Development Of Gestational Diabetes Mellitus Research Articles

Association of BDNF polymorphism with gestational diabetes mellitus risk: a novel insight into genetic predisposition.

Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder during pregnancy with potential long-term health implications for the mother and child. The interplay between genetics and GDM susceptibility remains an area of active research. Recently, brain-derived neurotrophic factor (BDNF) was investigated in relation to obesity and impaired glucose metabolism and pathogenesis. We aimed to investigate the association of common BDNF polymorphisms, with GDM risk in Israeli females. A cohort of 4,025 Israeli women data for BDNF common SNPs was analyzed for potential association with GDM using binary logistic regressions analysis (SPSS 29.0 and R) adjusted for confounding variables (age, T1DM, T2DM, PCOS) under different genetic models. The GDM and Non-GDM genetic frequencies for the BDNF rs925946 Tag-SNP were significantly different. The genetic frequencies were 54.16 %, and 66.91 % for the wild type (GG), 38.88 and 29.64 % for the heterozygotes (TC), and 6.94 and 3.48 % for the risk allele homozygotes (TT) for the GDM non-GDM populations, respectively. Carriers of BDNF rs925946 were significantly associated with higher risk for GDM, following the dominant genetic model (OR=1.7, 95 % CI 1.21-2.39, p=0.002), the recessive genetic model (OR=2.05, 95 % CI 1.04-4.03, p=0.03), and the additive genetic model (OR=1.62, 95 % CI 1.13-2.3, p=0.008). This association persisted after adjusting for age, T1DM, T2DM, and polycystic ovary syndrome (PCOS). Carrying BDNF rs925946 polymorphism predisposes to a higher risk of GDM pathogenesis. Its role and implications warrant further investigation, especially when considering preventive measures for GDM development.

Is gestational diabetes mellitus in lean women a distinct entity warranting a modified management approach?

During pregnancy, insulin resistance and impaired insulin secretion may lead to the development of Gestational Diabetes Mellitus (GDM). Although a higher Body Mass Index (BMI) is often cited as a risk factor for the development of GDM, lean pregnant women are also at risk of developing GDM based on evidence from several studies. It is proposed that insulin deficiency (more than insulin resistance) leads to the development of GDM in women with low BMI (BMI <18.5 kg/m2). Neonates of these women are more at risk of preterm birth and small-for-gestational-age. Given this unique pathophysiology and phenotype, this entity needs a modified management approach. This article aims to raise awareness of GDM in lean women to encourage more research on this topic and create a modified management approach.

A first trimester prediction model and nomogram for gestational diabetes mellitus based on maternal clinical risk factors in a resource-poor setting

BackgroundThe implementation of universal screening for Gestational Diabetes Mellitus (GDM) is challenged by several factors key amongst which is limited resources, hence the continued reliance on risk factor-based screening. Effective identification of high-risk women early in pregnancy may enable preventive intervention. This study aimed at developing a GDM prediction model based on maternal clinical risk factors that are easily assessable in the first trimester of pregnancy in a population of Nigerian women.MethodsThis was a multi-hospital prospective observational cohort study of 253 consecutively selected pregnant women from which maternal clinical data was collected at 8–12 weeks gestational age. Diagnosis of GDM was made via a one-step 75-gram Oral Glucose Tolerance Test (OGTT) at 24–28 weeks of gestation. A GDM prediction model and nomogram based on selected maternal clinical risk factors was developed using multiple logistic regression analysis, and its performance was assessed by Receiver Operator Curve (ROC) analysis. Data analysis was carried out using Statistical Package for Social Sciences (SPSS) version 25 and Python programming language (version 3.0).ResultsIncreasing maternal age, higher body mass index (BMI), a family history of diabetes mellitus in first-degree relative and previous history of foetal macrosomia were the major predictors of GDM. The model equation was: LogitP = 6.358 − 0.066 × Age − 0.075 × First trimester BMI − 1.879 × First-degree relative with diabetes mellitus − 0.522 × History of foetal macrosomia. It had an area under the receiver operator characteristic (ROC) curve (AUC) of 0.814 (95% CI: 0.751–0.877; p-value < 0.001), and at a predicted probability threshold of 0.745, it had a sensitivity of 79.2% and specificity of 74.5%.ConclusionThis first trimester prediction model reliably identifies women at high risk for GDM development in the first trimester, and the nomogram enhances its practical applicability, contributing to improved clinical outcomes in the study population.

