[Gestational diabetes mellitus (Update 2019)]

TGFβ1, SNAIL2, and PAPP-A Expression in Placenta of Gestational Diabetes Mellitus Patients

Background: Gestational diabetes mellitus (GDM) is a pregnancy-related diabetic condition that may cause serious complications. However, its pathogenesis remains unclear. Placental damage due to GDM may lead to several health issues that cannot be ignored. Thus, we aimed to identify the mechanisms underlying GDM by screening differentially expressed genes (DEGs) related to vascular endothelial cells in the GDM databases and verify the expression of these DEGs in the placentas of women afflicted by GDM. Methods: We used GDM microarray datasets integrated from the Gene Expression Omnibus (GEO) database. Functional annotation and protein-protein interaction (PPI) analyses were used to screen DEGs. Placental tissues from 20 pregnant women with GDM and 20 healthy pregnant women were collected, and differential gene expression in the placental tissues was verified via qRT-PCR, western blotting, and immunofluorescence. Results: Bioinformatics analysis revealed three significant DEGs: SNAIL2, PAPP-A, and TGFβ1. These genes were all predicted to be underexpressed in patients with GDM. The results of qRT-PCR, western blot, and immunofluorescence analyses indicated that SNAIL2 and PAPP-A in the placenta tissue of patients with GDM were significantly underexpressed. However, TGFβ1 in the placenta tissues of GDM was significantly overexpressed. Conclusion: SNAIL2, TGFβ1, and PAPP-A may affect the placentas of pregnant women with GDM, warranting further investigation.

iTRAQ proteomics analysis of placental tissue with gestational diabetes mellitus

BACKGROUND

Gestational diabetes mellitus is an endocrine and metabolic disorder that appears for the first time during pregnancy and causes varying degrees of short- and/or long-term effects on the mother and child. The etiology of the disease is currently unknown and isobaric tags for relative and absolute quantitation proteomics approach, the present study attempted to identify potential proteins in placental tissues that may be involved in the pathogenesis of GDM and adverse foetal pregnancy outcomes.

METHODS

Pregnant women with GDM hospitalised were selected as the experimental group, and pregnant women with normal glucose metabolism as the control group. The iTRAQ protein quantification technology was used to screen the differentially expressed proteins between the GDM group and the normal control group, and the differentially expressed proteins were analysed by GO, KEGG, PPI, etc., and the key proteins were subsequently verified by western blot.

RESULTS

Based on the proteomics of iTRAQ, we experimented with three different samples of placental tissues from GDM and normal pregnant women, and the total number of identified proteins were 5906, 5959, and 6017, respectively, which were similar in the three different samples, indicating that the results were reliable. Through the Wayne diagram, we found that the total number of proteins coexisting in the three groups was 4475, and 91 differential proteins that could meet the quantification criteria were strictly screened, of which 32 proteins were up-regulated and 59 proteins were down-regulated. By GO enrichment analysis, these differential proteins are widely distributed in extracellular membrane-bounded organelle, mainly in extracellular exosome, followed by intracellular vesicle, extracellular organelle. It not only undertakes protein binding, protein complex binding, macromolecular complex binding, but also involves molecular biological functions such as neutrophil degranulation, multicellular organismal process, developmental process, cellular component organization, secretion, regulated exocytosis. Through the analysis of the KEGG signaling pathway, it is found that these differential proteins are mainly involved in HIF-1 signaling pathway, Glycolysis/Gluconeogenesis, Central carbon metabolism in cancer, AMPK signaling pathway, Proteoglycans in cancer, Protein processing in endoplasmic reticulum, Thyroid cancer, Alcoholism, Glucagon signaling pathway.

DISCUSSION

This preliminary study helps us to understand the changes in the placental proteome of GDM patients, and provides new insights into the pathophysiology of GDM.

Lipids, apolipoproteins and gestational diabetes mellitus: a Mendelian randomization study

BACKGROUND

This study investigates the causal relationship between lipid traits and GDM in an effort to better understand the aetiology of GDM.

METHODS

Employing a two-sample Mendelian Randomization (MR) framework, we used Single Nucleotide Polymorphisms (SNPs) as instrumental variables to examine the impact of lipids and apolipoproteins on GDM. The research comprised univariable and multivariable MR analyses, with a prime focus on individual and combined effects of lipid-related traits. Statistical techniques included the fixed-effect inverse variance weighted (IVW) method and supplementary methods such as MR-Egger for comprehensive assessment.

RESULTS

Our findings revealed the following significant associations: apoA-I and HDL cholesterol were inversely correlated with GDM risk, while triglycerides showed a positive correlation. In multivariable analysis, apoA-I consistently exhibited a strong causal link with GDM, even after adjusting for other lipids and Body Mass Index (BMI).

CONCLUSION

The study demonstrates a significant causal relationship between apoA-I and GDM risk.

Establishment and validation of a prediction model for gestational diabetes

AIM

To develop a visual prediction model for gestational diabetes (GD) in pregnant women and to establish an effective and practical tool for clinical application.

METHODS

To establish a prediction model, the modelling set included 1756 women enrolled in the Zunyi birth cohort, the internal validation set included 1234 enrolled women, and pregnant women in the Wuhan cohort were included in the external validation set. We established a demographic-lifestyle factor model (DLFM) and a demographic-lifestyle-environmental pollution factor model (DLEFM) based on whether the women were exposed to environmental pollutants. The least absolute shrinkage and selection lasso-logistic regression analyses were used to identify the independent predictors of GD and construct a nomogram for predicting its occurrence.

RESULTS

The DLEFM regression analysis showed that a family history of diabetes (odd ratio [OR] 2.28; 95% confidence interval [CI] 1.05-4.71), a history of GD in pregnant women (OR 4.22; 95% CI 1.89-9.41), being overweight or obese before pregnancy (OR 1.71; 95% CI 1.27-2.29), a history of hypertension (OR 2.61; 95% CI 1.41-4.72), sedentary time (h/day) (OR 1.16; 95% CI 1.08-1.24), monobenzyl phthalate (OR 1.95; 95% CI 1.45-2.67) and Q4 mono-ethyl phthalate concentration (OR 1.85; 95% CI 1.26-2.73) were independent predictors. The area under the receiver operating curves for the internal validation of the DLEFM and the DLFM constructed using these seven factors was 0.827 and 0.783, respectively. The calibration curve of the DLEFM was close to the diagonal line. The DLEFM was thus the more optimal model, and the one which we chose.

