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Objective: Gestational diabetes mellitus (GDM) is a common complication during pregnancy and increases the risk of metabolic diseases in offspring. We hypothesize that the poor intrauterine environment in pregnant women with GDM may lead to chromosomal DNA damage and telomere damage in umbilical cord blood cells, providing evidence of an association between intrauterine programming and increased long-term metabolic disease risk in offspring. Methods: We measured telomere length (TL), serum telomerase (TE) activity, and oxidative stress markers in umbilical cord blood mononuclear cells (CBMCs) from pregnant women with GDM (N=200) and healthy controls (Ctrls) (N=200) and analysed the associations of TL with demographic characteristics, biochemical indicators, and blood glucose levels. Results: The length of telomeres in umbilical CBMCs in the GDM group was significantly shorter than that in the Ctrl group (P<0.001), and the shortening of telomeres in male infants in the GDM group was more significant than that in the Ctrl group (P<0.001) after adjustment for Pre-pregnancy body mass index (PBMI), Pregnancy weight gain (PGW), and Triglyceride (TG) as confounding factors. In addition, the TE expression level in the GDM group was lower after adjustment. There was no statistically significant difference in oxidative stress hydroxydeoxyguanosine (8-OHdG), malondialdehyde (MDA) and superoxide dismutase (SOD) between the two groups. TL was positively correlated with TE activity, and both were negatively correlated with blood glucose levels. There was no correlation between TL and Gestational age (GA), PBMI, PGW, or TG levels. Conclusion: The poor intrauterine environment in pregnant women with GDM increases telomere attrition and reduces TE activity, which may be potential genetic risk factors for an increased risk of metabolic diseases in offspring later in life due to intrauterine reprogramming. [ABSTRACT FROM AUTHOR]

Aims: To assess the predictive value of estradiol (E2) related parameters on the incidence of gestational diabetes mellitus (GDM) in women undergoing fresh embryo transfer. Materials and methods: A Post-hoc analysis of a prospective cohort study. Results: We identified an optimal E2/follicle (E2/F) ratio threshold of 246.03 pg/ml on the day of human chorionic gonadotropin (hCG) administration. Women with an E2/F ratio exceeding this threshold had significantly lower rates of GDM (12.75% vs. 20.41%, P < 0.001) and ovarian hyperstimulation syndrome (OHSS) (11.75% vs. 15.48%, P = 0.03). Additional E2 parameters were also evaluated: baseline E2, E2 on hCG day, E2 increase, and E2 fold change. Lower GDM rates were observed in women with baseline E2 above 31.50 pg/ml (13.51% vs. 19.42%, P <0.01), E2 on hCG day above 3794.50 pg/ml (12.26% vs. 19.32%, P < 0.001), and E2 increase above 3771.50 pg/ml (12.24% vs. 19.28%, P < 0.001). There were no significant differences in OHSS rates for these additional E2 parameters. After adjusting for confounders, lower E2/F ratio (OR: 1.626, 95% CI: 1.229-2.150, P <0.01), E2 on hCG day (OR: 1.511, 95% CI: 1.133-2.016, P = 0.01), and E2 increase (OR: 1.522, 95% CI: 1.141-2.031, P <0.01) were identified as risk factors for GDM. Conclusion: This study demonstrates that an E2/F ratio over 246.03 pg/ml is significantly associated with a reduced risk of both GDM and OHSS in women undergoing fresh embryo transfer, highlighting the E2/F ratio as a superior predictive biomarker compared to other E2-related parameters. [ABSTRACT FROM AUTHOR]

Pyroptosis is a form of programmed cell death that is crucial in the development of various diseases, including autoimmune diseases, atherosclerotic diseases, cancer, and pregnancy complications. In recent years, it has gained significant attention in national and international research due to its association with inflammatory immune overactivation and its involvement in pregnancy complications such as miscarriage and preeclampsia (PE). The mechanisms discussed include the canonical pyroptosis pathway of gasdermin activation and pore formation (caspase-1-dependent pyroptosis) and the non-canonical pyroptosis pathway (cysteoaspartic enzymes other than caspase-1). These pathways work on various cellular and factorial levels to influence normal pregnancy. This review aims to summarize and analyze the pyroptosis pathways associated with abnormal pregnancies and pregnancy complications. The objective is to enhance pregnancy outcomes by identifying various targets to prevent the onset of pyroptosis. [ABSTRACT FROM AUTHOR]

AimThe aim of this study was to explore the association between maternal pre-pregnancy body mass index (BMI) and neonatal birth weight in pregnancies with gestational diabetes mellitus (GDM).MethodsThis was a retrospective cohort study conducted between January 2019 and June 2020 at a university hospital in Fuzhou, China.ResultsPre-pregnancy BMI was used to categorize 791 pregnant women as underweight (3.03%), normal weight (51.71%), overweight (32.74%), and obese (12.52%). Among the 791 babies, 11.63% were small for gestational age (SGA), 77.37% were normal weight, and 11.00% were large for gestational age (LGA). The rate of the SGA babies increased with higher pre-pregnancy BMI. The percentage of LGA babies was higher in women who were overweight or obese compared to those of normal weight. Neonatal birth weight displayed a significantly increasing trend with increasing maternal pre-pregnancy BMI when maternal pre-pregnancy BMI was less than 27.78 kg/m2 [β = 0.03, 95% CI (0.01, 0.04); p = 0.0052

ObjectiveThe main objectives of our study are evaluating the health literacy level among women with gestational diabetes mellitus (GDM) in Southwest China and explore the influencing factors, using a multidimensional health literacy assessment scale (Chinese version of the HLS-14). Given that the HLS-14 has not been used in GDM previously, its reliability and validity testing was included as a secondary objective.MethodIt was a cross-sectional survey with 565 GDM pregnancies. The Maternal and child health information access questionnaire, Chinese version of the HLS-14, Perceived Social Support Scale (PSSS) and General Self-efficacy Scale (GSES) was used to collect health information access behaviors, health literacy, social support and self-efficacy levels, respectively. SPSS 21.0 was used for descriptive statistical, multiple stepwise linear regression analysis and exploratory factor analysis (EFA). Amos 26.0 was used for confirmatory factor analysis (CFA).ResultsThe Chinese version of HLS-14 has good reliability and validity in GDM pregnancies. The Cronbach’s α are 0.849, 0.866, 0.859, and 0.883, respectively. The exploratory factor analysis extracted three common factors with a cumulative variance contribution rate of 68.405%. The confirmatory factor analysis model fit was good (χ2/df = 2.595, RMSEA = 0.055, IFI = 0.970, TLI = 0.963, CFI = 0.970). The HL level in pregnancies with GDM was moderate with a mean score of 3.26 ± 0.41, of which 24.10% had limited HL, 41.87% had moderate HL, and 34.03% had adequate HL. Regression analysis showed that the women with higher family support (β = 0.298, p

ObjectiveGestational diabetes mellitus (GDM) is a common complication during pregnancy and increases the risk of metabolic diseases in offspring. We hypothesize that the poor intrauterine environment in pregnant women with GDM may lead to chromosomal DNA damage and telomere damage in umbilical cord blood cells, providing evidence of an association between intrauterine programming and increased long-term metabolic disease risk in offspring.MethodsWe measured telomere length (TL), serum telomerase (TE) activity, and oxidative stress markers in umbilical cord blood mononuclear cells (CBMCs) from pregnant women with GDM (N=200) and healthy controls (Ctrls) (N=200) and analysed the associations of TL with demographic characteristics, biochemical indicators, and blood glucose levels.ResultsThe length of telomeres in umbilical CBMCs in the GDM group was significantly shorter than that in the Ctrl group (P

AimConducted a one-day outpatient service for GDM patients, analyzed the relationship between stress adaptation disorder and insulin resistance in GDM patients after intervention, and tried to provide some new clues for the prevention and treatment of GDM, provide some theoretical basis for the multidisciplinary diagnosis and treatment model of GDM patients.Methods240 GDM women were included in this study, 120 women were included in one-day diabetes clinic management for GDM women as GDM Intervention Group, and 120 GDM women receiving regular dietary education as GDM Control Group. One-day diabetes clinic management including disease knowledge and dietary education, sports education and blood sugar monitoring and personalized issues and follow-up visits, and intervention time lasting for 1 month.ResultsAfter intervention, the concentration of 2-h postprandial blood glucose, and HOMA-IR were decreased in GDM Intervention Group, while weekly weight gain rate and insulin application rate were significantly lower than GDM Control Group (all p

BackgroundGestational diabetes mellitus (GDM) significantly affects the fetal metabolic environment, elevating risks of neonatal hypoglycemia and macrosomia. Metabolomics offers promising avenues for early prediction and diagnosis of GDM and associated adverse offspring outcomes.MethodsThis study analyzed serum samples from pregnant women diagnosed with GDM at 24 to 28 weeks of gestation using untargeted metabolomics. We monitored the health outcomes of their offspring to explore the correlation between initial serum metabolite profiles and subsequent health outcomes, to uncover the predictive markers for hypoglycemia and macrosomia in these offspring.ResultsOut of 200 participants, 154 had normal newborns, 33 had offspring with hypoglycemia, and 19 had offspring with macrosomia. From 448 identified metabolites, 66 showed significant differences in cases of hypoglycemia, and 45 in macrosomia. A panel of serum metabolite biomarkers achieved Area Under the Curve (AUC) values of 0.8712 for predicting hypoglycemia and 0.9434 for macrosomia.ConclusionThe study delineated metabolic disruptions in GDM during 24–28 weeks of gestation and pinpointed biomarkers capable of forecasting adverse neonatal outcomes. These findings could inform GDM management strategies and minimize the incidence of such outcomes.

