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Routine OGTT: a robust model including incretin effect for precise identification of insulin sensitivity and secretion in a single individual.

De Gaetano A, Panunzi S, Matone A, Samson A, Vrbikova J, Bendlova B, Pacini G - PLoS ONE (2013)

Bottom Line: ANOVA on kxgi values across groups resulted significant overall (P<0.001), and post-hoc comparisons highlighted the presence of three different groups: NGT (8.62×10(-5)±9.36×10(-5) min(-1)pM(-1)), IFG (5.30×10(-5)±5.18×10(-5)) and combined IGT, IFG+IGT and T2DM (2.09×10(-5)±1.95×10(-5), 2.38×10(-5)±2.28×10(-5) and 2.38×10(-5)±2.09×10(-5) respectively).No significance was obtained when comparing ISCOMO or ISDMMO across groups.The kxgi index, reflecting insulin secretion dependency on glycemia, also significantly differentiates clinically diverse subject groups.

View Article: PubMed Central - PubMed

Affiliation: Institute of System Analysis and Informatics (IASI) A. Ruberti, National Research Council (CNR), Rome, Italy.

ABSTRACT
In order to provide a method for precise identification of insulin sensitivity from clinical Oral Glucose Tolerance Test (OGTT) observations, a relatively simple mathematical model (Simple Interdependent glucose/insulin MOdel SIMO) for the OGTT, which coherently incorporates commonly accepted physiological assumptions (incretin effect and saturating glucose-driven insulin secretion) has been developed. OGTT data from 78 patients in five different glucose tolerance groups were analyzed: normal glucose tolerance (NGT), impaired glucose tolerance (IGT), impaired fasting glucose (IFG), IFG+IGT, and Type 2 Diabetes Mellitus (T2DM). A comparison with the 2011 Salinari (COntinuos GI tract MOdel, COMO) and the 2002 Dalla Man (Dalla Man MOdel, DMMO) models was made with particular attention to insulin sensitivity indices ISCOMO, ISDMMO and kxgi (the insulin sensitivity index for SIMO). ANOVA on kxgi values across groups resulted significant overall (P<0.001), and post-hoc comparisons highlighted the presence of three different groups: NGT (8.62×10(-5)±9.36×10(-5) min(-1)pM(-1)), IFG (5.30×10(-5)±5.18×10(-5)) and combined IGT, IFG+IGT and T2DM (2.09×10(-5)±1.95×10(-5), 2.38×10(-5)±2.28×10(-5) and 2.38×10(-5)±2.09×10(-5) respectively). No significance was obtained when comparing ISCOMO or ISDMMO across groups. Moreover, kxgi presented the lowest sample average coefficient of variation over the five groups (25.43%), with average CVs for ISCOMO and ISDMMO of 70.32% and 57.75% respectively; kxgi also presented the strongest correlations with all considered empirical measures of insulin sensitivity. While COMO and DMMO appear over-parameterized for fitting single-subject clinical OGTT data, SIMO provides a robust, precise, physiologically plausible estimate of insulin sensitivity, with which habitual empirical insulin sensitivity indices correlate well. The kxgi index, reflecting insulin secretion dependency on glycemia, also significantly differentiates clinically diverse subject groups. The SIMO model may therefore be of value for the quantification of glucose homeostasis from clinical OGTT data.

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Visual Predictive Check.Visual Predictive Check (VPC) for each of the 5 groups (panel A for NGT, IFG and IGT; panel B for IFG+IGT and T2DM). For each patient 200 simulations were performed with the model: the shaded area represents the 90% prediction interval, dashed lines represent the 25-th, 50-th and 75-th percentile. Observed data are reported as circles.
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pone-0070875-g002: Visual Predictive Check.Visual Predictive Check (VPC) for each of the 5 groups (panel A for NGT, IFG and IGT; panel B for IFG+IGT and T2DM). For each patient 200 simulations were performed with the model: the shaded area represents the 90% prediction interval, dashed lines represent the 25-th, 50-th and 75-th percentile. Observed data are reported as circles.

Mentions: The original set of parameters of the Salinari et. al. [13] model to be estimated for each subject consisted in fact of seven parameters: k, c2, SG, SI, p, GLPb, and bGLP (see Appendix S1 for a more detailed description of the implemented model). The remaining model parameters were set to fixed values by the same authors. In particular, in the present work the values used for the fixed parameters are those reported in the legend of Figure 2 in [13], with z1 = 0 cm, z2 = 630 cm, s1 = 35 cm, s2 = 140 cm, L = 630 cm, u = 3.5 cm/min, β = 1.2 and V = 0.19 L/kg. Parameters GLPb and bGLP should be estimated from the observed GLP-1 dynamics. Because of the lack of GLP-1 observations, in the present work GLPb, and bGLP were set to the average values reported in Table 1 of [13], that is to 17.6 pM and 6.33×10−9 L−1 respectively, while parameters k, c2, SG, SI and p were free and were therefore estimated.


