NMR-based metabolic profiling identifies biomarkers of liver regeneration following partial hepatectomy in the rat.

Tissue injury and repair are often overlapping consequences of disease or toxic exposure, but are not often considered as distinct processes in molecular studies. To establish the systemic metabolic response to liver regeneration, the partial hepatectomy (PH) model has been studied in the rat by an integrated metabonomics strategy, utilizing (1)H NMR spectroscopy of urine, liver and serum. Male Sprague-Dawley rats were subjected to either surgical removal of approximately two-thirds of the liver, sham operated (SO) surgery, or no treatment (n = 10/group) and samples collected over a 7 day period. A number of urinary metabolic perturbations were observed in PH rats compared with SO and control animals, including elevated levels of taurine, hypotaurine, creatine, guanidinoacetic acid, betaine, dimethylglycine and bile acids. Serum betaine and creatine were also elevated after PH, while levels of triglyceride were reduced. In the liver, triglycerides, cholesterol, alanine and betaine were elevated after PH, while choline and its derivatives were reduced. Upon examining the dynamic pattern of urinary response (the 'metabolic trajectory'), several metabolites could be categorized into groups likely to reflect perturbations to different processes such as dietary intake or hepatic 1-carbon metabolism. Several of the urinary perturbations observed during the regenerative phase of the PH model have also been observed after exposure to liver toxins, indicating that hepatic regeneration may make a contribution to the systemic alterations in metabolism associated with hepatotoxicity. The observed changes in 1-carbon and lipid metabolism are consistent with the proposed role of these pathways in the activation of a regenerative response and provide further evidence regarding the utility of urinary NMR profiles in the detection of liver-specific pathology. Biofluid (1)H NMR-based metabolic profiling provides new insight into the role of metabolism of liver regeneration, and suggests putative biomarkers for the noninvasive monitoring of the regeneration process.

Prediction and classification of drug toxicity using probabilistic modeling of temporal metabolic data: the consortium on metabonomic toxicology screening approach.

Detection and classification of in vivo drug toxicity is an expensive and time-consuming process. Metabolic profiling is becoming a key enabling tool in this area as it provides a unique perspective on the characterization and mechanisms of response to toxic insult. As part of the Consortium on Metabonomic Toxicology (COMET) project, a substantial metabolic and pathological database was constructed. We chose a set of 80 treatments to build a modeling system for toxicity prediction using NMR spectroscopy of urine samples (n=12935) from laboratory rats (n=1652). The compound structures and activities were diverse but there was an emphasis on the selection of hepato and nephrotoxins. We developed a two-stage strategy based on the assumptions that (a) adverse effects would produce metabolic profiles deviating from those of normal animals and (b) such deviations would be similar for treatments having similar physiological effects. To address the first stage, we developed a multivariate model of normal urine, using principal components analysis of specially preprocessed 1H NMR spectra. The model demonstrated a high correspondence between the occurrence of toxicity and abnormal metabolic profiles. In the second stage, we extended a density estimation method, "CLOUDS", to compute multidimensional similarities between treatments. Crucially, the technique allowed a distribution-free estimate of similarity across multiple animals and time points for each treatment and the resulting matrix of similarities showed segregation between liver toxins and other treatments. Using the similarity matrix, we were able to correctly identify the target organ of two "blind" treatments, even at sub-toxic levels. To further validate the approach, we then applied a leave-one-out approach to predict the main organ of toxicity (liver or kidney) showing significant responses using the three most similar matches in the matrix. Where predictions could be made, there was an error rate of 8%. The sensitivities to liver and kidney toxicity were 67 and 41%, respectively, whereas the corresponding specificities were 77 and 100%. In some cases, it was not possible to make predictions because of interference by drug-related metabolite signals (18%), an inconsistent histopathological or urinary response (11%), genuine class overlap (8%), or lack of similarity to any other treatment (2%). This study constitutes the largest validation to date of the metabonomic approach to preclinical toxicology assessment, confirming that the methodology offers practical utility for rapid in vivo drug toxicity screening.

Short-chain aliphatic amines in human urine: a mathematical examination of metabolic interrelationships.

