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The mechanisms by which the enteroinsular axis influences beta-cell function have not been investigated in detail. We performed oral and isoglycemic intravenous (IV) glucose administration in subjects with normal (NGT; n = 11) or impaired glucose tolerance (IGT; n = 10), using C-peptide deconvolution to calculate insulin secretion rates and mathematical modeling to quantitate beta-cell function. The incretin effect was taken to be the ratio of oral to IV responses. In NGT, incretin-mediated insulin release [oral glucose tolerance test (OGTT)/IV ratio = 1.59 +/- 0.18, P = 0.004] amounted to 18 +/- 2 nmol/m(2) (32 +/- 4% of oral response), and its time course matched that of total insulin secretion. The beta-cell glucose sensitivity (OGTT/IV ratio = 1.52 +/- 0.26, P = 0.02), rate sensitivity (response to glucose rate of change, OGTT/IV ratio = 2.22 +/- 0.37, P = 0.06), and glucose-independent potentiation were markedly higher with oral than IV glucose. In IGT, beta-cell glucose sensitivity (75 +/- 14 vs. 156 +/- 28 pmol.min(-1).m(-2).mM(-1) of NGT, P = 0.01) and potentiation were impaired on the OGTT. The incretin effect was not significantly different from NGT in terms of plasma glucagon-like peptide 1 and glucose-dependent insulinotropic polypeptide responses, total insulin secretion, and enhancement of beta-cell glucose sensitivity (OGTT/IV ratio = 1.73 +/- 0.24, P = NS vs. NGT). However, the time courses of incretin-mediated insulin secretion and potentiation were altered, with a predominance of glucose-induced vs. incretin-mediated stimulation. We conclude that, under physiological circumstances, incretin-mediated stimulation of insulin secretion results from an enhancement of all dynamic aspects of beta-cell function, particularly beta-cell glucose sensitivity. In IGT, beta-cell function is inherently impaired, whereas the incretin effect is only partially affected.

Insulin hyperpolarizes plasma membranes; we tested whether insulin affects ventricular repolarization. In 35 healthy volunteers, we measured the Q-T interval during electrocardiographic monitoring in the resting state and in response to hyperinsulinemia (euglycemic 1-mU. min(-1). kg(-1) insulin clamp). A computerized algorithm was used to identify T waves; Bazett's formula was employed to correct Q-T (QTc) by heart rate (HR). In the resting state, QTc was inversely related to indexes of body size (e.g., body surface area, r = -0.53, P = 0.001) but not to indexes of body fatness. During the clamp, HR (67 +/- 1 to 71 +/- 1 beats/min, P < 0.0001) and plasma norepinephrine levels (161 +/- 12 to 184 +/- 10 pg/ml, P < 0.001) increased. QTc rose promptly and consistently, averaging 428 +/- 6 ms between 30 and 100 min (P = 0.014 vs. the resting value of 420 +/- 5 ms). Fasting serum potassium (3.76 +/- 0.03 mM) declined to 3. 44 +/- 0.03 mM during insulin. After adjustment for body size, resting QTc was directly related to fasting plasma insulin (partial r = 0.43, P = 0.01); furthermore, QTc was inversely related to serum potassium levels both in the fasting state (partial r = -0.16, P < 0. 04) and during insulin stimulation (partial r = -0.47, P = 0.003). Neither resting nor clamp-induced QTc was related to insulin sensitivity. Physiological hyperinsulinemia acutely prolongs ventricular repolarization independent of insulin sensitivity. Both insulin-induced hypokalemia and adrenergic activation contribute to this effect.

The traditional methods for the assessment of insulin sensitivity yield only a single index, not the whole dose-response curve information. This curve is typically characterized by a maximally insulin-stimulated glucose clearance (Cl(max)) and an insulin concentration at half-maximal response (EC(50)). We developed an approach for estimating the whole dose-response curve with a single in vivo test, based on the use of tracer glucose and exogenous insulin administration (two steps of 20 and 200 mU x min(-1) x m(-2), 100 min each). The effect of insulin on plasma glucose clearance was calculated from non-steady-state data by use of a circulatory model of glucose kinetics and a model of insulin action in which glucose clearance is represented as a Michaelis-Menten function of insulin concentration with a delay (t(1/2)). In seven nondiabetic subjects, the model predicted adequately the tracer concentration: the model residuals were unbiased, and their coefficient of variation was similar to the expected measurement error (approximately 3%), indicating that the model did not introduce significant systematic errors. Lean (n = 4) and obese (n = 3) subjects had similar half-times for insulin action (t(1/2) = 25 +/- 9 vs. 25 +/- 8 min) and maximal responses (Cl(max) = 705 +/- 46 vs. 668 +/- 259 ml x min(-1) x m(-2), respectively), whereas EC(50) was 240 +/- 84 microU/ml in the lean vs. 364 +/- 229 microU/ml in the obese (P < 0.04). EC(50) and the insulin sensitivity index (ISI, initial slope of the dose-response curve), but not Cl(max), were related to body adiposity and fat distribution with r of 0.6-0.8 (P < 0.05). Thus, despite the small number of study subjects, we were able to reproduce information consistent with the literature. In addition, among the lean individuals, t(1/2) was positively related to the ISI (r = 0.72, P < 0.02). We conclude that the test here presented, based on a more elaborate representation of glucose kinetics and insulin action, allows a reliable quantitation of the insulin dose-response curve for whole body glucose utilization in a single session of relatively short duration.