Atlas of fetal metabolism during mid-to-late gestation and diabetic pregnancy.

Mounting evidence suggests metabolism instructs stem cell fate decisions. However, how fetal metabolism changes during development and how altered maternal metabolism shapes fetal metabolism remain unexplored. We present a descriptive atlas of in vivo fetal murine metabolism during mid-to-late gestation in normal and diabetic pregnancy. Using 13C-glucose and liquid chromatography-mass spectrometry (LC-MS), we profiled the metabolism of fetal brains, hearts, livers, and placentas harvested from pregnant dams between embryonic days (E)10.5 and 18.5. Our analysis revealed metabolic features specific to a hyperglycemic environment and signatures that may denote developmental transitions during euglycemic development. We observed sorbitol accumulation in fetal tissues and altered neurotransmitter levels in fetal brains isolated from hyperglycemic dams. Tracing 13C-glucose revealed disparate fetal nutrient sourcing depending on maternal glycemic states. Regardless of glycemic state, histidine-derived metabolites accumulated in late-stage fetal tissues. Our rich dataset presents a comprehensive overview of in vivo fetal tissue metabolism and alterations due to maternal hyperglycemia.

RANK links thymic regulatory T cells to fetal loss and gestational diabetes in pregnancy.

Successful pregnancies rely on adaptations within the mother1, including marked changes within the immune system2. It has long been known that the thymus, the central lymphoid organ, changes markedly during pregnancy3. However, the molecular basis and importance of this process remain largely obscure. Here we show that the osteoclast differentiation receptor RANK4,5 couples female sex hormones to the rewiring of the thymus during pregnancy. Genetic deletion of Rank (also known as Tnfrsf11a) in thymic epithelial cells results in impaired thymic involution and blunted expansion of natural regulatory T (Treg) cells in pregnant female mice. Sex hormones, in particular progesterone, drive the development of thymic Treg cells through RANK in a manner that depends on AIRE+ medullary thymic epithelial cells. The depletion of Rank in the mouse thymic epithelium results in reduced accumulation of natural Treg cells in the placenta, and an increase in the number of miscarriages. Thymic deletion of Rank also results in impaired accumulation of Treg cells in visceral adipose tissue, and is associated with enlarged adipocyte size, tissue inflammation, enhanced maternal glucose intolerance, fetal macrosomia, and a long-lasting transgenerational alteration in glucose homeostasis, which are all key hallmarks of gestational diabetes. Transplantation of Treg cells rescued fetal loss, maternal glucose intolerance and fetal macrosomia. In human pregnancies, we found that gestational diabetes also correlates with a reduced number of Treg cells in the placenta. Our findings show that RANK promotes the hormone-mediated development of thymic Treg cells during pregnancy, and expand the functional role of maternal Treg cells to the development of gestational diabetes and the transgenerational metabolic rewiring of glucose homeostasis.

Treatment of Gestational Diabetes Mellitus Diagnosed Early in Pregnancy.

BACKGROUND: Whether treatment of gestational diabetes before 20 weeks' gestation improves maternal and infant health is unclear. METHODS: We randomly assigned, in a 1:1 ratio, women between 4 weeks' and 19 weeks 6 days' gestation who had a risk factor for hyperglycemia and a diagnosis of gestational diabetes (World Health Organization 2013 criteria) to receive immediate treatment for gestational diabetes or deferred or no treatment, depending on the results of a repeat oral glucose-tolerance test [OGTT] at 24 to 28 weeks' gestation (control). The trial included three primary outcomes: a composite of adverse neonatal outcomes (birth at <37 weeks' gestation, birth trauma, birth weight of ≥4500 g, respiratory distress, phototherapy, stillbirth or neonatal death, or shoulder dystocia), pregnancy-related hypertension (preeclampsia, eclampsia, or gestational hypertension), and neonatal lean body mass. RESULTS: A total of 802 women underwent randomization; 406 were assigned to the immediate-treatment group and 396 to the control group; follow-up data were available for 793 women (98.9%). An initial OGTT was performed at a mean (±SD) gestation of 15.6±2.5 weeks. An adverse neonatal outcome event occurred in 94 of 378 women (24.9%) in the immediate-treatment group and in 113 of 370 women (30.5%) in the control group (adjusted risk difference, -5.6 percentage points; 95% confidence interval [CI], -10.1 to -1.2). Pregnancy-related hypertension occurred in 40 of 378 women (10.6%) in the immediate-treatment group and in 37 of 372 women (9.9%) in the control group (adjusted risk difference, 0.7 percentage points; 95% CI, -1.6 to 2.9). The mean neonatal lean body mass was 2.86 kg in the immediate-treatment group and 2.91 kg in the control group (adjusted mean difference, -0.04 kg; 95% CI, -0.09 to 0.02). No between-group differences were observed with respect to serious adverse events associated with screening and treatment. CONCLUSIONS: Immediate treatment of gestational diabetes before 20 weeks' gestation led to a modestly lower incidence of a composite of adverse neonatal outcomes than no immediate treatment; no material differences were observed for pregnancy-related hypertension or neonatal lean body mass. (Funded by the National Health and Medical Research Council and others; TOBOGM Australian New Zealand Clinical Trials Registry number, ACTRN12616000924459.).

