Journal article

Metabolomic analysis of insulin resistance across different mouse strains and diets

Jacqueline Stockli, Kelsey H Fisher-Wellman, Rima Chaudhuri, Xiao-Yi Zeng, Daniel J Fazakerley, Christopher C Meoli, Kristen C Thomas, Nolan J Hoffman, Salvatore P Mangiafico, Chrysovalantou E Xirouchaki, Chieh-Hsin Yang, Olga Ilkayeva, Kari Wong, Gregory J Cooney, Sofianos Andrikopoulos, Deborah M Muoio, David E James

JOURNAL OF BIOLOGICAL CHEMISTRY | AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC | Published : 2017

Abstract

Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolite..

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University of Melbourne Researchers

Grants

Awarded by National Health and Medical Research Council (NHMRC)


Awarded by National Institutes of Health


Awarded by National Institutes of Health F32 Fellowship


Awarded by NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES


Funding Acknowledgements

This work was supported in part by National Health and Medical Research Council (NHMRC) Project Grants GNT1061122, GNT1086851, and GNT1086850 (to D. E. J.) and National Institutes of Health Grants 2R01DK089312 and 2P01-DK058398 (to D. M. M.). The authors declare that they have no conflicts of interest with the contents of this article. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or NHMRC.Supported by National Institutes of Health F32 Fellowship 1F32DK105665-01A1.