CONCLUSIONS

A nomogram based on preconception factors was constructed to predict the occurrence of GD in the second and third trimesters. It provided an effective tool for the early prediction and timely management of GD.

Clinical Value of Circ-PNPT1 on Adverse Pregnancy Outcomes of Patients with Gestational Diabetes Mellitus

OBJECTIVE

Several circular RNAs are associated with important pathophysiological characteristics of gestational diabetes mellitus (GDM). This study intended to measure the expression of circ-PNPT1 in sera of GDM patients and to expound on its values on pregnancy outcomes.

METHODS

Totally 104 GDM patients and 71 healthy controls were recruited. The expression pattern of serum circ-PNPT1 was measured by reverse transcription-quantitative polymerase chain reaction. The diagnostic efficacy of circ-PNPT1 and fasting blood glucose (FBG) on GDM was evaluated by receiver operating characteristic (ROC) analysis. Parameters of glycolipid metabolism were determined using automatic biochemical analyzers. The correlation between circ-PNPT1 and glycolipid metabolism parameters was analyzed using Pearson analysis. GDM patients were divided into a high expression group and a low expression group based on the median value of circ-PNPT1 expression. Curves of adverse neonatal outcomes were drawn by Log Rank analysis.

RESULTS

GDM patients exhibited higher circ-PNPT1 expression than healthy controls. The area under the ROC curve of circ-PNPT1 diagnosing GDM was 0.9184 and the cut-off value was 1.435 (90.38% sensitivity, 85.92% specificity). Serum circ-PNPT1 expression was positively correlated with FBG, total cholesterol, and triglyceride in GDM patients. Neonates born to GDM patients with high circ- PNPT1 expression were prone to adverse outcomes.

CONCLUSION

Circ-PNPT1 was highly-expressed in the sera of GDM patients. Circ-PNPT1 affected glycolipid metabolism and its expression had certain reference values on adverse pregnancy outcomes.

Correlation between PAPP-A serum levels in the first trimester of pregnancy with the occurrence of gestational diabetes, a multicenter cohort study

OBJECTIVE

This study aimed to investigate the association between first-trimester Pregnancy-associated plasma protein A (PAPP-A) levels and subsequent gestational diabetes mellitus (GDM) development.

METHOD

The study was conducted on 5854 pregnant women who attended routine prenatal care. Maternal biomarkers, including PAPP-A and free beta hCG, were measured for all women in a referral laboratory and converted to MoM values. Pregnant women were divided into two groups, based on the serum concentration of PAPP-A, (PAPP-A > 0.4 (normal) and PAPP-A < 0.4 (low)). Data on the screening test for GDM and pregnancy outcomes were collected and analyzed with appropriate tests.

RESULT

Of the 5854 pregnant women, 889 (15.19%) developed GDM. The maternal PAPP-A MoM concentrations were significantly lower in GDM cases compared to controls. Indeed, gestational age at delivery and birth weight were significantly lower (p < 0.001) in PAPP-A MoM < 0.4, and the rate of intrauterine growth restriction (IUGR) was significantly higher (p < 0.001). ROC analysis revealed that the sensitivity and specificity of MoM concentration for predicting GDM were 53.3% and 51.9%, respectively.

CONCLUSION

Lower maternal PAPP-A in early pregnancy can lead to glucose intolerance and increase the risk of subsequent GDM development. In addition, decreased serum concentration of PAPP-A is significantly correlated to lower birth weight and IUGR.

Association between fetal liver diameter and glycemic control in pregnant women with gestational diabetes: A pilot study

BACKGROUND

This study aimed to investigate the relationship between fetal liver length (FLL) and maternal glycemic status in pregnant women with gestational diabetes mellitus (GDM), as well as to determine whether FLL measurement in the third trimester is associated with neonatal outcomes.

METHOD

A total of 51 singleton GDM pregnancies were included in this pilot study, and transabdominal ultrasound biometry and FLL measurements were performed between 34 and 36 weeks of gestation. Maternal indicators of glycemic control, including hemoglobin A1C (HbA1C), fasting blood sugar (FBS), and 2-h postprandial blood sugar were also evaluated during this period. The cases were followed up until delivery and maternal and neonatal outcomes were assessed to determine any correlation with FLL.

RESULT

The results showed a significant positive correlation between FLL and HbA1C (r = 0.464, P = 0.001), FBS (r = 0.574, P < 0.001), 2-h postprandial blood sugar (r = 0.405, P = 0.002), and AC (r = 0.515, P < 0.001). Additionally, FLL was significantly associated with fetal birth weight (r = 0.408, P = 0.003) and birth weight (r = 0.460, P = 0.001). The FLL≥95th percentile group demonstrated a higher number of polyhydramnios (p = 0.007), macrosomia (p < 0.001), and maternal intensive care unit (ICU) admissions (p = 0.006).

CONCLUSION

In conclusion, FLL measurement during third trimester of pregnancy is an indicator of maternal glycemic regulation and can be used as a predictor of macrosomia and neonatal birth weight in GDM pregnancies.

Long-term effects of streptozotocin-induced gestational diabetes mellitus on mechanical sensitivity and intraepidermal nerve fibers in female and male mice offspring

While the long-term complications of gestational diabetes mellitus (GDM) in the cardiovascular, endocrine, and central nervous systems from offspring have been widely studied, less is known about the long-term outcomes of GDM on the peripheral nervous system. Thus, here we assessed the mechanical sensitivity and density of nerve fibers of the hind paw from middle-aged offspring born from dams with GDM. GDM was induced by the intraperitoneal administration of streptozotocin (STZ) in mouse dams. Mechanical sensitivity in male and female offspring was bi-weekly evaluated from week 18 to week 40 of age. At 40 weeks old, offspring were sacrificed and glabrous hind paw skin was processed for immunohistochemistry to determine the density of intraepidermal CGRP and PGP9.5 positive nerve fibers. Offspring mice born from STZ-treated dams had significantly greater mechanical sensitivity from 18 to 40 weeks of age compared to offspring born from vehicle-treated dams (control group). The density of intraepidermal CGRP+ and PGP9.5+ nerve fibers were significantly lower in the hind paw skin of female but not male offspring, born from STZ-treated dams versus the control group. These results suggest that GDM has long-term sex-dependent complications on the nociceptive system. Further studies are necessary to elucidate the mechanisms underlying the GDM-induced long-term consequences.