Call to action for a life course approach.

Gestational diabetes remains the most common medical disorder in pregnancy, with short-term and long-term consequences for mothers and offspring. New insights into pathophysiology and management suggest that the current gestational diabetes treatment approach should expand from a focus on late gestational diabetes to a personalised, integrated life course approach from preconception to postpartum and beyond. Early pregnancy lifestyle intervention could prevent late gestational diabetes. Early gestational diabetes diagnosis and treatment has been shown to be beneficial, especially when identified before 14 weeks of gestation. Early gestational diabetes screening now requires strategies for integration into routine antenatal care, alongside efforts to reduce variation in gestational diabetes care, across settings that differ between, and within, countries. Following gestational diabetes, an oral glucose tolerance test should be performed 6-12 weeks postpartum to assess the glycaemic state. Subsequent regular screening for both dysglycaemia and cardiometabolic disease is recommended, which can be incorporated alongside other family health activities. Diabetes prevention programmes for women with previous gestational diabetes might be enhanced using shared decision making and precision medicine. At all stages in this life course approach, across both high-resource and low-resource settings, a more systematic process for identifying and overcoming barriers to preventative care and treatment is needed to reduce the current global burden of gestational diabetes.

Pathophysiology from preconception, during pregnancy, and beyond.

Gestational diabetes is the most common medical complication in pregnancy. Historically, gestational diabetes was considered a pregnancy complication involving treatment of rising glycaemia late in the second trimester. However, recent evidence challenges this view. Pre-pregnancy and pregnancy-specific factors influence gestational glycaemia, with open questions regarding roles of non-glycaemic factors in the aetiology and consequences of gestational diabetes. Varying patterns of insulin secretion and resistance in early and late pregnancy underlie a heterogeneity of gestational diabetes in the timing and pathophysiological subtypes with clinical implications: early gestational diabetes and insulin resistant gestational diabetes subtypes are associated with a higher risk of pregnancy complications. Metabolic perturbations of early gestational diabetes can affect early placental development, affecting maternal metabolism and fetal development. Fetal hyperinsulinaemia can affect the development of multiple fetal tissues, with short-term and long-term consequences. Pregnancy complications are prevented by managing glycaemia in early and late pregnancy in some, but not all women with gestational diabetes. A better understanding of the pathophysiology and heterogeneity of gestational diabetes will help to develop novel management approaches with focus on improved prevention of maternal and offspring short-term and long-term complications, from pre-conception, throughout pregnancy, and beyond.

Epidemiology and management of gestational diabetes.

Gestational diabetes is defined as hyperglycaemia first detected during pregnancy at glucose concentrations that are less than those of overt diabetes. Around 14% of pregnancies globally are affected by gestational diabetes; its prevalence varies with differences in risk factors and approaches to screening and diagnosis; and it is increasing in parallel with obesity and type 2 diabetes. Gestational diabetes direct costs are US$1·6 billion in the USA alone, largely due to complications including hypertensive disorders, preterm delivery, and neonatal metabolic and respiratory consequences. Between 30% and 70% of gestational diabetes is diagnosed in early pregnancy (ie, early gestational diabetes defined by hyperglycaemia before 20 weeks of gestation). Early gestational diabetes is associated with worse pregnancy outcomes compared with women diagnosed with late gestational diabetes (hyperglycaemia from 24 weeks to 28 weeks of gestation). Randomised controlled trials show benefits of treating gestational diabetes from 24 weeks to 28 weeks of gestation. The WHO 2013 recommendations for diagnosing gestational diabetes (one-step 75 gm 2-h oral glucose tolerance test at 24-28 weeks of gestation) are largely based on the Hyperglycemia and Adverse Pregnancy Outcomes Study, which confirmed the linear association between pregnancy complications and late-pregnancy maternal glycaemia: a phenomenon that has now also been shown in early pregnancy. Recently, the Treatment of Booking Gestational Diabetes Mellitus (TOBOGM) trial showed benefit in diagnosis and treatment of early gestational diabetes for women with risk factors. Given the diabesity epidemic, evidence for gestational diabetes heterogeneity by timing and subtype, and advances in technology, a life course precision medicine approach is urgently needed, using evidence-based prevention, diagnostic, and treatment strategies.

