METTL3 mediates m6A modification of hsa_circ_0072380 to regulate the progression of gestational diabetes mellitus

BACKGROUND

m6A modification plays a vital role in gestational diabetes mellitus (GDM) progression. However, the role of METTL3 and differential m6A-modified circRNAs in GDMremainsto be investigated.

METHODS

Placental tissue samples from GDM patients and normal controls (NC) were collected to measure changes in m6A modification levels. MeRIP-seq on placental tissue was performed to detect differential m6A-modified circRNAs.High glucose (HG)-treated JEG3 cells were used to establish the GDM cell model. Differentially expressed circRNAs levels in GDM and NC groups were measured by qRT-PCR. We knocked down METTL3 to study its function. Additionally, we conducted functional recovery experiments. Dot blot assay was utilized to assess changes in m6A levels. MeRIP-qPCR was performed to evaluate the effect of knocking down METTL3 on m6A modification of hsa_circ_0072380 in JEG3 cells.

RESULTS

Compared with the NC group, the GDM group exhibited increased levels of m6A modification and METTL3 expression. Differences in m6A modification of circRNAs exist between the GDM and NC groups. Hsa_circ_0000994, hsa_circ_0058733, and hsa_circ_0072380 were significantly down-regulated in the GDM group while hsa_circ_0036376, hsa_circ_0000471, and hsa_circ_0001173 showed no significant differences between two groups. HG treatment promoted METTL3 expression and m6A level of JEG3 cells, and inhibited cell proliferation, migration, and invasion abilities. Knocking down METTL3 reversed these effects. After HG treatment, hsa_circ_0072380 was significantly down-regulated. Knocking down METTL3 led to up-regulation of hsa_circ_0072380, while knocking down hsa_circ_0072380 restored the function of SiMETTL3. Additionally, knocking down METTL3 significantly reduced the m6A modification of hsa_circ_0072380.

CONCLUSION

METTL3 mediated m6A modification of hsa_circ_0072380 to regulate GDM progression.

A risk prediction model of gestational diabetes mellitus based on traditional and genetic factors

BACKGROUND

Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication during pregnancy. We aimed to evaluate a risk prediction model of GDM based on traditional and genetic factors.

METHODS

A total of 2744 eligible pregnant women were included. Face-to-face questionnaire surveys were conducted to gather general data. Serum test results were collected from the laboratory information system. Independent risk factors for GDM were identified using univariate and multivariate logistic regression analyses. A GDM risk prediction model was constructed and evaluated with the Hosmer-Lemeshow goodness-of-fit test, goodness-of-fit calibration plot, receiver operating characteristic curve and area under the curve.

RESULTS

Among traditional factors, age ≥30 years, family history, GDM history, impaired glucose tolerance history, systolic blood pressure ≥116.22 mmHg, diastolic blood pressure ≥74.52 mmHg, fasting plasma glucose ≥5.0 mmol/L, 1-hour postprandial blood glucose ≥8.8 mmol/L, 2-h postprandial blood glucose ≥7.9 mmol/L, total cholesterol ≥4.50 mmol/L, low-density lipoprotein ≥2.09 mmol/L and insulin ≥11.5 mIU/L were independent risk factors for GDM. Among genetic factors, 11 single nucleotide polymorphisms (SNPs) (rs2779116, rs5215, rs11605924, rs7072268, rs7172432, rs10811661, rs2191349, rs10830963, rs174550, rs13266634 and rs11071657) were identified as potential predictors of the risk of postpartum DM among women with GDM history, collectively accounting for 3.6% of the genetic risk.

CONCLUSIONS

Both genetic and traditional factors contribute to the risk of GDM in women, operating through diverse mechanisms. Strengthening the risk prediction of SNPs for postpartum DM among women with GDM history is crucial for maternal and child health protection.

