Metabolomics as a tool for personalizing medicine: 2012 update

Urine organic acids may be useful biomarkers for metabolic syndrome and its components in Korean adults

OBJECTIVES

Although metabolic syndrome (MetS) and its components are defined clinically, those with MetS may have various derangements in metabolic pathways. Thus, this study aimed to evaluate the traits of urine organic acid metabolites indicating the metabolic intermediates of the pathways in the subjects with MetS.

METHODS

This cross-sectional study included 246 men and 283 women in a hospital health check-up setting. Urine organic acid metabolites were assayed via high-performance liquid chromatography-mass spectrometry analyses. A high level of each metabolite was defined as the fifth quintile of the distribution.

RESULTS

The subjects with MetS had high levels of pyruvate, α-ketoglutarate, α-ketoisovalerate, α-ketoisocaproate, formiminoglutamate, and quinolinate (odds ratios from 1.915 to 2.809 in logistic models adjusted for age and sex). Among the metabolites, pyruvate, formiminoglutamate, and quinolinate were not independent of homeostatic model assessment of insulin resistance (HOMA2-IR). Several metabolites were associated with one or more components of MetS and HOMA2-IR.

CONCLUSIONS

Urine organic acid metabolites in MetS are characterized in altered carbohydrate and amino acid metabolism. MetS shared some traits in insulin resistance. These findings may promote the understanding of the pathophysiology of MetS.

An emerging potential of metabolomics in multiple sclerosis: a comprehensive overview

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the nervous system that primarily affects young adults. Although the exact etiology of the disease remains obscure, it is clear that alterations in the metabolome contribute to this process. As such, defining a reliable and disease-specific metabolome has tremendous potential as a diagnostic and therapeutic strategy for MS. Here, we provide an overview of studies aimed at identifying the role of metabolomics in MS. These offer new insights into disease pathophysiology and the contributions of metabolic pathways to this process, identify unique markers indicative of treatment responses, and demonstrate the therapeutic effects of drug-like metabolites in cellular and animal models of MS. By and large, the commonly perturbed pathways in MS and its preclinical model include lipid metabolism involving alpha-linoleic acid pathway, nucleotide metabolism, amino acid metabolism, tricarboxylic acid cycle, d-ornithine and d-arginine pathways with collective role in signaling and energy supply. The metabolomics studies suggest that metabolic profiling of MS patient samples may uncover biomarkers that will advance our understanding of disease pathogenesis and progression, reduce delays and mistakes in diagnosis, monitor the course of disease, and detect better drug targets, all of which will improve early therapeutic interventions and improve evaluation of response to these treatments.

Influence of Sex on Urinary Organic Acids: A Cross-Sectional Study in Children

The characterization of urinary metabolome, which provides a fingerprint for each individual, is an important step to reach personalized medicine. It is influenced by exogenous and endogenous factors; among them, we investigated sex influences on 72 organic acids measured through GC-MS analysis in the urine of 291 children (152 males; 139 females) aging 1–36 months and stratified in four groups of age. Among the 72 urinary metabolites, in all age groups, 4-hydroxy-butirate and homogentisate are found only in males, whereas 3-hydroxy-dodecanoate, methylcitrate, and phenylacetate are found only in females. Sex differences are still present after age stratification being more numerous during the first 6 months of life. The most relevant sex differences involve the mitochondria homeostasis. In females, citrate cycle, glyoxylate and dicarboxylate metabolism, alanine, aspartate, glutamate, and butanoate metabolism had the highest impact. In males, urinary organic acids were involved in phenylalanine metabolism, citrate cycle, alanine, aspartate and glutamate metabolism, butanoate metabolism, and glyoxylate and dicarboxylate metabolism. In addition, age specifically affected metabolic pathways, the phenylalanine metabolism pathway being affected by age only in males. Relevantly, the age-influenced ranking of metabolic pathways varied in the two sexes. In conclusion, sex deeply influences both quantitatively and qualitatively urinary organic acids levels, the effect of sex being age dependent. Importantly, the sex effects depend on the single organic acid; thus, in some cases the urinary organic acid reference values should be stratified according the sex and age.

