An Integrated Study of Acute Effects of Valproic Acid in the Liver Using Metabonomics, Proteomics, and Transcriptomics Platforms

N-acetylcysteine improves autism-like behavior by recovering autophagic deficiency and decreasing Notch-1/Hes-1 pathway activity

N-acetylcysteine (NAC) has been reported to improve social interaction behavior, irritability, self-injury, and anxiety-like behavior in autism. However, the molecular mechanism underlying the therapeutic roles of NAC in autism remains unknown. This study mainly aimed to investigate the therapeutic effect of NAC on valproic acid (VPA)-induced autism model and the underlying mechanisms. Our results showed that NAC ameliorated the deficits in sociability and the anxiety- and repetitive-like behaviors displayed by VPA-exposed rats. In addition, VPA exposure induced autophagic deficiency and enhanced Notch-1/Hes-1 pathway activity based on lowered Beclin-1 and LC3B levels, while increased expression of p62, Notch-1, and Hes-1 expression at the protein level. However, NAC recovered VPA-induced autophagic deficiency and reduced Notch-1/Hes-1 pathway activity in a VPA-exposed autism rat model and SH-SY5Y neural cells. The present results demonstrated that NAC improves autism-like behavioral abnormalities by inactivating Notch-1/Hes-1 signaling pathway and recovering autophagic deficiency. Taken together, this study helps to elucidate a novel molecular mechanism that underlies the therapeutic actions of NAC in autism and suggests its potential to ameliorate behavioral abnormalities in neurodevelopmental disorders.

Dried Blood Spots as Matrix for Evaluation of Valproate Levels and the Immediate and Delayed Metabolomic Changes Induced by Single Valproate Dose Treatment

The immediate and delayed metabolic changes in rats treated with valproate (VPA), a drug used for the treatment of epilepsy, were profiled. An established approach using dried blood spots (DBS) as sample matrices for gas chromatography/mass spectrometry-based metabolomics profiling was modified using double solvents in the extraction of analytes. With the modified method, some of the previously undetectable metabolites were recovered and subtle differences in the metabolic changes upon exposure to a single dose of VPA between males and female rats were identified. In male rats, changes in 2-hydroxybutyric acid, pipecolic acid, tetratriacontane and stearic acid were found between the control and treatment groups at various time points from 2.5 h up to 24 h. In contrast, such differences were not observed in female rats, which could be caused by the vast inter-individual variations in metabolite levels within the female group. Based on the measured DBS drug concentrations, clearance and apparent volume of distribution of VPA were estimated and the values were found to be comparable to those estimated previously from full blood drug concentrations. The current study indicated that DBS is a powerful tool to monitor drug levels and metabolic changes in response to drug treatment.

Top Trends in Multiomics Research: Evaluation of 52 Published Studies and New Ways of Thinking Terminology and Visual Displays

Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, Arabidopsis thaliana, Saccharomyces cerevisiae, and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.

Primary infection by Pneumocystis induces Notch-independent Clara cell mucin production in rat distal airways

Clara cells are the main airway secretory cells able to regenerate epithelium in the distal airways through transdifferentiating into goblet cells, a process under negative regulation of the Notch pathway. Pneumocystis is a highly prevalent fungus in humans occurring between 2 and 5 months of age, a period when airways are still developing and respiratory morbidity typically increases. Pneumocystis induces mucus hyperproduction in immunocompetent host airways and whether it can stimulate Clara cells is unknown. Markers of Clara cell secretion and Notch1 activation were investigated in lungs of immunocompetent rats at 40, 60, and 80 days of age during Pneumocystis primary infection with and without Valproic acid (VPA), a Notch inducer. The proportion of rats expressing mucin increased in Pneumocystis-infected rats respect to controls at 60 and 80 days of age. Frequency of distal airways Clara cells was maintained while mRNA levels for the mucin-encoding genes Muc5B and Muc5ac in lung homogenates increased 1.9 and 3.9 times at 60 days of infection (P. = 0.1609 and P. = 0.0001, respectively) and protein levels of the Clara cell marker CC10 decreased in the Pneumocystis-infected rats at 60 and 80 days of age (P. = 0.0118 & P. = 0.0388). CC10 and Muc5b co-localized in distal airway epithelium of Pneumocystis-infected rats at day 60. Co-localization of Muc5b and Ki67 as marker of mitosis in distal airways was not observed suggesting that Muc5b production by Clara cells was independent of mitosis. Notch levels remained similar and no transnucleation of activated Notch associated to Pneumocystis infection was detected. Unexpectedly, mucus was greatly increased at day 80 in Pneumocystis-infected rats receiving VPA suggesting that a Notch-independent mechanism was triggered. Overall, data suggests a Clara to goblet cell transdifferentiation mechanism induced by Pneumocystis and independent of Notch.

