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

A time differentiated dietary intervention effect on the biomarkers of exposure to pyrethroids and neonicotinoids pesticides

Tailoring medical models to the right person or risk subgroups delivered at the right time is important in personalized medicine/prevention initiatives. The CIRCA-CHEM randomized 2x2 crossover pilot trial investigated whether the consumption of fruits/vegetables within a time-restricted daily window would affect urinary biomarkers of exposure to neonicotinoids (6-chloronicotinic acid, 6-CN) and pyrethroids (3-phenoxybenzoic acid, 3-PBA) pesticides, a biomarker of oxidative damage (4-hydroxynonenal, 4-HNE) and the associated urinary NMR metabolome. A statistically significant difference (p < 0.001) in both creatinine-adjusted 6-CN and 3-PBA levels was observed between the two-time dietary intervention windows (morning vs. evening). In the evening intervention period, pesticides biomarker levels were higher compared to the baseline, whereas in the morning period, pesticide levels remained unchanged. Positive associations were observed between pesticides and 4-HNE suggesting a diurnal chrono-window of pesticide toxicity. The discovery of a chronotoxicity window associated with chrono-disrupted metabolism of food contaminants may find use in personalized medicine initiatives.

Metabonomic analysis of potential biomarkers and drug targets involved in diabetic nephropathy mice

Diabetic nephropathy (DN) is one of the lethal manifestations of diabetic systemic microvascular disease. Elucidation of characteristic metabolic alterations during diabetic progression is critical to understand its pathogenesis and identify potential biomarkers and drug targets involved in the disease. In this study, (1)H nuclear magnetic resonance ((1)H NMR)-based metabonomics with correlative analysis was performed to study the characteristic metabolites, as well as the related pathways in urine and kidney samples of db/db diabetic mice, compared with age-matched wildtype mice. The time trajectory plot of db/db mice revealed alterations, in an age-dependent manner, in urinary metabolic profiles along with progression of renal damage and dysfunction. Age-dependent and correlated metabolite analysis identified that cis-aconitate and allantoin could serve as biomarkers for the diagnosis of DN. Further correlative analysis revealed that the enzymes dimethylarginine dimethylaminohydrolase (DDAH), guanosine triphosphate cyclohydrolase I (GTPCH I), and 3-hydroxy-3-methylglutaryl-CoA lyase (HMG-CoA lyase) were involved in dimethylamine metabolism, ketogenesis and GTP metabolism pathways, respectively, and could be potential therapeutic targets for DN. Our results highlight that metabonomic analysis can be used as a tool to identify potential biomarkers and novel therapeutic targets to gain a better understanding of the mechanisms underlying the initiation and progression of diseases.

Potential of metabolomics in preclinical and clinical drug development

Metabolomics is an upcoming technology system which involves detailed experimental analysis of metabolic profiles. Due to its diverse applications in preclinical and clinical research, it became an useful tool for the drug discovery and drug development process. This review covers the brief outline about the instrumentation and interpretation of metabolic profiles. The applications of metabolomics have a considerable scope in the pharmaceutical industry, almost at each step from drug discovery to clinical development. These include finding drug target, potential safety and efficacy biomarkers and mechanisms of drug action, the validation of preclinical experimental models against human disease profiles, and the discovery of clinical safety and efficacy biomarkers. As we all know, nowadays the drug discovery and development process is a very expensive, and risky business. Failures at any stage of drug discovery and development process cost millions of dollars to the companies. Some of these failures or the associated risks could be prevented or minimized if there were better ways of drug screening, drug toxicity profiling and monitoring adverse drug reactions. Metabolomics potentially offers an effective route to address all the issues associated with the drug discovery and development.

Applications of metabolomics for understanding the action of peroxisome proliferator-activated receptors (PPARs) in diabetes, obesity and cancer

The peroxisome proliferator-activated receptors (PPARs) are a set of three nuclear hormone receptors that together play a key role in regulating metabolism, particularly the switch between the fed and fasted state and the metabolic pathways involving fatty-acid oxidation and lipid metabolism. In addition, they have a number of important developmental and regulatory roles outside metabolism. The PPARs are also potent targets for treating type II diabetes, dyslipidemia and obesity, although a number of individual agonists have also been linked to unwanted side effects, and there is a complex relationship between the PPARs and the development of cancer. This review examines the part that metabolomics, including lipidomics, has played in elucidating the roles PPARs have in regulating systemic metabolism, as well as their role in aspects of drug-induced cancer and xenobiotic metabolism. These studies have defined the role PPARδ plays in regulating fatty-acid oxidation in adipose tissue and the interaction between aging and PPARα in the liver. The potential translational benefits of these approaches include widening the role of PPAR agonists and improved monitoring of drug efficacy.

