The effects of gestational diabetes mellitus with maternal age between 35 and 40 years on the metabolite profiles of plasma and urine.

BACKGROUND: Gestational diabetes mellitus (GDM) is defined as impaired glucose tolerance in pregnancy and without a history of diabetes mellitus. While there are limited metabolomic studies involving advanced maternal age in China, we aim to investigate the metabolomic profiling of plasma and urine in pregnancies complicated with GDM aged at 35-40 years at early and late gestation. METHODS: Twenty normal and 20 GDM pregnant participants (≥ 35 years old) were enlisted from the Complex Lipids in Mothers and Babies (CLIMB) study. Maternal plasma and urine collected at the first and third trimester were detected using gas chromatography-mass spectrometry (GC-MS). RESULTS: One hundred sixty-five metabolites and 192 metabolites were found in plasma and urine respectively. Urine metabolomic profiles were incapable to distinguish GDM from controls, in comparison, there were 14 and 39 significantly different plasma metabolites between the two groups in first and third trimester respectively. Especially, by integrating seven metabolites including cysteine, malonic acid, alanine, 11,14-eicosadienoic acid, stearic acid, arachidic acid, and 2-methyloctadecanoic acid using multivariant receiver operating characteristic models, we were capable of discriminating GDM from normal pregnancies with an area under curve of 0.928 at first trimester. CONCLUSION: This study explores metabolomic profiles between GDM and normal pregnancies at the age of 35-40 years longitudinally. Several compounds have the potential to be biomarkers to predict GDM with advanced maternal age. Moreover, the discordant metabolome profiles between the two groups could be useful to understand the etiology of GDM with advanced maternal age.

Urinary phthalate and DINCH metabolite concentrations and gradations of maternal glucose intolerance.

BACKGROUND: Studies suggest a link between pregnancy phthalate exposures and gestational diabetes mellitus (GDM). Few studies have evaluated associations between phthalate biomarkers (individual or mixtures) with gradations of maternal glucose intolerance. METHODS: In a subset of 606 women participating in LIFECODES pregnancy cohort, a combination of 50-gram 1-h non-fasting glucose load test (GLT) and 100-gram 3-h fasting oral glucose tolerance test was used to determine pregnancy glycemic status (median: 27 weeks gestation): normoglycemia (n = 136), impaired glucose tolerance (IGT) (n = 296), and GDM (n = 174). Nineteen metabolites of phthalates and their replacements were measured during each trimester. We used multivariable logistic regression models to evaluate associations between biomarkers (in quartiles) and maternal glycemic status (GDM v. normoglycemia and IGT v. normoglycemia), adjusting for potential confounders. We also used principal component analysis to evaluate associations jointly accounting for metabolites as chemical mixtures. RESULTS: Higher 1st trimester mono-3-carboxypropyl phthalate (MCPP) was associated with decreased odds of GDM (Q4 v. Q1: 0.30; 95% CI: 0.13, 0.67) and IGT (Q4 v. Q1 OR: 0.37; 95% CI: 0.17, 0.79). Higher 2nd trimester mono-isobutyl phthalate (MiBP) was associated with increased IGT (Q4 v. Q1 OR: 2.07; 95% CI: 1.06, 4.07), and 2nd trimester mono-3-hydroxybutyl phthalate (MHBP) was non-monotonically associated with increased GDM (Q2 v. Q1 OR: 3.21; 95% CI: 1.54, 6.87). Mixture analyses showed similar associations (Q4 v. Q1 for 2nd trimester dibutyl phthalates metabotlites mixtures OR: 2.08; 95% CI: 1.04, 4.22). CONCLUSION: Some phthalate biomarkershad trimester-specific associations with glycemic outcomes, with long and short term health implications.

Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence.