Metabolomics Analysis of the Deterioration Mechanism and Storage Time Limit of Tender Coconut Water during Storage

Tender coconut water tastes sweet and is enjoyed by consumers, but its commercial development is restricted by an extremely short shelf life, which cannot be explained by existing research. UPLC-MS/MS-based metabolomics methods were used to identify and statistically analyze metabolites in coconut water under refrigerated storage. A multivariate statistical analysis method was used to analyze the UPLC-MS/MS datasets from 35 tender coconut water samples stored for 0-6 weeks. In addition, we identified other differentially expressed metabolites by selecting p-values and fold changes. Hierarchical cluster analysis and association analysis were performed with the differentially expressed metabolites. Metabolic pathways were analyzed using the KEGG database and the MetPA module of MetaboAnalyst. A total of 72 differentially expressed metabolites were identified in all groups. The OPLS-DA score chart showed that all samples were well grouped. Thirty-one metabolic pathways were enriched in the week 0-1 samples. The results showed that after a tender coconut is peeled, the maximum storage time at 4 °C is 1 week. Analysis of metabolic pathways related to coconut water storage using the KEGG and MetPA databases revealed that amino acid metabolism is one of the main causes of coconut water quality deterioration.

Metabolomic diagnostics and human digital image

The existing clinical laboratory practice has limitations in terms of specificity and sensitivity of diagnosis, making the introduction of new methods in medicine more topical. Application of 'omics' technologies, especially metabolomics, allows overcoming these limitations. The composition of blood metabolites reflects the physical state of an organism at the molecular level. The analysis of blood metabolome can serve as effective means of diagnosis, implementation of which in healthcare is timely and relevant. This paper demonstrates the versatility of metabolomic diagnostics, its applicability to various diseases. We discussed the standard of human digital image, which includes the metabolomic data sufficient to make an accurate assessment of general health and carry out precision diagnostics of a wide range of diseases.

Beta-3 Adrenoceptor Signaling Pathways in Urothelial and Smooth Muscle Cells in the Presence of Succinate

Succinate, an intermediate metabolite of the Krebs cycle, can alter the metabolomics response to certain drugs and controls an array of molecular responses in the urothelium through activation of its receptor, G-protein coupled receptor 91 (GPR91). Mirabegron, a β3-adrenergic receptor (β3-AR) agonist used to treat overactive bladder syndrome (OAB), increases intracellular cAMP in the detrusor smooth muscle cells (SMC), leading to relaxation. We have previously shown that succinate inhibits forskolin-stimulated cAMP production in urothelium. To determine whether succinate interferes with mirabegron-mediated bladder relaxation, we examined their individual and synergistic effect in urothelial-cell and SMC signaling. We first confirmed β3-AR involvement in the mirabegron response by quantifying receptor abundance by immunoblotting in cultured urothelial cells and SMC and cellular localization by immunohistochemistry in rat bladder tissue. Mirabegron increased cAMP levels in SMC but not in urothelial cells, an increase that was inhibited by succinate, suggesting that it impairs cAMP-mediated bladder relaxation by mirabegron. Succinate and mirabegron increased inducible nitric oxide synthesis and nitric oxide secretion only in urothelial cells, suggesting that its release can indirectly induces SMC relaxation. Succinate exposure decreased the expression of β3-AR protein in whole bladder in vivo and in SMC in vitro, indicating that this metabolite may lead to impaired pharmacodynamics of the bladder. Together, our results demonstrate that increased levels of succinate in settings of metabolic stress (e.g., the metabolic syndrome) may lead to impaired mirabegron and β3-AR interaction, inhibition of cAMP production, and ultimately requiring mirabegron dose adjustment for its treatment of OAB related to these conditions.

Application of metabolomics: Focus on the quantification of organic acids in healthy adults

Metabolomics, a 'budding' discipline, may accurately reflect a specific phenotype which is sensitive to genetic and epigenetic interactions. This rapidly evolving field in science has been proposed as a tool for the evaluation of the effects of epigenetic factors, such as nutrition, environment, drug and lifestyle on phenotype. Urine, being sterile, is easy to obtain and as it contains metabolized or non-metabolized products, is a favored study material in the field of metabolomics. Urine organic acids (OAs) reflect the activity of main metabolic pathways and have been used to assess health status, nutritional status, vitamin deficiencies and response to xenobiotics. To date, a limited number of studies have been performed which actually define reference OA values in a healthy population and as reference range for epigenetic influences, and not as a reference to congenital metabolic diseases. The aim of the present study was thus the determination of reference values (RVs) for urine OA in a healthy adult population. Targeted metabolomics analysis of 22 OAs in the urine of 122 healthy adults by gas chromatography-mass spectrometry, was conducted. Percentile distributions of the OA concentrations in urine, as a base for determining the RVs in the respective population sample, were used. No significant differences were detected between female and male individuals. These findings can facilitate the more sensitive determination of OAs in pathological conditions. Therefore, the findings of this study may contribute or add to the information already available on urine metabolite databases, and may thus promote the use of targeted metabolomics for the evaluation of OAs in a clinical setting and for pathophysiological evaluation. However, further studies with well-defined patients groups exhibiting specific symptoms or diseases are warranted in order to discern between normal and pathological values.

Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine

"Omics" sciences have been developed to provide a holistic point of view of biology and to better understand the complexity of an organism as a whole. These systems biology approaches can be examined at different levels, starting from the most fundamental, i.e., the genome, and finishing with the most functional, i.e., the metabolome. Similar to how genomics is applied to the exploration of DNA, metabolomics is the qualitative and quantitative study of metabolites. This emerging field is clearly linked to genomics, transcriptomics, and proteomics. In addition, metabolomics provides a unique and direct vision of the functional outcome of an organism's activities that are required for it to survive, grow, and respond to internal and external stimuli or stress, e.g., pathologies and drugs. The links between metabolic changes, patient phenotype, physiological and/or pathological status, and treatment are now well established and have opened a new area for the application of metabolomics in the drug discovery process and in personalized medicine.

Application of Systems Theory in Longitudinal Studies on the Origin and Progression of Alzheimer's Disease

This chapter questions the prevailing "implicit" assumption that molecular mechanisms and the biological phenotype of dominantly inherited early-onset alzheimer's disease (EOAD) could serve as a linear model to study the pathogenesis of sporadic late-onset alzheimer's disease (LOAD). Now there is growing evidence to suggest that such reductionism may not be warranted; these suppositions are not adequate to explain the molecular complexities of LOAD. For example, the failure of some recent amyloid-centric clinical trials, which were largely based on the extrapolations from EOAD biological phenotypes to the molecular mechanisms in the pathogenesis of LOAD, might be due to such false assumptions. The distinct difference in the biology of LOAD and EOAD is underscored by the presence of EOAD cases without evidence of familial clustering or Mendelian transmission and, conversely, the discovery and frequent reports of such clustering and transmission patterns in LOAD cases. The primary thesis of this chapter is that a radically different way of thinking is required for comprehensive explanations regarding the distinct complexities in the molecular pathogenesis of inherited and sporadic forms of Alzheimer's disease (AD). We propose using longitudinal analytical methods and the paradigm of systems biology (using transcriptomics, proteomics, metabolomics, and lipidomics) to provide us a more comprehensive insight into the lifelong origin and progression of different molecular mechanisms and neurodegeneration. Such studies should aim to clarify the role of specific pathophysiological and signaling pathways such as neuroinflammation, altered lipid metabolism, apoptosis, oxidative stress, tau hyperphosphorylation, protein misfolding, tangle formation, and amyloidogenic cascade leading to overproduction and reduced clearance of aggregating amyloid-beta (Aβ) species. A more complete understanding of the distinct difference in molecular mechanisms, signaling pathways, as well as comparability of the various forms of AD is of paramount importance. The development of knowledge and technologies for early detection and characterization of the disease across all stages will improve the predictions regarding the course of the disease, prognosis, and response to treatment. No doubt such advances will have a significant impact on the clinical management of both EOAD and LOAD patients. The approach propped here, combining longitudinal studies with the systems biology paradigm, will create a more effective and comprehensive framework for development of prevention therapies in AD.

Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms

Small molecules are indispensable to modern medical therapy. However, their use may lead to unintended, negative medical outcomes commonly referred to as adverse drug reactions (ADRs). These effects vary widely in mechanism, severity, and populations affected, making ADR prediction and identification important public health concerns. Current methods rely on clinical trials and postmarket surveillance programs to find novel ADRs; however, clinical trials are limited by small sample size, whereas postmarket surveillance methods may be biased and inherently leave patients at risk until sufficient clinical evidence has been gathered. Systems pharmacology, an emerging interdisciplinary field combining network and chemical biology, provides important tools to uncover and understand ADRs and may mitigate the drawbacks of traditional methods. In particular, network analysis allows researchers to integrate heterogeneous data sources and quantify the interactions between biological and chemical entities. Recent work in this area has combined chemical, biological, and large-scale observational health data to predict ADRs in both individual patients and global populations. In this review, we explore the rapid expansion of systems pharmacology in the study of ADRs. We enumerate the existing methods and strategies and illustrate progress in the field with a model framework that incorporates crucial data elements, such as diet and comorbidities, known to modulate ADR risk. Using this framework, we highlight avenues of research that may currently be underexplored, representing opportunities for future work.

