Do variations in insulin sensitivity and insulin secretion in pregnancy predict differences in obstetric and neonatal outcomes?

Subtypes of Gestational Diabetes Mellitus Are Differentially Associated With Newborn and Childhood Metabolic Outcomes

OBJECTIVE

Subtypes of gestational diabetes mellitus (GDM) based on insulin sensitivity and secretion have been described. We addressed the hypothesis that GDM subtypes are differentially associated with newborn and child anthropometric and glycemic outcomes.

RESEARCH DESIGN AND METHODS

Newborn and child (age 11-14 years) outcomes were examined in 7,970 and 4,160 mother-offspring dyads, respectively, who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study and HAPO Follow-Up Study. GDM was classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity), insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion), or mixed-defect GDM (both <25th percentile). Regression models for newborn and child outcomes included adjustment for field center, maternal BMI, and other pregnancy covariates. Child models also included adjustment for child age, sex, and family history of diabetes.

RESULTS

Compared with mothers with normal glucose tolerance, all three GDM subtypes were associated with birth weight and sum of skinfolds >90th percentile. Insulin-resistant and mixed-defect GDM were associated with higher risk of cord C-peptide levels >90th percentile. Insulin-resistant GDM was associated with higher risk of neonatal hypoglycemia. Insulin-resistant GDM was associated with higher risk of neonatal hypoglycemia and childhood obesity (odds ratio [OR] 1.53, 95% CI 1.127-2.08). The risk of childhood impaired glucose tolerance was higher with insulin-resistant GDM (OR 2.21, 95% CI 1.50-3.25) and mixed-defect GDM (OR 3.01, 95% CI 1.47-6.19).

CONCLUSIONS

GDM subtypes are differentially associated with newborn and childhood outcomes. Better characterizing individuals with GDM could help identify at-risk offspring to offer targeted, preventative interventions early in life.

Gestational hyperglycaemia impacts glucose control and insulin sensitivity in mouse offspring

Gestational diabetes mellitus (GDM) predisposes offspring to the development of obesity and type 2 diabetes. While GDM is studied in the context of maternal obesity and insulin resistance, the consequences of GDM in lean, insulin sensitive women for offspring health are unclear. This preclinical study investigated whether GDM in lean dams characterized by reduced insulin secretion affects offspring metabolic health. Lean GDM was induced by short-term 60% high-fat diet and low-dose streptozotocin injections before mating in mice. The control dams received only high-fat diet (HF) or low-fat diet (LF). Glucose homeostasis was studied in chow-fed offspring. GDM resulted in decreased birth weight, that resolved at postnatal day 15 (PN15). At PN100, higher postprandial glucose responses were found in GDM offspring, while insulin secretion was lower in both GDM and HF offspring. Female GDM offspring showed lower endogenous glucose production and increased liver insulin sensitivity at PN100 compared to controls. No differences in metabolic parameters were observed at PN200 and PN300. Prenatal exposure to elevated maternal glucose levels without maternal obesity modestly affected glucose regulation in mouse offspring during early adulthood. Future studies should clarify if a less favourable postnatal diet may further challenge metabolic health in offspring of GDM dams.

Research Progress of Risk Factors Associated with Gestational Diabetes Mellitus

Gestational Diabetes Mellitus (GDM) is a common endocrine condition associated with adverse pregnancy outcomes. In recent years, a growing number of risk factors associated with gestational diabetes mellitus have been defined. GDM poses a serious threat to maternal health. The etiology is complex and multifactorial and can be divided into inherent and modifiable factors. The inherent factors have been described in other literature, while the modifiable factors are mainly the risk of lifestyle habits. In this study, we performed a narrative review of the progress of risk factors associated with gestational diabetes mellitus.

The influence of fetal sex on antenatal maternal glucose and insulin dynamics

The 'Developmental Origins of Health and Disease' (DOHaD) hypothesis postulates that exposures during critical periods of development and growth, including maternal hyperglycemia, can have significant consequences for short- and long-term health in offspring. The influence of fetal status on maternal (patho)physiology is less well understood but gaining attention. Fetal sex specifically may be an independent risk factor for a range of adverse pregnancy outcomes, including increased gestational diabetes mellitus (GDM) frequency with male fetuses in multi-ethnic populations. Fetal sex has been thought to modulate maternal glucose metabolism, including insulin dynamics, through complex genetic and hormonal interactions. Mechanisms have not been fully elucidated, however, but may relate to sexual dimorphism in maternal-fetal-placental interactions. We review current evidence on the potential influence of fetal sex on maternal glucose and insulin dynamics, and fetal outcomes.