Lower versus Higher Glycemic Criteria for Diagnosis of Gestational Diabetes.

BACKGROUND: Treatment of gestational diabetes improves maternal and infant health, although diagnostic criteria remain unclear. METHODS: We randomly assigned women at 24 to 32 weeks' gestation in a 1:1 ratio to be evaluated for gestational diabetes with the use of lower or higher glycemic criteria for diagnosis. The lower glycemic criterion was a fasting plasma glucose level of at least 92 mg per deciliter (≥5.1 mmol per liter), a 1-hour level of at least 180 mg per deciliter (≥10.0 mmol per liter), or a 2-hour level of at least 153 mg per deciliter (≥8.5 mmol per liter). The higher glycemic criterion was a fasting plasma glucose level of at least 99 mg per deciliter (≥5.5 mmol per liter) or a 2-hour level of at least 162 mg per deciliter (≥9.0 mmol per liter). The primary outcome was the birth of an infant who was large for gestational age (defined as a birth weight above the 90th percentile according to Fenton-World Health Organization standards). Secondary outcomes were maternal and infant health. RESULTS: A total of 4061 women underwent randomization. Gestational diabetes was diagnosed in 310 of 2022 women (15.3%) in the lower-glycemic-criteria group and in 124 of 2039 women (6.1%) in the higher-glycemic-criteria group. Among 2019 infants born to women in the lower-glycemic-criteria group, 178 (8.8%) were large for gestational age, and among 2031 infants born to women in the higher-glycemic-criteria group, 181 (8.9%) were large for gestational age (adjusted relative risk, 0.98; 95% confidence interval, 0.80 to 1.19; P = 0.82). Induction of labor, use of health services, use of pharmacologic agents, and neonatal hypoglycemia were more common in the lower-glycemic-criteria group than in the higher-glycemic-criteria group. The results for the other secondary outcomes were similar in the two trial groups, and there were no substantial between-group differences in adverse events. Among the women in both groups who had glucose test results that fell between the lower and higher glycemic criteria, those who were treated for gestational diabetes (195 women), as compared with those who were not (178 women), had maternal and infant health benefits, including fewer large-for-gestational-age infants. CONCLUSIONS: The use of lower glycemic criteria for the diagnosis of gestational diabetes did not result in a lower risk of a large-for-gestational-age infant than the use of higher glycemic criteria. (Funded by the Health Research Council of New Zealand and others; GEMS Australian New Zealand Clinical Trials Registry number, ACTRN12615000290594.).

Identify gestational diabetes mellitus by deep learning model from cell-free DNA at the early gestation stage.

Gestational diabetes mellitus (GDM) is a common complication of pregnancy, which has significant adverse effects on both the mother and fetus. The incidence of GDM is increasing globally, and early diagnosis is critical for timely treatment and reducing the risk of poor pregnancy outcomes. GDM is usually diagnosed and detected after 24 weeks of gestation, while complications due to GDM can occur much earlier. Copy number variations (CNVs) can be a possible biomarker for GDM diagnosis and screening in the early gestation stage. In this study, we proposed a machine-learning method to screen GDM in the early stage of gestation using cell-free DNA (cfDNA) sequencing data from maternal plasma. Five thousand and eighty-five patients from north regions of Mainland China, including 1942 GDM, were recruited. A non-overlapping sliding window method was applied for CNV coverage screening on low-coverage (~0.2×) sequencing data. The CNV coverage was fed to a convolutional neural network with attention architecture for the binary classification. The model achieved a classification accuracy of 88.14%, precision of 84.07%, recall of 93.04%, F1-score of 88.33% and AUC of 96.49%. The model identified 2190 genes associated with GDM, including DEFA1, DEFA3 and DEFB1. The enriched gene ontology (GO) terms and KEGG pathways showed that many identified genes are associated with diabetes-related pathways. Our study demonstrates the feasibility of using cfDNA sequencing data and machine-learning methods for early diagnosis of GDM, which may aid in early intervention and prevention of adverse pregnancy outcomes.