Routine OGTT: a robust model including incretin effect for precise identification of insulin sensitivity and secretion in a single individual.

De Gaetano A, Panunzi S, Matone A, Samson A, Vrbikova J, Bendlova B, Pacini G - PLoS ONE (2013)

Visual Predictive Check.Visual Predictive Check (VPC) for each of the 5 groups (panel A for NGT, IFG and IGT; panel B for IFG+IGT and T2DM). For each patient 200 simulations were performed with the model: the shaded area represents the 90% prediction interval, dashed lines represent the 25-th, 50-th and 75-th percentile. Observed data are reported as circles.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3756988&req=5

pone-0070875-g002: Visual Predictive Check.Visual Predictive Check (VPC) for each of the 5 groups (panel A for NGT, IFG and IGT; panel B for IFG+IGT and T2DM). For each patient 200 simulations were performed with the model: the shaded area represents the 90% prediction interval, dashed lines represent the 25-th, 50-th and 75-th percentile. Observed data are reported as circles.
Mentions: The original set of parameters of the Salinari et. al. [13] model to be estimated for each subject consisted in fact of seven parameters: k, c2, SG, SI, p, GLPb, and bGLP (see Appendix S1 for a more detailed description of the implemented model). The remaining model parameters were set to fixed values by the same authors. In particular, in the present work the values used for the fixed parameters are those reported in the legend of Figure 2 in [13], with z1 = 0 cm, z2 = 630 cm, s1 = 35 cm, s2 = 140 cm, L = 630 cm, u = 3.5 cm/min, β = 1.2 and V = 0.19 L/kg. Parameters GLPb and bGLP should be estimated from the observed GLP-1 dynamics. Because of the lack of GLP-1 observations, in the present work GLPb, and bGLP were set to the average values reported in Table 1 of [13], that is to 17.6 pM and 6.33×10−9 L−1 respectively, while parameters k, c2, SG, SI and p were free and were therefore estimated.

Bottom Line: ANOVA on kxgi values across groups resulted significant overall (P<0.001), and post-hoc comparisons highlighted the presence of three different groups: NGT (8.62×10(-5)±9.36×10(-5) min(-1)pM(-1)), IFG (5.30×10(-5)±5.18×10(-5)) and combined IGT, IFG+IGT and T2DM (2.09×10(-5)±1.95×10(-5), 2.38×10(-5)±2.28×10(-5) and 2.38×10(-5)±2.09×10(-5) respectively).No significance was obtained when comparing ISCOMO or ISDMMO across groups.The kxgi index, reflecting insulin secretion dependency on glycemia, also significantly differentiates clinically diverse subject groups.

View Article: PubMed Central - PubMed

Affiliation: Institute of System Analysis and Informatics (IASI) A. Ruberti, National Research Council (CNR), Rome, Italy.

ABSTRACT
In order to provide a method for precise identification of insulin sensitivity from clinical Oral Glucose Tolerance Test (OGTT) observations, a relatively simple mathematical model (Simple Interdependent glucose/insulin MOdel SIMO) for the OGTT, which coherently incorporates commonly accepted physiological assumptions (incretin effect and saturating glucose-driven insulin secretion) has been developed. OGTT data from 78 patients in five different glucose tolerance groups were analyzed: normal glucose tolerance (NGT), impaired glucose tolerance (IGT), impaired fasting glucose (IFG), IFG+IGT, and Type 2 Diabetes Mellitus (T2DM). A comparison with the 2011 Salinari (COntinuos GI tract MOdel, COMO) and the 2002 Dalla Man (Dalla Man MOdel, DMMO) models was made with particular attention to insulin sensitivity indices ISCOMO, ISDMMO and kxgi (the insulin sensitivity index for SIMO). ANOVA on kxgi values across groups resulted significant overall (P<0.001), and post-hoc comparisons highlighted the presence of three different groups: NGT (8.62×10(-5)±9.36×10(-5) min(-1)pM(-1)), IFG (5.30×10(-5)±5.18×10(-5)) and combined IGT, IFG+IGT and T2DM (2.09×10(-5)±1.95×10(-5), 2.38×10(-5)±2.28×10(-5) and 2.38×10(-5)±2.09×10(-5) respectively). No significance was obtained when comparing ISCOMO or ISDMMO across groups. Moreover, kxgi presented the lowest sample average coefficient of variation over the five groups (25.43%), with average CVs for ISCOMO and ISDMMO of 70.32% and 57.75% respectively; kxgi also presented the strongest correlations with all considered empirical measures of insulin sensitivity. While COMO and DMMO appear over-parameterized for fitting single-subject clinical OGTT data, SIMO provides a robust, precise, physiologically plausible estimate of insulin sensitivity, with which habitual empirical insulin sensitivity indices correlate well. The kxgi index, reflecting insulin secretion dependency on glycemia, also significantly differentiates clinically diverse subject groups. The SIMO model may therefore be of value for the quantification of glucose homeostasis from clinical OGTT data.

Show MeSH
Related in: MedlinePlus