BackgroundOutside of pregnancy, intuitive eating (IE) is associated with lower body weight, blood glucose, and higher positive mood. However, little was known about the relationship between IE and anxiety-depression in the GDM population. Thus, this study aimed to investigate the association of IE with anxiety and depression, pregnancy weight and pregnancy blood glucose in the first and second GDM visit.MethodsData from 310 pregnant women with GDM from the Fujian Maternal and Child Health Hospital Trial (Approval Number: 2020Y9133) were analyzed. IE was assessed using the Intuitive Eating Scale-2 subscales of Eating for Physiological Reasons rather than Emotional Reasons (EPR), Relying on Hunger and Satiety Cues (RHSC) and Body-Food Choice Consistency (B-FCC). Observations included weight, body mass index (BMI), fasting plasma glucose (FPG) and 2-h postprandial blood glucose; the Hospital Anxiety and Depression Scale (HADS) was used to assess the level of anxiety and depression in pregnant women with GDM. Linear regression analysis was used to assess the correlation between IE and anxiety, depression, pregnancy blood glucose and weight.ResultsThe cross-sectional analysis showed that the EPR eating behavior was negatively correlated with anxiety and depression, and the B-FCC eating behavior was negatively correlated with depression at both the first and second GDM visit; in addition, the B-FCC eating behavior was associated with lower BMI in the third trimester (all p

During pregnancy, insulin resistance and impaired insulin secretion may lead to the development of Gestational Diabetes Mellitus (GDM). Although a higher Body Mass Index (BMI) is often cited as a risk factor for the development of GDM, lean pregnant women are also at risk of developing GDM based on evidence from several studies. It is proposed that insulin deficiency (more than insulin resistance) leads to the development of GDM in women with low BMI (BMI

BackgroundGestational diabetes mellitus (GDM) is a prevalent condition where diabetes is diagnosed during pregnancy, affecting both maternal and fetal outcomes. Retinol-binding protein 4 (RBP4) is a circulating adipokine which belongs to the lipocalin family and acts as a specific carrier protein that delivers retinol (vitamin A) from the liver to the peripheral tissues. Growing data indicate that circulating RBP4 levels may positively correlate with GDM. Thus, this systematic review and meta-analysis aimed to investigate the potential relationship between circulating RBP4 levels and GDM when measured at various stages of pregnancy.MethodsMEDLINE, CINAHL, EMCARE, EMBASE, Scopus, and Web of Science databases were searched to identify studies comparing pregnant women with and without GDM, whose circulating RBP4 levels were measured in at least one pregnancy trimester. Findings were reported using standardized mean difference (SMD) and random-effects models were used to account for variability among studies. Furthermore, the risk of bias was assessed using the RoBANS tool.ResultsOut of the 34 studies identified, 32 were included in the meta-analysis (seven with circulating RBP4 levels measured in the first trimester, 19 at 24–28 weeks, and 14 at >28 weeks of pregnancy). RBP4 levels were statistically higher in the GDM group than in controls when measured during all these pregnancy stages, with the noted RBP4 SMD being 0.322 in the first trimester (95% CI: 0.126–0.517; p 28 weeks of gestation (95% CI: 0.252–1.498; p = 0.006; 870 GDM cases vs. 1942 non-GDM controls). Significant study heterogeneity was noted for all three pregnancy timepoints.ConclusionThe present findings indicate consistently higher circulating RBP4 levels in GDM cases compared to non-GDM controls, suggesting the potential relevance of RBP4 as a biomarker for GDM. However, the documented substantial study heterogeneity, alongside imprecision in effect estimates, underscores the need for further research and standardization of measurement methods to elucidate whether RBP4 can be utilized in clinical practice as a potential GDM biomarker.Systematic review registrationPROSPERO (CRD42022340097: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022340097).

ObjectiveTo study the predictive value of autoantibodies for type 1 (T1DM) and type 2 (T2DM) diabetes morbidity after gestational diabetes (GDM) in a 23-year follow-up study.DesignProspective population-based cohort study.MethodsWe studied 391 women with GDM, and 391 age- and parity-matched controls, who delivered in 1984–1994. Four autoantibodies were analysed in first-trimester blood samples: islet cell autoantibodies (ICAs), glutamic acid decarboxylase autoantibodies (GADAs), insulin autoantibodies (IAAs) and insulinoma-associated antigen-2 autoantibodies (IA-2As). Two follow-up questionnaires (1995–1996, 2012–2013) were sent to assess development of T1DM and T2DM. Predictive value of autoantibodies and clinical factors were analysed by conditional linear regression and ROC analyses.ResultsSingle autoantibody positivity was detected in 12% (41/342) of the GDM cohort and in 2.3% (8/353) of the control cohort. In the GDM cohort, 2.6% (9/342) tested positive for two autoantibodies and 2.3% (8/342) for three autoantibodies, whereas only one subject in the control cohort had two autoantibodies. ICA positivity was found in 12.5% of the cases, followed by GADA (6.0%), IA-2A (4.9%) and IAA (1.2%). In the control cohort, GADA positivity was found in 1.4%, IA-2A in 0.8%, IAA in 0.6%, and ICA in 0.3% of the subjects. Detection of ICA, GADA and/or IA-2A autoantibodies decreased T1DM-free survival time and time to diagnosis. All subjects with three positive autoantibodies developed T1DM within seven years from the GDM pregnancy. Development of T2DM after GDM occurred independent of autoantibody positivity.ConclusionDevelopment of T1DM can be reliably predicted with GADA and ICA autoantibodies during early pregnancy.

BackgroundSeasons were found to be related to the occurrences of venous thromboembolism (VTE) in hospitalized patients. No previous study has explored whether seasons were associated with VTE risk in pregnant women. This study aimed to investigate the relationships between the season of delivery and VTE risk during hospitalization among pregnant women.MethodsThis is a multi-center retrospective cohort study of pregnant women. Participants were those who delivered at seven designated sites in Hubei Province, China, during the period from January 2017 to December 2022. They were categorized according to their season/month of delivery. Information on new-onset VTE during hospitalization was followed.ResultsApproximately 0.28% (104/37,778) of the pregnant women developed new-onset VTE during hospitalization for delivery. After adjustment, compared with participants in the spring group, participants in the summer, autumn, and winter groups had an increased risk of VTE during hospitalization. The ORs were 2.59 [1.30, 5.15], 2.83 [1.43, 5.60], and 2.35 [1.17, 4.75] for the summer, autumn, and winter groups, respectively. Pregnant women in the combined group (summer + autumn + winter) had an increased risk of VTE during hospitalization than those in the spring group (OR, 2.59 [1.39, 4.85]). By restricting the analyses among pregnant women without in vitro fertilization, gestational diabetes mellitus, and preterm, the results still remained robust. Compared with participants who delivered in March, April, and May, participants who delivered in June, July, September, November, December, and February had a higher risk of VTE during hospitalization.ConclusionThis study demonstrated that pregnant women who delivered in summer, autumn, and winter had an increased VTE risk during hospitalization compared with those who delivered in spring.