Multivariable prediction models for fetal macrosomia and large for gestational age: A systematic review

BACKGROUND

The identification of large for gestational age (LGA) and macrosomic fetuses is essential for counselling and managing these pregnancies.

OBJECTIVES

To systematically review the literature for multivariable prediction models for LGA and macrosomia, assessing the performance, quality and applicability of the included model in clinical practice.

SEARCH STRATEGY

MEDLINE, EMBASE and Cochrane Library were searched until June 2022.

SELECTION CRITERIA

We included observational and experimental studies reporting the development and/or validation of any multivariable prediction model for fetal macrosomia and/or LGA. We excluded studies that used a single variable or did not evaluate model performance.

DATA COLLECTION AND ANALYSIS

Data were extracted using the Checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist. The model performance measures discrimination, calibration and validation were extracted. The quality and completion of reporting within each study was assessed by its adherence to the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) checklist. The risk of bias and applicability were measured using PROBAST (Prediction model Risk Of Bias Assessment Tool).

MAIN RESULTS

A total of 8442 citations were identified, with 58 included in the analysis: 32/58 (55.2%) developed, 21/58 (36.2%) developed and internally validated and 2/58 (3.4%) developed and externally validated a model. Only three studies externally validated pre-existing models. Macrosomia and LGA were differentially defined by many studies. In total, 111 multivariable prediction models were developed using 112 different variables. Model discrimination was wide ranging area under the receiver operating characteristics curve (AUROC 0.56-0.96) and few studies reported calibration (11/58, 19.0%). Only 5/58 (8.6%) studies had a low risk of bias.

CONCLUSIONS

There are currently no multivariable prediction models for macrosomia/LGA that are ready for clinical implementation.

Placental IGFBP1 levels during early pregnancy and the risk of insulin resistance and gestational diabetes

Reduced insulin sensitivity (insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM). We conducted transcriptomic profiling of 434 human placentas and identified a positive association between insulin-like growth factor binding protein 1 gene (IGFBP1) expression in the placenta and insulin sensitivity at ~26 weeks gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which, together with high gene expression levels in our placenta samples, suggests a placental or decidual source. Higher circulating IGFBP1 levels were associated with greater insulin sensitivity (lesser insulin resistance) at ~26 weeks gestation in the same cohort and in two additional pregnancy cohorts. In addition, low circulating IGFBP1 levels in early pregnancy predicted subsequent GDM diagnosis in two cohorts of pregnant women. These results implicate IGFBP1 in the glycemic physiology of pregnancy and suggest a role for placental IGFBP1 deficiency in GDM pathogenesis.

Metabolomic and genetic architecture of gestational diabetes subtypes

AIMS/HYPOTHESIS

Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes.

METHODS

This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM).

RESULTS

Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM.

CONCLUSIONS/INTERPRETATION

This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

Clinical and Metabolic Characterization of Women With Gestational Diabetes Mellitus Within the First Year Postpartum

Context

Women with gestational diabetes mellitus (GDM) have an increased risk of long-term complications, including impaired glucose metabolism, type 2 diabetes (T2DM), cardiovascular disease, and obesity. In current clinical practice, a 1 size fits all approach to GDM is applied, although heterogeneity among women with GDM has been recognized.

Objective

To give the most adequate preventive care and postpartum (PP) guidance, we aimed to make a metabolic characterization and identify subgroups of women with previous GDM within the first year PP.

Methods

In this prospective cohort study, we collected data in gestational week 34-38, at 3 months, and 1 year PP on women with GDM who participated in a PP follow-up program in Central Region Denmark from April 2019 to December 2022.

Results

In total, 1270 women were included in the program in late pregnancy. Of the 768 women participating in either the oral glucose tolerance test 3 months PP (n = 545) or the 1-year follow-up (n = 493) or both (n = 261), 608 (79.2%) were normoglycemic, 137 (17.8%) had prediabetes, 20 (2.6%) had T2DM, and 3 (.4%) had developed T1DM. More than 40% of the women gained weight in the first year PP compared with their pregestational weight.

