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      Contributions of amino acid, acylcarnitine and sphingolipid profiles to type 2 diabetes risk among South-Asian Surinamese and Dutch adults

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          Abstract

          Introduction

          People of South Asian origin are at high risk of type 2 diabetes (T2D), but the underpinning mechanisms are not fully understood. We determined ethnic differences in acylcarnitine, amino acid and sphingolipid concentrations and determined the associations with T2D.

          Research design and methods

          Associations between these metabolites and incident T2D among Dutch and South-Asian Surinamese were determined in participants from the Healthy Life in an Urban Setting (HELIUS) study (Amsterdam, the Netherlands) using Prentice-weighted Cox regression. The HELIUS study includes 95 incident T2D cases and a representative subcohort of 700 people from a cohort of 5977 participants with a mean follow-up of 4 years.

          Results

          Concentrations of acylcarnitines were comparable between both ethnic groups. Amino acid and lactosylceramide concentrations were higher among South-Asian Surinamese than Dutch (eg, isoleucine 65.7 (SD 16.3) vs 60.7 (SD 15.6) µmol/L). Ceramide concentrations were lower among South-Asian Surinamese than Dutch (eg, Cer d18:1 8.48 (SD 2.04) vs 9.08 (SD 2.29) µmol/L). Metabolic dysregulation preceded T2D without evidence for a multiplicative interaction by ethnicity. Most amino acids and (dihydro)ceramides were associated with increased risk (eg, Cer d18:1 HR 2.38, 95% CI 1.81 to 3.12) while acylcarnitines, glycine, glutamine and lactosylceramides were associated with decreased risk for T2D (eg, LacCer d18:2 HR 0.56, 95% CI 0.42 to 0.77).

          Conclusions

          Overall, these data suggest that the disturbances underlying amino acid and sphingolipid metabolism may be predictive of T2D risk in populations of both South Asian and European background. These observations may be used as starting point to unravel the underlying metabolic disturbances.

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          Most cited references25

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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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            Increased levels of plasma acylcarnitines in obesity and type 2 diabetes and identification of a marker of glucolipotoxicity.

            Dysregulation of fatty acid oxidation (FAO) is recognized as important in the pathophysiology of obesity and insulin resistance (IR). However, demonstrating FAO defects in vivo in humans has entailed complex and invasive methodologies. Recently, the identification of genetic blocks in FAO has been vastly simplified by using tandem mass spectrometry (MS/MS) of dried bloodspots to specify acylcarnitine (AcylCN) alterations characteristic for each disorder. This technology has recently been applied to examine FAO alterations in human and animal models of obesity and type 2 diabetes mellitus (T2DM). This study focused on characterizing AcylCN profiles in human plasma from individuals with obesity and T2DM during fasting and insulin-stimulated conditions. Following an overnight fast, plasma was obtained from lean (n = 12), obese nondiabetic (n = 14), and T2DM (n = 10) participants and analyzed for AcylCN using MS/MS. Plasma samples were also obtained at the end of a 4-h insulin-stimulated euglycemic clamp. In obesity and T2DM, long-chain AcylCNs were similarly significantly increased in the fasted state; free-CN levels were also elevated. Additionally, T2DM subjects of comparable BMI had increased short- and medium-chain AcylCNs, both saturated and hydroxy, as well as increased C(4)-dicarboxylcarnitine (C(4)DC-CN) that correlated with an index of poor glycemic control (HbA(1c); r = 0.74; P < 0.0001). Insulin infusion reduced all species of plasma AcylCN but this reduction was blunted in T2DM. Plasma long-chain AcylCN species are increased in obesity and T2DM, suggesting that more fatty acids can enter mitochondria. In T2DM, many shorter species accumulate, suggesting that they have a generalized complex oxidation defect.
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              Increased rate of gluconeogenesis in type II diabetes mellitus. A 13C nuclear magnetic resonance study.

              To quantitate hepatic glycogenolysis, liver glycogen concentration was measured with 13C nuclear magnetic resonance spectroscopy in seven type II diabetic and five control subjects during 23 h of fasting. Net hepatic glycogenolysis was calculated by multiplying the rate of glycogen breakdown by the liver volume, determined from magnetic resonance images. Gluconeogenesis was calculated by subtracting the rate of hepatic glycogenolysis from the whole body glucose production rate, measured using [6-3H]glucose. Liver glycogen concentration 4 h after a meal was lower in the diabetics than in the controls; 131 +/- 20 versus 282 +/- 60 mmol/liter liver (P < 0.05). Net hepatic glycogenolysis was decreased in the diabetics, 1.3 +/- 0.2 as compared to 2.8 +/- 0.7 mumol/(kg body wt x min) in the controls (P < 0.05). Whole body glucose production was increased in the diabetics as compared to the controls, 11.1 +/- 0.6 versus 8.9 +/- 0.5 mumol/(kg body wt x min) (P < 0.05). Gluconeogenesis was consequently increased in the diabetics, 9.8 +/- 0.7 as compared to 6.1 +/- 0.5 mumol/(kg body wt x min) in the controls (P < 0.01), and accounted for 88 +/- 2% of total glucose production as compared with 70 +/- 6% in the controls (P < 0.05). increased gluconeogenesis is responsible for the increased whole body glucose production in type II diabetes mellitus after an overnight fast.
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                Author and article information

                Journal
                BMJ Open Diabetes Res Care
                BMJ Open Diabetes Res Care
                bmjdrc
                bmjdrc
                BMJ Open Diabetes Research & Care
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2052-4897
                2020
                5 May 2020
                : 8
                : 1
                : e001003
                Affiliations
                [1 ]departmentDepartment of Public Health, Amsterdam Public Health Research Institute , Amsterdam UMC, University of Amsterdam , Amsterdam, The Netherlands
                [2 ]departmentLaboratory Genetic Metabolic Diseases , Amsterdam UMC, University of Amsterdam , Amsterdam, The Netherlands
                [3 ]departmentBHF Glasgow Cardiovascular Research Centre , Institute of Cardiovascular and Medical Sciences, University of Glasgow , Glasgow, UK
                [4 ]departmentDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics , Amsterdam UMC, University of Amsterdam , Amsterdam, The Netherlands
                Author notes
                [Correspondence to ] Dr Mirthe Muilwijk; m.muilwijk@ 123456amsterdamumc.nl
                Author information
                http://orcid.org/0000-0002-3686-5116
                http://orcid.org/0000-0003-2612-3917
                Article
                bmjdrc-2019-001003
                10.1136/bmjdrc-2019-001003
                7228466
                32376636
                ba6913b7-e063-491f-a44e-ae0765936200
                © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/.

                History
                : 24 October 2019
                : 19 February 2020
                : 06 April 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001826, ZonMw;
                Funded by: European Fund for the Integration of non-EU immigrants (EIF);
                Funded by: European Union FP-7;
                Funded by: FundRef http://dx.doi.org/10.13039/501100002996, Hartstichting;
                Funded by: European Union, Health programme 2014-2020;
                Award ID: 664609 HP-PJ-2014
                Categories
                Epidemiology/Health Services Research
                1506
                1867
                Custom metadata
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                metabolism,epidemiology,ethnic differences,type 2 diabetes

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