Progression to type 2 diabetes in women with former gestational diabetes: time trajectories of metabolic parameters

Predictors of glycemic worsening in the next year in adults with screen-detected type 2 diabetes

Background and Aims

Identifying simple markers of risk for worsening glucose can allow care providers to target therapeutic interventions according to risk of worsening glycemic control. We aimed to determine which routine clinical measures herald near-term glycemic worsening in early type 2 diabetes(T2D).

Methods

The Early Diabetes Intervention Program (EDIP) was a clinical trial in individuals with screendetected T2D [HbA1C 6.3+0.63%(45+5mmol/mol)]. During the trial some participants experienced worsening fasting blood glucose (FBG). We investigated the time course of FBG, HbA1c, weight, and other clinical factors to determine which might herald glycemic worsening over the next year.

Results

Progressors (62/219, 28.5%) had higher FBG than non-progressors at baseline [118 vs 130mg/dL (6.6 vs 7.2 mmol/L), p=<0.001]. FBG was stable except in the year of progression, when progressors exhibited a large 1-year rise [mean change 14.2mg/dL(0.79 mmol/L)]. Current FBG and antecedent year change in FBG were associated with progression(p<0.01), although the magnitude of change was too small to be of clinical utility (0.19 mg/dL; 0.01 mmol/L). Current or antecedent year change in HbA1c, weight, TG or HDL were not associated with progression. In the year of glycemic worsening, rising glucose was strongly associated with a concurrent increase in weight (p<0.001).

Conclusions

Elevated FBG but not HbA1c identified individuals at risk for imminent glycemic worsening; the subsequent large rise in glucose was associated with a short-term increase in weight. Glucose and weight surveillance provide actionable information for those caring for patients with early diabetes.

Glucagon kinetics assessed by mathematical modelling during oral glucose administration in people spanning from normal glucose tolerance to type 2 diabetes

Background/Objectives

Glucagon is important in the maintenance of glucose homeostasis, with also effects on lipids. In this study, we aimed to apply a recently developed model of glucagon kinetics to determine the sensitivity of glucagon variations (especially, glucagon inhibition) to insulin levels ("alpha-cell insulin sensitivity"), during oral glucose administration.

Subjects/Methods

We studied 50 participants (spanning from normal glucose tolerance to type 2 diabetes) undergoing frequently sampled 5-hr oral glucose tolerance test (OGTT). The alpha-cell insulin sensitivity and the glucagon kinetics were assessed by a mathematical model that we developed previously.

Results

The alpha-cell insulin sensitivity parameter (named SGLUCA; "GLUCA": "glucagon") was remarkably variable among participants (CV=221%). SGLUCA was found inversely correlated with the mean glycemic values, as well as with 2-hr glycemia of the OGTT. When stratifying participants into two groups (normal glucose tolerance, NGT, N=28, and impaired glucose regulation/type 2 diabetes, IGR_T2D, N=22), we found that SGLUCA was lower in the latter (1.50 ± 0.50·10-2 vs. 0.26 ± 0.14·10-2 ng·L-1 GLUCA/pmol·L-1 INS, in NGT and IGR_T2D, respectively, p=0.009; "INS": "insulin").

Conclusions

The alpha-cell insulin sensitivity is highly variable among subjects, and it is different in groups at different glucose tolerance. This may be relevant for defining personalized treatment schemes, in terms of dietary prescriptions but also for treatments with glucagon-related agents.

Glucometabolism in Kidney Transplant Recipients with and without Posttransplant Diabetes: Focus on Beta-Cell Function

Posttransplant diabetes mellitus (PTDM) is a common complication after kidney transplantation. Pathophysiologically, whether beta-cell dysfunction rather than insulin resistance may be the predominant defect in PTDM has been a matter of debate. The aim of the present analysis was to compare glucometabolism in kidney transplant recipients with and without PTDM. To this aim, we included 191 patients from a randomized controlled trial who underwent oral glucose tolerance tests (OGTTs) 6 months after transplantation. We derived several basic indices of beta-cell function and insulin resistance as well as variables from mathematical modeling for a more robust beta-cell function assessment. Mean ± standard deviation of the insulin sensitivity parameter PREDIM was 3.65 ± 1.68 in PTDM versus 5.46 ± 2.57 in NON-PTDM. Model-based glucose sensitivity (indicator of beta-cell function) was 68.44 ± 57.82 pmol∙min-1∙m-2∙mM-1 in PTDM versus 143.73 ± 112.91 pmol∙min-1∙m-2∙mM-1 in NON-PTDM, respectively. Both basic indices and model-based parameters of beta-cell function were more than 50% lower in patients with PTDM, indicating severe beta-cell impairment. Nonetheless, some defects in insulin sensitivity were also present, although less marked. We conclude that in PTDM, the prominent defect appears to be beta-cell dysfunction. From a pathophysiological point of view, patients at high risk for developing PTDM may benefit from intensive treatment of hyperglycemia over the insulin secretion axis.

Glucometabolic Alterations in Pregnant Women with Overweight or Obesity but without Gestational Diabetes Mellitus: An Observational Study

INTRODUCTION

Maternal overweight is a risk factor for gestational diabetes mellitus (GDM). However, emerging evidence suggests that an increased maternal body mass index (BMI) promotes the development of perinatal complications even in women who do not develop GDM. This study aims to assess physiological glucometabolic changes associated with increased BMI.

METHODS

Twenty-one women with overweight and 21 normal weight controls received a metabolic assessment at 13 weeks of gestation, including a 60-min frequently sampled intravenous glucose tolerance test. A further investigation was performed between 24 and 28 weeks in women who remained normal glucose tolerant.

RESULTS

At baseline, mothers with overweight showed impaired insulin action, whereby the calculated insulin sensitivity index (CSI) was lower as compared to normal weight controls (3.5 vs. 6.7 10-4 min-1 [microU/mL]-1, p = 0.025). After excluding women who developed GDM, mothers with overweight showed higher average glucose during the oral glucose tolerance test (OGTT) at the third trimester. Moreover, early pregnancy insulin resistance and secretion were associated with increased placental weight in normal glucose-tolerant women.

CONCLUSION

Mothers with overweight or obesity show an unfavorable metabolic environment already at the early stage of pregnancy, possibly associated with perinatal complications in women who remain normal glucose tolerant.

TyGIS: improved triglyceride-glucose index for the assessment of insulin sensitivity during pregnancy

Background

The triglyceride-glucose index (TyG) has been proposed as a surrogate marker of insulin resistance, which is a typical trait of pregnancy. However, very few studies analyzed TyG performance as marker of insulin resistance in pregnancy, and they were limited to insulin resistance assessment at fasting rather than in dynamic conditions, i.e., during an oral glucose tolerance test (OGTT), which allows more reliable assessment of the actual insulin sensitivity impairment. Thus, first aim of the study was exploring in pregnancy the relationships between TyG and OGTT-derived insulin sensitivity. In addition, we developed a new version of TyG, for improved performance as marker of insulin resistance in pregnancy.