The role of ncRNA regulatory mechanisms in diseases-case on gestational diabetes.

Non-coding RNAs (ncRNAs) are a class of RNA molecules that do not have the potential to encode proteins. Meanwhile, they can occupy a significant portion of the human genome and participate in gene expression regulation through various mechanisms. Gestational diabetes mellitus (GDM) is a pathologic condition of carbohydrate intolerance that begins or is first detected during pregnancy, making it one of the most common pregnancy complications. Although the exact pathogenesis of GDM remains unclear, several recent studies have shown that ncRNAs play a crucial regulatory role in GDM. Herein, we present a comprehensive review on the multiple mechanisms of ncRNAs in GDM along with their potential role as biomarkers. In addition, we investigate the contribution of deep learning-based models in discovering disease-specific ncRNA biomarkers and elucidate the underlying mechanisms of ncRNA. This might assist community-wide efforts to obtain insights into the regulatory mechanisms of ncRNAs in disease and guide a novel approach for early diagnosis and treatment of disease.

Body Mass Index, Adverse Pregnancy Outcomes, and Cardiovascular Disease Risk.

BACKGROUND: Obesity is a well-established risk factor for both adverse pregnancy outcomes (APOs) and cardiovascular disease (CVD). However, it is not known whether APOs are mediators or markers of the obesity-CVD relationship. This study examined the association between body mass index, APOs, and postpartum CVD risk factors. METHODS: The sample included adults from the nuMoM2b (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be) Heart Health Study who were enrolled in their first trimester (6 weeks-13 weeks 6 days gestation) from 8 United States sites. Participants had a follow-up visit at 3.7 years postpartum. APOs, which included hypertensive disorders of pregnancy, preterm birth, small-for-gestational-age birth, and gestational diabetes, were centrally adjudicated. Mediation analyses estimated the association between early pregnancy body mass index and postpartum CVD risk factors (hypertension, hyperlipidemia, and diabetes) and the proportion mediated by each APO adjusted for demographics and baseline health behaviors, psychosocial stressors, and CVD risk factor levels. RESULTS: Among 4216 participants enrolled, mean±SD maternal age was 27±6 years. Early pregnancy prevalence of overweight was 25%, and obesity was 22%. Hypertensive disorders of pregnancy occurred in 15%, preterm birth in 8%, small-for-gestational-age birth in 11%, and gestational diabetes in 4%. Early pregnancy obesity, compared with normal body mass index, was associated with significantly higher incidence of postpartum hypertension (adjusted odds ratio, 1.14 [95% CI, 1.10-1.18]), hyperlipidemia (1.11 [95% CI, 1.08-1.14]), and diabetes (1.03 [95% CI, 1.01-1.04]) even after adjustment for baseline CVD risk factor levels. APOs were associated with higher incidence of postpartum hypertension (1.97 [95% CI, 1.61-2.40]) and hyperlipidemia (1.31 [95% CI, 1.03-1.67]). Hypertensive disorders of pregnancy mediated a small proportion of the association between obesity and incident hypertension (13% [11%-15%]) and did not mediate associations with incident hyperlipidemia or diabetes. There was no significant mediation by preterm birth or small-for-gestational-age birth. CONCLUSIONS: There was heterogeneity across APO subtypes in their association with postpartum CVD risk factors and mediation of the association between early pregnancy obesity and postpartum CVD risk factors. However, only a small or nonsignificant proportion of the association between obesity and CVD risk factors was mediated by any of the APOs, suggesting APOs are a marker of prepregnancy CVD risk and not a predominant cause of postpartum CVD risk.

Implications of pregnancy on cardiometabolic disease risk: preeclampsia and gestational diabetes.

Cardiometabolic disorders, such as obesity, insulin resistance, and hypertension, prior to and within pregnancy are increasing in prevalence worldwide. Pregnancy-associated cardiometabolic disease poses a great risk to the short- and long-term well-being of the mother and offspring. Hypertensive pregnancy, notably preeclampsia, as well as gestational diabetes are the major diseases of pregnancy growing in prevalence as a result of growing cardiometabolic disease prevalence. The mechanisms whereby obesity, diabetes, and other comorbidities lead to preeclampsia and gestational diabetes are incompletely understood and continually evolving in the literature. In addition, novel therapeutic avenues are currently being explored in these patients to offset cardiometabolic-induced adverse pregnancy outcomes in preeclamptic and gestational diabetes pregnancies. In this review, we discuss the emerging pathophysiological mechanisms of preeclampsia and gestational diabetes in the context of cardiometabolic risk as well as the most recent preclinical and clinical updates in the pathogenesis and treatment of these conditions.

