Your browser has javascript turned off or blocked. This will lead to some parts of our website to not work properly or at all. Turn on javascript for best performance.

The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Rashmi Prasad

Rashmi Prasad

Assistant researcher

Rashmi Prasad

Subtypes of type 2 diabetes determined from clinical parameters

Author

  • Emma Ahlqvist
  • Rashmi B. Prasad
  • Leif Groop

Summary, in English

Type 2 diabetes (T2D) is defined by a single metabolite, glucose, but is increasingly recognized as a highly heterogeneous disease, including individuals with varying clinical characteristics, disease progression, drug response, and risk of complications. Identification of subtypes with differing risk profiles and disease etiologies at diagnosis could open up avenues for personalized medicine and allow clinical resources to be focused to the patients who would be most likely to develop diabetic complications, thereby both im-proving patient health and reducing costs for the health sector. More homogeneous populations also offer increased power in experimental, genetic, and clinical studies. Clinical parameters are easily available and reflect relevant disease pathways, including the effects of both genetic and environmental exposures. We used six clinical parameters (GAD autoantibodies, age at diabetes onset, HbA1c, BMI, and measures of insulin resistance and insulin secretion) to cluster adult-onset diabetes patients into five subtypes. These sub-types have been robustly reproduced in several populations and associated with different risks of complications, comor-bidities, genetics, and response to treatment. Importantly, the group with severe insulin-deficient diabetes (SIDD) had increased risk of retinopathy and neuropathy, whereas the severe insulin-resistant diabetes (SIRD) group had the highest risk for diabetic kidney disease (DKD) and fatty liver, empha-sizing the importance of insulin resistance for DKD and hepatosteatosis in T2D. In conclusion, we believe that sub-classification using these highly relevant parameters could provide a framework for personalized medicine in diabetes.

Department/s

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

Publishing year

2020

Language

English

Pages

2086-2093

Publication/Series

Diabetes

Volume

69

Issue

10

Document type

Journal article

Publisher

American Diabetes Association Inc.

Topic

  • Endocrinology and Diabetes

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology

ISBN/ISSN/Other

  • ISSN: 0012-1797