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      Application of Metabolomics in Pediatric Asthma: Prediction, Diagnosis and Personalized Treatment

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          Abstract

          Asthma in children remains a significant public health challenge affecting 5–20% of children in Europe and is associated with increased morbidity and societal healthcare costs. The high variation in asthma incidence among countries may be attributed to differences in genetic susceptibility and environmental factors. This respiratory disorder is described as a heterogeneous syndrome of multiple clinical manifestations (phenotypes) with varying degrees of severity and airway hyper-responsiveness, which is based on patient symptoms, lung function and response to pharmacotherapy. However, an accurate diagnosis is often difficult due to diversities in clinical presentation. Therefore, identifying early diagnostic biomarkers and improving the monitoring of airway dysfunction and inflammatory through non-invasive methods are key goals in successful pediatric asthma management. Given that asthma is caused by the interaction between genes and environmental factors, an emerging approach, metabolomics—the systematic analysis of small molecules—can provide more insight into asthma pathophysiological mechanisms, enable the identification of early biomarkers and targeted personalized therapies, thus reducing disease burden and societal cost. The purpose of this review is to present evidence on the utility of metabolomics in pediatric asthma through the analysis of intermediate metabolites of biochemical pathways that involve carbohydrates, amino acids, lipids, organic acids and nucleotides and discuss their potential application in clinical practice. Also, current challenges on the integration of metabolomics in pediatric asthma management and needed next steps are critically discussed.

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          Mitochondrial TCA cycle metabolites control physiology and disease

          Mitochondria are signaling organelles that regulate a wide variety of cellular functions and can dictate cell fate. Multiple mechanisms contribute to communicate mitochondrial fitness to the rest of the cell. Recent evidence confers a new role for TCA cycle intermediates, generally thought to be important for biosynthetic purposes, as signaling molecules with functions controlling chromatin modifications, DNA methylation, the hypoxic response, and immunity. This review summarizes the mechanisms by which the abundance of different TCA cycle metabolites controls cellular function and fate in different contexts. We will focus on how these metabolites mediated signaling can affect physiology and disease.
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            Metabolomics: beyond biomarkers and towards mechanisms.

            Metabolomics, which is the profiling of metabolites in biofluids, cells and tissues, is routinely applied as a tool for biomarker discovery. Owing to innovative developments in informatics and analytical technologies, and the integration of orthogonal biological approaches, it is now possible to expand metabolomic analyses to understand the systems-level effects of metabolites. Moreover, because of the inherent sensitivity of metabolomics, subtle alterations in biological pathways can be detected to provide insight into the mechanisms that underlie various physiological conditions and aberrant processes, including diseases.
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              Metabolite profiles and the risk of developing diabetes.

              Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines and other polar metabolites were profiled in baseline specimens by liquid chromatography-tandem mass spectrometry (LC-MS). Cases and controls were matched for age, body mass index and fasting glucose. Five branched-chain and aromatic amino acids had highly significant associations with future diabetes: isoleucine, leucine, valine, tyrosine and phenylalanine. A combination of three amino acids predicted future diabetes (with a more than fivefold higher risk for individuals in top quartile). The results were replicated in an independent, prospective cohort. These findings underscore the potential key role of amino acid metabolism early in the pathogenesis of diabetes and suggest that amino acid profiles could aid in diabetes risk assessment.
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Metabolites
                Metabolites
                metabolites
                Metabolites
                MDPI
                2218-1989
                18 April 2021
                April 2021
                : 11
                : 4
                : 251
                Affiliations
                [1 ]Department of Dietetics, Human Nutrition & Sport, School of Allied Health, Human Services & Sport, La Trobe University, Melbourne 3086, Australia
                [2 ]European Institute of Nutritional Medicine, 00198 Rome, Italy; dtsoukalas@ 123456einum.org
                [3 ]Department of Experimental Physiology, Medical School, National & Kapodistrian University of Athens, 11527 Athens, Greece; katsardis@ 123456yahoo.gr
                [4 ]Metabolomic Medicine, Health Clinic for Autoimmune and Chronic Diseases, 10674 Athens, Greece; esarandi6@ 123456hotmail.com (E.S.); sl.georgaki@ 123456gmail.com (S.G.)
                [5 ]Laboratory of Toxicology and Forensic Sciences, Medical School, University of Crete, 71003 Heraklion, Greece
                [6 ]Department of Pediatrics, School of Medicine, University of Patras, 26500 Patras, Greece; eirinifrima@ 123456gmail.com (E.-S.F.); nata-var@ 123456med.upatras.gr (A.V.)
                Author notes
                [* ]Correspondence: sassipap@ 123456hotmail.com
                Author information
                https://orcid.org/0000-0003-1169-7141
                https://orcid.org/0000-0003-2272-5689
                https://orcid.org/0000-0001-6885-6209
                Article
                metabolites-11-00251
                10.3390/metabo11040251
                8072856
                33919626
                878a104d-16ce-471f-9bc7-427f06e8abcf
                © 2021 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 ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 23 February 2021
                : 15 April 2021
                Categories
                Review

                asthma,asthma phenotypes,pediatric,metabolomics,biomarkers
                asthma, asthma phenotypes, pediatric, metabolomics, biomarkers

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