Maternal glucose levels and late pregnancy circulating extracellular vesicle and particle miRNAs in the MADRES pregnancy cohort

Maternal hyperglycemia during pregnancy adversely affects maternal and child outcomes. While mechanisms are not fully understood, maternal circulating miRNAs may play a role. We examined whether continuous glucose levels and hyperglycemia subtypes (gestational diabetes, type 2 diabetes, and glucose intolerance) were associated with circulating miRNAs during late pregnancy. Seven miRNAs (hsa-miR-107, hsa-let-7b-5p, hsa-miR-126-3p, hsa-miR-181a-5p, hsa-miR-374a-5p, hsa-miR-382-5p, and hsa-miR-337-5p) were associated (p < 0.05) with either hyperglycemia or continuous glucose levels prior to multiple testing correction. These miRNAs target genes involved in pathways relevant to maternal and child health, including insulin signaling, placental development, energy balance, and appetite regulation.

Association of mRNA expression and polymorphism of antioxidant glutathione-S-transferase (GSTM1 and GSTT1) genes with the risk of Gestational Diabetes Mellitus (GDM)

Gestational Diabetes Mellitus (GDM) is a medical complication during the gestational period in which woman who had never been diagnosed with diabetes develops hyperglycemia. Prior studies have demonstrated that the advancement of GDM and its consequences arises from a disparity between oxidants and antioxidants in the cells. The observed outcomes can be attributed to an excessive formation of reactive oxygen species (ROS) within the cells, coupled with a reduced activity of anti-oxidative enzymes. Glutathione S-transferase (GSTs) is recognized as an antioxidant enzyme that is belong to as a phase II family member of detoxifying enzymes. These metabolic multigene catalysts are found into the cytoplasm of the cell. GSTs play a vital part in the elimination of cellular ROS or free radicals. The study involves total 300 pregnant women, (150 GDM cases and 150 healthy controls). The polymorphism study of GSTs genes (GSTM1 and GSTT1) was determined by conventional Polymerase Chain Reaction (PCR). The mRNA expression study of GSTM1 and GSTT1 genes analysed by qPCR/ RT-PCR (quantitative PCR/Real-Time PCR) followed by statistical analysis done using Prism8 software (version 8.01). The study revealed statistically significant variations in biochemical parameters between GDM cases and controls. It was found GSTM1-null (GSTM1-/-) polymorphism significantly (P < 0.0001) most prevalent in GDM cases (56.7%) when compared to healthy control (28%). However, no significant difference was observed for GSTT1 null and present polymorphism (P = 0.906). The gene expression levels of both GSTM1 and GSTT1 were found considerably downregulated in individuals with GDM as compared to the control group (P < 0.0001). The downregulation of gene expression has a significant (P<0.0001) association with the null/deletion polymorphism of both GSTM1/ GSTT1 genes respectively. Null/deletion genotype of GSTM1 gene and its expression showed significant association with GDM. Therefore, this gene variant has the potential to be used as a prognostic biomarker for GDM. However, there is need to study this gene variant in larger sample size and different ethnicity.

Genetic variants related to insulin metabolism are associated with gestational diabetes mellitus

The current study sought to investigate the associations of common genetic risk variants with gestational diabetes mellitus (GDM) risk in the north Indian population and to evaluate their utility in identifying GDM cases. A case-control study, including 300 pregnant women, was included, and clinical and pathological information was collected. The amplification-refractory mutation system (ARMS) was used for genotyping four single nucleotide polymorphisms (SNPs), namely FTO (rs9939609), PPARG2 (rs1801282), SLC30A8 (rs13266634), and TCF7L2 (rs12255372). The odds ratio and confidence interval were determined for each SNP in different genetic models. Further, attributable risk, population penetrance, and relative risk were also calculated. The risk allele A of FTO (rs9939609) poses a two times higher risk of GDM (p = 0.02, OR = 2.5). The CG and GG genotypes of PPARG2 (rs1801282) have half a lower risk of GDM. In SLC30A8 (rs13266634), the recessive model analysis showed a two times higher risk of having GDM, while the recessive model (TT vs. GG + GT) analysis in TCF7L2 (rs12255372) indicates a lower risk of GDM. Finally, the relative risk, population penetrance, and attributable risk for risk allele in all four variants was higher in GDM mothers. All four polymorphisms were found to be significantly associated with BMI, HbA1c, and insulin. Our study first time confirmed a significant association with GDM for four variants, FTO, PPARG2, SLC30A8, and TCF7L2, in the North Indian population.