Genetic Causal Relationship Between Alanine Aminotransferase Levels and Risk of Gestational Diabetes Mellitus: Mendelian Randomization Analysis Based on Two Samples.

Gestational diabetes mellitus (GDM) is a frequent complication of pregnancy. The specific mechanisms underlying GDM have not yet been fully elucidated. Contemporary research indicates a potential association between liver enzyme irregularities and an increased risk of metabolic disorders, including diabetes. The alanine aminotransferase (ALT) level is recognized as a sensitive marker of liver injury. An increase in ALT levels is hypothesized to be linked to the pathogenesis of insulin resistance and diabetes. Nonetheless, the definitive causal link between ALT levels and GDM still needs to be determined. This investigation utilized two-sample Mendelian randomization (MR) to examine the genetic causation between alanine aminotransferase (ALT) and GDM. We acquired alanine aminotransferase (ALT)-related GWAS summary data from the UK Biobank, Million Veteran Program, Rotterdam Study, and Lifeline Study. Gestational diabetes data were obtained from the FinnGen Consortium. We employed various MR analysis techniques, including inverse-variance weighted (IVW), MR Egger, weighted median, simple, and weighted weighting. In addition to MR-Egger intercepts, Cochrane's Q test was also used to assess heterogeneity in the MR data, and the MR-PRESSO test was used to assess horizontal pleiotropy. To assess the association's sensitivity, a leave-one-out approach was employed. The IVW results confirmed the independent risk factor for GDM development, as indicated by the ALT level (p = .011). As shown by leave-one-out analysis, horizontal pleiotrophy did not significantly skew the causative link (p > .05). Our dual-sample MR analysis provides substantiated evidence of a genetic causal relationship between alanine aminotransferase (ALT) levels and gestational diabetes.

Effect of Physical Activity during Pregnancy on the Risk of Hypertension Disorders and Gestational Diabetes: Evidence Generated by New RCTs and Systematic Reviews.

Hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) are the most common medical complications in pregnancy. Physical exercise is considered to be safe and beneficial during pregnancy. Moreover, pregnancy could be considered as an opportunity for healthcare providers to promote positive lifestyle behavior and optimize the well-being of pregnant women. Since there are few up-to-date reviews evaluating the role of exercise and the risks of developing obstetrical complications, we performed a review to investigate the effects of physical activity and exercise during pregnancy compared to a control group, focusing on the risk of development of HDP and GDM. We searched Medline and Web of Science, including only randomized controlled trials (RCTs) and systematic reviews. This review supports a beneficial effect of exercise and provides evidence that it significantly decreases the risk of HDP and GDM.

SCUBE1 Promotes Gestational Diabetes Mellitus: A Bioinformatics and Experimental Investigation.

Gestational diabetes mellitus (GDM) is one of the most common metabolic diseases in pregnant women, posing significant risks to the life and health of both mothers and fetuses. With improving living standards, the incidence of GDM is increasing rapidly. Therefore, understanding the underlying mechanism of GDM is of paramount importance. We downloaded two datasets from the Gene Expression Omnibus (GEO) database, containing sequencing data specifically related to "gestational diabetes" and "placenta". By merging these two datasets, a mRNA expression dataset was obtained and subjected to bioinformatics analyses. To screen out corresponding genes, differential analysis and weighted correlation network analysis (WGCNA) were carried out. Lasso, support vector machine and random forest analyses were subsequently performed for identifying key genes from the differentially expressed genes (DEGs) jointly screened out through differential analysis and WGCNA. Afterwards, immunoinfiltration and correlation analysis were performed to screen immune cells that play a role in disease progression and explore the correlation between the screened key genes and immune cells, after which Western Blot, quantitative real-time polymerase chain reaction, Immunohistochemistry, methyl thiazolyl tetrazolium, flow cytometry, scratch and Transwell assays were, respectively, performed for verification. For further verification, we found that the expression levels of MAP6D1 and SCUBE1 in embryonic tissues of GDM patients was higher compared to those of healthy pregnant women, which was consistent with the results of bioinformatics analysis. Consequently, SCUBE1 was selected for follow-up experiment. In order to explore the role of SCUBE1 in the development of GDM, we treated the trophoblastic cells HTR-8/SVneo with high glucose, and on this basis downregulated the expression of SCUBE1. Through further analysis, we observed that SCUBE1 had a role in reducing cell activity, migration and invasion, and promoting cell apoptosis. In summary, SCUBE1 promotes the development of GDM by increasing cell apoptosis and reducing cell activity, migration, and invasion.

