Genetic and inflammatory factors underlying gestational diabetes mellitus: a review

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

A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Caucasian and Latin American Pregnant Women

The pathophysiology of gestational diabetes mellitus (GDM) comprises clinical and genetic factors. In fact, GDM is associated with several single nucleotide polymorphisms (SNPs). This study aimed to build a prediction model of GDM combining clinical and genetic risk factors. A total of 1588 pregnant women from the San Carlos Cohort participated in the present study, including 1069 (67.3%) Caucasian (CAU) and 519 (32.7%) Latin American (LAT) individuals, and 255 (16.1%) had GDM. The incidence of GDM was similar in both groups (16.1% CAU and 16.0% LAT). Genotyping was performed via IPLEX Mass ARRAY PCR, selecting 110 SNPs based on literature references. SNPs showing the strongest likelihood of developing GDM were rs10830963, rs7651090, and rs1371614 in CAU and rs1387153 and rs9368222 in LAT. Clinical variables, including age, pre-pregnancy body mass index, and fasting plasma glucose (FPG) at 12 gestational weeks, predicted the risk of GDM (AUC 0.648, 95% CI 0.601-0.695 in CAU; AUC 0.688, 95% CI 0.628-9.748 in LAT), and adding SNPs modestly improved prediction (AUC 0.722, 95%CI 0.680-0.764 in CAU; AUC 0.769, 95% CI 0.711-0.826 in LAT). In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women.

RNA-seq analysis-based study on the effects of gestational diabetes mellitus on macrosomia

Background

Both the mother and the infant are negatively impacted by macrosomia. Macrosomia is three times as common in hyperglycemic mothers as in normal mothers. This study sought to determine why hyperglycemic mothers experienced higher macrosomia. Methods: Hematoxylin and Eosin staining was used to detect the placental structure of normal mother(NN), mothers who gave birth to macrosomia(NM), and mothers who gave birth to macrosomia and had hyperglycemia (DM). The gene expressions of different groups were detected by RNA-seq. The differentially expressed genes (DEGs) were screened with DESeq2 R software and verified by qRT-PCR. The STRING database was used to build protein-protein interaction networks of DEGs. The Cytoscape was used to screen the Hub genes of the different group.

Results

The NN group's placental weight differed significantly from that of the other groups. The structure of NN group's placenta is different from that of the other group, too. 614 and 3207 DEGs of NM and DM, respectively, were examined in comparison to the NN group. Additionally, 394 DEGs of DM were examined in comparison to NM. qRT-PCR verified the results of RNA-seq. Nucleolar stress appears to be an important factor in macrosomia, according on the results of KEGG and GO analyses. The results revealed 74 overlapped DEGs that acted as links between hyperglycemia and macrosomia, and 10 of these, known as Hub genes, were key players in this process. Additionally, this analysis believes that due of their close connections, non-overlapping Hubs shouldn't be discounted.

Conclusion

In diabetic mother, ten Hub genes (RPL36, RPS29, RPL8 and so on) are key factors in the increased macrosomia in hyperglycemia. Hyperglycemia and macrosomia are linked by 74 overlapping DEGs. Additionally, this approach contends that non-overlapping Hubs shouldn't be ignored because of their tight relationships.

Sex-Specific Alterations in Placental Proteomics Induced by Intrauterine Hyperglycemia

Gestational diabetes mellitus (GDM) with intrauterine hyperglycemia induces a series of changes in the placenta, which have adverse effects on both the mother and the fetus. The aim of this study was to investigate the changes in the placenta in GDM and its gender differences. In this study, we established an intrauterine hyperglycemia model using ICR mice. We collected placental specimens from mice before birth for histological observation, along with tandem mass tag (TMT)-labeled proteomic analysis, which was stratified by sex. When the analysis was not segregated by sex, the GDM group showed 208 upregulated and 225 downregulated proteins in the placenta, primarily within the extracellular matrix and mitochondria. Altered biological processes included cholesterol metabolism and oxidative stress responses. After stratification by sex, the male subgroup showed a heightened tendency for immune-related pathway alterations, whereas the female subgroup manifested changes in branched-chain amino acid metabolism. Our study suggests that the observed sex differences in placental protein expression may explain the differential impact of GDM on offspring.