Vitamin E Supplement Protects Against Gestational Diabetes Mellitus in Mice Through nuclear factor-erythroid factor 2-related factor 2/heme oxygenase-1 Signaling Pathway

Background

Gestational diabetes mellitus (GDM) is the most common pregnant disorder worldwide. In this study, we aimed to explore whether vitamin E (VE) treatment alone could protect against GDM in a mouse model.

Methods

6-week-old C57BL/6J female mice were fed on high-fat diet for two weeks and continued with high-fat diet after pregnancy to induce GDM. The pregnant mice were orally administrated with 2.5, 25 or 250 mg/kg VE twice per day during pregnancy together with high-fat diet. Oral glucose tolerance test, insulin amounts, oxidative stress and inflammation were then measured.

Results

Only 250 mg/kg VE could improve glucose tolerance and insulin level in pregnant mice. VE (250 mg/kg) effectively inhibited GDM-induced hyperlipidemia, and secretion of inflammatory cytokines such as tumor necrosis factor-α and interleukin-6. VE also significantly ameliorated maternal oxidative stress at the late stage of pregnancy, and also improved reproductive outcomes, including increasing the litter size and birth weight in GDM mice. Moreover, VE also activated GDM-reduced nuclear factor-erythroid factor 2-related factor 2 (Nrf2) / heme oxygenase-1 signaling pathway in the maternal liver tissues of GDM mice.

Conclusion

Our data clearly demonstrated that 250 mg/kg VE twice a day during pregnancy could significantly ameliorate the symptoms of GDM by alleviating oxidative stress, inflammation, hyperglycemia, and hyperlipidemia through Nrf2/HO-1 signaling pathway in GDM mice. Thus, additional VE supplement might be beneficial to GDM.

Clinical implications of the 100-g oral glucose tolerance test in the third trimester

PURPOSE

The clinical implications of gestational diabetes mellitus (GDM) diagnosed in the third trimester are not well established and controversy continues regarding the performance of diagnostic tests beyond 28-week gestation. This study aimed to evaluate the incidence of abnormal third trimester oral glucose tolerance test (OGTT) results in women at high risk and to compare the obstetric and neonatal outcomes with those of women with normal OGTT results.

METHODS

The study included 372 women who completed late (>29 weeks) 100-g OGTT due to suspected fetal macrosomia, polyhydramnios or a personal risk factor for GDM, diagnosed according to the Carpenter & Coustan criteria. Women with only one abnormal OGTT value were diagnosed with GDM by abnormal glucose follow-up and analyzed separately. Obstetric and neonatal outcomes were compared between the GDM and the non-GDM groups.

RESULTS

GDM was diagnosed in 85/372 (22%) women, including 35 (59.3%) women with one abnormal OGTT value who were later diagnosed with GDM. Of 200 women who had a normal 1-h 50-g glucose challenge test at 24-28 weeks, late GDM was diagnosed in 33 (16.5%). Seventy-six (89.5%) of those with GDM were treated by dietary therapy and 9 (10.5%) by pharmacological therapy. Among women with GDM, large-for-gestational-age fetuses, labor induction and elective cesarean section were more prevalent than for those without GDM. Significant differences were not found between the groups in macrosomia and neonatal outcomes.

CONCLUSIONS

The performance of OGTT in women with risk factors during the third trimester should be considered following further prospective trials.

[Diabetes mellitus: definition, classification, diagnosis, screening and prevention (Update 2023)]

Diabetes mellitus comprises of a group of heterogeneous disorders, which have an increase in blood glucose concentrations in common. The current classification for diabetes mellitus is presented and the main features of type 1 and type 2 diabetes are compared. Furthermore, the criteria for the correct biochemical diagnosis during fasting and oral glucose tolerance tests as well as the use of hemoglobin A1c (HbA1c) are summarized. The increasing prevalence of diabetes requires targeted screening for detecting diabetes and prediabetes in risk groups. This forms the basis for the early initiation of measures to prevent the onset of diabetes in these risk groups and to delay the progression of diabetes.

Construction of the experimental rat model of gestational diabetes

Objective

Numerous methods for modeling gestational diabetes mellitus (GDM) in rats exist. However, their repeatability and stability are unclear. This study aimed to compare the effects of high-fat and high-sugar (HFHS) diet, HFHS diet combined with streptozotocin (STZ) administration, and HFHS diet combined with movement restriction (MR) modeling methods on rat models to confirm the best method for constructing a rat model of GDM.

Method

Forty female Sprague-Dawley rats were randomly divided into four groups (n = 10): the normal control (NC), HFHS, HFHS+STZ, and HFHS+MR groups. The rats in the NC group were fed with a standard diet, and those in the remaining groups were fed with a HFHS diet. The rats in the HFHS+STZ group received 25 mg/kg STZ on their first day of pregnancy, and those in the HFHS+MR group were subjected to MR during pregnancy. Bodyweight, food intake, water intake, fasting blood glucose (FBG), fasting insulin (FINS), homeostasis model assessment of insulin resistance (HOMA-IR), homeostasis model assessment of insulin sensitivity (HOMA-IS), homeostasis model assessment of β-cell function, pancreatic and placental morphology, and the expression levels of glucose transporter 1 (GLUT1) and glucose transporter 3 (GLUT3) in placentas were then quantified. Moreover, iTRAQ was used to identify placental proteomics.