Gestational Diabetes and the Gut Microbiota: Fibre and Polyphenol Supplementation as a Therapeutic Strategy.

Gestational diabetes mellitus (GDM) is an escalating public health concern due to its association with short- and long-term adverse maternal and child health outcomes. Dysbiosis of microbiota within the gastrointestinal tract has been linked to the development of GDM. Modification of microbiota dysbiosis through dietary adjustments has attracted considerable attention as adjunct strategies to improve metabolic disease. Diets high in fibre and polyphenol content are associated with increased gut microbiota alpha diversity, reduced inflammation and oxidative processes and improved intestinal barrier function. This review explores the potential of fibre and polyphenol supplementation to prevent GDM by investigating their impact on gut microbiota composition and function.

Metabolomic profiling reveals decreased serum cysteine levels during gestational diabetes mellitus progression.

Gestational diabetes mellitus (GDM) is a pregnancy-related metabolic disorder associated with short-term and long-term adverse health outcomes, but its pathogenesis has not been clearly elucidated. Investigations of the dynamic changes in metabolomic markers in different trimesters may reveal the underlying pathophysiology of GDM progression. Therefore, in the present study, we analyzed the metabolic profiles of 75 women with GDM and 75 women with normal glucose tolerance (NGT) throughout the three trimesters. We found that the variation trends of 38 metabolites were significantly different during GDM development. Specifically, longitudinal analyses revealed that cysteine (Cys) levels significantly decreased over the course of GDM progression. Further study showed that Cys alleviated GDM in female mice at gestational day 14.5 possibly by inhibiting phosphoenolpyruvate carboxykinase to suppress hepatic gluconeogenesis. Taken together, these findings suggest that the Cys metabolic pathway might play a crucial role in GDM and that Cys supplementation represents a potential new treatment strategy for GDM patients.

The association between interpregnancy interval and gestational diabetes mellitus: A nationwide register-based study in Finland.

Previous results on the association between interpregnancy interval (IPI) and gestational diabetes mellitus (GDM) have been contradictory. Hence, the aim of this study was to examine the association between IPI and GDM using high-quality nationwide register data. All women with first and second pregnancies during our study period from the National Medical Birth Register during 2004-2018 were considered. A logistic regression model was used to assess the association between the length of the IPI and development of the GDM in the second pregnancy. Women were divided into three groups based on the length of the IPI: short IPI (0-11 months), normal IPI (12-47 months), and long IPI (48+ months). Adjusted odds ratios (aOR) with 95% CI were compared between the groups. A total of 47 078 women were included in the study. We found no evidence of difference when women with short IPI were compared with women with normal IPI (aOR 0.99, 95% CI 0.93-1.05). Women with long IPI had increased odds for the development of GDM when compared with women with normal IPI (aOR 1.28, 95% CI 1.19-1.38). In the logistic regression model for continuous IPI, the total odds for the development of GDM increased as the IPI increased (aOR 1.05 per year, 95% CI 1.03-1.06). The odds for the development of GDM increased as the IPI increased. This study's results serve as a clarion call for proactive measures in GDM prevention. Moreover, they advocate for intensified investigation into the underlying factors contributing to GDM among women with extended IPI. It is imperative that these insights inform both clinical practice and further research agendas, as we strive to safeguard maternal health and well-being.