Conclusion

Our study shows that 20.8% of women with GDM who volunteered to participate in a clinical follow-up program developed prediabetes or diabetes (T1DM and T2DM) within the first year PP. The GDM diagnosis encompasses a heterogenetic group of women and a deeper characterization may provide an opportunity for a more personalized risk assessment to prevent the progression to T2DM.

Reproductive risk factors across the female lifecourse and later metabolic health

Metabolic health is characterized by optimal blood glucose, lipids, cholesterol, blood pressure, and adiposity. Alterations in these characteristics may lead to the development of type 2 diabetes mellitus or dyslipidemia. Recent evidence suggests that female reproductive characteristics may be overlooked as risk factors that contribute to later metabolic dysfunction. These reproductive traits include the age at menarche, menstrual irregularity, the development of polycystic ovary syndrome, gestational weight change, gestational dysglycemia and dyslipidemia, and the severity and timing of menopausal symptoms. These risk factors may themselves be markers of future dysfunction or may be explained by shared underlying etiologies that promote long-term disease development. Disentangling underlying relationships and identifying potentially modifiable characteristics have an important bearing on therapeutic lifestyle modifications that could ease long-term metabolic burden. Further research that better characterizes associations between reproductive characteristics and metabolic health, clarifies underlying etiologies, and identifies indicators for clinical application is warranted in the prevention and management of metabolic dysfunction.

Evaluation of insulin secretion and insulin sensitivity in pregnant women: Application value of simple indices

The prevalence of gestational diabetes mellitus (GDM) is increasing annually, which poses substantial harm to the health of both mothers and children. Therefore, selection of clinically applicable and easily detectable indicators in the assessment of maternal insulin secretory function and insulin sensitivity in pregnant women undoubtedly holds great importance in evaluating the risk of GDM, guiding the choice of GDM therapy modalities, and improving the ability to provide early warning of adverse pregnancy outcomes. Compared with the classic clamp technique, many simple indices are more suited for use among pregnant women due to the low frequency of blood sampling and simple administration involved. While indices derived from fasting blood glucose and fasting insulin levels are most readily available, they are unable to provide information on the ability of insulin to manage the glucose load during pregnancy. Although the indices derived from the insulin and glucose values at each time point of the oral glucose tolerance test can provide a more comprehensive picture of the insulin sensitivity and insulin secretory function of the body, their application is constrained by the complexity of the procedure and associated high costs. Concomitantly, the findings from different studies are influenced by a variety of confounding factors, such as the gestational age during testing, race, and detection method. Furthermore, insulin secretory function and insulin sensitivity in pregnant women differ from those in non-pregnant women in that they change significantly with prolonged pregnancy; hence, there is an urgent need to develop a pregnancy-specific reference range. This article reviews the progress in the application of simple indices to help clinicians better understand their potential application in detecting GDM.

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM.

METHODS

Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA).

RESULTS

A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers.

CONCLUSIONS

Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Placental RNA sequencing implicates IGFBP1 in insulin sensitivity during pregnancy and in gestational diabetes

Reduced insulin sensitivity (or greater insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM) pathophysiology. We conducted transcriptomic profiling of 434 human placentas and identified a strong positive association between insulin-like growth factor binding protein 1 gene (IGFBP1) expression in the placenta and insulin sensitivity at ~ 26 weeks' gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which together with high placental gene expression levels, suggests a placental source. Higher circulating IGFBP1 levels were strongly associated with greater insulin sensitivity (lesser insulin resistance) at ~ 26 weeks' gestation in the same cohort and two additional pregnancy cohorts. In addition, low circulating IGFBP1 levels in early pregnancy predicted subsequent GDM diagnosis in two cohorts. These results implicate IGFBP1 in the glycemic physiology of pregnancy and suggest a role for placental IGFBP1 deficiency in GDM pathogenesis.

Precision gestational diabetes treatment: a systematic review and meta-analyses

BACKGROUND

Gestational Diabetes Mellitus (GDM) affects approximately 1 in 7 pregnancies globally. It is associated with short- and long-term risks for both mother and baby. Therefore, optimizing treatment to effectively treat the condition has wide-ranging beneficial effects. However, despite the known heterogeneity in GDM, treatment guidelines and approaches are generally standardized. We hypothesized that a precision medicine approach could be a tool for risk-stratification of women to streamline successful GDM management. With the relatively short timeframe available to treat GDM, commencing effective therapy earlier, with more rapid normalization of hyperglycaemia, could have benefits for both mother and fetus.