The causal relationship between 91 inflammatory cytokines and Gestational Diabetes Mmellitus: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Gestational Diabetes Mellitus (GDM) poses significant risks to maternal and fetal health, yet its precise etiology remains unclear. Observational studies have demonstrated a link between specific inflammatory cytokines and the occurrence of GDM, but the causal relationships remain uncertain.

METHODS

Utilizing publicly accessible genetic data, we performed a bidirectional two-sample mendelian randomization (MR) analysis to elucidate the causal association between 91 inflammatory cytokines and GDM. Sensitivity analysis was carried out to evaluate the robustness, heterogeneity, and potential presence of horizontal pleiotropy within the results.

RESULTS

Elevated levels of Interleukin-7 (IL7) and Neurturin (NRTN) (OR=1.104, 95 % CI=1.003-1.216, p = 0.042; OR=1.102, 95 % CI=1.023-1.187, p = 0.010), along with decreased levels of Glial cell line-derived neurotrophic factor (GDNF), Interleukin-12 subunit beta (IL12β), and Interleukin-20 (IL20) (OR=0.911, 95 % CI=0.849-0.979, p = 0.010;OR=0.955, 95 % CI=0.916-0.996, p = 0.033; OR=0.892, 95 % CI=0.819-0.971, p = 0.008), are associated with increased GDM risk. Additionally, GDM occurrence correlates with increased Matrix metalloproteinase-10 (MMP-10) and decreased Interleukin-20 receptor subunit alpha (IL-20Rα) levels (OR=1.042, 95 % CI=1.002-1.084, p = 0.038; OR=0.949, 95 % CI=0.909-0.992, p = 0.021). Sensitivity analyses detected no significant heterogeneity or pleiotropy.

CONCLUSION

This study has clarified the causal link between inflammatory cytokines and GDM, thereby enhancing our comprehension of the potential mechanisms involved in GDM pathogenesis. These findings offer new insights into the etiology, diagnosis, and therapeutic strategies for GDM.

Circulating inflammatory cytokines and gestational diabetes mellitus: Unraveling the role of macrophage migration inhibitory factor (MIF) through a bidirectional mendelian randomization study

BACKGROUND

Several studies have identified associations between some of circulating inflammatory cytokines and gestational diabetes mellitus (GDM). However, the causal role of these associations remains unclear and unsystematic. We aimed to provide evidence for the causal relationships between circulating inflammatory cytokines and gestational diabetes mellitus.

METHODS

We performed bidirectional two-sample Mendelian randomization (2SMR) to investigate the causal connection between circulating inflammatory cytokines and gestational diabetes mellitus. Publicly accessible data for circulating inflammatory cytokines (8,293 individuals) and gestational diabetes mellitus (123,579 individuals) were obtained from genome-wide association study (GWAS).

RESULTS

Only one causal association was identified between circulating inflammatory cytokines and GDM. The inverse variance weighting (IVW) method showed that macrophage migration inhibitory factor (MIF) increased the risk of GDM (OR 1.162, 95%CI 1.044,1.293). Moreover, two causal associations were detected between GDM and circulating inflammatory cytokines. GDM was negatively correlated with interferon gamma-induced protein 10 (IP10) (Beta -0.129, 95%CI -0.236,-0.231) and interleukin-18 (IL18) (Beta -0.133, 95%CI -0.241,-0.026).

