Prevalence of Gestational Diabetes and Risk of Progression to Type 2 Diabetes: a Global Perspective

Causal relationship between citrate and gestational diabetes mellitus: a two-sample Mendelian randomization analysis

BACKGROUND

Diabetes Mellitus (GDM) is a common metabolic disease during pregnancy, mainly manifested as impaired glucose tolerance in the middle and late stages of pregnancy. As a key intermediate product in the tricarboxylic acid cycle, citrate has been widely recognized for its role in regulating blood glucose levels. However, the potential association between citrate and impaired glucose tolerance during pregnancy needs further research, The aim of this study is to investigate the relationship between citrate levels in the human body and the incidence of gestational diabetes mellitus.

METHOD

This study adopts a two-sample Mendelian randomization approach, using genetic variants of citrate as instrumental variables, to investigate the causal relationship between citrate and gestational diabetes mellitus (GDM). The research data is derived from the OpenGWAS and FinnGen databases, with single nucleotide polymorphisms (SNPs) related to citrate levels and the incidence of GDM selected as analytical tools. Citrate is designated as the exposure factor, and GDM as the outcome variable. Comprehensive assessments of the causal relationship between the instrumental variables and GDM are conducted using methods such as Inverse Variance Weighted (IVW), MR Egger, Simple Mode, Weighted Median, and Weighted Mode. Additionally, Cochran's Q and I^2 statistics are utilized to evaluate heterogeneity, with visualization provided through funnel plots. To test the robustness of the results, a leave-one-out sensitivity analysis method is employed. Furthermore, the potential pleiotropy in this study is detected using MR Egger.

RESULT

In this study, a total of 6 SNPs related to citrate were included. The MR causal analysis revealed that the relevant genes of citrate had a significant impact on gestational diabetes mellitus in both the Inverse Variance Weighted method (OR = 0.170, 95% CI: 0.032 to 0.896, p = 0.037) and the Weighted Median method (OR = 0.116, 95% CI: 0.016 to 0.844, p = 0.033). The tests for heterogeneity, pleiotropy, and sensitivity used in this experiment all indicated that there were no special interfering factors in this experiment.

CONCLUSION

This study found that there is a negative correlation between the level of citrate in pregnant women and gestational diabetes mellitus.

Association between maternal diabetes and neurodevelopmental outcomes in children: a systematic review and meta-analysis of 202 observational studies comprising 56·1 million pregnancies

BACKGROUND

Maternal diabetes might alter fetal brain development. However, well-designed systematic analyses are needed to comprehensively assess and quantify the association between maternal diabetes and neurodevelopmental outcomes in children. We aimed to synthesise and evaluate the available evidence on the effects of maternal diabetes on neurodevelopmental outcomes in children.

METHODS

For this systematic review and meta-analysis we searched PubMed, Web of Science, Embase, and EBSCO databases from inception to Dec 1, 2024, for studies exploring neurodevelopmental outcomes of children born to mothers with diabetes. The primary outcome was neurodevelopmental disorders, as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition and International Classification of Diseases 11th Revision. Data were extracted from published reports. Data were pooled with random-effects models and presented as risk ratios or standard mean differences with 95% CIs. This study was prospectively registered on PROSPERO (CRD42023395464).

FINDINGS

202 studies, involving 56 082 462 mother-child pairs, were included in the meta-analysis. Of these, 110 (54%) examined gestational diabetes, while 80 (40%) investigated pre-gestational diabetes. Among the total studies reviewed, 169 (84%) exclusively focused on children and adolescents aged up to 18 years. In studies adjusting for at least one key confounder, maternal diabetes was associated with increased risks of all types of neurodevelopmental disorders as well as lower intelligence and psychomotor scores. In studies adjusting for multiple confounders (n=98, 49%), children exposed to maternal diabetes had an increased risk of any neurodevelopmental disorder (risk ratio 1·28; 95% CI 1·24-1·31), autism spectrum disorder (1·25; 1·20-1·31), attention-deficit hyperactivity disorder (1·30; 1·24-1·37), intellectual disability (1·32; 1·18-1·47), specific developmental disorders (1·27; 1·17-1·37), communication disorder (1·20; 1·11-1·28), motor disorder (1·17; 1·10-1·26), and learning disorder (1·16; 1·06-1·26), compared with unexposed children. Maternal pre-gestational diabetes was more strongly associated with the risk of most neurodevelopmental disorders in children than gestational diabetes (risk ratio 1·39; [95% CI 1·34-1·44] vs 1·18 [1·14-1·23]; subgroup difference p<0·0001).

INTERPRETATION

Maternal diabetes is associated with an increased risk of neurodevelopmental disorders and impaired neurodevelopmental performance in children. Further high-quality research is needed to establish causality and clarify the associations between specific types of diabetes and the full spectrum of neurodevelopmental disorders.

FUNDING

The National Natural Science Foundation of China, and the Science and Technology Innovation Program of Hunan Province.

TRANSLATION

For the Mandarin translation of the abstract see Supplementary Materials section.

Investigating predictive factors in treatment response with metformin in patients with gestational diabetes mellitus: a cross-sectional analytical-descriptive study

Objective

As the utilization of metformin for gestational diabetes mellitus (GDM) treatment continues to rise, a substantial segment of these patients will ultimately necessitate insulin during their therapeutic journey. Hence, assessing patients' clinical and laboratory attributes becomes invaluable in determining their likelihood of responding favorably to metformin medication. This discernment aids in selecting an optimal management approach, wherein the patients most likely to benefit significantly from metformin are identified, while alternative therapies like insulin are considered for individuals with a lower probability of treatment response.

Method

This was a cross-sectional analytical-descriptive study of individuals with GDM. Initially, the subject's laboratory results and demographic information were submitted. Following that, metformin was administered to all subjects along with counseling on maintaining a healthy diet and lifestyle. Following a 4-week interval, the patients were reassessed and divided into two groups based on their response to metformin medication and then analyzed.

Result

807 people participated in this study, of which 329 people (40.8%) responded to treatment and the failure rate of metformin treatment was 59.2%. This research revealed that the predictive factors of response to metformin medication were, respectively, the amount of 1-hour oral glucose tolerance test (OGTT) (OR = 62.66), 2-hour postprandial plasma glucose (OR = 54.04), 2-hour OGTT (OR = 17.37), followed by the history of abortion (OR = 14.88), the number of pregnancies (gravida 3 and more) (OR = 5.06) and history of infertility (OR = 2.6).

Conclusion

The current study's findings indicated that to enhance GDM care, metformin prescriptions should be prescribed to patients depending on their clinical characteristics and laboratory results.

The perspectives of healthcare professionals in providing care to women with GDM in high-income nations: A qualitative systematic review

BACKGROUND

Gestational Diabetes Mellitus (GDM) represents a growing challenge worldwide, with significant risks to both women and their babies that extend beyond the duration of the pregnancy and immediate post-partum period. Healthcare professionals (HCPs) play important roles in the screening, diagnosis, treatment and management of women with GDM.

METHODS

For this qualitative systematic review, a comprehensive search strategy explored the electronic databases Web of Science, CINAHL, Medline, and Scopus, as well as the reference lists of the included papers, for primary studies investigating the experiences, perspectives and practices of HCPs providing care to women with GDM in high-income healthcare settings. Studies were assessed with the Crowe Critical Appraisal Tool, and findings were synthesised using the approach described by Thomas and Harden.

RESULTS

This review included 33 articles - 26 qualitative and seven mixed method studies, representing ten high-income nations. The total number of HCP participants represented across the studies is 989. This figure is constituted by medical professionals (n = 226), nurses and midwives (n = 583), allied health (n = 40) and other or not numerically specified HCPs (n = 140). From 149 findings, four major themes and 10 subthemes were constructed. The four major themes are: multidisciplinary collaboration; healthcare practice; organizational factors; and working with women.

DISCUSSION AND CONCLUSION

There are barriers to providing optimal care to women with GDM. Including, time and resource constraints, a lack of consensus in practice guidelines, and variable multidisciplinary collaboration. Moving forward, there needs to be a focus on more explicit guidelines, multidisciplinary collaboration, and appropriate resources to support HCPs in providing care to women to manage the short-term and longer-term risks that are associated with a pregnancy affected by GDM.

Deciphering Shared Gene Signatures and Immune Infiltration Characteristics Between Gestational Diabetes Mellitus and Preeclampsia by Integrated Bioinformatics Analysis and Machine Learning

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are common and serious disorders of pregnancy that threaten maternal safety and perinatal outcomes. Generally, GDM is recognized as an independent risk factor for the development of preeclampsia, while a history of preeclampsia in primiparous women is also a risk factor for GDM in subsequent pregnancies. However, the intricate underlying mechanisms of GDM and PE remain elusive. This study developed a diagnostic prediction model for GDM and PE. It investigated the correlation between shared signature genes and immune infiltration characteristics, by employing bioinformatic analysis combined with a machine learning strategy. The microarray datasets GSE103552 and GSE74341 from the Gene Expression Omnibus (GEO) database were used to obtain differentially expressed genes (DEGs). Then, signature genes were identified from the common DEGs via the methods of random forest (RF) algorithms, and artificial neural network (ANN) models. Furthermore, the immune infiltration patterns associated with GDM and PE were explored and validated in the training and testing sets. Moreover, to uncover the molecular mechanisms involved, an mRNA-miRNA network of target genes was constructed, and potential therapeutic drugs for GDM and PE were explored by querying the Connectivity Map (CMap) database. We obtained 45 DEGs by intersecting upregulated and downregulated DEGs from the GSE103552 and GSE74341 datasets. The results of GO annotation indicated that these 45 DEGs were mainly enriched in the process of cell cycle, and KEGG enrichment analysis indicated significant associations with immune signal transduction pathways and immune-related infectious disease. Six signature genes, namely TRA2A, NPM3, PHF5A, SNORD1C, PLXNA3, and C14orf142, were determined by machine learning models, and a diagnostic prediction model for GDM and PE was constructed based on these key genes, validating the highest prediction in the testing set. Moreover, we found increased infiltration of iDCs and T cell co-inhibition in the GDM group, while neutrophil, Th2 cell, and HLA levels were found to have decreased significantly. The PE group showed a significant increase in mast cells. In addition, the identified key genes were found to have potential associations with various immunocytes, immune functions, and checkpoints in the training and testing sets. Then, a miRNA-gene network analysis predicted several key miRNAs-miR-204, miR-23abc, miR-9, miR-205, and miR-455-5p-that might play significant roles in regulating these DEGs. In addition, the research also identified four potential therapeutic compounds for GDM (prima-1-met, geranylgeraniol, MLN-8054, and LY-364947), along with other drugs (deferiprone, peucedanin, MPEP, and IWR-1-endo) that could be targeted for treating PE. In summary, this work identified six signature genes (TRA2A, NPM3, PHF5A, SNORD1C, PLXNA3, and C14orf142) as potential genetic biomarkers for the diagnostic prediction of GDM and PE. A diagnostic prediction model was constructed based on these key genes, demonstrating strong performance when validated with an independent dataset. Moreover, we investigated the similarities and differences between the two diseases in terms of immune infiltration landscape and analyzed the correlations between key genes and the immune infiltration landscape, which provided insights into the molecular mechanisms underlying the development of GDM and PE. This understanding could pave the way for breakthroughs in identifying new immunotherapeutic targets and strategies for disease prevention and treatment.