Gestational diabetes mellitus (GDM) is the fastest growing type of diabetes, affecting between 2 to 38% of pregnancies worldwide, varying considerably depending on diagnostic criteria used and sample population studied. Adverse obstetric outcomes include an increased risk of macrosomia, and higher rates of stillbirth, instrumental delivery, and birth trauma. Metabolomics, which is a platform used to analyse and characterise a large number of metabolites, is increasingly used to explore the pathophysiology of cardiometabolic conditions such as GDM. This review aims to summarise metabolomics studies in GDM (from inception to January 2021) in order to highlight prospective biomarkers for diagnosis, and to better understand the dysfunctional metabolic pathways underlying the condition. We found that the most commonly deranged pathways in GDM include amino acids (glutathione, alanine, valine, and serine), carbohydrates (2-hydroxybutyrate and 1,5-anhydroglucitol), and lipids (phosphatidylcholines and lysophosphatidylcholines). We also highlight the possibility of using certain metabolites as predictive markers for developing GDM, with the use of highly stratified modelling techniques. Limitations for metabolomic research are evaluated, and future directions for the field are suggested to aid in the integration of these findings into clinical practice.

Establishment of clinical diagnostic models using glucose, lipid, and urinary polypeptides in gestational diabetes mellitus.

BACKGROUND: Gestational diabetes mellitus (GDM) has many adverse outcomes that seriously threaten the short-term and long-term health of mothers and infants. This study comprehensively analyzed the clinical diagnostic value of GDM-related clinical indexes and urine polypeptide research results, and established comprehensive index diagnostic models. METHODS: In this study, diagnostic values from the clinical indexes of serum triglyceride (TRIG), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG) and glycosylated hemoglobin (HbA1c), and 7 GDM-related urinary polypeptides were analyzed retrospectively. The multiple logistic regression equation, multilayer perceptron neural network model, radial basis function, and discriminant analysis function models of GDM-related indexes were established using machine language. RESULTS: The results showed that HbA1c had the highest diagnostic value for GDM, with an area under the curve (AUC) of 0.769. When the cut-off value was 4.95, the diagnostic sensitivity and specificity were 70.5% and 70.0%, respectively. Among the seven GDM-related urinary polypeptides, human hemopexin (HEMO) had the highest diagnostic value, with an AUC of 0.690. When the cut-off value was 368.5, the sensitivity and specificity were 79.5% and 43.3%, respectively. The AUC of the multilayer perceptron neural network model was 0.942, followed by binary logistic regression (0.938), radial basis function model (0.909), and the discriminant analysis function model (0.908). CONCLUSION: The establishment of a GDM diagnostic model combining blood glucose, blood lipid, and urine polypeptide indexes can lay a foundation for exploring machine language and artificial intelligence in diagnostic systems.

Early pregnancy metabolites predict gestational diabetes mellitus: implications for fetal programming.

BACKGROUND: Aberrant fetal programming in gestational diabetes mellitus seems to increase the risk of obesity, type 2 diabetes, and cardiovascular disease. The inability to accurately identify gestational diabetes mellitus in the first trimester of pregnancy has thwarted ascertaining whether early therapeutic interventions reduce the predisposition to these prevalent medical disorders. OBJECTIVE: A metabolomics study was conducted to determine whether advanced analytical methods could identify accurate predictors of gestational diabetes mellitus in early pregnancy. STUDY DESIGN: This nested observational case-control study was composed of 92 gravidas (46 in the gestational diabetes mellitus group and 46 in the control group) in early pregnancy, who were matched by maternal age, body mass index, and gestational age at urine collection. Gestational diabetes mellitus was diagnosed according to community standards. A comprehensive metabolomics platform measured 626 endogenous metabolites in randomly collected urine. Consensus multivariate criteria or the most important by 1 method identified low-molecular weight metabolites independently associated with gestational diabetes mellitus, and a classification tree selected a subset most predictive of gestational diabetes mellitus. RESULTS: Urine for both groups was collected at a mean gestational age of 12 weeks (range, 6-19 weeks' gestation). Consensus multivariate analysis identified 11 metabolites independently linked to gestational diabetes mellitus. Classification tree analysis selected a 7-metabolite subset that predicted gestational diabetes mellitus with an accuracy of 96.7%, independent of maternal age, body mass index, and time of urine collection. CONCLUSION: Validation of this high-accuracy model by a larger study is now needed to support future studies to determine whether therapeutic interventions in the first trimester of pregnancy for gestational diabetes mellitus reduce short- and long-term morbidity.