Sex-Specific Alterations in Placental Proteomics Induced by Intrauterine Hyperglycemia.

Gestational diabetes mellitus (GDM) with intrauterine hyperglycemia induces a series of changes in the placenta, which have adverse effects on both the mother and the fetus. The aim of this study was to investigate the changes in the placenta in GDM and its gender differences. In this study, we established an intrauterine hyperglycemia model using ICR mice. We collected placental specimens from mice before birth for histological observation, along with tandem mass tag (TMT)-labeled proteomic analysis, which was stratified by sex. When the analysis was not segregated by sex, the GDM group showed 208 upregulated and 225 downregulated proteins in the placenta, primarily within the extracellular matrix and mitochondria. Altered biological processes included cholesterol metabolism and oxidative stress responses. After stratification by sex, the male subgroup showed a heightened tendency for immune-related pathway alterations, whereas the female subgroup manifested changes in branched-chain amino acid metabolism. Our study suggests that the observed sex differences in placental protein expression may explain the differential impact of GDM on offspring.

ChIP-seq and RNA-seq Reveal the Involvement of Histone Lactylation Modification in Gestational Diabetes Mellitus.

Lactylation is a novel post-translational modification of proteins. Although the histone lactylation modification has been reported to be involved in glucose metabolism, its role and molecular pathways in gestational diabetes mellitus (GDM) are still unclear. This study aims to elucidate the histone lactylation modification landscapes of GDM patients and explore lactylation-modification-related genes involved in GDM. We employed a combination of RNA-seq analysis and chromatin immunoprecipitation sequencing (ChIP-seq) analysis to identify upregulated differentially expressed genes (DEGs) with hyperhistone lactylation modification in GDM. We demonstrated that the levels of lactate and histone lactylation were significantly elevated in GDM patients. DEGs were involved in diabetes-related pathways, such as the PI3K-Akt signaling pathway, Jak-STAT signaling pathway, and mTOR signaling pathway. ChIP-seq analysis indicated that histone lactylation modification in the promoter regions of the GDM group was significantly changed. By integrating the results of RNA-seq and ChIP-seq analysis, we found that CACNA2D1 is a key gene for histone lactylation modification and is involved in the progression of GDM by promoting cell vitality and proliferation. In conclusion, we identified the key gene CACNA2D1, which upregulated and exhibited hypermodification of histone lactylation in GDM. These findings establish a theoretical groundwork for the targeted therapy of GDM.

Habitual carbohydrate intake is not correlated with circulating ß-hydroxybutyrate levels in pregnant women with overweight and obesity at 28 weeks' gestation.

AIMS/HYPOTHESIS: Pregnant women are advised to consume a minimum of 175 g per day of carbohydrate to meet maternal and fetal brain glucose requirements. This recommendation comes from a theoretical calculation of carbohydrate requirements in pregnancy, rather than from clinical data. This study aimed to determine whether fasting maternal ketone levels are associated with habitual carbohydrate intake in a subset of participants of the Study of PRobiotics IN Gestational diabetes (SPRING) randomised controlled trial. METHODS: Food frequency questionnaires on dietary intake during pregnancy were completed by pregnant women with overweight or obesity at 28 weeks' gestation (considering their intake from the beginning of pregnancy). Dietary intake from early pregnancy through to 28 weeks was analysed for macronutrient intake. At the same time, overnight fasting serum samples were obtained and analysed for metabolic parameters including serum ß-hydroxybutyrate, OGTTs, insulin and C-peptide. RESULTS: Fasting serum ß-hydroxybutyrate levels amongst 108 women (mean BMI 34.7 ± 6.3 kg/m2) ranged from 22.2 to 296.5 µmol/l. Median fasting ß-hydroxybutyrate levels were not different between women with high (median [IQR] 68.4 [49.1-109.2 µmol/l]) and low (65.4 [43.6-138.0 µmol/l]) carbohydrate intake in pregnancy. Fasting ß-hydroxybutyrate levels were not correlated with habitual carbohydrate intake (median 155 [126-189] g/day). The only metabolic parameter with which fasting ß-hydroxybutyrate levels were correlated was 1 h venous plasma glucose (ρ=0.23, p=0.03) during a 75 g OGTT. CONCLUSIONS/INTERPRETATION: Fasting serum ß-hydroxybutyrate levels are not associated with habitual carbohydrate intake at 28 weeks' gestation in pregnant women with overweight and obesity.