Results

During pregnancy, the rats in the HFHS+STZ group showed FBG levels that were kept stable in a state of moderate hyperglycemia; the typical GDM symptoms of polydipsia, polyphagia, polyuria, and increased body weight; and the modeling rate of 87.5%. On the first and 19th days of pregnancy, the rats in the HFHS group showed higher FBG than that of the NC group, increasing body weight and food intake and the modeling rate of 50%. On the 19th day of pregnancy, the FBG of the rats in the HFHS+MR group was higher than that of the rats in the NC group, and the modeling rate of 42.9%. Comparison with the NC group revealed that the three modeling groups exhibited increased FINS and HOMA-IR, decreased HOMA-IS, and different degrees of pathological changes in pancreases and placentas. Among the groups, the HFHS+STZ group displayed the greatest changes with significant reductions in the numbers of pancreatic and placental cells and appeared cavitation. The expression levels of GLUT1 and GLUT3 in the placentas of the HFHS+STZ and HFHS+MR groups were higher than those in the placentas of the NC and HFHS groups. The above results indicated that the rats in the HFHS+STZ group showed the best performance in terms of modeling indicators. After the changes in placental proteomics in the HFHS+STZ group were compared with those in the NC group, we found that in the HFHS+STZ group, five proteins were up-regulated and 18 were down-regulated; these proteins were enriched in estrogen signaling pathways.

Conclusion

HFHS combined with the intraperitoneal injection of 25 mg/kg STZ was the best modeling method for the nonspontaneous model of experimentally induced GDM, and its modeling rate was high. The pathological characteristics of the constructed GDM rat model were similar to those of human patients with GDM. Moreover, the model was stable and reliable. The modeling method can provide a basis for constructing a GDM rat model for subsequent research on the prevention and treatment of GDM.

Vitamin D Deficiency During the First Trimester of Pregnancy and the Risk of Developing Gestational Diabetes Mellitus

OBJECTIVE

To investigate the relationships among various factors that affect serum vitamin D levels and vitamin D in the first trimester and the risk of developing gestational diabetes mellitus (GDM).

DESIGN

A prospective cohort design.

SETTING

The family health center of Ankara, Turkey.

PARTICIPANTS

Out of 889 pregnant women who participated in the study in the first trimester (6-13 weeks gestation), 814 participated in GDM screening in the second trimester (24-28 weeks gestation).

METHODS

We determined serum vitamin D levels, demographic data, various biochemical and anthropometric parameters, and factors that affect vitamin D synthesis of participants in the first trimester and used logistic regression analysis to analyze the effects of the associations among vitamin D deficiency and the other variables on the occurrence of GDM.

RESULTS

Vitamin D deficiency in the first trimester was present in 425 (82.5%) participants. In the second trimester, 198 participants (24.3%) were diagnosed with GDM through oral glucose tolerance test screening. We detected GDM in the second trimester in 5.7% of participants who had vitamin D deficiency in the first trimester. Even after adjustment for vitamin D intake, clothing style, and duration of exposure to the sun, the risk of GDM was significantly greater in participants who were vitamin D deficient than those who were not deficient. The risk of GDM among women with vitamin D deficiency was sustained or increased significantly after we adjusted for age, parity, prepregnancy body mass index, history of diabetes, triglyceride levels, vitamin D intake, clothing style, and length of sun exposure, OR = 10.60, p < .001, 95% confidence interval [2.82, 39.76].

CONCLUSIONS

Our results suggest that vitamin D deficiency in the first trimester may significantly increase the risk of developing GDM.

Delivery, maternal and neonatal outcomes in nulliparous women with gestational diabetes undergoing epidural labour analgesia: a propensity score-matched analysis

OBJECTIVE

This study aimed to retrospectively analyse the influence of epidural labour analgesia (ELA) on delivery and maternal and neonatal outcomes in nulliparous women with gestational diabetes mellitus (GDM) using propensity score-matched analysis.

DESIGN

Retrospective cohort analysis.

SETTING

Primary care practices in a teaching hospital from March 2018 to October 2021.

PARTICIPANTS

A total of 816 delivery records of nulliparous women with GDM were collected and retrospectively analysed.

INTERVENTIONS

ELA and non-ELA (NELA) cohorts were assessed.

MAIN OUTCOME MEASURE

The primary outcome assessed was delivery type (spontaneous, assisted vaginal or caesarean). The secondary outcomes assessed included labour duration and maternal and neonatal outcomes.

RESULTS

A total of 137 propensity score-matched pairs of ELA and NELA patients were analysed. ELA was associated with a decreased rate of caesarean section (18.3% vs 46.0% in the ELA vs NELA cohort, respectively; p<0.05) and an increased occurrence of assisted vaginal delivery (35.8% vs 12.4% in the ELA vs NELA cohort, respectively; p<0.05). The duration of the first and total stages of labour was prolonged, the occurrence of postpartum fever increased, and the duration of hospital stay was shortened in those receiving ELA (all p<0.05). Additionally, neonatal birth weight, plasma glucose levels and neonatal macrosomia occurrence increased, while neonatal intensive care unit admissions and neonatal hypoglycaemia decreased in the ELA versus the NELA group (all p<0.05). With respect to other maternal and neonatal outcomes, both cohorts were similar.

CONCLUSIONS

The use of ELA decreases the rate of caesarean section and improves maternal and neonatal outcomes in nulliparous women with GDM.

TRIAL REGISTRATION NUMBER

ChiCTR-2000033091.