Urinary Peptides Associated Closely with Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) is a common disease of pregnant women, which has a higher incidence in recent years. The purpose of this study is to explore urinary biomarkers that could predict and monitor gestational diabetes mellitus (GDM). Urine samples from 30 normal pregnant women and 78 GDM patients were collected and purified by weak cationic exchange magnetic beads (MB-WCX), then analyzed by matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS). The urinary peptide signatures of the two groups were compared by BioExplorer software. The potential ability of the differently expressed peptides to distinguish GDM patients from normal pregnant women was evaluated by receiver operating characteristic (ROC) analysis. At last, the differently expressed peptides were identified by liquid chromatography tandem mass spectrometry (LC-MS). There were four differently expressed peptides (m/z 1000.5, 1117.5, 1142.9, and 2022.9) between two groups, which were identified as fragments of urinary albumin, α2-macroglobulin, human hemopexin, and α1-microglobulin, respectively. The diagnostic efficacy of m/z 1142.9 was better than the other peptides. The area under the curve (AUC) of the m/z 1142.9 was 0.690 (95% CI: 0.583-0.796). The discovery of urinary polypeptides provides the possibility for the early prediction of GDM and the monitoring of glucose metabolism in GDM patients by a noninvasive method.

Screening and analysis of small molecular peptides in urine of gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) is a common clinical disease with complicated clinical process and harmful effects on pregnant women and fetus. The purpose of this study is to use the convenient urine samples in combination with glucose levels to detect or predict GDM. In this study, urine samples of non-pregnant women, normal pregnant women and GDM patients were collected. The peptides in urine were enriched by weak cationic exchange magnetic beads (MB-WCX) and analyzed by matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). 46 polypeptide peaks with statistical difference (P < 0.01) were screened out by using Bioexplorer analysis software. The level of molecules with mass-to-charge ratio of 1079.2, 1290.6 and 1500.7 was higher in the GDM group than the other two groups. Through the analysis of differential molecules by liquid chromatography tandem mass spectrometry (LC-MS), the above molecules were identified as coagulation factor IX, TBC1 family member 5 isoform a [Homo sapiens] (TBC1D5a) and immunoglobulin kappa constant. The discovery of polypeptides provides the research basis for further primary screening and assistant diagnosis of GDM through urine samples.

Effects of Pregnancy on the Pharmacokinetics of Metformin.

This study's primary objective was to fully characterize the pharmacokinetics of metformin in pregnant women with gestational diabetes mellitus (GDM) versus nonpregnant controls. Steady-state oral metformin pharmacokinetics in pregnant women with GDM receiving either metformin monotherapy (n = 24) or a combination with glyburide (n = 30) as well as in nonpregnant women with type 2 diabetes mellitus (T2DM) (n = 24) were determined utilizing noncompartmental techniques. Maternal and umbilical cord blood samples were collected at delivery from 38 women. With both 500- and 1000-mg doses, metformin bioavailability, volume of distribution beta (V ß ), clearance, and renal clearance were significantly increased during pregnancy. In addition, in the women receiving metformin 500 mg, significantly higher metformin apparent oral clearance (CL/F) (27%), weight-adjusted renal secretion clearance (64%), and apparent oral volume of distribution beta (V ß /F) (33%) were seen during pregnancy. Creatinine clearance was significantly higher during pregnancy. Increasing metformin dose from 500 to 1000 mg orally twice daily significantly increased V ß /F by 28%, weight-adjusted V ß /F by 32% and CL/F by 25%, and weight-adjusted CL/F by 28% during pregnancy. Mean metformin umbilical cord arterial-to-venous plasma concentration ratio was 1.0 ± 0.1, venous umbilical cord-to-maternal concentration ratio was 1.4 ± 0.5, and arterial umbilical cord-to-maternal concentration ratio was 1.5 ± 0.5. Systemic exposure after a 500-mg dose of metformin was lower during pregnancy compared with the nonpregnant women with T2DM. However, in patients receiving metformin 1000 mg, changes in estimated bioavailability during pregnancy offset the changes in clearance leading to no significant change in CL/F with the higher dose. SIGNIFICANCE STATEMENT: Gestational diabetes mellitus complicates 5%-13% of pregnancies and is often treated with metformin. Pregnant women undergo physiological changes that alter drug disposition. Preliminary data suggest that pregnancy lowers metformin concentrations, potentially affecting efficacy and safety. This study definitively describes pregnancy's effects on metformin pharmacokinetics and expands the mechanistic understanding of pharmacokinetic changes across the dosage range. Here we report the nonlinearity of metformin pharmacokinetics and the increase in bioavailability, clearance, renal clearance, and volume of distribution during pregnancy.