Analysis of early-pregnancy metabolome in early- and late-onset gestational diabetes reveals distinct associations with maternal overweight.

AIMS/HYPOTHESIS: It is not known whether the early-pregnancy metabolome differs in patients with early- vs late-onset gestational diabetes mellitus (GDM) stratified by maternal overweight. The aims of this study were to analyse correlations between early-pregnancy metabolites and maternal glycaemic and anthropometric characteristics, and to identify early-pregnancy metabolomic alterations that characterise lean women (BMI <25 kg/m2) and women with overweight (BMI ≥25 kg/m2) with early-onset GDM (E-GDM) or late-onset GDM (L-GDM). METHODS: We performed a nested case-control study within the population-based prospective Early Diagnosis of Diabetes in Pregnancy cohort, comprising 210 participants with GDM (126 early-onset, 84 late-onset) and 209 normoglycaemic control participants matched according to maternal age, BMI class and primiparity. Maternal weight, height and waist circumference were measured at 8-14 weeks' gestation. A 2 h 75 g OGTT was performed at 12-16 weeks' gestation (OGTT1), and women with normal results underwent repeat testing at 24-28 weeks' gestation (OGTT2). Comprehensive metabolomic profiling of fasting serum samples, collected at OGTT1, was performed by untargeted ultra-HPLC-MS. Linear models were applied to study correlations between early-pregnancy metabolites and maternal glucose concentrations during OGTT1, fasting insulin, HOMA-IR, BMI and waist circumference. Early-pregnancy metabolomic features for GDM subtypes (participants stratified by maternal overweight and gestational timepoint at GDM onset) were studied using linear and multivariate models. The false discovery rate was controlled using the Benjamini-Hochberg method. RESULTS: In the total cohort (n=419), the clearest correlation patterns were observed between (1) maternal glucose concentrations and long-chain fatty acids and medium- and long-chain acylcarnitines; (2) maternal BMI and/or waist circumference and long-chain fatty acids, medium- and long-chain acylcarnitines, phospholipids, and aromatic and branched-chain amino acids; and (3) HOMA-IR and/or fasting insulin and L-tyrosine, certain long-chain fatty acids and phospholipids (q<0.001). Univariate analyses of GDM subtypes revealed significant differences (q<0.05) for seven non-glucose metabolites only in overweight women with E-GDM compared with control participants: linolenic acid, oleic acid, docosapentaenoic acid, docosatetraenoic acid and lysophosphatidylcholine 20:4/0:0 abundances were higher, whereas levels of specific phosphatidylcholines (P-16:0/18:2 and 15:0/18:2) were lower. However, multivariate analyses exploring the early-pregnancy metabolome of GDM subtypes showed differential clustering of acylcarnitines and long-chain fatty acids between normal-weight and overweight women with E- and L-GDM. CONCLUSIONS/INTERPRETATION: GDM subtypes show distinct early-pregnancy metabolomic features that correlate with maternal glycaemic and anthropometric characteristics. The patterns identified suggest early-pregnancy disturbances of maternal lipid metabolism, with most alterations observed in overweight women with E-GDM. Our findings highlight the importance of maternal adiposity as the primary target for prevention and treatment.

Identification and validation of gestational diabetes subgroups by data-driven cluster analysis.