Methods

At early pregnancy, a cohort of 109 women underwent assessment of maternal biometry and blood tests at fasting, for measurements of several variables (visit 1). Subsequently (26 weeks of gestation) all visit 1 analyses were repeated (visit 2), and a subgroup of women (84 selected) received a 2 h-75 g OGTT (30, 60, 90, and 120 min sampling) with measurement of blood glucose, insulin and C-peptide for reliable assessment of insulin sensitivity (PREDIM index) and insulin secretion/beta-cell function. The dataset was randomly split into 70% training set and 30% test set, and by machine learning approach we identified the optimal model, with TyG included, showing the best relationship with PREDIM. For inclusion in the model, we considered only fasting variables, in agreement with TyG definition.

Results

The relationship of TyG with PREDIM was weak. Conversely, the improved TyG, called TyGIS, (linear function of TyG, body weight, lean body mass percentage and fasting insulin) resulted much strongly related to PREDIM, in both training and test sets (R² > 0.64, p < 0.0001). Bland–Altman analysis and equivalence test confirmed the good performance of TyGIS in terms of association with PREDIM. Different further analyses confirmed TyGIS superiority over TyG.

Conclusions

We developed an improved version of TyG, as new surrogate marker of insulin sensitivity in pregnancy (TyGIS). Similarly to TyG, TyGIS relies only on fasting variables, but its performances are remarkably improved than those of TyG.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01649-8.

Pre-diabetes, diabetes and fluctuations of glucose tolerance after gestational diabetes mellitus: 5-year follow-up of a contemporary, prospective study in Germany

INTRODUCTION

Ten years ago, Germany started offering screening for gestational diabetes mellitus (GDM) to all pregnant women. This approach revealed more but also, on average, less severe cases of GDM than the risk-based screening practiced previously. We now examined the incidence of pre-diabetes and diabetes following a GDM diagnosis in the era of universal screening in Germany and compared our results with studies in the previous period. Additionally, we examined the year-to-year fluctuations of glucose tolerance after a pregnancy complicated by GDM.

RESEARCH DESIGN AND METHODS

We report 5-year follow-up data from 202 women in the prospective, monocenter, postpartum study PPSDiab. Consecutive recruitment took place in Munich, Germany between 2011 and 2016. In the study, we conducted yearly examinations that included anthropometrics, laboratory chemistry and oral glucose tolerance testing.

RESULTS

During the first 5 years post partum, 111 (55%) and 12 (6%) of the women developed pre-diabetes and type 2 diabetes, respectively, while 2 (1%) developed type 1 diabetes. Impaired fasting glucose (IFG) was the most common first manifestation of disturbed glucose tolerance, followed by impaired glucose tolerance (IGT), the combination of IFG and IGT, and diabetes. Glucose tolerance did not deteriorate steadily in most women but fluctuated from year to year.

CONCLUSIONS

In our analysis, the incidence of diabetes, both type 1 and type 2, after GDM diagnosed in universal screening was substantially lower than in studies from the previous period of risk-based screening. Nevertheless, the high incidence of pre-diabetes we observed after GDM still confirms the importance of this diagnosis as a risk marker. Additionally, we documented frequent fluctuations of glucose tolerance from 1 year to the next. Therefore, a single postpartum glucose tolerance test, as currently practiced in routine care, may be insufficient for reliable risk stratification after GDM.

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.

Risk and Risk Factors for Postpartum Type 2 Diabetes Mellitus in Women with Gestational Diabetes: A Korean Nationwide Cohort Study

BACKGROUND

There are differences in risk and risk factor findings of postpartum type 2 diabetes mellitus (T2DM) after gestational diabetes depending on study design and subjects of previous studies. This study aimed to assess these risk and risk factors more accurately through a population-based study to provide basic data for prevention strategies.

METHODS

This open retrospective cohort included data of 419,101 women with gestational diabetes and matched 1,228,802 control women who delivered between 2004 and 2016 from the South Korea National Health Information Database of the National Health Insurance Service. Following 14 (median 5.9) years of follow-up, the incidence and hazard ratio (HR) of postpartum T2DM were evaluated using Kaplan-Meier curves and Cox proportional regression models.

RESULTS

The incidence and HR of postpartum T2DM in women with gestational diabetes (compared to women without gestational diabetes) after the 14-year follow-up was 21.3% and 2.78 (95% confidence interval [CI], 2.74 to 2.82), respectively. Comorbid obesity (body mass index [BMI] ≥25 kg/m2) increased postpartum T2DM risk 7.59 times (95% CI, 7.33 to 7.86). Significant risk factors for postpartum T2DM were fasting glucose level, BMI, age, family history of diabetes, hypertension, and insulin use during pregnancy.

CONCLUSION

This population-based study showed higher postpartum T2DM risk in women with gestational diabetes than in those without, which was further increased by comorbid obesity. BMI and fasting glucose level were important postpartum risk factors. The management of obesity and glycemic control may be important strategies to prevent the incidence of diabetes after delivery.

Haplotypes of the genes (GCK and G6PC2) underlying the glucose/glucose-6-phosphate cycle are associated with pancreatic beta cell glucose sensitivity in patients with newly diagnosed type 2 diabetes from the VNDS study (VNDS 11)

BACKGROUND

Elevated fasting plasma glucose has been associated with increased risk for development of type 2 diabetes (T2D). The balance between glucokinase (GCK) and glucose-6-phosphate catalytic subunit 2 (G6PC2) activity are involved in glucose homeostasis through glycolytic flux, and subsequent insulin secretion.

AIM

In this study, we evaluated the association between the genetic variability of G6PC2 and GCK genes and T2D-related quantitative traits.

METHODS

In 794 drug-naïve, GADA-negative, newly diagnosed T2D patients (VNDS; NTC01526720) we performed: genotyping of 6 independent tag-SNPs within GCK gene and 5 tag-SNPs within G6PC2 gene; euglycaemic insulin clamp to assess insulin sensitivity; OGTT to estimate beta-cell function (derivative and proportional control; DC, PC) by mathematical modeling. Genetic association analysis has been conducted using Plink software.