Predictive and diagnostic biomarkers for gestational diabetes and its associated metabolic and cardiovascular diseases.

Gestational diabetes mellitus (GDM) is defined as the presence of high blood glucose levels with the onset, or detected for the first time during pregnancy, as a result of increased insulin resistance. GDM may be induced by dysregulation of pancreatic ß-cell function and/or by alteration of secreted gestational hormones and peptides related with glucose homeostasis. It may affect one out of five pregnancies, leading to perinatal morbidity and adverse neonatal outcomes, and high risk of chronic metabolic and cardiovascular injuries in both mother and offspring. Currently, GDM diagnosis is based on evaluation of glucose homeostasis at late stages of pregnancy, but increased age and body-weight, and familiar or previous occurrence of GDM, may conditionate this criteria. In addition, an earlier and more specific detection of GDM with associated metabolic and cardiovascular risk could improve GDM development and outcomes. In this sense, 1st-2nd trimester-released biomarkers found in maternal plasma including adipose tissue-derived factors such as adiponectin, visfatin, omentin-1, fatty acid-binding protein-4 and retinol binding-protein-4 have shown correlations with GDM development. Moreover, placenta-related factors such as sex hormone-binding globulin, afamin, fetuin-A, fibroblast growth factors-21/23, ficolin-3 and follistatin, or specific micro-RNAs may participate in GDM progression and be useful for its recognition. Finally, urine-excreted metabolites such as those related with serotonin system, non-polar amino-acids and ketone bodies, may complete a predictive or early-diagnostic panel of biomarkers for GDM.

Unhealthy Levels of Phthalates and Bisphenol A in Mexican Pregnant Women with Gestational Diabetes and Its Association to Altered Expression of miRNAs Involved with Metabolic Disease.

Several studies indicate that bisphenol A (BPA) and phthalates may have a role in the development of metabolic diseases using different molecular pathways, including epigenetic regulatory mechanisms. However, it is unclear whether exposure to these chemicals modifies serum levels of miRNAs associated with gestational diabetes mellitus (GDM) risk. In the present study, we evaluated the serum levels of miRNAs associated with GDM (miR-9-5p, miR-16-5p, miR-29a-3p and miR-330-3p) and urinary levels of phthalate metabolites (mono-n-butyl phthalate (MBP), mono-isobutyl phthalate (MiBP), mono-benzyl phthalate (MBzP) and mono(2-ethyl hexyl) phthalate (MEHP)) and bisphenol A in GDM patients and women without GDM during the second trimester of gestation. We observed higher levels of miR-9-5p, miR-29a-3p and miR-330-3p in sera of patients with GDM compared to non-diabetic subjects. Phthalates were detected in 97-100% of urine samples, while BPA only in 40%. Urinary MEHP and BPA concentrations were remarkably higher in both study groups compared to previously reported data. Unadjusted MEHP levels and adjusted BPA levels were higher in non-diabetics than in GDM patients (p = 0.03, p = 0.02). We found positive correlations between adjusted urinary MBzP levels and miR-16-5p expression levels (p < 0.05), adjusted MEHP concentrations and miR-29a-3p expression levels (p < 0.05). We also found negative correlations between unadjusted and adjusted MBP concentrations and miR-29a-3p expression levels (p < 0.0001, p < 0.05), unadjusted MiBP concentrations and miR-29a-3p expression levels (p < 0.01). Urinary MEHP levels reflect a striking exposure to di(2-ethylhexyl) phthalate (DEHP) in pregnant Mexican women. This study highlights the need for a regulatory strategy in the manufacture of several items containing endocrine disruptors in order to avoid involuntary ingestion of these compounds in the Mexican population.