CONCLUSION

Mendelian randomization study revealed MIF as a risk factor for gestational diabetes mellitus. This finding offers a new and valuable insight into the pathophysiological mechanisms underlying GDM.

Galectin-7 Expression in the Placentas of Women with Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a common condition during pregnancy. The prevalence of GDM is continuously increasing worldwide. Due to accessible diagnostic methods and a clear understanding of risk factors, GDM can be effectively diagnosed and managed. Galectins may influence immunomodulatory and inflammatory processes. This study examines the expression of galectin-7 in the placentas of women with gestational diabetes (GDM), compares it to its expression in healthy pregnancies, and evaluates the associated clinical outcomes. The placentas of 40 healthy women and 40 GDM placentas were included in the cohort. The expression level of galecin-7 was measured in the syncytiotrophoblast (SCT) and in the decidua of the placenta by immunohistochemistry and double immunofluorescence staining. The evaluation was performed by an immunoreactivity score (IRS). The study results show an increased expression of galectin-7 in the SCT and the decidua of GDM placentas as compared to the placentas of the control group. Elevated levels of galectin-7 were observed in both the nucleus and the cytoplasm. This study investigated the hypothesis that galectins are involved in pathophysiological processes of gestational diabetes. Statistical analysis of gene expression patterns confirmed that galectin-7 is indeed upregulated in GDM placentas. Further studies are needed to show the correlation of galectin-7 and the development and maintenance of gestational diabetes mellitus.

The role of microRNAs in pregnancies complicated by maternal diabetes

With the global prevalence of diabetes increasing, more people of reproductive age are experiencing hyperglycaemic pregnancies. Maternal Type 1 (T1DM) or Type 2 (T2DM) diabetes mellitus, and gestational diabetes mellitus (GDM) are associated with maternal cardiovascular and metabolic complications. Pregnancies complicated by maternal diabetes also increase the risk of short- and long-term health complications for the offspring, including altered fetal growth and the onset of T2DM and cardiometabolic diseases throughout life. Despite advanced methods for improving maternal glucose control, the prevalence of adverse maternal and offspring outcomes associated with maternal diabetes remains high. The placenta is a key organ at the maternal-fetal interface that regulates fetal growth and development. In pregnancies complicated by maternal diabetes, altered placental development and function has been linked to adverse outcomes in both mother and fetus. Emerging evidence suggests that microRNAs (miRNAs) are key molecules involved in mediating these changes. In this review, we describe the role of miRNAs in normal pregnancy and discuss how miRNA dysregulation in the placenta and maternal circulation is associated with suboptimal placental development and pregnancy outcomes in individuals with maternal diabetes. We also discuss evidence demonstrating that miRNA dysregulation may affect the long-term health of mothers and their offspring. As such, miRNAs are potential candidates as biomarkers and therapeutic targets in diabetic pregnancies at risk of adverse outcomes.

Serum CD44 levels in early pregnancy and its genetic variants for increased risk of gestational diabetes mellitus in Chinese pregnant women