AimsGestational diabetes mellitus (GDM) stands as a prevalent obstetric complication bearing consequential health implications for both mother and child. While existing studies have probed the alterations in acylcarnitines during GDM, an updated systematic meta-analysis is needed to consolidate these findings. Hence, this study endeavours to furnish a comprehensive systematic review and meta-analysis delineating the association between acylcarnitines and GDM, aimed at bolstering diagnostic accuracy and preventive measures against GDM.MethodsTo extract pertinent studies for this meta-analysis, we meticulously scoured databases such as PubMed, Web of Science, Embase, and Cochrane Library up until May 2023. The inclusion criteria were studies contrasting plasma metabolomics between two cohorts: women diagnosed with GDM and normoglycemic pregnant women. Weighted mean differences (SMDs) and 95% confidence intervals (CIs) were calculated using random-effects models. The I2 index was employed to quantify heterogeneity amongst the studies. All meta-analyses were executed using Stata version 12.0.ResultsOur meta-analysis included eight studies encompassing 878 pregnant women. The analysis disclosed that relative to normoglycemic pregnant women, women with GDM exhibited significantly elevated levels of Short-Chain Acylcarnitines (SCAC) (SMD: 0.19, 95% CI: 0.02–0.36, I2 = 71.3%). No substantial difference was discerned in fasting total carnitine levels (SMD: 0.15, 95% CI: −0.16–0.31, I2 = 68.2%), medium-chain acylcarnitines (MCAC) (SMD: 0.08, 95% CI: −0.02–0.36, I2 = 79.0%), and long-chain acylcarnitines (LCAC) (SMD: 0.04, 95% CI: −0.06–0.15, I2 = 0%). Neither funnel plot assessment nor Egger’s regression and Begg’s rank correlation tests indicated any evidence of publication bias.ConclusionOur meta-analysis suggests that elevated levels of SCAC may heighten the risk of GDM onset. Given GDM’s deleterious impact on pregnant women and their offspring, these findings underscore the clinical imperative of managing this condition. Early surveillance of plasma metabolomic profiles, particularly serum acylcarnitine concentrations, may equip clinicians with a valuable tool for timely diagnosis and intervention in GDM.

AimWe aimed to evaluate the association of pregestational diabetes mellitus (PGDM) and gestational diabetes mellitus (GDM) with neonatal seizures during neonatal hospitalization.MethodsIn this nested case–control study, all data were collected from the data files of the National Vital Statistics System (NVSS) 2016–2021. Considering the effect of confounders, we used the propensity-score matching (PSM; case:control = 1:4) method to select the study population. The outcome was considered the occurrence of neonatal seizures. Univariate and multivariate logistic regression analyses were adopted to assess the association of PGDM and GDM with neonatal seizures. We also conducted stratified analyses according to gestational age, birthweight, 5 min Apgar score, and maternal age to explore the potential disparities.ResultsAfter using the PSM method, a total of 6,674 cases of neonatal seizures and 26,696 controls were included. After adjusting for covariates, PGDM was associated with an increased risk of neonatal seizures [odds ratio (OR) = 1.51, 95% confidence interval (CI): 1.15–1.98], whereas the association between GDM and neonatal seizures is not statistically significant. In addition, the correlation between PGDM and increased risk of neonatal seizures was observed in neonates with a gestational age of 37–42 weeks and ≥42 weeks, with a 5 min Apgar score of ≥7, and with a maternal age of ≤40 years.ConclusionPGDM was found to be closely associated with an increased risk of neonatal seizures. The findings of our study indicated that neonatologists should consider monitoring the incidence of neonatal seizures in neonates born to mothers with PGDM.

Introduction: Gestational diabetes mellitus (GDM) is the most common pregnancy complication worldwide and is associated with short- and longterm health implications for both mother and child. Prevalence of GDM varies between ethnicities, with South Asians (SAs) experiencing up to three times the risk compared to white Europeans (WEs). Recent evidence suggests that underlying metabolic difference contribute to this disparity, but an investigation of causality is required. Methods: To address this, we paired metabolite and genomic data to evaluate the causal effect of 146 distinct metabolic characteristics on gestational dysglycemia in SAs and WEs. First, we performed 292 GWASs to identify ethnic-specific genetic variants associated with each metabolite (P = 1 x 10-5) in the Born and Bradford cohort (3688 SA and 3354 WE women). Following this, a one-sample Mendelian Randomisation (MR) approach was applied for each metabolite against fasting glucose and 2-hr post glucose at 26-28 weeks gestation. Additional GWAS and MR on 22 composite measures of metabolite classes were also conducted. Results: This study identified 15 novel genome-wide significant (GWS) SNPs associated with tyrosine in the FOXN and SLC13A2 genes and 1 novel GWS SNP (currently in no known gene) associated with acetate in SAs. Using MR approach, 14 metabolites were found to be associated with postprandial glucose in WEs, while in SAs a distinct panel of 11 metabolites were identified. Interestingly, in WEs, cholesterols were the dominant metabolite class driving with dysglycemia, while in SAs saturated fatty acids and total fatty acids were most commonly associated with dysglycemia. Discussion: In summary, we confirm and demonstrate the presence of ethnicspecific causal relationships between metabolites and dysglycemia in midpregnancy in a UK population of SA and WE pregnant women. Future work will aim to investigate their biological mechanisms on dysglycemia and translating this work towards ethnically tailored GDM prevention strategies. [ABSTRACT FROM AUTHOR]

IntroductionGestational diabetes mellitus (GDM) is the most common pregnancy complication worldwide and is associated with short- and long-term health implications for both mother and child. Prevalence of GDM varies between ethnicities, with South Asians (SAs) experiencing up to three times the risk compared to white Europeans (WEs). Recent evidence suggests that underlying metabolic difference contribute to this disparity, but an investigation of causality is required.MethodsTo address this, we paired metabolite and genomic data to evaluate the causal effect of 146 distinct metabolic characteristics on gestational dysglycemia in SAs and WEs. First, we performed 292 GWASs to identify ethnic-specific genetic variants associated with each metabolite (P ≤ 1 x 10-5) in the Born and Bradford cohort (3688 SA and 3354 WE women). Following this, a one-sample Mendelian Randomisation (MR) approach was applied for each metabolite against fasting glucose and 2-hr post glucose at 26-28 weeks gestation. Additional GWAS and MR on 22 composite measures of metabolite classes were also conducted.ResultsThis study identified 15 novel genome-wide significant (GWS) SNPs associated with tyrosine in the FOXN and SLC13A2 genes and 1 novel GWS SNP (currently in no known gene) associated with acetate in SAs. Using MR approach, 14 metabolites were found to be associated with postprandial glucose in WEs, while in SAs a distinct panel of 11 metabolites were identified. Interestingly, in WEs, cholesterols were the dominant metabolite class driving with dysglycemia, while in SAs saturated fatty acids and total fatty acids were most commonly associated with dysglycemia.DiscussionIn summary, we confirm and demonstrate the presence of ethnic-specific causal relationships between metabolites and dysglycemia in mid-pregnancy in a UK population of SA and WE pregnant women. Future work will aim to investigate their biological mechanisms on dysglycemia and translating this work towards ethnically tailored GDM prevention strategies.

Objective: This study aims to develop and evaluate a predictive nomogram for early assessment risk factors of gestational diabetes mellitus (GDM) during early pregnancy term, so as to help early clinical management and intervention. Methods: A total of 824 pregnant women at Zhongnan Hospital of Wuhan University and Maternal and Child Health Hospital of Hubei Province from 1 February 2020 to 30 April 2020 were enrolled in a retrospective observational study and comprised the training dataset. Routine clinical and laboratory information was collected; we applied least absolute shrinkage and selection operator (LASSO) logistic regression and multivariate ROC risk analysis to determine significant predictors and establish the nomogram, and the early pregnancy files (gestational weeks 12--16, n = 392) at the same hospital were collected as a validation dataset. We evaluated the nomogram via the receiver operating characteristic (ROC) curve, C-index, calibration curve, and decision curve analysis (DCA). Results: We conducted LASSO analysis and multivariate regression to establish a GDM nomogram during the early pregnancy term; the five selected risk predictors are as follows: age, blood urea nitrogen (BUN), fibrinogen-to-albumin ratio (FAR), blood urea nitrogen-to-creatinine ratio (BUN/Cr), and blood urea nitrogen-to-albumin ratio (BUN/ALB). The calibration curve and DCA present optimal predictive power. DCA demonstrates that the nomogram could be applied clinically. Conclusion: An effective nomogram that predicts GDM should be established in order to help clinical management and intervention at the early gestational stage. [ABSTRACT FROM AUTHOR]

Objectives: Studies that use continuous glucose monitoring (CGM) to monitor women with gestational diabetes (GDM), highlight the importance of managing dysglycemia over a 24-hour period. However, the effect of current treatment methods on dysglycemia over 24-hrs are currently unknown. This study aimed to characterise CGM metrics over 24-hrs in women with GDM and the moderating effect of treatment strategy. Methods: Retrospective analysis of CGM data from 128 women with GDM in antenatal diabetes clinics. CGM was measured for 7-days between 30-32 weeks gestation. Non-parametric tests were used to evaluate differences of CGM between periods of day (morning, afternoon, evening, and overnight) and between treatment methods (i.e., diet alone or diet+metformin). Exploratory analysis in a subgroup of 34 of participants was performed to investigate the association between self-reported macronutrient intake and glycaemic control. Results: Glucose levels significantly differed during the day (i.e., morning to evening; P<0.001) and were significantly higher (i.e., mean blood glucose and area under the curve [AUC]) and more variable (i.e., SD and CV) than overnight glucose levels. Morning showed the highest amount of variability (CV; 8.4% vs 6.5%, P<0.001 and SD; 0.49 mmol/L vs 0.38 mmol/L, P<0.001). When comparing treatment methods, mean glucose (6.09 vs 5.65 mmol/L; P<0.001) and AUC (8760.8 vs 8115.1 mmol/L.hr; P<0.001) were significantly higher in diet +metformin compared to diet alone. Finally, the exploratory analysis revealed a favourable association between higher protein intake (+1SD or +92 kcal/day) and lower mean glucose (-0.91 mmol/L p, P=0.02) and total AUC (1209.6 mmol/L.h, P=0.021). Conclusions: Glycemia varies considerably across a day, with morning glycemia demonstrating greatest variability. Additionally, our work supports that individuals assigned to diet+metformin have greater difficulty managing glycemia and results suggest that increased dietary protein may assist with management of dysglycemia. Future work is needed to investigate the benefit of increased protein intake on management of dysglycemia. [ABSTRACT FROM AUTHOR]

