Search

A new analytical strategy for biomarker recovery from directly coupled ultra-performance liquid chromatography time-of-flight mass spectrometry (UPLC Tof MS) data on biofluids is presented and exemplified using a study on hydrazine-induced liver toxicity. A key step in the strategy involves a novel procedure for reducing the spectroscopic search space by differential analysis of cohorts of normal and pathological samples using an orthogonal projection to latent structures discriminant analysis (O-PLS-DA). This efficiently sorts principal discriminators of toxicity from the background of thousands of metabolic features commonly observed in data sets generated by UPLC-MS analysis of biological fluids and is thus a powerful tool for biomarker discovery.

The renal Fanconi syndrome is a defect of proximal tubular function causing amino- aciduria and low-molecular-weight proteinuria. Dent's disease and Lowe syndrome are defined X-linked forms of Fanconi syndrome; there is also an autosomal dominant idiopathic form (ADIF), phenotypically similar to Dent's disease though its gene defect is still unknown. To assess whether their respective gene products are ultimately involved in a common reabsorptive pathway for proteins and low-molecular-mass endogenous metabolites, we compared renal Fanconi urinary proteomes and metabonomes with normal (control) urine using mass spectrometry and ¹H-NMR spectroscopy, respectively. Urine from patients with low-molecular-weight proteinuria secondary to ifosfamide treatment (tubular proteinuria; TP) was also analyzed for comparison. All four of the disorders studied had characteristic proteomic and metabonomic profiles. Uromodulin was the most abundant protein in normal urine, whereas Fanconi urine was dominated by albumin. ¹H-NMR spectroscopic data showed differences in the metabolic profiles of Fanconi urine vs. normal urine, due mainly to aminoaciduria. There were differences in the urinary metabolite and protein compositions between the three genetic forms of Fanconi syndrome: cluster analysis grouped the Lowe and Dent's urinary proteomes and metabonomes together, whereas ADIF and TP clustered together separately. Our findings demonstrate a distinctive "polypeptide and metabolite fingerprint" that can characterize the renal Fanconi syndrome; they also suggest that more subtle and cause-specific differences may exist between the different forms of Fanconi syndrome that might provide novel insights into the underlying mechanisms and cellular pathways affected. [ABSTRACT FROM AUTHOR]