Parabens exposure in early pregnancy and gestational diabetes mellitus.

BACKGROUND: Widespread exposure to parabens has been a concern, especially among pregnant women. Only one study reported that parabens are associated with glucose levels among pregnant women. However, studies on parabens exposure and gestational diabetes mellitus (GDM) are lacking. OBJECTIVES: This study investigated whether exposure to parabens in early pregnancy is related to GDM. METHODS: We conducted a prospective study of 1087 pregnant women from a single tertiary medical center between 2014 and 2015 in Wuhan, China. Parabens [methyl paraben (MeP), ethylparaben (EtP), propylparaben (PrP), butylparaben (BuP), and benzylparaben (BzP)] concentrations were measured in spot urine samples collected between 8 and 16 gestational weeks. GDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Groups Consensus Panel (IADPSG) recommendations. We used the Poisson regression with a robust error variance with generalized estimating equations (GEE) estimation analyses to evaluate associations between parabens exposure and GDM risk. RESULTS: A total of 103 (9.5%) women were diagnosed with GDM. We evaluated the associations of GDM risk with urinary MeP, EtP, and PrP (detection rate: >90%), but not with BuP and BzP due to the relatively low detection rate (<50%). After adjustment for potential confounders, urinary EtP was associated with GDM. The risk ratios (RRs) = 1.12 (95% CI: 0.63, 2.01) for the second quartile, RRs = 1.11 (95% CI: 0.64, 1.93) for the third quartile, and RRs = 1.70 (95% CI: 1.02, 2.82) for the highest quartile, compared with the lowest quartile. There was no evidence of associations between urinary MeP or PrP and GDM. CONCLUSIONS: To the best of our knowledge, this is the first report of an association between urinary paraben levels in early pregnancy and GDM. Our findings suggest that exposure to EtP may increase the risk of GDM.

Urinary Metabolites Altered during the Third Trimester in Pregnancies Complicated by Gestational Diabetes Mellitus: Relationship with Potential Upcoming Metabolic Disorders.

Gestational diabetes mellitus (GDM) is a disorder in pregnancy with highest impact in the future life of both mother and newborn. Increasing incidence, economic impact, and potential for severe GDM-related pregnancy complications are some factors that have motivated the deep study of physiopathology, risk factors for developing GDM, and potential biomarkers for its diagnosis. In the present pilot study, we analyzed the urinary metabolome profile of GDM patients in the 3rd trimester of pregnancy, when GDM is already established and the patients are under dietary and pharmacological control. An untargeted metabolomics method based on liquid chromatography⁻mass spectrometry analysis was developed to identify differentially expressed metabolites in the GDM group. We identified 14 metabolites that are significantly upregulated in the urine of GDM patients, and, more importantly, we identified those related with the steroid hormone biosynthesis and tryptophan (TRP) metabolism pathways, which are associated with GDM pathophysiology. Thus, these metabolites could be screened as potential prognostic biomarkers of type two diabetes mellitus, coronary artery disease and chronic renal failure in future follow-up studies with GDM patients.

Urinary metabolic variation analysis during pregnancy and application in Gestational Diabetes Mellitus and spontaneous abortion biomarker discovery.

