Understanding diabetes heterogeneity: key steps towards precision medicine in diabetes

Richard David Leslie (Lead / Corresponding author), Ronald Ching Wan Ma, Paul W. Franks, Kristen J Nadeau, Ewan R. Pearson, Maria Jose Redondo

Research output: Contribution to journalReview articlepeer-review

19 Citations (Scopus)

Abstract

Diabetes is a highly heterogeneous condition; yet, it is diagnosed by measuring a single blood-borne metabolite, glucose, irrespective of aetiology. Although pragmatically helpful, disease classification can become complex and limit advances in research and medical care. Here, we describe diabetes heterogeneity, highlighting recent approaches that could facilitate management by integrating three disease models across all forms of diabetes, namely, the palette model, the threshold model and the gradient model. Once diabetes has developed, further worsening of established diabetes and the subsequent emergence of diabetes complications are kept in check by multiple processes designed to prevent or circumvent metabolic dysfunction. The impact of any given disease risk factor will vary from person-to-person depending on their background, diabetes-related propensity, and environmental exposures. Defining the consequent heterogeneity within diabetes through precision medicine, both in terms of diabetes risk and risk of complications, could improve health outcomes today and shine a light on avenues for novel therapy in the future.

Original languageEnglish
Pages (from-to)848-860
Number of pages13
JournalThe Lancet: Diabetes and Endocrinology
Volume11
Issue number11
Early online date4 Oct 2023
DOIs
Publication statusPublished - Nov 2023

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