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The search for predictive metabolic biomarkers for incident T2DM

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A recent metabolomics study of plasma samples from normoglycaemic individuals has identified new predictive biomarkers for type 2 diabetes mellitus. The biomarkers described by the authors demonstrate a potential causal connection between changes in glycine and phenylalanine and incident diabetes mellitus.

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References

  1. Merino, J. et al. Metabolomics insights into early type 2 diabetes pathogenesis and detection in individuals with normal fasting glucose. Diabetologia 61, 1315–1324 (2018).

    Article  PubMed  CAS  Google Scholar 

  2. Noble, D., Mathur, R., Dent, T., Meads, C. & Greenhalgh, T. Risk models and scores for type 2 diabetes: systematic review. BMJ 343, d7163 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Herder, C., Kowall, B., Tabak, A. G. & Rathmann, W. The potential of novel biomarkers to improve risk prediction of type 2 diabetes. Diabetologia 57, 16–29 (2014).

    Article  PubMed  CAS  Google Scholar 

  4. Gall, W. E. et al. a-Hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population. PLoS ONE 5, e10883 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Newgard, C. B. et al. A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell. Metabolism 9, 311–326 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Lotta, L. A. et al. Genetic predisposition to an impaired metabolism of the branched-chain amino acids and risk of type 2 diabetes: a Mendelian randomisation analysis. PLoS Med. 13, e1002179 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Talmud, P. J. et al. Sixty-five common genetic variants and prediction of type 2 diabetes. Diabetes 64, 1830–1840 (2015).

    Article  PubMed  CAS  Google Scholar 

  8. Wang-Sattler, R. et al. Novel biomarkers for pre-diabetes identified by metabolomics. Mol. Syst. Biol. 8, 615 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Koivula, R. W. et al. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium. Diabetologia 57, 1132–1142 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Ahlqvist, E. et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 6, 361–369 (2018).

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors’ work was supported, in part, by Innovative Medicines Initiative Joint Undertaking under grant agreement number 115317 (DIRECT), European Institute of Innovation & Technology (EIT) Health Innovation Projects grant DeTecT2D (18428) and the German Federal Ministry of Education and Research (BMBF) to the German Center Diabetes Research (DZD e.V.) grant that was awarded to J.A. E.R.P. holds a Wellcome trust New investigator award (102820/Z/13/Z).

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Authors and Affiliations

  1. Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK

    Ewan Pearson

  2. Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany

    Jerzy Adamski

  3. Lehrstuhl für Experimentelle Genetik, Technische Universität, München, Germany

    Jerzy Adamski

  4. German Center for Diabetes Research (DZD), München-Neuherberg, Germany

    Jerzy Adamski

Authors
  1. Ewan Pearson
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  2. Jerzy Adamski
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Correspondence to Jerzy Adamski.

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The authors declare no competing interests.

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Pearson, E., Adamski, J. The search for predictive metabolic biomarkers for incident T2DM. Nat Rev Endocrinol 14, 444–446 (2018). https://doi.org/10.1038/s41574-018-0045-x

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