Dietary composition has been shown to influence metabolism and to impact on the prevalence and risk for certain diseases, but hitherto, there have been no systematic studies on the effects of dietary modulation of human metabolic phenotype (metabotype). Here, we have applied 1H NMR spectroscopy in combination with multivariate statistical analysis to characterize the effects of three diets: "vegetarian", "low meat", and "high meat" on the metabotype signature of human participants. Twelve healthy male participants (age range of 25-74 years) consumed each of these diets, in a randomized order, for continuous 15-day-periods with an intervening washout period between each diet of 7 days duration. Each participant provided three consecutive 24-hour urine collections on days 13, 14, and 15 of each dietary period, and 1H NMR spectra were acquired on all samples. Pattern recognition analysis allowed differentiation of the characteristic metabolic signatures of the diets with creatine, carnitine, acetylcarnitine, and trimethylamine-N-oxide (TMAO) being elevated in the high-meat consumption period. Application of orthogonal projection to latent structure discriminant analysis (O-PLS-DA) allowed the low-meat diet and vegetarian diet signatures to be characterized, and p-hydroxyphenylacetate (a microbial mammalian cometabolite) was higher in the vegetarian than meat diet samples, signaling an alteration of the bacterial composition or metabolism in response to diet. This work shows the potential for the routine use of metabonomics in nutritional and epidemiological studies, in characterizing and predicting the metabolic effects and the influence of diet on human metabotypes.

1H NMR spectroscopy of urine combined with pattern recognition (PR) methods of data analysis has been used to investigate the time-related biochemical changes induced in Sprague-Dawley rats by three model hepatotoxins: alpha-naphthyl isothiocyanate (ANIT), d-(+)-galactosamine (GalN), and butylated hydroxytoluene (BHT). The development of hepatic lesions was monitored by conventional plasma analysis and liver histopathology. Urine was collected continuously postdosing up to 144 h and analyzed by 600-MHz 1H NMR spectroscopy. NMR spectra of the urine samples showed a number of time-dependent perturbations of endogenous metabolite levels that were characteristic for each hepatotoxin. Biochemical changes common to all three hepatotoxins included a reduction in the urinary excretion of citrate and 2-oxoglutarate and an increased excretion of taurine and creatine. Increased urinary excretion of betaine, urocanic acid, tyrosine, threonine, and glutamate was characteristic of GalN toxicity. Both GalN and ANIT caused increased urinary excretion of bile acids, while glycosuria was evident in BHT- and ANIT-treated rats. Data reduction of the NMR spectra into 256 integrated regions was used to further analyze the data. Mean values of each integrated region were analyzed by principal components analysis (PCA). Each toxin gave a unique time-related metabolic trajectory that could be visualized in two-dimensional PCA maps and in which the maximum distance from the control point corresponded to the time of greatest cellular injury (confirmed by conventional toxicological tests). Thereafter, the metabolic trajectories changed direction and moved back toward the control region of the PR map during the postdose recovery phase. The combination of urinary metabolites which were significantly altered at various time points allowed for differentiation between biliary and parenchymal injury. This NMR-PR approach to the noninvasive detection of liver lesions will be of value in furthering the understanding of hepatotoxic mechanisms and assisting in the discovery of novel biomarkers of hepatotoxicity.

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The biochemical effects of acute and chronic psychological stress have been investigated in male Sprague-Dawley rats using a combination of 1H NMR spectral analysis of plasma and conventional hematological analyses. Animals were subjected to 35 consecutive days of 6-h sessions of stress, and following a 9 day break, were stressed for a further 6-h period. Plasma samples were collected at 0, 1, 3, and 6 h on days 1, 9, 21, 35, and 44, measured using 600 MHz 1H NMR spectroscopy, and analyzed by Principal Components Analysis. Time-dependent biochemical effects of psychological stress on a range of endogenous metabolites were evident and were correlated with the intensity of the stress response as defined by corticosterone and hematological parameters. Following acute stress, increases in the levels of glucose and ketone bodies, and decreases in the levels of acetate, alanine, isoleucine, lactate, leucine, valine, and lipoproteins, were observed. Chronic stress-induced increases in plasma levels of alanine, lactate (day 9), and leucine, valine, and choline (day 44) and decreases in acetate (day 9) and lipoprotein concentrations were observed. Positive correlations between plasma corticosterone level and glucose and glycerol, and between plasma lipoprotein concentrations and hemoglobin levels, were established using Projection to Latent Structures (PLS) analysis. This study indicates the potential of using NMR-based metabonomic strategies for the characterization of endogenous metabolic perturbations induced by psychological stressors and lifestyle choices.

