β-Cell Function and Insulin Sensitivity in Youth With Early Type 1 Diabetes From a 2-Hour 7-Sample OGTT

Abstract

Background The oral minimal model is a widely accepted noninvasive tool to quantify both β-cell responsiveness and insulin sensitivity from glucose, C-peptide and insulin concentrations during a 3-h 9-point oral glucose tolerance test (OGTT). Here, we aimed to validate a 2-h 7-point protocol against the 3-h OGTT and to test how variation in early sampling frequency impacts estimates of β-cell responsiveness and insulin sensitivity. Methods We conducted a secondary analysis on 15 lean youth with stage 1 T1D (≥2islet autoantibodies with no dysglycemia) who underwent a 3-h 9-point OGTT. The oral minimal model was used to quantitate β-cell responsiveness (φtotal) and insulin sensitivity (SI), allowing assessment of β-cell function by the disposition index (DI=φtotal × SI). Seven- and 5-point 2-h OGTT protocols were tested against the 3-h 9-point gold standard to determine agreement between estimates of φtotal and its dynamic and static components, SI, and DI across different sampling strategies. Results The 2-h estimates for the disposition index exhibited a strong correlation with 3-h measures (r = 0.975, p < 0.001) with similar results for β-cell responsiveness and insulin sensitivity (r = 0.997 and r = 0.982, p < 0.001, respectively). The agreement of the three estimates between the 7-point 2-h and 9-point 3-h protocols fell within the 95% CI on the Bland-Altman grid with a median difference of 16.9%(-35.3, 32.5), 0.2%(-0.6, 1.3) and 14.9%(-1.4, 28.3) for DI, φtotal and SI. Conversely, the 5-point protocol did not provide reliable estimates of φ dynamic and static components. Conclusion The 2-h 7-point OGTT is reliable in subjects with Stage 1 T1D for assessment of β-cell responsiveness, insulin sensitivity, and disposition index. Incorporation of these analyses into current 2-h diabetes staging and monitoring OGTTs offers the potential to more accurately quantify risk of progression in the early stages of T1D.

SAAM II: A general mathematical modeling rapid prototyping environment

“…14,15 SAAM II is a widely used software platform for glucose-insulin Minimal Model Analysis, aiding in monitoring diabetes progression and evaluating the efficacy of antidiabetic drugs in clinical trials by estimating key parameters of glucose disposition in vivo. 16,17 In Quantitative Systems Pharmacology, SAAM II was used for early research on the adaptive immune response, 18 indirectly influencing next-generation tools 19,20 that ultimately supported COVID-19 vaccine regimen designs. In the realm of PK/PD, SAAM II has been instrumental in studying complex PK and/or PD systems.…”

“…It also was used for the glucose‐insulin simulator, which became one of the first in‐silico tools approved by the FDA to partially substitute clinical trials in diabetes research 14,15 . SAAM II is a widely used software platform for glucose‐insulin Minimal Model Analysis, aiding in monitoring diabetes progression and evaluating the efficacy of antidiabetic drugs in clinical trials by estimating key parameters of glucose disposition in vivo 16,17 …”

“… 14 , 15 SAAM II is a widely used software platform for glucose‐insulin Minimal Model Analysis, aiding in monitoring diabetes progression and evaluating the efficacy of antidiabetic drugs in clinical trials by estimating key parameters of glucose disposition in vivo. 16 , 17 …”

Quantifying beta cell function in the preclinical stages of type 1 diabetes

“…The first-phase insulin response (FPIR) represents the response to a rapid glucose rise and is driven by the release of intracellular preformed insulin vesicles following glucose-induced beta cell depolarisation and calcium influx. The FPIR is classically assessed using an IVGTT, although a frequently sampled OGTT, with early samples taken during the first 30 min after the oral load, may also provide an accurate estimate [ 17 , 18 ] (Fig. 2 a).…”

“…A major advantage of metabolic modelling is the possibility of estimating both insulin secretion and insulin sensitivity once serial measurements of glucose, C-peptide and insulin are obtained. The availability of early time points in dynamic testing (10 and 20 min or 15 min) is of pivotal importance in estimating early insulin release ( dynamic ) [ 18 ]. The major limitation of this metabolic modelling in larger populations is the need for qualified personnel to run the analysis and the requirement to obtain multiple samples during testing.…”