Insulin clearance is altered in women with a history of gestational diabetes progressing to type 2 diabetes

Maternal overweight and obesity and its association with metabolic changes and fetal overgrowth in the absence of gestational diabetes mellitus: A prospective cohort study

INTRODUCTION

Previous studies indicated an association between fetal overgrowth and maternal obesity independent of gestational diabetes mellitus (GDM). However, the underlying mechanisms beyond this possible association are not completely understood. This study investigates metabolic changes and their association with fetal and neonatal biometry in overweight and obese mothers who remained normal glucose-tolerant during gestation.

MATERIAL AND METHODS

In this prospective cohort study 893 women who did not develop GDM were categorized according to their pregestational body mass index (BMI): 570 were normal weight, 220 overweight and 103 obese. Study participants received a broad metabolic evaluation before 16 weeks and were followed up until delivery to assess glucose levels during the oral glucose tolerance test (OGTT) at mid-gestation as well as fetal biometry in ultrasound and pregnancy outcome data.

RESULTS

Increased maternal BMI was associated with an adverse metabolic profile at the beginning of pregnancy, including a lower degree of insulin sensitivity (as assessed by the quantitative insulin sensitivity check index) in overweight (mean difference: -2.4, 95% CI -2.9 to -1.9, p < 0.001) and obese (mean difference: -4.3, 95% CI -5.0 to -3.7, p < 0.001) vs normal weight women. Despite not fulfilling diagnosis criteria for GDM, overweight and obese mothers showed higher glucose levels at fasting and during the OGTT. Finally, we observed increased measures of fetal subcutaneous tissue thickness in ultrasound as well as higher proportions of large-for-gestational-age infants in overweight (18.9%, odds ratio [OR] 1.74, 95% CI 1.08-2.78, p = 0.021) and obese mothers (21.0%, OR 1.99, 95% CI 1.06-3.59, p = 0.027) vs normal weight controls (11.8%). The risk for large for gestational age was further determined by OGTT glucose (60 min: OR 1.11, 95% CI 1.02-1.21, p = 0.013; 120 min: OR 1.13, 95% CI 1.02-1.27, P = 0.025, for the increase of 10 mg/dL) and maternal triglyceride concentrations (OR 1.11, 95% CI 1.01-1.22, p = 0.036, for the increase of 20 mg/dL).

CONCLUSIONS

Mothers affected by overweight or obesity but not GDM had a higher risk for fetal overgrowth. An impaired metabolic milieu related to increased maternal BMI as well as higher glucose levels at mid-gestation may impact fetal overgrowth in women still in the range of normal glucose tolerance.

Unraveling the Factors Determining Development of Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus Through Machine-Learning Techniques

Gestational diabetes mellitus (GDM) is a type of diabetes that usually resolves at the end of the pregnancy but exposes to a higher risk of developing type 2 diabetes mellitus (T2DM). This study aimed to unravel the factors, among those that quantify specific metabolic processes, which determine progression to T2DM by using machine-learning techniques. Classification of women who did progress to T2DM (labeled as PROG, n = 19) vs. those who did not (labeled as NON-PROG, n = 59) progress to T2DM has been performed by using Orange software through a data analysis procedure on a generated data set including anthropometric data and a total of 34 features, extracted through mathematical modeling/methods procedures. Feature selection has been performed through decision tree algorithm and then Naïve Bayes and penalized (L2) logistic regression were used to evaluate the ability of the selected features to solve the classification problem. Performance has been evaluated in terms of area under the operating receiver characteristics (AUC), classification accuracy (CA), precision, sensitivity, specificity, and F1. Feature selection provided six features, and based on them, classification was performed as follows: AUC of 0.795, 0.831, and 0.884; CA of 0.827, 0.813, and 0.840; precision of 0.830, 0.854, and 0.834; sensitivity of 0.827, 0.813, and 0.840; specificity of 0.700, 0.821, and 0.662; and F1 of 0.828, 0.824, and 0.836 for tree algorithm, Naïve Bayes, and penalized logistic regression, respectively. Fasting glucose, age, and body mass index together with features describing insulin action and secretion may predict the development of T2DM in women with a history of GDM.

