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      Relation of Whole Blood Amino Acid and Acylcarnitine Metabolome to Age, Sex, BMI, Puberty, and Metabolic Markers in Children and Adolescents

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          Abstract

          Background: Changes in the metabolic fingerprint of blood during child growth and development are a largely under-investigated area of research. The examination of such aspects requires a cohort of healthy children and adolescents who have been subjected to deep phenotyping, including collection of biospecimens for metabolomic analysis. The present study considered whether amino acid (AA) and acylcarnitine (AC) concentrations are associated with age, sex, body mass index (BMI), and puberty during childhood and adolescence. It also investigated whether there are associations between amino acids (AAs) and acylcarnitines (ACs) and laboratory parameters of glucose and lipid metabolism, as well as liver, kidney, and thyroid parameters. Methods: A total of 3989 dried whole blood samples collected from 2191 healthy participants, aged 3 months to 18 years, from the LIFE Child cohort (Leipzig, Germany) were analyzed using liquid chromatography tandem mass spectrometry to detect levels of 23 AAs, 6 ACs, and free carnitine (C0). Age- and sex-related percentiles were estimated for each metabolite. In addition, correlations between laboratory parameters and levels of the selected AAs and ACs were calculated using hierarchical models. Results: Four different age-dependent profile types were identified for AAs and ACs. Investigating the association with puberty, we mainly identified peak metabolite levels at Tanner stages 2 to 3 in girls and stages 3 to 5 in boys. Significant correlations were observed between BMI standard deviation score (BMI-SDS) and certain metabolites, among them, branched-chain (leucine/isoleucine, valine) and aromatic (phenylalanine, tyrosine) amino acids. Most of the metabolites correlated significantly with absolute concentrations of glucose, glycated hemoglobin (HbA1c), triglycerides, cystatin C (CysC), and creatinine. After age adjustment, significant correlations were observed between most metabolites and CysC, as well as HbA1c. Conclusions: During childhood, several AA and AC levels are related to age, sex, BMI, and puberty. Moreover, our data verified known associations but also revealed new correlations between AAs/ACs and specific key markers of metabolic function.

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          Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis

          OBJECTIVE To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes. RESEARCH DESIGN AND METHODS We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite. RESULTS We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24–1.48]; I 2 = 9.5%), 36% for leucine (1.36 [1.17–1.58]; I 2 = 37.4%), 35% for valine (1.35 [1.19–1.53]; I 2 = 45.8%), 36% for tyrosine (1.36 [1.19–1.55]; I 2 = 51.6%), and 26% for phenylalanine (1.26 [1.10–1.44]; I 2 = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81–0.96] and 0.85 [0.82–0.89], respectively; both I 2 = 0.0%). CONCLUSIONS In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.
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            Plasma amino acid levels and insulin secretion in obesity.

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              Relationships Between Circulating Metabolic Intermediates and Insulin Action in Overweight to Obese, Inactive Men and Women

              OBJECTIVE To determine whether circulating metabolic intermediates are related to insulin resistance and β-cell dysfunction in individuals at risk for type 2 diabetes. RESEARCH DESIGN AND METHODS In 73 sedentary, overweight to obese, dyslipidemic individuals, insulin action was derived from a frequently sampled intravenous glucose tolerance test. Plasma concentrations of 75 amino acids, acylcarnitines, free fatty acids, and conventional metabolites were measured with a targeted, mass spectrometry–based platform. Principal components analysis followed by backward stepwise linear regression was used to explore relationships between measures of insulin action and metabolic intermediates. RESULTS The 75 metabolic intermediates clustered into 19 factors comprising biologically related intermediates. A factor containing large neutral amino acids was inversely related to insulin sensitivity (S I) (R 2 = 0.26). A factor containing fatty acids was inversely related to the acute insulin response to glucose (R 2 = 0.12). Both of these factors, age, and a factor containing medium-chain acylcarnitines and glucose were inversely and independently related to the disposition index (DI) (R 2 = 0.39). Sex differences were found for metabolic predictors of S I and DI. CONCLUSIONS In addition to the well-recognized risks for insulin resistance, elevated concentrations of large, neutral amino acids were independently associated with insulin resistance. Fatty acids were inversely related to the pancreatic response to glucose. Both large neutral amino acids and fatty acids were related to an appropriate pancreatic response, suggesting that these metabolic intermediates might play a role in the progression to type 2 diabetes, one by contributing to insulin resistance and the other to pancreatic failure. These intermediates might exert sex-specific effects on insulin action.
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                Author and article information

                Journal
                Metabolites
                Metabolites
                metabolites
                Metabolites
                MDPI
                2218-1989
                10 April 2020
                April 2020
                : 10
                : 4
                : 149
                Affiliations
                [1 ]LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Philipp-Rosenthal-Strasse 27, 04103 Leipzig, Germany; Josephin.Hirschel@ 123456medizin.uni-leipzig.de (J.H.); Mandy.Vogel@ 123456medizin.uni-leipzig.de (M.V.); Ronny.Baber@ 123456medizin.uni-leipzig.de (R.B.); Yvonne.Dietz@ 123456medizin.uni-leipzig.de (Y.D.); Antje.Koerner@ 123456medizin.uni-leipzig.de (A.K.); Wieland.Kiess@ 123456medizin.uni-leipzig.de (W.K.)
                [2 ]Hospital for Children and Adolescents and Center for Pediatric Research (CPL), University of Leipzig, Liebigstrasse 20a, 04103 Leipzig, Germany; Antje.Garten@ 123456medizin.uni-leipzig.de
                [3 ]Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics (ILM), University Hospital Leipzig, Paul-List Str.13/15, 04103 Leipzig, Germany; Julia.Dittrich@ 123456medizin.uni-leipzig.de
                [4 ]Institute of Metabolism and Systems Research, University of Birmingham, Birmingham B15 2TT, UK
                [5 ]Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Härtelstrasse 16-18, 04107 Leipzig, Germany; cfbeuchel@ 123456imise.uni-leipzig.de
                Author notes
                Author information
                https://orcid.org/0000-0002-5354-287X
                https://orcid.org/0000-0001-6001-0356
                Article
                metabolites-10-00149
                10.3390/metabo10040149
                7240971
                32290284
                de85785e-3159-4f9a-88a0-cc46d0adf3d4
                © 2020 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
                : 20 March 2020
                : 08 April 2020
                Categories
                Article

                pediatrics,amino acids,acylcarnitines,metabolomics,dried blood,tandem mass spectrometry

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