Prediction of Gestational Diabetes Mellitus by Unconjugated Estriol Levels in Maternal Serum

Comparative analysis of obstetric, perinatal, and neurodevelopmental outcomes following chorionic villus sampling and amniocentesis

Background

The risks of invasive prenatal tests are reported in previous studies such as miscarriage, fetal anomalies, and bleeding. However, few compare short-term and long-term outcomes between invasive tests. This study aims to investigate obstetric, perinatal, and children's neurodevelopmental outcomes following chorionic villus sampling (CVS) or amniocentesis in singleton pregnancy.

Methods

This retrospective cohort study included healthy singleton pregnancies underwent transabdominal CVS (gestational age [GA] at 10-13 weeks) or amniocentesis (GA at 15-21 weeks) at a single medical center between 2012 and 2022. Only cases with normal genetic results were eligible. Short-term and long-term neurodevelopmental outcomes were evaluated.

Results

The study included 200 CVS cases and 498 amniocentesis cases. No significant differences were found in body mass index, parities, previous preterm birth, conception method, and cervical length (CL) before an invasive test between the groups. Rates of preterm labor, preterm premature rupture of the membranes, preterm birth, neonatal survival, neonatal short-term morbidities, and long-term neurodevelopmental delay were similar. However, the CVS group had a higher rate of cervical cerclage due to short CL before 24 weeks (7.0%) compared to the amniocentesis group (2.4%). CVS markedly increased the risk of cervical cerclage due to short CL (adjusted odd ratio [aOR] = 3.17, 95%CI [1.23-8.12], p = 0.016), after considering maternal characteristics.

Conclusion

Performing CVS resulted in a higher incidence of cerclage due to short cervix or cervical dilatation compared to amniocentesis in singleton pregnancies. This highlights the importance of cautious selection for CVS and the necessity of informing women about the associated risks beforehand.

Risk Factors in Fetal Ovarian Cysts for Postnatal Adverse Outcomes

AIM

To investigate the natural history of fetal ovarian cysts and elucidate the risk factors for postnatal adverse outcomes in fetal ovarian cysts.

METHODS

The study subjects were 18 cases with ovarian cysts prenatally diagnosed using ultrasonography at our hospital between 2007 and 2020. The subjects were classified by cyst characteristics according to echogenic patterns [simple cyst (S) and complex cyst (C)], changes in echogenic patterns (S-to-S, S-to-C, and C-to-C), and diameters (<40 and ≥ 40 mm). Clinical parameters and outcomes were compared between S and C patterns, S-to-S and S-to-C patterns, and <40 and ≥ 40 mm diameters.

RESULTS

Cases with S and C patterns (15 and 3, respectively) had median gestational ages of 35 and 36 weeks, respectively, and maximum cyst diameters of 36 and 57mm, respectively. The number of cases with S-to-S, S-to-C and C-to-C patterns were 11, 4 and 3, respectively. The maximum cyst diameter in cases with S-to-C patterns (58 mm) was larger than that in cases with S-to-S patterns (34 mm) (P<0.05). Placental weight in cases with cysts >40 mm and/or cyst expansion was greater than that in cases with neither or both conditions (P<0.05). Spontaneous resolution (before and after birth) occurred in 8 of 9 and 3 of 9 cases with maximum cyst diameters <40 and ≥ 40 mm, respectively. Ovarian function was lost in 2 cases with S-to-C patterns and in 2 cases with C-to-C patterns.

CONCLUSION

Cases with cyst diameters ≥ 40 mm and/or cyst expansion during the late third trimester had greater placental weight and more postnatal adverse outcomes.