METHODS

We conducted two systematic reviews, to identify precision markers that may predict effective lifestyle and pharmacological interventions.

RESULTS

There was a paucity of studies examining precision lifestyle-based interventions for GDM highlighting the pressing need for further research in this area. We found a number of precision markers identified from routine clinical measures that may enable earlier identification of those requiring escalation of pharmacological therapy (to metformin, sulphonylureas or insulin). This included previous history of GDM, Body Mass Index and blood glucose concentrations at diagnosis.

CONCLUSIONS

Clinical measurements at diagnosis could potentially be used as precision markers in the treatment of GDM. Whether there are other sensitive markers that could be identified using more complex individual-level data, such as omics, and if these can feasibly be implemented in clinical practice remains unknown. These will be important to consider in future studies.

Fetal abdominal obesity and the ensuing adverse perinatal outcomes in older obese pregnant women with or without obesity and with normal glucose tolerance

To investigate whether the increased risk of fetal abdominal obesity (FAO) is present in the older (≥ 35 years) and/or obese (≥ body mass index 25 kg/m2) women with normal glucose tolerance, we reviewed medical record of 6721 singleton pregnancy. At 24-28 gestational weeks (GW), fetal abdominal overgrowth was assessed by the fetal abdominal overgrowth ratios (FAORs) of the ultrasonographically estimated gestational age (GA) of abdominal circumference per actual GA by the last menstruation period, estimated GA of biparietal diameter or femur length, respectively. FAO was defined as FAOR ≥ 90th percentile. Compared to young and non-obese women, older women showed significantly higher FAORs irrespective of obesity and the prevalence of FAO in older and non-obese women was significantly higher (11.8% vs. 8.6%, p < 0.05). The odds ratio for large for gestational age at birth were 3.06(1.96-4.77, p < 0.005), 1.47(1.16-1.86, p < 0.005) and 2.82(1.64-4.84, p < 0.005) in young and obese, older and non-obese, and older and obese women, respectively. The odds ratio for primary cesarean delivery in older and non-obese women was 1.33 (1.18-1.51, p < 0.005). An increased risk of FAO at 24-28 GW and subsequent adverse perinatal outcomes have been observed in the older women with or without obesity, compared to younger and non-obese women, despite normal glucose tolerance.

Glycemic status during pregnancy according to fasting and post-load glucose values: The association with adverse pregnancy outcomes. An observational study

AIM

Prognosis of treated hyperglycemia in pregnancy (HIP) may differ according to whether diagnosis following an oral glucose tolerance test (OGTT) is based on high fasting and/or high post-load glucose values.

METHODS

From a multiethnic prospective study, we included 8,339 women screened for HIP after 22 weeks of gestation. We evaluated the risk of large-for-gestational-age (LGA) infant (primary endpoint) and other adverse pregnancy outcomes according to HIP status in four groups defined as follows: no HIP (n = 6,832, reference); isolated fasting HIP (n = 465), isolated post-load HIP (n = 646), and fasting and post-load HIP (n = 396).

RESULTS

After adjusting for age, body mass index, ethnicity, smoking during pregnancy and parity, compared with no HIP, the adjusted odds ratios [95% confidence interval] for LGA infant were higher in the isolated fasting HIP (1.47 [1.11-1.96]) and fasting and post-load HIP (1.65 [1.23-2.21]) groups, but not in the isolated post-load HIP (1.13 [0.86-1.48]) group. The adjusted odds ratios for preterm delivery and neonatal intensive care unit were higher in the post-load HIP group (1.44 [1.03-2.03] and 1.28 [1.04-1.57], respectively), the fasting and post-load HIP group (1.81 [1.23-2.68] and 1.42 [1.10-1.81], respectively) but not in the isolated fasting HIP group (1.34 [0.90-2.00] and 1.20 [0.94-1.52], respectively).

CONCLUSION

Despite glucose-lowering care and adjustment for confounders, compared with no HIP, fasting HIP was associated with a higher rate of LGA infant, whereas post-load HIP was associated with higher preterm delivery and neonatal intensive care unit admission rates.