The relationships between several small molecular weight aliphatic amines (methylamine, dimethylamine, trimethylamine, and ethylamine) and an associated N-oxide (trimethylamine N-oxide) quantified in human urine collected from 203 healthy volunteers have been assessed mathematically. Principal component analysis highlighted a female subgroup with raised trimethylamine levels and the possibility of hormonal influence on the N-oxidation of trimethylamine has been proposed. A second subgroup of men, who ate a large meal of fish before the study, displayed raised levels of all compounds except ethylamine. In all cases, ethylamine was least significantly correlated with the other urinary components and appeared metabolically unrelated.

Exploration of the direct metabolic effects of mercury II chloride on the kidney of Sprague-Dawley rats using high-resolution magic angle spinning 1H NMR spectroscopy of intact tissue and pattern recognition.

Mercury II chloride (HgCl2) toxicity was investigated in Sprague-Dawley rats using high-resolution magic angle spinning (HRMAS) 1H NMR spectroscopy in conjunction with principal component analysis (PCA). Intact renal cortex and papilla samples from Sprague-Dawley rats treated with HgCl2 at two dose levels (0.5 and 2 mg/kg) and from matched controls (n=5 per group) were assessed at 48 h p.d. HgCl2) caused depletion of renal osmolytes such as glycerophosphocholine (GPC), betaine, trimethylamine N-oxide (TMAO), myo-inositol and taurine in both the renal cortex and the papilla. In addition, relatively higher concentrations of valine, isobutyrate, threonine and glutamate were observed in HgCl2-treated rats, particularly in the renal cortex, which may reflect a counterbalance response to the observed loss of other classes of renal osmolytes. Increased levels of glutamate were present in the cortex of treated rats, which may be associated with HgCl2-induced renal acidosis and disruption of the tricarboxylic acid cycle. A dose response was observed in both cortical and papillary tissue with increasing severity of metabolic disruption in the high dose group. 1H HRMAS NMR profiles of individual animals correlated well with conventional clinical chemistry and histology confirming the reproducibility of the technology and generating complementary molecular pathway information.

Comparative metabonomics of differential hydrazine toxicity in the rat and mouse.

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 beta-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.

Integrated metabonomic analysis of the multiorgan effects of hydrazine toxicity in the rat.

Hydrazine is a model toxin that induces both hepatotoxic and neurotoxic effects in experimental animals. The direct biochemical effects of hydrazine in kidney, liver, and brain tissue were assessed in male Sprague-Dawley rats using magic angle spinning nuclear magnetic resonance (NMR) spectroscopy. A single dose of hydrazine (90 mg/kg) resulted in changes to the biochemical composition of the liver after 24 h including an increase in triglycerides and beta-alanine, together with a decrease in hepatic glycogen, glucose, choline, taurine, and trimethylamine-N-oxide (TMAO). From histopathology measurements of liver tissue, minimal to mild hepatocyte alteration was observed in all animals at 24 h. The NMR spectra of the renal cortex at 24 h after dosing were dominated by a marked increase in the tissue concentration of 2-aminoadipate (2-AA) and beta-alanine, concomitant with depletions in TMAO, myo-inositol, choline, taurine, glutamate, and lysine. No alteration to the NMR spectral profile of the substantia nigra was observed after hydrazine administration, but perturbations to the relative concentrations of creatine, aspartate, myo-inositol, and N-acetyl aspartate were apparent in the hippocampus of hydrazine-treated animals at 24 h postdose. No overt signs of histopathological toxicity were observed in either the kidney or the brain regions examined. Elevated alanine levels were observed in all tissues indicative of a general inhibition of alanine transaminase activity. By 168 h postdose, NMR spectral profiles of treated rats appeared similar to those of matched controls for all tissue types indicative of recovery from toxic insult.

NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition.

Strategies such as genomics, proteomics and metabonomics are being applied with increasing frequency in the pharmaceutical industry. For each of these approaches, toxicological response can be measured by terms of deviation from control or baseline status. However, in order to accurately define drug-induced response, it is necessary to characterize the normal degree of physiological variation in the absence of stimuli. Here, 1H NMR spectroscopic-based analyses of the metabolic composition of urine in experimental animals under various normal physiological conditions are reviewed. In particular, the effects of inter-animal and diurnal variation, gender, age, diet, species, strain, hormonal status and stress on the biochemical composition of urine are explored. Pattern recognition methods facilitate the comparison of urine NMR spectra over a given time-course, enabling the establishment of changes in profile and highlighting the dynamic metabolic status of an organism. Thus metabonomic approaches based on information-rich spectroscopic data sets can be used to evaluate normal physiological variation and for investigation of drug safety issues.