Source and health risk of urinary neonicotinoids in Tibetan pregnant women

High altitude could influence the level of exposure to neonicotinoids, but relevant data remain limited for people living in Tibet. We investigated 476 Tibetan pregnant women from Lhasa of Tibet, China in 2021 and measured eight neonicotinoids and four metabolites in urine. Food consumption was investigated by a food frequency questionnaire. Health risk was assessed by using hazard quotient (HQ) and hazard index (HI) based on acceptable daily dose or chronic reference dose. Neonicotinoids and metabolites were overall detected in 56.5% of urine samples with a median concentration being 0.73 μg g-1 creatinine. Four neonicotinoids or metabolites were detected in more than 10% of urine samples, including N-desmethyl-acetamiprid (47.5%), clothianidin (15.5%), thiamethoxam (16.0%), and imidacloprid (10.5%). Annual household income, family smoking, and pre-pregnancy body mass index were associated with the detection frequencies of neonicotinoids. Pregnant women with a higher consumption frequency of wheat, rice, fresh vegetable, fresh fruit, beef and mutton, fresh milk, yoghourt, candy and chocolate, or carbonated drinks had a higher detection frequency of neonicotinoids. Both HQ and HI were less than one. There was an evident exposure to neonicotinoids in Tibetan pregnant women with both plant- and animal-derived food items as exposure sources, but a low health risk was found based on current safety thresholds.

Association between sex steroid hormones and subsequent hyperglycemia during pregnancy

Objective

Sex steroid hormones may play a role in insulin resistance and glucose dysregulation. However, evidence regarding associations between early-pregnancy sex steroid hormones and hyperglycemia during pregnancy is limited. The primary objective of this study was to assess the relationships between first trimester sex steroid hormones and the subsequent development of hyperglycemia during pregnancy; with secondary evaluation of sex steroid hormones levels in mid-late pregnancy, concurrent with and subsequent to diagnosis of gestational diabetes.

Methods

Retrospective analysis of a prospective pregnancy cohort study was conducted. Medically low-risk participants with no known major endocrine disorders were recruited in the first trimester of pregnancy (n=319). Sex steroid hormones in each trimester, including total testosterone, free testosterone, estrone, estradiol, and estriol, were assessed using high-performance liquid chromatography and tandem mass spectrometry. Glucose levels of the 1-hour oral glucose tolerance test and gestational diabetes diagnosis were abstracted from medical records. Multivariable linear regression models were fitted to assess the associations of individual first trimester sex steroids and glucose levels.

Results

In adjusted models, first trimester total testosterone (β=5.24, 95% CI: 0.01, 10.46, p=0.05) and free testosterone (β=5.98, 95% CI: 0.97, 10.98, p=0.02) were positively associated with subsequent glucose concentrations and gestational diabetes diagnosis (total testosterone: OR=3.63, 95% CI: 1.50, 8.78; free testosterone: OR=3.69; 95% CI: 1.56, 8.73). First trimester estrone was also positively associated with gestational diabetes (OR=3.66, 95% CI: 1.56, 8.55). In mid-late pregnancy, pregnant people with gestational diabetes had lower total testosterone levels (β=-0.19, 95% CI: -0.36, -0.02) after adjustment for first trimester total testosterone.

Conclusion

Early-pregnancy sex steroid hormones, including total testosterone, free testosterone, and estrone, were positively associated with glucose levels and gestational diabetes in mid-late pregnancy. These hormones may serve as early predictors of gestational diabetes in combination with other risk factors.

Metabolic alteration of circulating steroid hormones in women with gestational diabetes mellitus and the related risk factors

Background

Abnormally changed steroid hormones during pregnancy are closely related to the pathological process of gestational diabetes mellitus (GDM). Our aim was to systematically profile the metabolic alteration of circulating steroid hormones in GDM women and screen for risk factors.

Methods

This study was a case-control study with data measured from 40 GDM women and 70 healthy pregnant women during their 24-28 gestational weeks. 36 kinds of steroid hormones, including 3 kinds of corticosteroids, 2 kinds of progestins, 5 kinds of androgens and 26 kinds of downstream estrogens in serum were systematically measured using a combined sensitive UPLC-MS/MS method. The flux of different metabolic pathways of steroid hormones was analyzed. Logistic regression and ROC curve model analyses were performed to identify potential steroid markers closely associated with GDM development.

Results

Serum corticosteroids, progestins and almost all the estrogen metabolites via 16-pathway from parent estrogens were higher in GDM women compared with healthy controls. Most of the estrogen metabolites via 4-pathway and more than half of the metabolites via 2-pathway were not significantly different. 16α-hydroxyestrone (16OHE1), estrone-glucuronide/sulfate (E1-G/S) and the ratio of total 2-pathway estrogens to total estrogens were screened as three indicators closely related to the risk of GDM development. The adjusted odds ratios of GDM for the highest quartile compared with the lowest were 72.22 (95% CI 11.27-462.71, P _trend <0.001) for 16OHE1 and 6.28 (95% CI 1.74-22.71, P _trend <0.05) for E1-G/S. The ratio of 2-pathway estrogens to total estrogens was negatively associated with the risk of GDM.