Development and validation of risk prediction models for large for gestational age infants using logistic regression and two machine learning algorithms

BACKGROUND

Large for gestational age (LGA) is one of the adverse outcomes during pregnancy that endangers the life and health of mothers and offspring. We aimed to establish prediction models for LGA at late pregnancy.

METHODS

Data were obtained from an established Chinese pregnant women cohort of 1285 pregnant women. LGA was diagnosed as >90th percentile of birth weight distribution of Chinese corresponding to gestational age of the same-sex newborns. Women with gestational diabetes mellitus (GDM) were classified into three subtypes according to the indexes of insulin sensitivity and insulin secretion. Models were established by logistic regression and decision tree/random forest algorithms, and validated by the data.

RESULTS

A total of 139 newborns were diagnosed as LGA after birth. The area under the curve (AUC) for the training set is 0.760 (95% confidence interval [CI] 0.706-0.815), and 0.748 (95% CI 0.659-0.837) for the internal validation set of the logistic regression model, which consisted of eight commonly used clinical indicators (including lipid profile) and GDM subtypes. For the prediction models established by the two machine learning algorithms, which included all the variables, the training set and the internal validation set had AUCs of 0.813 (95% CI 0.786-0.839) and 0.779 (95% CI 0.735-0.824) for the decision tree model, and 0.854 (95% CI 0.831-0.877) and 0.808 (95% CI 0.766-0.850) for the random forest model.

CONCLUSION

We established and validated three LGA risk prediction models to screen out the pregnant women with high risk of LGA at the early stage of the third trimester, which showed good prediction power and could guide early prevention strategies.

Genetic Risk Factors and Gene-Lifestyle Interactions in Gestational Diabetes

Paralleling the increasing trends of maternal obesity, gestational diabetes (GDM) has become a global health challenge with significant public health repercussions. In addition to short-term adverse outcomes, such as hypertensive pregnancy disorders and fetal macrosomia, in the long term, GDM results in excess cardiometabolic morbidity in both the mother and child. Recent data suggest that women with GDM are characterized by notable phenotypic and genotypic heterogeneity and that frequencies of adverse obstetric and perinatal outcomes are different between physiologic GDM subtypes. However, as of yet, GDM treatment protocols do not differentiate between these subtypes. Mapping the genetic architecture of GDM, as well as accurate phenotypic and genotypic definitions of GDM, could potentially help in the individualization of GDM treatment and assessment of long-term prognoses. In this narrative review, we outline recent studies exploring genetic risk factors of GDM and later type 2 diabetes (T2D) in women with prior GDM. Further, we discuss the current evidence on gene-lifestyle interactions in the development of these diseases. In addition, we point out specific research gaps that still need to be addressed to better understand the complex genetic and metabolic crosstalk within the mother-placenta-fetus triad that contributes to hyperglycemia in pregnancy.

Characteristics of the gut microbiome in women with gestational diabetes mellitus: A systematic review

Background

The incidence of women developing gestational diabetes mellitus (GDM) is increasing, which is associated with an increased risk of type 2 diabetes mellitus (T2DM) for both mother and child. Gut microbiota dysbiosis may contribute to the pathogenesis of both GDM and the accompanying risk of T2DM. Thus, a better understanding of the microbial communities associated with GDM could offer a potential target for intervention and treatment in the future. Therefore, we performed a systematic review to investigate if the GDM women have a distinct gut microbiota composition compared to non-GDM women.

Methods

We identified 21 studies in a systematic literature search of Embase and PubMed up to February 24, 2021. Data on demographics, methodology and identified microbial metrics were extracted. The quality of each study was assessed according to the Newcastle-Ottawa Scale.

Results

Sixteen of the studies did find a GDM-associated gut microbiota, although no consistency could be seen. Only Collinsella and Blautia showed a tendency to be increased in GDM women, whereas the remaining genera were significantly different in opposing directions.

Conclusion

Although most of the studies found an association between GDM and gut microbiota dysbiosis, no overall GDM-specific gut microbiota could be identified. All studies in the second trimester found a difference between GDM and non-GDM women, indicating that dysbiosis is present at the time of diagnosis. Nevertheless, it is still unclear when the dysbiosis develops, as no consensus could be seen between the studies investigating the gut microbiota in the first trimester of pregnancy. However, studies varied widely concerning methodology and study design, which might explain the highly heterogeneous gut microbiota compositions between studies. Therefore, future studies need to include multiple time points and consider possible confounding factors such as ethnicity, pre-pregnancy body mass index, and GDM treatment.

