Validating a dimensionless number for glucose homeostasis in humans.

Understanding type 2 diabetes is challenged by the diversity of patient phenotypes. Translating data across species and among individuals is a barrier for understanding the genetic loci that underpin this multifactorial disease. Dynamic scaling, based upon dimensional analysis, is a common technique in engineering used to translate data among different systems. The objective of this study was to gain insight using dimensional analysis into the relative changes in insulin production capacity vs. insulin-dependent glucose metabolism in patient groups that represent distinct stages of disease progression. A dimensionless number was derived using variables involved in the production of insulin and in the sensitivity of glucose metabolism to insulin. The resulting dynamic scaling relationship was validated against patient data obtained for over 2000 individuals that range in phenotype from normal to severe type 2 diabetes. Individuals were identified in the third National Health and Nutrition Evaluation Survey. Patient groups clustered in different regions based upon the severity of clinical symptoms. The cross-sectional comparison among patient groups shows that progression from normal to clinical onset of type 2 diabetes exhibits a non-linear change in the ratio of insulin production to insulin-dependent glucose metabolism: normals are balanced, pre-diabetic individuals exhibit an increase, and individuals with clinical type 2 diabetes exhibit a decrease in this ratio. This dimensionless number provides a method for discriminating between patient groups from first principles. By analogy with other dimensionless numbers, this number may be used to monitor basic physiological variables responsible for glucose homeostasis. In addition, a similar dynamic trajectory to the clinical populations could provide a criterion for selecting relevant animal models for diabetes.