TCF7L2 Polymorphism rs7903146 (C/T) and Gestational Diabetes Influence on Obstetric Outcome: A Romanian Case-Control Study

Gestational diabetes mellitus (GDM) is one of the most frequent predictors of obstetric outcome among Romanian pregnant women. Thus, we aimed to investigate the role of rs7903146 (C/T) TCF7L2 gene polymorphism in the presence of GDM and to evaluate the influence on maternal-fetal outcomes in a cohort of pregnant women from Northern Transylvania. Our prospective case-control study was performed in a tertiary maternity center on 61 patients diagnosed with GDM and 55 normal pregnant patients. The patients were genotyped for rs7903146 (C/T) polymorphism of the TCF7L2 gene using the PCR-RFLP method between 24 and 28 weeks of gestation. The minor T allele was associated with a high risk of developing GDM (OR 1.71 [95% CI 0.82-3.59]) if both heterozygote and homozygote types were considered. Also, a higher risk of developing GDM was observed in homozygous carriers (OR 3.26 [95% CI 1.10-9.68]). Women with the TT genotype were more likely to require insulin therapy during pregnancy than other genotypes with a 5.67-fold increased risk ([1.61-19.97], p = 0.015). TT homozygote type was significantly associated with fetal macrosomia for birth weights greater than the 95th percentile (p = 0.034). The homozygous TT genotype is associated with an increased risk of developing GDM. Also, rs7903146 (C/T) TCF7L2 variant is accompanied by a high probability of developing insulin-dependent gestational diabetes mellitus (ID-GDM). The presence of at least one minor T allele was associated with a higher risk of fetal macrosomia.

Causal relationship between gestational diabetes and preeclampsia: A bidirectional mendelian randomization analysis

AIMS

The study aimed to explore the potential causal link between gestational diabetes mellitus (GDM) and preeclampsia (PE) using a bidirectional mendelian randomization (MR) analysis.

MATERIALS

We conducted a bidirectional MR analysis to investigate the causal relationship between GDM and PE. Data from public genome-wide association studies (GWAS) for GDM and PE were obtained from the FinnGen consortium. Various MR methods were employed, including inverse-variance weighted (IVW), MR-Egger, and sensitivity analyses. Additionally, a knowledge-based approach identified genes underlying this potential connection.

RESULTS

The IVW method revealed a lack of significant association between GDM and PE (OR: 1.04, 95 % CI: 0.96-1.14; p = 0.275). Conversely, IVW analysis indicated a causal connection from PE to GDM (OR: 1.14, 95 % CI: 1.06-1.23; p < 0.001). Molecular pathway analysis identified 20 key genes, including ASAP2, central to the PE-GDM relationship. Tissue enrichment analysis showed pertinent gene expression in significant tissues. Moreover, lower ASAP2 expression was detected in PE patients' placentas.

CONCLUSIONS

Our bidirectional MR analysis offers evidence supporting a causal link between PE and GDM, elucidating their interconnected pathogenesis. Genetic and knowledge-based insights facilitate a deeper comprehension of these complex pregnancy complications.

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

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

MicroRNA Associations with Preterm Labor-A Systematic Review

This systematic review delves into the connections between microRNAs and preterm labor, with a focus on identifying diagnostic and prognostic markers for this crucial pregnancy complication. Covering studies disseminated from 2018 to 2023, the review integrates discoveries from diverse pregnancy-related scenarios, encompassing gestational diabetes, hypertensive disorders and pregnancy loss. Through meticulous search strategies and rigorous quality assessments, 47 relevant studies were incorporated. The synthesis highlights the transformative potential of microRNAs as valuable diagnostic tools, offering promising avenues for early intervention. Notably, specific miRNAs demonstrate robust predictive capabilities. In conclusion, this comprehensive analysis lays the foundation for subsequent research, intervention strategies and improved outcomes in the realm of preterm labor.

Non-alcoholic fatty liver disease and gestational diabetes mellitus: a bidirectional two-sample mendelian randomization study

PURPOSE

Previous observational studies have revealed a potential link between non-alcoholic fatty liver disease (NAFLD) and gestational diabetes mellitus (GDM), but their causal relationship remains unclear. Thus, this study aimed to examine whether a causal link exists between genetically determined NAFLD and GDM.