Association of CDKAL1 gene polymorphisms variations with gestational diabetes mellitus risk in women: A case-control study and meta-analysis

BACKGROUND

Gestational diabetes mellitus (GDM) has seen a significant rise and has become a growing concern worldwide, especially in Asian populations. Genetic factors, such as variations in the CDKAL1 gene, have been linked to its development. However, existing research on this connection is limited and inconclusive, highlighting the need for further investigation. This study aims to explore the association between CDKAL1 gene polymorphisms and GDM risk in a Chinese population using a comprehensive case-control study and meta-analysis.

METHODS

The SNPscan™ genotyping assay was used to genotype rs7754840 and rs7756992, in 502 control participants and 500 GDM patients. ANOVA, T-test, chi-square test, logistic regression, and other statistical tests were used to determine the differences in genotypes and alleles and their associations to the risk of GDM. Additionally, a meta-analysis of existing studies on CDKAL1 polymorphisms and GDM was performed to provide a broader context and resolve inconsistencies in the literature.

RESULTS

The GDM group had a significantly older average mean age and higher blood pressure, and fasting plasma glucose levels than the control group (P < 0.05). CDKAL1 rs7754840 showed significant associations under codominant homozygous model (CC vs. GG: OR = 1.748; 95% CI: 1.178-2.593; P = 0.006). After adjusting, these results indicated an association between CDKAL1 rs7754840 and increased risk of GDM in the codominant model (OR = 1.715; 95% CI: 1.133-2.595; P = 0.011). However, further analysis revealed no significant associations under all genetic models for CDKAL1 rs7756992. The study found that individuals under 30 with the rs7754840 CC genotype had higher fasting glucose and postprandial glucose levels (P < 0.05) compared to those with the GG genotype. Figure 3 A demonstrated a modest association between the CDKAL1 and GDM susceptibility (OR 1.16, 95% CI 1.104-1.29, P = 0.0258).

CONCLUSION

Individuals with the CDKAL1 rs7754840 polymorphism was associated to an increased risk of GDM, whereas rs7756992 did not show significant association with GDM risk. These results provide a theoretical foundation for GDM testing to mitigate its associated complications by enhancing our ability to predict, prevent and manage GDM. Ultimately improving outcomes for both mothers and their children. This research contributes to the growing evidence of genetic predisposition to GDM and highlights the importance of CDKAL1 as a potential genetic marker for GDM risk assessment.

The recurrence risk of gestational diabetes according to the number of abnormal values in the oral glucose tolerance test

INTRODUCTION

Oral glucose tolerance test (OGTT) results may be used to estimate the risk of recurrent gestational diabetes mellitus (GDM) in a subsequent pregnancy in the different study settings. This study assesses the association between the number of abnormal glucose values in the OGTT in the first pregnancy and GDM recurrence in a subsequent pregnancy in a Nordic cohort.

MATERIAL AND METHODS

This register-based cohort study included 1677 women who had their first singleton delivery in 2009, underwent a 75 g 2-h OGTT during the pregnancy, and gave birth at least once more within 10 years according to the Finnish Medical Birth Register. The cut-off values were as follows: ≥5.3 mmol/L at fasting, ≥10.0 mmol/L at 1 h, and ≥8.6 mmol/L at 2 h. The odds ratio (OR) for GDM recurrence in the second pregnancy was analyzed via multivariable logistic regression adjusted for other potential factors associated with recurrence risk.

RESULTS

During the first pregnancy, GDM was diagnosed in 331 (24.5%) women based on one (n = 250) or two or three (n = 81) abnormal glucose values in the OGTT. The total recurrence rate for GDM in the subsequent pregnancy was 56.2%. The rate differed significantly between women with one (51.6%) and women with two or three (70.4%) abnormal values in first-pregnancy OGTT. Compared with those with normal OGTT results, the adjusted OR (aOR) for GDM in the subsequent pregnancy in women with one abnormal glucose value was 6.00 (95% CI, 4.34-8.30), while it was 13.37 (7.52-23.76) in women with two or three abnormal values. The odds for GDM recurrence among those with two or three abnormal glucose values was double compared to those with only one abnormal value (aOR 2.03, 1.12-3.68).

CONCLUSIONS

Primiparous women with one abnormal glucose value in the first OGTT have remarkable odds of GDM recurrence, with the odds doubling when there are two or three abnormal values during the first pregnancy. These findings can be used when planning effective counseling, prevention, and screening strategies for GDM in the subsequent pregnancy.

DUSP9-mediated inhibition of IRS1/PI3K/AKT pathway contributes to insulin resistance and metabolic dysfunction in gestational diabetes mellitus

BACKGROUND

Gestational diabetes mellitus (GDM) is a common pregnancy complication associated with adverse maternal and fetal outcomes. Recent studies suggest a role for dual-specificity phosphatase 9 (DUSP9) in insulin resistance and metabolic dysregulation, though its specific contribution to GDM remains unclear. This study aims to investigate the function of DUSP9 in GDM pathophysiology and its underlying molecular mechanisms.

METHODS

We analyzed DUSP9 expression in umbilical cord blood and placental tissues from GDM patients (n = 16) and healthy controls (n = 14) using RT-qPCR and western blot assays. In vitro, functional assays were conducted on high glucose-induced HTR-8/SVneo trophoblast cells to evaluate the effects of DUSP9 knockdown on cell viability, apoptosis, and insulin signaling. In vivo, a GDM mouse model was constructed, and lentivirus-mediated shRNA was used to downregulate DUSP9 expression. Furthermore, metabolic parameters, including insulin resistance indices, lipid metabolism, and placental apoptosis were assessed, along with the phosphorylation status of key proteins in the IRS1/PI3K/AKT pathway.

RESULTS

We first observed that DUSP9 expression was significantly upregulated in the umbilical cord blood and placental tissues of GDM patients compared to healthy controls (p < 0.01). Using high glucose-induced HTR-8/SVneo trophoblast cells to mimic GDM conditions, we found that downregulation of DUSP9 increased cell viability and inhibited apoptosis (p < 0.01). Mechanistically, co-immunoprecipitation and pull-down assays demonstrated that DUSP9 directly interacts with insulin receptor substrate 1 (IRS1) and inhibits HG-mediated IRS1 phosphorylation at Tyr632, impairing downstream insulin signaling (p < 0.01). In vivo, a GDM mouse model revealed elevated DUSP9 expression, along with significant metabolic dysfunction, including insulin resistance and increased placental apoptosis (p < 0.01). Lentivirus-mediated knockdown of DUSP9 in these mice ameliorated insulin resistance, improved lipid metabolism, and reduced placental apoptosis by improving fasting glucose and insulin levels, lipid profiles, and decreased apoptotic markers (p < 0.01). Moreover, DUSP9 knockdown in these mice promoted activation of the IRS1/PI3K/AKT signaling pathway (p < 0.01).

CONCLUSIONS

DUSP9 contributes to GDM progression by inhibiting the IRS1/PI3K/AKT pathway, leading to insulin resistance and metabolic dysfunction. The knockdown of DUSP9 ameliorates key pathological features of GDM, including insulin resistance, impaired lipid metabolism, and placental apoptosis, suggesting that targeting DUSP9 may represent a potential therapeutic strategy for GDM.

Gestational Diabetes and Risk of Stroke Among US Black Women

BACKGROUND

There is a paucity of evidence on whether gestational diabetes (GDM) is a risk factor for cerebral vascular disease for Black women and lack of data on incident stroke as end point.

METHODS

We conducted a large prospective cohort study of Black women across the United States and assessed the association between self-reported history of GDM and incident stroke. The study began when participants became parous or enrolled in 1995. We followed up 41 143 parous Black women who were free of cerebral vascular disease or cancer and followed up until incident stroke, death, or the end of 2021. Our exposure was self-reported history of GDM, and outcome was incident stroke. Multivariable Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% CIs, adjusting for major known risk factors for stroke.

RESULTS

A total of 1495 incident stroke cases were identified among 41 143 Black women from 1995 until 2021 (881 505 person-years of follow-up). Black women with a history of GDM had a consistent 1.4-fold increased risk of stroke compared with those with a healthy pregnancy (age-adjusted HR, 1.44 [95% CI, 1.14-1.82]; multivariable HR, 1.41 [95% CI, 1.11-1.79]). Compared with healthy parous women with neither GDM nor type 2 diabetes, women with a history of both had a 2.6-fold increased stroke risk (multivariable HR, 2.59 [95% CI, 1.88-3.57]); women with only type 2 diabetes have 2-fold increased stroke risk (multivariable HR, 2.04 [95% CI, 1.79-2.32]); women with a history of GDM but no progression to type 2 diabetes do not have an increased risk of stroke (multivariable HR, 1.22 [95% CI, 0.86-1.73]).

CONCLUSIONS

In this large prospective study of Black women, a vulnerable population at high risk for stroke, a history of GDM increased stroke incidence by 41%. There was no elevated risk of stroke for Black women with a history of GDM and no progression to type 2 diabetes, while the stroke risk increased by 2.6-fold for Black women with GDM and progression to type 2 diabetes. Our results highlight the importance of consideration of history of GDM for stroke early prevention, especially Black women with progression to T2DM after GDM.

Study on MTHFR (C677T & A1298C) Gene Polymorphisms in the Condition of Glucose Intolerance During Pregnancy

INTRODUCTION

Gestational diabetes mellitus (GDM) is a prevalent medical complication in pregnancy, characterized by glucose intolerance. The global expected prevalence of GDM is approximately 15.1%. This study builds upon previous research by investigating elevated hematological parameters and exploring MTHFR gene polymorphisms in GDM.

MATERIALS AND METHODS

This study included 304 pregnant women, comprising 152 patients with GDM and an equal number of normal pregnant women. Employing PCR-RFLP techniques, we identified MTHFR gene polymorphisms (C677T & A1298C) associated with gestational diabetes.

RESULTS

Significant associations were found in gestational age and platelet count, indicating their relevance to GDM risk. The odds ratios for both MTHFR A1298C (p value: 0.034; OR = 0.7; 95% CI: 0.5021-0.9758) and MTHFR C677T (p value: 0.008; OR = 0.5453; 95% CI: 0.3292-0.9011) gene polymorphisms demonstrated an increased risk of GDM development.

CONCLUSION

The study reveals that elevated platelet count and polymorphs increase the risk of developing GDM in pregnant women. Gestational age also plays a role. The study also finds a link between the MTHFR C677T SNP and the MTHFR A1298C gene polymorphism and the risk of gestational diabetes in Andhra Pradesh. This gives us new information about genetic and hematological factors.

Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus

BACKGRUOUND

Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.

METHODS

High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.

RESULTS

Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.

