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      Metabolic Fingerprint of Chronic Obstructive Lung Diseases: A New Diagnostic Perspective

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          Abstract

          Chronic obstructive lung disease (COLD) is a group of airway diseases, previously known as emphysema and chronic bronchitis. The heterogeneity of COLD does not allow early diagnosis and leads to increased morbidity and mortality. The increasing number of COLD incidences stresses the need for precision medicine approaches that are specific to the patient. Metabolomics is an emerging technology that allows for the discrimination of metabolic changes in the cell as a result of environmental factors and specific genetic background. Thus, quantification of metabolites in human biofluids can provide insights into the metabolic state of the individual in real time and unravel the presence of, or predisposition to, a disease. In this article, the advantages of and potential barriers to putting metabolomics into clinical practice for COLD are discussed. Today, metabolomics is mostly lab-based, and research studies with novel COLD-specific biomarkers are continuously being published. Several obstacles in the research and the market field hamper the translation of these data into clinical practice. However, technological and computational advances will facilitate the clinical interpretation of data and provide healthcare professionals with the tools to prevent, diagnose, and treat COLD with precision in the coming decades.

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          Pharmaco-metabonomic phenotyping and personalized drug treatment.

          There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.
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            Targeted metabolomics.

            The metabolome is the terminal downstream product of the genome and consists of the total complement of all the low-molecular-weight molecules (metabolites) in a cell, tissue, or organism. Metabolomics aims to measure a wide breadth of small molecules in the context of physiological stimuli or disease states. Metabolomics methodologies fall into two distinct groups: untargeted metabolomics, an intended comprehensive analysis of all the measurable analytes in a sample including chemical unknowns, and targeted metabolomics, the measurement of defined groups of chemically characterized and biochemically annotated metabolites. The methodologies considered in this unit focus on the processes of conducting targeted metabolomics experiments, and the advantages of this general approach are highlighted herein. This unit outlines procedures for extracting nitrogenous metabolites (including amino acids), lipids, and intermediary metabolites (including TCA cycle oxoacids) from blood plasma. Specifically, protocols are described for analyzing these metabolites using targeted metabolomics experiments based on liquid chromatography-mass spectrometry. © 2012 by John Wiley & Sons, Inc.
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              Metabolomics: an emerging but powerful tool for precision medicine

              Metabolomics, which is defined as the comprehensive analysis of metabolites in a biological specimen, is an emerging technology that holds promise to inform the practice of precision medicine. Historically, small numbers of metabolites have been used to diagnose complex metabolic diseases as well as monogenic disorders such as inborn errors of metabolism. Current metabolomic technologies go well beyond the scope of standard clinical chemistry techniques and are capable of precise analyses of hundreds to thousands of metabolites. Consequently, metabolomics affords detailed characterization of metabolic phenotypes and can enable precision medicine at a number of levels, including the characterization of metabolic derangements that underlie disease, discovery of new therapeutic targets, and discovery of biomarkers that may be used to either diagnose disease or monitor activity of therapeutics.
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                Author and article information

                Journal
                Metabolites
                Metabolites
                metabolites
                Metabolites
                MDPI
                2218-1989
                26 November 2019
                December 2019
                : 9
                : 12
                : 290
                Affiliations
                [1 ]Department of Clinical Pharmacy, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania; calinadaniela@ 123456gmail.com
                [2 ]Metabolomic Medicine Clinic, Health Clinics for Autoimmune and Chronic Diseases, 10674 Athens, Greece; research@ 123456metabolomicmedicine.com (E.S.); mariathanasoula84@ 123456gmail.com (M.T.); clinic@ 123456drtsoukalas.com (G.T.)
                [3 ]Laboratory of Toxicology and Forensic Sciences, Medical School, University of Crete, 71003 Heraklion, Greece; tsatsaka@ 123456uoc.gr
                [4 ]Department of Toxicology, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania; daoana00@ 123456gmail.com
                Author notes
                [* ]Correspondence: dtsoukalas@ 123456einum.org ; Tel.: +30-21-0361-1054
                Author information
                https://orcid.org/0000-0001-6885-6209
                https://orcid.org/0000-0002-1523-9116
                https://orcid.org/0000-0003-3824-2462
                Article
                metabolites-09-00290
                10.3390/metabo9120290
                6949962
                31779131
                f574042f-4d94-4b79-bd18-68ab3c7fcbc5
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 02 October 2019
                : 20 November 2019
                Categories
                Communication

                cold,metabolomics,precision medicine,biomarkers
                cold, metabolomics, precision medicine, biomarkers

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