Gestational diabetes mellitus (GDM) is a disorder which manifests itself for the first time during pregnancy and is mainly connected with glucose metabolism. It is also known that fatty acid profile changes in erythrocyte membranes and plasma could be associated with obesity and insulin resistance. These factors can lead to the development of diabetes. In the reported study, we applied the untargeted analysis of plasma in GDM against standard glucose-tolerant (NGT) women to identify the differences in metabolomic profiles between those groups. We found higher levels of 2-hydroxybutyric and 3-hydroxybutyric acids. Both secondary metabolites are associated with impaired glucose metabolism. However, they are products of different metabolic pathways. Additionally, we applied lipidomic profiling using gas chromatography to examine the fatty acid composition of cholesteryl esters in the plasma of GDM patients. Among the 14 measured fatty acids characterizing the representative plasma lipidomic cluster, myristic, oleic, arachidonic, and α-linoleic acids revealed statistically significant changes. Concentrations of both myristic acid, one of the saturated fatty acids (SFAs), and oleic acid, which belong to monounsaturated fatty acids (MUFAs), tend to decrease in GDM patients. In the case of polyunsaturated fatty acids (PUFAs), some of them tend to increase (e.g., arachidonic), and some of them tend to decrease (e.g., α-linolenic). Based on our results, we postulate the importance of hydroxybutyric acid derivatives, cholesteryl ester composition, and the oleic acid diminution in the pathophysiology of GDM. There are some evidence suggests that the oleic acid can have the protective role in diabetes onset. However, metabolic alterations that lead to the onset of GDM are complex; therefore, further studies are needed to confirm our observations.

AimTo evaluate the improvement of glycemic control and stress adaptation in patients with GDM by mobile phone WeChat management during novel coronavirus pneumonia.MethodsIn this study, 75 women with GDM were included, of whom 35 were included in mobile WeChat group management as the GDM-M group and 40 as the GDM group.ResultsAfter mobile WeChat group management for 4 weeks, E and NE were lower. MDA was lower, and SOD was higher. HOMA-IR was lower. E, NE, and cortisol were related to HOMA-IR positively, MDA was positively related to HOMA-IR, and SOD was negatively related to HOMA-IR. E and cortisol were positively related to MDA but negatively related to SOD.ConclusionThe stress adaptation disorder and insulin resistance in patients with GDM who have completed mobile WeChat group management can be improved during novel coronavirus pneumonia. Mobile WeChat management played a positive role in improving the insulin resistance of women with GDM under special circumstances, which may reduce the risk of maternal and fetal complications.

ObjectiveWe aimed to explore whether irisin participates in the beneficial effects of exercise in preventing gestational diabetes mellitus (GDM) in overweight and obese pregnant women.Study designSixty overweight and obese pregnant women each in the exercise and control groups were randomly selected from our previous randomized controlled trial. Eighteen obese model mice were generated and divided into exercise and control groups in which body weight, abdominal circumference, anal temperature, glucose tolerance test, and insulin tolerance test were recorded. The plasma irisin level, the expression of PGC-1α/FNDC5 and brown (UCP1) and beige adipose (CD137, TMEM26, and TBX-1) marker genes were detected in muscle and adipose tissue.ResultsIn the human study, women in the exercise group had a significantly higher irisin level and lower insulin resistance level than those in the control group. Enhanced expression of beige adipose tissue marker genes (CD137, TMEM26, and TBX-1) in omental adipose tissue and the CD137 gene in subcutaneous adipose tissue were found in the exercise group compared to the control group. In a mouse model, body weight and abdominal circumference were decreased, while glucose homeostasis and insulin sensitivity were significantly improved, and anal temperature was elevated after exercise intervention. A significantly higher level of irisin was revealed in the exercise group after undergoing exercise treatment. The expression of the beige adipose marker genes CD137 and TBX-1 was significantly higher in the exercise group than in the control group in posterior subcutaneous adipose tissue from the inguinal area and interscapular adipose tissue respectively.ConclusionOur observations show that regular exercise during pregnancy can increase irisin levels, promote white fat beiging/browning, improve glucose homeostasis and enhance body energy expenditure, which may be one of the mechanisms by which exercise prevents GDM.

ObjectivesStudies that use continuous glucose monitoring (CGM) to monitor women with gestational diabetes (GDM), highlight the importance of managing dysglycemia over a 24-hour period. However, the effect of current treatment methods on dysglycemia over 24-hrs are currently unknown. This study aimed to characterise CGM metrics over 24-hrs in women with GDM and the moderating effect of treatment strategy.MethodsRetrospective analysis of CGM data from 128 women with GDM in antenatal diabetes clinics. CGM was measured for 7-days between 30-32 weeks gestation. Non-parametric tests were used to evaluate differences of CGM between periods of day (morning, afternoon, evening, and overnight) and between treatment methods (i.e., diet alone or diet+metformin). Exploratory analysis in a subgroup of 34 of participants was performed to investigate the association between self-reported macronutrient intake and glycaemic control.ResultsGlucose levels significantly differed during the day (i.e., morning to evening; P

Backgrounds: Given the roles of microRNA (miRNA) in human diseases and the high incidence of gestational diabetes mellitus (GDM), the aim of the study was to examine miRNA signatures and crucial pathways, as well as possible biomarkers for GDM diagnosis.Methods: We conducted a two-stage study to explore functional miRNA and those target genes. Twelve participants (6 GDM and 6 non-GDM) were first enrolled and performed RNA sequencing analysis. The overlapped candidate genes were further screened in combination with differentially expressed genes (DEGs) of GEO datasets (GSE87295, GSE49524 and GSE19649) and potential target genes of DEMs. Candidate genes, critical pathways, small molecular compounds and regulatory networks were identified using bioinformatic analysis. The potential candidate genes were then investigated using the GEO dataset (GSE103552) of 19 participants in the validation stage (11 GDM and 8 non-GDM women).Results: Briefly, blood samples were sequenced interrogating 50 miRNAs, including 20 upregulated and 30 downregulated differentially expressed microRNAs(DEMs) in our internal screening dataset. After screening GEO databases, 123 upregulated and 70 downregulated genes were overlapped through DEGs of GEO datasets and miRNA-target genes. MiR-29b-1-5p-TGFB2, miR-142-3p-TGFB2, miR-9-5p-FBN2, miR-212-5p-FBN2, miR-542-3p-FBN1, miR-9-5p-FBN1, miR-508-3p-FBN1, miR-493-5p-THBS1, miR-29b-3p-COL4A1, miR-432-5p-COL5A2, miR-9-5p-TGFBI, miR-486-3p-SLC7A5 and miR-6515-5p-SLC1A5 were revealed as thirteen possible regulating pathways by integrative analysis.Conclusion: Overall, thirteen candidate miRNA-target gene regulatory pathways representing potentially novel biomarkers of GDM diseases were revealed. Ten chemicals were identified as putative therapeutic agents for GDM. This study examined a series of DEGs that are associated with epigenetic alternations of miRNA through an integrated approach and gained insight into biological pathways in GDM. Precise diagnosis and therapeutic targets of GDM would be further explored through putative genes in the future.

Gestational diabetes mellitus (GDM), or any degree of glucose intolerance recognized for the first time during pregnancy, is one of the diseases that most frequently aggravates the course of gestation. Missed or late diagnosis and inadequate treatment are associated with high maternal and fetal morbidity, with possible short- and long-term repercussions. Estimates on the prevalence of GDM are alarming and increasing by about 30% in the last 10–20 years. In addition, there is the negative influence of the SARS-CoV-2 emergency on the glycemic control of pregnant women, making the matter increasingly topical. To date, knowledge on the metabolic maturation of newborns is still incomplete. However, in light of the considerable progress of the theory of “developmental origins of health and disease,” the relevant role of the intrauterine environment cannot be overlooked. In fact, due to the high plasticity of the early stages of development, some detrimental metabolic alterations during fetal growth, including maternal hyperglycemia, are associated with a higher incidence of chronic diseases in adult life. In this context, metabolomic analysis which allows to obtain a detailed phenotypic portrait through the dynamic detection of all metabolites in cells, tissues and different biological fluids could be very useful for the early diagnosis and prevention of complications. Indeed, if the diagnostic timing is optimized through the identification of specific metabolites, the detailed understanding of the altered metabolic pathway could also allow better management and more careful monitoring, also from a nutritional profile, of the more fragile children. In this context, a further contribution derives from the analysis of the intestinal microbiota, the main responsible for the fecal metabolome, given its alteration in pregnancies complicated by GDM and the possibility of transmission to offspring. The purpose of this review is to analyze the available data regarding the alterations in the metabolomic profile and microbiota of the offspring of mothers with GDM in order to highlight future prospects for reducing GDM-related complications in children of mothers affected by this disorder.