AIMS/HYPOTHESIS: Gestational diabetes mellitus (GDM) is a heterogeneous condition. Given such variability among patients, the ability to recognise distinct GDM subgroups using routine clinical variables may guide more personalised treatments. Our main aim was to identify distinct GDM subtypes through cluster analysis using routine clinical variables, and analyse treatment needs and pregnancy outcomes across these subgroups. METHODS: In this cohort study, we analysed datasets from a total of 2682 women with GDM treated at two central European hospitals (1865 participants from Charité University Hospital in Berlin and 817 participants from the Medical University of Vienna), collected between 2015 and 2022. We evaluated various clustering models, including k-means, k-medoids and agglomerative hierarchical clustering. Internal validation techniques were used to guide best model selection, while external validation on independent test sets was used to assess model generalisability. Clinical outcomes such as specific treatment needs and maternal and fetal complications were analysed across the identified clusters. RESULTS: Our optimal model identified three clusters from routinely available variables, i.e. maternal age, pre-pregnancy BMI (BMIPG) and glucose levels at fasting and 60 and 120 min after the diagnostic OGTT (OGTT0, OGTT60 and OGTT120, respectively). Cluster 1 was characterised by the highest OGTT values and obesity prevalence. Cluster 2 displayed intermediate BMIPG and elevated OGTT0, while cluster 3 consisted mainly of participants with normal BMIPG and high values for OGTT60 and OGTT120. Treatment modalities and clinical outcomes varied among clusters. In particular, cluster 1 participants showed a much higher need for glucose-lowering medications (39.6% of participants, compared with 12.9% and 10.0% in clusters 2 and 3, respectively, p<0.0001). Cluster 1 participants were also at higher risk of delivering large-for-gestational-age infants. Differences in the type of insulin-based treatment between cluster 2 and cluster 3 were observed in the external validation cohort. CONCLUSIONS/INTERPRETATION: Our findings confirm the heterogeneity of GDM. The identification of subgroups (clusters) has the potential to help clinicians define more tailored treatment approaches for improved maternal and neonatal outcomes.

Maternal and neonatal outcomes according to the timing of diagnosis of hyperglycaemia in pregnancy: a nationwide cross-sectional study of 695,912 deliveries in France in 2018.

AIMS/HYPOTHESIS: We aimed to assess maternal-fetal outcomes according to various subtypes of hyperglycaemia in pregnancy. METHODS: We used data from the French National Health Data System (Système National des Données de Santé), which links individual data from the hospital discharge database and the French National Health Insurance information system. We included all deliveries after 22 gestational weeks (GW) in women without pre-existing diabetes recorded in 2018. Women with hyperglycaemia were classified as having overt diabetes in pregnancy or gestational diabetes mellitus (GDM), then categorised into three subgroups according to their gestational age at the time of GDM diagnosis: before 22 GW (GDM<22); between 22 and 30 GW (GDM22-30); and after 30 GW (GDM>30). Adjusted prevalence ratios (95% CI) for the outcomes were estimated after adjusting for maternal age, gestational age and socioeconomic status. Due to the multiple tests, we considered an association to be statistically significant according to the Holm-Bonferroni procedure. To take into account the potential immortal time bias, we performed analyses on deliveries at ≥31 GW and deliveries at ≥37 GW. RESULTS: The study population of 695,912 women who gave birth in 2018 included 84,705 women (12.2%) with hyperglycaemia in pregnancy: overt diabetes in pregnancy, 0.4%; GDM<22, 36.8%; GDM22-30, 52.4%; and GDM>30, 10.4%. The following outcomes were statistically significant after Holm-Bonferroni adjustment for deliveries at ≥31 GW using GDM22-30 as the reference. Caesarean sections (1.54 [1.39, 1.72]), large-for-gestational-age (LGA) infants (2.00 [1.72, 2.32]), Erb's palsy or clavicle fracture (6.38 [2.42, 16.8]), preterm birth (1.84 [1.41, 2.40]) and neonatal hypoglycaemia (1.98 [1.39, 2.83]) were more frequent in women with overt diabetes. Similarly, LGA infants (1.10 [1.06, 1.14]) and Erb's palsy or clavicle fracture (1.55 [1.22, 1.99]) were more frequent in GDM<22. LGA infants (1.44 [1.37, 1.52]) were more frequent in GDM>30. Finally, women without hyperglycaemia in pregnancy were less likely to have preeclampsia or eclampsia (0.74 [0.69, 0.79]), Caesarean section (0.80 [0.79, 0.82]), pregnancy and postpartum haemorrhage (0.93 [0.89, 0.96]), LGA neonate (0.67 [0.65, 0.69]), premature neonate (0.80 [0.77, 0.83]) and neonate with neonatal hypoglycaemia (0.73 [0.66, 0.82]). Overall, the results were similar for deliveries at ≥37 GW. Although the estimation of the adjusted prevalence ratio of perinatal death was five times higher (5.06 [1.87, 13.7]) for women with overt diabetes, this result was non-significant after Holm-Bonferroni adjustment. CONCLUSIONS/INTERPRETATION: Compared with GDM22-30, overt diabetes, GDM<22 and, to a lesser extent, GDM>30 were associated with poorer maternal-fetal outcomes.

