Brian C. Sweatman

A metabolomic study of the CRND8 transgenic mouse model of Alzheimer's disease.

Alzheimers disease is the most common neurodegenerative disease of the central nervous system characterized by a progressive loss in memory and deterioration of cognitive functions. In this study the transgenic mouse TgCRND8, which encodes a mutant form of the amyloid precursor protein 695 with both the Swedish and Indiana mutations and develops extracellular amyloid beta-peptide deposits as early as 2-3 months, was investigated. Extract from eight brain regions (cortex, frontal cortex, cerebellum, hippocampus, olfactory bulb, pons, midbrain and striatum) were studied using (1)H NMR spectroscopy. Analysis of the NMR spectra discriminated control from APP695 tissues in hippocampus, cortex, frontal cortex, midbrain and cerebellum, with hippocampal and cortical region being most affected. The analysis of the corresponding loading plots for these brain regions indicated a decrease in N-acetyl-L-aspartate, glutamate, glutamine, taurine (exception hippocampus), gamma-amino butyric acid, choline and phosphocholine (combined resonances), creatine, phosphocreatine and succinate in hippocampus, cortex, frontal cortex (exception gamma-amino butyric acid) and midbrain of affected animals. An increase in lactate, aspartate, glycine (except in midbrain) and other amino acids including alanine (exception frontal cortex), leucine, iso-leucine, valine and water soluble free fatty acids (0.8-0.9 and 1.2-1.3 ppm) were observed in the TgCRND8 mice. Our findings demonstrate that the perturbations in metabolism are more widespread and include the cerebellum and midbrain. Furthermore, metabolic perturbations are associated with a wide range of metabolites which could improve the diagnosis and monitoring of the progression of Alzheimers disease.

Effects of feeding and body weight loss on the 1H-NMR-based urine metabolic profiles of male Wistar Han Rats: Implications for biomarker discovery

For almost two decades, 1H-NMR spectroscopy has been used as an ‘open’ system to study the temporal changes in the biochemical composition of biofluids, including urine, in response to adverse toxic events. Many of these in vivo studies have reported changes in individual metabolites and patterns of metabolites that correlated with toxicological changes. However, many of the proposed novel biomarkers are common to a number of different types of toxicity. These may therefore reflect non-specific effects of toxicity, such as weight loss, rather than a specific pathology. A study was carried out to investigate the non-specific effects on urinary metabolite profiles by administering four hepatotoxic compounds, as a single dose, to rats at two dose levels: hydrazine hydrate (0.06 or 0.08 g kg−1), 1,2-dimethylhydrazine (0.1 or 0.3 g kg−1), α-napthylisothiocyanate (0.1 or 0.15 g kg−1) and carbon tetrachloride (1.58 or 3.16 g kg−1). The study included weight-matched control animals along with those that were dosed, which were then ‘pair-fed’ with the treated animals so they achieved a similar weight loss. The urinary metabolite profiles were investigated over time using 1H-NMR spectroscopy and compared with the pathology from the same animals. The temporal changes were analysed statistically using multivariate statistical data analysis including principal component analysis, partial least squares, parallel factor analysis and Fishers criteria. A number of metabolites associated with energy metabolism or which are partially dietary in origin, such as creatine, creatinine, tricarboxylic acid (TCA) cycle intermediates, phenylacetylglycine, fumarate, glucose, taurine, fatty acids and N-methylnicotinamide, showed altered levels in the urine of treated and pair-fed animals. Many of these changes correlated well with weight loss. Interestingly, there was no increase in ketone bodies (acetate and β-hydroxybutyrate), which might be expected if energy metabolism was switched from glycolysis to fatty acid β-oxidation. In some instances, the metabolites that changed were considered to be non-specific markers of toxicity, but were also identified as markers of a specific type of toxicity. For example, taurine was raised significantly in carbon tetrachloride-treated animals but reduced in the pair-fed group. However, raised urinary bile acid levels were only seen after α-napthylisothiocyanate treatment. The methodology, statistical analysis used and the data generated will help improve the identification of specific markers or patterns of urinary markers of specific toxic effects.

Automatic reduction of NMR spectroscopic data for statistical and pattern recognition classification of samples

A general method of automatically reducing NMR spectra to provide numerical descriptors of samples has been developed and investigated. These descriptors can be used as input to pattern recognition or multivariate algorithms for sample classification. The methods have been tested using 600 MHz one-dimensional 1H NMR spectra of biofluids which are complex mixtures. The approach is, in principle, applicable to multidimensional and heteronuclear NMR spectra and to other types of liquid samples such as oils and foodstuffs as well as to situations such as 1H or 31P NMR in vivo and solid state NMR in drug formulation analysis. The method relies upon apportioning the information in the spectra to individual contiguous segments and allowing specified regions of the spectra to be omitted. Three approaches, based on the number of peaks, the summed peak heights and the summed peak areas respectively in each segment, have been tested. The effect of segment width and overlap and the effects of manipulation of the NMR spectra have been evaluated in terms of the classification of the samples using principal components analysis. A simple method of generating NMR based spectral descriptors for object classification is thus proposed.