Gestational diabetes mellitus (GDM) is associated with considerable imbalances in intestinal microbiota that may underlie pathological conditions in both mothers and infants. To more definitively identify these alterations, we evaluated the maternal and infant gut microbiota through the shotgun metagenomic analysis of a subset of stool specimens collected from a randomized, controlled trial in diet-controlled women with GDM. The women were fed either a CHOICE diet (60% complex carbohydrate/25% fat/15% protein, n=18) or a conventional diet (CONV, 40% complex carbohydrate/45% fat/15% protein, n=16) from 30 weeks' gestation through delivery. In contrast to other published studies, we designed the study to minimize the influence of other dietary sources by providing all meals, which were eucaloric and similar in fiber content. At 30 and 37 weeks' gestation, we collected maternal stool samples; performed the fasting measurements of glucose, glycerol, insulin, free fatty acids, and triglycerides; and administered an oral glucose tolerance test (OGTT) to measure glucose clearance and insulin response. Infant stool samples were collected at 2 weeks, 2 months, and 4-5 months of age. Maternal glucose was controlled to conventional targets in both diets, with no differences in Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). No differences in maternal alpha or beta diversity between the two diets from baseline to 37 weeks' gestation were observed. However, women on CHOICE diet had higher levels of Bifidobacteriaceae, specifically Bifidobacterium adolescentis, compared with women on CONV. Species-level taxa varied significantly with fasting glycerol, fasting glucose, and glucose AUC after the OGTT challenge. Maternal diet significantly impacted the patterns of infant colonization over the first 4 months of life, with CHOICE infants showing increased microbiome alpha diversity (richness), greater Clostridiaceae, and decreased Enterococcaceae over time. Overall, these results suggest that an isocaloric GDM diet containing greater complex carbohydrates with reduced fat leads to an ostensibly beneficial effect on the maternal microbiome, improved infant gut microbiome diversity, and reduced opportunistic pathogens capable of playing a role in obesity and immune system development. These results highlight the critical role a maternal diet has in shaping the maternal and infant microbiome in women with GDM. [ABSTRACT FROM AUTHOR]

The placenta is a vital organ for fetal development, providing the fetus with nutrients, oxygen, and other important factors. Placenta is rich in blood vessels. Abnormal placental vascular function and blood circulation may lead to insufficient blood supply to the fetus in the uterus, leading to serious consequences such as pregnancy complications, fetal distress and even stillbirth. Pregnancy-induced hypertension (PIH) and gestational diabetes mellitus (GDM) are common complications of pregnancy. Recent studies report that pregnancy complications are often accompanied by changes in placental vascular structure and function. What are the physiological characteristics of human placental blood vessels? What are the pathological changes in the state of PIH and GDM? What are the relationships between these pathological changes and the occurrence of these pregnancy complications? Answers to these questions not only increase the understanding of placental vascular characteristics, but also provide important information for revealing the pathological mechanism of PIH and GDM. This article will summarize the research on the pathological changes of placental blood vessels in PIH and GDM, hoping to further unravel the physiological and pathological characteristics of placental blood vessels in the state of PIH and GDM, provide information for guiding clinical treatment for PIH and GDM. [ABSTRACT FROM AUTHOR]

Background & Aims: Hepatitis B virus (HBV) infection is a significant cause of liver function damage. However, previous studies on HBV mainly aimed at ordinary people, and there is a lack of consensus on the relationship between HBV infection and gestational diabetes mellitus (GDM) and whether HBV-infected pregnant women should undergo antiviral treatment. In addition, systematic studies on the impact of HBV infection on GDM have rarely been studied directly. Therefore, the overall goal of this study was to pursue the association between HBV infection, liver function, and GDM using Xiamen area gestational big data. Methods: Using the Xiamen Primary Health Information System-maternal and child health information system, the data on participants (138,867 in total) expected confinement between 2008 and 2018 were included. Using univariate and multivariate logistic regressions, we constructed models to determine the role of HBV infection and liver function status in GDM. In addition, an analysis of variance tests was performed to study whether the relationship between HBsAg and GDM differed in the normal liver function and the abnormal liver function subgroups. Results: HBsAg's positive status showed a substantial correlation with GDM onset in univariate and multivariate logistic regressions (p < 0.001). Subgroup analysis among HBsAg, liver function, and GDM suggests that both HBsAg and liver function affect the onset of GDM and have the highest prevalence of both abnormalities. Furthermore, ANOVA was used to investigate the association of HBsAg positive (p < 0.001), abnormal liver function (p < 0.001), and their interaction (p = 0.302) on the onset of GDM. This result showed that HBsAg is an independent factor of GDM pathogenesis, regardless of liver function status. Conclusion: HBsAg and liver function are independent factors in GDM. Therefore, regarding these results, while clinicians consider the traditional risk factors of GDM, it is necessary to consider the HBV infection status. Conducting a dietary intervention for HBsAg-positive pregnant women at the early stage of pregnancy is conducive to reducing the adverse effects. [ABSTRACT FROM AUTHOR]

Aims: Universal screening of gestational diabetes mellitus (GDM) in women with no risk factors (RF) for GDM remains controversial. This study identified the impact of the presence of RF on perinatal and postpartum outcomes. Methods: This prospective cohort study included 780 women with GDM. GDM RF included previous GDM, first grade family history of type 2 diabetes, high-risk ethnicity and pre-pregnancy overweight/obesity (OW/OB). Outcomes included obstetrical, neonatal and maternal metabolic parameters during pregnancy and up to 1 year postpartum. Results: Out of 780 patients, 24% had no RF for GDM. Despite this, 40% of them needed medical treatment and they had a high prevalence of glucose intolerance of 21 and 27% at 6-8 weeks and 1-year postpartum, respectively. Despite similar treatment, women with RF had more neonatal and obstetrical complications, but they had especially more frequent adverse metabolic outcomes in the short- and long-term. The most important RF for poor perinatal outcome were previous GDM and pre-pregnancy OW/OB, whereas high-risk ethnicity and pre-pregnancy OW/OB were RF for adverse postpartum metabolic outcomes. Increasing number of RF were associated with worsened perinatal and long-term postpartum outcomes except for pregnancy-induced hypertension, C-section delivery and neonatal hypoglycaemia. Conclusion: Women with no RF had a high prevalence of adverse perinatal and postpartum outcomes, while the presence of RF particularly increased the risk for postpartum adverse metabolic outcomes. This calls for a RF-based long-term follow-up of women with GDM. [ABSTRACT FROM AUTHOR]

Gestational diabetes mellitus (GDM) is a high-risk pregnancy complication that is associated with metabolic disorder phenotypes, such as abnormal blood glucose and obesity. The active interface between gut microbiota and diet contributes to metabolic homeostasis in GDM. However, the contributions of gut mycobiome have been neglected. Here, we profiled the gut fungi between GDM and healthy subjects at two time points and investigate whether variations in gut mycobiome correlate with key features of host metabolism and diet management in this observational study. We identified that Hanseniaspora, Torulaspora, Auricularia, Alternaria , and Candida contributed to GDM patient clustering, indicating that these fungal taxa are associated with abnormal blood glucose levels, and the causality needs to be further explored. While Penicillium, Ganoderma, Fusarium, Chaetomium , and Heterobasidion had significant explanatory effects on healthy subject clustering. In addition, spearman analysis further indicated that blood glucose levels were negatively correlated with polysaccharide-producing genera, Ganoderma , which could be reshaped by the short-term diet. The Penicillium which was negatively correlates with metabolic parameters, also exhibited the antimicrobial attribute by the fungal-bacterial interaction analysis. These data suggest that host metabolic homeostasis in GDM may be influenced by variability in the mycobiome and could be reshaped by the diet intervention. This work reveals the potential significance of the gut mycobiome in health and has implications for the beneficial effects of diet intervention on host metabolic homeostasis through regulating gut fungal abundance and metabolites. [ABSTRACT FROM AUTHOR]