Conclusion

The whole metabolic flux from cholesterol to downstream steroid hormones increased in GDM condition. The most significant changes were observed in the 16-pathway metabolism of estrogens, rather than the 2- or 4-pathway or other types of steroid hormones. 16OHE1 may be a strong marker associated with the risk for GDM.

Establishment and validation of a sensitive LC-MS/MS method for quantification of urinary estrogens in women with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is not only a threat to the health of pregnant women, but also has profound effects on the health of offspring. Studies have shown that the imbalance of estrogen metabolism is associated with an increased risk of GDM. In this study, an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was established and validated for simultaneous quantification of thirteen estrogens in the urine of GDM women, including estrone (E1), estradiol (E2), estriol (E3), and their hydroxylated and methylated metabolites. The method was achieved on a Waters CORTECS C18 column (2.1 mm × 150 mm, 1.6 µm) within 8.5 min. The linear range of thirteen estrogens in urine was 2-1000 pg·mL^-1. Both intra- and inter-day precision for each analyte were less than 15%, with accuracies ranging from 8.3% to 7.3%. The extraction recoveries rate were between 86% and 111%, and stability verification results met the requirements for determination of biological samples. The results suggested that the concentrations of estrogens in all urine samples range from 0.08 to 134.06 (pg·mg^-1 creatinine). The mean levels of E1, E2 and most estrogen metabolites in the urine of GDM women were higher than those in healthy pregnant women. Notably, the mean level of 2-hydroxyestrone (2-OHE1) in GDM women was 13.2-fold lower than that in healthy pregnant women. The types of estrogens with the highest mean levels in the urine of GDM and healthy pregnant women were obviously different, which are 2-methoxyestrone (2MeOE1) and E3, respectively. Our results demonstrated that this specific and sensitive method is suitable for quantifying estrogens in human urine and could provide support for further research on estrogen-related pathological mechanisms in GDM and other diseases.

Second trimester prediction of gestational diabetes: maternal analytes as an additional screening tool

OBJECTIVES

Early diagnosis of gestational diabetes can lead to greater optimization of glucose control. We evaluated associations between maternal serum analytes (alpha-fetoprotein [AFP], free beta-human chorionic gonadotropin [beta-hCG], inhibin, and estriol) and the development of gestational diabetes mellitus (GDM).

METHODS

This retrospective cohort study identified single-ton pregnancies with available second trimester serum analytes between 2009 and 2017. GDM was identified by ICD-9 and -10 codes. We examined the associations between analyte levels and GDM and to adjust for potential confounders routinely collected during genetic serum screening (maternal age, BMI, and race) using logistic regression. Optimal logistic regression predictive modeling for GDM was then performed using the analyte levels and the above mentioned potential confounders. The performance of the model was assessed by receiver operator curves.

RESULTS

Out of 5,709 patients, 660 (11.6%) were diagnosed with GDM. Increasing AFP and estriol were associated with decreasing risk of GDM, aOR 0.76 [95% CI 0.60-0.95] and aOR 0.67 [95% CI 0.50-0.89] respectively. Increasing beta-hCG was associated with a decreasing risk for GDM(aOR 0.84 [95% CI 0.73-0.97]). There was no association with inhibin. The most predictive GDM predictive model included beta-hCG and estriol in addition to the clinical variables of age, BMI, and race (area under the curve (AUC 0.75), buy this was not statistically different than using clinical variables alone (AUC 0.74) (p=0.26).

CONCLUSIONS

Increasing second trimester AFP, beta-hCG, and estriol are associated with decreasing risks of GDM, though do not improve the predictive ability for GDM when added to clinical risk factors of age, BMI, and race.

Effect of maternal body mass index on the steroid profile in women with gestational diabetes mellitus

OBJECTIVE

To explore the effect of maternal body mass index (BMI) on steroid hormone profiles in women with gestational diabetes mellitus (GDM) and those with normal glucose tolerance (NGT).

METHODS

We enrolled 79 women with NGT and 80 women with GDM who had a gestational age of 24-28 weeks. The participants were grouped according to their BMI. We quantified 11 steroid hormones profiles by liquid chromatography-tandem mass spectrometry and calculated the product-to-precursor ratios in the steroidogenic pathway.