Physiological subtypes of gestational glucose intolerance and risk of adverse pregnancy outcomes

BACKGROUND

Women with gestational glucose intolerance, defined as an abnormal initial gestational diabetes mellitus screening test, are at risk of adverse pregnancy outcomes even if they do not have gestational diabetes mellitus. Previously, we defined the physiological subtypes of gestational diabetes mellitus based on the primary underlying physiology leading to hyperglycemia and found that women with different subtypes had differential risks of adverse outcomes. Physiological subclassification has not yet been applied to women with gestational glucose intolerance.

OBJECTIVE

We defined the physiological subtypes of gestational glucose intolerance based on the presence of insulin resistance, insulin deficiency, or mixed pathophysiology and aimed to determine whether these subtypes are at differential risks of adverse outcomes. We hypothesized that women with the insulin-resistant subtype of gestational glucose intolerance would have the greatest risk of adverse pregnancy outcomes.

STUDY DESIGN

In a hospital-based cohort study, we studied women with gestational glucose intolerance (glucose loading test 1-hour glucose, ≥140 mg/dL; n=236) and normal glucose tolerance (glucose loading test 1-hour glucose, <140 mg/dL; n=1472). We applied homeostasis model assessment to fasting glucose and insulin levels at 16 to 20 weeks' gestation to assess insulin resistance and deficiency and used these measures to classify women with gestational glucose intolerance into subtypes. We compared odds of adverse outcomes (large for gestational age birthweight, neonatal intensive care unit admission, pregnancy-related hypertension, and cesarean delivery) in each subtype to odds in women with normal glucose tolerance using logistic regression with adjustment for age, race and ethnicity, marital status, and body mass index.

RESULTS

Of women with gestational glucose intolerance (12% with gestational diabetes mellitus), 115 (49%) had the insulin-resistant subtype, 70 (27%) had the insulin-deficient subtype, 40 (17%) had the mixed pathophysiology subtype, and 11 (5%) were uncategorized. We found increased odds of large for gestational age birthweight (primary outcome) in women with the insulin-resistant subtype compared with women with normal glucose tolerance (odds ratio, 2.35; 95% confidence interval, 1.43-3.88; P=.001; adjusted odds ratio, 1.74; 95% confidence interval, 1.02-3.48; P=.04). The odds of large for gestational age birthweight in women with the insulin-deficient subtype were increased only after adjustment for covariates (odds ratio, 1.69; 95% confidence interval, 0.84-3.38; P=.14; adjusted odds ratio, 2.05; 95% confidence interval, 1.01-4.19; P=.048). Among secondary outcomes, there was a trend toward increased odds of neonatal intensive care unit admission in the insulin-resistant subtype in an unadjusted model (odds ratio, 2.09; 95% confidence interval, 0.99-4.40; P=.05); this finding was driven by an increased risk of neonatal intensive care unit admission in women with the insulin-resistant subtype and a body mass index of <25 kg/m². Infants of women with other subtypes did not have increased odds of neonatal intensive care unit admission. The odds of pregnancy-related hypertension in women with the insulin-resistant subtype were increased (odds ratio, 2.09; 95% confidence interval, 1.31-3.33; P=.002; adjusted odds ratio, 1.77; 95% confidence interval, 1.07-2.92; P=.03) compared with women with normal glucose tolerance; other subtypes did not have increased odds of pregnancy-related hypertension. There was no difference in cesarean delivery rates in nulliparous women across subtypes.

CONCLUSION

Insulin-resistant gestational glucose intolerance is a high-risk subtype for adverse pregnancy outcomes. Delineating physiological subtypes may provide opportunities for a more personalized approach to gestational glucose intolerance.

Metabolic characteristics and adverse pregnancy outcomes for women with hyperglycaemia in pregnancy as a function of insulin resistance

AIM

Recent studies have shown that women with hyperglycaemia in pregnancy and insulin resistance have a greater risk of adverse pregnancy outcomes than women with normoglycaemic pregnancies. This study aimed to determine adverse pregnancy outcomes of women with hyperglycaemia in pregnancy only as a function of insulin resistance.

