Chemometric Models for Toxicity Classification Based on NMR Spectra of Biofluids

1H NMR spectroscopic and pattern recognition (PR)-based methods were used to investigate the biochemical variability in urine obtained from control rats and from rats treated with a hydrazine (a model hepatotoxin) or HgCl2 (a model renal cortical toxin). The 600 MHz 1H NMR spectra of urine samples o...

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Bibliographic Details
Published in:Chemical research in toxicology 2000-06, Vol.13 (6), p.471-478
Main Authors: Holmes, Elaine, Nicholls, Andrew W, Lindon, John C, Connor, Susan C, Connelly, John C, Haselden, John N, Damment, Stephen J. P, Spraul, Manfred, Neidig, Peter, Nicholson, Jeremy K
Format: Article
Language:English
Subjects:
Animals
Biotransformation
Drug-Related Side Effects and Adverse Reactions - classification
Drug-Related Side Effects and Adverse Reactions - urine
Factor Analysis, Statistical
Hydrazines - chemistry
Hydrazines - toxicity
Hydrazines - urine
Kidney Cortex - drug effects
Kidney Cortex - pathology
Liver - drug effects
Liver - pathology
Magnetic Resonance Spectroscopy
Mercuric Chloride - chemistry
Mercuric Chloride - toxicity
Mercuric Chloride - urine
Models, Chemical
pattern recognition
Pattern Recognition, Automated
Rats
Rats, Sprague-Dawley
Rats, Wistar
Reproducibility of Results
Structure-Activity Relationship
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Summary:1H NMR spectroscopic and pattern recognition (PR)-based methods were used to investigate the biochemical variability in urine obtained from control rats and from rats treated with a hydrazine (a model hepatotoxin) or HgCl2 (a model renal cortical toxin). The 600 MHz 1H NMR spectra of urine samples obtained from vehicle- or toxin-treated Han-Wistar (HW) and Sprague-Dawley (SD) rats were acquired, and principal components analysis (PCA) and soft independent modeling of class analogy (SIMCA) analysis were used to investigate the 1H NMR spectral data. Variation and strain differences in the biochemical composition of control urine samples were assessed. Control urine 1H NMR spectra obtained from the two rat strains appeared visually similar. However, chemometric analysis of the control urine spectra indicated that HW rat urine contained relatively higher concentrations of lactate, acetate, and taurine and lower concentrations of hippurate than SD rat urine. Having established the extent of biochemical variation in the two populations of control rats, PCA was used to evaluate the metabolic effects of hydrazine and HgCl2 toxicity. Urinary biomarkers of each class of toxicity were elucidated from the PC loadings and included organic acids, amino acids, and sugars in the case of mercury, while levels of taurine, β-alanine, creatine, and 2-aminoadipate were elevated after hydrazine treatment. SIMCA analysis of the data was used to build predictive models (from a training set of 416 samples) for the classification of toxicity type and strain of rat, and the models were tested using an independent set of urine samples (n = 124). Using models constructed from the first three PCs, 98% of the test samples were correctly classified as originating from control, hydrazine-treated, or HgCl2-treated rats. Furthermore, this method was sensitive enough to predict the correct strain of the control samples for 79% of the data, based upon the class of best fit. Incorporation of these chemometric methods into automated NMR-based metabonomics analysis will enable on-line toxicological assessment of biofluids and will provide a tool for probing the mechanistic basis of organ toxicity.
ISSN:0893-228X
1520-5010
DOI:10.1021/tx990210t