600 MHz 1H-NMR spectroscopy of human cerebrospinal fluid: Effects of sample manipulation and assignment of resonances

Extensive assignments of resonances in the 600 MHz 1H-NMR spectra of cerebrospinal fluid are reported. These have been achieved by the measurement of a combination of two-dimensional experiments comprising homonuclear J-resolved, COSY45, and double-quantum filtered COSY (DQCOSY) spectra. By these means the previous total of 18 endogenous metabolites, of which in general only selected resonances have been assigned, has been augmented to 46 molecules including all of the resonances of both alpha- and beta-anomers of glucose. With only a few exceptions all resonances have been assigned for all of the metabolites. In addition, the effect of freeze-drying on the 600 MHz 1H-NMR spectrum of human cerebrospinal fluid (CSF) is presented using both lyophilization with reconstitution into either H2O or D2O. Freeze-drying and reconstitution into H2O causes a significant sharpening of many small molecule resonances, including notably those of glutamate and glutamine as well as other amino acids and in addition causes the loss of volatile components, principally acetone. Further exchange of the H2O solvent by D2O causes no additional changes in the spectra.

Peak alignment of urine NMR spectra using fuzzy warping.

Proton nuclear magnetic resonance (1H NMR) spectroscopic analysis of mixtures has been used extensively for a variety of applications ranging from the analysis of plant extracts, wine, and food to the evaluation of toxicity in animals. For example, NMR analysis of urine samples has been used extensively for biomarker discovery and, more simply, for the construction of classification models of toxicity, disease, and biochemical phenotype. However, NMR spectra of complex mixtures typically show unwanted local peak shifts caused by matrix and instrument variability, which must be compensated for prior to statistical analysis and interpretation of the data. One approach is to align the spectral peaks across the data set. An efficient and fast warping algorithm is required as the signals typically contain ca. 32,000-64,000 data points and there can be several thousand spectra in a data set. As demonstrated in our study, the iterative fuzzy warping algorithm fulfills these requirements and can be used on-line for an alignment of the NMR spectra. Correlation coefficients between the aligned and target spectra are used as the evaluation function for the algorithm, and its performance is compared with those of other published warping methods.

Tryptophan–NAD+ pathway metabolites as putative biomarkers and predictors of peroxisome proliferation

The present study was designed to provide further information about the relevance of raised urinary levels of N-methylnicotinamide (NMN), and/or its metabolites N-methyl-4-pyridone-3-carboxamide (4PY) and N-methyl-2-pyridone-3-carboxamide (2PY), to peroxisome proliferation by dosing rats with known peroxisome proliferator-activated receptor α (PPARα) ligands [fenofibrate, diethylhexylphthalate (DEHP) and long-chain fatty acids (LCFA)] and other compounds believed to modulate lipid metabolism via PPARα-independent mechanisms (simvastatin, hydrazine and chlorpromazine). Urinary NMN was correlated with standard markers of peroxisome proliferation and serum lipid parameters with the aim of establishing whether urinary NMN could be used as a biomarker for peroxisome proliferation in the rat. Data from this study were also used to validate a previously constructed multivariate statistical model of peroxisome proliferation (PP) in the rat. The predictive model, based on 1H nuclear magnetic resonance (NMR) spectroscopy of urine, uses spectral patterns of NMN, 4PY and other endogenous metabolites to predict hepatocellular peroxisome count. Each treatment induced pharmacological (serum lipid) effects characteristic of their class, but only fenofibrate, DEHP and simvastatin increased peroxisome number and raised urinary NMN, 2PY and 4PY, with simvastatin having only a transient effect on the latter. These compounds also reduced mRNA expression for aminocarboxymuconate-semialdehyde decarboxylase (ACMSDase, EC 4.1.1.45), the enzyme believed to be involved in modulating the flux of tryptophan through this pathway, with decreasing order of potency, fenofibrate (−10.39-fold) >DEHP (−3.09-fold) >simvastatin (−1.84-fold). Of the other treatments, only LCFA influenced mRNA expression of ACMSDase (−3.62-fold reduction) and quinolinate phosphoribosyltransferase (QAPRTase, EC 2.4.2.19) (−2.42-fold) without any change in urinary NMN excretion. Although there were no correlations between urinary NMN concentration and serum lipid parameters, NMN did correlate with peroxisome count (r2=0.63) and acyl-CoA oxidase activity (r2=0.61). These correlations were biased by the large response to fenofibrate compared to the other treatments; nevertheless the data do indicate a relationship between the tryptophan–NAD+ pathway and PPARα-dependent pathways, making this metabolite a potentially useful biomarker to detect PP. In order to strengthen the observed link between the metabolites associated with the tryptophan–NAD+ pathway and more accurately predict PP, other urinary metabolites were included in a predictive statistical model. This statistical model was found to predict the observed PP in 26/27 instances using a pre-determined threshold of 2-fold mean control peroxisome count. The model also predicted a time-dependent increase in peroxisome count for the fenofibrate group, which is important when considering the use of such modelling to predict the onset and progression of PP prior to its observation in samples taken at autopsy.