This study aimed to explore associations of serum cluster of differentiation 44 (CD44) levels and its genetic variants in early pregnancy with gestational diabetes mellitus (GDM). We conducted a 1:1 case-control study (n = 414) nested in a prospective cohort of 22,302 pregnant women recruited from 2010 to 2012 in Tianjin, China. Blood samples were collected at the first antenatal care visit (at a median of 10th gestational week). Binary conditional logistic regressions were performed to examine associations of serum CD44 levels and its genetic variants with increased risk of GDM. In this study, we found that serum CD44 levels in early pregnancy was associated with GDM risk in a U-shaped manner. High serum CD44 levels and its genetic risk score in early pregnancy were associated with markedly increased risk of GDM after adjustment for traditional confounders (OR: 1.95, 95%CI: 1.12-3.40 & 1.95, 1.05-3.61). Furthermore, after adjustment for serum CD44 levels, the OR of CD44 genetic risk score for GDM was slightly attenuated but not significant (1.84, 0.98-3.48). In conclusion, serum CD44 levels and its genetic variants in early pregnancy were associated with GDM risk in Chinese pregnant women, with the effect of CD44 genetic variants being accounted for by serum CD44. SIGNIFICANCE: Recent studies suggested that pregnant women with GDM may have abnormal levels of CD44 and abnormal expression of CD44 gene, but it is uncertain whether abnormal CD44 plays a causal role in occurrence of GDM. Specifically, it remains unknown whether serum CD44 levels in early pregnancy and its genetic variants can predict the later occurrence of GDM. In this study, we found that high serum CD44 levels in early pregnancy and its genetic variants were associated with markedly increased risk of GDM in Chinese pregnant women, with the effect of CD44 genetic variants being largely accounted for by serum CD44 levels. Our study is the first reporting that serum CD44 levels and its genetic variants were associated with markedly increased risk of GDM. These multi-omics risk markers may be useful for identification of women at high risk of GDM in early pregnancy. Our findings also provide new insights into the disease mechanisms.

Mendelian randomization analysis reveals causal effects of blood lipidome on gestational diabetes mellitus

BACKGROUND

Observational studies have revealed associations between maternal lipid metabolites and gestational diabetes mellitus (GDM). However, whether these associations are causal remain uncertain.

OBJECTIVE

To evaluate the causal relationship between lipid metabolites and GDM.

METHODS

A two-sample Mendelian randomization (MR) analysis was performed based on summary statistics. Sensitivity analyses, validation analyses and reverse MR analyses were conducted to assess the robustness of the MR results. Additionally, a phenome-wide MR (Phe-MR) analysis was performed to evaluate potential side effects of the targeted lipid metabolites.

RESULTS

A total of 295 lipid metabolites were included in this study, 29 of them had three or more instrumental variables (IVs) suitable for sensitivity analyses. The ratio of triglycerides to phosphoglycerides (TG_by_PG) was identified as a potential causal biomarker for GDM (inverse variance weighted (IVW) estimate: odds ratio (OR) = 2.147, 95% confidential interval (95% CI) 1.415-3.257, P = 3.26e-4), which was confirmed by validation and reverse MR results. Two other lipid metabolites, palmitoyl sphingomyelin (d18:1/16:0) (PSM(d18:1/16:0)) (IVW estimate: OR = 0.747, 95% CI 0.583-0.956, P = 0.021) and triglycerides in very small very low-density lipoprotein (XS_VLDL_TG) (IVW estimate: OR = 2.948, 95% CI 1.197-5.215, P = 0.015), were identified as suggestive potential biomarkers for GDM using a conventional cut-off P-value of 0.05. Phe-MR results indicated that lowering TG_by_PG had detrimental effects on two diseases but advantageous effects on the other 13 diseases.

CONCLUSION

Genetically predicted elevated TG_by_PG are causally associated with an increased risk of GDM. Side-effect profiles indicate that TG_by_PG might be a target for GDM prevention, though caution is advised due to potential adverse effects on other conditions.

Unravelling the Metabolic Underpinnings of Gestational Diabetes Mellitus: A Comprehensive Mendelian Randomisation Analysis Identifying Causal Metabolites and Biological Pathways

BACKGROUND

Gestational diabetes mellitus (GDM) has a strong genetic predisposition. Integrating metabolomics with Mendelian randomisation (MR) analysis offers a potent method to uncover the metabolic factors causally linked to GDM pathogenesis.

OBJECTIVES

This study aims to identify specific metabolites and metabolic pathways causally associated with GDM susceptibility through a comprehensive MR analysis. Additionally, it seeks to explore the potential of these identified metabolites as circulating biomarkers for early GDM detection and risk assessment. Furthermore, it aims to evaluate the implicated metabolic pathways as potential therapeutic targets for preventive or interventional strategies against GDM.