Phenotypic characterisation of regulatory T cells in patients with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a common complication that occurs during pregnancy. Emerging evidence suggests that immune abnormalities play a pivotal role in the development of GDM. Specifically, regulatory T cells (Tregs) are considered a critical factor in controlling maternal–fetal immune tolerance. However, the specific characteristics and alterations of Tregs during the pathogenesis of GDM remain poorly elucidated. Therefore, this study aimed to investigate the changes in Tregs among pregnant women diagnosed with GDM compared to healthy pregnant women. A prospective study was conducted, enrolling 23 healthy pregnant women in the third trimester and 21 third-trimester women diagnosed with GDM. Participants were followed up until the postpartum period. The proportions of various Treg, including Tregs, mTregs, and nTregs, were detected in the peripheral blood of pregnant women from both groups. Additionally, the expression levels of PD-1, HLA-G, and HLA-DR on these Tregs were examined. The results revealed no significant differences in the proportions of Tregs, mTregs, and nTregs between the two groups during the third trimester and postpartum period. However, GDM patients exhibited significantly reduced levels of PD-1+ Tregs (P < 0.01) and HLA-G+ Tregs (P < 0.05) in the third trimester compared to healthy pregnant women in the third trimester. Furthermore, GDM patients demonstrated significantly lower levels of PD-1+ mTregs (P < 0.01) and HLA-G+ (P < 0.05) mTregs compared to healthy pregnant women in the third trimester. Overall, the proportion of Tregs did not exhibit significant changes during the third trimester in GDM patients compared to healthy pregnant women. Nevertheless, the observed dysregulation of immune regulation function in Tregs and mTregs may be associated with the development of GDM in pregnant women.

The Relationship between Iron Markers, Cortisol and Insulin Resistance in Gestational Diabetes Mellitus

Background: Gestational diabetes mellitus (GDM) is a significant metabolic disorder occurring during pregnancy, associated with serious maternal and fetal complications if left untreated. The global prevalence of GDM emphasizes the urgent need for research into its pathogenesis and contributing factors, including hormonal changes, insulin resistance, and the role of iron metabolism. Objective: The aim of this study was to investigate the relationship between iron markers (hemoglobin, serum iron, and serum ferritin), cortisol, insulin resistance (measured by HOMA-IR), and the development of GDM in pregnant women between 24 and 28 weeks of gestation. Methods: This analytical cross-sectional study included 150 pregnant women, divided into GDM and non-GDM groups based on oral glucose tolerance test results. Iron markers, cortisol, fasting plasma glucose, insulin, and HOMA-IR levels were measured. Data analysis was performed using SPSS version 25, employing descriptive and inferential statistics, including the Mann-Whitney U test for non-normally distributed variables. Results: Women with GDM exhibited significantly higher mean levels of hemoglobin (12.41±0.68 g/dl), serum iron (19.57±1.14 μmol/L), serum ferritin (25.92±2.58 ng/ml), cortisol (451.32±25.20 nmol/L), fasting plasma glucose (6.83±0.46 mmol/L), insulin (12.50±1.72 μU/mL), and HOMA-IR (3.83±0.78) compared to non-GDM participants (p&lt;0.001 for all comparisons). These findings underscore the pronounced biochemical and hormonal alterations associated with GDM. Conclusion: The study identified a significant association between elevated levels of iron markers, cortisol, and insulin resistance with the development of GDM. These findings suggest that monitoring these parameters during pregnancy could be crucial for the early detection and management of GDM. Individualized iron supplementation strategies may be necessary to prevent iron overload and minimize GDM risk.