CONCLUSION

Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Timing of eating and glycemic control during pregnancy: A systematic review

AIMS

Glycemic dysregulation during pregnancy is common and increases risk of adverse birth outcomes and future chronic disease. Timing of eating is known to influence glycemic control but has not been thoroughly examined in the context of pregnancy. We systematically reviewed the literature assessing timing of eating and glycemic outcomes during pregnancy.

DATA SYNTHESIS

PubMed, CINAHL, EMBASE, and Web of Science were searched for studies published before March 2024. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered the review with PROSPERO (CRD42024574992). Eligible studies were interventional or observational and collected quantitative data on the association of timing of eating with glycemic outcomes in pregnant persons with or without gestational diabetes mellitus (GDM). 1804 articles were evaluated for inclusion, of which 14 articles met criteria (from 5 interventional and 8 observational studies).

CONCLUSIONS

Timing of eating was associated with glycemic outcomes independent of GDM status; later timing and a shorter overnight fasting duration were associated with poorer glycemic control. Timing considerations may be a valuable addition to recommendations for glycemia management during pregnancy.

Correlation of perfluoroalkyl and polyfluoroalkyl substance levels during pregnancy with gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are a major class of contaminants in recent years. Pregnant women are more susceptible to the influence of these compounds, which could heighten the risk of developing gestational diabetes mellitus (GDM). This study aims to conduct an updated systematic review and meta-analysis to determine the correlation between PFAS exposure during pregnancy and the risk of developing GDM and delve into their dose-response relationship.

METHODS

Pubmed, EMBASE, Web of Science, and Cochrane Library databases were searched. Data were statistically analyzed using Stata 15.0. Fixed-effects (FEM) or random-effects (REM) models were used to combine STD mean difference (SMD) or odds ratio (OR) and 95% confidence intervals (CIs) according to heterogeneity. Dose-response meta-analyses were performed when applicable.

RESULTS

A total of 12 papers were included in this study. Meta-analysis results indicated significantly higher levels of PFOA, PFBS, and PFUnDA in GDM patients compared to healthy pregnant women. Pregnant women exposed to high levels of PFOA and PFBS had a significantly increased risk of developing GDM, with ORs of 1.513 and 1.436, respectively. Dose-response analyses indicated that for each 1 ng/ml increase in PFOA and PFBS exposure, the risk of GDM increased by 0.3% and 11.7%, respectively. In contrast, no significant associations were observed between high exposure to other PFAS compounds, such as PFNA, PFHxS, and PFOS, and the development of GDM. Subgroup analyses suggested that PFOA, PFBS, and PFOS levels were higher in GDM patients from China compared to those from Western countries. The differences in PFOA and PFOS levels between GDM and normal pregnant women were more pronounced during late pregnancy.

CONCLUSION

Exposure to PFOA, PFBS, and PFUnDA during pregnancy is associated with an increased risk of GDM. Given the elevated risk, particularly in the Chinese population, it is crucial to reduce exposure to these substances, especially from the preconception period onward.

Metabolic profiling and early prediction models for gestational diabetes mellitus in PCOS and non-PCOS pregnant women

BACKGROUND

Gestational diabetes mellitus (GDM) is the most common pregnancy complication, significantly affecting maternal and neonatal health. Polycystic ovary syndrome (PCOS) is a common endocrine disorder characterized by metabolic abnormalities, which notably elevates the risk of developing GDM during pregnancy.

METHODS

In this study, we utilized ultra-high-performance liquid chromatography for untargeted metabolomics analysis of serum samples from 137 pregnant women in the early-to-mid-pregnancy. The cohort consisted of 137 participants, including 70 in the PCOS group (36 who developed GDM in mid-to-late pregnancy and 34 who did not) and 67 in the non-PCOS group (37 who developed GDM and 30 who remained GDM-free). The aim was to investigate metabolic profile differences between PCOS and non-PCOS patients and to construct early GDM prediction models separately for the PCOS and non-PCOS groups.

RESULTS

Our findings revealed significant differences in the metabolic profiles of PCOS patients, which may help elucidate the higher risk of GDM in the PCOS population. Moreover, tailored early GDM prediction models for the PCOS group demonstrated high predictive performance, providing strong support for early diagnosis and intervention in clinical practice.

CONCLUSIONS

Untargeted metabolomics analysis revealed distinct metabolic patterns between PCOS patients and non-PCOS patients, particularly in pathways related to GDM. Based on these findings, we successfully constructed GDM prediction models for both PCOS and non-PCOS groups, offering a promising tool for clinical management and early intervention in high-risk populations.

Diabetes and prediabetes among women universally screened for gestational diabetes: a multi-ethnic, population-based, prospective study with eleven years follow-up

BACKGROUND

Gestational diabetes (GDM) is a strong risk factor for later development of diabetes. However, data are scarce on the long-term risk for diabetes or prediabetes diagnosed by HbA1c, in non-selected, multi-ethnic populations universally screened for GDM using the WHO2013 criteria. We aimed to investigate the development of diabetes or prediabetes eleven years after the index pregnancy and identify risk factors in pregnancy or shortly after.

METHODS

A population-based cohort study of 360 women with complete eleven years follow-up data for diabetes (HbA1c ≥ 48 mmol/mol) or prediabetesADA (HbA1c 39-47 mmol/mol). Women were enrolled in gestational week 15 and universally screened with an oral glucose tolerance test in week 28. We performed least absolute shrinkage and selection operator (LASSO) regression to identify predictors of future diabetes or prediabetesADA and constructed a nomogram to predict individual risks.

RESULTS

Diabetes or prediabetesADA combined, was found in 26.9%, and the prevalence was slightly higher in previous GDM compared with non-GDM women (35.6% versus 23.5%; p = 0.019). The relative risk (RR) for developing diabetes or prediabetesADA was moderately elevated in GDM compared with non-GDM women (1.4 [1.0, 1.9], p = 0.035). Seven women (1.9%) had diabetes and all of these except for one, had previous GDM. Hence, the crude prevalence was 5.8% among GDM women vs. 0.4% among non-GDM women. The RR for developing diabetes was substantially higher in GDM vs. non-GDM women (14.8 [2.6, 277.1], p = 0.012). PrediabetesADA was found in 25% and the RR for prediabetesADA was not significantly increased for GDM compared to non-GDM women (1.3 [0.9, 1.8], p = 0.143). Among Europeans, 17.0% had diabetes or prediabetesADA, compared to 43.0% among South Asians (p < 0.001) and 34.4% among other ethnicities (p = 0.002). The most significant predictors identified from the LASSO were HbA1c measured in early pregnancy, ethnicity, and a family history of diabetes.

CONCLUSIONS

The risk for developing diabetes was low, overall and among GDM women. Still GDM represented a strong risk for diabetes, but not for prediabetesADA. HbA1c early in pregnancy, non-European ethnicity, and a family history of diabetes were the strongest risk factors for developing diabetes or prediabetesADA.

TRIAL REGISTRATION

STORK G2 Women and Risk of Diabetes. NCT03870724 (ClinicalTrials.gov). February 27th, 2019.

Development and validation of a prediction model for gestational diabetes mellitus risk among women from 8 to 14 weeks of gestation in Western China

OBJECTIVES

To develop a clinically applicable and promotable prediction model for assessing the risk of gestational diabetes mellitus (GDM) within the context of primary healthcare institutions.

METHODS

The construction and the internal validation of the prediction model involved a cohort of 6,216 pregnant women observed from January 2019 to June 2019 in a Class A tertiary hospital in western China. External validation was subsequently conducted with 443 pregnant women from October 2020 to June 2021. Core characteristics were identified and the model was established using the least absolute shrinkage and selection operator (LASSO) regression. Internal validation was performed using the Bootstrap method. Model evaluation included discrimination and calibration tests, decision curve analysis (DCA), and the clinical impact curve. Visualization of the model was achieved through a static nomogram and a risk-scoring model.

RESULTS

The simplified prediction model possessed seven variables, including age, prepregnancy body mass index (BMI), polycystic ovary syndrome (PCOS), history of GDM, family history of diabetes, fasting plasma glucose (FPG), and urine glucose. This model exhibited a predictive accuracy, as reflected by a C-index of 0.736 (95% CI: 0.720 ~ 0.753) in the training set. The C-indexes were 0.735 and 0.694 in the internal and external testing set. Well-fitted calibration curves, the DCA curve, and the clinical impact curve demonstrated the feasibility of the simplified prediction model. For enhanced clinical application, the static nomogram and the risk-scoring model were employed to visualize the model.

CONCLUSIONS

This study developed a prediction model for assessing the risk of GDM among women from 8 to 14 weeks of gestation in western China. The model demonstrated moderate discriminatory ability, well-fitted calibration, and convenient visualization, suggesting its suitability for implementation and widespread adoption, particularly within the context of primary healthcare institutions.

The impact of environmental and dietary exposure on gestational diabetes mellitus: a comprehensive review emphasizing the role of oxidative stress

Gestational diabetes mellitus (GDM) is a common pregnancy complication closely associated with maternal oxidative and antioxidant imbalance, known as oxidative stress. Environmental and dietary exposure plays an important role in inducing oxidative stress during pregnancy. This review aims to provide an in-depth analysis of the role of oxidative stress induced by environmental and dietary exposure in GDM while incorporating current research frontiers. Environmental pollution, smoking, excessive nutrition, and unhealthy eating habits such as a high-fat diet and vitamin deficiency, may contribute to the generation and accumulation of reactive oxygen species (ROS), leading to oxidative stress. Within the pathway of oxidative stress in GDM, the production and clearance mechanisms of ROS play a pivotal role. Relevant studies have demonstrated that ROS production is closely linked to insulin resistance, adipose tissue accumulation, inflammation, and other pathological processes. Antioxidant substances like vitamins C and E or glutathione can mitigate oxidative stress damage on pregnant women and fetuses by scavenging ROS. Currently, there remain several cutting-edge issues regarding the involvement of the oxidative stress pathway in GDM pathogenesis as well as its relationship with environmental and dietary factors, for instance: how to reduce maternal oxidative stress levels through dietary adjustments or lifestyle modifications; how antioxidant substances can be utilized for intervention treatment; and accurate assessment methods for maternal oxidative stress status along with its association with GDM risk. In conclusion, environmental and dietary factors exert significant influence on GDM pathogenesis while highlighting increasing attention toward understanding the role played by the oxidative stress pathway within this context. In-depth research endeavors within this field are anticipated to offer novel insights into prevention strategies as well as therapeutic approaches for GDM.