RESULTS

Two SNPs within GCK gene (rs882019 and rs1303722) were associated to DC in opposite way (both p < 0.004). Two G6PC2 variants (rs13387347 and rs560887) were associated to both parameters of insulin secretion (DC and PC) and to fasting C-peptide levels (all p < 0.038). Moreover, subjects carrying the A allele of rs560887 showed higher values of 2h-plasma glucose (2hPG) (p = 0.033). Haplotype analysis revealed that GCK (AACAAA) haplotype was associated to decreased fasting C-peptide levels, whereas, the most frequent haplotype of G6PC2 (GGAAG) was associated with higher fasting C-peptide levels (p = 0.001), higher PC (β = 6.87, p = 0.022) and the lower 2hPG (p = 0.012).

CONCLUSION

Our findings confirmed the role of GCK and G6PC2 in regulating the pulsatility in insulin secretion thereby influencing insulin-signaling and leading to a gradual modulation in glucose levels in Italian patients with newly diagnosed T2D.

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.

Utility of oral glucose tolerance test in predicting type 2 diabetes following gestational diabetes: Towards personalized care

BACKGROUND

Women with gestational diabetes mellitus (GDM) are at a seven-fold higher risk of developing type 2 diabetes (T2D) within 7-10 years after childbirth, compared with those with normoglycemic pregnancy. Although raised fasting blood glucose (FBG) levels has been said to be the main significant predictor of postpartum progression to T2D, it is difficult to predict who among the women with GDM would develop T2D. Therefore, we conducted a cross-sectional retrospective study to examine the glycemic indices that can predict postnatal T2D in Emirati Arab women with a history of GDM.

AIM

To assess how oral glucose tolerance test (OGTT) can identify the distinct GDM pathophysiology and predict possible distinct postnatal T2D subtypes.

METHODS

The glycemic status of a cohort of 4603 pregnant Emirati Arab women, who delivered in 2007 at both Latifa Women and Children Hospital and at Dubai Hospital, United Arab Emirates, was assessed retrospectively, using the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Of the total, 1231 women were followed up and assessed in 2016. The FBG and/or the 2-h blood glucose (2hrBG) levels after a 75-g glucose load were measured to assess the prevalence of GDM and T2D, according to the IADPSG and American Diabetes Association (ADA) criteria, respectively. The receiver operating characteristic curve for the OGTT was plotted and sensitivity, specificity, and predictive values of FBG and 2hrBG for T2D were determined.

RESULTS

Considering both FBG and 2hrBG levels, according to the IADPSG criteria, the prevalence of GDM in pregnant Emirati women in 2007 was 1057/4603 (23%), while the prevalence of pre-pregnancy T2D among them, based on ADA criteria, was 230/4603 (5%). In the subset of women (n = 1231) followed up in 2016, the prevalence of GDM in 2007 was 362/1231 (29.6%), while the prevalence of pre-pregnancy T2D was 36/1231 (2.9%). Of the 362 pregnant women with GDM in 2007, 96/362 (26.5%) developed T2D; 142/362 (39.2%) developed impaired fasting glucose; 29/362 (8.0%) developed impaired glucose tolerance, and the remaining 95/362 (26.2%) had normal glycemia in 2016. The prevalence of T2D, based on ADA criteria, stemmed from the prevalence of 36/1231 (2.9%) in 2007 to 141/1231 (11.5%), in 2016. The positive predictive value (PPV) for FBG suggests that if a woman tested positive for GDM in 2007, the probability of developing T2D in 2016 was approximately 24%. The opposite was observed when 2hrBG was used for diagnosis. The PPV value for 2hrBG suggests that if a woman was positive for GDM in 2007 then the probability of developing T2D in 2016 was only 3%.

CONCLUSION

FBG and 2hrBG could predict postpartum T2D, following antenatal GDM. However, each test reflects different pathophysiology and possible T2D subtype and could be matched with a relevant T2D prevention program.

Therapeutics for type-2 diabetes mellitus: a glance at the recent inclusions and novel agents under development for use in clinical practice

Diabetes mellitus (DM) is a chronic, progressive, and multifaceted illness resulting in significant physical and psychological detriment to patients. As of 2019, 463 million people are estimated to be living with DM worldwide, out of which 90% have type-2 diabetes mellitus (T2DM). Over the years, significant progress has been made in identifying the risk factors for developing T2DM, understanding its pathophysiology and uncovering various metabolic pathways implicated in the disease process. This has culminated in the implementation of robust prevention programmes and the development of effective pharmacological agents, which have had a favourable impact on the management of T2DM in recent times. Despite these advances, the incidence and prevalence of T2DM continue to rise. Continuing research in improving efficacy, potency, delivery and reducing the adverse effect profile of currently available formulations is required to keep pace with this growing health challenge. Moreover, new metabolic pathways need to be targeted to produce novel pharmacotherapy to restore glucose homeostasis and address metabolic sequelae in patients with T2DM. We searched PubMed, MEDLINE, and Google Scholar databases for recently included agents and novel medication under development for treatment of T2DM. We discuss the pathophysiology of T2DM and review how the emerging anti-diabetic agents target the metabolic pathways involved. We also look at some of the limiting factors to developing new medication and the introduction of unique methods, including facilitating drug delivery to bypass some of these obstacles. However, despite the advances in the therapeutic options for the treatment of T2DM in recent years, the industry still lacks a curative agent.

An Analysis of Glucose Effectiveness in Subjects With or Without Type 2 Diabetes via Hierarchical Modeling

Glucose effectiveness, defined as the ability of glucose itself to increase glucose utilization and inhibit hepatic glucose production, is an important mechanism maintaining normoglycemia. We conducted a minimal modeling analysis of glucose effectiveness at zero insulin (GEZI) using intravenous glucose tolerance test data from subjects with type 2 diabetes (T2D, n=154) and non-diabetic (ND) subjects (n=343). A hierarchical statistical analysis was performed, which provided a formal mechanism for pooling the data from all study subjects, to yield a single composite population model that quantifies the role of subject specific characteristics such as weight, height, age, sex, and glucose tolerance. Based on the resulting composite population model, GEZI was reduced from 0.021 min-1 (standard error - 0.00078 min-1) in the ND population to 0.011 min-1 (standard error - 0.00045 min-1) in T2D. The resulting model was also employed to calculate the proportion of the non-insulin-dependent net glucose uptake in each subject receiving an intravenous glucose load. Based on individual parameter estimates, the fraction of total glucose disposal independent of insulin was 72.8% ± 12.0% in the 238 ND subjects over the course of the experiment, indicating the major contribution to the whole-body glucose clearance under non-diabetic conditions. This fraction was significantly reduced to 48.8% ± 16.9% in the 30 T2D subjects, although still accounting for approximately half of the total in the T2D population based on our modeling analysis. Given the potential application of glucose effectiveness as a predictor of glucose intolerance and as a potential therapeutic target for treating diabetes, more investigations of glucose effectiveness in other disease conditions can be conducted using the hierarchical modeling framework reported herein.