Quality assurance of metabolomics

Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however – from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining – is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics.

The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools.

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.

Combined effects of a high-fat diet and chronic valproic acid treatment on hepatic steatosis and hepatotoxicity in rats

AIM

To investigate the potential interactive effects of a high-fat diet (HFD) and valproic acid (VPA) on hepatic steatosis and hepatotoxicity in rats.

METHODS

Male SD rats were orally administered VPA (100 or 500 mg·kg⁻¹·d⁻¹) combined with HFD or a standard diet for 8 weeks. Blood and liver samples were analyzed to determine lipid levels and hepatic function biomarkers using commercial kit assays. Low-molecular-weight compounds in serum, urine and bile samples were analyzed using a metabonomic approach based on GC/TOF-MS.

RESULTS

HFD alone induced extensive hepatocyte steatosis and edema in rats, while VPA alone did not cause significant liver lesions. VPA significantly aggravated HFD-induced accumulation of liver lipids, and caused additional spotty or piecemeal necrosis, accompanied by moderate infiltration of inflammatory cells in the liver. Metabonomic analysis of serum, urine and bile samples revealed that HFD significantly increased the levels of amino acids, free fatty acids (FFAs) and 3-hydroxy-butanoic acid, whereas VPA markedly decreased the levels of amino acids, FFAs and the intermediate products of the tricarboxylic acid cycle (TCA) compared with the control group. HFD aggravated VPA-induced inhibition on lipid and amino acid metabolism.

CONCLUSION

HFD magnifies VPA-induced impairment of mitochondrial β-oxidation of FFAs and TCA, thereby increases hepatic steatosis and hepatotoxicity. The results suggest the patients receiving VPA treatment should be advised to avoid eating HFD.

Review: toxicometabolomics

Metabolomics use in toxicology is rapidly increasing, particularly owing to advances in mass spectroscopy, which is widely used in the life sciences for phenotyping disease states. Toxicology has the advantage of having the disease agent, the toxicant, available for experimental induction of metabolomics changes monitored over time and dose. This review summarizes the different technologies employed and gives examples of their use in various areas of toxicology. A prominent use of metabolomics is the identification of signatures of toxicity - patterns of metabolite changes predictive of a hazard manifestation. Increasingly, such signatures indicative of a certain hazard manifestation are identified, suggesting that certain modes of action result in specific derangements of the metabolism. This might enable the deduction of underlying pathways of toxicity, which, in their entirety, form the Human Toxome, a key concept for implementing the vision of Toxicity Testing for the 21st century. This review summarizes the current state of metabolomics technologies and principles, their uses in toxicology and gives a thorough overview on metabolomics bioinformatics, pathway identification and quality assurance. In addition, this review lays out the prospects for further metabolomics application also in a regulatory context.

The role of metabolic biomarkers in drug toxicity studies

ABSTRACT Metabolic profiling is a technique that can potentially provide more sensitive and specific biomarkers of toxicity than the current clinical measures benefiting preclinical and clinical drug studies. Both nuclear magnetic resonance (NMR) and mass spectrometry (MS) platforms have been used for metabolic profiling studies of drug toxicity. Not only can both techniques provide novel biomarker(s) of toxicity but the combination of both techniques gives a broader range of metabolites evaluated. Changes in metabolic patterns can provide insight into mechanism(s) of toxicity and help to eliminate a potentially toxic new chemical entity earlier in the developmental process. Metabolic profiling offers numerous advantages in toxicological research and screening as sample collection and preparation are relatively simple. Further, sample throughput, reproducibility, and accuracy are high. The area of drug toxicity of therapeutic compounds has already been impacted by metabolic profiling studies and will continue to be impacted as new, more specific biomarker(s) are found. In order for a biomarker or pattern of biomarkers to be accepted, it must be shown that they originate from the target tissue of interest. Metabolic profiling studies are amenable to any biofluid or tissue sample making it possible to link the changes noted in urine for instance as originating from renal injury. Additionally, the ease of sample collection makes it possible to follow a single animal or subject over time in order to determine whether and when the toxicity resolves itself. This review focuses on the advantages of metabolic profiling for drug toxicity studies.

Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data

Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR-like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage.

Foodomics: MS-based strategies in modern food science and nutrition

Modern research in food science and nutrition is moving from classical methodologies to advanced analytical strategies in which MS-based techniques play a crucial role. In this context, Foodomics has been recently defined as a new discipline that studies food and nutrition domains through the application of advanced omics technologies in which MS techniques are considered indispensable. Applications of Foodomics include the genomic, transcriptomic, proteomic, and/or metabolomic study of foods for compound profiling, authenticity, and/or biomarker-detection related to food quality or safety; the development of new transgenic foods, food contaminants, and whole toxicity studies; new investigations on food bioactivity, food effects on human health, etc. This review work does not intend to provide an exhaustive revision of the many works published so far on food analysis using MS techniques. The aim of the present work is to provide an overview of the different MS-based strategies that have been (or can be) applied in the new field of Foodomics, discussing their advantages and drawbacks. Besides, some ideas about the foreseen development and applications of MS-techniques in this new discipline are also provided.

Review article: Drug-induced liver injury--its pathophysiology and evolving diagnostic tools

BACKGROUND

Drug-induced liver injury (DILI) is a significant cause of morbidity and mortality accounting for at least 13% of acute liver failure cases in the US. It is the leading cause of acute liver failure among patients referred for liver transplantation and the most common reason that drugs in development do not obtain FDA approval. The incidence of DILI has been reported to be one in 10,000 to one in 100,000 patients; however, the actual incidence is probably higher due in part to the difficulty of diagnosis.

AIM

To present a review of the current literature on DILI with a focus on its pathophysiology and evolving diagnostic modalities.

METHODS

A PubMed literature search was conducted using the terms 'drug induced liver injury', 'pathophysiology', 'causality', 'diagnosis', 'toxicogenomics' and 'pharmacogenetics'.

RESULTS

Drug-induced liver injury is an area of ongoing research. From the time it was first recognised, our understanding of the pathophysiology, its classification, diagnosis and reporting by established national networks continues to challenge and evolve. Metabonomics, pharmacogenetics, proteomics and transcriptomics are more recent areas of study that have been applied to further the understanding of DILI.

CONCLUSIONS

Despite recent advances in our understanding of drug-induced liver injury, many aspects of its pathophysiology and clinical impact remain unclear. In addition, genomic-based studies are evolving concepts, which undoubtedly continue to contribute to our understanding of the underlying mechanisms of drug-induced liver injury.

Effects of valproic acid on organic acid metabolism in children: a metabolic profiling study

Young children are at increased risk for valproic acid (VPA) hepatotoxicity. Urinary organic acid profiles, as a measure of mitochondrial function, were obtained in children 3.5 to 17.3 years old treated for seizure disorders with valproic acid (VPA; n=52). Age-matched patients treated with carbamazepine (CBZ; n=50) and untreated healthy children (n=22) served as controls. Age-related changes in organic acid profiles were observed in all three groups. Although untreated and CBZ control subjects were not distinguished by the principal component analysis (PCA) scores plot, a distinct boundary was apparent between the VPA and control/CBZ groups. Inter-individual variability in VPA-induced alterations in endogenous pathways reflecting branched chain amino acid metabolism and oxidative stress was observed. The data suggest that more detailed metabolomic analysis may provide novel insights into biological mechanisms and predictive biomarkers for children at highest risk for serious toxicity.

Age-related differences in susceptibility to cisplatin-induced renal toxicity

Limited experimental models exist to assess drug toxicity in pediatric populations. We recently reported how a multi-age rat model could be used for pre-clinical studies of comparative drug toxicity in pediatric populations. The objective of this study was to expand the utility of this animal model, which previously demonstrated an age-dependent sensitivity to the classic nephrotoxic compound, gentamicin, to another nephrotoxicant, namely cisplatin (Cis). Sprague-Dawley rats (10, 25, 40 and 80 days old) were injected with a single dose of Cis (0, 1, 3 or 6 mg kg(-1) i.p.). Urine samples were collected prior and up to 72 h after treatment in animals that were >or= 25 days old. Several serum, urinary and 'omic' injury biomarkers as well as renal histopathology lesions were evaluated. Statistically significant changes were noted with different injury biomarkers in different age groups. The order of age-related Cis-induced nephrotoxicity was different than our previous study with gentamicin: 80 > 40 > 10 > 25 day-old vs 10 >or= 80 > 40 > 25-day-old rats, respectively. The increased levels of kidney injury molecule-1 (Kim-1: urinary protein/tissue mRNA) provided evidence of early Cis-induced nephrotoxicity in the most sensitive age group (80 days old). Levels of Kim-1 tissue mRNA and urinary protein were significantly correlated to each other and to the severity of renal histopathology lesions. These data indicate that the multi-age rat model can be used to demonstrate different age-related sensitivities to renal injury using mechanistically distinct nephrotoxicants, which is reflected in measurements of a variety of metabolite, gene transcript and protein biomarkers.