NRF2 deficiency leads to inadequate beta cell adaptation during pregnancy and gestational diabetes

The late stages of mammalian pregnancy are accompanied by a mild increase in insulin resistance likely due to enhanced glucose demand of the growing fetus. Therefore, as an adaptive process to maintain euglycemia during pregnancy, maternal β-cell mass expands leading to increased insulin release. Defects in functional β-cell adaptive expansion during pregnancy can lead to gestational diabetes mellitus (GDM). While the exact mechanisms that promote GDM are poorly understood, GDM is associated with inadequate functional β-cell mass expansion and with a systematic increase of oxidative stress. Here, we show that NRF2 levels are upregulated in mouse β-cells at gestational day 15 (GD15). Inducible β-cell-specific Nrf2 deleted (βNrf2KO) mice display reduced β-cell proliferation, increased β-cell oxidative stress and lipid peroxidation, compromised β-cell function, and elevated β-cell death, leading to impaired β-cell mass expansion and dysregulated glucose homeostasis towards the end of pregnancy. Importantly, the gestational hormone 17-β-estradiol (E2) increases NRF2 levels, and downregulation of NRF2 suppresses E2-induced protection of β-cells against oxidative stress, suggesting that E2 exerts its antioxidant effects through activation of NRF2 signaling in β-cells. Collectively, these data highlight the critical role of NRF2 in regulating oxidative stress during the adaptive response of β-cells in pregnancy and identify NRF2 as a potential therapeutic target for GDM treatment.

The Immunohistochemical and Bioinformatics Analysis of the Placental Expressions of Vascular Cell Adhesion Protein 1 (VCAM-1) and High Mobility Group Box 1 (HMGB1) Proteins in Gestational Diabetic Mothers

OBJECTIVE

  We aimed to examine both the expression levels of high mobility group box 1 (HMGB1) and vascular cell adhesion molecule-1 (VCAM-1) proteins in the placentas of pregnant women with gestational diabetes mellitus (GDM) and control groups by immunohistochemical (IHC) method.

MATERIAL AND METHODS

  An experimental case-control study was conducted, including 40 pregnant women complicated with GDM and 40 healthy pregnant women. Placental tissues obtained following cesarean delivery were subjected to routine tissue monitoring. The placental sections were stained with VCAM-1 and HMGB1 immunostains and subjected to IHC examination under a light microscope. H-score (HS) was used to evaluate the results of IHC staining by semi-quantitative analysis. Pathway analysis in Cytoscape software identified GDM-associated proteins within HMGB1 and VCAM-1 interaction networks, followed by GO analysis to explore associated biological processes.

RESULTS

  Placental HGMB1 expression was significantly increased in the GDM group compared to the control group (p<0.001). However, placental VCAM-1 expression was found to be statistically similar in GDM and control groups (p=0.584). The shared 19 proteins were identified between HMGB1 and GDM, and 13 between VCAM-1 and GDM, with notable GO biological process terms such as immune system activation for HMGB1 and interleukin-6 regulation for VCAM-1 associated with GDM.

CONCLUSION

  We consider that GDM-related inflammation and oxidative stress may contribute to tissue damage and inflammation by increasing placental HMGB1 expression. The blockade of HMGB1 and its receptors might represent a promising therapeutic approach to control inflammation in GDM. Understanding the distinct roles of HMGB1 and VCAM-1 may provide valuable insights for the development of targeted therapies aimed at mitigating the inflammatory processes associated with GDM and improving maternal and fetal outcomes.

Vitronectin stimulates hepatic gluconeogenesis by activating the cAMP/PKA/CREB axis in the liver

Vitronectin, a protein derived the human placenta, has been identified as an inducer of insulin resistance in trophoblast cells in gestational diabetes mellitus (GDM). As a secreted protein, vitronectin may have systemic effects on dysregulated glucose metabolism in GDM. To address this speculation, we generated a GDM mouse model using high-fat diet-induced obese mice. Consistent with findings in placentas of GDM patients, GDM mouse placentas showed higher vitronectin expression, accompanied by increased serum vitronectin levels. Reduced insulin signaling transduction was observed in both the placentas and livers of GDM mice, along with enhanced hepatic gluconeogenesis. To further explore the role of vitronectin in hepatic gluconeogenesis, we constructed an adeno-associated virus expressing Vtn (AAV-VTN), which was administered to mice via tail vein injection. In AAV-VTN-treated mice, glucose production from exogenous pyruvate increased, and the expression of gluconeogenic genes in the liver was upregulated, indicating that hepatic gluconeogenesis was stimulated by vitronectin. Mechanistically, vitronectin binds to its receptor CD51/61, activating the cAMP/PKA/CREB axis in hepatocytes, thereby promoting hepatic gluconeogenesis. In summary, our findings suggest that placenta-derived vitronectin plays a critical role in inducing insulin resistance in the liver in GDM. Moreover, vitronectin stimulates hepatic gluconeogenesis through activation of the cAMP/PKA/CREB axis. These results point to vitronectin as a potential therapeutic target for managing hyperglycemia in GDM.

The impact of lowering the blood glucose cut-off values in gestational diabetes mellitus on maternal and perinatal outcomes

BACKGROUND

Gestational diabetes mellitus (GDM) is associated with a risk of giving birth to neonates large for gestational age (LGA). Giving birth to a LGA child increases the risk of maternal and perinatal complications. In Sweden, the blood glucose level required for GDM diagnosis has been lowered, resulting in an increased number of women receiving a GDM diagnosis.

PURPOSE

The study aimed to determine whether the change in diagnostic criteria for GDM impacted the incidence of LGA and the assessment of additional maternal and perinatal complications.

METHODS

This retrospective cohort study involved 1237 women diagnosed with GDM. Among them, 92 delivered infants with LGA, 31 delivered infants small for gestational age (SGA), and 1111 delivered infants appropriate for gestational age (AGA). The primary outcome was to compare the incidence of LGA in the different cohorts based on the year they gave birth. Women without GDM at the same periods and their offspring were also analysed.

RESULTS

The incidence of LGA decreased following the change in diagnostic criteria for GDM (OR 0.43; CI 95 %, 0.27-0.68), a result that remained consistent after adjusting for known risk factors (aOR 0.44; CI 95 %, 0.27-0.7).

CONCLUSION

Lowering blood glucose cut-off values was associated with reduced risk of LGA. Compared to the group of mothers without GDM, the intervention did not appear to account for the lower incidence of LGA. Instead, the results suggest a dilution effect, indicating that mothers included after the change were healthier, exhibiting milder diabetes and, therefore, showed improved outcomes.

THE CLINICAL TRIAL REGISTRATION NUMBER

NCT04794283.

Psychosocial, Behavioral, and Medical Drivers of Gestational Diabetes among Racial-Ethnic Groups

Certain racial and ethnic groups have historically been labeled "high-risk" for the development of gestational diabetes mellitus (GDM). Our objective was to identify the psychosocial, behavioral, and medical factors associated with GDM and determine if they differ by race/ethnicity.Secondary analysis of a multicenter, prospective cohort study of pregnant nulliparous individuals with singleton gestations (2010-2013). The primary outcome was GDM. Psychosocial, behavioral, and medical characteristics were compared by self-reported race/ethnicity. Multivariable logistic regression with backward selection identified factors associated with GDM. Interaction terms between race/ethnicity and risk factors were tested.Of 8,672 pregnant individuals, 61% were non-Hispanic White, 13% non-Hispanic Black, 17% Hispanic, 4% Asian, and 5% other. The incidence of GDM differed by race/ethnicity with 4% non-Hispanic White, 3% non-Hispanic Black, 5% Hispanic, 11% Asian, and 5% other (p < 0.001). Of 34 psychosocial, behavioral, and medical factors, those associated with GDM were parent with history of diabetes (adjusted odds ratio [aOR]: 1.72; 95% confidence interval [CI]: 1.33-2.23), non-English language (aOR: 2.57; 95% CI: 1.14-5.79), daily calorie intake (aOR: 1.18; 95% CI: 1.08-1.29), daily fiber intake (aOR: 0.84; 95% CI: 0.75-0.94), maternal age (aOR: 1.53; 95% CI: 1.37-1.70), prepregnancy BMI (aOR: 1.21; 95% CI: 1.02-1.44), and waist circumference (aOR: 1.21; 95% CI: 1.03-1.43). These associations did not differ based on race/ethnicity (interaction p-values > 0.1).Replacing race/ethnicity as a risk factor for GDM with significant upstream psychosocial, behavioral, and medical factors should be considered. · GDM varies in incidence based on race.. · GDM was linked to a parent with various factors.. · These factors are the history of diabetes, non-English language, and daily calorie intake.. · These factors also include lower daily fiber intake, maternal age, prepregnancy BMI, and waist circumference.. · The psychosocial, behavioral, and medical factors associated with GDM did not differ based on race/ethnicity..

Association between gestational diabetes mellitus and offspring health: a two-sample mendelian randomization study

BACKGROUND

Gestational diabetes mellitus (GDM) constitutes a significant contributor to maternal and fetal morbidity, which is observed to be associated with future risks of offspring health. Nevertheless, it is essential to acknowledge that observational findings may be susceptible to residual confounding and bias.

METHODS

To investigate the association of GDM with offspring health, a genome-wide genetic association study employing Mendelian Randomization (MR) is conducted between May 31 and November 30, 2023. The inverse-variance-weighted (IVW) is utilized in the primary analysis stage. The study data of the majority patients are European ancestry, which are sourced from the IEU open genome-wide association study project.

RESULTS

Genetically predicted GDM is associated with an increased risk of various short- and long-term health problem in offspring. For fetal and neonatal conditions, GDM is linked to an elevated risk of preterm delivery [ odd ratio (OR) = 1.150, false discovery rate (FDR)-adjusted PIVW = 0.009] and placental disorders (OR = 2.143, FDR-adjusted PIVW = 0.028). In respiratory diseases, it is associated with a higher likelihood of influenza (OR = 1.175, FDR-adjusted PIVW = 0.008), bacterial pneumonia (OR = 1.141, FDR-adjusted PIVW = 0.008), congenital malformations of the respiratory system (OR = 1.673, FDR-adjusted PIVW = 0.033), influenza with pneumonia (OR = 1.078, FDR-adjusted PIVW = 0.008), and need for non-invasive ventilation (OR = 1.265, FDR-adjusted PIVW = 0.028). In terms of neurodevelopmental and psychiatric outcomes, GDM is linked to a higher risk of cerebral palsy (OR = 1.721, FDR-adjusted PIVW = 0.008). For urinary conditions, GDM increases the risk of acute tubulo-interstitial nephritis (OR = 1.098, FDR-adjusted PIVW = 0.008). No association is identified between genetically predicted GDM and major digestive diseases, such as gastroesophageal reflux, or cardiovascular conditions in offspring.

CONCLUSIONS

The findings of this study provide genetic evidence supporting an association between GDM and higher risk of offspring diseases. This supports classification of GDM as risk factors for short- and long-term offspring health.