¹H nuclear magnetic resonance based metabolic urinary profiling of patients with ischemic heart failure

OBJECTIVES

We sought to identify metabolic pathways characterizing human heart failure (HF) using ¹NMR based urinary metabolomic analysis in conjunction with multivariate statistics.

DESIGN AND METHODS

Patients with systolic HF of ischemic origin (n=15) and healthy controls (n=20) participated in this study. Patients with type 2 diabetes mellitus were excluded.

RESULTS

The results showed that the urine of the HF patients had higher levels of metabolites for acetate (p<0.05) and acetone (p<0.01) compared to the healthy controls. In addition, there was a perturbation in methylmalonate metabolism as shown by increased urinary levels of methylmalonic acid (p<0.001) in the HF patients. HF patients also had increased urinary levels of cytosine (p<0.01) and phenylacetylglycine (p<0.01) and decreased 1-methylnicotinamide (p<0.05) compared to healthy controls.

CONCLUSIONS

TCA cycle metabolites and fatty acid metabolism were modified in the HF patients, indicating altered energy metabolism. Moreover, perturbations of metabolism in nucleotide and methylmalonate were observed.

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).

Human urinary metabolomic profile of PPARalpha induced fatty acid beta-oxidation

Activation of the peroxisome proliferator-activated receptor alpha (PPARalpha) is associated with increased fatty acid catabolism and is commonly targeted for the treatment of hyperlipidemia. To identify latent, endogenous biomarkers of PPARalpha activation and hence increased fatty acid beta-oxidation, healthy human volunteers were given fenofibrate orally for 2 weeks and their urine was profiled by UPLC-QTOFMS. Biomarkers identified by the machine learning algorithm random forests included significant depletion by day 14 of both pantothenic acid (>5-fold) and acetylcarnitine (>20-fold), observations that are consistent with known targets of PPARalpha including pantothenate kinase and genes encoding proteins involved in the transport and synthesis of acylcarnitines. It was also concluded that serum cholesterol (-12.7%), triglycerides (-25.6%), uric acid (-34.7%), together with urinary propylcarnitine (>10-fold), isobutyrylcarnitine (>2.5-fold), (S)-(+)-2-methylbutyrylcarnitine (5-fold), and isovalerylcarnitine (>5-fold) were all reduced by day 14. Specificity of these biomarkers as indicators of PPARalpha activation was demonstrated using the Ppara-null mouse. Urinary pantothenic acid and acylcarnitines may prove useful indicators of PPARalpha-induced fatty acid beta-oxidation in humans. This study illustrates the utility of a pharmacometabolomic approach to understand drug effects on lipid metabolism in both human populations and in inbred mouse models.

Subacute exposure to N-ethyl perfluorooctanesulfonamidoethanol results in the formation of perfluorooctanesulfonate and alters superoxide dismutase activity in female rats

Perfluorooctanesulfonamides, such as N-ethyl perfluorooctanesulfonamidoethanol (N-EtFOSE), are large scale industrial chemicals but their disposition and toxicity are poorly understood despite significant human exposure. The hypothesis that subacute exposure to N-EtFOSE, a weak peroxisome proliferator, causes a redox imbalance in vivo was tested using the known peroxisome proliferator, ciprofibrate, as a positive control. Female Sprague-Dawley rats were treated orally with N-EtFOSE, ciprofibrate or corn oil (vehicle) for 21 days, and levels of N-EtFOSE and its metabolites as well as markers of peroxisome proliferation and oxidative stress were assessed in serum, liver and/or uterus. The N-EtFOSE metabolite profile in liver and serum was in good agreement with reported in vitro biotransformation pathways in rats and the metabolite levels decreasing in the order perfluorooctanesulfonate >> perfluorooctanesulfonamide ~ N-ethyl perfluorooctanesulfonamidoacetate >> perfluorooctanesulfonamidoethanol approximately N-EtFOSE. Although N-EtFOSE treatment significantly decreased the growth rate, increased relative liver weight and activity of superoxide dismutases (SOD) in liver and uterus (total SOD, CuZnSOD and MnSOD), a metabolic study revealed no differences in the metabolome in serum from N-EtFOSE-treated and control animals. Ciprofibrate treatment increased liver weight and peroxisomal acyl Co-A oxidase activity in the liver and altered antioxidant enzyme activities in the uterus and liver. According to NMR metabolomic studies, ciprofibrate treated animals had altered serum lipid profiles compared to N-EtFOSE-treated and control animals, whereas putative markers of peroxisome proliferation in serum were not affected. Overall, this study demonstrates the biotransformation of N-EtFOSE to PFOS in rats that is accompanied by N-EtFOSE-induced alterations in antioxidant enzyme activity.

