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Incretin effect potentiates -cell responsivity to glucose as well as to its rate of change: OGTT and matched intravenous study

¹Department of Information Engineering, University of Padua, Padua, Italy; ²Department of Internal Medicine, Women's Health Clinic; and ³Department of Internal Medicine, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic and Foundation, Rochester, Minnesota

Submitted 25 January 2006 ; accepted in final form 24 July 2006

	ABSTRACT

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The aim of this study is to gain greater insight into the mechanism whereby "incretins" (greater insulinemia after oral than intravenous glucose) enhance insulin secretion. To do so, we use a model of C-peptide secretion to reanalyze data from a previously published study in which glycemic profiles observed following glucose ingestion were matched in the same 10 subjects by means of an intravenous glucose infusion. We report that incretins increase insulin secretion by enhancing both the dynamic (to the rate of increase of glucose) and static (to given glucose concentration) response with an increase of 58% for the static (_s = 16.4 ± 1.8 vs. 24.6 ± 2.0 10^–9 min^–1, P = 0.01) and 63% for the dynamic (_d = 278 ± 32 vs. 463 ± 86 10^–9, P = 0.02) indexes. Since increases in the dynamic response to glucose are believed to be due to an increase in the rate of docking, and exocytosis of insulin containing granules and increases in the static response to glucose are believed to be caused by a shift in the sensitivity of the -cell to glucose, these results suggest that incretins may modulate more than one step in the -cell insulin secretory cascade.

oral glucose tolertance test; insulin secretion; -cell function; minimal model

Recently, C-peptide-based models of insulin secretion have become available that can not only quantify the overall amount of insulin secreted but also determine the extent to which changes in the dynamic (i.e., the response to a change in glucose) and static (the response to a given glucose concentration) contribute to changes in insulin secretion. Dynamic phase is likely related to exocytosis of readily releasable pool of docked granules, whereas the static phase requires a replacement of the released docked granules from a large reserve pool to the plasma membrane followed by docking and preparation for release (11).

A previous study (13) has suggested that incretins enhance the static component of insulin secretion through the so-called potentiation factor. However, since the model used in those experiments [meal and oral glucose tolerance test (OGTT)] allowed only potentiation of the static component of insulin secretion, it is presently not known whether the incretin effect also enhances the dynamic component of insulin secretion. A study based on hyperglycemic clamp (HGC) suggests a potentiation on both the first and second phase of insulin secretion (8), and the recent reports on treatment of islets with GLP-1 provide further support for such an effect, as do experiments in rat where GIP receptors were either knocked out or pharmacologically inhibited (12, 14).

The present experiments were undertaken to determine whether the incretin effect results from an increase in the dynamic response to glucose, static response to glucose, or a combination of both. To do so, we used a model of C-peptide secretion and kinetics to reanalyze data from a previously published study (17) where glycemic profiles observed following glucose ingestion were matched in the same subjects by means of an intravenous glucose infusion. We report that the incretin effect increases insulin secretion by enhancing both the dynamic and static responses to glucose, with changes in the latter being more marked than the former. Since increases in the dynamic response to glucose are believed to be due to an increase in the rate of docking and exocytosis of insulin containing granules and the static response to glucose are believed to be caused by a shift in the sensitivity of the -cell to glucose, these suggest that incretins may modulate more than one step in the -cell insulin secretory cascade.

	MATERIALS AND METHODS

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Subjects. Studies were performed on 10 healthy subjects: 5 men, age 28.8 ± 1.8 yr (means ± SE), body mass index (BMI) 24.8 ± 0.7 kg/m²; and 5 women, age 29.2 ± 2.3 yr, BMI 20.2 ± 1.0 kg/m². All subjects were nonobese (BMI <27 for men and <25 for women) and had body weights that ranged from 68 to 99 kg for men and from 49 to 61 kg for women. Subjects were taking no medications and had no family history of diabetes. All studies were performed at the General Clinical Research Center of the Mayo Foundation after written informed consent was obtained.