Risk Factors for Progression From Gestational Diabetes to Postpartum Type 2 Diabetes: A Review

Gestational diabetes mellitus (GDM) complicates 6% to 8% of pregnancies and up to 50% of women with GDM progress to type 2 diabetes mellitus (DM) within 5 years postpartum. Clinicians have little guidance on which women are most at risk for DM progression or when evidence-based prevention strategies should be implemented in a woman's lifecycle. To help address this gap, the authors review identifiable determinants of progression from GDM to DM across the perinatal period, considering prepregnancy, pregnancy, and postpartum periods. The authors categorize evidence by pathways of risk including genetic, metabolic, and behavioral factors that influence progression to DM among women with GDM.

Genome-Wide Association Analysis of Pancreatic Beta-Cell Glucose Sensitivity

CONTEXT

Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta-cell glucose sensitivity.

OBJECTIVE

To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies.

DESIGN

We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and nondiabetic subjects from 6 independent cohorts (n = 5706). Beta-cell glucose sensitivity was calculated from mixed meal and oral glucose tolerance tests, and its associations between known glycemia-related single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) SNPs were estimated using linear regression models.

RESULTS

Beta-cell glucose sensitivity was moderately heritable (h2 ranged from 34% to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P value = 2.64 × 10-9) and rs9368219 in the CDKAL1 (P value = 3.15 × 10-9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia-associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity.

CONCLUSION

We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta-cell glucose sensitivity.

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

BACKGROUND AND AIMS

Insulin clearance is a relevant process in glucose homeostasis. In this observational study, we aimed to assess insulin clearance (Cl_INS) in women with former gestational diabetes (fGDM) both early after delivery and after a follow-up.

METHODS AND RESULTS

We analysed 59 fGDM women, and 16 women not developing GDM (CNT). All women underwent an oral glucose tolerance test (OGTT) yearly, and an insulin-modified intravenous glucose tolerance test (IVGTT) at baseline and at follow-up end (until 7 years). Both IVGTT and OGTT Cl_INS was assessed as insulin secretion to plasma insulin ratio. We also defined IVGTT first (0-10 min) and second phase (10-180 min) Cl_INS. We found that 14 fGDM women progressed to type 2 diabetes (PROG), whereas 45 women remained diabetes-free (NONPROG). At baseline, IVGTT Cl_INS showed alterations in PROG, especially in second phase (0.88 ± 0.10 l·min^-1 in PROG, 0.60 ± 0.06 in NONPROG, 0.54 ± 0.07 in CNT, p ≤ 0.03). Differences in Cl_INS were not found from OGTT. Cox regression analysis showed second phase Cl_INS as significant type 2 diabetes predictor (hazard ratio = 1.90, 95% confidence interval 1.09-3.30, p = 0.02).

CONCLUSION

This study showed that insulin clearance derived from an insulin-modified IVGTT is notably altered in women with history of GDM progressing towards type 2 diabetes.

Effects of treatment with metformin and/or sitagliptin on beta-cell function and insulin resistance in prediabetic women with previous gestational diabetes

AIM

To investigate the effect of sitagliptin (SITA) and metformin (MET) monotherapy as well as in combination (MET+SITA) on beta-cell function and insulin sensitivity in women with recent gestational diabetes (GDM) and impaired glucose regulation (IGR: impaired fasting glucose and/or impaired glucose tolerance).

MATERIAL AND METHODS

Forty women were randomly assigned to receive SITA (100 mg qd), MET (850 mg bid) or MET+SITA (50 + 850 mg bid) for 16 weeks. A 75 g oral glucose tolerance test (OGTT) and +125 mg/dL hyperglycaemic clamp followed by 5 g i.v. L-arginine were performed at baseline and end of study. The primary outcome of the study was the mean change in arginine-stimulated insulin secretion rate during the hyperglycaemic clamp test from baseline to 16-week therapy.

RESULTS

At week 16, body mass index declined in all groups (-1.2 ± 0.2 kg/m² ; P < 0.05). MET+SITA gave a greater increase of first phase_{(2-10 min)} insulin secretion and arginine-stimulated response (720.3 ± 299.0 to 995.5 ± 370.3 pmol/L and 3.2 ± 0.6 to 4.8 ± 1.0 pmoL/min, respectively, both P < 0.05) compared with MET and SITA. Similarly, MET+SITA was more effective in increasing OGTT-based glucose sensitivity (55.7 ± 11.3 to 108 ± 56.2 pmol x min^-1 m^-2 x mM^-1 ; P = 0.04) and insulin-stimulated glucose disposal (M/I: 2.2 ± 0.5 to 4.6 ± 1.3 mg/kg/min÷μIU/min/ml; P = 0.04; Matsuda index [SI]: 3.1 ± 0.4 to 5.7 ± 1.1; P = 0.03) compared with either MET or SITA. Disposition index (ISSI-2) increased with MET+SITA and SITA (both P < 0.05), while no significant change was observed in MET. Among MET+SITA women, 33% reverted to normal glucose tolerance (NGT) compared with 14% with MET and 7% with SITA (P < 0.05).

CONCLUSION

This study shows that MET+SITA is superior to SITA and MET monotherapy regarding beta-cell function and insulin sensitivity improvement in IGR women with previous GDM, and may offer a potential pharmacologic intervention to reduce the risk of type 2 diabetes in this high-risk population.

Glucose Effectiveness from Short Insulin-Modified IVGTT and Its Application to the Study of Women with Previous Gestational Diabetes Mellitus

BACKGROUND

This study aimed to design a simple surrogate marker (i.e., predictor) of the minimal model glucose effectiveness (S_G), namely calculated S_G (CS_G), from a short insulin-modified intravenous glucose tolerance test (IM-IVGTT), and then to apply it to study women with previous gestational diabetes mellitus (pGDM).

METHODS

CS_G was designed using the stepwise model selection approach on a population of subjects (n=181) ranging from normal tolerance to type 2 diabetes mellitus (T2DM). CS_G was then tested on a population of women with pGDM (n=57). Each subject underwent a 3-hour IM-IVGTT; women with pGDM were observed early postpartum and after a follow-up period of up to 7 years and classified as progressors (PROG) or non-progressors (NONPROG) to T2DM. The minimal model analysis provided a reference S_G.