METHODS

From a prospective cohort study, we included 1,423 women with hyperglycaemia in pregnancy whose insulin resistance was evaluated using homeostatic model assessment for insulin resistance (HOMA-IR) when care was first provided for this condition. We compared the adverse pregnancy outcomes for different tertiles of HOMA-IR (intertertile range 1.9 and 3.3).

RESULTS

Increasing HOMA-IR tertiles were positively associated with the rate of insulin therapy (tertile 1, 2 and 3: 32.7, 47.0 and 58.7%, P < 0.0001), caesarean section (23.7, 26.0 and 32.2%, respectively, P < 0.01), gestational hypertension (1.3, 2.8 and 5.4% respectively, P < 0.01), preeclampsia (1.5, 2.8 and 4.5% respectively, P < 0.05), large-for-gestational-age infant (13.3, 10.4 and 17.6% respectively, P < 0.05), and neonatal hypoglycaemia (0.8, 1.5 and 3.2% respectively, P < 0.05). Women in the 3^rd HOMA-IR tertile were more likely to have insulin therapy (odds ratio 2.09 (95% interval confidence 1.61-2.71)), hypertensive disorders (2.26 (1.42-3.36)), and large-for-gestational-age infant (1.42 (1.01-1.99)) than those in the 1^st and 2^nd tertiles combined in multivariable logistic regression analyses adjusted for gestational age at HOMA-IR measurement, glycaemic status, age, body mass index, family history of diabetes, parity and ethnicity.

CONCLUSION

Despite suitable care and increased rates of insulin therapy during pregnancy, higher insulin resistance in women with hyperglycaemia in pregnancy was associated with a greater risk of adverse pregnancy outcomes.

Pregnancy in Women With Monogenic Diabetes due to Pathogenic Variants of the Glucokinase Gene: Lessons and Challenges

Heterozygous loss-of-function variants of the glucokinase (GCK) gene are responsible for a subtype of maturity-onset diabetes of the young (MODY). GCK-MODY is characterized by a mild hyperglycemia, mainly due to a higher blood glucose threshold for insulin secretion, and an up-regulated glucose counterregulation. GCK-MODY patients are asymptomatic, are not exposed to diabetes long-term complications, and do not require treatment. The diagnosis of GCK-MODY is made on the discovery of hyperglycemia by systematic screening, or by family screening. The situation is peculiar in GCK-MODY women during pregnancy for three reasons: 1. the degree of maternal hyperglycemia is sufficient to induce pregnancy adverse outcomes, as in pregestational or gestational diabetes; 2. the probability that a fetus inherits the maternal mutation is 50% and; 3. fetal insulin secretion is a major stimulus of fetal growth. Consequently, when the fetus has not inherited the maternal mutation, maternal hyperglycemia will trigger increased fetal insulin secretion and growth, with a high risk of macrosomia. By contrast, when the fetus has inherited the maternal mutation, its insulin secretion is set at the same threshold as the mother's, and no fetal growth excess will occur. Thus, treatment of maternal hyperglycemia is necessary only in the former situation, and will lead to a risk of fetal growth restriction in the latter. It has been recommended that the management of diabetes in GCK-MODY pregnant women should be guided by assessment of fetal growth by serial ultrasounds, and institution of insulin therapy when the abdominal circumference is ≥ 75th percentile, considered as a surrogate for the fetal genotype. This strategy has not been validated in women with in GCK-MODY. Recently, the feasibility of non-invasive fetal genotyping has been demonstrated, that will improve the care of these women. Several challenges persist, including the identification of women with GCK-MODY before or early in pregnancy, and the modalities of insulin therapy. Yet, retrospective observational studies have shown that fetal genotype, not maternal treatment with insulin, is the main determinant of fetal growth and of the risk of macrosomia. Thus, further studies are needed to specify the management of GCK-MODY pregnant women during pregnancy.

Subtypes of gestational diabetes and future risk of pre-diabetes or diabetes

BACKGROUND

Recent studies have suggested that gestational diabetes (GDM) is a heterogeneous condition with distinct subtypes determined by whether the predominant metabolic abnormality is impaired insulin sensitivity or deficient insulin secretion. However, it is not known if the elevated future risk of pre-diabetes/diabetes associated with GDM varies according to these subtypes. Thus, we sought to evaluate maternal metabolic function in the 1st year postpartum in relation to GDM subtypes.