Navigating Diabetes in Pregnancy: Critical Approaches to Mitigate Risks and Improve Outcomes for Mother and Child

With the increasing prevalence of diabetes and its growing impact on maternal and fetal health, management during pregnancy has become critical. This review describes the pathophysiology of insulin resistance during pregnancy, adverse outcomes correlated with diabetic pregnancies, and current management strategies. We investigate two leading approaches to managing pregnant patients with diabetes-lifestyle intervention and drug treatment. Lifestyle intervention, including dietary counseling, exercise regimens, patient education, and self-administered blood glucose monitoring, has demonstrated promising results in the management and prevention of gestational diabetes mellitus (GDM). Early intervention and treatment of at-risk patients have been critical for positive outcomes. Drug treatment, focusing on the utilization of insulin, insulin analogs, and antihyperglycemic agents has shown efficacy in achieving glycemic control and improving maternal and neonatal outcomes. These findings indicate that a combination of early lifestyle intervention and targeted drug treatment yields the most benefit in managing diabetes in pregnancy. To augment treatment, continuous glucose monitoring and telemedicine have become valuable tools in managing diabetes during pregnancy. Future research should aim to develop more effective antihyperglycemic agents, improve telehealth accessibility, and enhance preconception care for women at risk of developing GDM. By addressing these areas, we can significantly reduce the adverse outcomes associated with diabetes in pregnancy and improve overall maternal and fetal health.

Unveiling Gestational Diabetes: An Overview of Pathophysiology and Management

Gestational diabetes mellitus (GDM) is characterized by an inadequate pancreatic β-cell response to pregnancy-induced insulin resistance, resulting in hyperglycemia. The pathophysiology involves reduced incretin hormone secretion and signaling, specifically decreased glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), impairing insulinotropic effects. Pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), impair insulin receptor substrate-1 (IRS-1) phosphorylation, disrupting insulin-mediated glucose uptake. β-cell dysfunction in GDM is associated with decreased pancreatic duodenal homeobox 1 (PDX1) expression, increased endoplasmic reticulum stress markers (CHOP, GRP78), and mitochondrial dysfunction leading to impaired ATP production and reduced glucose-stimulated insulin secretion. Excessive gestational weight gain exacerbates insulin resistance through hyperleptinemia, which downregulates insulin receptor expression via JAK/STAT signaling. Additionally, hypoadiponectinemia decreases AMP-activated protein kinase (AMPK) activation in skeletal muscle, impairing GLUT4 translocation. Placental hormones such as human placental lactogen (hPL) induce lipolysis, increasing circulating free fatty acids which activate protein kinase C, inhibiting insulin signaling. Placental 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) overactivity elevates cortisol levels, which activate glucocorticoid receptors to further reduce insulin sensitivity. GDM diagnostic thresholds (≥92 mg/dL fasting, ≥153 mg/dL post-load) are lower than type 2 diabetes to prevent fetal hyperinsulinemia and macrosomia. Management strategies focus on lifestyle modifications, including dietary carbohydrate restriction and exercise. Pharmacological interventions, such as insulin or metformin, aim to restore AMPK signaling and reduce hepatic glucose output. Emerging therapies, such as glucagon-like peptide-1 receptor (GLP-1R) agonists, show potential in improving glycemic control and reducing inflammation. A mechanistic understanding of GDM pathophysiology is essential for developing targeted therapeutic strategies to prevent both adverse pregnancy outcomes and the progression to overt diabetes in affected women.

Lymphocyte Subsets and Cytokine Changes in Women With Gestational Diabetes Mellitus: A Systematic Review

Introduction: Gestational diabetes mellitus (GDM) is a major health concern during pregnancy, affecting both the mother and the baby. Immune system alterations, particularly changes in lymphocyte subsets and cytokine profiles, have been associated with the pathophysiology of various metabolic disorders, including diabetes. This study is aimed at systematically reviewing the literature on the changes in lymphocyte subsets and cytokines in GDM. Methods: In this systematic review, we applied specific criteria to select observational studies (such as case-controls, cross-sectionals, or cohorts) that focused on pregnant women. We performed an extensive search across electronic databases, including Web of Science, Scopus, PubMed, MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Google Scholar, from January 1, 2010, to March 20, 2024. Results: A total of 19 articles, with 2517 participants (1128 with GDM and 1389 without GDM), were included in the qualitative synthesis. Due to high heterogeneity among the articles, a meta-analysis was not conducted. The studies assessed 35 different lymphocyte subsets or proportions. The most commonly assessed subsets were CD3+ T cell (five articles, mostly no difference between GDM and non-GDM), CD4+ T cell (five articles with contradictory results), CD8+ T cell (four articles with contradictory results), B cell and NK cell (three articles, mostly no difference between GDM and non-GDM), and Tregs (three articles with contradictory results). Additionally, 32 cytokines or proportions were assessed in the studies. The most commonly assessed cytokines were IL-6 (eight articles, higher or similar levels in GDM compared to non-GDM), TNF-α (seven articles, mostly higher or similar levels in GDM compared to non-GDM), IL-10 (six articles, mostly no difference between GDM and non-GDM), IL-2 (three articles, mostly no difference between GDM and non-GDM), and IFN-γ (three articles with contradictory results). Conclusion: According to the results, there were no significant changes in CD3+ T cells, B cells, NK cells, IL-10, and IL-2 in GDM. However, the levels of IL-6 and TNF-α were higher or similar in GDM compared to non-GDM. The changes of other lymphocyte subsets and cytokines in GDM remained unclear.

Association Between Neighborhood Deprivation and Gestational Diabetes: A Systematic Review and Meta-Analysis

Gestational diabetes mellitus (GDM) is a major global health concern, affecting maternal and child health. Although genetic predispositions and individual medical histories are well-recognized risk factors, emerging research suggests a significant impact of external factors like neighborhood socioeconomic characteristics. This study systematically reviews and meta-analyzes the association between neighborhood deprivation and GDM incidence. We searched multiple databases up to January 10, 2024, for studies linking neighborhood deprivation with GDM. Eligible studies were selected based on predefined criteria, with the Nested Knowledge software assisting in screening and data extraction. Quality assessment utilized the Newcastle-Ottawa Scale, and a random-effects model computed the pooled relative risk (RR) using R software, version 4.3. The review included six studies varying significantly in design, sample sizes, and deprivation assessment methods. The meta-analysis combined data from five studies totaling 15 827 participants from the least deprived and 18 147 from the most deprived neighborhoods, yielding an RR of 0.909, indicating a non-significant lower risk of GDM in more deprived groups. A substantial heterogeneity (I2 = 70%) was observed, and sensitivity analysis confirmed the robustness of these findings. This analysis suggests that living in a deprived neighborhood does not significantly alter GDM risk, underscoring the necessity for further research to refine public health strategies and interventions. The variability in neighborhood deprivation definitions and potential unaccounted confounding factors highlight the need for comprehensive studies, especially from low-income and middle-income countries, to elucidate the intricate links between socioeconomic factors and GDM.

Risk Factors for Gestational Diabetes Mellitus in Mainland China: A Systematic Review and Meta-Analysis

Objective

This study aimed to identify and evaluate risk factors associated with gestational diabetes mellitus (GDM) in mainland China.

Methods

Eight electronic databases were searched for literature published from January 2010 until December 2023. Heterogeneity was quantified using I2. Data were pooled by fixed or random effects models and expressed as odds ratio and 95% confidence intervals.

Results

A total of 69 observational studies with an overall sample size of 2,138,032 Chinese women and 219,303 patients with GDM were included in the analysis. After adjusting confounders, older maternal age (OR = 1.12, 95% CI: 1.09-1.15), maternal age ≥35 years (OR = 1.96, 95% CI: 1.74-2.21), higher pre-pregnancy body mass index (OR = 1.24, 95% CI: 1.17-1.32), pre-pregnancy overweight (OR = 1.78, 95% CI: 1.64-1.92) or obesity (OR 2.52, 95% CI: 2.06-3.08), family history of diabetes (OR = 1.85, 95% CI: 1.58-2.17), history of GDM (OR = 4.09, 95% CI: 2.13-7.82), and elevated levels of fasting plasma glucose (OR = 2.54, 95% CI: 2.13-3.01), hemoglobin (OR = 1.47, 95% CI: 1.14-1.89) and serum triglycerides (OR = 1.69, 95% CI: 1.31-2.16) in early pregnancy were associated with an increased risk of GDM in mainland China. But gravidity ≥2 (OR = 1.06, 95% CI: 0.89-1.27), conception by assisted reproductive technology analyses (OR = 1.54, 95% CI: 0.95-2.51) were not associated with GDM, and parity ≥1 (OR = 0.88, 95% CI: 0.82-0.94) was related to lower risk of GDM. In available unadjusted studies, history of abortion (OR = 1.34, 95% CI: 1.31-1.37) increased risk of GDM, non-Han ethnicity (OR = 0.78, 95% CI: 0.59-1.03) and high school or lower education level (OR1.09, 95% CI: 0.94-1.26) showed no correlation with GDM.

Conclusion

The key risk factors for GDM in mainland China included older maternal age, maternal age ≥35 years, pre-pregnancy overweight or obesity, family history of diabetes, history of GDM, elevated levels of FPG, Hb, and serum TG in early pregnancy. Early identification and intervention for women at high risk should be performed to prevent the development of GDM.

Air Pollution Exposure and Gestational Diabetes Mellitus Risk: A Retrospective Case-Control Study with Multi-Pollutant Analysis in Wuhan, Hubei Province

Ambient air pollution has been associated with gestational diabetes mellitus (GDM); however, evidence regarding trimester-specific effects from China remains limited. This case-control study study analyzed data from pregnant women who delivered in Wuhan, China, between 2017 and 2022 (164 GDM cases and 731 controls), integrating geographic information, air quality measurements, and maternal characteristics. Using Inverse Distance Weighting interpolation and Generalized Linear Mixed Models (GLMM), we assessed associations between air pollutant exposure and GDM across different gestational periods. Results indicated that NO2 demonstrated the strongest association with GDM compared to other pollutants. Specifically, increased NO2 exposure was consistently associated with higher GDM risk throughout pregnancy. PM2.5 exposure showed significant associations during early and mid-pregnancy, while SO2 exposure was significantly associated with GDM risk exclusively in early pregnancy. Sensitivity analyses stratified by urban maternity status and maternal age revealed the stability of the study's findings. These findings underscore the importance of reducing air pollution exposure during pregnancy and implementing targeted interventions for high-risk populations to prevent GDM development.

Microscopic changes and gross morphology of placenta in women affected by gestational diabetes mellitus in dietary treatment: A systematic review

Introduction/objective

Gestational diabetes mellitus (GDM) influences adverse maternal and fetal outcomes. Nutritional therapy and exercise are the first steps to maintain normal glucose levels. During pregnancy, metabolic status influences placental development.

Methods

This systematic review focused only on the morphology of the placenta and its microscopic changes in GMD under dietary therapy. A systematic search was performed on the main databases from inception to September 2024 (PROSPERO ID: CRD42024581621). Only original articles on GDM in diet and exercise treatment that reported at least one outcome of interest (microscopic features and macroscopic morphology of the placenta) were included.

Results

A total of 716 studies were identified, and nine met the inclusion criteria. The analysis confirmed that despite dietary control, some morphological changes in the placenta, including villus immaturity, chorangiosis, and fibrinoid necrosis, occurred at a different rate. In addition, the included studies reported an increase in placental weight in the diet-controlled GDM group.

Conclusion

Therefore, the results of the present qualitative analysis show that pregnant women with diet-controlled GDM, despite adequate glycemic control, abnormal placental development may persist. Our findings remark on the importance of the correct diet-managed GDM pregnancy monitoring due to the placental morphology abnormalities related to GMD.