METHODS

A two-sample MR study was conducted using summary statistics from a metabolite genome-wide association study (GWAS) of 8299 individuals and a GDM GWAS comprising 13,039 cases and 197,831 controls. Rigorous criteria were applied to select robust genetic instruments for 850 metabolites.

RESULTS

MR analysis revealed 47 metabolites exhibiting putative causal associations with GDM risk. Among these, five metabolites demonstrated statistically significant associations after multiple-testing correction: Beta-citrylglutamate, Isobutyrylcarnitine (c4), 1,2-dilinoleoyl-GPC (18:2/18:2), Alliin and Cis-3,4-methyleneheptanoylcarnitine. Importantly, all these metabolites exhibited protective effects against GDM development. Additionally, metabolic pathway enrichment analysis implicated the methionine metabolism and spermidine and spermine biosynthesis pathways in the pathogenesis of GDM.

CONCLUSION

This comprehensive MR study has robustly identified specific metabolites and metabolic pathways with causal links to GDM susceptibility. These findings provide novel insights into the metabolic underpinnings of GDM aetiology and offer promising translational implications. The identified metabolites could serve as potential circulating biomarkers for early detection and risk stratification, while the implicated metabolic pathways may represent therapeutic targets for preventive or interventional strategies against GDM.

Unveiling the role of microRNAs in metabolic dysregulation of Gestational Diabetes Mellitus

Gestational Diabetes Mellitus (GDM) presents a significant health concern globally, necessitating a comprehensive understanding of its metabolic intricacies for effective management. MicroRNAs (miRNAs) have emerged as pivotal regulators in GDM pathogenesis, influencing glucose metabolism, insulin signaling, and lipid homeostasis during pregnancy. Dysregulated miRNA expression, both upregulated and downregulated, contributes to GDM-associated metabolic abnormalities. Ethnic and temporal variations in miRNA expression underscore the multifaceted nature of GDM susceptibility. This review examines the dysregulation of miRNAs in GDM and their regulatory functions in metabolic disorders. We discuss the involvement of specific miRNAs in modulating key pathways implicated in GDM pathogenesis, such as glucose metabolism, insulin signaling, and lipid homeostasis. Furthermore, we explore the potential diagnostic and therapeutic implications of miRNAs in GDM management, highlighting the promise of miRNA-based interventions for mitigating the adverse consequences of GDM on maternal and offspring health.

miR-942-5p Regulates Proliferation, Invasion and EMT of Trophoblast Cells in Gestational Diabetes by Targeting the CEBPA

Objective

Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder caused by abnormal glucose metabolism during pregnancy. Trophoblast dysfunction induced by hyperglycemia during pregnancy is the main factor leading to the development of GDM. In this study, we evaluated the expression of miR-942-5p in the placenta of patients with GDM and its regulation of trophoblast cell biological function.

Methods

HTR-8/SVneo trophoblast cells were incubated with glucose to establish in vitro models, and miR-942-5p mimics transfected cells were added. The expression levels of miR-942-5p, CCAAT-enhancer-binding protein alpha (CEBPA) and N-cadherin in tissues and cells were detected by reverse-transcription quantitative polymerase chain reaction (RT-qPCR), protein blotting and immunohistochemistry (IHC). MTT, flow cytometry and Transwell assays were used to determine changes in cell proliferation, apoptosis and invasion. Dual-luciferase reporter assay and Pearson analysis were used to confirm the association between miR-942-5p and CEBPA.

Results

miR-942-5p and N-cadherin were decreased in placental tissue and in human placental trophoblast cells (HTR-8/SVneo) exposed to high glucose (HG) conditions, while CEBPA was increased in placental tissue and HTR-8/SVneo exposed to HG conditions. Elevated levels of miR-942-5p suppressed apoptosis induced by HG and facilitated the proliferative and invasive capacities of HTR-8/SVneo. Mechanistically, we confirmed that miR-942-5p overexpression directly targeted CEBPA and suppressed CEBPA expression, while upregulating N-cadherin expression, which is involved in the EMT process of trophoblast cells and alleviated the dysfunction of trophoblast cells induced by HG in GDM.

