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John C Lindon

Publications and source records attributed to John C Lindon.

At least 37 records · Page 2Linked to original sources
PubMed2005

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.

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.

3-Hydroxybutyric Acid↗
PubMed2005

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.

Algorithms↗
PubMed2005

The Consortium for Metabonomic Toxicology (COMET): aims, activities and achievements.

The utility of metabonomics in the evaluation of xenobiotic toxicity has been comprehensively assessed by the Consortium for Metabonomic Toxicology (COMET), formed between five major pharmaceutical companies and Imperial College London, UK. The main objectives were to assess methodologies, to generate a metabonomic database using (1)H nuclear magnetic resonance (NMR) spectroscopy of rodent urine and blood serum and to build a predictive expert system for target organ toxicity. The analytic and biologic variation that might arise through the use of metabonomics was evaluated and a high degree of robustness demonstrated. With the completion of 147 studies, the chief deliverables of a curated database of rodent biofluid NMR spectra and computer-based expert systems for the prediction of kidney or liver toxicity in rat and mouse based on the spectral data have been generated, and delivered to the sponsoring companies. The project, with its relatively modest resources, has met and exceeded all of its targets and was judged a resounding success by the sponsoring companies who are, in many cases, already enhancing and making use of the data in their in-house studies.

Animals↗
PubMed2004

Evaluation of metabolic variation in normal rat strains from a statistical analysis of 1H NMR spectra of urine.

NMR spectroscopic and statistical methods have been applied to investigate the biochemical variations within and between two phenotypically normal rat strains. The 600 MHz (1)H NMR spectra of urine were acquired as part of a series of drug toxicity studies from 450 control rat urine samples from each of two strains of laboratory rat (Han Wistar and Sprague Dawley). The spectra were data-reduced to 256 intensity descriptors over a range of delta 0.2-10.0. The spectral variation was analysed both within and between strains in terms of the mean, standard deviation, skewness and kurtosis of each descriptor. It is demonstrated that spectral intensities corresponding to a number of endogenous metabolites do not show Gaussian distributions and there is evidence for bimodality for some metabolites. Additionally, despite the visual similarity of the NMR spectra from the two strains of rat, the descriptor distributions and the statistics derived from them revealed differences in the metabolite profiles, which clearly distinguished the two populations. This work is of value in the determination of biochemical normality and variability, and thus can be used to investigate, and place confidence limits on the biochemical deviations, which arise as a consequence of genetic modification or pathophysiological events.

Animals↗
PubMed2004

Sample classification based on Bayesian spectral decomposition of metabonomic NMR data sets.

1H NMR spectra of biofluids provides a wealth of biochemical information on the metabolic status of an organism. Through the application of pattern recognition and classification algorithms, the data have been shown to provide information on disease diagnosis and the beneficial and adverse effects of potential therapeutics. Here, a novel approach is described for identifying subsets of spectral patterns in databases of NMR spectra, and it is shown that the intensities of these spectral patterns can be related to the onset and recovery from a toxic lesion in both a time-related and dose-related fashion. These patterns form a new type of combination biomarker for the biological effect under study. The approach is illustrated with a study of liver toxicity in rats using NMR spectra of urine following administration of a model hepatotoxin hydrazine.

Animals↗
PubMed2004

Probing molecular dynamics in chromatographic systems using high-resolution 1H magic-angle-spinning NMR spectroscopy: interaction between p-Xylene and C18-bonded silica.

The exact nature of the interaction between small molecules and chromatographic solid phases has been the subject of much research, but detailed understanding of the molecular dynamics in such systems remains elusive. High-resolution (1)H magic-angle-spinning (MAS) NMR spectroscopy has been applied to the investigation of C18-bonded silica material as used in chromatographic separation techniques together with an adsorbed model analyte, p-xylene. Two distinct p-xylene and water environments were identified within the C18-bonded silica through the measurement of (1)H NMR chemical shifts, T(1) and T(2) relaxation times and diffusion coefficients, including their temperature dependence. The results have been analyzed in terms of two environments, p-xylene within the C18 chains, in slow exchange on the NMR time scale with p-xylene in a more mobile state adsorbed as a layer in close proximity to the C18 particles, but which is distinct from free liquid p-xylene. The techniques used here could have more general applications, including the study of drug molecules bound into phospholipid membranes in micelles or vesicles.

Journal Article↗
PubMed2004

Integrated application of transcriptomics and metabonomics yields new insight into the toxicity due to paracetamol in the mouse.

Gene chip array (Affymetrix) data from liver tissue and high resolution 1H NMR spectra from intact liver tissue, tissue extracts and plasma have been analyzed to identify biochemical changes arising from hepatotoxicity in mice dosed with acetaminophen. These data sets have been co-interpreted in terms of common metabolic pathways. The principal metabolic changes comprised a decrease in hepatic glucose and glycogen in intact tissue, coupled with an increase in lipid content, with increases in the levels of glucose, pyruvate, acetate and lactate in plasma, and increases in alanine and lactate in the aqueous tissue extracts. Collectively these data provide evidence for an increased rate of hepatic glycolysis. The metabolic observations were consistent with the altered levels of gene expression relating to lipid and energy metabolism in liver which both preceded and were concurrent with the metabolic perturbations. The results show that these two technology platforms together offer a complementary view into cellular responses to toxic processes, providing new insight into the toxic consequences, even for well-studied therapeutic agents such as acetaminophen.