The impact of intermittent energy restriction on women's health

Intermittent energy-restricted diets are used amongst women with overweight and obesity and a healthy weight. For those with overweight and obesity weight control is typically achieved through daily energy restriction (DER) which has reduced adherence and attenuated metabolic benefits over time. Several intermittent energy restriction (IER) regimens have been developed aiming to promote maintained weight loss and additional weight independent metabolic benefits including the 5:2 diet, alternate day fasting (ADF) and time-restricted eating (TRE). This review summarises the potential benefits or harms of these regimens for managing women’s health. 5:2 and ADF diets have equivalent long term (≥ 6-month) adherence, weight loss and metabolic benefits to DER. Current limited evidence suggests IER is a safe weight loss intervention for women which does not affect reproductive or bone health, increase eating disorders or disturb sleep. Adherence and weight loss with both IER and DER are lower amongst younger women compared to older women and men. Weight loss with ADF and TRE has, respectively, improved symptoms of polycystic ovarian syndrome and premenstrual syndrome, but there is no evidence of weight-independent effects of IER on these conditions. There is little evidence of the benefits and/or harms of IER amongst healthy weight women in whom there is a greater potential for adverse effects on reproductive and bone health, fat free mass, eating disorders and sleep. Further research benefits of IER for weight control and metabolic health as well as harms are required.

Lactation duration and the risk of type 2 diabetes mellitus in parous women: A perspective on socioeconomic status disparity

BACKGROUND & AIMS

Whether and how socioeconomic status (SES) influences the associations between type 2 diabetes mellitus (T2DM) and lactation remains unknown. We aimed to evaluate the associations between lactation duration and T2DM from a perspective of SES disparity.

METHODS

A total of 263,859 parous women without diabetes at baseline (2004-2008) in the China Kadoorie Biobank were included. Lactation duration was counted for the first-child, per-child and lifetime. The latent class analysis of education level, household income, occupation, and residence was conducted to derive SES as low, intermediate, and high. T2DM cases were identified through linkage with records in hospitals, disease registry system and health insurance data during follow-up (2008-2015). Multivariable Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95 % confidence intervals for T2DM. Population attributable fraction evaluated the cases tied to insufficient lactation by SES.

RESULTS

In a median 9.2-year follow-up, 8,204 cases were identified. Women who breastfed their first child for 12-24 and > 24 months respectively, had a reduced risk of diabetes (fully adjusted HR: 0.84 [0.75-0.94] and 0.81 [0.70-0.95]). Similar results were found for per-child (0.84 [0.72-0.98] and 0.71 [0.59, 0.85]), and lifetime lactation for > 36 months (0.66 [0.56, 0.77]). For dose-response associations, every 5-month increase in lactation duration (first-child, per-child, lifetime) was linked to a 7 %, 10 %, and 4 % lower T2DM risk. These associations were significant among low SES women but not for intermediate or high SES women. For low SES women, 36.42 % of diabetes cases were attributable to per-child lactation duration of < 24 months, and 5.76 %, 25.37 %, 47.29 %, 19.04 % of cases would be prevented if women lactating for 0, 0-6, 6-12, and 12-24 months extended their per-child lactation duration to at least 2 years.

CONCLUSION

Longer lactation duration is associated with a decreased risk of T2DM among women, especially those with low SES. The promotion of extended breastfeeding could potentially prevent a significant proportion of diabetes events.

Quality of information in gestational diabetes mellitus videos on TikTok: Cross-sectional study

BACKGROUND

TikTok is an important channel for consumers to obtain and adopt health information. However, misinformation on TikTok could potentially impact public health. Currently, the quality of content related to GDM on TikTok has not been thoroughly reviewed.

OBJECTIVE

This study aims to explore the information quality of GDM videos on TikTok.

METHODS

A comprehensive cross-sectional study was conducted on TikTok videos related to GDM. The quality of the videos was assessed using three standardized evaluation tools: DISCERN, the Journal of the American Medical Association (JAMA) benchmarks, and the Global Quality Scale (GQS). The comprehensiveness of the content was evaluated through six questions covering definitions, signs/symptoms, risk factors, evaluation, management, and outcomes. Additionally, a correlational analysis was conducted between video quality and the characteristics of the uploaders and the videos themselves.

RESULTS

A total of 216 videos were included in the final analysis, with 162 uploaded by health professionals, 40 by general users, and the remaining videos contributed by individual science communicators, for-profit organizations, and news agencies. The average DISCERN, JAMA, and GQS scores for all videos were 48.87, 1.86, and 2.06, respectively. The videos uploaded by health professionals scored the highest in DISCERN, while the videos uploaded by individual science communicators scored significantly higher in JAMA and GQS than those from other sources. Correlation analysis between video quality and video features showed DISCERN scores, JAMA scores and GQS scores were positively correlated with video duration (P<0.001). Content scores were positively correlated with the number of comments (P<0.05), the number of shares (P<0.001), and video duration (P<0.001).

CONCLUSION

We found that the quality of GDM video on TikTok is poor and lack of relevant information, highlighting the potential risks of using TikTok as a source of health information. Patients should pay attention to identifying health-related information on TikTok.

Correlations Between Gut Microbiota Composition, Medical Nutrition Therapy, and Insulin Resistance in Pregnancy-A Narrative Review

Many physiological changes accompany pregnancy, most of them involving metabolic perturbations. Alterations in microbiota composition occur both before and during pregnancy and have recently been correlated with an important role in the development of metabolic complications, such as insulin resistance and gestational diabetes mellitus (GDM). These changes may be influenced by physiological adaptations to pregnancy itself, as well as by dietary modifications during gestation. Medical nutritional therapy (MNT) applied to pregnant women at risk stands out as one of the most important factors in increasing the microbiota's diversity at both the species and genus levels. In this review, we discuss the physiological changes during pregnancy and their impact on the composition of the intestinal microbiota, which may contribute to GDM. We also discuss findings from previous studies regarding the effectiveness of MNT in reducing insulin resistance. In the future, additional studies should aim to identify specific gut microbial profiles that serve as early indicators of insulin resistance during gestation. Early diagnosis, achievable through stool analysis or metabolite profiling, may facilitate the timely implementation of dietary or pharmaceutical modifications, thereby mitigating the development of insulin resistance and its associated sequelae.

The association between the dietary inflammatory index during pregnancy and risk of gestational diabetes: a prospective cohort study and a meta-analysis

INTRODUCTION

To examine the association between dietary inflammatory index (DII) and risk of gestational diabetes mellitus (GDM).

METHODS

A prospective birth cohort study was conducted in Iran. During the first trimester of pregnancy, food intake was measured using a food frequency questionnaire. Each participant's DII score was calculated, and then, the Cox proportional hazard model was used to calculate the hazard ratio (HR) and 95% CI of GDM across the quartiles of DII. We systematically searched the literature to conduct a meta-analysis of observational studies (PROSPERO: CRD42022331703). To estimate the summary relative risk for the highest versus lowest category of DII, a random-effects meta-analysis was performed. The certainty of evidence was assessed using the GRADE approach.

RESULTS

In the prospective cohort study (n = 635 pregnant mothers), the multivariable HRs of GDM for the third and fourth quartiles of DII were 2.98 (95%CI: 1.98, 6.46) and 2.72 (95%CI: 1.11, 6.63), respectively. Based on a meta-analysis of six prospective cohorts and a case-control study (1014 cases of GDM in 7027 pregnant mothers), being in the highest category of the DII was associated with a 27% higher risk of GDM (relative risk: 1.27, 95%CI: 1.01, 1.59; I2 = 50%; low certainty of evidence). A dose-response meta-analysis suggested a positive monotonic association between DII and GDM risk.

CONCLUSIONS

Our prospective cohort demonstrated a positive correlation between GDM risk and the inflammatory potential of diet in the first trimester of pregnancy. The results need to be confirmed by larger cohort studies.

CLINICAL TRIAL NUMBER

Not applicable.

Glucokinase Regulatory Protein as a Putative Target for Gestational Diabetes Mellitus and Related Complications: Evidence From the Mendelian Randomization Study

BACKGROUND

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy and is highly associated with adverse perinatal outcomes and long-term health problems for the mother and offspring. However, there are respective limitations in the pharmacological strategies for the current treatment of GDM. Glucokinase regulatory protein (GCKR) has been associated with GDM in observational studies and animal experiments and thus represents a potential drug target of interest for investigation.

METHODS

We applied two-sample Mendelian randomization (MR) and colocalization analysis using summary-level data from genome-wide association studies of GCKR and GDM. Two-step MR was used to explore the mediating effects of several metabolic factors on the association. We also applied MR to explore the associations of GCKR levels with GDM-related outcomes. Finally, we performed a phenome-wide association study (PheWAS) to query the potential effects of altered GCKR levels across multiple health categories.

RESULTS

We found a significant association between elevated GCKR levels and GDM (OR = 3.466, 95% CI = 2.401-5.002, p = 3.16 × 10-11), also supported by the colocalization analysis ([Pcoloc] = 0.997). The estimates were replicated in an independent study (OR = 2.640, 95% CI = 1.983-3.513, p = 2.84 × 10-11, Pcoloc = 0.983). Elevated GCKR levels were also associated with higher risk of type 2 diabetes (OR = 2.183, 95% CI = 1.846-2.581, p = 6.53 × 10-20). Two-step MR suggested that fasting glucose, fasting insulin, and triglycerides partly mediated the causal relationship. PheWAS found that targeting GCKR may improve renal function and glucose homeostasis but cause dyslipidemia and uric acid abnormalities.

CONCLUSIONS

This study provided novel evidence that circulating GCKR levels are causally implicated in GDM and related complications, suggesting that it may be a promising target for treatment.

Breastfeeding Experiences of Women With Gestational Diabetes Mellitus

OBJECTIVE

To understand the perinatal experiences of women with gestational diabetes mellitus (GDM) who intended to breastfeed.

DESIGN

Qualitative descriptive study.

SETTING

Online focus groups conducted via Zoom.

PARTICIPANTS

Women who had GDM in their most recent pregnancy, had a full-term birth in the United States, and were no more than 18 months postpartum.

METHODS

Virtual focus groups were held between November 2022 and August 2023. Focus group transcripts were coded and analyzed to identify major themes and subthemes.

RESULTS

Three major themes and 14 subthemes emerged: (a) Challenges, including subthemes of GDM Diagnosis, Doubt, Physical Challenges, Balancing Demands, Lack of Support, and Pressure or Judgment; (b) Lack of Informationor SupportFrom Health Care Providers, with subthemes of Separation of GDM From Breastfeeding, Inadequate Information or Support, and Provider Neutrality; and (c) Facilitating or Motivating Factors, including subthemes of Knowledge; Intention, Confidence, and Determination; and Positive Support.

CONCLUSION

Women with GDM experienced many breastfeeding challenges and felt they had received little information or support from health care providers, including but not limited to nurses. They also expressed feelings of pressure or judgment about their infant feeding choices, reported a desire to know more about the connection between GDM and breastfeeding, and highlighted the value of having support systems in person or online.