1H nuclear magnetic resonance (NMR)-based metabonomics is a well-established technique used to analyse and interpret complex multiparametric metabolic data, and has a wide number of applications in the development of pharmaceuticals. However, interpretation of biological data can be confounded by extraneous variation in the data such as fluctuations in either experimental conditions or in physiological status. Here we have shown the novel application of a data filtering method, orthogonal signal correction (OSC), to biofluid NMR data to minimise the influence of inter- and intra-spectrometer variation during data acquisition, and also to minimise innate physiological variation. The removal of orthogonal variation exposed features of interest in the NMR data and facilitated interpretation of the derived multivariate models. Furthermore, analysis of the orthogonal variation provided an explanation of the systematic analytical/biological changes responsible for confounding the original NMR data.

It has been shown extensively, that chemometric investigations of 1 H NMR spectra of rat urine taken from animals dosed with model toxins produce characteristic patterns of metabolic responses and that this permits the identification of biomarkers of toxic response and regeneration. To date, metabonomic methods have been mainly optimised for urine which contains mainly low molecular weight moieties, and thus a conventional 1-dimensional 1 H NMR pulse sequence is an efficient means of obtaining information-rich data. In the case of biofluids such as blood plasma or serum, which contain a wide range of macromolecules the resonances of which can overlap with peaks from small molecule metabolites, the information giving rise to sample classification can be concealed in a conventional NMR spectrum and this presents a different analytical challenge in terms of chemometric analysis of spectral profiles. Here, the use of other types of NMR data have been investigated and it is shown that by using spectra where the peak intensities are edited according to their molecular diffusion coefficients, it is possible to improve differentiation of control animals and those treated with the model hepatotoxin, a-naphthylisothiocyanate (ANIT). By using diffusion-edited spectroscopy, plasma lipid moieties are less attenuated than those from small endogenous metabolites and thus the toxin-induced changes to the lipoprotein profiles are more easily detectable.

The biochemical effects of a series of commonly used drug carrier vehicles were investigated using (1)H NMR spectroscopic and pattern recognition based metabonomic analysis. Animals were treated by oral gavage with six dosage vehicles: 0.5% (w/v) sodium carboxymethylcellulose/0.2% (v/v)tween; microemulsion (consisting of propylene glycol, ethanol, cremophor, and corn oil glycerides); labrafil [consisting of poly(ethylene glycol) 300 esterified with oleic acid] (30%)/corn oil (70%); 0.1 M sodium phosphate buffered water; poly(ethylene glycol) 300 and 0.5% methocel. Urine samples (n = 7) collected over a 96 h period post administration were analyzed using 600 MHz (1)H NMR spectroscopy, and principal components analysis of the spectral data was used to analyze these data. Of the six vehicles studied, three (labrafil/corn oil, PEG 300 and microemulsion) gave rise to strong vehicle-related signals in the (1)H NMR spectra of urine and were, therefore, deemed to be less suitable for NMR-based toxicity studies. To investigate any biochemical consequences of vehicle dosing, PCA was used to analyze spectral regions that did not contain vehicle-related signals, i.e., the NMR-detectable endogenous metabolite profile. PEG 300 and labrafil/corn oil induced changes in the biochemical composition of urine including increased concentrations of dicarboxylic acids, creatinine, taurine, and sugars, indicating that these vehicles were bioactive in their own right and that this might confound interpretation of biochemical effects of weakly toxic drugs dosed in these carriers. This study shows the importance of selecting appropriate vehicles for NMR-based metabonomic studies with a view to minimizing the possibility of vehicle resonances obscuring endogenous compound peaks. Furthermore, we have shown that at least two of the commonly used drug carrier vehicles caused metabolic perturbations in the urine profile. These alterations in the biochemical profile reflect vehicle-induced changes in the physiological status of the organism that may obscure the pharmacologic or toxicologic effects of drugs.