Protocol. The design of the experiments was described previously (17). In brief, each subject was studied twice. On the first occasion the subjects ingested 1 g of glucose/kg body wt at time 0 min, whereas on the second occasion a glucose infusion was initiated at 0 min and given in amounts sufficient to match the glucose concentrations observed on the first occasion. On both occasions arterialized blood samples were collected through an 18-gauge indwelling plastic cannula inserted into a dorsal hand vein in a retrograde fashion; the hand was maintained at 50–60°C in a temperature-controlled enclosure. The blood for measurement of glucose, C-peptide, and insulin concentrations was obtained at –30, 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 150, 180, 210, and 240 min (Fig. 1).

View larger version (8K): [in this window] [in a new window]   Fig. 1. Mean plasma glucose (top), insulin (middle), and C-peptide (bottom) concentrations in the 10 subjects during oral glucose tolerance test (OGTT) and isoglycemic intravenous glucose infusion (I-IVG).

C-peptide model. Insulin secretion profiles (SR, pmol/l), their basal (SR_b, pmol/l), static [SR_s (pmol/l), controlled by glucose concentration], and dynamic [SR_d (pmol/l), controlled by glucose rate of increase] components, and indexes of -cell responsivity were estimated from C-peptide and glucose levels of the OGTT and of the isoglycemic intravenous glucose infusion (I-IVG) by using the minimal model of C-peptide secretion and kinetics as previously described (30). This approach models the three components of pancreatic secretion normalized to the C-peptide volume of distribution V_C (l) (21), namely sr_s, sr_d, and sr_b (pmol·min^–1·l^–1):

(1)

sr_s is assumed equal to the provision of releasable insulin to -cells, controlled by glucose concentration in a linear dynamic fashion, i.e., in response to a glucose step increase above threshold level h (mmol/l), provision, and thus sr_s tends with a rate constant (min^–1), and thus with a delay t = 1/ (min^–1) toward a steady-state value that is linearly related to the glucose step through the parameter _s (10^–9 min^–1):

(2)

_s thus represents the static responsivity index and measures the effect of a given glucose concentration on -cell secretion at steady state.

In the following equation, sr_d (pmol·min^–1·l^–1) represents the secretion of insulin from the promptly releasable pool and is proportional to the rate of increase of glucose through parameter _d (10^–9).

(3)

_d thus represents the dynamic responsivity index and measures the stimulatory effect of the rate of increase of glucose on secretion of stored insulin, whereas it was assumed that a decrease in glucose doesn't affect this process, accordingly with the threshold distribution hypothesis for packet storage of insulin and its mathematical modeling formulated by Grodsky (9).

In the following equation, sr_b (pmol·min^–1·l^–1) represents the basal secretion and the basal responsivity index _b (10^{– 9} min^–1) represents the effect of glucose on insulin secretion in basal state, defined as the ratio between basal insulin secretion and glucose concentration:

(4)

Profile of incretin potentiation. From model-reconstructed profiles of total insulin secretion during the OGTT (SR^OGTT) and the I-IVG (SR^I-IVG), it is possible to define the profile of the potentiation on insulin secretion due to incretin effect as

(5)

which can be separated in two additive terms, related to the contribution of static and dynamic components:

(6)

Model identification. The pancreatic secretion is linked to plasma C-peptide concentration by the two-compartment model of C-peptide kinetics originally proposed by Eaton et al. (7):

(7)

where CP₁ and CP₂ (pmol/l) are C-peptide concentrations above basal in the accessible and peripheral compartments, respectively, and k₀₁, k₁₂, and k₂₁ (min^–1) are C-peptide kinetic parameters, fixed to standard values (21) to assure numerical identification of the overall model (Eqs. 1–4 and 7). C-peptide model secretory parameters (_s, _d, _b, T, h) were estimated, together with a measure of their precision, by fitting the model to C-peptide concentration data by nonlinear least squares algorithm using SAAM II software (1). When parameter T was estimated with poor precision, the Bayesian approach implemented in SAAM II was used. Absolute weights were chosen, equal to the inverse of the variance of the measurement errors, assumed to be independent, gaussian, and zero mean with a variance linked to C-peptide (20). Glucose concentration and its time derivative were assumed as error-free model inputs.

