BACKGROUND:Data regarding the impact of real-time continuous glucose monitoring (rt-CGM) on reducing adverse pregnancy outcomes in women with gestational diabetes are contradictory. We aimed to assess differences in the proportion of large-for-gestational-age (LGA) newborns between women using rt-CGM versus self-monitoring of blood glucose (SMBG). METHODS:For this open-label, parallel-group, multicentre, randomised controlled trial, women aged 18-55 years with singleton pregnancy and gestational diabetes (diagnosed according to the International Association of the Diabetes and Pregnancy Study Groups criteria), were randomly assigned (1:1) to rt-CGM or SMBG. The first allocation was by chance; for subsequent allocations, minimisation was used to balance three prespecified factors: gestational age at study entry, previous gestational diabetes, and preconceptional BMI. SMBG participants used blinded CGM for 10 days after randomisation and at 36-38 weeks; rt-CGM participants used open rt-CGM until delivery. All were managed according to standard care protocols in four university hospitals in Austria, Germany, and Switzerland. The primary endpoint was the proportion of LGA newborns (using the Perinatal Institute's GROW customised birthweight percentiles), assessed in the intention-to-treat population. Secondary endpoints included the requirement for glucose-lowering medication, CGM metrics, and non-glycaemic maternal and neonatal outcomes. Recruitment and follow-up are complete. This study is registered with ClinicalTrials.gov (NCT03981328). FINDINGS:Between Aug 24, 2020, and May 30, 2024, 610 women were screened for eligibility, of whom 375 (diagnosed with gestational diabetes at a mean of 25·2 weeks [SD 2·3] of gestation), were randomly assigned to rt-CGM (n=190) or SMBG (n=185) at a mean of 28·6 weeks (SD 1·9) of gestation. 170 intervention and 175 control participants with available data were assessed for the primary endpoint. LGA neonates were born to six (4%) of 170 rt-CGM and 18 (10%) of 175 SMBG participants (OR 0·32, 95% CI 0·10-0·87, p=0·014). Small-for-gestational-age (SGA) neonates were born to 33 (19%) and 23 (13%) participants, respectively (OR 1·59, 0·86-2·99, p=0·11). Serious adverse events occurred in 23 (12%) of 190 versus 28 (15%) of 185 participants (OR 0·77, 0·42-1·40, p=0·39). INTERPRETATION:rt-CGM use in women with gestational diabetes reduced LGA births, without differences in serious adverse events. The higher-than-expected overall prevalence of SGA infants, possibly related to the tight glycaemic control in our cohort, requires further research. FUNDING:Dexcom. TRANSLATION:For the German translation of the abstract see Supplementary Materials section.

There is no clear consensus regarding accurate risk stratification in early pregnancy for later developing gestational diabetes mellitus (GDM). Therefore, this study aims to evaluate the predictive performance of an OGTT and several biomarkers in the first trimester of pregnancy. Their association with insulin action, beta cell function and requirement for insulin were additionally assessed. In this prospective cohort study, we included 657 pregnant women in six Central European centres. Patient history and anthropometric data were obtained, a blinded 75 g OGTT was performed and biochemical markers were assessed at a median gestational age of 13.4 weeks (IQR 12.7–14.1). Another OGTT was performed in later pregnancy to identify women with GDM. A detailed investigation of glucose homeostasis was performed at both visits in a subgroup of women. Eighty-three women (12.6