RESULTS

Women with GDM and BMI<25kg/m² showed higher concentrations of dehydroepiandrosterone (DHEA) (p<0.001), testosterone (T) (p=0.020), estrone (E1) (p=0.010) and estradiol (E2) (p=0.040) and lower Matsuda index and HOMA-β than women with NGT and BMI<25kg/m². In women with GDM, concentrations of E1 (p=0.006) and E2 (p=0.009) declined, accompanied by reduced E2/T (p=0.008) and E1/androstenedione (A4) (p=0.010) in the BMI>25 kg/m² group, when compared to that in the BMI<25 kg/m² group. The values of E2/T and E1/A4 were used to evaluate the cytochrome P450 aromatase enzyme activity in the steroidogenic pathway. Both aromatase activities negatively correlated with the maternal BMI and positively correlated with the Matsuda index in women with GDM.

CONCLUSIONS

NGT women and GDM women with normal weight presented with different steroid hormone profiles. Steroidogenic pathway profiling of sex hormones synthesis showed a significant increase in the production of DHEA, T, E1, and E2 in GDM women with normal weight. Additionally, the alteration of steroid hormone metabolism was related to maternal BMI in women with GDM, and GDM women with overweight showed reduced estrogen production and decreased insulin sensitivity compared with GDM women with normal weight.

Placental Endocrine Activity: Adaptation and Disruption of Maternal Glucose Metabolism in Pregnancy and the Influence of Fetal Sex

The placenta is an endocrine fetal organ, which secretes a plethora of steroid- and proteo-hormones, metabolic proteins, growth factors, and cytokines in order to adapt maternal physiology to pregnancy. Central to the growth of the fetus is the supply with nutrients, foremost with glucose. Therefore, during pregnancy, maternal insulin resistance arises, which elevates maternal blood glucose levels, and consequently ensures an adequate glucose supply for the developing fetus. At the same time, maternal β-cell mass and function increase to compensate for the higher insulin demand. These adaptations are also regulated by the endocrine function of the placenta. Excessive insulin resistance or the inability to increase insulin production accordingly disrupts physiological modulation of pregnancy mediated glucose metabolism and may cause maternal gestational diabetes (GDM). A growing body of evidence suggests that this adaptation of maternal glucose metabolism differs between pregnancies carrying a girl vs. pregnancies carrying a boy. Moreover, the risk of developing GDM differs depending on the sex of the fetus. Sex differences in placenta derived hormones and bioactive proteins, which adapt and modulate maternal glucose metabolism, are likely to contribute to this sexual dimorphism. This review provides an overview on the adaptation and maladaptation of maternal glucose metabolism by placenta-derived factors, and highlights sex differences in this regulatory network.

Steroid profiling and genetic variants in Chinese women with gestational diabetes mellitus

Previous studies have demonstrated that steroids were associated with gestational diabetes mellitus (GDM). However, results from different studies remained inconsistent, and only a limited range of steroids were investigated in these studies. Therefore, we aimed to analyze comprehensive steroid profiling in Chinese women with GDM during third-trimester pregnancy. In 97 Chinese pregnant women, we measured steroid profile using a LC-MS/MS method, and calculated product-to-precursor ratios in metabolic pathways of steroids. Then sixteen genetic variants of genes encoding steroidogenic enzymes were genotyped by MassARRAY system. There were significant differences (P < 0.05) and obvious changes (fold change <0.67 or>1.5) in steroids (testosterone, estriol, pregnenolone and dehydroepiandrosterone) and product-to-precursor ratios (E2/T and T/AD) between GDM and control groups. After adjusting for maternal age, the TT genotype and T allele of CYP19A1 rs10046 were associated with an increased risk of GDM. And the CC genotype and C allele of HSD17B3 rs2257157 were also associated with an increased risk of GDM. Besides, pregnant women carrying TT genotype of CYP19A1 rs10046 and CC genotype of HSD17B3 rs2257157 had a lower E2/T ratio and higher T/AD ratio respectively comparing with those carrying other genotypes. In conclusion, our study suggested that testosterone, estriol, pregnenolone and dehydroepiandrosterone might be differential metabolites for gestational diabetes mellitus. The genetic variants rs10046 of CYP19A1 and rs2257157 of HSD17B3 could predispose to GDM in Chinese women.