METHODS

Utilizing publicly accessible genome-wide association studies (GWAS), a two-sample bidirectional Mendelian randomization (MR) analysis was conducted. The GWASs data pertaining to NAFLD and GDM were obtained from the UK Biobank Consortium and FinnGen database in primary analysis, respectively. The random-effects inverse variance weighted (IVW) method was utilized as primary analysis method. Several sensitivity analyses were utilized to verify the robustness of the results. Additionally, we also analyzed the causal effect of potential shared influencing factors on these two conditions.

RESULTS

The result of the IVW method showed that there was no significant causal relationship between genetically determined NAFLD and GDM (OR = 0.98, 95% CI: 0.90-1.07, P = 0.691). Similarly, our reverse MR analysis failed to detect a significant causal effect of GDM on NAFLD (OR = 1.14, 95% CI: 0.97-1.36, P = 0.118). Sensitivity analyses further confirmed the robustness of the results. Moreover, we found that genetically determined body mass index, waist-to-hip ratio, triglycerides, and television viewing time may be positively correlated with NAFLD and GDM, while high-density lipoprotein cholesterol and apolipoprotein A-I may both be negatively correlated with NAFLD and GDM.

CONCLUSIONS

The current bidirectional MR study failed to provide sufficient genetic evidence for the causal relationship between NAFLD and GDM.

Novel MYH7 Variant in the Neonate of a Mother with Gestational Diabetes Mellitus Showing Left Ventricular Hypertrophy and Noncompaction

BACKGROUND

Left ventricular hypertrophy (LVH) is a well-recognized cardiac dysfunction in infants of mothers with gestational diabetes mellitus (GDM). Left ventricular noncompaction (LVNC) is a cardiomyopathy that is morphologically characterized by numerous prominent trabeculations and deep intertrabecular recesses on cardiovascular imaging. However, there have been no case reports on neonates of mothers with GDM showing LVH and LVNC.

CASE PRESENTATION

A patient, with LVH of a mother with GDM, was delivered at 36 weeks of gestation. Prominent trabeculations in the LV, suggesting LVNC, instead of LVH, were apparent 1 week after birth. A heterozygous deletion variant in the MYH7 gene (NM_000257.4: c.1090T>C, p.Phe364Leu) was discovered through genetic testing using a cardiomyopathy-associated gene panel in the patient and his father and the older brother who had LVNC. The patient is now 5 years old and does not have major cardiac events, although LVNC persisted. This is the first case of LVH secondary to a mother with GDM and LVNC with a novel variant in the MYH7 gene.

CONCLUSION

Genetic testing should be conducted to obtain an accurate outcome and medical care in a patient with LVH and subsequently prominent hypertrabeculation in the LV.

Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes

Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1-3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1-7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8-10, and the three prior genome-wide association studies of GDM11-13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.

Changes of miR-139-5p, TGFB1, and COL1A1 in the placental tissue of cases with gestational diabetes mellitus

There are structural changes in the placenta of cases with Gestational Diabetes Mellitus (GDM). TGF-β and collagen pathways have crucial roles in tissue remodeling and TGF-β1 and COL1A1 are important genes in these signalling respectively. Also, lncRNA NEAT1, and miRNA hsa-miR-139-5p and hsa-miR-129-5p have regulatory effects on TGF-β1 and COL1A1. Here we aimed to assess their expressions in the placenta tissue of GDM cases. 30 patients with GDM and 30 healthy pregnant women participated in the study. Placental tissues taken during normal or cesarean delivery were used and total RNA was isolated from the tissues. mRNA levels were determined by qPCR and protein levels were determined by ELISA methods. An in silico analysis was done to elucidate the possible relation of TGF-β1 and COL1A1 gene networks with GDM. We determined that NEAT1 and miR-129-5p expression levels did not differ between GDM and healthy control groups (p = 0.697 and 0.412, respectively). But, miR-139-5p mRNA level, TGFB1 and COL1A1 protein levels significantly differ between the GDM and control groups (p = 0.000, p = 0.000 and p = 0.001, respectively). The in silico analysis revealed that TGFB1 and COL1A1 genes network may have important role in the GDM with their variety of members and regulatory molecules NEAT1, hsa-miR-139-5p, and hsa-miR-129-5p can control their functions. The expression of TGFB1, COL1A1 and miR-139-5p is changed in placenta tissue of GDM cases and many genes in the interacting networks of TGFB1 and COL1A1 could contribute to the pathogenicity of GDM.

