Metabonomic Study of Ochratoxin A Toxicity in Rats after Repeated Administration: Phenotypic Anchoring Enhances the Ability for Biomarker Discovery

Abstract

For early detection of toxicity and improved mechanistic understanding, GC/MS-, 1H NMR-, and LC/MS-based metabonomics were applied to urine samples from a rodent toxicity study on the mycotoxin and renal carcinogen ochratoxin A (OTA). OTA was administered at doses of 0, 21, 70, and 210 microg/kg body wt for up to 90 days. Urine samples were collected at 24 h intervals 14, 28, and 90 days after the start of treatment and analyzed with GC/MS, 1H NMR, and LC/MS. Principal component analysis and orthogonal projection to latent structures discriminate analysis (OPLS-DA) based on GC/MS and 1H NMR data discriminated controls from animals dosed with 210 microg/kg body wt OTA as early as 14 days and animals dosed with 70 microg/kg body wt 28 days after the start of treatment, correlating with mild histopathological changes in the kidney. Integration of histopathology scores as discriminators in OPLS-DA models resulted in better multivariate model predictivity and facilitated marker identification. Decreased 2-oxoglutarate and citrate excretion and increased glucose, creatinine, pseudouridine, 5-oxoproline, and myo-inositol excretion were detected with GC/MS. Decreased 2-oxoglutarate and citrate excretion and increased amino acid excretion were found with 1H NMR. Increased urinary glucose is a well-established indicator of kidney damage, and altered excretion of TCA cycle intermediates (citrate and 2-oxoglutarate) is found as a general response to toxic insult in many metabonomics studies. Other markers are associated with cell proliferation (pseudouridine), changes in renal osmolyte handling (myo-inositol), and oxidative stress (5-oxoproline), established mechanisms of OTA toxicity. LC/MS was also able to discriminate controls and treated animals but contained more noise, and marker annotation was only speculative due to lack of reference databases. Use of multiple analytical platforms for metabonomics analysis may result in a more comprehensive metabolite coverage and may be applied to obtain mechanistic information from conventional rodent toxicity studies.