How Can We Adopt the Glucose Tolerance Test to Facilitate Predicting Pregnancy Outcome in Gestational Diabetes Mellitus?

BACKGROUND

We investigated how 100-g oral glucose tolerance test (OGTT) results can be used to predict adverse pregnancy outcomes in gestational diabetes mellitus (GDM) patients.

METHODS

We analyzed 1,059 pregnant women who completed the 100-g OGTT between 24 and 28 weeks of gestation. We compared the risk of adverse pregnancy outcomes according to OGTT patterns by latent profile analysis (LPA), numbers to meet the OGTT criteria, and area under the curve (AUC) of the OGTT graph. Adverse pregnancy outcomes were defined as a composite of preterm birth, macrosomia, large for gestational age, low APGAR score at 1 minute, and pregnancy-induced hypertension.

RESULTS

Overall, 257 participants were diagnosed with GDM, with a median age of 34 years. An LPA led to three different clusters of OGTT patterns; however, there were no significant associations between the clusters and adverse pregnancy outcomes after adjusting for confounders. Notwithstanding, the risk of adverse pregnancy outcome increased with an increase in number to meet the OGTT criteria (P for trend=0.011); odds ratios in a full adjustment model were 1.27 (95% confidence interval [CI], 0.72 to 2.23), 2.16 (95% CI, 1.21 to 3.85), and 2.32 (95% CI, 0.66 to 8.15) in those meeting the 2, 3, and 4 criteria, respectively. The AUCs of the OGTT curves also distinguished the patients at risk of adverse pregnancy outcomes; the larger the AUC, the higher the risk (P for trend=0.007).

CONCLUSION

The total number of abnormal values and calculated AUCs for the 100-g OGTT may facilitate tailored management of patients with GDM by predicting adverse pregnancy outcomes.

Metabolomic profile associated with obstructive sleep apnoea severity in obese pregnant women with gestational diabetes mellitus: A pilot study

Obstructive sleep apnoea (OSA) is prevalent in obese women with gestational diabetes mellitus (GDM). The present pilot study explored associations between OSA severity and metabolites in women with GDM. A total of 81 obese women with diet-controlled GDM had OSA assessment (median gestational age [GA] 29 weeks). The metabolic profile was assayed from fasting serum samples via liquid chromatography-mass spectrometry (LC-MS) using an untargeted approach. Metabolites were extracted and subjected to an Agilent 1,290 UPLC coupled to an Agilent 6,545 quadrupole time-of-flight (Q-TOF) MS. Data were acquired using electrospray ionisation in positive and negative ion modes. The raw LC-MS data were processed using the OpenMS toolkit to detect and quantify features, and these features were annotated using the Human Metabolite Database. The feature data were compared with OSA status, apnea-hypopnea index (AHI), body mass index (BMI) and GA using "limma" in R. Correlation analyses of the continuous covariates were performed using Kendall's Tau test. The p values were adjusted for multiple testing using the Benjamini-Hochberg false discovery rate correction. A total of 42 women (51.8%) had OSA, with a median AHI of 9.1 events/hr. There were no significant differences in metabolomics profiles between those with and without OSA. However, differential analyses modelling in GA and BMI found 12 features that significantly associated with the AHI. These features could be annotated to oestradiols, lysophospholipids, and fatty acids, with higher levels related to higher AHI. Metabolites including oestradiols and phospholipids may be involved in pathogenesis of OSA in pregnant women with GDM. A targeted approach may help elucidate our understanding of their role in OSA in this population.

Predictability of Macrosomic Birth based on Maternal Factors and Fetal Aneuploidy Screening Biochemical Markers in Hyperglycemic Mothers