Statistical analysis. Results are given as means ± SE. The statistical significance of differences between the same parameters in the two experiments was calculated using the Wilcoxon's signed-rank test. The statistical significance between patterns in different experiments was tested with multivariate ANOVA (MANOVA) applied to repeated measures. For sake of simplicity, when the test is not specified, the Wilcoxon's signed-rank test was used. Linear regression and Pearson correlation analyses were used to examine the relationship between parameters. Significance was declared at P < 0.05.

	RESULTS

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Plasma glucose, C-peptide, and insulin concentrations. The average concentrations of plasma glucose, C-peptide, and insulin obtained during both OGTT and I-IVG experiments are shown in Fig. 1. There were no significant differences between the basal concentrations of glucose, insulin, and C-peptide before oral and intravenous glucose administration. The glucose concentration during OGTT and I-IVG also were virtually identical, as well as the rate of glucose change (MANOVA). However, C-peptide and insulin concentrations were significantly higher (MANOVA) in OGTT than I-IVG (on average 26 and 69% from 0 to 120 min, respectively), indicating an incretin effect.

Indexes of -cell responsivity. As shown in Fig. 2, values derived using the C-peptide model closely predicted the concentrations actually observed during the OGTT and I-IVG. _s (_static) and _d (_dynamic) were estimated with good precision for all subjects, with average coefficients of variation of 6 ± 1 and 15 ± 2%, respectively. The static response to glucose was significantly greater (58%; _s = 16.4 ± 1.8 vs. 24.6 ± 2.0 10^–9 min^–1), and the dynamic response was also significantly greater (63%; _d = 278 ± 32 vs. 463 ± 86 10^–9) following ingestion than it was following infusion of glucose (Fig. 2, left). This resulted in a significant upward shift in the mean dose-response curves for both the dynamic and static response to glucose (Fig. 2, middle), with a significantly higher incretin effect for the dynamic than for the static response (MANOVA). The correlation between _s during OGTT and I-IVG was not significant (R = 0.40), whereas a significant correlation was found for _d (R = 0.65, P = 0.04) (Fig. 2, right). There also was no significant difference in either the basal responsivity index (_b = 5.4 ± 0.5 vs. 5.3 ± 0.5 10^–9 min^–1), the delay between static phase secretion and glucose concentration (T = 10.6 ± 1.8 vs. 10.3 ± 2.1 min), or the threshold concentration for insulin secretion (h = 5.4 ± 0.2 vs. 5.4 ± 0.2 mmol/l), which, as expected, was very close to the basal glucose concentration (G_b = 5.3 ± 0.2 vs. 5.3 ± 0.5 mmol/l).

View larger version (15K): [in this window] [in a new window]   Fig. 2. -cell dynamic (top) and static (bottom) responsivity during I-IVG and OGTT: indexes (means ± SE; left), dose-response curves (middle), and correlation plots (right). *P < 0.05, Wilcoxon's signed-rank test.

View larger version (12K): [in this window] [in a new window]   Fig. 3. Insulin secretion (top) and its dynamic (SRd; middle) and static (SRs; bottom) components during OGTT and I-IVG. Shaded areas indicate regions where OGTT and I-IVG values are significantly different (P < 0.05, Wilcoxon's signed-rank test, test performed at sampling times).

View larger version (10K): [in this window] [in a new window]   Fig. 4. Incretin potentiation on insulin secretion (top) and its 2 contributions from SRd (middle) and SRs (bottom) components. Shaded areas indicate regions where OGTT and I-IVG values are significantly different (P < 0.05, Wilcoxon's signed-rank test, test performed at sampling times).

View larger version (8K): [in this window] [in a new window]   Fig. 5. Incretin potentiation of insulin secretion (Fig. 4, top) plotted against corresponding values of plasma glucose concentration during OGTT.