Pregnancy is associated with the onset of many adaptation processes that are likely to change over the course of gestation. Understanding normal metabolites' variation with pregnancy progression is crucial for gaining insights of the key nutrients for normal fetal growth, and for comparative research of pregnancy-related complications. This work presents liquid chromatography-mass spectrum-based urine metabolomics study of 50 health pregnant women at three time points during pregnancy. The influence of maternal physiological factors, including age, BMI, parity and gravity to urine metabolome was explored. Additionally, urine metabolomics was applied for early prediction of two pregnancy complications, gestational diabetes mellitus and spontaneous abortion. Our results suggested that during normal pregnancy progression, pathways of steroid hormone biosynthesis and tyrosine metabolism were significantly regulated. BMI is a factor that should be considered during cross-section analysis. Application analysis discovered potential biomarkers for GDM in the first trimester with AUC of 0.89, and potential biomarkers for SA in the first trimester with AUC of 0.90. In conclusion, our study indicated that urine metabolome could reflect variations during pregnancy progression, and has potential value for pregnancy complications early prediction. The clinical trial number for this study is NCT03246295.

Maternal urinary phthalate metabolites in relation to gestational diabetes and glucose intolerance during pregnancy.

BACKGROUND: Phthalates are common plasticizer chemicals that have been linked to glucose intolerance in the general population, but there is only limited research on their association with gestational diabetes (GDM). OBJECTIVE: We evaluated the association between 11 urinary phthalate metabolites and GDM, impaired glucose tolerance (IGT), and continuous blood glucose concentration during pregnancy in The Infant Development and Environment Study (TIDES). Based on prior study results, our primary analyses focused on monoethyl phthalate (MEP) in relation to our outcomes of interest. STUDY DESIGN: We used multi-variable logistic regression to examine the odds of GDM and IGT in relation to an interquartile-range (IQR) increase in natural log (ln)-transformed, specific gravity (SG)-adjusted first trimester (T1) and average of T1 and third trimester (T3) ("T1T3avg") phthalate metabolite concentrations. We fit linear regression models to examine the percent change in blood glucose per IQR increase in ln-transformed, SG-adjusted T1 and T1T3avg phthalates. In sensitivity analyses, we examined interactions between exposure and race. We adjusted for maternal age, maternal body mass index, study center, race/ethnicity, parity, and gestational age at glucose testing. RESULTS: In our sample of 705 pregnant women, we observed 60 cases of GDM, 90 cases of IGT, and an average GLT blood glucose of 113.6 ±â€¯27.7 mg/dL. In our primary analysis, T1T3avg MEP was positively associated with GDM ([OR (95% CI) per IQR increase] T1T3avg MEP: 1.61 (1.10, 2.36)). In secondary analyses, most other phthalates were not found to be related to study outcomes, though some associations were noted. Sensitivity analyses indicated possible strong race-specific associations in Asians, though these results are based on a small sample size (n = 35). CONCLUSION: In alignment with our a priori selection, we documented an association between T1T3avg MEP and GDM. Additional phthalate metabolites were also found to be linked to glucose intolerance, with possible stronger associations in certain racial/ethnic subgroups. Given the prevalence of phthalate exposures and the growing evidence of associations with metabolic outcomes, future studies should continue to examine this question in diverse cohorts of pregnant women, particularly in those who may be at higher risk for GDM and IGT.

Antimony in urine during early pregnancy correlates with increased risk of gestational diabetes mellitus: A prospective cohort study.