Bioinformatics-based Identification of Ferroptosis-Related Genes and their Diagnostic Value in Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) is considered a risk factor for heart metabolic disorder in future mothers and offspring. Ferroptosis is a new type of programmed cell death, which may participate in the occurrence and development of GDM. This study aims to identify ferroptosis-related genes in GDM by bioinformatics methods and to explore their clinical diagnostic value. The dataset GSE103552 was analyzed using the Gene Expression Omnibus (GEO) database to screen for differentially expressed genes (DEGs) in GDM. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and proteinprotein interaction (PPI) network were performed. Gene sets for ferroptosis were retrieved in MSigDB and GSVA gene set analysis was performed on the database. Finally, logistic regression was performed to differentiate between GDM patients and controls to screen for diagnostic markers. A total of 179 DEGs were identified in the expression profile of GDM. GO and KEGG enrichment analysis revealed significant enrichment in the TGF-β, p53 signaling pathway, platelet activation, glutathione metabolism, sensory perception of taste, and leukocyte and vascular endothelial cell migration regulation. DEGs (n = 107) associated with the ferroptosis gene set were screened by GSVA analysis. The screened DEGs for disease and DEGs for ferroptosis scores were intersected and 35 intersected genes were identified. PPI identified two key genes associated with GDM as CCNB2 and CDK1. Wilcox-test showed low expression of CCNB2 and CDK1 in GDM. The area under the ROC curve (AUC) of the CCNB2 and CDK1 prognostic model was 0.822. The genes associated with ferroptosis in GDM were CCNB2 and CDK1, which can be used as valid indicators for the diagnosis of GDM.

Aberrant NK cell profile in gestational diabetes mellitus with fetal growth restriction.

Gestational diabetes mellitus (GDM) is a gestational disorder characterized by hyperglycemia, that can lead to dysfunction of diverse cells in the body, especially the immune cells. It has been reported that immune cells, specifically natural killer (NK) cells, play a crucial role in normal pregnancy. However, it remains unknown how hyperglycemia affects NK cell dysfunction thus participates in the development of GDM. In this experiment, GDM mice were induced by an intraperitoneal injection of streptozotocin (STZ) after pregnancy and it has been found that the intrauterine growth restriction occurred in mice with STZ-induced GDM, accompanied by the changed proportion and function of NK cells. The percentage of cytotoxic CD27-CD11b+ NK cells was significantly increased, while the proportion of nourished CD27-CD11b- NK cells was significantly reduced in the decidua of GDM mice. Likewise, the same trend appeared in the peripheral blood NK cell subsets of GDM patients. What's more, after intrauterine reinfusion of NK cells to GDM mice, the fetal growth restriction was alleviated and the proportion of NK cells was restored. Our findings provide a theoretical and experimental basis for further exploring the pathogenesis of GDM.

Association of MTHFD1 G1958A Polymorphism with Gestational Diabetes Mellitus.

Background The MTHFD1 G1958A polymorphism is a common variation in the gene encoding methylenetetrahydrofolate dehydrogenase 1 (MTHFD1), an enzyme crucial for folate metabolism. This study investigated the association between the MTHFD1 G1958A polymorphism, which is involved in folate metabolism, and gestational diabetes mellitus (GDM) risk. Methods A case-control study was conducted and 304 pregnant women (152 with gestational diabetes as cases and 152 healthy pregnantas controls) participated in the study. The polymerase chain reaction-restriction fragment length polymorphisms (PCR-RFLP) techniques were used to determine the MTHFD1 1958G>A polymorphism genotypes. Results Analysis of genotype frequencies revealed a statistically significant difference (p-value < 0.05) between the GDM group and the control group, suggesting a potential association between this gene variant and the development of GDM. Interestingly, while allele frequencies alone did not show a significant association with GDM risk, analysis in a recessive model (both severe and mild forms) demonstrated a strong link between the homozygous AA genotype and increased susceptibility to GDM. Conclusion This study provides the first evidence linking the MTHFD1 G1958A polymorphism and GDM risk in an Indian setting. These findings warrant further investigation into the functional impact of the MTHFD1 G1958A polymorphism and its potential role in the pathogenesis of GDM.