Study of valproic acid-induced endogenous and exogenous metabolite alterations using LC–MS-based metabolomics

Background: Valproic acid (VPA; an anticonvulsant drug) therapy is associated with hepatotoxicity as well as renal toxicity. An LC–MS-based metabolomics approach was undertaken in order to detect urinary VPA metabolites and to discover early biomarkers of the adverse effects induced by VPA. Results: CD-1 mice were either subcutaneously injected with 600-mg VPA/kg body weight or vehicle only, and urine samples were collected at 6, 12, 24 and 48 h postinjection. A metabolomics approach combined with principal component analysis was utilized to identify VPA-related metabolites and altered endogenous metabolites in urine. Some VPA metabolites indicated potential liver toxicity caused by VPA administration. Additionally, some altered endogenous metabolites suggested that renal function might be perturbed by VPA dosing. Conclusion: LC–MS-based metabolomics is capable of rapidly profiling VPA drug metabolites and is a powerful tool for the discovery of potential early biomarkers related to perturbations in liver and kidney function.

Nutritional systems biology: definitions and approaches

Nutrigenetics and nutrigenomics are nascent areas that are evolving quickly and riding on the wave of "personalized medicine" that is providing opportunities in the discovery and development of nutraceutical compounds. The human genome sequence and sequences of model organisms provide the equivalent of comprehensive blueprints and parts lists that describe dynamic networks and the bases for understanding their responses to external and internal perturbations. Unfolding the interrelationships among genes, gene products, and dietary habits is fundamental for identifying individuals who will benefit most from, or be placed at risk by, intervention strategies. More accurate assessment of the inputs to human health and the consequences of those inputs measured as accurate transcriptomic, proteomic, and metabolomic analyses would bring personalized health/diet to practice far faster than would waiting for a predictive knowledge of genetic variation. It is widely recognized that systems and network biology has the potential to increase our understanding of how nutrition influences metabolic pathways and homeostasis, how this regulation is disturbed in a diet-related disease, and to what extent individual genotypes contribute to such diseases.

Single valproic acid treatment inhibits glycogen and RNA ribose turnover while disrupting glucose-derived cholesterol synthesis in liver as revealed by the [U-C(6)]-d-glucose tracer in mice

Previous genetic and proteomic studies identified altered activity of various enzymes such as those of fatty acid metabolism and glycogen synthesis after a single toxic dose of valproic acid (VPA) in rats. In this study, we demonstrate the effect of VPA on metabolite synthesis flux rates and the possible use of abnormal (13)C labeled glucose-derived metabolites in plasma or urine as early markers of toxicity. Female CD-1 mice were injected subcutaneously with saline or 600 mg/kg) VPA. Twelve hours later, the mice were injected with an intraperitoneal load of 1 g/kg [U-(13)C]-d-glucose. (13)C isotopomers of glycogen glucose and RNA ribose in liver, kidney and brain tissue, as well as glucose disposal via cholesterol and glucose in the plasma and urine were determined. The levels of all of the positional (13)C isotopomers of glucose were similar in plasma, suggesting that a single VPA dose does not disturb glucose absorption, uptake or hepatic glucose metabolism. Three-hour urine samples showed an increase in the injected tracer indicating a decreased glucose re-absorption via kidney tubules. (13)C labeled glucose deposited as liver glycogen or as ribose of RNA were decreased by VPA treatment; incorporation of (13)C via acetyl-CoA into plasma cholesterol was significantly lower at 60 min. The severe decreases in glucose-derived carbon flux into plasma and kidney-bound cholesterol, liver glycogen and RNA ribose synthesis, as well as decreased glucose re-absorption and an increased disposal via urine all serve as early flux markers of VPA-induced adverse metabolic effects in the host.