Molecular Docking and Dynamics Simulation of Natural Compounds from Betel Leaves (Piper betle L.) for Investigating the Potential Inhibition of Alpha-Amylase and Alpha-Glucosidase of Type 2 Diabetes

Piper betle L. is widely distributed and commonly used medicinally important herb. It can also be used as a medication for type 2 diabetes patients. In this study, compounds of P. betle were screened to investigate the inhibitory action of alpha-amylase and alpha-glucosidase against type 2 diabetes through molecular docking, molecular dynamics simulation, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The molecule apigenin-7-O-glucoside showed the highest binding affinity among 123 (one hundred twenty-three) tested compounds. This compound simultaneously bound with the two-target proteins alpha-amylase and alpha-glucosidase, with high molecular mechanics-generalized born surface area (MM/GBSA) values (ΔG Bind = -45.02 kcal mol^-1 for alpha-amylase and -38.288 for alpha-glucosidase) compared with control inhibitor acarbose, which had binding affinities of -36.796 kcal mol^-1 for alpha-amylase and -29.622 kcal mol^-1 for alpha-glucosidase. The apigenin-7-O-glucoside was revealed to be the most stable molecule with the highest binding free energy through molecular dynamics simulation, indicating that it could compete with the inhibitors' native ligand. Based on ADMET analysis, this phytochemical exhibited a wide range of physicochemical, pharmacokinetic, and drug-like qualities and had no significant side effects, making them prospective drug candidates for type 2 diabetes. Additional in vitro, in vivo, and clinical investigations are needed to determine the precise efficacy of drugs.

Early pregnancy hyperglycaemia as a significant predictor of large for gestational age neonates

AIMS

We aimed to determine the effect of early pregnancy hyperglycaemia on having a large for gestational age (LGA) neonate.

METHODS

A prospective cohort study was conducted among pregnant women in their first trimester. One-step plasma glucose (PG) evaluation procedure was performed to assess gestational diabetes mellitus (GDM) and diabetes mellitus (DM) in pregnancy as defined by the World Health Organization (WHO) criteria with International Association of Diabetes in Pregnancy Study Group (IADPSG) thresholds. The main outcome studied was large for gestational age neonates (LGA).

RESULTS

A total of 2,709 participants were recruited with a mean age of 28 years (SD = 5.4) and a median gestational age (GA) of eight weeks (interquartile range [IQR] = 2). The prevalence of GDM in first trimester (T1) was 15.0% (95% confidence interval [CI] = 13.7-16.4). Previously undiagnosed DM was detected among 2.5% of the participants. Out of 2,285 live births with a median delivery GA of 38 weeks (IQR = 3), 7.0% were LGA neonates. The cumulative incidence of LGA neonates in women with GDM and DM was 11.1 and 15.5 per 100 women, respectively. The relative risk of having an LGA neonate among women with DM and GDM was 2.30 (95% CI = 1.23-4.28) and 1.80 (95% CI = 1.27-2.53), respectively. The attributable risk percentage of a LGA neonate for hyperglycaemia was 15.01%. T1 fasting PG was significantly correlated with both neonatal birth weight and birth weight centile.

CONCLUSIONS

The proposed WHO criteria for hyperglycaemia in pregnancy are valid, even in T1, for predicting LGA neonates. The use of IADPSG threshold for Fasting PG, for risk assessment in early pregnancy in high-risk populations is recommended.

Early-Pregnancy Intermediate Hyperglycemia and Adverse Pregnancy Outcomes Among Women Without Gestational Diabetes

CONTEXT

Universal early-pregnancy screening for overt diabetes reveals intermediate hyperglycemia (fasting plasma glucose [FPG] [5.1-6.9 mM]).

OBJECTIVE

We evaluated the association between early-pregnancy intermediate hyperglycemia and adverse pregnancy outcomes among women without gestational diabetes.

METHODS

This retrospective cohort study was conducted at the Obstetrics and Gynecology Hospital, Shanghai, China, from 2013 to 2017. All singleton pregnancies with FPG less than or equal to 6.9 mM in early pregnancy and receiving a 75-g oral glucose tolerance test (OGTT) were included. Women with prepregnancy diabetes were excluded. Individuals with normal OGTT were analyzed. Pregnancy outcomes for FPG less than 5.1 mM and intermediate hyperglycemia were evaluated. The primary outcomes were large for gestational age (LGA) and primary cesarean delivery. Multivariate logistic regressions were conducted. Statistical significance was defined as P less than .05.

RESULTS

In total, 24 479 deliveries were included, of which 23 450 (95.8%) had normal OGTTs later in pregnancy (NGT). There were 807 (3.4%) women who had an FPG of 5.1 to 6.9 mM in early pregnancy. Compared to the NGT group with an FPG of less than 5.1 mM in early pregnancy (N = 20692), the intermediate hyperglycemia NGT group (N = 693) had a higher age and body mass index (BMI), and significantly higher rates of LGA, primary cesarean delivery, preterm birth, preeclampsia, and neonatal distress. The rates of primary cesarean delivery (adjusted odds ratio [AOR] 1.24; 95% CI, 1.05-1.45), preterm birth (AOR 1.75; 95% CI, 1.29-2.36), and neonatal distress (AOR 3.29; 95% CI, 1.57-6.89) remained statistically significantly higher after adjustments for maternal age, BMI, and other potential confounding factors.

CONCLUSION

Women with intermediate hyperglycemia in early pregnancy are at an increased risk for adverse maternal-fetal outcomes, even with normal future OGTTs.

Glypican-4 in pregnancy and its relation to glucose metabolism, insulin resistance and gestational diabetes mellitus status

Glypican-4 (GPC-4) is an adipokine that enhances insulin receptor signaling. Plasma concentrations were found to be elevated in patients with prediabetes but reduced in type 2 diabetes mellitus. No study on Glypican-4 in pregnancy and pregnancy-related insulin resistance has been published yet. GPC-4 levels were investigated in 59 overweight women throughout their pregnancy at the Medical University of Vienna. GPC-4 levels, fasting insulin, fasting glucose, estradiol, liver and renal parameters, and markers of bone development were assessed before the < 21st week of gestation (GW), and at GW 35-37. GPC-4 levels increased from < 21 GW (mean = 2.38 pg/ml, SD = 0.68 pg/ml) to GW 35-37 (mean = 2.96 pg/ml, SD = 0.77 pg/ml, p < 0.001). At the same time, GPC-4 levels correlated negatively with estimated glomerular filtration rate (eGFR), serum protein and serum albumin levels and were positively related to creatinine and uric acid levels at GW 35-37. Concerning glucose metabolism, GPC-4 levels were inversely related to ISSI-2, fasting insulin and HOMA-IR, however, not significantly different between women with normal glucose tolerance (NGT) and GDM (p = 0.239). In conclusion, GPC-4 levels rose significantly during pregnancy, correlated negatively with fasting insulin and HOMA-IR but might not be related to gestational diabetes mellitus status.