Pediococcus acidilactici CECT 9879 (pA1c®) and heat inactivated pA1c® (pA1c® HI) ameliorate gestational diabetes mellitus in mice

AIMS

Gestational diabetes mellitus (GDM) is the most common complication of pregnancy and is known to be associated with an increased risk of postpartum metabolic disease. Based on the important role that the intestinal microbiota plays in blood glucose regulation and insulin sensitivity, supplementation of probiotic and postbiotic strains could improve glucose metabolism and tolerance in GDM.

MAIN METHODS

56 4-week-old female C57BL/6J-mice were divided into 4 groups (n = 14 animals/group): control (CNT), high-fat/high-sucrose (HFS), pA1c® alive (pA1c®) and heat-inactivated pA1c® (pA1c®HI). Serum biochemical parameters were analyzed, gene expression analyses were conducted, and fecal microbiota composition was evaluated by shot-gun sequencing.

KEY FINDINGS

pA1c®- and pA1c® HI-supplemented groups presented reduced fasting blood glucose levels and reduced insulin resistance during gestation and exhibited lower visceral adiposity and increased muscle tissue, together with an improvement in intrahepatic TGs content and ALT levels. Liver gene expression analyses demonstrated that pA1c® and pA1c® HI activities were mediated by modulation of the insulin receptor, but also by an overexpression of beta-oxidation genes, and downregulation of fatty acid biosynthesis genes. Shot-gun metagenomics demonstrated that Pediococcus acidilactici was detected in the feces of all the pA1c® and pA1c® HI-group after the supplementation period (75 % of the microbial profile was Pediococcus acidilactici) in only nine weeks of supplementation, and modulated gut microbiota composition.

SIGNIFICANCE

These results may be considered as future perspectives for the development of preventive, even therapeutic options for GDM based on hyperglycemia reduction, blood glucose regulation, hepatic steatosis attenuation and insulin resistance alleviation.

Association between periodontal disease and gestational diabetes: Systematic review and meta-analysis

AIM

Periodontal disease (PD) can aggravate insulin resistance during pregnancy and trigger the development of gestational diabetes mellitus (GDM).

METHODS

A systematic review and meta-analysis was carried out. Two researchers carried out a literature search using internet databases. Studies that met the inclusion criteria were selected. OR was used as the measure of association. The fixed effects model was applied, and due to the presence of heterogeneity, the DerSimonian and Laird random effects model was applied. The level of significance was p < 0.05. The presence of biases was assessed using the Egger test and the funnel plot.

RESULTS

Of the 176 articles found, 11 were included. 2032 pregnant women were analyzed, of which 572 developed GDM. It was found that PD was a risk factor for developing GDM when all studies were assessed (OR=1.83 95 % CI 1.25-2.69, p < 0.0017) and when analyzing only those that included an adjusted OR (OR= 1.83 95 % CI 1.31-2.56, p < 0.004).

CONCLUSIONS

PD poses a high risk of suffering from GDM. The development of oral health programs in women who wish to conceive is essential to improve metabolic control and reduce obstetric and perinatal complications.

Genetic Insights Into Lipid Traits and Lipid-Modifying Drug Targets in Pregnancy Complications: A Two-Sample Mendelian Randomization Study

Background

Dyslipidemia is linked to pregnancy complications, but its causal role remains uncertain. This two-sample Mendelian Randomization (MR) study investigated the causal relationship between lipid traits and pregnancy complications and evaluated the impact of lipid-modifying drug targets.

Methods

Genetic instruments for lipid traits and targets for lipid-modifying drugs were obtained from the Global Lipids Genetics Consortium. Three pregnancy complications' summary statistics came from the FinnGen R9 database. Significant drug targets underwent further analysis using Expression Quantitative Trait Loci data, and mediation analysis identified potential mediators.

Results

Increased high-density lipoprotein cholesterol (HDL-C) reduced the incidence of preeclampsia (OR: 0.755, 95% CI: 0.639-0.891, p=0.001, FDR=0.012) and gestational diabetes mellitus (GDM) (OR: 0.835, 95% CI: 0.741-0.942, p=0.003, FDR=0.018). Genetic proxies for cholesteryl ester transfer protein (CETP) inhibition correlated with a decreased risk of preeclampsia (OR: 0.863, 95% CI: 0.786-0.947, p=0.002, FDR=0.027), while genetic inhibition of HMG-CoA reductase (HMGCR) increased preeclampsia risk (OR: 1.700, 95% CI: 1.189-2.431, p=0.004, FDR=0.036). Genetically mimicking the enhancement of lipoprotein lipase (LPL) related to a reduced risk of GDM (OR: 0.681, 95% CI: 0.560-0.829, p=1.29×10-4, FDR=0.004). Higher LPL expression in subcutaneous adipose tissue also reduced GDM risk (OR: 0.642, 95% CI: 0.454-0.909, p=0.013). Waist circumference (4.2%) and waist-to-hip ratio adjusted by BMI (5.7%) partially mediated LPL's effect on GDM risk.

Conclusion

Elevated HDL-C levels help prevent preeclampsia and GDM. CETP and LPL could be therapeutic targets for preeclampsia and GDM, respectively. However, caution is advised with HMGCR-targeting drugs, as they may increase the preeclampsia risk.

A scientometric visualization analysis of the gut microbiota and gestational diabetes mellitus

Background

The prevalence of gestational diabetes mellitus (GDM), a condition that is widespread globally, is increasing. The relationship between the gut microbiota and GDM has been a subject of research for nearly two decades, yet there has been no bibliometric analysis of this correlation. This study aimed to use bibliometrics to explore the relationship between the gut microbiota and GDM, highlighting emerging trends and current research hotspots in this field.

Results

A total of 394 papers were included in the analysis. China emerged as the preeminent nation in terms of the number of publications on the subject, with 128 papers (32.49%), whereas the United States had the most significant impact, with 4,874 citations. The University of Queensland emerged as the most prolific institution, contributing 18 publications. Marloes Dekker Nitert was the most active author with 16 publications, and Omry Koren garnered the most citations, totaling 154. The journal Nutrients published the most studies (28 publications, 7.11%), whereas PLoS One was the most commonly co-cited journal, with a total of 805 citations. With respect to keywords, research focuses can be divided into 4 clusters, namely, "the interrelationship between the gut microbiota and pregnancy, childbirth," "the relationship between adverse metabolic outcomes and GDM," "the gut microbiota composition and metabolic mechanisms" and "microbiota and ecological imbalance." Key areas of focus include the interactions between the gut microbiota and individuals with GDM, as well as the formation and inheritance of the gut microbiota. Increasing attention has been given to the impact of probiotic supplementation on metabolism and pregnancy outcomes in GDM patients. Moreover, ongoing research is exploring the potential of the gut microbiota as a biomarker for GDM. These topics represent both current and future directions in this field.

Conclusion

This study provides a comprehensive knowledge map of the gut microbiota and GDM, highlights key research areas, and outlines potential future directions.

Effect of stress management based self-care counseling on glycemic control in women with gestational diabetes mellitus: a randomized controlled trial study

BACKGROUND

Stress plays an important role in the consequences of gestational diabetes mellitus [GDM]. It is possible to make a change in the lifestyle by providing counseling in the field of self-care based on stress management in order to avoid the adverse consequences of GDM. Therefore, the present study was designed and implemented with the aim of determining the effect of self-care counseling based on stress management on blood sugar control in women with GDM.

METHODS

A randomized trial with two parallel arms was conducted involving 75 pregnant women diagnosed with GDM at 20-30 weeks of gestation, who were referred to Shohada Hospital in Behshahr city from July 2022 to March 2023. The women with GDM were divided into two groups for intervention and control through random block allocation. The intervention group received 8 virtual counseling sessions once a week for 45-50 min continuously based on stress management, while the control group only received antenatal usual care (AUC). The data were measured before and after the intervention using Fasting Blood Sugar [FBS] and HbA1c (glycated hemoglobin) tests, SDSCA [summary of diabetes self-care activities, NuPDQ‑17 [Prenatal Distress Questionnaire]and DASS [stress, depression and anxiety] questionnaires.

RESULTS

The mean FBS in the intervention group were significantly lower than the control group after the intervention (P < 0.001, η2 = 0.49). The HbA1c level was lower in the intervention group than in the control group, but not statistically significant (P = 0.078). The mean score of SDSCA after counseling in the intervention group was significantly higher than the control group (P < 0.001, η2 = 0.79). Also, the NuPDQ-17 after counseling in the intervention group was significantly lower than the control group (P < 0.001, η2 = 0.67). Moreover, the mean scores of the depression (P < 0.001, η2 = 0.82), anxiety (P < 0.001, η2 = 0.67) and stress (P < 0.001, η2 = 0.77) were significantly lower in the intervention group than in the control group.

CONCLUSION

Stress management-based self-care counseling to prenatal usual care could be considered as an adjunctive care option for reducing on blood sugar and increasing the self-care activities of pregnant women with gestational diabetes and reducing their stress during pregnancy.

Circulating fibroblast growth factor 21 levels in gestational diabetes mellitus and preeclampsia: a systematic review and meta-analysis

BACKGROUND

The connection between fibroblast growth factor 21 (FGF21) and the likelihood of gestational diabetes mellitus (GDM) or preeclampsia (PE) has received more attention recently. Based on published articles, meta-analysis were conducted to explore the differences in FGF21 levels in GDM or PE compared to control groups.

METHODS

Articles published before April 5, 2024 were searched across four databases: PubMed, Web of Science, Embase, and Cochrane Library, and studies exploring the association of FGF21 levels and GDM or PE were collected. Additionally, ClinicalTrials.gov was also searched for completed and ongoing trials. (Prospero Registration CRD42024504738). The standardized mean differences (SMDs) and 95% confidence intervals (CIs) were utilized to determine FGF21 levels among different groups.

RESULTS

This analysis incorporated a total of 16 articles, with 714 GDM and 701 non-GDM in the control group. The GDM-affected pregnant women had greater levels of circulating FGF21 than the control group (SMD = 0.529, 95% CI: 0.168 ~ 0.890, p = 0.004). Moreover, the PE case group covered 120 while the control group contained 134. The findings indicated that pregnant women with PE had significantly greater levels of circulating FGF21 than healthy expectant mothers (SMD = 0.743, 95% CI: 0.527 ~ 0.958, p = 0.000).

CONCLUSIONS

Our study found that FGF21 has the potential to serve as a diagnostic marker for GDM or PE. However, due to the limited number of studies and the fact that most data were from the second and third trimesters of pregnancy, more large-scale prospective studies are needed to validate these conclusions, investigate the potential of FGF21 in enabling early diagnosis, and further examine the role of FGF21 in the development and progression of GDM/PE.

TRIAL REGISTRATION

Not applicable.

Predictive value of machine learning for the progression of gestational diabetes mellitus to type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

This systematic review aims to explore the early predictive value of machine learning (ML) models for the progression of gestational diabetes mellitus (GDM) to type 2 diabetes mellitus (T2DM).