Nuclear magnetic resonance: a key metabolomics platform in the drug discovery process

Metabolomics is an innovative tool that is now emerging in the drug discovery process. Indeed, its ability to follow the dynamic perturbations in the metabolome resulting from pathologies but also from drug treatment and or/toxicity is of value for the development of new therapeutic approaches. Nuclear magnetic resonance (NMR) spectroscopy, which is an important analytical technique for several steps of the lead discovery, validation and optimization processes, has been described, together with mass spectrometry (MS) as one of the major platform that could be used for metabolomics studies. This review highlights why NMR could be considered a key tool for the application of metabolomics in drug discovery.

Population pharmacokinetic/pharmacogenetic model of lopinavir/ritonavir in HIV-infected patients

AIM

This study aims to develop a population pharmacokinetic/pharmacogenetic model for lopinavir/ritonavir (LPV/r) in European HIV-infected patients.

MATERIALS & METHODS

A total of 693 LPV/r plasma concentrations were assessed and 15 single-nucleotide polymorphisms were genotyped. The population pharmacokinetic/pharmacogenetic model was created using a nonlinear mixed-effect approach (NONMEM^® v.7.2.0., ICON Development Solutions, Dublin, Ireland).

RESULTS

Covariates significantly related to LPV/r apparent clearance (CL/F) were ritonavir trough concentration (RTC), BMI, high-density lipoprotein cholesterol (HDL-C) and certain single-nucleotide polymorphisms in genes encoding for metabolizing enzymes, which are representable as follows: CL/F = (0.216BMI + 0.0125HDL-C) × 0.713^RTC × 1.26^{rs28371764[C/T]} × 0.528^{rs6945984[C/C]} × 0.302 ^{CYP3A4[1461insA/del]} Conclusion: The LPV/r standard dose appears to be appropriate for the rs28371764[C/T] genotype. However, lower doses should be recommended for the rs6945984[C/C] and CYP3A4[1461insA/del] genotypes and even for those patients without any of these variants, as the standard dose seems to be higher than that which is required in order to achieve therapeutic levels.

Metabolomic profiling in colorectal cancer: opportunities for personalized medicine

Colorectal cancer (CRC) is one of the most common types of cancer in the world, with high prevalence and mortality. Understanding the alterations of cancer metabolism and identifying reliable biomarkers would facilitate the development of novel technologies of CRC screening and early diagnosis, as well as new approaches to providing personalized medicine. Metabolomics, as an emerging molecular phenotyping approach, provides a clinical platform technology with an unprecedented amount of metabolic readout information, which is ideal for theranostic biomarker discovery. Metabolic signatures can link the unique pathophysiological states of patients to personalized health monitoring and intervention strategies. This article presents an overview of the metabolomic studies of CRC with a focus on recent advances in the biomarker discovery in serum, urine, fecal water and tissue samples for cancer diagnosis. The development and application of metabolomics towards personalized medicine, including early diagnosis, cancer staging, treatment and drug discovery are also discussed.

Pharmacometabonomics and personalized medicine

BACKGROUND

Pharmacometabonomics is a new branch of science, first described in 2006 and defined as 'the prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles'. Pharmacometabonomics has been used to predict drug metabolism, pharmacokinetics (PK), drug safety and drug efficacy in both animals and humans and is complementary to both pharmacogenomics (PGx) and pharmacoproteomics.

METHODS

A literature review using the search terms pharmacometabonomics, pharmacometabolomics, pharmaco-metabonomics, pharmaco-metabolomics and the singular form of all those terms was conducted in October 2012 using PubMed and Web of Science. The review was updated until mid April 2013.

RESULTS

Since the original description of pharmacometabonomics in 2006, 21 original publications and eight reviews have emerged, covering a broad range of applications from the prediction of PK to the prediction of drug metabolism, efficacy and safety in humans and animals.

CONCLUSIONS

Pharmacometabonomics promises to be an important new approach to the delivery of personalized medicine to improve both drug efficacy and safety for patients in the future. Pharmacometabonomics is particularly powerful as it is sensitive to both genetic and environmental factors such as diet, drug intake and most importantly, a person's microbiome. PGx is now over 50 years old and although it has not achieved as much as some hoped, it is starting to have important applications in personalized medicine. We predict that pharmacometabonomics will be equally important in the next few decades and will be both valuable in its own right and complementary to pharmacoproteomics and PGx.