Acetaminophen↗
PubMed2004

Use of relaxation-edited one-dimensional and two dimensional nuclear magnetic resonance spectroscopy to improve detection of small metabolites in blood plasma.

The 1H nuclear magnetic resonance (NMR) spectra of biological samples, such as blood plasma and tissues, are information rich but data complex owing to superposition of the resonances from a multitude of different chemical entities in multiple-phase compartments, hampering detection and subsequent resonance assignments. To overcome these problems, several spectral-editing NMR experiments are described here, combining spin-relaxation filters (based on T(1), T(rho), and T(2)) with both one-dimensional and two-dimensional (2D) NMR spectroscopy. These techniques enable the separation of NMR resonances based on their relaxation times and allow simplification of the complex spectra. In this paper, the approach is exemplified using a control human blood plasma, which is a complex mixture of proteins, lipoproteins, and small-molecule metabolites. In the case of T(1rho)- and T(2)-edited 2D NMR experiments, a "flip-back" pulse was introduced after the relaxation editing to make the phase cycling of the "relaxation filter" and the 2D NMR part independent, thus enabling easy implementation of the phase-sensitive 2D NMR experiments. These methods also permit much higher receiver gains to be used to reduce digitization error, in particular, for the small resonances, which are sometimes vitally important for metabonomics studies. Both pulse sequences and experimental results are discussed for T(1)-, T(1rho)-, and T(2)-filtered COSY, T(2)-filtered phase-sensitive DQF-COSY, and T(1), T(1rho)-, and T(2)-filtered TOCSY NMR.

Blood Chemical Analysis↗
PubMed2004

Environmental metabonomics: applying combination biomarker analysis in earthworms at a metal contaminated site.

Earthworms were taken across an environmental gradient of metal contamination for ecotoxicology assessment. Both indigenous (Lumbricus rubellus and L. terrestris) and introduced earthworms (Eisenia andrei, exposed in mesh bags) were studied. Changes in the levels of small molecule metabolites in earthworm tissue extracts were analysed by 1H NMR spectroscopy as a means of identifying combination biomarker compounds. Principal components analysis of the NMR spectral data revealed that biochemical changes were induced across the metal contamination gradient. Native worms (L. rubellus) from the most polluted sites were associated with an increase in the relative concentration of maltose; a decrease was also seen in the concentration of an as yet unidentified biomarker compound. Introduced worms (E. andrei) did not show differences to the same extent. Direct integration of the resonances from histidine and 1-methylhistidine showed that relative histidine concentrations were elevated slightly for L. rubellus, confirming the results of earlier mesocosm studies. Conversely, the relative concentrations of both histidine and 1-methylhistidine were greatly reduced by metal contamination in L. terrestris. This study demonstrates the utility of NMR spectroscopy in detecting previously unknown potential biomarkers for ecotoxicity testing and identified maltose as a potential biomarker compound deserving of further study.

Animals↗
PubMed2004

Automatic alignment of individual peaks in large high-resolution spectral data sets.

Pattern recognition techniques are effective tools for reducing the information contained in large spectral data sets to a much smaller number of significant features which can then be used to make interpretations about the chemical or biochemical system under study. Often the effectiveness of such approaches is impeded by experimental and instrument induced variations in the position, phase, and line width of the spectral peaks. Although characterizing the cause and magnitude of these fluctuations could be important in its own right (pH-induced NMR chemical shift changes, for example) in general they obscure the process of pattern discovery. One major area of application is the use of large databases of (1)H NMR spectra of biofluids such as urine for investigating perturbations in metabolic profiles caused by drugs or disease, a process now termed metabonomics. Frequency shifts of individual peaks are the dominant source of such unwanted variations in this type of data. In this paper, an automatic procedure for aligning the individual peaks in the data set is described and evaluated. The proposed method will be vital for the efficient and automatic analysis of large metabonomic data sets and should also be applicable to other types of data.

Animals↗
PubMed2004

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.

Animals↗
PubMed2004

The challenges of modeling mammalian biocomplexity.

Understanding the relationships between human genetic factors, the risks of developing major diseases and the molecular basis of drug efficacy and toxicity is a fundamental problem in modern biology. Predicting biological outcomes on the basis of genomic data is a major challenge because of the interactions of specific genetic profiles with numerous environmental factors that may conditionally influence disease risks in a nonlinear fashion. 'Global' systems biology attempts to integrate multivariate biological information to better understand the interaction of genes with the environment. The measurement and modeling of such diverse information sets is difficult at the analytical and bioinformatic modeling levels. Highly complex animals such as humans can be considered 'superorganisms' with an internal ecosystem of diverse symbiotic microbiota and parasites that have interactive metabolic processes. We now need novel approaches to measure and model metabolic compartments in interacting cell types and genomes that are connected by cometabolic processes in symbiotic mammalian systems.