	DISCUSSION

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To additionally support the incretin effect on both the dynamic and the static components of insulin secretion, the relationship of potentiation of insulin secretion to glucose concentration shows a hysteresis (Fig. 5), i.e., potentiation to a given plasma glucose concentration appears to be higher with increasing than with decreasing glucose. Differences are consistent (43 vs. 18% at 7.2 mmol/l), thus indicating the major role of glucose rate of change and thus of dynamic component (which is only active when glucose concentration is rising) of insulin secretion in determining incretin effect. These findings are not a by-product of the model structure, because the insulin secretion profiles, and thus P(t), are virtually superimposable, with secretion profiles reconstructed by a model-free technique such as deconvolution of C-peptide data (4).

On the other hand, no significant difference was found for the parameter describing the delay between plasma glucose concentration and static insulin secretion, suggesting that incretin amplifies the -cell response to a glucose load but does not affect the timing of this response. This is consistent with previous studies, where delay was minimally affected by the route of glucose administration in a group of 88 healthy nondiabetic subjects studied with intravenous glucose tolerance test and mixed meal (2).

The correlation between _s during OGTT and I-IVG was not significant (R = 0.40), although a significant correlation was found for _d (R = 0.65, P = 0.04). The lack of correlation for _s is probably due to a smaller range of variation of this parameter in the group of subjects (Fig. 2, right). However, it is worth noting that the low number of subjects does not allow a coefficient of correlation lower than 0.64 to be considered significant. Thus we can only conclude that incretin effect on _s has a higher inter-individual variability with respect to _d, but additional studies based on a larger number of subjects are needed to clarify this aspect of incretin potentiation.

Several models were proposed in literature for the assessment of -cell function during an oral test (6, 10, 13). All models are similar to our model insofar as each describes glucose-induced insulin secretion in terms of components related to glucose level, either immediately or with a delayed reaction, and/or reacting to the rate of change of glucose. More precisely, the model proposed by Hovorka et al. (10) assumes an instantaneous linear control of glucose on insulin secretion, i.e., there is no delay between glucose stimulus and -cell response, whereas the model proposed by Cretti et al. (6) describes insulin secretion with the static component of glucose control of the C-peptide minimal model, and thus it is characterized by a delay but does not include any dynamic, i.e., rate of change, glucose control. Interestingly, the same authors have recently included a dynamic control to describe first-phase secretion in a subsequent publication (22). However, we have argued that a rate of change of glucose component of insulin secretion is necessary to fit the data (3) and that a model without delay between glucose stimulus and -cell response is not able to fit the data in the majority of subjects that support its existence (5). However, the estimation of delay is problematic in some cases, i.e., when its value is low, because the usual sampling schedule, with samples every 10 min, does not allow estimation of delays of less than 7 min. Use of Bayesian identification solves the problem. More recently, similar results and considerations were reported (18), where it was shown that our model was able to fit both meal and HGC. The results strongly suggested that a rate of change of glucose component of insulin secretion was present during both meal and HGC; moreover, the delay was precisely estimated in all HGC studies, but only in 10 of 17 meal studies (in 5 of the 7, T was <5 min). The authors concluded that there was evidence supporting the existence of the delay in meal but noted that this delay can be suppressed or reduced in some cases. However, difficulties in estimation of delay in meals is in all likelihood related to the sparse sampling schedule, with samples every 30 min (Dr. Garry M. Steil, personal communication). Finally, in the recently proposed model of insulin secretion (13), the authors choose to account for the inability of a proportional plus derivative glucose control to account for C-peptide measurements, with a time-varying term correcting only the static component of insulin secretion. This term was named potentiation factor and was put in relation to incretin effect. Our database offers a unique data set to better elucidate the meaning of this parameter. Results of the potentiation factor of the model (13) are shown in Fig. 6. There is no difference between the time course of the potentiation factor during OGTT and I-IVG nor between the mean time of the potentiation factor (OGTT: 118.9 ± 1.1 min; I-IVG: 119.5 ± 0.8 min). These results clearly indicate that the potentiation factor of the model (13) is not related to the incretin effect. Other factors need to be advocated for putting this term on physiological grounds. It may well be that this term is simply compensating the absence of a delay in the provision of new insulin.

