Literature DB >> 21426036

¹H NMR-based metabonomics for investigating diabetes.

Anthony D Maher1, John C Lindon, Jeremy K Nicholson.   

Abstract

Diabetes is characterized by hyperglycemia due to dysfunction of insulin secretion or action. The two most common forms are Type 1 diabetes, in which pancreatic β-cells are destroyed, and Type 2 diabetes, in which a combination of disordered insulin action and secretion results in abnormal carbohydrate, lipid and protein metabolism. Metabonomics employs analytical technologies to measure 'global' metabolic responses to a disease state. With the aid of statistical pattern recognition, this can reveal novel insights into the biochemical consequences of diabetes. The metabonomic method can be divided into four stages: sample collection; preparation; data acquisition and processing; and statistical analyses. In this review, we describe the most recent developments at each experimental stage in detail, and comment on specific precautions or improvements that should be taken into account when studying diabetes. Finally, we end with speculations as to where and how the field will develop in the future. Metabonomics provides a logical framework for understanding the global metabolic effects of diabetes. Continuing technological improvements will expand our knowledge of the causes and progression of this disease, and enhance treatment options for individuals.

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Year:  2009        PMID: 21426036     DOI: 10.4155/fmc.09.54

Source DB:  PubMed          Journal:  Future Med Chem        ISSN: 1756-8919            Impact factor:   3.808


  14 in total

1.  Metabolomics study of type 2 diabetes using ultra-performance LC-ESI/quadrupole-TOF high-definition MS coupled with pattern recognition methods.

Authors:  Ai-hua Zhang; Hui Sun; Guang-li Yan; Ye Yuan; Ying Han; Xi-jun Wang
Journal:  J Physiol Biochem       Date:  2013-08-24       Impact factor: 4.158

2.  Ancient Wheat Diet Delays Diabetes Development in a Type 2 Diabetes Animal Model.

Authors:  Anne Cathrine Thorup; Søren Gregersen; Per Bendix Jeppesen
Journal:  Rev Diabet Stud       Date:  2015-02-10

Review 3.  Risk factors and biomarkers of age-related macular degeneration.

Authors:  Nathan G Lambert; Hanan ElShelmani; Malkit K Singh; Fiona C Mansergh; Michael A Wride; Maximilian Padilla; David Keegan; Ruth E Hogg; Balamurali K Ambati
Journal:  Prog Retin Eye Res       Date:  2016-05-06       Impact factor: 21.198

Review 4.  Applications of NMR spectroscopy to systems biochemistry.

Authors:  Teresa W-M Fan; Andrew N Lane
Journal:  Prog Nucl Magn Reson Spectrosc       Date:  2016-02-06       Impact factor: 9.795

5.  NMR Metabolomics Analysis of Parkinson's Disease.

Authors:  Shulei Lei; Robert Powers
Journal:  Curr Metabolomics       Date:  2013

6.  Biomarker Discovery and Translation in Metabolomics.

Authors:  G A Nagana Gowda; D Raftery
Journal:  Curr Metabolomics       Date:  2013

7.  Metabolic Profiling of Green Tea Treatments in Zucker Diabetic Rats Using 1H NMR.

Authors:  Shucha Zhang; Angela Myracle; Ke Xiao; Ping Yan; Tao Ye; Elsa Janle; Daniel Raftery
Journal:  J Nutr Food Sci       Date:  2013-11-11

8.  Satiety hormone and metabolomic response to an intermittent high energy diet differs in rats consuming long-term diets high in protein or prebiotic fiber.

Authors:  Raylene A Reimer; Alannah D Maurer; Lindsay K Eller; Megan C Hallam; Rustem Shaykhutdinov; Hans J Vogel; Aalim M Weljie
Journal:  J Proteome Res       Date:  2012-07-23       Impact factor: 4.466

9.  A Metabolomics Profiling Study in Hand-Foot-and-Mouth Disease and Modulated Pathways of Clinical Intervention Using Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry.

Authors:  Cheng Lu; Xinru Liu; Xiaorong Ding; Xiao Chen; Haiwei Fan; Yunqiang Liu; Ning Xie; Yong Tan; Joshua Ko; Weidong Zhang; Aiping Lu
Journal:  Evid Based Complement Alternat Med       Date:  2013-02-19       Impact factor: 2.629

10.  NMR-based metabolomics of urine in a mouse model of Alzheimer's disease: identification of oxidative stress biomarkers.

Authors:  Kiyoshi Fukuhara; Akiko Ohno; Yosuke Ota; Yuya Senoo; Keiko Maekawa; Haruhiro Okuda; Masaaki Kurihara; Alato Okuno; Shumpei Niida; Yoshiro Saito; Osamu Takikawa
Journal:  J Clin Biochem Nutr       Date:  2013-03-01       Impact factor: 3.114

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