Animals↗
PubMed2004

Metabonomics and its role in drug development and disease diagnosis.

This article describes the new approach known as metabonomics, a combination of data-rich analytical chemistry and chemometrics for profiling metabolism in complex systems. Two main analytical approaches have been used, namely nuclear magnetic resonance spectroscopy and mass spectrometry, however, most literature on mammalian systems pertains to nuclear magnetic resonance spectroscopy. The technologies are reviewed in relation to other -omics, and how these methods can be applied to drug safety assessment, characterization of genetically modified animal models of disease, diagnosis of human disease and drug therapy monitoring is demonstrated.

Animals↗
PubMed2004

Metabonomics: systems biology in pharmaceutical research and development.

Metabonomics uses a combination of data-rich analytical chemical methods such as nuclear magnetic resonance spectroscopy and mass spectrometry together with chemometrics for profiling metabolism and interpreting metabolic fingerprints in complex biological systems. The methods have been applied in many areas of relevance to pharmaceutical research and development, including drug safety assessment, characterization of genetically modified animal models of disease, diagnosis of human disease, understanding physiological variation and drug therapy monitoring. As well as providing a novel means of sample classification and effect evaluation, the approach can lead to identification of combinations of biomarkers for those effects. These attributes mean that metabonomics will be integral in the drive towards personalized healthcare.

Animals↗
PubMed2003

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.

Alanine↗
PubMed2003

Hepatotoxin-induced hypercreatinaemia and hypercreatinuria: their relationship to one another, to liver damage and to weakened nutritional status.

Hypercreatinuria is a well-known feature of liver and testicular toxicity and we have recently proposed that hepatotoxin-induced hypercreatinuria would arise as a consequence of increased cysteine synthesis associated with the provision of protective substances (glutathione and/or taurine). Here a direct relationship between hepatotoxin-induced hypercreatinaemia and hypercreatinuria is shown and the possible relationships of hepatotoxin-induced hypercreatinaemia and hypercreatinuria to hepatic damage and to weakened nutritional status are examined. Male Sprague-Dawley rats were dosed with a variety of model hepatotoxins at two dose levels per toxin. Blood plasma samples taken at 24 h post-dosing and urine samples collected from 24-31 h post-dosing were analysed by (1)H NMR spectroscopy. Both hypercreatinaemia and hypercreatinuria were found in rats dosed with allyl formate (75 mg/kg), chlorpromazine (30 and 60 mg/kg), alpha-naphthylisothiocyanate (ANIT, 100 mg/kg) and thioacetamide (200 mg/kg), whilst significant hypercreatinuria, but not hypercreatinaemia, was found after dosing with thioacetamide (50 mg/kg). Neither hypercreatinaemia nor hypercreatinuria were found after dosing with allyl formate (25 mg/kg), ethionine (300 and 1000 mg/kg) or ANIT (30 mg/kg). Reduced feeding is known to cause hypercreatinuria in rats and, of the four hepatotoxins that induced hypercreatinaemia and hypercreatinuria at the given time-points, two, chlorpromazine and ANIT, also affected nutritional status with ketosis being clearly identifiable from the plasma (1)H NMR spectra. Thus, the creatine changes induced by ANIT and chlorpromazine are potentially attributable, in whole or in part, to reduced feeding rather than to liver effects alone and, consequently, the results were examined with and without inclusion of the ANIT and chlorpromazine data. With all of the data included, there were eight out of ten points of correspondence between the incidence of hypercreatinaemia and/or hypercreatinuria and the incidence of increases in plasma alanine aminotransferase (ALT) activity. At the same time there were nine out of ten points of correspondence between the incidence of hypercreatinaemia and/or hypercreatinuria and the incidence of increases in plasma aspartate aminotransferase (AST) activity. However, with the ANIT and chlorpromazine data excluded there was complete (six out of six points) correspondence between the incidence of hypercreatinaemia and/or hypercreatinuria and the incidence of increases in plasma AST and ALT in the remaining data. Likewise, with all of the data included, there was some apparent correlation (correlation coefficient, r=0.80) between the group mean levels of plasma AST and plasma creatine when expressed relative to the mean values for controls sampled at the same time-point. However, with the ANIT and chlorpromazine data excluded, that correlation coefficient was increased to 0.95. The findings of these studies suggest that the ANIT- and chlorpromazine-induced creatine changes may have been caused by reduced feeding rather than by liver toxicity. The allyl formate and thioacetamide data indicate that hepatocellular necrosis is accompanied by increases in plasma and urinary creatine, and suggest the possibility of a quantitative relationship between the increases in plasma AST and the increases in plasma creatine that are associated with hepatocellular necrosis. The ethionine and ANIT data suggest that fatty liver (steatosis) and cholestatic damage may not be associated with hypercreatinaemia and hypercreatinuria.

Administration, Oral↗