View larger version (8K): [in this window] [in a new window]   Fig. 6. Time course of the potentiation factor of the model (13) during OGTT and I-IVG.

	GRANTS

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This study was partially supported by National Institutes of Health Grants RR-00585 and DK-29953.

	ACKNOWLEDGMENTS

 
We thank Dr. Gianluigi Pillonetto for helpful discussion on literature models.

	FOOTNOTES

 

Address for reprint requests and other correspondence: C. Cobelli, Dept. of Information Engineering, Via Gradenigo 6a, 35131 Padua, Italy (e-mail: cobelli{at}dei.unipd.it)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

	REFERENCES

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1. Barrett PH, Bell BM, Cobelli C, Golde H, Schumitzky A, Vicini P, Foster DM. SAAM II: Simulation, Analysis, and Modeling Software for tracer and pharmacokinetic studies. Metabolism 47: 484–492, 1998.[CrossRef][Web of Science][Medline]
2. Basu R, Breda E, Oberg AL, Powell CC, Dalla Man C, Basu A, Vittone JL, Klee GG, Arora P, Jensen MD, Toffolo G, Cobelli C, Rizza RA. Mechanisms of the age-associated deterioration in glucose tolerance: contribution of alterations in insulin secretion, action, and clearance. Diabetes 52: 1738–1748, 2003 [Erratum in Diabetes 52: 3014, 2003].[Abstract/Free Full Text]
3. Breda E, Cavaghan MK, Toffolo G, Polonsky KS, Cobelli C. Oral glucose tolerance test minimal model indexes of beta-cell function and insulin sensitivity. Diabetes 50: 150–158, 2001.[Abstract/Free Full Text]
4. Breda E, Cobelli C. Insulin secretion rate during glucose stimuli: alternative analyses of C-peptide data. Ann Biomed Eng 29: 692–700, 2001.[CrossRef][Web of Science][Medline]
5. Breda E, Toffolo G, Polonsky KS, Cobelli C. Insulin release in impaired glucose tolerance: oral minimal model predicts normal sensitivity to glucose but defective response times. Diabetes 51, Suppl 1: S227–S233, 2002.[Abstract/Free Full Text]
6. Cretti A, Lehtovirta M, Bonora E, Brunato B, Zenti MG, Tosi F, Caputo M, Caruso B, Groop LC, Muggeo M, Bonadonna RC. Assessment of beta-cell function during the oral glucose tolerance test by a minimal model of insulin secretion. Eur J Clin Invest 31: 405–416, 2001.[CrossRef][Web of Science][Medline]
7. Eaton RP, Allen RC, Schade DS, Erickson KM, Standefer J. Prehepatic insulin production in man: kinetic analysis using peripheral connecting peptide behavior. J Clin Endocrinol Metab 51: 520–528, 1980.[Abstract/Free Full Text]
8. Elahi D. In praise of the hyperglycemic clamp. A method for assessment of beta-cell sensitivity and insulin resistance. Diabetes Care 19: 278–286, 1996.[Abstract]
9. Grodsky GM. A threshold distribution hypothesis for packet storage of insulin and its mathematical modeling. J Clin Invest 51: 2047–2059, 1972.[Web of Science][Medline]
9. Heding LG. Radioimmunological determination of human C-peptide in serum. Diabetologia 11: 541–548, 1975.[CrossRef][Web of Science][Medline]
9. Herbert V, Lau KS, Gottlieb CW, Bleicher SJ. Coated charcoal immunoassay of insulin. J Clin Endocrinol Metab 25: 1375–1384, 1965.[Abstract/Free Full Text]
10. Hovorka R, Chassin L, Luzio SD, Playle R, Owens DR. Pancreatic beta-cell responsiveness during meal tolerance test: model assessment in normal subjects and subjects with newly diagnosed noninsulin-dependent diabetes mellitus. J Clin Endocrinol Metab 83: 744–750, 1998.[Abstract/Free Full Text]