RESULTS

CS_G was described as CS_G=1.06×10⁻²+5.71×10⁻²×K_G/G_peak, K_G being the mean slope (absolute value) of loge glucose in 10-25- and 25-50-minute intervals, and G_peak being the maximum of the glucose curve. Good agreement between CS_G and S_G in the general population and in the pGDM group, both at baseline and follow-up (even in PROG and NONPROG subgroups), was shown by the Bland-Altman plots (<5% observations outside limits of agreement), and by the test for equivalence (equivalence margin not higher than one standard deviation). At baseline, the PROG subgroup showed significantly lower S_G and CS_G values compared to the NONPROG subgroup (P<0.03).

CONCLUSION

CS_G is a valid S_G predictor. In the pGDM group, glucose effectiveness appeared to be impaired in women progressing to T2DM.

Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction?

BACKGROUND

An early identification of the risk groups might be beneficial in reducing morbidities in patients with gestational diabetes mellitus (GDM). Therefore, this study aimed to assess the biochemical predictors of glycemic conditions, in addition to fasting indices of glucose disposal, to predict the development of GDM in later stage and the need of glucose-lowering medication.

METHODS

A total of 574 pregnant females (103 with GDM and 471 with normal glucose tolerance [NGT]) were included. A metabolic characterization was performed before 15⁺⁶ weeks of gestation by assessing fasting plasma glucose (FPG), fasting insulin (FI), fasting C-peptide (FCP), and glycosylated hemoglobin (HbA1c). Thereafter, the patients were followed-up until the delivery.

RESULTS

Females with NGT had lower levels of FPG, FI, FCP, or HbA1c at the early stage of pregnancy, and therefore, showed an improved insulin action as compared to that in females who developed GDM. Higher fasting levels of FPG and FCP were associated with a higher risk of developing GDM. Moreover, the predictive accuracy of this metabolic profiling was also good to distinguish the patients who required glucose-lowering medications. Indices of glucose disposal based on C-peptide improved the predictive accuracy compared to that based on insulin. A modified quantitative insulin sensitivity check index (QUICKIc) showed the best differentiation in terms of predicting GDM (area under the receiver operating characteristics curve [ROC-AUC], 72.1%) or need for pharmacotherapy (ROC-AUC, 83.7%).

CONCLUSION

Fasting measurements of glucose and C-peptide as well as the surrogate indices of glycemic condition could be used for stratifying pregnant females with higher risk of GDM at the beginning of pregnancy.

Review of methods for measuring β-cell function: Design considerations from the Restoring Insulin Secretion (RISE) Consortium

The Restoring Insulin Secretion (RISE) study was initiated to evaluate interventions to slow or reverse the progression of β-cell failure in type 2 diabetes (T2D). To design the RISE study, we undertook an evaluation of methods for measurement of β-cell function and changes in β-cell function in response to interventions. In the present paper, we review approaches for measurement of β-cell function, focusing on methodologic and feasibility considerations. Methodologic considerations included: (1) the utility of each technique for evaluating key aspects of β-cell function (first- and second-phase insulin secretion, maximum insulin secretion, glucose sensitivity, incretin effects) and (2) tactics for incorporating a measurement of insulin sensitivity in order to adjust insulin secretion measures for insulin sensitivity appropriately. Of particular concern were the capacity to measure β-cell function accurately in those with poor function, as is seen in established T2D, and the capacity of each method for demonstrating treatment-induced changes in β-cell function. Feasibility considerations included: staff burden, including time and required methodological expertise; participant burden, including time and number of study visits; and ease of standardizing methods across a multicentre consortium. After this evaluation, we selected a 2-day measurement procedure, combining a 3-hour 75-g oral glucose tolerance test and a 2-stage hyperglycaemic clamp procedure, augmented with arginine.

Family history of diabetes and the risk of gestational diabetes mellitus in Iran: A systematic review and meta-analysis

OBJECTIVE

Gestational diabetes is the most prevalent metabolic disorder being firstly diagnosed during pregnancy. The relationship between the family history of diabetes and the gestational diabetes mellitus (GDM) has been investigated in several primary studies with a number of contradictions in the results. Hence, the purpose of the present study is to determine the relationship between the GDM and the family history of diabetes using the meta-analysis method.

METHOD

All published papers in main national and international databases were systematically searched with some specific keywords to find the related studies between 2000 and 2016. We calculated the odds ratio (OR) with 95% confidence interval (CI) in analysis for each study using a random-effect and Mantel-Haenzel method. We also determined heterogeneity among these 33 articles and their publication bias.

RESULTS

We entered 33 relevant studies of 2516 articles into the meta-analysis process including 2697 women with family history of diabetes mellitus as well as 29134 women without. Of them, 954 and 4372 subjects developed GDM respectively. Combining the results of the primary studies using the meta-analysis method, the overall odds ratio of family history for developing GDM was estimated as of 3.46 (95% CI: 2.80-4.27).

CONCLUSION

This meta-analysis study revealed that the family history of diabetes is an important risk factor for the gestational diabetes mellitus.

Interventions to Improve Rate of Diabetes Testing Postpartum in Women With Gestational Diabetes Mellitus

PURPOSE OF REVIEW

Gestational diabetes mellitus (GDM) is one of the most common medical complications of pregnancy. In the USA, four million women are screened annually for GDM in pregnancy in part to improve pregnancy outcomes but also because diagnosis predicts a high risk of future type 2 diabetes mellitus (T2DM). Therefore, among women with GDM, postpartum care should be focused on T2DM prevention. This review describes the current literature aimed to increase postpartum diabetes testing among women with GDM.

RECENT FINDINGS

Data suggest that proactive patient contact via a health educator, a phone call, or even postal mail is associated with higher rates of postpartum diabetes testing. There may also be utility to changing the timing of postpartum diabetes testing. Despite the widespread knowledge regarding the importance of postpartum testing for women with GDM, testing rates remain low. Alternative testing strategies and large randomized trials addressing postpartum testing are warranted.

Quantification of the type 2 diabetes risk in women with gestational diabetes: a systematic review and meta-analysis of 95,750 women

AIMS/HYPOTHESIS

Women with gestational diabetes mellitus (GDM) are at risk of developing type 2 diabetes, but individualised risk estimates are unknown. We conducted a meta-analysis to quantify the risk of progression to type 2 diabetes for women with GDM.

METHODS

We systematically searched the major electronic databases with no language restrictions. Two reviewers independently extracted 2 × 2 tables for dichotomous data and the means plus SEs for continuous data. Risk ratios were calculated and pooled using a random effects model.