Gestational diabetes mellitus (GDM) is associated with considerable imbalances in intestinal microbiota that may underlie pathological conditions in both mothers and infants. To more definitively identify these alterations, we evaluated the maternal and infant gut microbiota through the shotgun metagenomic analysis of a subset of stool specimens collected from a randomized, controlled trial in diet-controlled women with GDM. The women were fed either a CHOICE diet (60% complex carbohydrate/25% fat/15% protein, n=18) or a conventional diet (CONV, 40% complex carbohydrate/45% fat/15% protein, n=16) from 30 weeks’ gestation through delivery. In contrast to other published studies, we designed the study to minimize the influence of other dietary sources by providing all meals, which were eucaloric and similar in fiber content. At 30 and 37 weeks’ gestation, we collected maternal stool samples; performed the fasting measurements of glucose, glycerol, insulin, free fatty acids, and triglycerides; and administered an oral glucose tolerance test (OGTT) to measure glucose clearance and insulin response. Infant stool samples were collected at 2 weeks, 2 months, and 4–5 months of age. Maternal glucose was controlled to conventional targets in both diets, with no differences in Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). No differences in maternal alpha or beta diversity between the two diets from baseline to 37 weeks’ gestation were observed. However, women on CHOICE diet had higher levels of Bifidobacteriaceae, specifically Bifidobacterium adolescentis, compared with women on CONV. Species-level taxa varied significantly with fasting glycerol, fasting glucose, and glucose AUC after the OGTT challenge. Maternal diet significantly impacted the patterns of infant colonization over the first 4 months of life, with CHOICE infants showing increased microbiome alpha diversity (richness), greater Clostridiaceae, and decreased Enterococcaceae over time. Overall, these results suggest that an isocaloric GDM diet containing greater complex carbohydrates with reduced fat leads to an ostensibly beneficial effect on the maternal microbiome, improved infant gut microbiome diversity, and reduced opportunistic pathogens capable of playing a role in obesity and immune system development. These results highlight the critical role a maternal diet has in shaping the maternal and infant microbiome in women with GDM.

AimsUniversal screening of gestational diabetes mellitus (GDM) in women with no risk factors (RF) for GDM remains controversial. This study identified the impact of the presence of RF on perinatal and postpartum outcomes.MethodsThis prospective cohort study included 780 women with GDM. GDM RF included previous GDM, first grade family history of type 2 diabetes, high-risk ethnicity and pre-pregnancy overweight/obesity (OW/OB). Outcomes included obstetrical, neonatal and maternal metabolic parameters during pregnancy and up to 1 year postpartum.ResultsOut of 780 patients, 24% had no RF for GDM. Despite this, 40% of them needed medical treatment and they had a high prevalence of glucose intolerance of 21 and 27% at 6-8 weeks and 1-year postpartum, respectively. Despite similar treatment, women with RF had more neonatal and obstetrical complications, but they had especially more frequent adverse metabolic outcomes in the short- and long-term. The most important RF for poor perinatal outcome were previous GDM and pre-pregnancy OW/OB, whereas high-risk ethnicity and pre-pregnancy OW/OB were RF for adverse postpartum metabolic outcomes. Increasing number of RF were associated with worsened perinatal and long-term postpartum outcomes except for pregnancy-induced hypertension, C-section delivery and neonatal hypoglycaemia.ConclusionWomen with no RF had a high prevalence of adverse perinatal and postpartum outcomes, while the presence of RF particularly increased the risk for postpartum adverse metabolic outcomes. This calls for a RF-based long-term follow-up of women with GDM.

Gestational diabetes mellitus (GDM) is a high-risk pregnancy complication that is associated with metabolic disorder phenotypes, such as abnormal blood glucose and obesity. The active interface between gut microbiota and diet contributes to metabolic homeostasis in GDM. However, the contributions of gut mycobiome have been neglected. Here, we profiled the gut fungi between GDM and healthy subjects at two time points and investigate whether variations in gut mycobiome correlate with key features of host metabolism and diet management in this observational study. We identified that Hanseniaspora, Torulaspora, Auricularia, Alternaria, and Candida contributed to GDM patient clustering, indicating that these fungal taxa are associated with abnormal blood glucose levels, and the causality needs to be further explored. While Penicillium, Ganoderma, Fusarium, Chaetomium, and Heterobasidion had significant explanatory effects on healthy subject clustering. In addition, spearman analysis further indicated that blood glucose levels were negatively correlated with polysaccharide-producing genera, Ganoderma, which could be reshaped by the short-term diet. The Penicillium which was negatively correlates with metabolic parameters, also exhibited the antimicrobial attribute by the fungal-bacterial interaction analysis. These data suggest that host metabolic homeostasis in GDM may be influenced by variability in the mycobiome and could be reshaped by the diet intervention. This work reveals the potential significance of the gut mycobiome in health and has implications for the beneficial effects of diet intervention on host metabolic homeostasis through regulating gut fungal abundance and metabolites.

Introduction: Weight change during the interpregnancy is related to gestational diabetes mellitus (GDM) in the subsequent pregnancy. In interpregnancy care/counseling, the timeframe for goal setting is important, while the timing of the next conception is unpredictable and preventing age-related body weight gain is difficult. This study aimed to investigate the association between annual weight gain during the interpregnancy, which provide clearer timeframe, and GDM in subsequent pregnancies. Methods: This multicenter retrospective study was conducted by collecting data on two pregnancies of the same women in 2009–2019. The association between annual BMI gain and GDM during the subsequent pregnancy was examined. Results: This study included 1,640 pregnant women. A history of GDM [adjusted odds ratio (aOR), 26.22; 95% confidence interval (CI), 14.93–46.07] and annual BMI gain (aOR, 1.48; 95% CI, 1.22–1.81) were related to GDM during the subsequent pregnancy. In the women with a pre-pregnant BMI of <25.0 kg/m2 and without GDM during the index pregnancy, an annual BMI gain of ≥0.6 kg/m2/year during the interpregnancy were associated with GDM in subsequent pregnancies; however, in the other subgroups, it was not associated with GDM in subsequent pregnancies. Conclusions: For women with a pre-pregnant BMI of <25.0 kg/m2 and without GDM during the index pregnancy, maintaining an annual BMI gain of <0.6 kg/m2/year may prevent GDM during the subsequent pregnancy. [ABSTRACT FROM AUTHOR]

BackgroundThe implications of gestational diabetes mellitus (GDM) on the short- and long-term health outcomes of both mother and child have been extensively studied. However, studies related to negative Oral Glucose Tolerance Test (OGTT) results in the second trimester but dysglycemia in late pregnancy on maternal and infant pregnancy outcomes are rare.MethodsWe conducted a nest case-control study within the Xi'an Longitudinal Mother-Child Cohort study (XAMC) to investigate the risk of adverse pregnancy outcomes in mothers and children with maternal negative mid-pregnancy OGTT results but high glycated hemoglobin (HbA1c) levels (≥5.7%) in late pregnancy. All target women who delivered from January 1st, 2017 to December 31st, 2018 in Northwest Women's and Children's Hospital in Xi'an were enrolled as the case group (HbA1c ≥ 5.7%). Others with HbA1c < 5.7% but without GDM were selected as the control group (HbA1c < 5.7%) by matching with the same delivery period. The logistic regression models were used to find out the risk factors of adverse pregnancy outcomes in the target population.ResultsA total of 2,116 and 1,907 women were finally enrolled in the case and control groups, respectively. Compared to the control group, more newborns with macrosomia (9.2% vs 4.1%, P < 0.001) and large for gestational age (LGA) (23.7% vs. 13.5%, P < 0.001), but less small for gestational age (SGA) (4.4% vs. 6.1%, P = 0.017) were found in the case group. The differences in other outcomes were not statistically significant. The multiple logistic regression analysis showed that gestational age, fetal length, prenatal HbA1c, and total cholesterol (TG) were independent risk factors for newborns with large-for-gestational-age (LGA). The case group had a 2.516-fold (95% CI, 1.692–3.739) risk of delivering LGA newborns compared to the control group.ConclusionThe glycemic management during the late pregnancy of non-GDM women should be given special consideration to reduce the risk of overweight offspring at birth.

