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      Metabolomics enables precision medicine: “A White Paper, Community Perspective”

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          Abstract

          Introduction: Background to metabolomics

          Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or “-omics” level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person’s metabolic state provides a close representation of that individual’s overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates.

          Objectives of White Paper—expected treatment outcomes and metabolomics enabling tool for precision medicine

          We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject’s response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient’s metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine.

          Conclusions: Key scientific concepts and recommendations for precision medicine

          Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its “Precision Medicine and Pharmacometabolomics Task Group”, with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.

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          Innovation: Metabolomics: the apogee of the omics trilogy.

          Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry. With emerging technologies in mass spectrometry, thousands of metabolites can now be quantitatively measured from minimal amounts of biological material, which has thereby enabled systems-level analyses. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and are shaping our understanding of cell biology, physiology and medicine.
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            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).
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              Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism.

              We provide a demonstration in humans of the principle of pharmacometabonomics by showing a clear connection between an individual's metabolic phenotype, in the form of a predose urinary metabolite profile, and the metabolic fate of a standard dose of the widely used analgesic acetaminophen. Predose and postdose urinary metabolite profiles were determined by (1)H NMR spectroscopy. The predose spectra were statistically analyzed in relation to drug metabolite excretion to detect predose biomarkers of drug fate and a human-gut microbiome cometabolite predictor was identified. Thus, we found that individuals having high predose urinary levels of p-cresol sulfate had low postdose urinary ratios of acetaminophen sulfate to acetaminophen glucuronide. We conclude that, in individuals with high bacterially mediated p-cresol generation, competitive O-sulfonation of p-cresol reduces the effective systemic capacity to sulfonate acetaminophen. Given that acetaminophen is such a widely used and seemingly well-understood drug, this finding provides a clear demonstration of the immense potential and power of the pharmacometabonomic approach. However, we expect many other sulfonation reactions to be similarly affected by competition with p-cresol and our finding also has important implications for certain diseases as well as for the variable responses induced by many different drugs and xenobiotics. We propose that assessing the effects of microbiome activity should be an integral part of pharmaceutical development and of personalized health care. Furthermore, we envisage that gut bacterial populations might be deliberately manipulated to improve drug efficacy and to reduce adverse drug reactions.
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                Author and article information

                Contributors
                rima.kaddurahdaouk@duke.edu
                Journal
                Metabolomics
                Metabolomics
                Metabolomics
                Springer US (New York )
                1573-3882
                1573-3890
                2 September 2016
                2 September 2016
                2016
                : 12
                : 10
                : 149
                Affiliations
                [1 ]Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079 USA
                [2 ]School of Biosciences, Phenome Centre Birmingham and Institute of Metabolism and Systems Research (IMSR), University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
                [3 ]Advanced Pattern Analysis and Countermeasures Group, Research Innovation Center, Colorado State University, Fort Collins, CO 80521 USA
                [4 ]Department of Pharmacology, Weill Cornell Medical College, New York, NY 10021 USA
                [5 ]School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
                [6 ]Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Av Diagonal 643, 08028 Barcelona, Spain
                [7 ]Institute of Biomedicine of Universitat de Barcelona (IBUB) and CSIC-Associated Unit, Barcelona, Spain
                [8 ]UCD Institute of Food and Health, UCD, Belfield, Dublin Ireland
                [9 ]Departments of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB Canada
                [10 ]Turku Centre for Biotechnology, University of Turku, Turku, Finland
                [11 ]Division of Analytical Biosciences and Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University & Netherlands Metabolomics Centre, Leiden, The Netherlands
                [12 ]School of Science, Edith Cowan University, Perth, Australia
                [13 ]Center for Environmental Systems Biochemistry, Department Toxicology and Cancer Biology, Markey Cancer Center, Lexington, KY USA
                [14 ]Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Doha, Qatar
                [15 ]Institute of Bioinformatics and Systems Biology, Helmholtz Center Munich, Oberschleißheim, Germany
                [16 ]Discovery Sciences, RTI International, Research Triangle Park, Durham, NC USA
                [17 ]University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Campus Belval, Esch-Sur-Alzette, Luxembourg
                [18 ]West Coast Metabolomics Center, UC Davis, Davis, CA USA
                [19 ]Biochemistry Department, King Abdulaziz University, Jeddah, Saudi Arabia
                [20 ]Psychiatry and Behavioral Sciences, Duke Internal Medicine and Duke Institute for Brain Sciences and Center for Applied Genomics and Precision Medicine, Duke University Medical Center, Box 3903, Durham, NC 27710 USA
                Article
                1094
                10.1007/s11306-016-1094-6
                5009152
                27642271
                9c5d8666-a321-4b49-983f-f39cbb539b83
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 19 July 2016
                : 8 August 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: RC2GM092729
                Award ID: R24 GM 078233
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: 1R01AG046171
                Award Recipient :
                Funded by: National Institutes on Aging
                Award ID: RF1AG051550
                Award Recipient :
                Categories
                Original Article
                Custom metadata
                © Springer Science+Business Media New York 2016

                Molecular biology
                metabolomics,metabonomics,pharmacometabolomics,pharmacometabonomics,precision medicine,personalized medicine

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