RESULTS

There were 39 relevant studies (including 95,750 women) BMI (RR 1.95 [95% CI 1.60, 2.31]), family history of diabetes (RR 1.70 [95% CI 1.47, 1.97]), non-white ethnicity (RR 1.49 [95% CI 1.14, 1.94]) and advanced maternal age (RR 1.20 [95% CI 1.09, 1.34]) were associated with future risk of type 2 diabetes. There was an increase in risk with early diagnosis of GDM (RR 2.13 [95% CI 1.52, 3.56]), raised fasting glucose (RR 3.57 [95% CI 2.98, 4.04]), increased HbA1c (RR 2.56 [95% CI 2.00, 3.17]) and use of insulin (RR 3.66 [95% CI 2.78, 4.82]). Multiparity (RR 1.23 [95% CI 1.01, 1.50]), hypertensive disorders in pregnancy (RR 1.38 [95% CI 1.32, 1.45]) and preterm delivery (RR 1.81 [95% CI 1.35, 2.43]) were associated with future diabetes. Gestational weight gain, macrosomia in the offspring or breastfeeding did not increase the risk.

CONCLUSIONS/INTERPRETATION

Personalised risk of progression to type 2 diabetes should be communicated to mothers with GDM.

SYSTEMATIC REVIEW REGISTRATION

www.crd.york.ac.uk/PROSPERO CRD42014013597.

Human insulin dynamics in women: a physiologically based model

Currently available models of insulin dynamics are mostly based on the classical compartmental structure and, thus, their physiological utility is limited. In this work, we describe the development of a physiologically based model and its application to data from 154 patients who underwent an insulin-modified intravenous glucose tolerance test (IM-IVGTT). To determine the time profile of endogenous insulin delivery without using C-peptide data and to evaluate the transcapillary transport of insulin, the hepatosplanchnic, renal, and peripheral beds were incorporated into the circulatory model as separate subsystems. Physiologically reasonable population mean estimates were obtained for all estimated model parameters, including plasma volume, interstitial volume of the peripheral circulation (mainly skeletal muscle), uptake clearance into the interstitial space, hepatic and renal clearance, as well as total insulin delivery into plasma. The results indicate that, at a population level, the proposed physiologically based model provides a useful description of insulin disposition, which allows for the assessment of muscle insulin uptake.

Application of Penalized Regression Techniques in Modelling Insulin Sensitivity by Correlated Metabolic Parameters

This paper aims to introduce penalized estimation techniques in clinical investigations of diabetes, as well as to assess their possible advantages and limitations. Data from a previous study was used to carry out the simulations to assess: a) which procedure results in the lowest prediction error of the final model in the setting of a large number of predictor variables with high multicollinearity (of importance if insulin sensitivity should be predicted) and b) which procedure achieves the most accurate estimate of regression coefficients in the setting of fewer predictors with small unidirectional effects and moderate correlation between explanatory variables (of importance if the specific relation between an independent variable and insulin sensitivity should be examined). Moreover a special focus is on the correct direction of estimated parameter effects, a non-negligible source of error and misinterpretation of study results. The simulations were performed for varying sample size to evaluate the performance of LASSO, Ridge as well as different algorithms for Elastic Net. These methods were also compared with automatic variable selection procedures (i.e. optimizing AIC or BIC).We were not able to identify one method achieving superior performance in all situations. However, the improved accuracy of estimated effects underlines the importance of using penalized regression techniques in our example (e.g. if a researcher aims to compare relations of several correlated parameters with insulin sensitivity). However, the decision which procedure should be used depends on the specific context of a study (accuracy versus complexity) and moreover should involve clinical prior knowledge.

The stool microbiota of insulin resistant women with recent gestational diabetes, a high risk group for type 2 diabetes

The gut microbiota has been linked to metabolic diseases. However, information on the microbiome of young adults at risk for type 2 diabetes (T2D) is lacking. The aim of this cross-sectional analysis was to investigate whether insulin resistant women with previous gestational diabetes (pGDM), a high risk group for T2D, differ in their stool microbiota from women after a normoglycemic pregnancy (controls). Bacterial communities were analyzed by high-throughput 16S rRNA gene sequencing using fecal samples from 42 pGDM and 35 control subjects 3-16 months after delivery. Clinical characterization included a 5-point OGTT, anthropometrics, clinical chemistry markers and a food frequency questionnaire. Women with a Prevotellaceae-dominated intestinal microbiome were overrepresented in the pGDM group (p < 0.0001). Additionally, the relative abundance of the phylum Firmicutes was significantly lower in women pGDM (median 48.5 vs. 56.8%; p = 0.013). Taxa richness (alpha diversity) was similar between the two groups and with correction for multiple testing we observed no significant differences on lower taxonomic levels. These results suggest that distinctive features of the intestinal microbiota are already present in young adults at risk for T2D and that further investigations of a potential pathophysiological role of gut bacteria in early T2D development are warranted.

Factors associated with diabetes mellitus prediction among pregnant Arab subjects with gestational diabetes

There is scarcity of available information on the possible significant risk factors related to diabetes mellitus (DM) prediction among expectant Saudi mothers with gestational diabetes mellitus (GDM). The present study is the first to identify such risk factors in the Arab cohort. A total of 300 pregnant subjects (mean age 33.45 ± 6.5 years) were randomly selected from all the deliveries registered at the Obstetrics Department of King Fahad Medical City, Riyadh Saudi Arabia from April 2011 to March 2013. Demographic and baseline glycemic information were collected. A total of 7 highly significant and independent risk factors were identified: age, obesity, and family history of DM, GDM < 20 weeks, macrosomia, insulin therapy and recurrent GDM. Among these factors, subjects who had insulin therapy use are 5 times more likely to develop DMT2 (p-value 3.94 × 10(-14)) followed by recurrent GDM [odds-ratio 4.69 (Confidence Interval 2.34-4.84); P = 1.24 × 10(-13)). The identification of the risk factors mentioned with their respective predictive powers in the detection of DMT2 needs to be taken seriously in the post-partum assessment of Saudi pregnant patients at highest risk.

To explain the variation of OGTT dynamics by biological mechanisms: a novel approach based on principal components analysis in women with history of GDM

Early reexamination of carbohydrate metabolism via an oral glucose tolerance test (OGTT) is recommended after pregnancy with gestational diabetes (GDM). In this report, we aimed to assess the dominant patterns of dynamic OGTT measurements and subsequently explain them by meanings of the underlying pathophysiological processes. Principal components analysis (PCA), a statistical procedure that aims to reduce the dimensionality of multiple interrelated measures to a set of linearly uncorrelated variables (the principal components) was performed on OGTT data of glucose, insulin and C-peptide in addition to age and body mass index (BMI) of 151 women (n = 110 females after GDM and n = 41 controls) at 3-6 mo after delivery. These components were explained by frequently sampled intravenous glucose tolerance test (FSIGT) parameters. Moreover, their relation with the later development of overt diabetes was studied. Three principal components (PC) were identified, which explained 71.5% of the variation of the original 17 variables. PC1 (explained 47.1%) was closely related to postprandial OGTT levels and FSIGT-derived insulin sensitivity (r = 0.68), indicating that it mirrors insulin sensitivity in the skeletal muscle. PC2 (explained 17.3%) and PC3 (explained 7.1%) were shown to be associated with β-cell failure and fasting (i.e., hepatic) insulin resistance, respectively. All three components were related with diabetes progression (occurred in n = 25 females after GDM) and showed significant changes in long-term trajectories. A high amount of the postpartum OGTT data is explained by principal components, representing pathophysiological mechanisms on the pathway of impaired carbohydrate metabolism. Our results improve our understanding of the underlying biological processes to provide an accurate postgestational risk stratification.