The identification of mothers at risk for gestational diabetes mellitus (GDM) at start of pregnancy may be beneficial to improve perinatal outcomes. This study aims evaluating the predictive performance of fasting and dynamic indices of glucose metabolism at first trimester and their association with later GDM development. A cohort of 198 women received detailed metabolic assessment at median gestational age (13 weeks) including 75-g oral glucose tolerance test (OGTT) with assessment of glucose, insulin and C-peptide, and biochemical markers (including triglycerides) to calculate different indices of insulin sensitivity either at fasting and in the OGTT dynamic conditions. Moreover, parameters of β-cell function were assessed. A second OGTT was performed between 24 and 28 gestational weeks (GW) to identify women with GDM. We found that 28 women developed GDM, and, in univariable analysis, this was fairly predicted by several first trimester indices, both at fasting and in dynamic conditions. However, fasting indices containing maternal triglycerides showed better accuracy as compared to traditional indices (even the dynamic ones). In multivariable analysis, the best predictive model of GDM development included fasting and OGTT glucose values, HbA1c, and an insulin sensitivity marker that includes triglycerides (e.g. the improved triglyceride-glucose index, TyGIS). β-Cell function was not included in such predictive model, but at 24–28 GW it showed remarkable impairment in women with GDM. In conclusion, both fasting and dynamic parameters of glucose homeostasis at early pregnancy showed fair predictive accuracy for later GDM, with TyGIS showing excellent performance. β-Cell dysfunction role needs being further elucidated.

Accurate assessment of pancreatic beta-cell function parameters, such as glucose sensitivity (G-Sens), rate sensitivity (R-Sens), and potentiation factor ratio (PFR), relies on mathematical modelling coupled with C-peptide measurement, both not always accessible in clinical settings. Machine learning may provide surrogate markers of model-and-C-peptide-based parameters. Aim of the study was to leverage machine learning to build predictive equations of G-Sens, R-Sens, and PFR in pregnant women, without the need of modeling and C-peptide. To this aim, predictive approaches were implemented (multivariate polynomial regressions), under different scenarios of data availability. We found that G-Sens prediction showed good performance (R-adj(2) = 0.45, p<0.0001 in test set), whereas results were unsatisfactory for R-Sens. PFR prediction showed moderate performance (R-adj(2) = 0.33, p < 0.01 in test set). In conclusion, machine learning is appropriate for G-Sens and PFR prediction, while R-Sens prediction appears hardly feasible.

IntroductionWomen with migration background present specific challenges related to risk stratification and care of gestational diabetes mellitus (GDM). Therefore, this study aims to investigate the role of ethnic origin on the risk of developing GDM in a multiethnic European cohort.MethodsPregnant women were included at a median gestational age of 12.9 weeks and assigned to the geographical regions of origin: Caucasian Europe (n = 731), Middle East and North Africa countries (MENA, n = 195), Asia (n = 127) and Sub-Saharan Africa (SSA, n = 48). At the time of recruitment maternal characteristics, glucometabolic parameters and dietary habits were assessed. An oral glucose tolerance test was performed in mid-gestation for GDM diagnosis.ResultsMothers with Caucasian ancestry were older and had higher blood pressure and an adverse lipoprotein profile as compared to non-Caucasian mothers, whereas non-Caucasian women (especially those from MENA countries) had a higher BMI and were more insulin resistant. Moreover, we found distinct dietary habits. Non-Caucasian mothers, especially those from MENA and Asian countries, had increased incidence of GDM as compared to the Caucasian population (OR 1.87, 95%CI 1.40 to 2.52, p < 0.001). Early gestational fasting glucose and insulin sensitivity were consistent risk factors across different ethnic populations, however, pregestational BMI was of particular importance in Asian mothers.DiscussionPrevalence of GDM was higher among women from MENA and Asian countries, who already showed adverse glucometabolic profiles at early gestation. Fasting glucose and early gestational insulin resistance (as well as higher BMI in women from Asia) were identified as important risk factors in Caucasian and non-Caucasian patients.

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.

