4.7 Review

A novel diabetes typology: towards precision diabetology from pathogenesis to treatment

Journal

DIABETOLOGIA
Volume 65, Issue 11, Pages 1770-1781

Publisher

SPRINGER
DOI: 10.1007/s00125-021-05625-x

Keywords

Clustering; Complications; Diabetes subgroups; Personalised medicine; Precision medicine; Reclassification; Review

Funding

  1. Projekt DEAL
  2. Ministry of Culture and Science of the State of North Rhine-Westphalia
  3. German Federal Ministry of Health
  4. German Federal Ministry of Education and Research

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This review discusses the complexity of diabetes and proposes novel subgroups (subtypes) of diabetes. These subgroups display distinct patterns of clinical features, disease progression, and onset of comorbidities and complications, providing possibilities for personalized treatments in the future.
The current classification of diabetes, based on hyperglycaemia, islet-directed antibodies and some insufficiently defined clinical features, does not reflect differences in aetiological mechanisms and in the clinical course of people with diabetes. This review discusses evidence from recent studies addressing the complexity of diabetes by proposing novel subgroups (subtypes) of diabetes. The most widely replicated and validated approach identified, in addition to severe autoimmune diabetes, four subgroups designated severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes and mild age-related diabetes subgroups. These subgroups display distinct patterns of clinical features, disease progression and onset of comorbidities and complications, with severe insulin-resistant diabetes showing the highest risk for cardiovascular, kidney and fatty liver diseases. While it has been suggested that people in these subgroups would benefit from stratified treatments, RCTs are required to assess the clinical utility of any reclassification effort. Several methodological and practical issues also need further study: the statistical approach used to define subgroups and derive recommendations for diabetes care; the stability of subgroups over time; the optimal dataset (e.g. phenotypic vs genotypic) for reclassification; the transethnic generalisability of findings; and the applicability in clinical routine care. Despite these open questions. the concept of a new classification of diabetes has already allowed researchers to gain more insight into the colourful picture of diabetes and has stimulated progress in this field so that precision diabetology may become reality in the future.

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