Skip to main content
SpringerLink
Log in

DIABETES

Subclassification of diabetes based on quantitative traits

  • News & Views
  • Published:

From Nature Reviews Nephrology

View current issue Sign up to alerts

A new subclassification of diabetes based on quantitative traits, including age, body mass index, insulin resistance and β-cell function suggests five clusters with distinct phenotypes and prognoses. This approach may offer a novel way to classify diabetes by providing more information on risks and potential therapeutic strategies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1: Clinical parameter-based diabetes classification of the ANDIS cohort.

References

  1. Kim, S. H. Measurement of insulin action: a tribute to Sir Harold Himsworth. Diabet. Med. 28, 1487–1493 (2011).

    Article  PubMed  CAS  Google Scholar 

  2. Jorgensen, M. E., Kristensen, J. K., Reventlov Husted, G., Cerqueira, C. & Rossing, P. The Danish adult diabetes registry. Clin. Epidemiol. 8, 429–434 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hattersley, A. T. & Patel, K. A. Precision diabetes: learning from monogenic diabetes. Diabetologia 60, 769–777 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  4. 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. https://doi.org/10.1016/S2213-8587(18)30051-2 (2018).

  5. Gnudi, L., Coward, R. J. M. & Long, D. A. Diabetic nephropathy: perspective on novel molecular mechanisms. Trends Endocrinol. Metab. 27, 820–830 (2016).

    Article  PubMed  CAS  Google Scholar 

  6. Waden, J. et al. Leisure-time physical activity and development and progression of diabetic nephropathy in type 1 diabetes: the FinnDiane Study. Diabetologia 58, 929–936 (2015).

    Article  PubMed  Google Scholar 

  7. Look, A. R. G. Effect of a long-term behavioural weight loss intervention on nephropathy in overweight or obese adults with type 2 diabetes: a secondary analysis of the Look AHEAD randomised clinical trial. Lancet Diabetes Endocrinol. 2, 801–809 (2014).

    Article  Google Scholar 

  8. de Zeeuw, D. & Lambers Heerspink, H. Do diabetic kidneys deserve a lifestyle change? Lancet Diabetes Endocrinol. 2, 769–770 (2014).

    Article  PubMed  Google Scholar 

  9. Oellgaard, J. et al. Intensified multifactorial intervention in type 2 diabetics with microalbuminuria leads to long-term renal benefits. Kidney Int. 91, 982–988 (2017).

    Article  PubMed  Google Scholar 

  10. Palmer, N. D. et al. Metabolomic profile associated with insulin resistance and conversion to diabetes in the Insulin Resistance Atherosclerosis Study. J. Clin. Endocrinol. Metab. 100, E463–E468 (2015).

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Steno Diabetes Center Copenhagen, Gentofte, Denmark

    Peter Rossing

  2. Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark

    Peter Rossing

Authors
  1. Peter Rossing
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Rossing.

Ethics declarations

Competing interests

The author declares no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rossing, P. Subclassification of diabetes based on quantitative traits. Nat Rev Nephrol 14, 355–356 (2018). https://doi.org/10.1038/s41581-018-0011-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41581-018-0011-9

  • Springer Nature Limited

Search

Navigation