Insulin clearance and incretin hormones following oral and "isoglycemic" intravenous glucose in type 2 diabetes patients under different antidiabetic treatments

It has not been elucidated whether incretins affect insulin clearance in type 2 diabetes (T2D). We aimed exploring possible associations between insulin clearance and endogenously secreted or exogenously administered incretins in T2D patients. Twenty T2D patients were studied (16 males/4 females, 59 ± 2 years (mean ± standard error), BMI = 31 ± 1 kg/m2, HbA1c = 7.0 ± 0.1%). Patients were treated with metformin, sitagliptin, metformin/sitagliptin combination, and placebo (randomized order). On each treatment period, oral and isoglycemic intravenous glucose infusion tests were performed (OGTT, IIGI, respectively). We also studied twelve T2D patients (9 males/3 females, 61 ± 3 years, BMI = 30 ± 1 kg/m2, HbA1c = 7.3 ± 0.4%) that underwent infusion of GLP-1(7-36)-amide, GIP, GLP-1/GIP combination, and placebo. Plasma glucose, insulin, C-peptide, and incretins were measured. Insulin clearance was assessed as insulin secretion to insulin concentration ratio. In the first study, we found OGTT/IIGI insulin clearance ratio weakly inversely related to OGTT/IIGI total GIP and intact GLP-1 (R2 = 0.13, p < 0.02). However, insulin clearance showed some differences between sitagliptin and metformin treatment (p < 0.02). In the second study we found no difference in insulin clearance following GLP-1 and/or GIP infusion (p > 0.5). Thus, our data suggest that in T2D there are no relevant incretin effects on insulin clearance. Conversely, different antidiabetic treatments may determine insulin clearance variations.

Low Birth Weight, β-Cell Function and Insulin Resistance in Adults: The Brazilian Longitudinal Study of Adult Health

BACKGROUND

Adverse intrauterine environment-reflected by low birth weight (LBW)-has been linked to insulin resistance and type 2 diabetes later in life. Whether β-cell function reduction and insulin resistance could be detected even in middle-aged adults without overt diabetes is less investigated. We examined the association of LBW with β-cell function and insulin sensitivity in non-diabetic middle-aged adults from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

METHODS

This is a cross-sectional analysis of 2,634 ELSA-Brasil participants aged between 34 and 59 years, without diabetes. Participants were stratified according to LBW defined as <2.5 kg and their clinical data were compared. HOMA-IR, HOMA-β, HOMA-adiponectin, TyG index, QUICKI and TG/HDL were calculated and their association with LBW were tested using multiple linear regression including adjustments suggested by Directed Acyclic Graphs and propensity score matching was applied.

RESULTS

The sample (47.4 ± 6.3 years) was composed of 57.5% of women and 9% had LBW. Subjects with LBW and normal-weight reported similar BMI values at the age of 20 years and current BMI was slightly lower in the LBW group. In average, cardiometabolic risk profile and also indexes of β-cell function and insulin sensitivity were within normal ranges. In regression analysis, log-transformed HOMA-β-but not with the other indexes-was associated with LBW (p = 0.014) independent of sex, skin color, prematurity, and family history of diabetes. After applying propensity-score matching in a well-balanced sample, HOMA-AD and TG/HDL indexes were associated with LBW.

CONCLUSION

The association between LBW and insulin sensitivity markers may occur in healthy middle-aged adults before overt glucose metabolism disturbances. Our data are coherent with the detection of early life events consequent with insulin resistance markers that could contribute to the risk of glucose metabolism disturbances.

Model-Based Assessment of Hepatic and Extrahepatic Insulin Clearance from Short Insulin-Modified IVGTT in Women with a History of Gestational Diabetes

Insulin clearance is an integral component of insulin metabolism. Yet, little is known about separate contribution of hepatic and extrahepatic insulin clearance in type 2 diabetes and in high-risk populations, such as women who experienced gestational diabetes mellitus (pGDM). A model-based method was recently proposed to assess both contributions from 3-hour insulin-modified intravenous glucose tolerance test (IM-IVGTT); the aim of this study was to assess the reliability of short (1 hour) IM-IVGTT in the application of such model-based method and to evaluate the role of the two contributions in determining insulin clearance in pGDM. A total of 115 pGDM women and 41 who remained healthy during pregnancy (CNT) were analyzed early postpartum and underwent a 3-hour IMIVGTT. Peripheral insulin clearance (CL_P), hepatic fractional extraction (FE_L) and extrahepatic distribution volume (V_P) were estimated by performing a best-fit procedure on insulin IMIVGTT data considering firstly the overall 3-hour duration and then limiting data to 1 hour. Results showed no significant difference in parameter values between the 3-hour and the 1-hour IM-IVGTT. Comparison between pGDM and CNT (1-hour) showed no significant difference in CL_p (0.23 [0.29] vs. 0.27 [0.43] L·min^-1; p=0.64), FE_L (50.2 [15.1] vs. 50.9 [11.7] %; p=0.63) and V_P (2.01 [2.99] vs. 2.70 [4.00] L; p=0.92). In conclusion, short IM-IVGTT provides a reliable assessment of hepatic and extrahepatic insulin clearance through such model-based method. Its application to the study of pGDM women showed no alteration in hepatic and extrahepatic contributions with respect to women who had a healthy pregnancy.Clinical Relevance- This study proves the reliability of short (1 hour) IM-IVGTT to assess hepatic and extrahepatic insulin clearance in women who experienced gestational diabetes.

Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA_1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA_1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISR_r), and insulin secretion potentiation (P < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISR_r (P < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, P < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.

Hepatic and Extrahepatic Insulin Clearance in Mice with Double Deletion of Glucagon-Like Peptide-1 and Glucose-Dependent Insulinotropic Polypeptide Receptors

The aim of this study was to investigate whether incretins, at physiological levels, affect hepatic and/or extrahepatic insulin clearance. Hepatic and extrahepatic insulin clearance was studied in 31 double incretin receptor knockout (DIRKO) and 45 wild-type (WT) mice, which underwent an Intravenous Glucose Tolerance Test (IVGTT). A novel methodology based on mathematical modeling was designed to provide two sets of values (FE_L-P1, CL_P-P1; FE_L-P2, CL_P-P2) accounting for hepatic and extrahepatic clearance in the IVGTT first and second phases, respectively, plus the respective total clearances, CL_T-P1 and CL_T-P2. A statistically significant difference between DIRKO and WT was found in CL_T-P1 (0.61 [0.48–0.82] vs. 0.51 [0.46–0.65] (median [interquartile range]); p = 0.02), which was reflected in the peripheral component, CL_P-P1 (0.18 [0.13–0.27] vs. 0.15 [0.11–0.22]; p = 0.04), but not in the hepatic component, FE_L-P1 (29.7 [26.7–34.9] vs. 28.9 [25.7–32.0]; p = 0.18). No difference was detected between DIRKO and WT in CL_T-P2 (1.38 [1.13–1.75] vs. 1.69 [1.48–1.87]; p = 0.10), neither in CL_P-P2 (0.72 [0.64–0.81] vs. 0.79 [0.69–0.87]; p = 0.27) nor in FE_L-P2 (37.8 [35.1–43.1] vs. 39.8 [35.8–44.2]; p = 0.46). In conclusion, our findings suggest that the higher insulin clearance observed in DIRKO compared with WT during the IVGTT first phase may be due to its extrahepatic component.

Mathematical Model of Glucagon Kinetics for the Assessment of Insulin-Mediated Glucagon Inhibition During an Oral Glucose Tolerance Test

Glucagon is secreted from the pancreatic alpha cells and plays an important role in the maintenance of glucose homeostasis, by interacting with insulin. The plasma glucose levels determine whether glucagon secretion or insulin secretion is activated or inhibited. Despite its relevance, some aspects of glucagon secretion and kinetics remain unclear. To gain insight into this, we aimed to develop a mathematical model of the glucagon kinetics during an oral glucose tolerance test, which is sufficiently simple to be used in the clinical practice. The proposed model included two first-order differential equations -one describing glucagon and the other describing C-peptide in a compartment remote from plasma - and yielded a parameter of possible clinical relevance (i.e., S_GLUCA(t), glucagon-inhibition sensitivity to glucose-induced insulin secretion). Model was validated on mean glucagon data derived from the scientific literature, yielding values for S_GLUCA(t) ranging from -15.03 to 2.75 (ng of glucagon·nmol of C-peptide^-1). A further validation on a total of 100 virtual subjects provided reliable results (mean residuals between -1.5 and 1.5 ng·L^-1) and a negative significant linear correlation (r = -0.74, p < 0.0001, 95% CI: -0.82 - -0.64) between S_GLUCA(t) and the ratio between the areas under the curve of suprabasal remote C-peptide and glucagon. Model reliability was also proven by the ability to capture different patterns in glucagon kinetics. In conclusion, the proposed model reliably reproduces glucagon kinetics and is characterized by sufficient simplicity to be possibly used in the clinical practice, for the estimation in the single individual of some glucagon-related parameters.