Metabonomics technologies and their applications in physiological monitoring, drug safety assessment and disease diagnosis.

In this review, metabonomics, a combination of data-rich analytical chemical measurements and chemometrics for profiling metabolism in complex systems, is described and its applications are reviewed. Metabonomics is typically carried out using biofluids or tissue samples. The relevance of the technique is reviewed in relation to other '-omics', and it is shown how the methods can be applied to physiological evaluation, drug safety assessment, characterization of genetically modified animal models of disease, diagnosis of human disease, and drug therapy monitoring. The different types of analytical data, mainly from nuclear magnetic resonance spectroscopy and mass spectrometry, are summarized. The outputs from a metabonomics study allow sample classification, for example according to phenotype, drug safety or disease diagnosis, and interpretation of the reasons for classification yields information on combination biomarkers of effect. Transcriptomic and metabonomic data is currently being further integrated into a holistic understanding of systems biology. An assessment of the possible future role and impact of metabonomics is presented.

Geometric trajectory analysis of metabolic responses to toxicity can define treatment specific profiles.

Metabonomics can be viewed as the process of defining multivariate metabolic trajectories that describe the systemic response of organisms to physiological perturbations through time. We have explored the hypothesis that the homothetic geometry of a metabolic trajectory, i.e., the metabolic response irrespective of baseline values and overall magnitude, defines the mode of response of the organism to treatment and is hence the key property when considering the similarity between two sets of measurements. A modeling strategy to test for homothetic geometry, called scaled-to-maximum, aligned, and reduced trajectories (SMART) analysis, is presented that together with principal components analysis (PCA) facilitates the visualization of multivariate response similarity and hence the interpretation of metabonomic data. Several examples of the utility of this approach from toxicological studies are presented as follows: interlaboratory variation in hydrazine response, CCl(4) dose-response relationships, and interspecies comparison of bromobenzene toxicity. In each case, the homothetic trajectories hypothesis is shown to be an important concept for the successful multivariate modeling and interpretation of systemic metabolic change. Overall, geometric trajectory analysis based on a homothetic modeling strategy like SMART facilitates the amalgamation and comparison of metabonomic data sets and can improve the accuracy and precision of classification models based on metabolic profile data. Because interlaboratory variation, normal physiological variation, dose-response relationships, and interspecies differences are also key areas of concern in genomic and proteomic as well as metabonomic studies, the methods presented here may also have an impact on many other multilaboratory efforts to produce screenable "-omics" databases useful for gauging toxicity in safety assessment and drug discovery.

Spectral editing and pattern recognition methods applied to high-resolution magic-angle spinning 1H nuclear magnetic resonance spectroscopy of liver tissues.

Principal component analysis (PCA) has been applied to three nuclear magnetic resonance (NMR) spectral editing methods, namely, the Carr-Purcell-Meiboom-Gill spin-echo, diffusion editing, and skyline projection of a two-dimensional J-resolved spectrum, obtained from high-resolution magic-angle spinning NMR spectroscopy of liver tissues, to distinguish between control and hydrazine-treated rats. The effects of the toxin on rat liver biochemistry were directly observed and characterized by depleted levels of liver glycogen, choline, taurine, trimethylamine N-oxide, and glucose and by elevated levels of lipids and alanine. The highly unsaturated omega-3-type fatty acid was observed for the first time in hydrazine-treated rat liver. The contributions of the metabolites to the separation of control from dosed liver tissues varied depending on the type of spectral editing method used. We have shown that subtle changes in the metabolic profiles can be selectively amplified using a metabonomics approach based on the different NMR spectral editing techniques in conjunction with PCA.

Contemporary issues in toxicology the role of metabonomics in toxicology and its evaluation by the COMET project.

