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.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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 Fisher's 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.
Celotno besedilo
Dostopno za:
DOBA, FSPLJ, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This study identified two potential novel biomarkers of peroxisome proliferation in the rat. Three peroxisome proliferator-activated receptor (PPAR) ligands, chosen for their high selectivity towards ...the PPARα, - and -γ subtypes, were given to rats twice daily for 7 days at doses known to cause a pharmacological effect or peroxisome proliferation. Fenofibrate was used as a positive control. Daily treatment with the PPARα and - agonists produced peroxisome proliferation and liver hypertrophy. 1H nuclear magnetic resonance spectroscopy and multivariate statistical data analysis of urinary spectra from animals given the PPARα and - agonists identified two new potential biomarkers of peroxisome proliferation - N-methylnicotinamide (NMN) and N-methyl-4-pyridone-3-carboxamide (4PY) - both endproducts of the tryptophan-nicotinamide adenine dinucleotide (NAD+) pathway. After 7 days, excretion of NMN and 4PY increased 24- and three-fold, respectively, following high doses of fenofibrate. The correlation between total NMN excretion over 7 days and the peroxisome count was r=0.87 (r2=0.76). Plasma NMN, measured using a sensitive high performance liquid chromatography method, was increased up to 61-fold after 7 days' treatment with high doses of fenofibrate. Hepatic gene expression of aminocarboxymuconate-semialdehyde decarboxylase (EC 4.1.1.45) was downregulated following treatment with the PPARα and - agonists. The decrease was up to 11-fold compared with controls in the groups treated with high doses of fenofibrate. This supports the link between increased NMN and 4PY excretion and regulation of the tryptophan-NAD+ pathway in the liver. In conclusion, NMN, and possibly other metabolites in the pathway, are potential non-invasive surrogate biomarkers of peroxisome proliferation in the rat.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
The InnoMed PredTox consortium was formed to evaluate whether conventional preclinical safety assessment can be significantly enhanced by incorporation of molecular profiling (aomicsa) technologies. ...In short-term toxicological studies in rats, transcriptomics, proteomics and metabolomics data were collected and analyzed in relation to routine clinical chemistry and histopathology. Four of the sixteen hepato- and/or nephrotoxicants given to rats for 1, 3, or 14days at two dose levels induced similar histopathological effects. These were characterized by bile duct necrosis and hyperplasia and/or increased bilirubin and cholestasis, in addition to hepatocyte necrosis and regeneration, hepatocyte hypertrophy, and hepatic inflammation. Combined analysis of liver transcriptomics data from these studies revealed common gene expression changes which allowed the development of a potential sequence of events on a mechanistic level in accordance with classical endpoint observations. This included genes implicated in early stress responses, regenerative processes, inflammation with inflammatory cell immigration, fibrotic processes, and cholestasis encompassing deregulation of certain membrane transporters. Furthermore, a preliminary classification analysis using transcriptomics data suggested that prediction of cholestasis may be possible based on gene expression changes seen at earlier time-points. Targeted bile acid analysis, based on LC-MS metabonomics data demonstrating increased levels of conjugated or unconjugated bile acids in response to individual compounds, did not provide earlier detection of toxicity as compared to conventional parameters, but may allow distinction of different types of hepatobiliary toxicity. Overall, liver transcriptomics data delivered mechanistic and molecular details in addition to the classical endpoint observations which were further enhanced by targeted bile acid analysis using LC/MS metabonomics.
1H NMR spectra have been measured at 500 and 600 MHz on 23 human cerebrospinal fluid samples obtained at autopsy from Alzheimer's disease patients and controls. The spectra at 500 MHz were quantified ...using 42 descriptors based on NMR peak heights and it was shown that differences between the two classes were apparent in the delta 2.4-2.9 region. Remeasured at 600 MHz a detailed examination of this chemical shift range identified citrate, aspartate, N-acetyl aspartate, methionine and glutamate in this region of the spectra. Principal components analysis showed that a separation of the two classes was possible and detailed statistics indicated that citrate level was the principal marker. Patient age and the interval between death and autopsy (parameters not closely matched between the two groups) were examined statistically to establish whether these might account for the citrate differences. Although they could possibly account for them to some extent, the relationship between citrate levels and disease state remained significant at p < 0.05. The data invite a test of the importance of citrate levels in Alzheimer's disease using samples taken ex vivo.
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
2O. 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
°C. More changes were observed after storage at 4
°C or room temperature, including an increase in glycerol and choline levels, which may have resulted from lipid hydrolysis.
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 alpha (PPAR alpha ) ligands fenofibrate, diethylhexylphthalate (DEHP) and long-chain fatty acids (LCFA) and other compounds believed to modulate lipid metabolism via PPAR alpha -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 super(1)H 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 (r super(2)=0.63) and acyl-CoA oxidase activity (r super(2)=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 super(+) pathway and PPAR alpha -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 super(+) 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.
For almost two decades, super(1)H-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 super(-1)), 1,2-dimethylhydrazine (0.1 or 0.3 g kg super(- 1)), alpha -napthylisothiocyanate (0.1 or 0.15 g kg super(-1)) and carbon tetrachloride (1.58 or 3.16 g kg super(-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 super(1)H-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 Fisher's 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 beta -hydroxybutyrate), which might be expected if energy metabolism was switched from glycolysis to fatty acid beta -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 alpha -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.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