Aims A family history of type 2 diabetes mellitus (T2DM) markedly increases an individual's lifetime risk of developing the disease. For gestational diabetes (GDM), this risk factor is less well characterized. This study aimed to investigate the relationship between family history of T2DM in first- and second-degree relatives in women with GDM and the differences in metabolic characteristics at early gestation. Methods This prospective cohort study included 1129 pregnant women. A broad risk evaluation was performed before 16 + 0 weeks of gestation, including a detailed family history of the different types of diabetes and a laboratory examination of glucometabolic parameters. Participants were followed up until delivery and GDM assessed according to the latest diagnosis criteria. Results We showed that pregnant women with first- (FHD1, 26.6%, OR 1.91, 95%CI 1.16 to 3.16, p = 0.005), second- (FHD2, 26.3%, OR 1.88, 95%CI 1.16 to 3.05, p = 0.005) or both first- and second-degree relatives with T2DM (FHD1 + D2, 33.3%, OR 2.64, 95%CI 1.41 to 4.94, p < 0.001) had a markedly increased risk of GDM compared to those with negative family history (FHN) ( n = 100, 15.9%). The association was strongest if both parents were affected (OR 4.69, 95%CI 1.33 to 16.55, p = 0.009). Women with FHD1 and FHD1 + D2 had adverse glucometabolic profiles already in early pregnancy. Conclusions Family history of T2DM is an important risk factor for GDM, also by applying the current diagnostic criteria. Furthermore, we showed that the degree of kinship plays an essential role in quantifying the risk already at early pregnancy.

Background and aims In addition to the well-known association between increased glucose concentrations and the development of fetal overgrowth, some recent evidence suggested that also other factors, such as preconceptional, maternal body mass index (BMI) have possible impact on the development of large for gestational age (LGA) offspring even in in non-diabetic women. This study aims to assess the associations between LGA in offspring with maternal biometry, biomarkers, and early pregnancy glucose metabolism.

Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection may negatively affect glucose metabolism. This study aims to assess glucose levels, prevalence of gestational diabetes mellitus (GDM) and perinatal outcome in women with history of COVID-19. To this purpose, a group of 65 patients with history of COVID-19 and 94 control patients were retrospectively recruited among pregnant women who attended the pregnancy outpatient department between 01/2020 and 02/2022. Glucose data from an oral glucose tolerance test (OGTT), GDM status and obstetric complications were assessed. We observed no differences in average (p = 0.37), fasting (p = 0.62) or post-load glucose concentrations (60 min: p = 0.19; 120 min: p = 0.95) during OGTT. A total of 15 (23.1%) women in the COVID-19 group and 18 (19.1%) women in the control group developed GDM (p = 0.55). Moreover, caesarean section rate, weight percentiles and pregnancy outcomes were comparable between the groups (p = 0.49). In conclusion, in this study we did not identify a possible impact of COVID-19 on glucose metabolism in pregnancy, especially with regard to glucose concentrations during the OGTT and prevalence of GDM.

Zielsetzung Eine positive Familienanamnese für Typ-2 Diabetes (T2DM) erhöht das Lebenszeitrisiko für die Erkrankung deutlich. Für Gestationsdiabetes (GDM) ist dieser Risikofaktor schlechter charakterisiert. Ziel dieser Studie war es, den Zusammenhang zwischen positiver T2DM-Familienanamnese und GDM Diagnose zu untersuchen und den Glukosestoffwechsel in der Frühschwangerschaft bei Schwangeren mit und ohne Familienanamnese für T2DM in Bezug auf eine spätere GDM Diagnose zu vergleichen.

Based on data measured during an oral glucose tolerance test, machine learning techniques were implemented to derive a simple empirical index for the estimation of the pancreatic beta-cell function in pregnant women, as assessed by mathematical modelling (beta-cell glucose sensitivity parameters). We studied a group of 84 pregnant women, who were analyzed by measuring and assessing a wide set of variables and parameters. Through a LASSO regularized support vector machine, we analyzed such wide batteries of variables/parameters and identified an index based on a simple algebraic equation (including glucose and C-peptide measurements only), which can predict the beta-cell glucose sensitivity with good accuracy (R 2 =0.64, p<0.0001, in the test set). In conclusion, the index is a good surrogate marker for the assessment of model-based beta-cell glucose sensitivity in pregnant women, thus it can be useful for easy application in the clinical context, where modelling analysis is not always possible.