METHODS

A comprehensive and systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science up to July 02, 2024. The quality of the studies included was assessed. The risk of bias was assessed through the prediction model risk of bias assessment tool and a graph was drawn accordingly. The meta-analysis was performed using Stata15.0.

RESULTS

A total of 13 studies were included in the present review, involving 11,320 GDM patients and 22 ML models. The meta-analysis for ML models showed a pooled C-statistic of 0.82 (95% CI: 0.79 ~ 0.86), a pooled sensitivity of 0.76 (0.72 ~ 0.80), and a pooled specificity of 0.57 (0.50 ~ 0.65).

CONCLUSION

ML has favorable diagnostic accuracy for the progression of GDM to T2DM. This provides evidence for the development of predictive tools with broader applicability.

Cross-cultural adaptation: South African Gestational Diabetes Mellitus Knowledge Questionnaire

BACKGROUND

Many serious adverse events associated with gestational diabetes mellitus (GDM) can be mitigated by timely glucose control during pregnancy, achieved through education and lifestyle choices. The aim of this study was to translate and cross-culturally adapt and test the preliminary internal consistency and test-retest reliability of the South African English, Afrikaans and isiXhosa versions of the GDM Knowledge Questionnaire (GDMKQ).

METHODS

A prospective, observational study was conducted at a high-risk antenatal clinic in South Africa. Pregnant women ≥ 18 years with GDM were consecutively sampled. Semantic equivalence between the original and adapted versions was assessed. Face and content validity, internal consistency and test-retest reliability were evaluated.

RESULTS

The three SA-GDMKQ versions demonstrated good face and content validity. For internal consistency, Cronbach's alpha values were 0.534 for the Afrikaans version, 0.434 for the English version and 0.621 for the isiXhosa version. Test-retest reliability found kappa (standard error [s.e.]) values ranged between -0.03 (0.18) and 0.89 (0.13) for the English version, between -0.07 (0.18) and 0.53 (0.13) for the Afrikaans version and between 0.28 (0.18) and 0.87 (0.17) for the isiXhosa version. All versions of the SA-GDMKQ had a statistically significant (p  0.001) positive linear correlation between the total scores.

CONCLUSION

The English, Afrikaans and isiXhosa SA-GDMKQ versions were found to be feasible and easy to comprehend, although lower internal consistency and test-retest reliability were displayed. Further validation of the psychometric properties of the English, Afrikaans and isiXhosa versions of the SA-GDMKQ among larger sample groups is however warranted.Contribution: This study adds to the knowledge around developing and using culturally appropriate questionnaires and outcome measures in research and clinical practice.

Positive association of triglyceride glucose index and gestational diabetes mellitus: a retrospective cohort study

Background

Gestational diabetes mellitus (GDM) is a common metabolic disorder with important health implications for both mother and offspring. This study aims to assess the relationship between the Triglyceride Glucose (TyG) index and GDM and explore its clinical significance.

Methods

A retrospective cohort study included 631 singleton pregnant women. The study collected data on the TyG index, glucose levels, and clinical outcomes from all participants. Research objectives were validated using logistic regression analysis and Receiver Operating Characteristic curves.

Results

We found an independent correlation between TyG index and increased risk of GDM, with an odds ratio (OR) of 3.11 (95% confidence interval (CI): 2.09-4.63, P<0.001). The spline model revealed a linear association between TyG index and GDM in early pregnancy (non-linear P=0.748), and the risk of GDM increased with the increase of TyG index. In addition, we found that TyG has high diagnostic performance in predicting GDM, with an AUC value of 0.668. Combined with Age, it can improve predictive performance, with an AUC value of 0.684. Compared to the lower quartile of the TyG index, women in the higher quartile have a higher incidence of premature birth, hypertensive disorders of pregnancy, and intrahepatic cholestasis of pregnancy (ICP). In the GDM group, the TyG index was negatively correlated with 25 (OH) D and TBIL, and positively correlated with FBG, TG, and TC.

Conclusions

The TyG index is strongly linked to the development of GDM and is an independent risk factor for predicting it. Monitoring TyG levels in early pregnancy is valuable for identifying women at high risk for GDM.

Predicting Gestational Diabetes Mellitus in the first trimester using machine learning algorithms: a cross-sectional study at a hospital fertility health center in Iran

BACKGROUND

Gestational Diabetes Mellitus (GDM) is a common complication during pregnancy. Late diagnosis can have significant implications for both the mother and the fetus. This research aims to create an early prediction model for GDM in the first trimester of pregnancy. This model will help obstetricians and gynecologists make appropriate decisions for treating and preventing GDM complications.

METHODS

This applied descriptive study was conducted at the fertility health center of Vali-e-Asr Hospital in Tehran, Iran. The dataset was collected from the records of pregnant women registered in the hospital's system from 2020 to 2022. Risk factors for designing predictive models were identified through literature review, expert opinions, and clinical specialists' input. The extracted information underwent preprocessing, and six machine learning (ML) methods were developed and evaluated for GDM prediction in the first trimester of pregnancy: decision tree (DT), multilayer perceptron (MLP), k-nearest neighbors (KNN), Naïve Bayes (NB), random forest (RF), and extreme gradient boosting (XGBoost).

RESULTS

Models were evaluated using accuracy, precision, sensitivity, and the area under the receiver operating characteristic curve (AUC). Based on the glucose tolerance test (GTT) results, the RF model achieved the best performance in GDM prediction, with 89% accuracy, 86% precision, 92% recall, and 94% AUC, using demographic variables, medical history, and clinical findings. In modeling based on insulin consumption, the RF model achieved the best results with 62% accuracy, 60% precision, 63% recall, and 63% AUC in predicting GDM using demographic variables and medical history.

CONCLUSION

The results of this study demonstrate that ML algorithms, especially RF, have acceptable accuracy in the early prediction of GDM during the first trimester of pregnancy.

Use of mobile fitness app to improve pelvic floor muscle training in puerperal women with gestational diabetes mellitus: A randomized controlled trial

Background: Gestational diabetes mellitus (GDM) is one of the risk factors for postpartum urinary incontinence. Pelvic floor muscle training (PFMT) improves pelvic floor dysfunction in puerperal women, but patient compliance is low. Mobile Health (mHealth) is a promising solution. Objective: To investigate PFMT compliance and effects on pelvic floor muscles in GDM puerperal women guided by the mobile fitness app Keep. Methods: This randomized controlled trial included puerperal women with GDM (n = 72) who were delivered at a tertiary general hospital, selected from November 2021 to April 2022 using convenience sampling, and randomly divided into control (n = 36) and experimental (n = 36) groups. The control group performed PFMT based on routine postpartum PFMT training instruction. The experimental group performed PFMT based on Keep. Both groups had a 4-week intervention period. The PFMT compliance, International Consultation on Incontinence Questionnaire Short Form (ICIQ-SF), Pelvic Muscle Self-efficacy Scale, and the Knowledge, Attitude, Belief, and Practice (KAP) scores of PFMT in puerperal women in the groups were compared pre- and post-intervention. Pelvic floor surface electromyographic biofeedback was used to compare the post-intervention pelvic floor muscle strength between the two groups. Results: Compared with the control group, the test group had higher post-intervention maternal PFMT compliance, pelvic floor muscle strength, pelvic floor muscle self-efficacy, and KAP scores (p < 0.05); incontinence scores were lower (p < 0.05). Pelvic floor muscles in both groups recovered better post-intervention (p < 0.05). Conclusion: The Keep app can improve PFMT adherence, urinary incontinence, KAP scores, self-efficacy, and pelvic floor muscle strength in GDM puerperal women and promote pelvic floor rehabilitation after delivery.

Impact of family income on the development of gestational diabetes mellitus and the associated birth outcomes: A nationwide study

AIMS/INTRODUCTION

The relationship between economic disadvantages and the risk of developing gestational diabetes mellitus (GDM), as well as its impact on birth outcomes, remains uncertain.

MATERIALS AND METHODS

From the Taiwan Maternal and Child Health Database, we identified 984,712 pregnant women between 1 January 2007 and 31 December 2018. Using propensity score matching, we selected 5,068 pairs of women across four income levels: very low, low, middle and high. We used a multivariable Cox regression model to assess the risk of GDM in these pregnant women and analyzed the birth outcomes.

RESULTS

The mean age of the pregnant women was 30.89 years. We found no significant difference in GDM risk among pregnant women with different family income. However, newborns of women with GDM and very low-income were at higher risk for several adverse conditions, such as small for gestational age (adjusted odds ratio (aOR) 1.17, 95% confidence interval (CI) 1.04-1.31), large for gestational age (aOR 1.27, 95% CI 1.08-1.51), hypoxic-ischemic encephalopathy (aOR 3.19, 95% CI 1.15-8.86), respiratory distress (aOR 1.58, 95% CI 1.14-2. 19), congenital anomalies (aOR 1.32, 95% CI 1.08-1.62), jaundice requiring phototherapy or exchange transfusion (aOR 1.14, 95% CI 1.05-1.24) and so on.

CONCLUSIONS

This study found that low family income alone was not associated with GDM development. However, for a GDM pregnancy, pregnant women with lower income had worse birth outcomes. Improving maternal health and nutrition among low-income pregnant women with GDM might be critical to improving birth outcomes.

Optimizing screening practice for gestational diabetes mellitus in primary healthcare facilities in Tanzania: research protocol

BACKGROUND

Tanzania, like most low- and middle-income countries, is facing an increasing prevalence of obesity in the general population, including among women of reproductive age. Excess weight pre-pregnancy is a risk factor for the onset of gestational diabetes mellitus (GDM), which is associated with several poor pregnancy outcomes. Screening for GDM, as a primary preventive measure, is not systematically done in Tanzania. This study aims to explore current practices of screening for GDM during routine antenatal care (ANC), estimate the prevalence of GDM among ANC users and compare the performance of two commonly used GDM screening algorithms. We will then explore the best ways for implementing a functional screening practice for GDM at primary level hospitals using perspectives of health care workers, health managers, and pregnant women.

METHODS

This will be an observational cross-sectional study design with sequential mixed-methods approach conducted in ANC clinics of two primary level hospitals: Kisarawe District Hospital in Coast region and Mbagala Rangi Tatu Hospital in Dar es Salaam region, Tanzania. Quantitative data will be collected to determine the current structural capacity and screening practices for GDM, the prevalence of GDM among ANC users, and the sensitivity and specificity of the two recommended screening algorithms. Qualitative data will be collected through key informant interviews with health managers and pregnant women and focus group discussions with healthcare workers to understand the rationale, challenges, possible solutions and benefits of the used screening algorithm. We will also explore the meaning of screening/diagnosis to pregnant women, and propose a functional GDM screening algorithm informed by users (i.e. pregnant women, health managers and care workers).

DISCUSSION

ANC is an entry point for pregnant women to access preventive services including screening for GDM. When done appropriately, GDM screening would reduce undesired outcomes attributed to GDM also beyond the pregnancy period. Through this study we will understand the bottlenecks and propose evidence to inform feasible ways to overcome them and establish a functional and standardized GDM screening service.