BACKGROUND: Antimony (Sb) has been associated with type 2 diabetes in previous studies. However, the role of Sb in the incidence of Gestational diabetes mellitus (GDM) remains unclear. OBJECTIVES: We investigated the association between Sb exposure during early pregnancy and the risk of GDM. METHODS: We performed a prospective study of 2093 pregnant women from the Tongji Maternal and Child Health Cohort (TMCHC). Sb concentrations were measured in urine samples during early pregnancy by ICP-MS. The association between urinary Sb concentration and GDM incidence was assessed using robust Poisson regression model after adjustment for confounders. RESULTS: The 95th percentile value of creatinine-corrected Sb (CC-Sb) concentration in the urine of all pregnant women was 1.33 µg/g. The CC-Sb concentrations were significantly higher in women with GDM than those without GDM (median value: 0.49 µg/g vs. 0.38 µg/g, p = 0.001). After adjustment for potential confounders, for each one natural logarithmic unit increase in Sb concentration, there was 29% [adjusted relative risk (RR) = 1.29; 95% confidence interval (CI): 1.06, 1.57] increase in the risk of GDM. Women in the highest tertile for CC-Sb had a 1.92-fold (95% CI: 1.42, 2.60) higher risk of GDM compared with women in the lowest tertile (p-value for trend <0.001). CONCLUSION: To our knowledge, this is the first research of an association between urinary Sb levels during pregnancy and GDM. Our study suggests that pregnant women with higher Sb exposure levels may have a higher risk of GDM and this association remains consistent even after stratification.

Association between urinary parabens and gestational diabetes mellitus across prepregnancy body mass index categories.

Increasing evidence suggests a potential role of endocrine disrupting chemicals (EDCs) in inducing gestational diabetes mellitus (GDM). However, as far as we know, no study has examined the associations between GDM and exposure to parabens, a kind of EDCs. In this study, we explored the association between urinary parabens of pregnant women and GDM and studied the modification effect of prepregnancy body mass index (BMI). Urine samples were collected from 696 pregnant women and parabens were measured, including four alkyl side chain substituted para-hydroxybenzoic acid ester, substituents varying from methyl to butyl (abbreviates as MeP, EtP, PrP and BuP), and benzyl substituted para-hydroxybenzoic acid ester (BzP). Logistic regression models adjusting for potential confounders were used to study the association of parabens and GDM in the overall population, and further stratified analysis by prepregnancy BMI categories was also performed. The detection rates for the five parabens in the urine samples were 97.70% (MeP), 71.26% (EtP), 96.55% (PrP), 15.80% (BuP) and 2.73% (BzP). No significant association was found between parabens and GDM among the overall population. However, significant non-linear associations of PrP and the summed estrogenic activity of parabens with GDM were found in the stratified analysis by prepregnancy BMI in the overweight/obese population, with adjusted odds ratios (aORs) of 3.47 (95% CI: 1.28, 9.42) and 2.87 (95% CI: 1.07, 7.73) for GDM in the second tertile of urinary PrP and the summed estrogen activity, respectively, when compared to the first tertile. Although no statistically significant association between parabens and GDM was found in the overall population, we found that among the overweight/obese pregnant women, who represent a subgroup more prone to GDM, moderately higher levels of PrP and summed estrogenic activity of parabens were significantly associated with an increasing GDM prevalence.

Ghrelin in Serum and Urine of Post-Partum Women with Gestational Diabetes Mellitus.

Women with a previous history of gestational diabetes mellitus (GDM) have a significantly increased risk of developing type 2 diabetes, obesity, and cardiovascular diseases in the future. The aim of the study was to evaluate ghrelin concentrations in serum and urine in the GDM group in the early post-partum period, with reference to laboratory results, body composition, and hydration status. The study subjects were divided into two groups, that is, 28 healthy controls and 26 patients with diagnosed GDM. The maternal body composition and hydration status were evaluated by the bioelectrical impedance analysis (BIA) method. The concentrations of ghrelin in the maternal serum and urine were determined via enzyme-linked immunosorbent assay (ELISA). The laboratory and BIA results of the mothers with GDM were different from those without GDM. Urine ghrelin positively correlated with serum ghrelin and high-density lipoprotein cholesterol (HDL) levels in healthy mothers. There were direct correlations between urine ghrelin and HDL as well as triglycerides levels in the GDM group. Neither the lean tissue index nor body cell mass index were related to the serum ghrelin concentrations in this group. Only the urine ghrelin of healthy mothers correlated with the fat tissue index. Our results draw attention to urine as an easily available and appropriable biological material for further studies.

Urinary Inorganic Arsenic Concentration and Gestational Diabetes Mellitus in Pregnant Women from Arica, Chile.