Genome-wide association and Mendelian randomisation analysis among 30,699 Chinese pregnant women identifies novel genetic and molecular risk factors for gestational diabetes and glycaemic traits.

AIMS/HYPOTHESIS: Gestational diabetes mellitus (GDM) is the most common disorder in pregnancy; however, its underlying causes remain obscure. This study aimed to investigate the genetic and molecular risk factors contributing to GDM and glycaemic traits. METHODS: We collected non-invasive prenatal test (NIPT) sequencing data along with four glycaemic and 55 biochemical measurements from 30,699 pregnant women during a 2 year period at Shenzhen Baoan Women's and Children's Hospital in China. Genome-wide association studies (GWAS) were conducted between genotypes derived from NIPTs and GDM diagnosis, baseline glycaemic levels and glycaemic levels after glucose challenges. In total, 3317 women were diagnosed with GDM, while 19,565 served as control participants. The results were replicated using two independent cohorts. Additionally, we performed one-sample Mendelian randomisation to explore potential causal associations between the 55 biochemical measurements and risk of GDM and glycaemic levels. RESULTS: We identified four genetic loci significantly associated with GDM susceptibility. Among these, MTNR1B exhibited the highest significance (rs10830963-G, OR [95% CI] 1.57 [1.45, 1.70], p=4.42×10-29), although its effect on type 2 diabetes was modest. Furthermore, we found 31 genetic loci, including 14 novel loci, that were significantly associated with the four glycaemic traits. The replication rates of these associations with GDM, fasting plasma glucose levels and 0 h, 1 h and 2 h OGTT glucose levels were 4 out of 4, 6 out of 9, 10 out of 11, 5 out of 7 and 4 out of 4, respectively. Mendelian randomisation analysis suggested that a genetically regulated higher lymphocytes percentage and lower white blood cell count, neutrophil percentage and absolute neutrophil count were associated with elevated glucose levels and an increased risk of GDM. CONCLUSIONS/INTERPRETATION: Our findings provide new insights into the genetic basis of GDM and glycaemic traits during pregnancy in an East Asian population and highlight the potential role of inflammatory pathways in the aetiology of GDM and variations in glycaemic levels. DATA AVAILABILITY: Summary statistics for GDM; fasting plasma glucose; 0 h, 1 h and 2h OGTT; and the 55 biomarkers are available in the GWAS Atlas (study accession no.: GVP000001, https://ngdc.cncb.ac.cn/gwas/browse/GVP000001) .

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.

A loss-of-function mutation in KCNJ11 causing sulfonylurea-sensitive diabetes in early adult life.

AIMS/HYPOTHESIS: The ATP-sensitive potassium (KATP) channel couples beta cell electrical activity to glucose-stimulated insulin secretion. Loss-of-function mutations in either the pore-forming (inwardly rectifying potassium channel 6.2 [Kir6.2], encoded by KCNJ11) or regulatory (sulfonylurea receptor 1, encoded by ABCC8) subunits result in congenital hyperinsulinism, whereas gain-of-function mutations cause neonatal diabetes. Here, we report a novel loss-of-function mutation (Ser118Leu) in the pore helix of Kir6.2 paradoxically associated with sulfonylurea-sensitive diabetes that presents in early adult life. METHODS: A 31-year-old woman was diagnosed with mild hyperglycaemia during an employee screen. After three pregnancies, during which she was diagnosed with gestational diabetes, the patient continued to show elevated blood glucose and was treated with glibenclamide (known as glyburide in the USA and Canada) and metformin. Genetic testing identified a heterozygous mutation (S118L) in the KCNJ11 gene. Neither parent was known to have diabetes. We investigated the functional properties and membrane trafficking of mutant and wild-type KATP channels in Xenopus oocytes and in HEK-293T cells, using patch-clamp, two-electrode voltage-clamp and surface expression assays. RESULTS: Functional analysis showed no changes in the ATP sensitivity or metabolic regulation of the mutant channel. However, the Kir6.2-S118L mutation impaired surface expression of the KATP channel by 40%, categorising this as a loss-of-function mutation. CONCLUSIONS/INTERPRETATION: Our data support the increasing evidence that individuals with mild loss-of-function KATP channel mutations may develop insulin deficiency in early adulthood and even frank diabetes in middle age. In this case, the patient may have had hyperinsulinism that escaped detection in early life. Our results support the importance of functional analysis of KATP channel mutations in cases of atypical diabetes.