IntroductionWeight change during the interpregnancy is related to gestational diabetes mellitus (GDM) in the subsequent pregnancy. In interpregnancy care/counseling, the timeframe for goal setting is important, while the timing of the next conception is unpredictable and preventing age-related body weight gain is difficult. This study aimed to investigate the association between annual weight gain during the interpregnancy, which provide clearer timeframe, and GDM in subsequent pregnancies.MethodsThis multicenter retrospective study was conducted by collecting data on two pregnancies of the same women in 2009–2019. The association between annual BMI gain and GDM during the subsequent pregnancy was examined.ResultsThis study included 1,640 pregnant women. A history of GDM [adjusted odds ratio (aOR), 26.22; 95% confidence interval (CI), 14.93–46.07] and annual BMI gain (aOR, 1.48; 95% CI, 1.22–1.81) were related to GDM during the subsequent pregnancy. In the women with a pre-pregnant BMI of

Gestational diabetes mellitus (GDM) refers to different degrees of glucose tolerance abnormalities that occur during pregnancy or are discovered for the first time, which can have a serious impact on the mother and the offspring. The screening of GDM mainly relies on the oral glucose tolerance test (OGTT) at 24–28 weeks of gestation. The early diagnosis and intervention of GDM can greatly improve adverse pregnancy outcomes. However, molecular markers for early prediction and diagnosis of GDM are currently lacking. Therefore, looking for GDM-specific early diagnostic markers has important clinical significance for the prevention and treatment of GDM and the management of subsequent maternal health. Circular RNA (circRNA) is a new type of non-coding RNA. Recent studies have found that circRNAs were involved in the occurrence and development of malignant tumors, metabolic diseases, cardiovascular and cerebrovascular diseases, etc., and could be used as the molecular marker for early diagnosis. Our previous research showed that circRNAs are differentially expressed in serum of GDM pregnant women in the second and third trimester, placental tissues during cesarean delivery, and cord blood. However, the mechanism of circular RNA in GDM still remains unclear. This article focuses on related circRNAs involved in insulin resistance and β-cell dysfunction, speculating on the possible role of circRNAs in the pathophysiology of GDM under the current research context, and has the potential to serve as early molecular markers for the diagnosis of GDM.

Gestational diabetes mellitus (GDM) is a high-risk pregnancy complication that is associated with metabolic disorder phenotypes, such as abnormal blood glucose and obesity. The link between microbiota and diet management contributes to metabolic homeostasis in GDM. Therefore, it is crucial to understand the structure of the gut microbiota in GDM and to explore the effect of dietary management on the microbiota structure. In this study, we analyzed the composition of the gut microbiota between 27 GDM and 30 healthy subjects at two time points using Illumina HiSeq 2500 platform. The taxonomy analyses suggested that the overall bacteria clustered by diabetes status, rather than diet intervention. Of particular interest, the phylum Acidobacteria in GDM was significantly increased, and positively correlated with blood glucose levels. Moreover, Partial least-squares discriminant analysis (PLS-DA) revealed that certain genera in the phyla Firmicutes, Bacteroidetes, Proteobacteria, and Lentisphaerae characterized the GDM gut microbiota. Correlation analysis indicated that blood glucose levels and BMI index were correlated with the relative abundance of SCFAS-producing genera. Through the comparison between the GDM and healthy samples with or without diet intervention, we discovered that the role of short-term diet management in GDM processes is associated with the change in the Firmicutes/Bacteroidetes ratio and some specific taxa, rather than an alternative gut microbial pattern. Our study have important implications for understanding the beneficial effects of diet intervention on the specific gut microbiota and thus possibly their metabolism in pregnant women with GDM.

Gestational diabetes mellitus (GDM) is a high-risk pregnancy complication that is associated with metabolic disorder phenotypes, such as abnormal blood glucose and obesity. The link between microbiota and diet management contributes to metabolic homeostasis in GDM. Therefore, it is crucial to understand the structure of the gut microbiota in GDM and to explore the effect of dietary management on the microbiota structure. In this study, we analyzed the composition of the gut microbiota between 27 GDM and 30 healthy subjects at two time points using Illumina HiSeq 2500 platform. The taxonomy analyses suggested that the overall bacteria clustered by diabetes status, rather than diet intervention. Of particular interest, the phylum Acidobacteria in GDM was significantly increased, and positively correlated with blood glucose levels. Moreover, Partial least-squares discriminant analysis (PLS-DA) revealed that certain genera in the phyla Firmicutes, Bacteroidetes, Proteobacteria , and Lentisphaerae characterized the GDM gut microbiota. Correlation analysis indicated that blood glucose levels and BMI index were correlated with the relative abundance of SCFAS-producing genera. Through the comparison between the GDM and healthy samples with or without diet intervention, we discovered that the role of short-term diet management in GDM processes is associated with the change in the Firmicutes/Bacteroidetes ratio and some specific taxa, rather than an alternative gut microbial pattern. Our study have important implications for understanding the beneficial effects of diet intervention on the specific gut microbiota and thus possibly their metabolism in pregnant women with GDM. [ABSTRACT FROM AUTHOR]

Background: Previous evidence indicates that birth season is associated with type 2 diabetes in adults. However, information on the association of birth with gestational diabetes mellitus (GDM) is lacking. The present study explores the association between birth seasonality and GDM in East China. Methods: This retrospective cohort study was conducted at the International Peace Maternal and child health hospital between 2014 and 2019. A total of 79, 292 pregnant women were included in the study after excluding participants with previous GDM, stillbirth, polycystic ovary syndrome, and lack of GDM laboratory records. The multivariate logistic regression model was employed to estimate the odds ratio and 95% confidence interval. After log transformation of blood glucose level, the percentage change and 95% confidence interval were estimated by a multivariate linear model. Results: The risk of GDM among pregnant women born in spring, autumn, and winter was not significantly different compared to that among participants born in summer. Pregnant women born in autumn had significantly higher 1-hour postprandial blood glucose (PBG-1h) and 2-hour postprandial blood glucose (PBG-2h) levels than pregnant women born in summer. Compared to pregnant women born in August, the PBG-1h level of pregnant women born in October, November, and December increased significantly, whereas the PBG-2h levels of pregnant women born in November and December increased significantly. Conclusion: Pregnant women born in autumn exhibit higher postprandial blood glucose levels during pregnancy than in those born in summer. The findings provide evidence that exposure to seasonal changes in early life may influence blood glucose metabolism during pregnancy. [ABSTRACT FROM AUTHOR]

Background: Gestational Diabetes Mellitus (GDM) is defined as the type of hyperglycemia diagnosed for the first-time during pregnancy, presenting with intermediate glucose levels between normal levels for pregnancy and glucose levels diagnostic of diabetes in the non-pregnant state. We aimed to systematically review and meta-analyze studies of prevalence of GDM in European countries at regional and sub-regional levels, according to age, trimester, body weight, and GDM diagnostic criteria. Methods: Systematic search was conducted in five databases to retrieve studies from 2014 to 2019 reporting the prevalence of GDM in Europe. Two authors have independently screened titles and abstracts and full text according to eligibility using Covidence software. A random-effects model was used to quantify weighted GDM prevalence estimates. The National Heart, Lung, and Blood Institute criteria was used to assess the risk of bias. Results: From the searched databases, 133 research reports were deemed eligible and included in the meta-analysis. The research reports yielded 254 GDM-prevalence studies that tested 15,572,847 pregnant women between 2014 and 2019. The 133 research reports were from 24 countries in Northern Europe (44.4%), Southern Europe (27.1%), Western Europe (24.1%), and Eastern Europe (4.5%). The overall weighted GDM prevalence in the 24 European countries was estimated at 10.9% (95% CI: 10.0–11.8, I2 : 100%). The weighted GDM prevalence was highest in the Eastern Europe (31.5%, 95% CI: 19.8–44.6, I2 : 98.9%), followed by in Southern Europe (12.3%, 95% CI: 10.9–13.9, I2 : 99.6%), Western Europe (10.7%, 95% CI: 9.5–12.0, I2 : 99.9%), and Northern Europe (8.9%, 95% CI: 7.9–10.0, I2 : 100). GDM prevalence was 2.14-fold increased in pregnant women with maternal age ≥30 years (versus 15-29 years old), 1.47-fold if the diagnosis was made in the third trimester (versus second trimester), and 6.79- fold in obese and 2.29-fold in overweight women (versus normal weight). Conclusions: In Europe, GDM is significant in pregnant women, around 11%, with the highest prevalence in pregnant women of Eastern European countries (31.5%). Findings have implications to guide vigilant public health awareness campaigns about the risk factors associated with developing GDM. Systematic Review Registration: PROSPERO [ https://www.crd.york.ac.uk/PROSPERO/ ], identifier CRD42020161857. [ABSTRACT FROM AUTHOR]

BackgroundPrevious evidence indicates that birth season is associated with type 2 diabetes in adults. However, information on the association of birth with gestational diabetes mellitus (GDM) is lacking. The present study explores the association between birth seasonality and GDM in East China.MethodsThis retrospective cohort study was conducted at the International Peace Maternal and child health hospital between 2014 and 2019. A total of 79, 292 pregnant women were included in the study after excluding participants with previous GDM, stillbirth, polycystic ovary syndrome, and lack of GDM laboratory records. The multivariate logistic regression model was employed to estimate the odds ratio and 95% confidence interval. After log transformation of blood glucose level, the percentage change and 95% confidence interval were estimated by a multivariate linear model.ResultsThe risk of GDM among pregnant women born in spring, autumn, and winter was not significantly different compared to that among participants born in summer. Pregnant women born in autumn had significantly higher 1-hour postprandial blood glucose (PBG-1h) and 2-hour postprandial blood glucose (PBG-2h) levels than pregnant women born in summer. Compared to pregnant women born in August, the PBG-1h level of pregnant women born in October, November, and December increased significantly, whereas the PBG-2h levels of pregnant women born in November and December increased significantly.ConclusionPregnant women born in autumn exhibit higher postprandial blood glucose levels during pregnancy than in those born in summer. The findings provide evidence that exposure to seasonal changes in early life may influence blood glucose metabolism during pregnancy.

