Logistic model of glucose-regulated C-peptide secretion: hysteresis pathway disruption in impaired fasting glycemia

Abstract

The present analysis tests the hypothesis that quantifiable disruption of the glucose-stimulated insulin-secretion dose-response pathway mediates impaired fasting glycemia (IFG) and type 2 diabetes mellitus (DM). To this end, adults with normal and impaired fasting glycemia (NFG, n = 30), IFG (n = 32), and DM (n = 14) were given a mixed meal containing 75 g glucose. C-peptide and glucose were measured over 4 h, 13 times in NFG and IFG and 16 times in DM (age range 50-57 yr, body mass index 28-32 kg/m(2)). Wavelet-based deconvolution analysis was used to estimate time-varying C-peptide secretion rates. Logistic dose-response functions were constructed analytically of the sensitivity, potency, and efficacy (in the pharmacological sense of slope, one-half maximal stimulation, and maximal effect) of glucose's stimulation of prehepatic insulin (C-peptide) secretion. A hysteresis changepoint time, demarcating unequal glucose potencies for onset and recovery pathways, was estimated simultaneously. According to this methodology, NFG subjects exhibited distinct onset and recovery potencies of glucose in stimulating C-peptide secretion (6.5 and 8.5 mM), thereby defining in vivo hysteresis (potency shift -2.0 mM). IFG patients manifested reduced glucose onset potency (8.6 mM), and diminished C-peptide hysteretic shift (-0.80 mM). DM patients had markedly decreased glucose potency (18.8 mM), reversal of C-peptide's hysteretic shift (+4.5 mM), and 30% lower C-peptide sensitivity to glucose stimulation. From these data, we conclude that a dynamic dose-response model of glucose-dependent control of C-peptide secretion can identify disruption of in vivo hysteresis in patients with IFG and DM. Pathway-defined analytic models of this kind may aid in the search for prediabetes biomarkers.

Slow potentials encode intercellular coupling and insulin demand in pancreatic beta cells

“…This concentration is lower than that which usually elicits in vitro, in a single or few steps, maximal insulin secretion [32,37], but it is similar to that which attains the same secretory effect using a glucose ramp [38] or had been reported from in vivo patch-clamp experiments in anaesthetised mice [39]. The glucose concentrations inducing the maximal frequency of SPs coincide with those observed in humans during an OGTT [40]. GLP-1 and adrenaline increased and decreased SP frequencies, respectively, consistent with their effects on insulin secretion.…”

“…The curve is hysteretic, reflecting a reduced sensitivity of the signals towards decreasing glucose levels, reminiscent of that described in man during GTTs [40]. This control is presumably beneficial to prevent hypoglycaemia as a consequence of a sustained insulin release.…”

Towards the Integration of an Islet-Based Biosensor in Closed-Loop Therapies for Patients With Type 1 Diabetes

“…In addition, modern hybrid closedloop systems frequently integrate a hypoglycaemic alarm to trigger the suspension of basal insulin delivery, referred to as Low Glucose Suspend (LGS). Although the biosensor response presents a natural glucose-dependent hysteresis protecting from hypoglycaemia (11,61), it may have a shortcoming that is worth mentioning: b-cell activity at low glucose, i.e., the SP frequency, is not yet fully explored and the biosensor output may eventually not suffice, when the patient BG level is below the islet glucose stimulation threshold, to trigger such hypoglycaemia-prevention feature. The co-integration of a CGM technology and our biosensing one into a single device, may thus be necessary.…”

A novel measure of glucose homeostasis (or loss thereof) comprising the joint dynamics of glucose, insulin, glucagon, and cortisol

“…In the present nonparametric homeostasis model, the secretion (production) rates of the four components (Glc, Ins, Ggn, and Cort) are first estimated using an accepted published methodology (9,12). The secretion rate Z(t) is defined as the sum of a constant basal rate ␤ 0 and a nonconstant pulsatile rate:…”

“…The dose-response (sigmoidal) functions will then hypothesize parameters of re-sponsiveness (potency, sensitivity, and efficacy) and associated time delays. These parameters and time delays need to be estimated from the data (2,9,14,17,18,19). The inherent biological variation and the dynamically changing dose-response parameters and time delays have made their statistical estimation very difficult (1,9,16).…”