Defining and Classifying New Subgroups of Diabetes

Area of Science:

• Endocrinology and Metabolism
• Genetics and Genomics
• Bioinformatics

Background:

• Current diabetes classifications inadequately address its heterogeneity.
• Emerging and rare forms of diabetes require novel categorization.
• Type 1 and Type 2 diabetes (T1D and T2D) represent a spectrum of etiological factors.

Purpose of the Study:

• To propose an etiologically based classification for diabetes.
• To explore the concept of a diabetes spectrum for clinical discovery.
• To identify promising methodologies for defining new diabetes subgroups.

Main Methods:

• Consideration of rare diabetes forms (e.g., maturity onset diabetes of youth, neonatal diabetes) as models.
• Phenotypic dissection of complex forms like ketosis-prone diabetes.
• Application of bioinformatic approaches, including clustering analyses and multi-omics investigations.

Main Results:

• Maturity onset diabetes of youth and neonatal diabetes exemplify etiologically defined rare diabetes forms.
• Ketosis-prone diabetes serves as a model for complex, dissectible diabetes phenotypes.
• Bioinformatic and multi-omics approaches show promise for identifying novel diabetes subgroups.

Conclusions:

• An etiologically based classification is crucial for understanding diabetes heterogeneity.
• Viewing diabetes as a spectrum facilitates both classification and clinical discovery.
• Advanced computational and omics techniques are essential for defining new diabetes classifications.