BackgroundGestational Diabetes Mellitus (GDM) is defined as the type of hyperglycemia diagnosed for the first-time during pregnancy, presenting with intermediate glucose levels between normal levels for pregnancy and glucose levels diagnostic of diabetes in the non-pregnant state. We aimed to systematically review and meta-analyze studies of prevalence of GDM in European countries at regional and sub-regional levels, according to age, trimester, body weight, and GDM diagnostic criteria.MethodsSystematic search was conducted in five databases to retrieve studies from 2014 to 2019 reporting the prevalence of GDM in Europe. Two authors have independently screened titles and abstracts and full text according to eligibility using Covidence software. A random-effects model was used to quantify weighted GDM prevalence estimates. The National Heart, Lung, and Blood Institute criteria was used to assess the risk of bias.ResultsFrom the searched databases, 133 research reports were deemed eligible and included in the meta-analysis. The research reports yielded 254 GDM-prevalence studies that tested 15,572,847 pregnant women between 2014 and 2019. The 133 research reports were from 24 countries in Northern Europe (44.4%), Southern Europe (27.1%), Western Europe (24.1%), and Eastern Europe (4.5%). The overall weighted GDM prevalence in the 24 European countries was estimated at 10.9% (95% CI: 10.0–11.8, I2: 100%). The weighted GDM prevalence was highest in the Eastern Europe (31.5%, 95% CI: 19.8–44.6, I2: 98.9%), followed by in Southern Europe (12.3%, 95% CI: 10.9–13.9, I2: 99.6%), Western Europe (10.7%, 95% CI: 9.5–12.0, I2: 99.9%), and Northern Europe (8.9%, 95% CI: 7.9–10.0, I2: 100). GDM prevalence was 2.14-fold increased in pregnant women with maternal age ≥30 years (versus 15-29 years old), 1.47-fold if the diagnosis was made in the third trimester (versus second trimester), and 6.79- fold in obese and 2.29-fold in overweight women (versus normal weight).ConclusionsIn Europe, GDM is significant in pregnant women, around 11%, with the highest prevalence in pregnant women of Eastern European countries (31.5%). Findings have implications to guide vigilant public health awareness campaigns about the risk factors associated with developing GDM.Systematic Review RegistrationPROSPERO [https://www.crd.york.ac.uk/PROSPERO/], identifier CRD42020161857.

Diabetes in pregnancy is associated with adverse pregnancy outcomes including preterm birth. Although the mechanisms leading to these pregnancy complications are still poorly understood, aberrant angiogenesis and endothelial dysfunction play a key role. FKBPL and SIRT-1 are critical regulators of angiogenesis, however, their roles in pregnancies affected by diabetes have not been examined before in detail. Hence, this study aimed to investigate the role of FKBPL and SIRT-1 in pre-gestational (type 1 diabetes mellitus, T1D) and gestational diabetes mellitus (GDM). Placental protein expression of important angiogenesis proteins, FKBPL, SIRT-1, PlGF and VEGF-R1, was determined from pregnant women with GDM or T1D, and in the first trimester trophoblast cells exposed to high glucose (25 mM) and varying oxygen concentrations [21%, 6.5%, 2.5% (ACH-3Ps)]. Endothelial cell function was assessed in high glucose conditions (30 mM) and following FKBPL overexpression. Placental FKBPL protein expression was downregulated in T1D (FKBPL; p

Diabetes in pregnancy is associated with adverse pregnancy outcomes including preterm birth. Although the mechanisms leading to these pregnancy complications are still poorly understood, aberrant angiogenesis and endothelial dysfunction play a key role. FKBPL and SIRT-1 are critical regulators of angiogenesis, however, their roles in pregnancies affected by diabetes have not been examined before in detail. Hence, this study aimed to investigate the role of FKBPL and SIRT-1 in pre-gestational (type 1 diabetes mellitus, T1D) and gestational diabetes mellitus (GDM). Placental protein expression of important angiogenesis proteins, FKBPL, SIRT-1, PlGF and VEGF-R1, was determined from pregnant women with GDM or T1D, and in the first trimester trophoblast cells exposed to high glucose (25 mM) and varying oxygen concentrations [21%, 6.5%, 2.5% (ACH-3Ps)]. Endothelial cell function was assessed in high glucose conditions (30 mM) and following FKBPL overexpression. Placental FKBPL protein expression was downregulated in T1D (FKBPL; p<0.05) whereas PlGF/VEGF-R1 were upregulated (p<0.05); correlations adjusted for gestational age were also significant. In the presence of GDM, only SIRT-1 was significantly downregulated (p<0.05) even when adjusted for gestational age (r=-0.92, p=0.001). Both FKBPL and SIRT-1 protein expression was reduced in ACH-3P cells in high glucose conditions associated with 6.5%/2.5% oxygen concentrations compared to experimental normoxia (21%; p<0.05). FKBPL overexpression in endothelial cells (HUVECs) exacerbated reduction in tubule formation compared to empty vector control, in high glucose conditions (junctions; p<0.01, branches; p<0.05). In conclusion, FKBPL and/or SIRT-1 downregulation in response to diabetic pregnancies may have a key role in the development of vascular dysfunction and associated complications affected by impaired placental angiogenesis. [ABSTRACT FROM AUTHOR]

Gestational diabetes mellitus (GDM) is defined as glucose intolerance with onset or first recognition in the second or third trimester of pregnancy. GDM has a considerable impact on health outcomes of the mother and offspring during pregnancy, delivery, and beyond. Although the exact mechanism regarding GDM remains unclear, numerous studies have suggested that non-coding RNAs, including long non-coding (lnc)RNAs, microRNAs, and circular RNAs, were involved in the pathogenesis of GDM in which they played vital regulatory roles. Additionally, several studies have revealed that extracellular vehicles also participated in the pathogenesis of GDM, highlighting their important role in this disease. Considering the lack of effective biomarkers for the early identification of and specific treatment for GDM, non-coding RNAs and extracellular vehicles may be promising biomarkers and even targets for GDM therapies. This review provides an update on our understanding of the role of non-coding RNAs and extracellular vehicles in GDM. As our understanding of the function of lncRNAs and extracellular vehicles improves, the future appears promising for their use as potential biomarkers and treatment targets for GDM in clinical practice.

BackgroundThe association of complications of pregnancy and the risk of developing gynecological cancer is controversial with the limited study. In this study, we investigated the association of preeclampsia, or gestational diabetes mellitus (GDM), or large for gestational age (LGA), or intrauterine growth restriction (IUGR) and the risk of endometrial or ovarian cancer.MethodsIn this case-control study, 189 women with endometrial cancer and 119 women with ovarian cancer were included. 342 women without gynecological cancers were randomly selected as a control group. Data on the history of pregnancy and age at diagnosis of gynecological cancer as well as the use of intrauterine devices (IUDs) were collected.ResultsWomen with a history of preeclampsia or IUGR did not have an increased risk of developing endometrial or ovarian cancer. While women with a history of GDM or with the delivery of LGA infant increased the risk of developing endometrial cancer but not ovarian cancer. The odds of women with a history of GDM or with the delivery of LGA infant developing endometrial cancer was 2.691 (95% CI: 1.548, 4.3635, p=0.0003), or 6.383 (95% CI: 2.812, 13.68, p

Spatial variation in community composition may be driven by a variety of processes, including environmental filtering and dispersal limitation. While work has been conducted on the relative importance of these processes on various taxa and at varying resolutions, tests using high-resolution empirical data across large spatial extents are sparse. Here, we use a dataset on the presence/absence of breeding bird species collected at the 10 km × 10 km scale across the whole of Britain. Pairwise spatial taxonomic and functional beta diversity, and the constituent components of each (turnover and nestedness/richness loss or gain), were calculated alongside two other measures of functional change (mean nearest taxon distance and mean pairwise distance). Predictor variables included climate and land use measures, as well as a measure of elevation, human influence, and habitat diversity. Generalized dissimilarity modeling was used to analyze the contribution of each predictor variable to variation in the different beta diversity metrics. Overall, we found that there was a moderate and unique proportion of the variance explained by geographical distance per se, which could highlight the role of dispersal limitation in community dissimilarity. Climate, land use, and human influence all also contributed to the observed patterns, but a large proportion of the explained variance in beta diversity was shared between these variables and geographical distance. However, both taxonomic nestedness and functional nestedness were uniquely predicted by a combination of land use, human influence, elevation, and climate variables, indicating a key role for environmental filtering. These findings may have important conservation implications in the face of a warming climate and future land use change.