Investigating the Potential Mechanisms of Ferroptosis and Autophagy in the Pathogenesis of Gestational Diabetes

Ferroptosis and autophagy are two different cellular processes that have recently been highlighted for their potential roles in the pathogenesis and progression of gestational diabetes (GD). This research sought to uncover the crucial genes tied to ferroptosis and autophagy in GD, further investigating their mechanisms. Differentially expressed genes (DEGs) linked to ferroptosis and autophagy in GD were identified using publicly available data. Pathway enrichment, protein interactions, correlation with immune cell infiltration, and diagnostic value of DEGs were analyzed. HTR-8/SVneo cells were subjected to varying glucose levels to evaluate cell viability and the expression of markers related to ferroptosis and proteins associated with autophagy. Crucial DEGs were validated in vitro. A total of 12 DEGs associated with ferroptosis and autophagy in GD were identified, enriched in the PI3K-AKT signaling pathway. These genes exhibited significant correlations with monocyte infiltration, resting CD4 memory T cells, and follicular helper T cells. They exhibited high diagnostic value for GD (AUC: 0.77-0.97). High glucose treatment inhibited cell viability, induced ferroptosis, and activated autophagy in HTR-8/SVneo cells. Validation confirmed altered expression of SNCA, MTDH, HMGB1, TLR4, SOX2, SESN2, and HMOX1 after glucose treatments. In conclusion, ferroptosis and autophagy may play a role in GD development through key genes (e.g., TLR4, SOX2, SNCA, HMOX1, HMGB1). These genes could serve as promising biomarkers for GD diagnosis.

Body composition and risk of gestational diabetes mellitus: A univariable and multivariable Mendelian randomization study

OBJECTIVE

In this study, we employed a Mendelian randomization (MR) approach to investigate the independent causal associations of six body composition traits with gestational diabetes mellitus (GDM).

METHODS

Genome-wide significant levels (P < 10 × 5-8 ) of single nucleotide polymorphisms associated with body water mass, total protein, whole body fat-free mass, weight, whole body fat mass, and body fat percentage were used as instrumental variables. Data on GDM were obtained from the FinnGen Consortium, and both univariable and multivariable Mendelian randomization were performed. We utilized five different analytical methods including inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode to assess the robustness of the results.

RESULTS

With univariable Mendelian randomization, the risk of GDM increased per 1-standard deviation (SD) increase in weight (ORweight  = 1.297, P = 3.06 × 10-5 ), whole body fat mass (ORwhole body fat mass  = 1.408, P = 1.32 × 10-6 ), and the risk of GDM increased per percent increase in body fat percentage (ORbody fat percentage  = 1.661, P = 1.01 × 10-8 ). Total protein had a protective effect on the risk of GDM (ORtotal protein  = 0.880, P = 0.048). However, there was no significant causal association between increases in body water mass and whole body fat-free mass per SD and the risk of GDM. Causal associations between weight, whole body fat mass, body fat percentage, and total protein with GDM were reduced to null in multivariable Mendelian randomization.

CONCLUSION

The present study furnishes genetic evidence to elucidate the causal relationship between body composition traits and GDM. Additionally, further studies are imperative to establish a causal connection between body composition traits and gestational diabetes mellitus.

A retrospective cohort study evaluating pregnancy outcomes in women with MIDD

AIMS

The most common pathogenic mitochondrial mutation associated with mitochondrial disease is m.3243A>G. Increased obstetric complications, such as spontaneous abortion, gestational diabetes (GDM), preterm delivery, and preeclampsia, have been reported in women carrying this mutation. We aimed to determine the fetal and maternal outcomes in pregnant women with mitochondrial disease.

METHODS

We retrospectively studied the obstetric and perinatal outcomes in 88 pregnancies of 26 women with genetically confirmed mitochondrial disease (m.3243A>G in the MTTL1 gene (n = 25); m.12258C>A in the MT-TS2 gene (n = 1)). Outcomes included pregnancy related complications, mode of delivery, gestational age at delivery and birthweight.