Aims: Non-invasive hepatic steatosis indices can be used to assess the risk for metabolic (dysfunction) associated fatty liver disease (MAFLD). This may be helpful to detect metabolic disorders in pregnancy, specifically gestational diabetes (GDM). We aim to examine the association of these indices with parameters of glucose metabolism. Methods: 109 women underwent a metabolic characterization at 16 weeks of gestation and were classified according to the fatty-liver index (FLI) and hepaticsteatosis index (HSI) into low (G1), intermediate (G2) and high risk (G3). At 26 weeks, participants received an oral glucose tolerance test (OGTT) to assess insulin action, beta-cell function and GDM status. Results: Both MAFLD indices were associated with impaired insulin sensitivity and compensatory increase of insulin release. G3 groups showed impaired insulin action. The higher circulating insulin concentrations were not able to compensate for insulin resistance in women with higher MAFLD scores, resulting in an increased risk of GDM (OR: 1.05, 95% CI 1.03 to 1.08, p < 0.001 for FLI). MAFLD scores were associated with fetal overgrowth. Conclusions: Maternal MAFLD represents a high-risk obstetric condition. Hepatic steatosis indices are associated with impaired glucose regulation and may provide a useful tool for early risk assessment for impaired glucose metabolism.

Abstract 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.

Background: Maternal overweight is a risk factor for Gestational Diabetes Mellitus (GDM) . However, there is emerging evidence that increased maternal BMI has considerable impact on the development of large for gestational age (LGA) offspring even in women who do not develop GDM, possibly related to subtle impairments in glucose metabolism. This study aims to assess physiological changes associated with increased BMI. Methods: 21 women with overweight and 21 normal weight controls were included in this explorative study and received a metabolic assessment at early pregnancy (13.3 weeks) (Visit 1) , including a 60 min frequently sampled intravenous glucose tolerance test (FSIGT) . An OGTT was performed between 24 and 28 weeks of gestation (Visit 2) in women who remained normal glucose tolerant. Results: At V1 mothers with overweight showed significantly elevated fasting glucose and HbA1c values, a well as impaired insulin sensitivity at fasting condition and dynamically assessed during the FSIGT, whereby the Calculated Insulin Sensitivity index (CSI) was lower in the overweight group as compared to normal weight controls (3.5 vs. 6.7 10-4⋅[μU/mL]-1⋅min-1, p=0.025) . The Disposition Index (DI) as a parameter of β-cell function was significantly decreased in mothers with overweight. Likewise, maternal BMI was inversely related to fasting (rho=0.56, p=0.005) and dynamically assessed insulin sensitivity (rho=0.51, p=0.014) as well as the DI (rho=0.51, p=0.014) and the AUC of glucose (rho=0.66, p<0.001) and C-Peptide (rho=0.46, p=0.020) during the OGTT in mothers who remained normal glucose tolerant during pregnancy at V2. Conclusions: Increased maternal BMI is associated to insulin resistance and impaired β-cell function already at early pregnancy. We also observed that maternal BMI was associated with impaired glucose metabolism and especially elevated glucose levels during the OGTT at mid gestation in women who did not develop GDM and remained normal glucose tolerant. Disclosure T.Linder: None. D.Eppel: None. C.Monod: None. G.Kotzaeridi: None. A.Tura: None. C.S.Göbl: Research Support; Dexcom, Inc., Sanofi.

Members of the PIAS (protein inhibitor of activated STAT) family perform essential functions in modulating the activity of transcriptional regulators. Zimp7 and Zimp10 are two proteins that together form a subfamily of the PIAS. Like the other members of this family, they contain the zinc-binding SP-RING/Miz domain, which confers SUMO-conjugating activity. Both proteins have been shown to stimulate androgen receptor-mediated transcription. Previously, we reported that both Zimp7 and Zimp10 genes are extensively expressed and dynamically regulated in the developing mouse embryo. In this work, we investigated the expression of these genes during gonadal development. We found that their expression is sex-specific. Both genes initiate their transcription at early stages in the embryonic male gonad, reaching their peak at 13.5days post coitum, which coincides with the process of sex-specific germ cell mitotic arrest. Zimp7 is expressed in germ cells of the embryonic gonad and the adult testis. Immunofluorescence of spermatogenic cells revealed that Zimp7 protein localizes to nuclear territories in meiotic spermatocytes, including the XY bodies. On the other hand, Zimp10 is found in somatic cells, outside the testis cords and ceases to be expressed in the adult testis.

