Literature DB >> 27913577

Metabolite Profiling of LADA Challenges the View of a Metabolically Distinct Subtype.

Mahmoud Al-Majdoub1, Arslan Ali1,2, Petter Storm3, Anders H Rosengren4, Leif Groop1,5, Peter Spégel6,7.   

Abstract

Latent autoimmune diabetes in adults (LADA) usually refers to GAD65 autoantibodies (GADAb)-positive diabetes with onset after 35 years of age and no insulin treatment within the first 6 months after diagnosis. However, it is not always easy to distinguish LADA from type 1 or type 2 diabetes. In this study, we examined whether metabolite profiling could help to distinguish LADA (n = 50) from type 1 diabetes (n = 50) and type 2 diabetes (n = 50). Of 123 identified metabolites, 99 differed between the diabetes types. However, no unique metabolite profile could be identified for any of the types. Instead, the metabolome varied along a C-peptide-driven continuum from type 1 diabetes via LADA to type 2 diabetes. LADA was more similar to type 2 diabetes than to type 1 diabetes. In a principal component analysis, LADA patients overlapping with type 1 diabetes progressed faster to insulin therapy than those overlapping with type 2 diabetes. In conclusion, we could not find any unique metabolite profile distinguishing LADA from type 1 and type 2 diabetes. Rather, LADA was metabolically an intermediate of type 1 and type 2 diabetes, with those patients closer to the former showing a faster progression to insulin therapy than those closer to the latter.
© 2017 by the American Diabetes Association.

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Year:  2016        PMID: 27913577     DOI: 10.2337/db16-0779

Source DB:  PubMed          Journal:  Diabetes        ISSN: 0012-1797            Impact factor:   9.461


  3 in total

1.  Fatty Acid Profiles and Their Association With Autoimmunity, Insulin Sensitivity and β Cell Function in Latent Autoimmune Diabetes in Adults.

Authors:  Huiqin Tian; Shiqi Wang; Yating Deng; Yanke Xing; Lin Zhao; Xia Zhang; Ping Zhang; Nan Liu; Benli Su
Journal:  Front Endocrinol (Lausanne)       Date:  2022-06-29       Impact factor: 6.055

2.  The induction of the fibroblast extracellular senescence metabolome is a dynamic process.

Authors:  Emma N L James; Mark H Bennett; E Kenneth Parkinson
Journal:  Sci Rep       Date:  2018-08-14       Impact factor: 4.379

3.  Population-Level Analysis to Determine Parameters That Drive Variation in the Plasma Metabolite Profiles.

Authors:  Mahmoud Al-Majdoub; Katharina Herzog; Bledar Daka; Martin Magnusson; Lennart Råstam; Ulf Lindblad; Peter Spégel
Journal:  Metabolites       Date:  2018-11-15
  3 in total

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