Relationships Among Pre-Pregnancy BMI, Gestational, and Postpartum Oral Glucose Tolerance Results in Women With Gestational Diabetes Mellitus

Background and Aims: To investigate the relationship among maternal demographic and clinical characteristics, gestational and postpartum oral glucose tolerance test (ppOGTT) results in patients with gestational diabetes mellitus (GDM). Methods: Patients with gestational diabetes mellitus from January 1, 2016, to August 31, 2019, were enrolled. General characteristics, dietary energy intake, pre-gestational body mass index (BMI), gestational oral glucose tolerance test (gOGTT), and 42 days ppOGTT results of all participants were collected. The relationships among maternal clinical characteristics, fasting glucose of gOGTT (gOGTT-FPG), 1 h postprandial glucose of gOGTT (gOGTT-1h PG), 2 h postprandial glucose of gOGTT (gOGTT-2h PG), and maternal postpartum glucose outcomes were evaluated. Results: A total of 156 patients with GDM were included in this study. Among them, 73.7% had inadequate daily total energy intake, an insufficient ratio of carbohydrates and protein, and an excessive fat ratio. Most of the patients (81.4%) were normal in their ppOGTT examination. Less than 20% of the patients (16.7%) were in the pre-diabetic situation, and 3 patients (1.9%) had diabetes. Pre-pregnancy BMI of patients with GDM was a risk factor for increased gOGTT-FPG levels. Those who were overweight before pregnancy had a greater risk for a higher gOGTT-FPG compared to those who had normal pre-pregnancy BMI (P = 0.021, odds ratio [OR] = 4.583). Abnormal gOGTT-2hPG was a risk factor for abnormal ppOGTT (P = 0.04). Those who had an elevated gOGTT-2hPG (≧8.5 mmol/L) had a 2.426 times higher risk for abnormal ppOGTT than those who had normal gOGTT-2hPG (<8.5 mmol/L) results. Conclusion: For women who are overweight before pregnancy, it is better to control their BMI to normal before getting pregnant. Women who had abnormal gOGTT-2h PG should pay more attention to the ppOGTT results.

Performance of early risk assessment tools to predict the later development of gestational diabetes

BACKGROUND

Several prognostic models for gestational diabetes mellitus (GDM) are provided in the literature; however, their clinical significance has not been thoroughly evaluated, especially with regard to application at early gestation and in accordance with the most recent diagnostic criteria. This external validation study aimed to assess the predictive accuracy of published risk estimation models for the later development of GDM at early pregnancy.

METHODS

In this cohort study, we prospectively included 1132 pregnant women. Risk evaluation was performed before 16 + 0 weeks of gestation including a routine laboratory examination. Study participants were followed-up until delivery to assess GDM status according to the IADPSG 2010 diagnostic criteria. Fifteen clinical prediction models were calculated according to the published literature.

RESULTS

Gestational diabetes mellitus was diagnosed in 239 women, that is 21.1% of the study participants. Discrimination was assessed by the area under the ROC curve and ranged between 60.7% and 76.9%, corresponding to an acceptable accuracy. With some exceptions, calibration performance was poor as most models were developed based on older diagnostic criteria with lower prevalence and therefore tended to underestimate the risk of GDM. The highest variable importance scores were observed for history of GDM and routine laboratory parameters.

CONCLUSIONS

Most prediction models showed acceptable accuracy in terms of discrimination but lacked in calibration, which was strongly dependent on study settings. Simple biochemical variables such as fasting glucose, HbA1c and triglycerides can improve risk prediction. One model consisting of clinical and laboratory parameters showed satisfactory accuracy and could be used for further investigations.

Early Pregnancy Glycemic Levels in Non-Diabetic Women and Pregnancy Outcome: A Retrospective Cross-Sectional Study

Background

Maternal fasting blood sugar (FBS) variations within normal range and lower than that in diabetes mellitus (DM) may be associated with adverse feto-maternal outcomes.

Objective

To find out if a rise of maternal FBS level above 80 but still below 120 mg/dL (group 2) has an influence on feto-maternal outcomes compared with a maternal FBS below 80 mg/dL (group 1).

Methods

Retrospective cross-sectional study. FBS was measured at the booking visit. Subjects whose FBS was measured before 20 weeks were categorized according to their FBS (>80 mg/dL or ≤80 mg/dL) and correlation between FBS levels in the two groups with several parameters were tested.

Results

Group 1 (130 healthy pregnant women) and group 2 (88 healthy pregnant women) did not show a statistical difference in age or BMI. More statistically significant cases were diagnosed with GDM in group 2 than in group 1 (39.8% vs 16.9%, P value 0.000). More cases that needed pharmacological intervention in the form of metformin or insulin or both were seen in group 2 than in group 1 (p value 0.007 and 0.061, respectively). More but not statistically significant polyhydramnios was seen more in group 2 than in group 1 (9.1% vs 3.1%, p value 0.056). There was no statistically significant difference between the 2 groups in relation to all other fetomaternal outcome parameters that were studied.

Conclusion

Raised maternal fasting blood glucose level (80–120 mg/dL) in healthy primigravid women in early pregnancy was associated with significant diagnosis of gestational diabetes mellitus and need for pharmacological intervention. An association was found with polyhydramnios but this was not statistically significant. No influence was found on preterm birth, fetal weight, mode of delivery or APGAR score. More attention should be given to FBS levels early in pregnancy to reduce the risk for later complications.

Characteristics of gestational diabetes subtypes classified by oral glucose tolerance test values

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.

Screening of postpartum diabetes in women with gestational diabetes: high-risk subgroups and areas for improvements-the STRONG observational study

AIMS

To assess the proportion of women with gestational diabetes (GDM) by performing postpartum Oral Glucose Tolerance Test (OGTT) and to identify GDM phenotypes at high-risk of postpartum dysglycemia (PPD).

