| Abstract
| - Metabonomic analysis of biofluids and tissues utilizing high-resolution NMR spectroscopyand chemometric techniques has proven valuable in characterizing the biochemical responseto toxicity for many xenobiotics. To assess the analytical reproducibility of metabonomicprotocols, sample preparation and NMR data acquisition were performed at two sites (oneusing a 500 MHz and the other using a 600 MHz system) using two identical (split) sets ofurine samples from an 8-day acute study of hydrazine toxicity in the rat. Despite the differencein spectrometer operating frequency, both datasets were extremely similar when analyzed usingprincipal components analysis (PCA) and gave near-identical descriptions of the metabolicresponses to hydrazine treatment. The main consistent difference between the datasets wasrelated to the efficiency of water resonance suppression in the spectra. In a 4-PC model ofboth datasets combined, describing all systematic dose- and time-related variation (88% ofthe total variation), differences between the two datasets accounted for only 3% of the totalmodeled variance compared to ca. 15% for normal physiological (pre-dose) variation. Furthermore, <3% of spectra displayed distinct inter-site differences, and these were clearly identifiedas outliers in their respective dose-group PCA models. No samples produced clear outliers inboth datasets, suggesting that the outliers observed did not reflect an unusual samplecomposition, but rather sporadic differences in sample preparation leading to, for example,very dilute samples. Estimations of the relative concentrations of citrate, hippurate, and taurinewere in >95% correlation (r2) between sites, with an analytical error comparable to normalphysiological variation in concentration (4−8%). The excellent analytical reproducibility androbustness of metabonomic techniques demonstrated here are highly competitive compared tothe best proteomic analyses and are in significant contrast to genomic microarray platforms,both of which are complementary techniques for predictive and mechanistic toxicology. Theseresults have implications for the quantitative interpretation of metabonomic data, and theestablishment of quality control criteria for both regulatory agencies and for integrating dataobtained at different sites.
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