Curve; D015415:Biomarkers / Q000378:metabolism; D002853:Chromatography, Liquid / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D007674:Kidney Diseases / Q000652:urine; D013058:Mass Spectrometry / Q000379:methods*; D008969:Molecular Sequence Data; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D011507:Proteinuria / Q000175:diagnosis* / Q000652:urine*; D012815:Signal Processing, Computer-Assisted; D016482:Urinalysis / Q000379:methods*
chemical_list: D015415:Biomarkers