Introduction: Previous studies demonstrated a continuous decline in fetal growth throughout singleton pregnancy after bariatric surgery. However, intrauterine growth in twin pregnancy is subjected to further underlying processes. This study was to investigate the longitudinal assessment of fetal biometry and abdominal fat thickness of twin pregnancies conceived after gastric bypass (GB) surgery and compare them to body mass index-matched (BMIM) and obese (OB) controls. Materials and Methods: We retrospectively assessed ultrasound data of 30 women with dichorionic-diamniotic twin pregnancy (11 women after GB surgery, 9 OB mothers with pregestational BMI ≥30 kg/m2, and 10 BMIM and age-matched controls). We assessed fetal growth parameters including fetal subcutaneous adipose tissue thickness (FSCTT) as well as newborn biometry after delivery. Patient characteristics were obtained from the medical records. Results: The rise in FSCTT curves was markedly slower in the twin offspring of women with history of GB as compared to the offspring of OB mothers and offspring of BMIM controls. Hence, FSCTT was significantly decreased in the GB offspring as compared to both control groups at 34 weeks of gestation. Also, growth curves of abdominal circumference were decreased in the offspring of GB patients as compared to OB mothers. Infants of mothers with history of GB showed significantly lower birth weight percentiles compared to newborns of OB mothers (27.2 vs. 48.8 pct, p = 0.025). There was no significant difference in inter-twin birth weight difference between the offspring of GB (median: 9.9%, interquartile ranges [IQR]: 6.5–20.0) versus OB (median: 14.6%, IQR: 8.2–21.6) and BMIM controls (median: 9.0%, IQR: 6.3–12.6, p = 0.714). Conclusions: In summary, intrauterine growth delay in twin pregnancies after GB is assumed to be a multifactorial event with altered metabolism as the most important factor. However, special attention must be paid to the particularity of twin pregnancies as they seem to be subject to other additional mechanism.

BACKGROUND:In clinical practice, gestational diabetes mellitus (GDM) is treated as a homogenous disease but emerging evidence suggests that the diagnosis of GDM possibly comprises different metabolic entities. In this study, we aimed to assess early pregnancy characteristics of gestational diabetes mellitus entities classified according to the presence of fasting and/or post-load hyperglycaemia in the diagnostic oral glucose tolerance test performed at mid-gestation.METHODS:In this prospective cohort study, 1087 pregnant women received a broad risk evaluation and laboratory examination at early gestation and were later classified as normal glucose tolerant (NGT), as having isolated fasting hyperglycaemia (GDM-IFH), isolated post-load hyperglycaemia (GDM-IPH) or combined hyperglycaemia (GDM-CH) according to oral glucose tolerance test results. Participants were followed up until delivery to assess data on pharmacotherapy and pregnancy outcomes.RESULTS:Women affected by elevated fasting and post-load glucose concentrations (GDM-CH) showed adverse metabolic profiles already at beginning of pregnancy including a higher degree of insulin resistance as compared to women with normal glucose tolerance and those with isolated defects (especially GDM-IPH). The GDM-IPH subgroup had lower body mass index at early gestation and required glucose-lowering medications less often (28.9%) as compared to GDM-IFH (47.8%, P = .019) and GDM-CH (54.5%, P = .005). No differences were observed in pregnancy outcome data.CONCLUSIONS:Women with fasting hyperglycaemia, especially those with combined hyperglycaemia, showed an unfavourable metabolic phenotype already at early gestation. Therefore, categorization based on abnormal oral glucose tolerance test values provides a practicable basis for clinical risk stratification.