NMR-based metabolic profiling and metabonomic approaches to problems in molecular toxicology

We have reviewed the main contributions to the development of NMR-based metabonomic and metabolic profiling approaches for toxicological assessment, biomarker discovery, and studies on toxic mechanisms. The metabonomic approach, (defined as the quantitative measurement of the multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification) was originally developed to assist interpretation in NMR-based toxicological studies. However, in recent years there has been extensive fusion with metabolomic and other metabolic profiling approaches developed in plant biology, and there is much wider coverage of the biomedical and environmental fields. Specifically, metabonomics involves the use of spectroscopic techniques with statistical and mathematical tools to elucidate dominant patterns and trends directly correlated with time-related metabolic fluctuations within spectral data sets usually derived from biofluids or tissue samples. Temporal multivariate metabolic signatures can be used to discover biomarkers of toxic effect, as general toxicity screening aids, or to provide novel mechanistic information. This approach is complementary to proteomics and genomics and is applicable to a wide range of problems, including disease diagnosis, evaluation of xenobiotic toxicity, functional genomics, and nutritional studies. The use of biological fluids as a source of whole organism metabolic information enhances the use of this approach in minimally invasive longitudinal studies.

Biomarker discovery for drug development and translational medicine using metabonomics

There exists at present an urgent desire for better biomarkers, especially in the context of pharmaceutical drug development and in the detection and management of disease. Many researchers in the area of biomarker discovery and development have turned to the "-omics" sciences as a way of addressing these needs. Metabolic profiling, or metabonomics, defines the metabolic phenotype and offers a source of novel biomarkers that have better potential to translate effectively. This review will discuss the broad philosophy and motivations behind metabonomics, and illustrate the case with applications relevant to pharmaceutical development and patient management. Particular focus will be paid to the potential of metabonomics to contribute to biomarker discovery in toxicology and cancer research.

Metabolomic and genetic analysis of biomarkers for peroxisome proliferator-activated receptor alpha expression and activation

Peroxisome proliferator-activated receptor alpha (PPARalpha) is a nuclear receptor with manifold effects on intermediary metabolism. To define a set of urinary biomarkers that could be used to determine the efficacy of PPARalpha agonists, a metabolomic investigation was undertaken in wild-type and Pparalpha-null mice fed for 2 wk either a regular diet or a diet containing the PPARalpha ligand Wy-14,643 ([4-chloro-6-(2,3-xylidino)-2-pyrimidinylthio] acetic acid), and their urine was analyzed by ultra-performance liquid chromatography coupled with time-of-flight mass spectrometry. Principal components analysis of 6393 accurate mass positive ions revealed clustering as a single phenotype of the treated and untreated Pparalpha (-/-) mice plus two additional discrete phenotypes for the treated and untreated Pparalpha (+/+) mice. Biomarkers of PPARalpha activation were identified from their accurate masses and confirmed by tandem mass spectrometry of authentic compounds. Biomarkers were quantitated from raw chromatographic data using appropriate calibration curves. PPARalpha urinary biomarkers highly statistically significantly elevated by Wy-14,643 treatment included 11beta-hydroxy-3,20-dioxopregn-4-en-21-oic acid (>3700-fold), 11beta,20-dihydroxy-3-oxopregn-4-en-21-oic acid (50-fold), nicotinamide (>2-fold), nicotinamide 1-oxide (5-fold), 1-methylnicotinamide (1.5-fold), hippuric acid (2-fold), and 2,8-dihydroxyquinoline-beta-d-glucuronide (3-fold). PPARalpha urinary biomarkers highly statistically significantly attenuated by Wy-14,643 treatment included xanthurenic acid (1.3-fold), hexanoylglycine (20-fold), phenylpropionylglycine (4-fold), and cinnamoylglycine (9-fold). These biomarkers arise from PPARalpha effects on tryptophan, corticosterone, and fatty acid metabolism and on glucuronidation. This study underscores the power of mass spectrometry-based metabolomics combined with genetically modified mice in the definition of monogenic metabolic phenotypes.

A gender-specific discriminator in Sprague–Dawley rat urine: The deployment of a metabolic profiling strategy for biomarker discovery and identification

The use of nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS) as complementary analytical techniques for open metabolic profiling is illustrated in the context of defining urinary biochemical discriminators between male and female Sprague-Dawley rats. Subsequent to the discovery of a female-specific urinary discriminator by LC-MS, further LC, MS, and NMR methods have been applied in a coordinated effort to identify this urinary component. Thereafter, the biological relevance and context of the identified component, in this case a steroid metabolite, has been achieved. This approach will be deployed in future studies of disease, drug efficacy, and toxicity to discover and identify biologically relevant markers.