Delineating liver events in trichloroethylene-induced autoimmune hepatitis

Exposure to the environmental pollutant trichloroethylene (TCE) has been linked to autoimmune disease development in humans. Chronic (32-week) low-level exposure to TCE has been shown to promote autoimmune hepatitis in association with CD4(+) T cell activation in autoimmune-prone MRL+/+ mice. MRL+/+ mice are usually thought of as a model of systemic lupus rather than an organ-specific disease such as autoimmune hepatitis. Consequently, the present study examined gene expression and metabolites to delineate the liver events that skewed the autoimmune response toward that organ in TCE-treated mice. Female MRL+/+ mice were treated with 0.5 mg/mL TCE in their drinking water. The results showed that TCE-induced autoimmune hepatitis could be detected in as little as 26 weeks. TCE exposure also generated a time-dependent increase in the number of antibodies specific for liver proteins. The gene expression correlated with the metabolite analysis to show that TCE upregulated the methionine/homocysteine pathway in the liver after 26 weeks of exposure. The results also showed that TCE exposure altered the expression of selective hepatic genes associated with immunity and inflammation. On the basis of these results, future mechanistic studies will focus on how alterations in genes associated with immunity and inflammation, in conjunction with protein alterations in the liver, promote liver immunogenicity in TCE-treated MRL+/+ mice.

Global metabolic profiling and its role in systems biology to advance personalized medicine in the 21st century

Systems biology attempts to elucidate the complex interaction between genes, proteins and metabolites to provide a mechanistic understanding of cellular function and how this function is affected by disease processes, drug toxicity or drug efficacy effects. Global metabolic profiling is an important component of systems biology that can be applied in both preclinical and clinical settings for drug discovery and development, and to study disease mechanisms. The metabolic profile encodes the phenotype, which is composed of the genotype and environmental factors. The phenotypic profile can be used to make decisions about the best course of treatment for an individual patient. Understanding the combined effects of genetics and environment through a systems biology framework will enable the advancement of personalized medicine.

The challenges for molecular nutrition research 3: comparative nutrigenomics research as a basis for entering the systems level

Human nutrition and metabolism may serve as the paradigm for the complex interplay of the genome with its environment. The concept of nutrigenomics now enables science with new tools and comprehensive analytical techniques to investigate this interaction at all levels of the complexity of the organism. Moreover, nutrigenomics seeks to better define the homeostatic control mechanisms, identify the de-regulation in the early phases of diet-related diseases, and attempts to assess to what extent an individual's sensitizing genotype contributes to the overall health or disease state. In a comparative approach nutrigenomics uses biological systems of increasing complexity from yeast to mammalian models to define the general rules of metabolic and genetic mechanisms in adaptations to the nutritional environment. Powerful information technology, bioinformatics and knowledge management tools as well as new mathematical and computational approaches now make it possible to study these molecular mechanisms at the cellular, organ and whole organism level and take it on to modeling the processes in a "systems biology" approach. This review summarizes some of the concepts of a comparative approach to nutrigenomics research, identifies current lacks and proposes a concerted scientific effort to create the basis for nutritional systems biology.

Metabolomics: a tool for personalizing medicine?

The concept of personalized medicine is based upon using personal genetic information to predict individual responses to drug therapy. However, environmental factors such as diet, energy status, gut microbiota, health status and age will influence the expression of one’s genetic potential. Metabolomics data from biofluid and tissue sample analysis hold information regarding a patient’s genotype and phenotype. Metabolomics data can be rapidly collected from biofluid samples over time, providing temporal metabolic analyses of patient samples. In addition to metabolic markers of a patient’s phenotype, metabolomics can provide markers of drug efficacy, toxicity and clearance.

Technology insight: metabonomics in gastroenterology-basic principles and potential clinical applications

Metabonomics-the study of metabolic changes in an integrated biologic system-is an emerging field. This discipline joins the other 'omics' (genomics, transcriptomics and proteomics) to give rise to a comprehensive, systems-biology approach to the evaluation of holistic in vivo function. Metabonomics, especially when based on nuclear magnetic resonance spectroscopy, has the potential to identify biomarkers and prognostic factors, enhance clinical diagnosis, and expand hypothesis generation. As a consequence, the use of metabonomics has been extensively explored in the past decade, and applied successfully to the study of human diseases, toxicology, microbes, nutrition, and plant biology. This Review introduces the basic principles of nuclear magnetic resonance spectroscopy and commonly used tools for multivariate data analysis, before considering the applications and future potential of metabonomics in basic and clinical research, with emphasis on applications in the field of gastroenterology.

