Literature DB >> 24321733

Metabolomics in diabetes.

Ai-hua Zhang1, Shi Qiu1, Hong-ying Xu1, Hui Sun1, Xi-jun Wang2.   

Abstract

Characterization of metabolic changes is key to early detection, treatment, and understanding molecular mechanisms of diabetes. Diabetes represents one of the most important global health problems. Approximately 90% of diabetics have type 2 diabetes. Identification of effective screening markers is critical for early treatment and intervention that can delay and/or prevent complications associated with this chronic disease. Fortunately, metabolomics has introduced new insights into the pathology of diabetes as well as to predict disease onset and revealed new biomarkers to improve diagnostics in a range of diseases. Small-molecule metabolites have an important role in biological systems and represent attractive candidates to understand T2D phenotypes. Characteristic patterns of metabolites can be revealed that broaden our understanding of T2D disorder. This technique-driven review aims to demystify the mechanisms of T2D, to provide updates on the applications of metabolomics in addressing T2D with a focus on metabolites based biomarker discovery.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biomarkers; Diabetes; Diagnosis; Metabolites; Metabolomics

Mesh:

Substances:

Year:  2013        PMID: 24321733     DOI: 10.1016/j.cca.2013.11.037

Source DB:  PubMed          Journal:  Clin Chim Acta        ISSN: 0009-8981            Impact factor:   3.786


  23 in total

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Authors:  Andreas Pfützner
Journal:  J Diabetes Sci Technol       Date:  2014-11-26

2.  Omics, big data and machine learning as tools to propel understanding of biological mechanisms and to discover novel diagnostics and therapeutics.

Authors:  Nikolaos Perakakis; Alireza Yazdani; George E Karniadakis; Christos Mantzoros
Journal:  Metabolism       Date:  2018-08-08       Impact factor: 8.694

3.  Antibiotics-mediated intestinal microbiome perturbation aggravates tacrolimus-induced glucose disorders in mice.

Authors:  Yuqiu Han; Xiangyang Jiang; Qi Ling; Li Wu; Pin Wu; Ruiqi Tang; Xiaowei Xu; Meifang Yang; Lijiang Zhang; Weiwei Zhu; Baohong Wang; Lanjuan Li
Journal:  Front Med       Date:  2019-05-02       Impact factor: 4.592

4.  Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors.

Authors:  Vannina G Marrachelli; Pilar Rentero; María L Mansego; Jose Manuel Morales; Inma Galan; Mercedes Pardo-Tendero; Fernando Martinez; Juan Carlos Martin-Escudero; Laisa Briongos; Felipe Javier Chaves; Josep Redon; Daniel Monleon
Journal:  PLoS One       Date:  2016-09-02       Impact factor: 3.240

5.  Effect of Cosmos caudatus (Ulam raja) supplementation in patients with type 2 diabetes: Study protocol for a randomized controlled trial.

Authors:  Shi-Hui Cheng; Amin Ismail; Joseph Anthony; Ooi Chuan Ng; Azizah Abdul Hamid; Barakatun-Nisak Mohd Yusof
Journal:  BMC Complement Altern Med       Date:  2016-02-27       Impact factor: 3.659

6.  Metabolic fingerprinting to understand therapeutic effects and mechanisms of silybin on acute liver damage in rat.

Authors:  Qun Liang; Cong Wang; Binbing Li; Ai-Hua Zhang
Journal:  Pharmacogn Mag       Date:  2015 Jul-Sep       Impact factor: 1.085

7.  Lipidomic and metabolomic characterization of a genetically modified mouse model of the early stages of human type 1 diabetes pathogenesis.

Authors:  Anne Julie Overgaard; Jacquelyn M Weir; David Peter De Souza; Dedreia Tull; Claus Haase; Peter J Meikle; Flemming Pociot
Journal:  Metabolomics       Date:  2015-11-17       Impact factor: 4.290

8.  Genomics and Metabolomics in Obesity and Type 2 Diabetes.

Authors:  Adam Kretowski; Francisco J Ruperez; Michal Ciborowski
Journal:  J Diabetes Res       Date:  2016-05-25       Impact factor: 4.011

9.  Three plasma metabolite signatures for diagnosing high altitude pulmonary edema.

Authors:  Li Guo; Guangguo Tan; Ping Liu; Huijie Li; Lulu Tang; Lan Huang; Qian Ren
Journal:  Sci Rep       Date:  2015-10-13       Impact factor: 4.379

Review 10.  Chromatography/Mass Spectrometry-Based Biomarkers in the Field of Obstructive Sleep Apnea.

Authors:  Huajun Xu; Xiaojiao Zheng; Wei Jia; Shankai Yin
Journal:  Medicine (Baltimore)       Date:  2015-10       Impact factor: 1.817

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