| 1. |
- Bollard, Mary E, et al.
(författare)
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Comparative metabonomics of differential hydrazine toxicity in the rat and mouse
- 2005
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Ingår i: Toxicology and Applied Pharmacology. - : Elsevier BV. - 0041-008X. ; 204:2, s. 135-51
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Tidskriftsartikel (refereegranskat)abstract
- Interspecies variation between rats and mice has been studied for hydrazine toxicity using a novel metabonomics approach. Hydrazine hydrochloride was administered to male Sprague–Dawley rats (30 mg/kg, n = 10 and 90 mg/kg, n = 10) and male B6C3F mice (100 mg/kg, n = 8 and 250 mg/kg, n = 8) by oral gavage. In each species, the high dose was selected to produce the major histopathologic effect, hepatocellular lipid accumulation. Urine samples were collected at sequential time points up to 168 h post dose and analyzed by 1H NMR spectroscopy. The metabolites of hydrazine, namely diacetyl hydrazine and 1,4,5,6-tetrahydro-6-oxo-3-pyridazine carboxylic acid (THOPC), were detected in both the rat and mouse urine samples. Monoacetyl hydrazine was detected only in urine samples from the rat and its absence in the urine of the mouse was attributed to a higher activity of N-acetyl transferases in the mouse compared with the rat. Differential metabolic effects observed between the two species included elevated urinary β-alanine, 3-d-hydroxybutyrate, citrulline, N-acetylcitrulline, and reduced trimethylamine-N-oxide excretion unique to the rat. Metabolic principal component (PC) trajectories highlighted the greater degree of toxic response in the rat. A data scaling method, scaled to maximum aligned and reduced trajectories (SMART) analysis, was used to remove the differences between the metabolic starting positions of the rat and mouse and varying magnitudes of effect, to facilitate comparison of the response geometries between the rat and mouse. Mice followed “biphasic” open PC trajectories, with incomplete recovery 7 days after dosing, whereas rats followed closed “hairpin” time profiles, indicating functional reversibility. The greater magnitude of metabolic effects observed in the rat was supported by the more pronounced effect on liver pathology in the rat when compared with the mouse.
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| 2. |
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| 3. |
- Clayton, T. Andrew, et al.
(författare)
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Pharmaco-metabonomic phenotyping and personalized drug treatment.
- 2006
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Ingår i: Nature. - 1476-4687. ; 440:7087, s. 1073-7
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Tidskriftsartikel (refereegranskat)abstract
- There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.
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| 4. |
- Cloarec, Olivier, et al.
(författare)
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Evaluation of the Orthogonal Projection on Latent Structure Model Limitations Caused by Chemical Shift Variability and Improved Visualization of Biomarker Changes in 1H NMR Spectroscopic Metabonomic Studies
- 2005
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Ingår i: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 77:2, s. 517-26
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Tidskriftsartikel (refereegranskat)abstract
- In general, applications of metabonomics using biofluid NMR spectroscopic analysis for probing abnormal biochemical profiles in disease or due to toxicity have all relied on the use of chemometric techniques for sample classification. However, the well-known variability of some chemical shifts in 1H NMR spectra of biofluids due to environmental differences such as pH variation, when coupled with the large number of variables in such spectra, has led to the situation where it is necessary to reduce the size of the spectra or to attempt to align the shifting peaks, to get more robust and interpretable chemometric models. Here, a new approach that avoids this problem is demonstrated and shows that, moreover, inclusion of variable peak position data can be beneficial and can lead to useful biochemical information. The interpretation of chemometric models using combined back-scaled loading plots and variable weights demonstrates that this peak position variation can be handled successfully and also often provides additional information on the physicochemical variations in metabonomic data sets.
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| 5. |
- Cloarec, Olivier, et al.
(författare)
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Statistical Total Correlation Spectroscopy: An Exploratory Approach for Latent Biomarker Identification from Metabolic 1H NMR Data Sets
- 2005
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Ingår i: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 77:5, s. 1282-89
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Tidskriftsartikel (refereegranskat)abstract
- We describe here the implementation of the statistical total correlation spectroscopy (STOCSY) analysis method for aiding the identification of potential biomarker molecules in metabonomic studies based on NMR spectroscopic data. STOCSY takes advantage of the multicollinearity of the intensity variables in a set of spectra (in this case 1H NMR spectra) to generate a pseudo-two-dimensional NMR spectrum that displays the correlation among the intensities of the various peaks across the whole sample. This method is not limited to the usual connectivities that are deducible from more standard two-dimensional NMR spectroscopic methods, such as TOCSY. Moreover, two or more molecules involved in the same pathway can also present high intermolecular correlations because of biological covariance or can even be anticorrelated. This combination of STOCSY with supervised pattern recognition and particularly orthogonal projection on latent structure-discriminant analysis (O-PLS-DA) offers a new powerful framework for analysis of metabonomic data. In a first step O-PLS-DA extracts the part of NMR spectra related to discrimination. This information is then cross-combined with the STOCSY results to help identify the molecules responsible for the metabolic variation. To illustrate the applicability of the method, it has been applied to 1H NMR spectra of urine from a metabonomic study of a model of insulin resistance based on the administration of a carbohydrate diet to three different mice strains (C57BL/6Oxjr, BALB/cOxjr, and 129S6/SvEvOxjr) in which a series of metabolites of biological importance can be conclusively assigned and identified by use of the STOCSY approach.
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