Metabolomics as an extension of proteomic analysis: study of acute kidney injury

Although proteomics studies the global expression of proteins, metabolomics characterizes and quantifies their end products: the metabolites, produced by an organism under a certain set of conditions. From this perspective it is apparent that proteomics and metabolomics are complementary and when joined allow a fuller appreciation of an organism's phenotype. Our studies using (1)H-nuclear magnetic resonance spectroscopic analysis showed the presence of glucose, amino acids, and trichloroacetic acid cycle metabolites in the urine after 48 hours of cisplatin administration. These metabolic alterations precede changes in serum creatinine. Biochemical studies confirmed the presence of glucosuria, but also showed the accumulation of nonesterified fatty acids, and triglycerides in serum, urine, and kidney tissue, despite increased levels of plasma insulin. These metabolic alterations were ameliorated by the use of fibrates. We propose that the injury-induced metabolic profile may be used as a biomarker of cisplatin-induced nephrotoxicity. These studies serve to illustrate that metabolomic studies add insight into pathophysiology not provided by proteomic analysis alone.

Chemometrics in metabonomics

We provide an overview of how the underlying philosophy of chemometrics is integrated throughout metabonomic studies. Four steps are demonstrated: (1) definition of the aim, (2) selection of objects, (3) sample preparation and characterization, and (4) evaluation of the collected data. This includes the tools applied for linear modeling, for example, Statistical Experimental Design (SED), Principal Component Analysis (PCA), Partial least-squares (PLS), Orthogonal-PLS (OPLS), and dynamic extensions thereof. This is illustrated by examples from the literature.

Metabolomic biomarkers: their role in the critical path

Global metabolic profiling is being applied to identify biomarkers of health. Some small molecules are exquisitely sensitive indicators of health status. Metabolic profiling analyses are being used to determine biomarkers of drug safety and effectiveness as well as disease diagnosis and prognosis including organ transplant rejection. To understand the mechanism(s) of drug toxicity and disease, a systems biology approach that considers the information generated from metabolic profiling, genetics, transcriptomics and proteomics research paradigms is necessary. This will allow for a better understanding of the mechanism(s) of drug interactions and disease while possibly identifying susceptible populations, an important goal in the move toward personalized medicine.:

Gene expression profiles of murine fatty liver induced by the administration of valproic acid

Valproic acid (VPA) has been used as anticonvulsants, however, it induces hepatotoxicity such as microvesicular steatosis and necrosis in the liver. To explore the mechanisms of VPA-induced steatosis, we profiled the gene expression patterns of the mouse liver that were altered by treatment with VPA using microarray analysis. VPA was orally administered as a single dose of 100 mg/kg (low-dose) or 1000 mg/kg (high-dose) to ICR mice and the animals were killed at 6, 24, or 72 h after treatment. Serum alanine aminotransferase and aspartate aminotransferase levels were not significantly altered in the experimental animals. However, symptoms of steatosis were observed at 72 h with low-dose and at 24 h and 72 h with high-dose. After microarray data analysis, 1910 genes were selected by two-way ANOVA (P<0.05) as VPA-responsive genes. Hierarchical clustering revealed that gene expression changes depended on the time rather than the dose of VPA treatment. Gene profiling data showed striking changes in the expression of genes associated with lipid, fatty acid, and steroid metabolism, oncogenesis, signal transduction, and development. Functional categorization of 1156 characteristically up- and down-regulated genes (cutoff >1.5-fold) revealed that 60 genes were involved in lipid metabolism that was interconnected with biological pathways for biosynthesis of triglyceride and cholesterol, catabolism of fatty acid, and lipid transport. This gene expression profile may be associated with the known steatogenic hepatotoxicity of VPA and it may provide useful information for prediction of hepatotoxicity of unknown chemicals or new drug candidates through pattern recognition.

Monitoring the health to disease continuum with global metabolic profiling and systems biology

Global metabolic profiling, which includes both metabolomics and metabonomics studies, is the latest ‘omics’ research platform that is being applied to understand the health and disease continuum. Metabolic profiling analyses have been demonstrated for the investigation of inborn errors of metabolism, organ transplant rejection, drug toxicity, disease diagnosis and prognosis, drug efficacy and nutritional status. Combining information generated from a metabolic profiling platform with that obtained based on genetics, transcriptomics and proteomics research paradigms will pave the way for a better understanding of the mechanisms of disease and toxicity. Metabolomics and nutrition will lay the groundwork for the application of personalized medicine in the 21st century.