Mathematical modeling reveals differential dynamics of insulin action models on glycerol and glucose in adolescent girls with obesity.

Under healthy conditions, the pancreas responds to a glucose challenge by releasing insulin. Insulin suppresses lipolysis in adipose tissue, thereby decreasing plasma glycerol concentration, and it regulates plasma glucose concentration through action in muscle and liver. Insulin resistance (IR) occurs when more insulin is required to achieve the same effects, and IR may be tissue-specific. IR emerges during puberty as a result of high concentrations of growth hormone and is worsened by youth-onset obesity. Adipose, liver, and muscle tissue exhibit distinct dose-dependent responses to insulin in multi-phase hyperinsulinemic-euglycemic (HE) clamps, but the HE clamp protocol does not address potential differences in the dynamics of tissue-specific insulin responses. Changes to the dynamics of insulin responses would alter glycemic control in response to a glucose challenge. To investigate the dynamics of insulin acting on adipose tissue, we developed a novel differential-equations based model that describes the coupled dynamics of glycerol concentrations and insulin action during an oral glucose tolerance test in female adolescents with obesity and IR. We compared these dynamics to the dynamics of insulin acting on muscle and liver as assessed with the oral minimal model applied to glucose and insulin data collected under the same protocol. We found that the action of insulin on glycerol peaks approximately 67 min earlier (p < 0.001) and follows the dynamics of plasma insulin more closely compared to insulin action on glucose as assessed by the parameters representing the time constants for insulin action on glucose and glycerol (p < 0.001). These findings suggest that the dynamics of insulin action show tissue-specific differences in our IR adolescent population, with adipose tissue responding to insulin more quickly compared to muscle and liver. Improved understanding of the tissue-specific dynamics of insulin action may provide novel insights into the progression of metabolic disease in patient populations with diverse metabolic phenotypes.

Pancreatic fat relates to fasting insulin and postprandial lipids but not polycystic ovary syndrome in adolescents with obesity.

OBJECTIVE: Adolescents with polycystic ovary syndrome (PCOS) and obesity can have insulin resistance, dysglycemia, and hepatic steatosis. Excess pancreatic fat may disturb insulin secretion and relate to hepatic fat. Associations between pancreatic fat fraction (PFF) and metabolic measures in PCOS were unknown. METHODS: This secondary analysis included 113 sedentary, nondiabetic adolescent girls (age = 15.4 [1.9] years), with or without PCOS and BMI ≥ 90th percentile. Participants underwent fasting labs, oral glucose tolerance tests, and magnetic resonance imaging for hepatic fat fraction (HFF) and PFF. Groups were categorized by PFF (above or below the median of 2.18%) and compared. RESULTS: Visceral fat and HFF were elevated in individuals with PCOS versus control individuals, but PFF was similar. PFF did not correlate with serum androgens. Higher and lower PFF groups had similar HFF, with no correlation between PFF and HFF, although hepatic steatosis was more common in those with higher PFF (≥5.0% HFF; 60% vs. 36%; p = 0.014). The higher PFF group had higher fasting insulin (p = 0.026), fasting insulin resistance (homeostatic model assessment of insulin resistance, p = 0.032; 1/fasting insulin, p = 0.028), free fatty acids (p = 0.034), and triglycerides (p = 0.004) compared with those with lower PFF. ß-Cell function and insulin sensitivity were similar between groups. CONCLUSIONS: Neither PCOS status nor androgens related to PFF. However, fasting insulin and postprandial lipids were worse with higher PFF.

Oral minimal model-based estimates of insulin sensitivity in obese youth depend on oral glucose tolerance test protocol duration.

INTRODUCTION: The Oral Minimal Model (OMM), a differential-equations based mathematical model of glucose-insulin dynamics, utilizes data from a frequently sampled oral glucose tolerance test (OGTT) to quantify insulin sensitivity ( S I ). OMM-based estimates of S I can detect differences in insulin resistance (IR) across population groups and quantify effects of clinical or behavioral interventions. These estimates of S I have been validated in healthy adults using data from OGTTs with durations from 2 to 7 h. However, data demonstrating how protocol duration affects S I estimates in highly IR populations such as adolescents with obesity are limited. METHODS: A 6-h frequently sampled OGTT was performed in adolescent females with obesity. Two, 3-, and 4- hour implementations of OMM assuming an exponentially-decaying rate of glucose appearance beyond measured glucose concentrations were compared to the 6-h implementation. A 4- hour OMM implementation with truncated data (4h Tr) was also considered. RESULTS: Data from 68 participants were included (age 15.8 ± 1.2 years, BMI 35.4 ± 5.6 kg/m2). Although S I values were highly correlated for all implementations, they varied with protocol duration (2h: 2.86 ± 3.31, 3h: 2.55 ± 2.62, 4h: 2.81 ± 2.59, 4h tr: 3.13 ± 3.14, 6h: 3.06 ± 2.85 x 10-4 dl/kg/min per U/ml). S I estimates based on 2 or 3 h of data underestimated S I values, whereas 4-h S I estimates more closely approximated 6-h S I values. DISCUSSION: These results suggest that OGTT protocol duration should be considered when implementing OMM to estimate S I in adolescents with obesity and other IR populations.

Good agreement between hyperinsulinemic-euglycemic clamp and 2 hours oral minimal model assessed insulin sensitivity in adolescents.

BACKGROUND/OBJECTIVE: Rates of dysglycemia are increasing in youth, secondary to obesity and decreased insulin sensitivity (IS) in puberty. The oral minimal model (OMM) has been developed in order to measure IS using an easy oral glucose load, such as an oral glucose tolerance test (OGTT), instead of an hyperinsulinemic-euglycemic clamp (HE-clamp), a more invasive and time-consuming procedure. However, this model, following a standard 2 hour- OGTT has never been validated in youth, a population known for a different physiologic response to OGTT than adults. Thus, we compared IS measurements obtained from OMM following a 2-hour OGTT to HE-clamp and isotope tracer-assessed tissue IS in adolescents. We also compared the liver/muscle-specific IS from HE-clamp with other liver/muscle-specific IS surrogates following an OGTT previously validated in adults. METHODS: Secondary analysis of a cross-sectional study. Adolescent girls with (n = 26) and without (n = 7) polycystic ovary syndrome (PCOS) (14.6 ± 1.7 years; BMI percentile 23.3%-98.2%) underwent a 2-hour 75 g OGTT and a 4-phase HE-clamp. OMM IS (Si), dynamic Si (Sid ) and other OGTT-derived muscle and liver IS indices were correlated with HE-clamp tissue-specific IS. RESULTS: OMM Si and Sid correlated with HE-clamp-measured peripheral IS (r = 0.64, P <.0001 and r = 0.73; P <.0001, respectively) and the correlation coefficient trended higher than the Matsuda index (r = 0.59; P =.003). The other tissue-specific indices were poorly correlated with their HE-clamp measurements. CONCLUSION: In adolescent girls, the 2-hour OMM provided the best estimate of peripheral IS. Additional surrogates for hepatic IS are needed for youth.