A metabonomics study of the hepatotoxicants galactosamine, methylene dianiline and clofibrate in rats

The efficacy of high-resolution (1)H nuclear magnetic resonance ((1)H-NMR) spectroscopy-based metabonomics was studied in a model of rat liver toxicity. Hepatotoxicities were induced in male rats using methylene dianiline, clofibrate and galactosamine. Twenty-four-hr urine from days 1 to 5 after treatment were subjected to (1)H-NMR evaluation of the biochemical effects. Blood were also taken at Days 2, 3 and 5 to examine biochemical changes associated with hepatotoxicities, and histopathological changes were evaluated at termination. Increases in liver enzymes were observed in animals treated with methylene dianiline or galactosamine, and histopathological analysis revealed changes associated with hepatobiliary damage and hepatocellular necrosis in methylene dianiline- and galactosamine-treated animals, respectively. Principal component analysis and statistical Spotfire analyses were used to visualize similarities and differences in urine biochemical profiles produced by (1)H-NMR spectra. The biochemical effects of methylene dianiline and galactosamine were characterized by elevated levels of glucose, fructose, beta-hydroxybutyrate, alanine, acetoacetate, lactate and creatine and decreased levels of hippurate, 2-oxoglutarate, citrate, succinate, trimethylamine-N-oxide, taurine and N-acetylglutamate in rat urine. Clofibrate treatment elevated the levels of N-methylnicotinamide and 3,4-dihydroxymandelate and decreased the levels of 2-oxoglutarate and N-acetylaspartate. This work shows that combinations of (1)H-NMR and pattern recognition are powerful tools in the evaluation of the biochemical effects of xenobiotics in liver.

A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human

Type 2 diabetes mellitus is the result of a combination of impaired insulin secretion with reduced insulin sensitivity of target tissues. There are an estimated 150 million affected individuals worldwide, of whom a large proportion remains undiagnosed because of a lack of specific symptoms early in this disorder and inadequate diagnostics. In this study, NMR-based metabolomic analysis in conjunction with multivariate statistics was applied to examine the urinary metabolic changes in two rodent models of type 2 diabetes mellitus as well as unmedicated human sufferers. The db/db mouse and obese Zucker (fa/fa) rat have autosomal recessive defects in the leptin receptor gene, causing type 2 diabetes. 1H-NMR spectra of urine were used in conjunction with uni- and multivariate statistics to identify disease-related metabolic changes in these two animal models and human sufferers. This study demonstrates metabolic similarities between the three species examined, including metabolic responses associated with general systemic stress, changes in the TCA cycle, and perturbations in nucleotide metabolism and in methylamine metabolism. All three species demonstrated profound changes in nucleotide metabolism, including that of N-methylnicotinamide and N-methyl-2-pyridone-5-carboxamide, which may provide unique biomarkers for following type 2 diabetes mellitus progression.

The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

To date most global approaches to functional genomics have centred on genomics, transcriptomics and proteomics. However, since a number of high-profile publications, interest in metabolomics, the global profiling of metabolites in a cell, tissue or organism, has been rapidly increasing. A range of analytical techniques, including 1H NMR spectroscopy, gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), Fourier Transform mass spectrometry (FT-MS), high performance liquid chromatography (HPLC) and electrochemical array (EC-array), are required in order to maximize the number of metabolites that can be identified in a matrix. Applications have included phenotyping of yeast, mice and plants, understanding drug toxicity in pharmaceutical drug safety assessment, monitoring tumour treatment regimes and disease diagnosis in human populations. These successes are likely to be built on as other analytical and bioinformatic approaches are developed to fully exploit the information obtained in metabolic profiles. To assist in this process, databases of metabolomic data will be necessary to allow the passage of information between laboratories. In this prospective review, the capabilities of metabolomics in the field of medicine will be assessed in an attempt to predict the impact this 'Cinderella approach' will have at the 'functional genomic ball'.

Metabonomics in preclinical drug development

Metabonomics has emerged as a key technology in preclinical drug discovery and development. The technology enables noninvasive systems assessment of untoward effects induced by candidate compounds characterising a broad spectrum of biological responses on an individual animal basis in a relatively rapid-throughput fashion, thus making it an ideal addition to early preclinical safety assessment. However, the implementation and interpretation of the technology and data it generates is not something that should be trivialised. Proper expertise in biological sciences, analytical sciences (nuclear magnetic resonance and/or mass spectrometry) and chemometrics should all be considered necessary prerequisites. If these factors are properly considered, the technology can add significant value as a tool for preclinical toxicologists.

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 alpha (PPARalpha) ligands [fenofibrate, diethylhexylphthalate (DEHP) and long-chain fatty acids (LCFA)] and other compounds believed to modulate lipid metabolism via PPARalpha-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 PPARalpha-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.