The clinical consequences of heterogeneity within and between different diabetes types

Abstract

Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The 'palette model' and the 'threshold hypothesis' can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. Graphical abstract.

Keywords: Atypical; Classification; Diabetes; Endotype; Genetics; Heterogeneity; Palette; Precision medicine; Review; Threshold.

Fig 1

Illustration of heterogeneity within and between diabetes types. Genetic and environmental factors, and their interaction, influence multiple mechanisms (e.g. autoimmunity, reduced beta cell mass, insulin secretion defects, inflammation, barriers to health care) that may contribute in variable degree to the development and progression of diabetes in each individual. This individual variability leads to heterogeneity within diabetes types (e.g. very early onset type 1 diabetes, LADA) and between diabetes types (e.g. KPD, LADA type 1.5 diabetes). Therapeutic leverage of pathophysiological heterogeneity will allow advancement of precision medicine in diabetes. T1D, type 1 diabetes; T2D, type 2 diabetes; MGD, monogenic diabetes.

Fig. 2

Algorithm for classification of paediatric diabetes based on the presence or absence of autoimmunity and insulin sensitivity. Secondary causes of diabetes include steroid-induced diabetes and cystic fibrosis-related diabetes. Other genetic causes of diabetes include lipodystrophy, mitochondrial diabetes, etc. IA-2A, insulin antigen-2 autoantibodies; IAA, insulin autoantibodies, ZnT8A, zinc transporter 8 autoantibodies. Modified from [58] with the permission of American Diabetes Association. © 2014 American Diabetes Association.

Fig. 3

Model of diabetes pathophysiology that integrates the palette model [56] and the threshold hypothesis [57]. Multiple pathophysiological pathways (colours in a palette) can be at play in a given individual, as represented here (e.g. islet autoimmunity, monogenic insulin secretion defect, polygenic insulin secretion defect, insulin resistance), in addition to others not illustrated here (e.g. low beta cell mass due to monogenic mutation). The degrees of abnormality for each diabetogenic pathway in a given individual are combined to determine whether the blood glucose level crosses the threshold for dysglycaemia or diabetes (e.g. compare stages 1 and 2 of type 1 diabetes, or asymptomatic MODY and MODY with symptoms). The relative predominance of each diabetogenic pathway determines the clinical phenotype (e.g. compare insulin-resistant type 2 diabetes and insulin-deficient type 2 diabetes). Different pathophysiological processes may be involved in diabetes types currently considered a single entity (e.g. examples 1 and 2 of adult-onset type 1 diabetes). This perspective provides a framework to understand heterogeneity within and between diabetes types, address the challenges of diabetes classification into distinct categories, and may be leveraged for personalised treatment. The x-axis presents some examples of possible palettes in different individuals or over time in a given individual. DM, diabetes; T1D, type 1 diabetes; T2D, type 2 diabetes; LADA, latent autoimmune diabetes in adults.