Abstract
Since little is known about the disposition index (DI) in autoantibody-positive individuals, we have assessed whether DI has a similar association between insulin secretion and sensitivity to the association observed in other populations. In TrialNet Pathway to Prevention (TNPTP; n = 6,620) and Diabetes Prevention Trial–Type 1 (DPT-1; n = 704) study participants, two secretion-sensitivity pairs, each representing a DI, were analyzed cross-sectionally at baseline: area under the curve (AUC) C-peptide/AUC glucose (AUC ratio) and Matsuda index (MI) from TNPTP oral glucose tolerance tests (oral DI), first-phase insulin response (FPIR), and 1 / fasting insulin (1/FI) from DPT-1 from intravenous glucose tolerance tests (DI). Participants were followed for progression to type 1 diabetes (T1D). Within the normal and diabetes glucose ranges, associations of AUC ratio with MI in TNPTP and FPIR with 1/FI in DPT-1 had inverse curvilinear patterns with convexities to the origin. After logarithmic transformations to linearize the secretion and sensitivity measures, the inverse slope was steeper for the diabetes range (P < 0.0001). In a Cox regression model including the AUC ratio and MI as variables and another model including FPIR and 1/FI, the interaction terms of secretion x sensitivity (i.e., the DI/oral DI) predicted stage 3 T1D in both (P < 0.0001). The DI remained significantly predictive (P < 0.0001) when the DPT-1 risk score was added as a co-variate in regression models. In autoantibody-positive populations, insulin secretion is inversely related to sensitivity in a quasi-hyperbolic relationship in normal and diabetes ranges of glucose. The DI can be represented by a statistical and physiologic interaction between secretion and sensitivity that is predictive of stage 3 T1D.
Cite
CITATION STYLE
Ismail, H. M., Cuthbertson, D., Galderisi, A., Libman, I., Jacobsen, L., Moran, A., … Sosenko, J. M. (2025). The Disposition Index in Autoantibody-Positive Individuals at Risk for Type 1 Diabetes. Diabetes, 74(7), 1196–1204. https://doi.org/10.2337/db24-1000
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.