RESULTS

Mean heteroplasmy rate was 18%. The miscarriage rate was higher than background at 25%. 21 pregnancies (24%) were complicated by GDM; 9 pregnancies (13.6%) had a preterm delivery and 2 of them (3%) an extreme premature delivery < 32 weeks. One woman had preeclampsia and one had a postpartum hemorrhage. The caesarean section (CS) rate was 20%. For every unit increase in maternal heteroplasmy levels there was a 26% increased risk of undergoing an assisted operative vaginal delivery (OR 1.26, 95% CI 1.04-1.53, P = 0.002, Bonferroni corrected P = 0.005) and an 18% increased risk of undergoing a CS (OR 1.18, 95% CI 1.01-1.39, P = 0.01, Bonferroni corrected P = 0.03) compared to a spontaneous vaginal delivery. There was a statistical significant correlation between maternal and offspring heteroplasmy levels. Spearman correlation rho = 0.96, 95% CI 0.78-0.99, P = 0.0002.

CONCLUSION

Women with mitochondrial disease appear to have more frequent obstetric complications including miscarriage and GDM. Pre-pregnancy diagnosis of m.3243A>G will enable the counseling of women and increase awareness of possible obstetric complications.

Review of Genetic and Artificial Intelligence approaches to improving Gestational Diabetes Mellitus Screening and Diagnosis in sub-Saharan Africa

Background: Adverse outcomes from gestational diabetes mellitus (GDM) in the mother and newborn are well established. Genetic variants may predict GDM and Artificial Intelligence (AI) can potentially assist with improved screening and early identification in lower resource settings. There is limited information on genetic variants associated with GDM in sub-Saharan Africa and the implementation of AI in GDM screening in sub-Saharan Africa is largely unknown. Methods: We reviewed the literature on what is known about genetic predictors of GDM in sub-Saharan African women. We searched PubMed and Google Scholar for single nucleotide polymorphisms (SNPs) involved in GDM predisposition in a sub-Saharan African population. We report on barriers that limit the implementation of AI that could assist with GDM screening and offer possible solutions. Results: In a Black South African cohort, the minor allele of the SNP rs4581569 existing in the PDX1 gene was significantly associated with GDM. We were not able to find any published literature on the implementation of AI to identify women at risk of GDM before second trimester of pregnancy in sub-Saharan Africa. Barriers to successful integration of AI into healthcare systems are broad but solutions exist. Conclusions: More research is needed to identify SNPs associated with GDM in sub-Saharan Africa. The implementation of AI and its applications in the field of healthcare in the sub-Saharan African region is a significant opportunity to positively impact early identification of GDM.

The integrated bioinformatic analysis identifies immune microenvironment-related potential biomarkers for patients with gestational diabetes mellitus

Background

Gestational diabetes mellitus (GDM), a transient disease, may lead to short- or long-term adverse influences on maternal and fetal health. Therefore, its potential functions, mechanisms and related molecular biomarkers must be comprehended for the control, diagnosis and treatment of GDM.

Methods

The differentially expressed genes (DEGs) were identified using GSE49524 and GSE87295 associated with GDM from the Gene Expression Omnibus database, followed by function enrichment analysis, protein-protein interactions network construction, hub DEGs mining, diagnostic value evaluation and immune infiltration analysis. Finally, hub DEGs, the strongest related to immune infiltration, were screened as immune-related biomarkers.

Results

A hundred and seven DEGs were identified between patients with GDM and healthy individuals. Six hub genes with high diagnostic values, including ALDH1A1, BMP4, EFNB2, MME, PLAUR and SLIT2, were identified. Among these, two immune-related genes (PLAUR and SLIT2) with the highest absolute correlation coefficient were considered immune-related biomarkers in GDM.

Conclusion

Our study provides a comprehensive analysis of GDM, which would provide a foundation for the development of diagnosis and treatment of GDM.

DNA methylation risk score for type 2 diabetes is associated with gestational diabetes

BACKGROUND

Gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) share many pathophysiological factors including genetics, but whether epigenetic marks are shared is unknown. We aimed to test whether a DNA methylation risk score (MRS) for T2DM was associated with GDM across ancestry and GDM criteria.