Conclusion

Overexpression of miR-942-5p promotes proliferation, invasion and EMT of trophoblast cells by targeting and negatively regulating CEBPA. These findings offer novel understanding regarding the treatment of GDM.

Genome-Wide Polygenic Risk Score Predicts Incident Type 2 Diabetes in Women With History of Gestational Diabetes

OBJECTIVE

Women with a history of gestational diabetes mellitus (GDM) are at increased risk of developing type 2 diabetes (T2D). It remains unclear whether genetic information improves prediction of incident T2D in these women.

RESEARCH DESIGN AND METHODS

Using five independent cohorts representing four different ancestries (n = 1,895), we investigated whether a genome-wide T2D polygenic risk score (PRS) is associated with increased risk of incident T2D. We also calculated the area under the receiver operating characteristics curve (AUROC) and continuous net reclassification improvement (NRI) following the incorporation of T2D PRS into clinical risk models to assess the diagnostic utility.

RESULTS

Among 1,895 women with previous history of GDM, 363 (19.2%) developed T2D in a range of 2 to 30 years. T2D PRS was higher in those who developed T2D (-0.08 vs. 0.31, P = 2.3 × 10-11) and was associated with an increased risk of incident T2D (odds ratio 1.52 per 1-SD increase, 95% CI 1.05-2.21, P = 0.03). In a model that includes age, family history of diabetes, systolic blood pressure, and BMI, the incorporation of PRS led to an increase in AUROC for T2D from 0.71 to 0.74 and an intermediate improvement of NRI (0.32, 95% CI 0.15-0.49, P = 3.0 × 10-4). Although there was variation, a similar trend was observed across study cohorts.

CONCLUSIONS

In cohorts of GDM women with diverse ancestry, T2D PRS was significantly associated with future development of T2D. A significant but small improvement was observed in AUROC when T2D PRS was integrated into clinical risk models to predict incident T2D.

MiR-322-5p is involved in regulating chondrocyte proliferation and differentiation in offspring's growth plate of maternal gestational diabetes

Pregestational diabetes mellitus (PGDM) has an impact on fetal bone formation, but the underlying mechanism is still obscure. Although miRNAs have been extensively investigated throughout bone formation, their effects on fetal bone development caused by PGDM still need clarification. This study intends to examine the mechanism by which hyperglycemia impairs the bone formation of offspring via miR-322-5p (miR-322). In this study, miR-322 was selected by systemically screening utilizing bioinformatics and subsequent validation experiments. Using streptozotocin (STZ)-induced diabetic mice and ATDC5 cell lines, we found that miR-322 was abundantly expressed in the proliferative and hypertrophic zones of the growth plate, and its expression pattern was disturbed in the presence of hyperglycemia, suggesting that miR-322 is involved in the chondrocyte proliferation and differentiation in absence/presence of hyperglycemia. This observation was proved by manipulating miR-322 expression in ATDC5 cells by transfecting mimic and inhibitor of miR-322. Furthermore, Adamts5, Col12a1, and Cbx6 were identified as the potential target genes of miR-322, verified by the co-transfection of miR-322 inhibitor and the siRNAs, respectively. The evaluation criteria are the chondrocyte proliferation and differentiation and their relevant key gene expressions (proliferation: Sox9 and PthIh; differentiation: Runx2 and Col10a1) after manipulating the gene expressions in ATDC5 cells. This study revealed the regulative role miR-322 on chondrocyte proliferation and differentiation of growth plate by targeting Adamts5, Col12a1, and Cbx6 in hyperglycemia during pregnancy. This translational potential represents a promising avenue for advancing our understanding of bone-related complications in diabetic pregnancy and mitigating bone deficiencies in diabetic pregnant individuals, improving maternal and fetal outcomes.