Glutamic acid decarboxylase autoantibody-positivity post-partum is associated with impaired β-cell function in women with gestational diabetes mellitus

AIMS

To investigate whether the presence of glutamic acid decarboxylase (GAD) autoantibodies post-partum in women with prior gestational diabetes mellitus was associated with changes in metabolic characteristics, including β-cell function and insulin sensitivity.

METHODS

During 1997-2010, 407 women with gestational diabetes mellitus were offered a 3-month post-partum follow-up including anthropometrics, serum lipid profile, HbA1c and GAD autoantibodies, as well as a 2-h oral glucose tolerance test (OGTT) with blood glucose, serum insulin and C-peptide at 0, 30 and 120 min. Indices of insulin sensitivity and insulin secretion were estimated to assess insulin secretion adjusted for insulin sensitivity, disposition index (DI).

RESULTS

Twenty-two (5.4%) women were positive for GAD autoantibodies (GAD+ve) and the remainder (94.6%) were negative for GAD autoantibodies (GAD-ve). The two groups had similar age and prevalence of diabetes mellitus. Women who were GAD+ve had significantly higher 2-h OGTT glucose concentrations during their index-pregnancy (10.5 vs. 9.8 mmol/l, P = 0.001), higher fasting glucose (5.2 vs. 5.0 mmol/l, P = 0.02) and higher 2-h glucose (7.8 vs. 7.1 mmol/l, P = 0.05) post-partum. Fasting levels of C-peptide and insulin were lower in GAD+ve women compared with GAD-ve women (520 vs. 761 pmol/l, P = 0.02 and 33 vs. 53 pmol/l, P = 0.05) Indices of insulin sensitivity were similar in GAD+ve and GAD-ve women, whereas all estimates of DI were significantly reduced in GAD+ve women.

CONCLUSION

GAD+ve women had higher glucose levels and impaired insulin secretion adjusted for insulin sensitivity (DI) compared with GAD-ve women. The combination of OGTT and GAD autoantibodies post-partum identify women with impaired β-cell function. These women should be followed with special focus on development of Type 1 diabetes.

Hidden metabolic disturbances in women with normal glucose tolerance five years after gestational diabetes

Background. The study aimed to assess whether women with prior gestational diabetes (pGDM), despite maintenance of normal glucose tolerance (NGT) five years after delivery, display metabolic disturbances compared to healthy controls. Methods. 45 pGDM with NGT were compared to 18 women without a history of GDM (CON), matched for age (37.0 ± 4.1 versus 35.2 ± 5.3, P = ns) and BMI (24.3 ± 3.1 versus 23.3 ± 3.3, P = ns). Metabolic parameters were derived from oral and intravenous glucose tolerance tests; furthermore lipid profile, C-reactive protein (CRP), adiponectin, leptin, and glucagon were assessed. Results. Five years postpartum, pGDM had increased glucose concentrations during the OGTT (AUC: 1.12 ± 0.15 versus 1.0 ± 0.12 mol/L ∗ min, P = 0.003) and insulin sensitivity was decreased compared to CON (OGIS: 467.2 ± 64.1 versus 510.6 ± 53.1 mL/min ∗ m(2), P = 0.01). pGDM had lower adiponectin (8.1 ± 2.6 versus 12.6 ± 5.3, P < 0.008) but increased waist circumference and CRP compared to CON. Conclusions. Despite diagnosis of normal glucose tolerance, pGDM are characterized by hyperglycemia and insulin resistance compared to healthy controls, accompanied by decreased adiponectin and increased CRP concentrations, thus linking metabolic disturbances to an increased cardiovascular risk in pGDM.

Biomarkers of endothelial dysfunction in relation to impaired carbohydrate metabolism following pregnancy with gestational diabetes mellitus

Background

History of gestational diabetes mellitus (GDM) identifies a very young population of females predisposed for type 2 diabetes and cardiovascular disease. Endothelial dysfunction might represent a shared precursor of both disorders. Hence, this study aimed to characterize endothelial biomarkers in relation to impaired insulin sensitivity and progression to overt diabetes early after index pregnancy.

Methods

108 women with previous GDM and 40 controls were included three to six months after delivery and underwent specific metabolic assessments including a frequently sampled intravenous glucose tolerance test and an oral glucose tolerance test. Diabetes progression was assessed in females with pGDM over 10 years of follow-up. Circulating sICAM-1 (intracellular-adhesion-molecule-1), sVCAM-1 (vascular-cell-adhesion-molecule-1) and sE-selectin, representing biomarkers of endothelial dysfunction were assessed at baseline and annually over five years.

Results

Endothelial biomarkers were significantly associated with insulin sensitivity (sICAM-1: r = -0.23, p = 0.009; sVCAM-1: r = -0.22, p = 0.011; sE-selectin: r = -0.21, p = 0.018) as well as with GDM status and parameters of subtle inflammation. Analysis of long-term trajectories revealed constantly elevated sICAM-1 (p = 0.033) and sE-selectin (p = 0.007) in 25 subjects with diabetes progression. Accordingly, sE-selectin levels at the early post partum visit predicted a later development of the disease (HR =1.02 95%CI 1.01 to 1.04, p = 0.013), however, this was attenuated after adjustment for BMI.

Conclusions

Elevated circulating markers of endothelial dysfunction in young females with GDM history might reflect an early stage on the pathway to the manifestation of future cardiometabolic disorders. Timely identification of women at high risk and optimization of follow-up management might provide an opportunity to prevent disease progression.

Is early postpartum HbA1c an appropriate risk predictor after pregnancy with gestational diabetes mellitus?