METHODS

In this prospective cohort study conducted in Toronto, Canada, 613 women underwent GDM screening by oral glucose tolerance test (OGTT) in pregnancy, followed by repeat OGTT at both 3-months and 12-months postpartum between 09/2003 and 03/2016. The antepartum OGTT identified 3 groups of women: GDM with predominant sensitivity defect (GDM-sensitivity), GDM with predominant secretion defect (GDM-secretion), and non-GDM.

FINDINGS

Antepartum findings persisted after pregnancy, with lower insulin sensitivity in GDM-sensitivity (Matsuda index; HOMA-IR) and lower insulin secretion in GDM-secretion (Stumvoll first-phase; insulinogenic index (IGI)) at both 3-months and 12-months (all p<0.005). Beta-cell compensation (Insulin Secretion-Sensitivity Index-2; IGI/HOMA-IR) was lower in both GDM subtypes compared to non-GDM (all p<0.0005) but did not differ between GDM-sensitivity and GDM-secretion. Similarly, both subtypes exhibited higher post-challenge glycemia on OGTT at 3-months and 12-months than non-GDM (all p<0.0005) but did not differ from one another. The prevalence of pre-diabetes/diabetes was higher in both GDM-sensitivity (30.9%; 95%CI: 21.7-41.2) and GDM-secretion (27.6%; 16.7-40.9) than in non-GDM (10.4%; 7.7-13.6) at 12-months (both p<0.005), with no difference between GDM subtypes (p = 0.75).

INTERPRETATION

Beta-cell dysfunction, glycemia and incident pre-diabetes/diabetes do not vary between GDM subtypes in the 1st year postpartum.

FUNDING

Canadian Institutes of Health Research; Diabetes Canada.

Exposome and foetoplacental vascular dysfunction in gestational diabetes mellitus

A balanced communication between the mother, placenta and foetus is crucial to reach a successful pregnancy. Several windows of exposure to environmental toxins are present during pregnancy. When the women metabolic status is affected by a disease or environmental toxin, the foetus is impacted and may result in altered development and growth. Gestational diabetes mellitus (GDM) is a disease of pregnancy characterised by abnormal glucose metabolism affecting the mother and foetus. This disease of pregnancy associates with postnatal consequences for the child and the mother. The whole endogenous and exogenous environmental factors is defined as the exposome. Endogenous insults conform to the endo-exposome, and disruptors contained in the immediate environment are the ecto-exposome. Some components of the endo-exposome, such as Selenium, vitamins D and B₁₂, adenosine, and a high-fat diet, and ecto-exposome, such as the heavy metals Arsenic, Mercury, Lead and Copper, and per- and polyfluoroakyl substances, result in adverse pregnancies, including an elevated risk of GDM or gestational diabesity. The impact of the exposome on the human placenta's vascular physiology and function in GDM and gestational diabesity is reviewed.

Prediction of large-for-gestational age infants in relation to hyperglycemia in pregnancy - A comparison of statistical models

AIMS

Using data from a large multi-centre cohort, we aimed to create a risk prediction model for large-for-gestational age (LGA) infants, using both logistic regression and naïve Bayes approaches, and compare the utility of these two approaches.

METHODS

We have compared the two techniques underpinning machine learning: logistic regression (LR) and naïve Bayes (NB) in terms of their ability to predict large-for-gestational age (LGA) infants. Using data from five centres involved in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, we developed LR and NB models and compared the predictive ability and stability between the models. Models were developed combining the risks of hyperglycaemia (assessed in three forms: IADPSG GDM yes/no, GDM subtype, OGTT z-score quintiles), demographic and clinical variables as potential predictors.

RESULTS

The two approaches resulted in similar estimates of LGA risk (intraclass correlation coefficient 0.955, 95% CI 0.952, 0.958) however the AUROC for the LR model was significantly higher (0.698 vs 0.682; p < 0.001). When comparing the three LR models, use of individual OGTT z-score quintiles resulted in statistically higher AUROCs than the other two models.

CONCLUSIONS

Logistic regression can be used with confidence to assess the relationship between clinical and biochemical variables and outcome.