Maternal fasting serum C-peptide concentrations in the first and second trimesters and subsequent risk of gestational diabetes mellitus: A nested case-control study among Chinese women

ObjectiveTo examine the association of serum connecting peptide (C-peptide) concentrations with gestational diabetes mellitus (GDM) risk among Chinese women. MethodsA nested case-control study was conducted on 436 reproductive-aged women, involving 218 GDM cases and 218 controls matched at 1:1 by maternal age, in Beijing, China between January 2016 and December 2017. Fasting serum C-peptide were successively determined at 10–14 and 15–20 weeks of gestation. Restricted cubic spline and logistic regression analyses were utilized, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive capacity of C-peptide for GDM. ResultsFasting serum C-peptide concentrations exhibited a significant decrease from the initial to the subsequent trimester in females with normal glucose tolerance (NGT). For each 1 log ng/mL increase of fasting serum C-peptide during the first and second trimesters, GDM risk increased by 2.38-fold [odds ratio (OR): 2.38, 95% confidence intervals (95%CI): 1.33–4.40] and 3.07-fold (OR: 3.07, 95%CI: 1.49–6.62), respectively. The areas under the ROC curves for the first- and second-trimester C-peptide were 80.4% and 82.4%. ConclusionOur findings revealed a positive correlation between fasting serum C-peptide during the first and second trimesters and the risk of GDM or its subtypes, underscoring the potential of C-peptide as a predictor for GDM development.

Elevated first-trimester neutrophil elastase and proteinase 3 increase the risk of gestational diabetes mellitus and adverse fetal outcomes

BackgroundChronic inflammation plays a vital role in the development of gestational diabetes mellitus (GDM). Studies in mouse models show that neutrophil serine proteases (NSPs), neutrophil elastase (NE) and proteinase-3 (PR3) are important drivers of chronic inflammation with consequent metabolic disturbances. This study evaluated the association of NE and PR3 with GDM development and adverse fetal outcomes.Method(s)This was a prospective cohort study. Serum PR3 and NE concentration was measured in all enrolled pregnant women in the first and the second trimester to determine the connection between NSPs and GDM and adverse fetal outcomes. Logistic regression, spline regression and linear regression analyses were applied to investigate the association of NE or PR3 with GDM development and adverse fetal outcomes. The concentration of NE and PR3 in placental biopsies was evaluated by semi-quantitative analysis of immunohistochemistry staining.Result(s)NE or PR3 concentration in the first trimester, rather than the second, increased more significantly in women with GDM than in those without, regardless of pre-pregnancy body mass index and age. There was a stepwise increase in GDM occurrence as well as comprehensive adverse fetal outcomes across tertiles of NE and PR3. NE and PR3 were positively associated with neutrophil count, pre-pregnancy BMI, plasma glucose level and newborn weight. Logistic regression revealed NE or PR3 to be independent risk factors for the development of GDM and comprehensive adverse fetal outcomes. Spline regression showed a significant increased risk of GDM occurrence and comprehensive adverse fetal outcomes when serum NE concentration exceeded 417.60 ng/mL and a similar result for PR3 and GDM occurrence when the latter exceeded 88.52 ng/mL. Immunohistochemistry data confirmed that enriched NE and PR3 content in placental tissue may have contributed to the development of GDM.Conclusion(s)This work demonstrates that excessive first-trimester NE and PR3 increase the risk of GDM development and comprehensive adverse fetal outcomes.

Association of Maternal Serum Gamma-Glutamyltransfetase Level at First Trimester as a Predictive Biomaker of Gestational Diabetes Mellitus