Compared to the 2-h oral glucose tolerance test (OGTT), the assessment of HbA1c was proposed as a less time-consuming alternative to detect pathologies in carbohydrate metabolism. This report aims to assess the predictive accuracy of HbA1c to detect alterations in glucose disposition early after gestational diabetes mellitus (GDM) pregnancy. A detailed metabolic characterization was performed in 77 women with previous GDM (pGDM) and 41 controls 3-6 month after delivery: 3-h OGTT, frequently sampled intravenous glucose tolerance test. Follow-up examinations of pGDMs were performed up to 10 years. HbA1c (venous samples, HPLC) was assessed at baseline as well as during the follow-up period (475 patient contacts). Moderate associations were observed between HbA1c and measurements of plasma glucose during the OGTT at the baseline examination: The strongest correlation was found for FPG (r = 0.40, p < 0.001), decreasing after ingestion. No associations were detected between HbA1c and OGTT dynamics of insulin or C-peptide. Moreover, baseline HbA1c showed only modest correlation with insulin sensitivity (r = -0.25, p = 0.010) and disposition index (r = -0.26, p = 0.007). A linear model including fasting as well as post-load glucose levels was not improved by HbA1c. However, pGDM females with overt diabetes manifestation during the follow-up period showed more pronounced increasing HbA1c in contrast to females remaining normal glucose tolerant or developing prediabetes. It is suggested that the performance of HbA1c assessed early after delivery is inferior to the OGTT for the detection of early alterations in glucose metabolism. However, an increase in HbA1c levels could be used as an indicator of risk for diabetes manifestation.

β-Cell function in type 2 diabetes

Different in vivo tests explore different aspects of β-cell function. Because intercorrelation of insulin secretion indices is modest, no single in vivo test allows β-cell function to be assessed with accuracy and specificity comparable to insulin sensitivity. Physiologically-based mathematical modeling is necessary to interpret insulin secretory responses in terms of relevant parameters of β-cell function. Models can be used to analyze intravenous glucose tests, but secretory responses to intravenous glucose may be paradoxical in subjects with diabetes. Use of oral glucose (or mixed meal) data may be preferable not only for simplicity but also for physiological interpretation. While the disposition index focuses on the relationship between insulin secretion and insulin resistance, secretion parameters reflecting the dynamic response to changing glucose levels over a time frame of minutes or hours--such as β-cell glucose sensitivity--are key to explain changes in glucose tolerance and are largely independent of insulin sensitivity. Pathognomonic of the β-cell defect of type 2 diabetes is a reduced glucose sensitivity, which is accompanied by normal or raised absolute insulin secretion rates--compensatory to the attendant insulin resistance--and impaired incretin-induced potentiation. As β-cell mass is frequently within the range of nondiabetic individuals, these defects are predominantly functional and potentially reversible. Any intervention, on lifestyle or with drugs, that improves glucose tolerance does so primarily through increased β-cell glucose sensitivity. So far, however, no intervention has proven unequivocally capable of modifying the natural course of β-cell dysfunction.

Predicting the metabolic condition after gestational diabetes mellitus from oral glucose tolerance test curves shape

The objective of this feasibility study is to predict the metabolic condition in women with a history of gestational diabetes mellitus (GDM) from the shape of oral glucose tolerance test (OGTT) data. The rationale for this approach is that the evolution to a metabolic condition could be traceable in the shape of OGTT curves. 3-h OGTT data of 136 women with follow up, for a total of 401 OGTTs were analyzed. Subjects were classified as having normal (NGT) or non-normal glucose tolerance (NON-NGT), according to the American Diabetes Association criteria. The measured glucose, insulin, C-peptide data and combination of them were used to build up NGT and NON-NGT reference curves. Similarity between reference and individual OGTT-based curves was calculated using the Kullback-Leibler divergence. Our findings suggest that the shape of OGTT curves (1) contains information on the evolution to disease and (2) could be a reliable indicator to predict with high sensitivity (75%) and high specificity (69%) the metabolic condition of women with a history of GDM. In the future, the proposed shape-based prediction could be easily translated to the clinical practice, because it does not require the intervention of an operator specifically trained, thus facilitating its application in a clinical setting and ultimately empowering risk estimation, by improving/complementing the information which is currently adopted for risk stratification after pregnancy with GDM.

Gestational diabetes mellitus worsens the profile of cardiometabolic risk markers and decrease indexes of beta-cell function independently of insulin resistance in nondiabetic women with a parental history of type 2 diabetes

BACKGROUND

Women with a history of both parental type 2 diabetes (pt2DM) and previous gestational diabetes (pGDM) represent a group at high risk of cardiovascular events. We hypothesized that pGDM changes cardiometabolic risk markers levels as well as theirs associations with glucose indices in nondiabetic pt2DM women.

METHODS

Anthropometric parameters, glucose regulation (OGTT), insulin resistance (HOMA-IR), beta-cell function, lipid levels, parameters of endothelial dysfunction, and inflammation were evaluated in 55 women with pt2DM, 40 with both pt2DM and pGDM 2-24 months postpartum, and 35 controls.

RESULTS

Prediabetes was diagnosed more frequently in women with both pt2DM and pGDM in comparison with women with only pt2DM (10 versus 8, P = 0.04). The pGDM group had higher LDL-cholesterol, sICAM-1, tPa Ag, fibrinogen, and lower beta-cell function after adjustment for HOMA-IR, in comparison with pt2DM group. In pt2DM group postchallenge glucose correlated independently with hsCRP and in pGDM group fasting glucose with HOMA-IR.

CONCLUSIONS

pGDM exerts a combined effect on cardiometabolic risk markers in women with pt2DM. In these women higher LDL-cholesterol, fibrinogen, sICAM-1, tPa Ag levels and decreased beta cell function are associated with pGDM independently of HOMA-IR index value. Fasting glucose is an important cardiometabolic risk marker and is independently associated with HOMA-IR.

Regulation of pancreatic islet beta-cell mass by growth factor and hormone signaling

Dysfunction and destruction of pancreatic islet beta cells is a hallmark of diabetes. Better understanding of cellular signals in beta cells will allow development of therapeutic strategies for diabetes, such as preservation and expansion of beta-cell mass and improvement of beta-cell function. During the past several decades, the number of studies analyzing the molecular mechanisms, including growth factor/hormone signaling pathways that impact islet beta-cell mass and function, has increased exponentially. Notably, somatolactogenic hormones including growth hormone (GH), prolactin (PRL), and insulin-like growth factor-1 (IGF-1) and their receptors (GHR, PRLR, and IGF-1R) are critically involved in beta-cell growth, survival, differentiation, and insulin secretion. In this chapter, we focus more narrowly on GH, PRL, and IGF-1 signaling, and GH-IGF-1 cross talk. We also discuss how these signaling aspects contribute to the regulation of beta-cell proliferation and apoptosis. In particular, our novel findings of GH-induced formation of GHR-JAK2-IGF-1R protein complex and synergistic effects of GH and IGF-1 on beta-cell signaling, proliferation, and antiapoptosis lead to a new concept that IGF-1R may serve as a proximal component of GH/GHR signaling.