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Rashmi Prasad

Rashmi Prasad

Assistant researcher

Rashmi Prasad

Precision medicine in Type 2 Diabetes

Author

  • Rashmi B Prasad
  • Leif Groop

Summary, in English

The Precision Medicine Initiative defines precision medicine as "an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person." This approach will facilitate more accurate treatment and prevention strategies in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for generalized usage. Diabetes is clearly more heterogeneous than the conventional sub-classification into type 1 and type 2 diabetes. Monogenic forms of diabetes like MODY and neonatal diabetes have paved the way for precision medicine in diabetes, as carriers of unique mutations require unique treatment. Diagnosis of diabetes in the past has been dependent upon measuring one metabolite, glucose. By instead including 6 variables in a clustering analysis, we could break down diabetes into 5 distinct subgroups, with better prediction of disease progression and outcome. The severe insulin resistant diabetes (SIRD) cluster showed the highest risk of kidney disease and highest prevalence of non-alcoholic fatty liver disease whereas patients in the insulin deficient cluster 2 (SIDD) had the highest risk of retinopathy. In the future this will certainly be improved and expanded by including genetic, epigenetic and other biomarker to allow better prediction of outcome and choice of more precise treatment. This article is protected by copyright. All rights reserved.

Department/s

  • Genomics, Diabetes and Endocrinology
  • EXODIAB: Excellence in Diabetes Research in Sweden

Publishing year

2019

Language

English

Pages

40-48

Publication/Series

Journal of Internal Medicine

Volume

285

Issue

1

Document type

Journal article review

Publisher

Wiley-Blackwell

Topic

  • Endocrinology and Diabetes

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology

ISBN/ISSN/Other

  • ISSN: 1365-2796