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Clustering for a better prediction of type 2 diabetes mellitus

Nature Reviews Endocrinology volume 17, pages 193–194 (2021)Cite this article

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Complex phenotypic and genetic clustering of individuals who are potentially at increased risk of type 2 diabetes mellitus (T2DM) can enable the identification of individuals who are likely to develop T2DM and vascular complications. Precision medicine for prediabetes should improve prevention programmes and reduce mortality.

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Acknowledgements

A.B. and P.F. are supported by grants from the French National Research Agency (ANR-10-LABX-46 (European Genomics Institute for Diabetes) and ANR-10-EQPX-07-01 (LIGAN-PM)); from the European Research Council (ERC GEPIDIAB – 294785, to PF; ERC Reg-Seq – 715575, to A.B.); and from the National Center for Precision Diabetic Medicine — PreciDIAB, which is jointly supported by the French National Agency for Research (ANR-18-IBHU-0001), by the European Union (FEDER), by the Hauts-de-France Regional Council and by the European Metropolis of Lille (MEL).

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Authors and Affiliations

  1. Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille, France

    Amélie Bonnefond & Philippe Froguel

  2. Université de Lille, CHU de Lille, Lille, France

    Amélie Bonnefond & Philippe Froguel

  3. Department of Metabolism, Imperial College London, London, UK

    Amélie Bonnefond & Philippe Froguel

Authors
  1. Amélie Bonnefond
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  2. Philippe Froguel
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Correspondence to Amélie Bonnefond or Philippe Froguel.

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Bonnefond, A., Froguel, P. Clustering for a better prediction of type 2 diabetes mellitus. Nat Rev Endocrinol 17, 193–194 (2021). https://doi.org/10.1038/s41574-021-00475-4

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