Background: Macrosomic birth weight has been implicated as a significant risk factor for developing various adult metabolic diseases such as diabetes mellitus and coronary heart diseases; it has also been associated with higher incidences of complicated births. This study aimed to examine the predictability of macrosomic births in hyperglycemic pregnant women using maternal clinical characteristics and serum biomarkers of aneuploidy screening performed in the first half of pregnancy. Methods: A retrospective observational study was performed on a cohort of 1,668 pregnant women who 1) had positive outcomes after undergoing 50-g oral glucose challenge test (OGCT) at two university-based hospitals and 2) underwent any one of the following maternal biomarker screening tests for fetal aneuploidy: triple test, quadruple test, and integrated test. Logistic regression-based models for predicting macrosomic births using maternal characteristics and serum biomarkers were developed and evaluated for prediction power. A nomogram, which is a graphical display of the best predictable model, was then generated. Results: The study cohort included 157 macrosomic birth cases defined as birth weight ≥3,820 g, which was equivalent to the top 10 percentile of the modeling cohort. Three primary models solely based on serum biomarkers achieved area under curves (AUCs) of 0.55-0.62. Expanded models, including maternal demographic and clinical factors, demonstrated an improved performance by 25% (AUCs, 0.69-0.73). Conclusion: Our prediction models will help to identify pregnancies with an elevated risk of macrosomic births in hyperglycemic mothers using maternal clinical factors and serum markers from routine antenatal screening tests. Prediction of macrosomic birth at mid-pregnancy may allow customized antenatal care to reduce the risk of macrosomic births.

The correlation between plasma total homocysteine level and gestational diabetes mellitus in a Chinese Han population

To assess the correlation between plasma total homocysteine (tHcy) level and gestational diabetes mellitus (GDM) in a Chinese Han population. This case–control study included 350 GDM patients and 346 gestational week-matched normal glucose tolerance (NGT) pregnant women. Plasma tHcy and insulin levels were analyzed by HPLC and ELISA respectively. Logistic regression analysis was used to investigate the correlation between plasma tHcy level and risk of GDM. Women with GDM had a higher plasma tHcy level than NGT women (6.61 ± 1.32 vs. 6.17 ± 1.29 μmol/L, P = 0.001)). The GDM risk was 1.79 (OR = 1.79, 95% CI 1.18–2.72, P = 0.006) times higher in women whose plasma tHcy level was ≥ 7.29 μmol/L compared to women with plasma tHcy level < 5.75 μmol/L. Stratified analysis showed the GDM risk were much higher when HOMA-IR index ≥ 2 (OR = 5.42, 95% CI 2.51–11.74, P < 0.001), age ≥ 30 years (OR = 5.14, 95% CI 2.78–9.52, P < 0.001), or women with a family history of type 2 diabetes mellitus (T2DM) (OR = 4.13, 95% CI 1.78–9.56, P = 0.001). In the Chinese Han population, an elevated plasma tHcy level may increase the overall risk of GDM especially in women with a high HOMA-IR index, increasing age or with family history of T2DM.

Prediction of gestational diabetes mellitus in the first 19 weeks of pregnancy using machine learning techniques

AIM

Our objective was to develop a first 19 weeks risk prediction model with several potential gestational diabetes mellitus (GDM) predictors including hepatic and renal and coagulation function measures.

METHODS

A total of 490 pregnant women, 215 with GDM and 275 controls, participated in this case-control study. Forty-three blood examination indexes including blood routine, hepatic and renal function, and coagulation function were obtained. Support vector machine (SVM) and light gradient boosting machine (lightGBM) were applied to estimate possible associations with GDM and build the predict model. Cutoff points were estimated using receiver operating characteristic curve analysis.

RESULTS

It was observed that a cutoff of Prothrombin time (PAT-PT) and Activated partial thromboplastin time (PAT-APTT) could reliably predict GDM with sensitivity of 88.3% and specificity of 99.47% (AUC of 94.2%). If we only use hepatic and renal function examination, a cutoff of DBIL and FPG with sensitivity of 82.6% and specificity of 90.0% (AUC of 91.0%) was obvious and a negative correlation with PAT-PT (r=-0.430549) and patient activated partial thromboplastin time (PAT-APTT) (r=-0.725638). A negative correlation with direct bilirubin (DBIL) (r=-0.379882) and positive correlation with fasting plasma glucose (FPG) (r = 0.458332) neglect coagulation function examination.

CONCLUSION

The results of this study point out the possible roles of PAT-PT and PAT-APTT as potential novel biomarkers for the prediction and earlier diagnosis of GDM. A first 19 weeks risk prediction model, which incorporates novel biomarkers, accurately identifies women at high risk of GDM, and relevant measures can be applied early to achieve the prevention and control effects.

