Literature DB >> 29239245

Serum and plasma amino acids as markers of prediabetes, insulin resistance, and incident diabetes.

C Gar1,2,3, M Rottenkolber1,2,3, C Prehn4, J Adamski3,4,5, J Seissler1,2,3, A Lechner1,2,3.   

Abstract

Presently, routine screening misses many cases of prediabetes and early type 2 diabetes (T2D). Therefore, better biomarkers are needed for a simple and early detection of abnormalities of glucose metabolism and prediction of future T2D. Possible candidates for this include plasma or serum amino acids because glucose and amino acid metabolism are closely connected. This review presents the available evidence of this connectivity and discusses its clinical implications. First, we examine the underlying physiological, pre-analytical, and analytical issues. Then, we summarize results of human studies that evaluate amino acid levels as markers for insulin resistance, prediabetes, and future incident T2D. Finally, we illustrate the interconnection of amino acid levels and metabolic syndrome with our own data from a deeply phenotyped human cohort. We also discuss how amino acids may contribute to the pathophysiology of T2D. We conclude that elevated branched-chain amino acids and reduced glycine are currently the most robust and consistent amino acid markers for prediabetes, insulin resistance, and future T2D. Yet, we are cautious regarding the clinical potential even of these parameters because their discriminatory power is insufficient and their levels depend not only on glycemia, but also on other components of the metabolic syndrome. The identification of more precise intermediates of amino acid metabolism or combinations with other biomarkers will, therefore, be necessary to obtain in order to develop laboratory tests that can improve T2D screening.

Entities:  

Keywords:  Metabolomics; biomarker panel; metabolism; prediction

Mesh:

Substances:

Year:  2017        PMID: 29239245     DOI: 10.1080/10408363.2017.1414143

Source DB:  PubMed          Journal:  Crit Rev Clin Lab Sci        ISSN: 1040-8363            Impact factor:   6.250


  31 in total

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3.  Metabolomic Analysis of Serum and Tear Samples from Patients with Obesity and Type 2 Diabetes Mellitus.

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Journal:  Int J Mol Sci       Date:  2022-04-20       Impact factor: 6.208

4.  Plasma Metabolic Signatures of Healthy Overweight Subjects Challenged With an Oral Glucose Tolerance Test.

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Journal:  Front Nutr       Date:  2022-06-14

5.  Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children.

Authors:  Sergey A Krupenko; Shelley A Cole; Ruixue Hou; Karin Haack; Sandra Laston; Nitesh R Mehta; Anthony G Comuzzie; Nancy F Butte; V Saroja Voruganti
Journal:  Am J Clin Nutr       Date:  2022-08-04       Impact factor: 8.472

6.  Untargeted metabolomic analysis in non-fasted diabetic dogs by UHPLC-HRMS.

Authors:  A L O'Kell; T J Garrett; C Wasserfall; M A Atkinson
Journal:  Metabolomics       Date:  2019-01-22       Impact factor: 4.290

7.  Visceral Adipose Tissue Displays Unique Metabolomic Fingerprints in Obesity, Pre-Diabetes and Type 2 Diabetes.

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Journal:  Int J Mol Sci       Date:  2021-05-27       Impact factor: 5.923

8.  Identification of Dysregulated Complement Activation Pathways Driven by N-Glycosylation Alterations in T2D Patients.

Authors:  Yang Zhao; Man Wang; Bo Meng; Ying Gao; Zhichao Xue; Minjun He; You Jiang; Xinhua Dai; Dan Yan; Xiang Fang
Journal:  Front Chem       Date:  2021-06-11       Impact factor: 5.221

9.  CMap analysis identifies Atractyloside as a potential drug candidate for type 2 diabetes based on integration of metabolomics and transcriptomics.

Authors:  Hailong Li; Xiaodong Shi; Hua Jiang; Junren Kang; Miao Yu; Qifei Li; Kang Yu; Zhengju Chen; Hui Pan; Wei Chen
Journal:  J Cell Mol Med       Date:  2020-05-29       Impact factor: 5.310

10.  Methionine Partially Replaced by Methionyl-Methionine Dipeptide Improves Reproductive Performance over Methionine Alone in Methionine-Deficient Mice.

Authors:  Qiong Chen; Wenting Dai; Yalu Sun; Fengqi Zhao; Jianxin Liu; Hongyun Liu
Journal:  Nutrients       Date:  2018-09-01       Impact factor: 5.717

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