METHODS

Observational, retrospective, multicenter study involving consecutive GDM women. Recursive partitioning (RECPAM) analysis was used to identify distinct and homogeneous subgroups of women at different PPD risk.

RESULTS

From a sample of 2,736 women, OGTT was performed in 941 (34.4%) women, of whom 217 (23.0%) developed PPD. Insulin-treated women having family history of diabetes represented the subgroup with the highest PPD risk (OR 5.57, 95% CI 3.60-8.63) compared to the reference class (women on diet with pre-pregnancy BMI <  = 28.1 kg/m2). Insulin-treated women without family diabetes history and women on diet with pre-pregnancy BMI > 28.1 kg/m2 showed a two-fold PPD risk. Previous GDM and socioeconomic status represent additional predictors. Fasting more than post-prandial glycemia plays a predictive role, with values of 81-87 mg/dl (4.5-4.8 mmol/l) (lower than the current diagnostic GDM threshold) being associated with PPD risk.

CONCLUSIONS

Increasing compliance to postpartum OGTT to prevent/delay PPD is a priority. Easily available characteristics identify subgroups of women more likely to benefit from preventive strategies. Fasting BG values during pregnancy lower than those usually considered deserve attention.

Resveratrol ameliorates the glucose uptake and lipid metabolism in gestational diabetes mellitus mice and insulin-resistant adipocytes via miR-23a-3p/NOV axis

BACKGROUND

Resveratrol improves insulin-resistance (IR) of gestational diabetes mellitus (GDM) mice. Low-expressed miR-23a-3p in diabetes patients regulates IR of adipocytes. Hence, we speculated the effect of Res on GDM mice was realized through regulating miR-23a-3p.

METHODS

The GDM model was established in mice by high-fat diet, treated with miR-23a-3p antagomiR, and further performed with glucose and insulin tolerance tests. The bodyweight, serum glucose and serum insulin, and the expressions of miR-23a-3p and nephroblastoma overexpressed (NOV) in mouse adipose tissues were detected. MiR-23a-3p target was identified by Starbase and dual-luciferase reporter. Then, an IR adipocyte model was established by dexamethasone-inducing and further treated with Resveratrol or transfected with miR-23a-3p inhibitor or siNOV. The cell glucose intake was detected by radioimmunoassay. The expressions of miR-23a-3p, NOV, Adiponectin, Leptin, p-PI3K, PI3K, p-Akt, and Akt in the adipocytes were determined by qPCR or Western blot.

RESULTS

Resveratrol decreased bodyweight, glucose level, insulin level, and the expressions of miR-23a-3p and NOV in the GDM mice, which was reversed by miR-23a-3p antagomiR. MiR-23a-3p targeted NOV. Resveratrol increased the glucose intake and the expressions of miR-23a-3p, Adiponectin, Leptin, p-PI3K, and p-Akt, decreased NOV expression in the IR adipocytes. The effect of the miR-23a-3p inhibitor on adipocytes with IR was opposite to Resveratrol, and the effects siNOV was the same as Resveratrol, except for its effect on miR-23a-3p expression. Effect of Res on the adipocytes with IR was counteracted by miR-23a-3p inhibitor whose effect was reversed by siNOV.

CONCLUSION

Resveratrol ameliorated glucose uptake and lipid metabolism of the GDM mice and adipocytes with IR by regulating miR-23a-3p/NOV axis.

A systematic review and meta-analysis of the prevalence and determinants of gestational diabetes mellitus in Nigeria

BACKGROUND

Gestational diabetes mellitus (GDM) is any degree of glucose intolerance with onset or first diagnosis in pregnancy. GDM has numerous potential complications and it is important to estimate its burden and risk factors. The objective of the meta-analysis was to determine the pooled prevalence of GDM in Nigeria and identify its determinants.

METHODS

The study design was a meta-analysis; therefore the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Electronic databases (African Journal Online, PubMed, SCOPUS, and Google Scholar) and the gray literature were systematically searched. Statistical analysis was done with MetaXL using the random effect model. Heterogeneity was determined using the I2 statistic and the publication bias was checked with the Doi plot.

RESULTS

The total sample size was 46 210. The prevalence of GDM in Nigeria was 0.5 - 38% and the pooled prevalence was 11.0% (95% CI 8-13). The I2 statistic was 99%. The Doi plot suggested some degree of bias. The most frequently reported determinants of GDM were previous macrosomic babies, maternal obesity, family history of diabetes, previous miscarriage, and advanced maternal age.

CONCLUSION

The prevalence of GDM in Nigeria is high and efforts should be geared at modifying its risk factors so as to reduce its prevalence and prevent the associated complications.

Glycaemic Variability and Risk Factors of Pregnant Women with and without Gestational Diabetes Mellitus Measured by Continuous Glucose Monitoring

Background: The aim of the study was to compare the continuous glucose monitoring (CGM)-determined glycaemic variability (GV) of pregnant women with gestational diabetes mellitus (GDM) and without GDM (CG; control group). The secondary aim was to evaluate the association between risk factors of diabetes in pregnancy and parameters of glyceamic control. Methods: Demographic, biometric and biochemical parameters were obtained for pregnant women (20-38 years old) who after an oral glucose tolerance test were examined by 7-day continuous glucose monitoring using a iPro^®2 Professional CGM. Results: The differences in GV between women with GDM and CG compared by total area under glucose curve (total AUC, (mmol·day/L) was statistically significant (p = 0.006). Other parameters of glycaemic control such as mean glucose, standard deviation, coefficient of variation, J-index, % time-above target range 7.8 mmol/L (%TAR), % time-in range 3.5-7.8 mmol/L (%TIR), time-below target range 3.5 mmol/L (%TBR), glycated haemoglobin were not significantly different in the study groups. Risk factors (a family history of diabetes, pre-pregnancy BMI, higher weight gain and age) correlated with parameters of glycaemic control. Conclusions: We found a significant difference in GV of women with and without GDM by total AUC determined from CGM. TIR metrics were close to significance. Our work points at an increased GV in relation to the risk factors of GDM. Pregnant women with risk factors have higher probability of severe GV with its consequences on maternal and fetal health state.