Optimisation of collection, storage and preparation of rat plasma for 1H NMR spectroscopic analysis in toxicology studies to determine inherent variation in biochemical profiles

Biofluid 1H NMR spectroscopy has been assessed as a tool for toxicological investigations for almost two decades, with most studies focussing on urinary changes. This study has examined variations in the 1H NMR spectroscopy spectra of plasma collected from control rats at different times of the day. The collection, preparation and storage of samples were optimised and potential sources of variation in samples taken for toxicology studies identified. Plasma samples were collected into heparinised containers and analysed following a standard dilution with D(2)O. The value of deproteinising plasma with acetonitrile to look at low molecular weight metabolites has also been assessed. Variations in lactate and citrate levels in whole blood plasma were found and are consistent with the observation that lactate is one of the most variable metabolites in human plasma. Lipids levels also varied, in particular higher levels of lipids were found in spectra from male rats compared to female rats, and in samples collected in the morning following the feeding period. No significant changes were identified in samples which were snap-frozen and stored for up to 9 months at -80 degrees C. More changes were observed after storage at 4 degrees C or room temperature, including an increase in glycerol and choline levels, which may have resulted from lipid hydrolysis.

4,4-Dimethyl-4-silapentane-1-ammonium trifluoroacetate (DSA), a promising universal internal standard for NMR-based metabolic profiling studies of biofluids, including blood plasma and serum

Nuclear magnetic resonance (NMR)-based metabolic profiling of biofluids and tissues are of key interest to enhance biomarker discovery for disease, drug efficacy and toxicity studies. Urine and blood plasma/serum are the biofluids of most interest as they are the most accessible in both clinical and preclinical studies. However, proteinaceous fluids, such as blood serum or plasma, represent the greatest technical challenge since the chemical shift (δ) and line-width (ν1/2) of internal standards currently used for aqueous NMR samples are greatly affected by protein binding. We have therefore investigated the suitability of 4,4-dimethyl-4-silapentane-1-ammonium trifluoroacetate (DSA) as a universal internal standard for biofluids. Proton (1H) NMR spectroscopy was used to determine the effect of serum pH (3, 7.4 and 10) and DSA concentration on the overall lineshape and position of the trimethylsilyl resonance of DSA. The results were compared to that of 3-(trimethylsilyl)propionic acid sodium salt (TSP). Both the chemical shift and line-width of the DSA peak were not significantly affected by pH or DSA concentration, whereas these parameters for TSP showed large variations due to protein binding. Furthermore, the peak area of DSA correlated linearly with its concentration under all pH conditions, whilst no linear correlation was observed with TSP. Overall, in contrast to TSP, these results support the use of DSA as an accurate universal internal chemical shift reference and concentration/normalisation standard for biofluids. In the case of proteinaceous biofluids such as serum, where no current standard is available, this offers a considerable saving in both operator and spectrometer time.

An automatic data reduction and transfer method to aid pattern recognition analysis and classification of NMR spectra

A method of automatically generating reduced NMR data and transferring it between computers is proposed. These data can then be used as descriptors for input to non-parametric statistical routines for classification of the samples.

Development of a multivariate statistical model to predict peroxisome proliferation in the rat, based on urinary 1H-NMR spectral patterns

A previous report of this work (Ringeissen et al. 2003) described the use of nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical data analysis (MVDA) to identify novel biomarkers of peroxisome proliferation (PP) in Wistar Han rats. Two potential biomarkers of peroxisome proliferation in the rat were described, N-methylnicotinamide (NMN) and N-methyl-4-pyridone-3-carboxamide (4PY). The inference from these results was that the tryptophan-nicotinamide adenine dinucleotide (NAD+) pathway was altered in correlation with peroxisome proliferation, a hypothesis subsequently confirmed by TaqMan® analysis of the relevant genes encoding two key enzymes in the pathway, aminocarboxymuconate-semialdehyde decarboxylase (EC 4.1.1.45) and quinolinate phosphoribosyltransferase (EC 2.4.2.19). The objective of the present study was to investigate these data further and identify other metabolites in the NMR spectrum correlating equally with PP. MVDA Partial Least Squares (PLS) models were constructed that provided a better prediction of PP in Wistar Han rats than levels of 4PY and NMN alone. The resulting Wistar Han rat predictive models were then used to predict PP in a test group of Sprague Dawley rats following administration of fenofibrate. The models predicted the presence or absence of PP (above on arbitrary threshold of >2-fold mean control) in all Sprague Dawley rats in the test group.