11. Kwan EP, Gaisano HY. Glucagon-like peptide 1 regulates sequential and compound exocytosis in pancreatic islet beta-Cells. Diabetes 54: 2734–2743, 2005.[Abstract/Free Full Text]
12. Lewis JT, Dayanandan B, Habener JF, Kieffer TJ. Glucose-dependent insulinotropic polypeptide confers early phase insulin release to oral glucose in rats: demonstration by a receptor antagonist. Endocrinology 141: 3710–3716, 2000.[Abstract/Free Full Text]
13. Mari A, Schmitz O, Gastaldelli A, Oestergaard T, Nyholm B, Ferrannini E. Meal and oral glucose tests for assessment of -cell function: modeling analysis in normal subjects. Am J Physiol Endocrinol Metab 283: E1159–E1166, 2002.[Abstract/Free Full Text]
14. Miyawaki K, Yamada Y, Yano H, Niwa H, Ban N, Ihara Y, Kubota A, Fujimoto S, Kajikawa M, Kuroe A, Tsuda K, Hashimoto H, Yamashita T, Jomori T, Tashiro F, Miyazaki J, Seino Y. Glucose intolerance caused by a defect in the entero-insular axis: a study in gastric inhibitory polypeptide receptor knockout mice. Proc Natl Acad Sci USA 96: 14843–14847, 1999.[Abstract/Free Full Text]
15. Nauck MA, Homberger E, Siegel EG, Allen RC, Eaton RP, Ebert R, Creutzfeldt W. Incretin effects of increasing glucose loads in man calculated from venous insulin, and C-peptide responses. J Clin Endocrinol Metab 63: 492–498, 1986.[Abstract/Free Full Text]
16. Shapiro ET, Tillil H, Miller MA, Frank BH, Galloway JA, Rubenstein AH, Polonsky KS. Insulin secretion and clearance. Comparison after oral and intravenous glucose. Diabetes 36: 1365–1371, 1987.[Abstract]
17. Shuster LT, Go VL, Rizza RA, O'Brien PC, Service FJ. Incretin effect due to increased secretion and decreased clearance of insulin in normal humans. Diabetes 37: 200–203, 1988.[Abstract]
18. Steil GM, Hwu CM, Janowski R, Hariri F, Jinagouda S, Darwin C, Tadros S, Rebrin K, Saad MF. Evaluation of insulin sensitivity and beta-cell function indexes obtained from minimal model analysis of a meal tolerance test. Diabetes 53: 1201–1207, 2004.[Abstract/Free Full Text]
19. Tillil H, Shapiro ET, Miller MA, Karrison T, Frank BH, Galloway JA, Rubenstein AH, Polonsky KS. Dose-dependent effects of oral and intravenous glucose on insulin secretion and clearance in normal humans. Am J Physiol Endocrinol Metab 254: E349–E357, 1988.[Abstract/Free Full Text]
20. Toffolo G, Campioni M, Basu R, Rizza RA, Cobelli C. A minimal model of insulin secretion and kinetics to assess hepatic insulin extraction. Am J Physiol Endocrinol Metab 290: E169–E176, 2006.[Abstract/Free Full Text]
21. Van Cauter E, Mestrez F, Sturis J, Polonsky KS. Estimation of insulin secretion rates from C-peptide levels. Comparison of individual and standard kinetic parameters for C-peptide clearance. Diabetes 41: 368–377, 1992.[Abstract]
22. Weiss R, Caprio S, Trombetta M, Taksali SE, Tamborlane WV, Bonadonna R. Beta-cell function across the spectrum of glucose tolerance in obese youth. Diabetes 54: 1735–1743, 2005.[Abstract/Free Full Text]

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This Article Abstract Full Text (PDF) All Versions of this Article: 292/1/E54    most recent 00033.2006v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (7) Citing Articles via Google Scholar Google Scholar Articles by Campioni, M. Articles by Cobelli, C. Search for Related Content PubMed PubMed Citation Articles by Campioni, M. Articles by Cobelli, C.