The role that metabonomics has in the evaluation of xenobiotic toxicity studies is presented here together with a brief summary of published studies. To provide a comprehensive assessment of this approach, the Consortium for Metabonomic Toxicology (COMET) has been formed between six pharmaceutical companies and Imperial College of Science, Technology and Medicine (IC), London, UK. The objective of this group is to define methodologies and to apply metabonomic data generated using (1)H NMR spectroscopy of urine and blood serum for preclinical toxicological screening of candidate drugs. This is being achieved by generating databases of results for a wide range of model toxins which serve as the raw material for computer-based expert systems for toxicity prediction. The project progress on the generation of comprehensive metabonomic databases and multivariate statistical models for prediction of toxicity, initially for liver and kidney toxicity in the rat and mouse, is reported. Additionally, both the analytical and biological variation which might arise through the use of metabonomics has been evaluated. An evaluation of intersite NMR analytical reproducibility has revealed a high degree of robustness. Second, a detailed comparison has been made of the ability of the six companies to provide consistent urine and serum samples using a study of the toxicity of hydrazine at two doses in the male rat, this study showing a high degree of consistency between samples from the various companies in terms of spectral patterns and biochemical composition. Differences between samples from the various companies were small compared to the biochemical effects of the toxin. A metabonomic model has been constructed for urine from control rats, enabling identification of outlier samples and the metabolic reasons for the deviation. Building on this success, and with the completion of studies on approximately 80 model toxins, first expert systems for prediction of liver and kidney toxicity have been generated.

Metabolic profiling of the effects of D-galactosamine in liver spheroids using (1)H NMR and MAS-NMR spectroscopy.

We report here the combined application of (1)H magic angle spinning (MAS) and high-resolution NMR spectroscopy and pattern recognition methods to study the effects of a model toxin (D-galactosamine) in liver spheroid cultures. (1)H NMR spectra of metabolic profiles of spheroids showed closer similarities to intact liver spectra than those of isolated hepatocytes, suggesting their superiority as an in vitro model system. Batches of spheroids were prepared from male Sprague Dawley rat livers and incubated in control hepatocyte medium or medium containing D-galactosamine (4 or 20 mM) for 4 or 24 h. Intact spheroids were packed into rotors and analyzed using MAS-NMR spectroscopy or homogenized and analyzed using conventional (1)H NMR spectroscopy. Principal components analysis, (PCA), of the NMR data revealed separation of control and D-galactosamine-treated spheroids based on changes in the concentrations of the triglycerides and elevations in cholesterol and esters. The absence of cholesterol in hepatocytes and the relative under-representation of the lipid resonances offer an important advantage of spheroids over hepatocytes for the (1)H NMR studies of fatty liver. Orthogonal signal correction (OSC) was used as a data filter to remove non-dose-dependent variation from the NMR spectra, improving the classification of treated spheroids and controls. This work shows that useful metabolic information can be obtained on drug toxicity by the use of combined MAS-NMR and high-resolution NMR of liver spheroids and that such studies may enhance the validation of in vitro techniques against in vivo models for metabolic profiling.

Analytical reproducibility in (1)H NMR-based metabonomic urinalysis.

Metabonomic analysis of biofluids and tissues utilizing high-resolution NMR spectroscopy and chemometric techniques has proven valuable in characterizing the biochemical response to toxicity for many xenobiotics. To assess the analytical reproducibility of metabonomic protocols, sample preparation and NMR data acquisition were performed at two sites (one using a 500 MHz and the other using a 600 MHz system) using two identical (split) sets of urine samples from an 8-day acute study of hydrazine toxicity in the rat. Despite the difference in spectrometer operating frequency, both datasets were extremely similar when analyzed using principal components analysis (PCA) and gave near-identical descriptions of the metabolic responses to hydrazine treatment. The main consistent difference between the datasets was related to the efficiency of water resonance suppression in the spectra. In a 4-PC model of both datasets combined, describing all systematic dose- and time-related variation (88% of the total variation), differences between the two datasets accounted for only 3% of the total modeled variance compared to ca. 15% for normal physiological (pre-dose) variation. Furthermore, <3% of spectra displayed distinct inter-site differences, and these were clearly identified as outliers in their respective dose-group PCA models. No samples produced clear outliers in both datasets, suggesting that the outliers observed did not reflect an unusual sample composition, but rather sporadic differences in sample preparation leading to, for example, very dilute samples. Estimations of the relative concentrations of citrate, hippurate, and taurine were in >95% correlation (r(2)) between sites, with an analytical error comparable to normal physiological variation in concentration (4-8%). The excellent analytical reproducibility and robustness of metabonomic techniques demonstrated here are highly competitive compared to the best proteomic analyses and are in significant contrast to genomic microarray platforms, both of which are complementary techniques for predictive and mechanistic toxicology. These results have implications for the quantitative interpretation of metabonomic data, and the establishment of quality control criteria for both regulatory agencies and for integrating data obtained at different sites.