Introduction: The prevalence of GDM is increasing globally. GDM is associated with many maternal and fetal complications. Hence identifying and treating maternal hyperglycemia is beneficial for both mother and baby. Proper monitoring of women is necessary during pre-conceptional and early pregnancy period to prevent GDM and its complication. Objective: To assess the level of maternal serum Gamma-glutamyltransferase (GGT) as predictor of Gestational Diabetes Mellitus (GDM). Methods: A Prospective cohort study was carried out at Department of Obstetrics and Gynaecology, Dhaka Medical College Hospital, Dhaka from January 2021 to December 2021. Total sample size was 144. Pregnant women attending Obstetric OPD, DMCH at her 1st trimester (8 -12 weeks) without the evidence of GDM, DM, or any comorbid condition and drugs that affects blood glucose level. Data regarding demographic profile, medical and family history (history of chronic hypertension, diabetes mellitus, autoimmune disease, and CKD) were recorded. Obstetric history regarding gravity, parity, past obstetric history was documented. Then a complete physical examination of the subjects including height, weight, blood pressure level was carried out with an appropriate procedure. Period of the gestation was confirmed by recording CRL in early USG. Patient’s fasting blood sugar and 2hrs after 75- gram glucose at first trimester was measured. Results: In the current study 144 pregnant women, at their first trimester (8-12 week) were included, but during follow up about 12 patients were dropped out due to mid trimester abortion, migration to another place and so on. Most of them were primi (56.1%) housewife (75%), had completed their secondary education (59.1%), and about 61.4% belong to middle class family. The clinical parameter like BMI 25.80±4.56kg/m2, gestational age at delivery 38.09±1.28 weeks. The mean ±SD BMI 27.52±4.72 kg/m in GDM group 25.40±4.46 kg/m in Non GDM group. The mean ± SD birth weight was 3.07±0.37 kg in GDM group and 2.86±0.33 in Non GDM group. The difference was statistically non- significant (p&gt;0.05) between two groups. Among 45.45% subjects had GGT level &lt;10 U/L,34.09% had 11-20 U/L and 20.45% had GGT &gt;20 U/L. Among total 132 respondents 25 respondents (18.94%) developed GDM. The total population divided in two groups, Group I (GDM) and Group II (non GDM). Shows that in group A (GGT ≥12.5 U/L) total respondents were 61, GDM developed in 29.50% (n=18), GDM not developed in 70.49% (n=43). On the Other hand in Group B (GGT &lt;12.5 U/L) total respondents were 71, GDM developed in 9.85% (n=07) and GDM not developed in 90.14% (n=64) and p value was 0.004. Conclusion: The result of our study indicated that pregnant women with high GGT (&gt;12.5 U/L) at booking visit had greater risk of developing GDM (72%).Sensitivity, Specificity, PPV ,NPV of this diagnostic test was 72% , 59.81%, 29.50%, 90.14% respectively and accuracy is 94.69%. Among these 132 respondents, those having GGT&gt;12.5IU/L relative risk (RR) of development of GDM is 3.01. As measurement of GGT is easy, inexpensive and easy to carry out, it can be used as a predictive biomarker who are at increased risk for the subsequent development of GDM.

Genetic and inflammatory factors underlying gestational diabetes mellitus: a review.

Gestational diabetes mellitus (GDM) poses a significant global health concern, impacting both maternal and fetal well-being. Early detection and treatment are imperative to mitigate adverse outcomes during pregnancy. This review delves into the pivotal role of insulin function and the influence of genetic variants, including SLC30A8, CDKAL1, TCF7L2, IRS1, and GCK, in GDM development. These genetic variations affect beta-cell function and insulin activity in crucial tissues, such as muscle, disrupting glucose regulation during pregnancy. We propose a hypothesis that this variation may disrupt zinc transport, consequently impairing insulin production and secretion, thereby contributing to GDM onset. Furthermore, we discussed the involvement of inflammatory pathways, such as TNF-alpha and IL-6, in predisposing individuals to GDM. Genetic modulation of these pathways may exacerbate glucose metabolism dysregulation observed in GDM patients. We also discussed how GDM affects cardiovascular disease (CVD) through a direct correlation between pregnancy and cardiometabolic function, increasing atherosclerosis, decreased vascular function, dyslipidemia, and hypertension in women with GDM history. However, further research is imperative to unravel the intricate interplay between inflammatory pathways, genetics, and GDM. This understanding is pivotal for devising targeted gene therapies and pharmacological interventions to rectify genetic variations in SLC30A8, CDKAL1, TCF7L2, IRS1, GCK, and other pertinent genes. Ultimately, this review offers insights into the pathophysiological mechanisms of GDM, providing a foundation for developing strategies to mitigate its impact.