METHODS

In two independent pregnancy cohorts, EPIPREG (n = 480) and EPIDG (n = 32), DNA methylation in peripheral blood leukocytes was measured at a gestational age of 28 ± 2. We constructed an MRS in EPIPREG and EPIDG based on CpG hits from a published epigenome-wide association study (EWAS) of T2DM.

RESULTS

With mixed models logistic regression of EPIPREG and EPIDG, MRS for T2DM was associated with GDM: odd ratio (OR)[95% CI]: 1.3 [1.1-1.8], P = 0.002 for the unadjusted model, and 1.4 [1.1-1.7], P = 0.00014 for a model adjusted by age, pre-pregnant BMI, family history of diabetes and smoking status. Also, we found 6 CpGs through a meta-analysis (cg14020176, cg22650271, cg14870271, cg27243685, cg06378491, cg25130381) associated with GDM, and some of their methylation quantitative loci (mQTLs) were related to T2DM and GDM.

CONCLUSION

For the first time, we show that DNA methylation marks for T2DM are also associated with GDM, suggesting shared epigenetic mechanisms between GDM and T2DM.

MTNR1B gene variations and high pre-pregnancy BMI increase gestational diabetes mellitus risk in Chinese women

AIM

To investigate the association of melatonin receptor 1B (MTNR1B) gene variations and pre-pregnancy body mass index (BMI) with gestational diabetes mellitus (GDM).

MATERIALS AND METHOD

In this study, 1566 Chinese Han pregnant women were enrolled and multiple genetic models were used to evaluate the association between MTNR1B gene polymorphisms and the risk of GDM. The clinical value of pre-pregnancy BMI in predicting GDM was analyzed and evaluated using receiver operating characteristic (ROC) curves. Several methods of analysis were used to examine the impact of gene-gene and gene-BMI interactions on the incidence of GDM influence.

RESULTS

For the MTNR1B gene, rs1387153 (C > T), rs10830962 (C > G), rs4753426 (T > C), and rs10830963 (C > G) are all risk mutations associated with the susceptibility of GDM. The ROC curve analysis indicated that the BMI demonstrated an area under the curve (AUC) of 0.595. Alongside, the sensitivity and specificity stood at 0.676 and 0.474 respectively. The maximum Joden index was found to be 0.150, with a corresponding critical BMI value of 20.5691 kg/m2. Interaction analysis revealed that gene-gene and gene-BMI interactions had no significant effect on GDM occurrence.

CONCLUSION

MTNR1B genetic variations confers the risk to GDM in Chinese women. Furthermore, the high pre-pregnancy BMI (≥20.5691 kg/m2) significantly increases the risk of GDM in Chinese women.

Investigating the causal impact of polycystic ovary syndrome on gestational diabetes mellitus: a two-sample Mendelian randomization study

Introduction

Determining the causal relationship between polycystic ovary syndrome (PCOS) and gestational diabetes mellitus (GDM) holds significant implications for GDM prevention and treatment. Despite numerous observational studies suggesting an association between PCOS and GDM, it remains unclear whether a definitive causal relationship exists between these two conditions and which specific features of PCOS contribute to increased incidence of GDM.

Methods

The causal relationship between polycystic ovary syndrome (PCOS), its characteristic indices, and gestational diabetes mellitus (GDM) was investigated using a two-sample Mendelian randomization study based on publicly available statistics from genome-wide association studies (GWAS). The inverse-variance weighted method was employed as the primary analytical approach to examine the association between PCOS, its characteristic indices, and GDM. MR Egger intercept was used to assess pleiotropy, while Q values and their corresponding P values were utilized to evaluate heterogeneity. It is important to note that this study adopts a two-sample MR design where PCOS and its characteristic indices are considered as exposures, while GDM is treated as an outcome.

Results

The study results indicate that there is no causal relationship between PCOS and GDM (all methods P > 0.05, 95% CI of OR values passed 1). The IVW OR value was 1.007 with a 95% CI of 0.906 to 1.119 and a P value of 0.904. Moreover, the MR Egger Q value was 8.141 with a P value of 0.701, while the IVW Q value was also 8.141 with a P value of 0.774, indicating no significant heterogeneity. Additionally, the MR Egger intercept was 0.0004, which was close to zero with a P value of 0.988, suggesting no pleiotropy. However, the study did find a causal relationship between several other factors such as testosterone, high-density lipoprotein, sex hormone-binding globulin, body mass index, waist-hip ratio, apolipoprotein A-I, number of children, diabetes illnesses of mother, father and siblings, hemoglobin A1c, fasting insulin, fasting blood glucose, years of schooling, and GDM based on the IVW method.