Introduction: The association of total arsenic exposure with impaired glucose tolerance and gestational diabetes has been shown; however, evidence regarding urinary inorganic arsenic in pregnant women is still limited. Our aim was to evaluate the association between urinary inorganic arsenic concentration and gestational diabetes among pregnant women living in Arica, Chile. Methods: Cross-sectional study of pregnant women receiving care at primary health centers in urban Arica. The exposure was urinary inorganic arsenic concentration, while gestational diabetes was the outcome. The association was evaluated using multiple logistic regression models adjusted by age, education level, ethnicity, and pre-pregnancy body mass index. Results: 244 pregnant women were surveyed. The median urinary inorganic arsenic was 14.95 μg/L, and the prevalence of gestational diabetes was 8.6%. After adjusting, we did not find a significant association between gestational diabetes and inorganic arsenic exposure tertiles (Odds ratio (OR) 2.98, 95% CI = 0.87⁻10.18), (OR 1.07, 95% CI = 0.26⁻4.33). Conclusion: This study did not provide evidence on the relationship between urinary inorganic arsenic concentration and gestational diabetes. Further research is needed to elucidate the factors underlying this association.

Insulin sensitivity assessed using urine C peptide creatinine ratio (UCPCR) in pregnancy: cross-sectional analysis of an English multiethnic cohort.

AIMS: To assess urinary C peptide creatinine ratio (UCPCR) used in a modified Matsuda equation to measure insulin sensitivity (IS) in pregnancy. RESEARCH AND DESIGN METHODS: In this cross-sectional study, two IS measurements were calculated in 73 pregnant women at ~28 weeks of gestation by two separate methods using modified Matsuda equations. The first using the 0 and 120 min serum C peptide concentration during a 75 g oral glucose tolerance test (OGTT) and the second using the 0 and 120 min UCPCR values. The calculated IS measurements from the two methodologies were evaluated using Person's test and linear regression analysis. The relationship between ISOGTT UCPCR and the fasting second void UCPCR and 120 min UCPCR was assessed using Pearson correlation and linear regression analysis after logarithmic transformation of the variables. Statistical analysis was performed using SPSS V.22. RESULTS: The IS measured using serum C peptide (ISOGTTc-pep) in the modified Matsuda equation correlated with the IS measurement using serum UCPCR (ISOGTT-UCPCR) (r 0.704, p<0.0001). A strong correlation was found between the ISOGTT-UCPCR and the fasting UCPCR (r -0.916, p<0.0001), displaying a hyperbolic relationship. CONCLUSION: The UCPCR provides a practical methodology to assess IS and ß-cell function in pregnancy.

Identification of urinary biomarkers for the prediction of gestational diabetes mellitus in early second trimester of young gravidae based on iTRAQ quantitative proteomics.

Gestational Diabetes Mellitus (GDM) has brought great harm to maternal and fetus. Up to now, only a few plasma biomarkers for its early diagnosis have been reported; nevertheless, there is no report about identification of urinary biomarkers for prediction of GDM. Thus, it is necessary to correct this deficiency. In our study, urine samples were collected from 889 healthy young gravidae at the early second trimester (15 to 20 weeks), 69 of whom were subsequently diagnosed with GDM at 24 to 28 weeks. iTRAQ (the isobaric tags for relative and absolute quantification) quantitative proteomics was conducted on sixteen GDM (trial group) and an equal number of matched healthy young gravidae (control group). Validation was performed in 40 cases of each group by ELISA. A total of 1,901 proteins were identified in this study, including 119 significantly differential proteins (fold change ≧1.2 or ≦0.83 and p < 0.05). Compared with control group, 83 differential proteins were increased and 36 proteins were decreased in GDM group. The validation for expression of CD59 and IL1RA showed significant difference and the area under the receiver operating characteristic curve was 0.729 and 0.899, respectively (p < 0.05). The two candidate protein biomarkers (CD59 and IL1RA) in urine could be an early, noninvasive diagnostic predictors of young pravidae with GDM, and IL1RA is stronger diagnostic power than CD59.