Evaluation of thiol/disulfide homeostasis in patients with gestational diabetes mellitus

This study aimed to study the dynamic thiol/disulfide homeostasis in pregnant women with gestational diabetes mellitus (GDM). Forty-five pregnant women with GDM and 45 age-matched healthy pregnancies were included in this study. Thiol/disulfide homeostasis was measured using a commercial kit (Rel Assay Diagnostics). The patients with GDM had significantly higher disulfide concentrations than healthy pregnant patients (p = .001). Besides, the GDM group had significantly higher disulfide/total thiol, disüplhide/native thiol, and native thiol/total thiol ratio than healthy pregnant patients (p = .001, p = .001 and p = .001, respectively). The significantly higher concentrations of disulfide, disulfide/total thiol, disüplhide/native thiol, and native thiol/total thiol ratio in women with GDM could be considered as the increased oxidative stress.

The combination of symphysis-fundal height and abdominal circumference as a novel predictor of macrosomia in GDM and normal pregnancy

Background

Macrosomia is a major adverse pregnancy outcome of gestational diabetes mellitus (GDM). Although BMI, symphysis-fundal height (SFH) and abdominal circumference (AC) are associated with foetal weight, there are some limitations to their use, especially for the prediction of macrosomia. This study aimed to identify a novel predictive methodology to improve the prediction of high-risk macrosomia.

Methods

Clinical information was collected from 3730 patients. The association between the ISFHAC (index of the SFH algorithm multiplied by the square of AC) and foetal weight was determined and validated. A new index, the ISFHAC, was evaluated by area under the curve (AUC) analysis.

Results

A total of 1087 GDM and 657 normal singleton pregnancies were analysed. The ISFHAC was positively correlated with foetal weight in GDM pregnancies and normal pregnancies (NPs). The AUCs of the ISFHAC were 0.815 in the GDM group and 0.804 in the NP group, which were higher than those of BMI, SFH, AC and GA. The ISFHAC cut-off points were 41.7 and 37 in the GDM and NP groups, respectively. The sensitivity values for the prediction of macrosomia with high ISFHAC values were 75.9 and 81.3% in the GDM and NP groups, respectively, which were higher than those with BMI. Regarding the validation data, the sensitivity values for prediction with high ISFHAC values were 78.9% (559 GDM pregnancies) and 78.3% (1427 NPs).

Conclusions

The ISFHAC can be regarded as a new predictor of and risk factor for macrosomia in GDM pregnancy and NP.

Serum miR-195-5p is upregulated in gestational diabetes mellitus

BACKGROUND

Gestational diabetes mellitus (GDM) is defined as varying degrees of glucose intolerance with an onset or first recognition during pregnancy in women without previously diagnosed diabetes. Accumulating evidence indicates that miRNAs exert crucial roles in the pathogenesis and development of diabetes, including GDM. In the present study, we aimed to determine the clinical performance of miR-195-5p in GDM.

METHODS

First, the miR-195-5p expressions in serum samples from healthy pregnant women and women with GDM at 25 weeks pregnancy were detected using real-time polymerase chain reaction (RT-qPCR). Then, receive characteristic (ROC) curve was used to determine the diagnostic value of miR-195-5p in GDM. Finally, the correlation analysis of miR-195-5p expression with related clinicopathological factors was carried out to determine the clinical value of miR-195-5p in GDM.

RESULTS

In this study, we found that miR-195-5p expression was significantly increased in serum samples from GDM patients as compared with that in healthy pregnancies. Furthermore, miR-195-5p might be a putative biomarker for GDM diagnosis with an area under the curve (AUC) of 0.8451; the cutoff value was 1.598, sensitivity was 73.69%, specificity was 96.85%, accuracy was 81.26%, and Youden index was 70.54%. Expression of miR-195-5p was positively associated with fasting plasma glucose, one-hour plasma glucose, and two-hour plasma glucose.

CONCLUSION

miR-195-5p might function as a putative diagnostic biomarker for GDM and contribute to identifying at-risk mothers in pregnancy.

Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study

BACKGROUND

Gestational diabetes mellitus (GDM) contributes to adverse pregnancy and birth outcomes. In recent decades, extensive research has been devoted to the early prediction of GDM by various methods. Machine learning methods are flexible prediction algorithms with potential advantages over conventional regression.

OBJECTIVE

The purpose of this study was to use machine learning methods to predict GDM and compare their performance with that of logistic regressions.

METHODS

We performed a retrospective, observational study including women who attended their routine first hospital visits during early pregnancy and had Down's syndrome screening at 16-20 gestational weeks in a tertiary maternity hospital in China from 2013.1.1 to 2017.12.31. A total of 22,242 singleton pregnancies were included, and 3182 (14.31%) women developed GDM. Candidate predictors included maternal demographic characteristics and medical history (maternal factors) and laboratory values at early pregnancy. The models were derived from the first 70% of the data and then validated with the next 30%. Variables were trained in different machine learning models and traditional logistic regression models. Eight common machine learning methods (GDBT, AdaBoost, LGB, Logistic, Vote, XGB, Decision Tree, and Random Forest) and two common regressions (stepwise logistic regression and logistic regression with RCS) were implemented to predict the occurrence of GDM. Models were compared on discrimination and calibration metrics.

RESULTS

In the validation dataset, the machine learning and logistic regression models performed moderately (AUC 0.59-0.74). Overall, the GBDT model performed best (AUC 0.74, 95% CI 0.71-0.76) among the machine learning methods, with negligible differences between them. Fasting blood glucose, HbA1c, triglycerides, and BMI strongly contributed to GDM. A cutoff point for the predictive value at 0.3 in the GBDT model had a negative predictive value of 74.1% (95% CI 69.5%-78.2%) and a sensitivity of 90% (95% CI 88.0%-91.7%), and the cutoff point at 0.7 had a positive predictive value of 93.2% (95% CI 88.2%-96.1%) and a specificity of 99% (95% CI 98.2%-99.4%).

CONCLUSION

In this study, we found that several machine learning methods did not outperform logistic regression in predicting GDM. We developed a model with cutoff points for risk stratification of GDM.