Conclusion

We observed no association between genetically predicted PCOS and the risk of GDM, implying that PCOS itself does not confer an increased susceptibility to GDM. The presence of other PCOS-related factors such as testosterone, high-density lipoprotein, and sex hormone-binding globulin may elucidate the link between PCOS and GDM. Based on these findings, efforts aimed at preventing GDM in individuals with PCOS should prioritize those exhibiting high-risk features rather than encompassing all women with PCOS.

Autoimmune diseases and risk of gestational diabetes mellitus: a Mendelian randomization study

AIMS

Observational studies have reported that autoimmune diseases are associated with gestational diabetes mellitus (GDM), but the causality is unknown. The study aimed to evaluate the potential causal effect of autoimmune diseases on GDM.

METHODS

A two-sample Mendelian randomization (MR) study was designed using the summary statistics of GDM (123,579 individuals) and three common autoimmune diseases, including inflammatory bowel disease (IBD, 59,957 individuals), rheumatoid arthritis (RA, 80,799 individuals) and systemic lupus erythematosus (SLE, 14,267 individuals), from the genome-wide association study (GWAS). The fixed-effects inverse variance weighted (IVW) was used to deduce the causal association between autoimmune diseases and GDM, and sensitivity analyses were further performed.

RESULTS

The inverse variance weighting (IVW) method showed that RA and SLE increased the risk of GDM (RA: OR = 1.076, 95%CI = 1.033-1.122, P = 4.649E-04; SLE: OR = 1.025, 95%CI = 1.001-1.049, P = 0.044). But there were no any associations of IBD with GDM (P > 0.05). No significant horizontal pleiotropy was found by MR Egger regression (IBD: P for intercept = 0.905; RA: P for intercept = 0.103; SLE = P for intercept = 0.608).

CONCLUSION

This two-sample MR study found that both SLE and RA are positively associated with the risk of GDM. Our findings provide help for the future prevention and treatment of GDM to reduce associated maternal and fetal complications. However, more research is needed to obviate the role of the GC and the HCQ to ensure this relationship is causal.

Meta-analysis of a family history of diabetes in schizophrenia

OBJECTIVE

Type 2 diabetes (T2DM) is common in patients with schizophrenia and non-affective psychosis. These patients also have an increased prevalence of a family history of T2DM. We performed a systematic review and meta-analysis of the association between a family history of T2DM and schizophrenia.

METHOD

We searched electronic databases from inception until July 2022 for studies of a family history of T2DM or gestational diabetes in patients with schizophrenia and controls. We performed random effects meta-analysis, calculating odds ratios (ORs) and 95 % confidence intervals (CI) and meta-regression analyses.

RESULTS

Nine studies were included, comprising 2953 patients with non-affective psychosis and 4484 controls. Schizophrenia was associated with an over two-fold increased odds of a family history of T2DM or gestational diabetes (OR = 2.18, 95 % CI 1.61-2.96, p < 0.01). In meta-regression analyses, age, sex, study quality score, and year of publication were all unrelated to the association.

CONCLUSION

We found that patients with schizophrenia had a 2.2-fold increased odds of a family history of T2DM versus controls. This association may be relevant to both the pathophysiology of schizophrenia and the reported increased risk of development of diabetes with antipsychotic treatment.