Maternal Serum Copper and Some Metabolic Indexes in Late Second Trimester of Gestational Diabetes Mellitus Pregnancy.

Copper (Cu) is a physiologically important trace element during pregnancy. The study aim is to assess the altered level of serum Cu and its association with some metabolic indexes in Gestational Diabetes Mellitus (GDM). A total of 108 pregnant women (aged 18 - 40, second trimester) are included in the study and divided into two groups (GDM n = 54; pregnant with normal glucose tolerance (NGT), n = 54) after performing a 2-hour 75-g oral glucose tolerance test (OGTT). Maternal blood samples are collected at 26 - 28 gestational week. All biochemical parameters are measured in serum from fasting venous blood. Serum Cu levels are analyzed by flame atomic absorption spectrophotometry (Perkin Elmer AAnalyst 300, USA). Body Mass Index (BMI), insulin sensitivity/resistance, triglyceride-glucose (TyG), TyG-BMI (triglyceride glucose-body mass) indexes are calculated by formulas. The following data were observed: significantly higher levels of serum Cu (p = 0.009), pre-pregnancy BMI (pre-pBMI), BMI at the GDM diagnosis (pBMI), TyG, pregnancy TyG-BMI (pTyG-BMI) p < 0.001, and triglycerides (Tgl) (p = 0.02) in GDM compared to NGT pregnancy. The study presents a positive correlation between serum Cu and pre-pBMI (p < 0.02), pBMI and pTyG-BMI (p < 0.001). Besides, pre-pBMI (mean ≥ 25 kg/m2), pBMI (mean ≥ 30 kg/m2), and pTyG-BMI are associated with 14.5% (OR 1.145, 95% CI: 1.064 - 1.232; p < 0.001), 15.3% (OR 1.153, 95% CI: 1.070 - 1.243; p < 0.001), and 5.9% (OR 1.059, 95% CI: 1.022 - 1.086; p < 0.001) increased risk for GDM development. No association is found between Cu and Tgl levels, fasting plasma glucose e(FPG) and TyG. ROC analysis suggests the serum Cu as a possible risk factor for GDM development. The analysis shows that at a cutoff point of ≥ 31.9 µmol/L, serum Cu presents a sensitivity and specificity of 64.8% and 66.7% in the prediction of GDM development (AUC = 0.659, p < 0.012). After adjustment for maternal age, gestational age, and family predisposition, the odds ratios (ORs) (95% CIs) still show association of Cu levels with increased GDM risk (OR 1.099, 95% CI 1.018 - 1.184, p = 0.013). pTyG-BMI index exhibits a better interaction than TyG index, Tgl, and glucose separately with serum Cu levels where BMI has a mediator's role.

Comparative Evaluation of Adipokine Metrics for the Diagnosis of Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) is one of the most common medical disorders in pregnancy. Adipokines, predominantly secreted by adipose tissue, are involved in numerous metabolic processes. The exact role of adipokines in the pathogenesis of GDM is still not well known, and numerous adipokines have been analysed throughout pregnancy and proposed as biomarkers of GDM. This study aimed to evaluate serum adiponectin, chemerin, lipocalin and apelin levels in GDM and non-GDM women, to assess them as clinically useful biomarkers of the occurrence of GDM and to demonstrate the correlation between the levels of the above adipokines in the blood serum and the increased risk of the development of GDM. The role of these adipokines in the pathogenesis of GDM was also analysed. The statistically significant differences between the levels of adiponectin (7234.6 vs. 9837.5 ng/mL, p < 0.0001), chemerin (264.0 vs. 206.7 ng/mL, p < 0.0001) and lipocalin (39.5 vs. 19.4 ng/mL, p < 0.0001) were observed between pregnant women with GDM and healthy ones. The diagnostic usefulness of the tested adipokines in detecting GDM was also assessed. The research results confirm the hypothesis on the significance of adiponectin, chemerin, lipocalin and apelin in the pathophysiological mechanisms of GDM. We speculate that these adipokines could potentially be established as novel biomarkers for the prediction and early diagnosis of GDM.