Diagnostic accuracy of maternal serum multiple marker screening for early detection of gestational diabetes mellitus in the absence of a gold standard test

Background

Gestational diabetes mellitus (GDM) is associated with adverse diabetic complications for both mother and child during pregnancy. The common Gold Standard (GS) for diagnosis of GDM is 75 g oral glucose tolerance test (OGTT) during 24–28 gestational weeks which seems a little late for any proper intervention. This study aimed to employ the Bayesian latent class models (LCMs) for estimating the early diagnostic power of combination of serum multiple marker in detecting GDM during 14–17 weeks of gestation.

Methods

Data from a sample of 523 pregnant women who participated in gestational diabetes screening tests at health centers affiliated to Shahid Beheshti University of Medical Sciences in Tehran, Iran from 2017 to 2018 were used. The beta-human chorionic gonadotropin (β-hCG), unconjugated estriol (uE3), and alfa-fetoprotein (AFP) values were extracted from case records for all participants. The Bayesian LCMs were applied for estimating sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of combining the three biomarkers’ results in the absence of GS, adjusting for maternal age and body mass index.

Results

The mean (standard deviation) maternal age of the participants was 28.76 (±5.33) years. Additionally, the mean (standard deviation) BMI was 24.57 (±3.22) kg/m². According to the Bayesian model, the cSensitivity, cSpecificity, and cAUC for the optimal composite diagnostic test were estimated as 94% (95% credible interval (CrI) [0.91–0.99]), 86% (95% CrI [0.80–0.92]), and 0.92 (95% CrI [0.87–0.98]), respectively.

Conclusions

Overall, the findings revealed that the combination of uE3, AFP, and β-hCG results might be considered as an acceptable predictor for detecting GDM with a rather high level of accuracy in the early second trimester of pregnancy without a GS.

Depression precedes, but does not follow, gestational diabetes

OBJECTIVES

To determine whether past history of depression is associated with increased rates of gestational diabetes, and whether history of gestational diabetes is associated with increased rates of postpartum depression.

RESEARCH DESIGN

Data for this case-control study consisted of de-identified chart records for 1439 women who received pregnancy care at a large university hospital between 1998 and 2017.

RESULTS

A history of depression prior to pregnancy was associated with gestational diabetes requiring insulin, although not with subtler degrees of gestational hyperglycemia. Diabetes in pregnancy was not associated with an increased risk of postpartum depression. Trauma history was associated with both impaired glucose tolerance in pregnancy and postpartum depression.

CONCLUSIONS

Past episodes of depression increase risk for the most severe form of gestational diabetes; however, gestational diabetes does not contribute significantly to risk for postpartum depression. This suggests a unidirectional association, unlike the bidirectional association of diabetes with depression among the general population. History of trauma increases risk for both gestational hyperglycemia and postpartum depression, suggesting important health effects of trauma that may differ measurably from those associated with depression.

Methylation of HIF3A promoter CpG islands contributes to insulin resistance in gestational diabetes mellitus

BACKGROUND

Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance during pregnancy, and will lead to high risk of diabetes even after pregnancy. Hypoxia-inducible factor (HIF) family proteins are transcriptional factors that are highly correlated with methylation, which might be involved in the regulation of GDM.

METHODS

Baseline clinical characteristics of the GDM patients and healthy women were analyzed. Omental tissue from GDM patients and control groups were collected and detected for the expression levels of HIF1A, HIF2A, and HIF3A. The CpG islands of HIF3A promoter were predicted by "methprimer" software, and the methylation level of CpG islands was detected by bisulfite sequencing PCR.

RESULTS

HIF3A was downregulated in the omental tissue from GDM patients, whereas HIF1A and HIF2A were not affected. Furthermore, HIF3A expression was positively correlated with levels of estrogen receptor α (ESR1) and solute carrier family 2 member 4 (SLC2A4). Moreover, CpG islands of HIF3A promoter were highly methylated in GDM patients. In addition, methylation level of CpG islands could be upregulated by Estradiol (E2) treatment, since high dose of E2 reduced HIF3A mRNA expression in 3T3-L1 adipocytes.

CONCLUSION

Our findings demonstrate that the expression level of HIF3A, but not HIF1A or HIF2A, is downregulated in GDM patients. The methylation status of HIF3A promoter region is highly correlated with GDM, which could be a novel therapeutic target for GDM treatment.