MicroRNA-322 overexpression reduces neural tube defects in diabetic pregnancies

BACKGROUND

Hyperglycemia from pregestational diabetes mellitus induces neural tube defects in the developing fetus. Folate supplementation is the only effective way to prevent neural tube defects; however, some cases of neural tube defects are resistant to folate. Excess folate has been linked to higher maternal cancer risk and infant allergy. Therefore, additional interventions are needed. Understanding the mechanisms underlying maternal diabetes mellitus-induced neural tube defects can identify potential targets for preventing such defects. Despite not yet being in clinical use, growing evidence suggests that microRNAs are important intermediates in embryonic development and can serve as both biomarkers and drug targets for disease intervention. Our previous studies showed that maternal diabetes mellitus in vivo activates the inositol-requiring transmembrane kinase/endoribonuclease 1α (IRE1α) in the developing embryo and that a high glucose condition in vitro reduces microRNA-322 (miR-322) levels. IRE1α is an RNA endonuclease; however, it is unknown whether IRE1α targets and degrades miR-322 specifically or whether miR-322 degradation leads to neural tube defects via apoptosis. We hypothesize that IRE1α can inhibit miR-322 in maternal diabetes mellitus-induced neural tube defects and that restoring miR-322 expression in developing neuroepithelium ameliorates neural tube defects.

OBJECTIVE

This study aimed to identify potential targets for preventing maternal diabetes mellitus-induced neural tube defects and to investigate the roles and relationship of a microRNA and an RNA endonuclease in mouse embryos exposed to maternal diabetes mellitus.

STUDY DESIGN

To determine whether miR-322 reduction is necessary for neural tube defect formation in pregnancies complicated by diabetes mellitus, male mice carrying a transgene expressing miR-322 were mated with nondiabetic or diabetic wide-type female mice to generate embryos with or without miR-322 overexpression. At embryonic day 8.5 when the neural tube is not yet closed, embryos were harvested for the assessment of 3 miR-322 transcripts (primary, precursor, and mature miR-322), tumor necrosis factor receptor-associated factor 3 (TRAF3), and neuroepithelium cell survival. Neural tube defect incidences were determined in embryonic day 10.5 embryos when the neural tube should be closed if there is no neural tube defect formation. To identify which miR-322 transcript is affected by maternal diabetes mellitus and high glucose conditions, 3 miR-322 transcripts were assessed in embryos from dams with or without diabetes mellitus and in C17.2 mouse neural stem cells treated with different concentrations of glucose and at different time points. To determine whether the endonuclease IRE1α targets miR-322, small interfering RNA knockdown of IRE1α or overexpression of inositol-requiring transmembrane kinase/endoribonuclease 1α by DNA plasmid transfection was used to determine the effect of IRE1α deficiency or overexpression on miR-322 expression. RNA immunoprecipitation was performed to reveal the direct targets of inositol-requiring transmembrane kinase/endoribonuclease 1α.

RESULTS

Maternal diabetes mellitus suppressed miR-322 expression in the developing neuroepithelium. Restoring miR-322 expression in the neuroepithelium blocked maternal diabetes mellitus-induced caspase-3 and caspase-8 cleavage and cell apoptosis, leading to a neural tube defect reduction. Reversal of maternal diabetes mellitus-inhibited miR-322 via transgenic overexpression prevented TRAF3 up-regulation in embryos exposed to maternal diabetes mellitus. Activated IRE1α acted as an endonuclease and degraded precursor miR-322, resulting in mature miR-322 reduction.

CONCLUSION

This study supports the crucial role of the IRE1α-microRNA-TRAF3 circuit in the induction of neuroepithelial cell apoptosis and neural tube defect formation in pregnancies complicated by diabetes mellitus and identifies IRE1α and miR-322 as potential targets for preventing maternal diabetes mellitus-induced neural tube defects.

Maternal obesity induced metabolic disorders in offspring and myeloid reprogramming by epigenetic regulation

Maternal obesity and gestational diabetes are associated with childhood obesity and increased cardiovascular risk. In this review, we will discuss and summarize extensive clinical and experimental studies that metabolically imbalanced environment exposure in early life plays a critical role in influencing later susceptibility to chronic inflammatory diseases and metabolic syndrome. The effect of maternal obesity and metabolic disorders, including gestational diabetes cause Large-for-gestational-age (LGA) children to link future development of adverse health issues such as obesity, atherosclerosis, hypertension, and non-alcoholic fatty liver disease by immune reprogramming to adverse micro-environment. This review also addresses intrauterine environment-driven myeloid reprogramming by epigenetic regulations and the epigenetic markers as an underlying mechanism. This will facilitate future investigations regarding maternal-to-fetal immune regulation and the epigenetic mechanisms of obesity and cardiovascular diseases.