Deciphering DNA Methylation in Gestational Diabetes Mellitus: Epigenetic Regulation and Potential Clinical Applications

Gestational diabetes mellitus (GDM) represents a prevalent complication during pregnancy, exerting both short-term and long-term impacts on maternal and offspring health. This review offers a comprehensive outline of DNA methylation modifications observed in various maternal and offspring tissues affected by GDM, emphasizing the intricate interplay between DNA methylation dynamics, gene expression, and the pathogenesis of GDM. Furthermore, it explores the influence of environmental pollutants, maternal nutritional supplementation, and prenatal gut microbiota on GDM development through alterations in DNA methylation profiles. Additionally, this review summarizes recent advancements in DNA methylation-based diagnostics and predictive models in early GDM detection and risk assessment for subsequent type 2 diabetes. These insights contribute significantly to our understanding of the epigenetic mechanisms underlying GDM development, thereby enhancing maternal and fetal health outcomes and advocating further efforts in this field.

Uric acid and risk of gestational diabetes mellitus: an observational study and mendelian randomization analysis

OBJECTIVE

Our aim was to explore the relationship between serum uric acid (UA) levels in early pregnancy and the development of gestational diabetes mellitus (GDM), and to further explore whether there is a causal relationship.

METHODS

684 pregnant women with GDM and 1162 pregnant women without GDM participated in this study. 311 pregnant women with GDM and 311 matched controls were enrolled in a 1:1 case-control study. We used conditional logistic regression to explore the relationship between UA levels and the risk of developing GDM. The causal relationship between the two was examined by two-sample Mendelian randomization (MR) analysis.

RESULTS

In the 1:1 matched population, the odds ratio (OR) of developing GDM compared with the extreme tertiles of UA levels was 1.967 (95% confidence interval [CI]: 1.475-2.625; P < 0.001). Restricted cubic spline analyses showed a linear relationship between UA and GDM when UA exceeded 222 µmol/L. GDM and UA levels maintained a statistically significant positive correlation in different stratified regression analyses (P < 0.001). However, no evidence of a causal relationship between uric acid and GDM was found by MR analyses with an OR of 1.06 (95% CI: 0.91-1.25) per unit increase in UA.

CONCLUSION

There is a positive correlation between UA levels in early pregnancy and the subsequent risk of developing GDM. However, no genetic evidence was found to support a cause-effect relationship between UA and GDM.

Circulating extracellular vesicle-derived miR-1299 disrupts hepatic glucose homeostasis by targeting the STAT3/FAM3A axis in gestational diabetes mellitus

BACKGROUND

Extracellular vesicles (EVs) are membrane-enclosed structures containing lipids, proteins, and RNAs that play a crucial role in cell-to-cell communication. However, the precise mechanism through which circulating EVs disrupt hepatic glucose homeostasis in gestational diabetes mellitus (GDM) remains unclear.

RESULTS

Circulating EVs isolated from human plasma were co-cultured with mammalian liver cells to investigate the potential induction of hepatic insulin resistance by GDM-EVs using glucose output assays, Seahorse assays, metabolomics, fluxomics, qRT-PCR, bioinformatics analyses, and luciferase assays. Our findings demonstrated that hepatocytes exposed to GDM-EVs exhibited increased gluconeogenesis, attenuated energy metabolism, and upregulated oxidative stress. Particularly noteworthy was the discovery of miR-1299 as the predominant miRNA in GDM-EVs, which directly targeting the 3'-untranslated regions (UTR) of STAT3. Our experiments involving loss- and gain-of-function revealed that miR-1299 inhibits the insulin signaling pathway by regulating the STAT3/FAM3A axis, resulting in increased insulin resistance through the modulation of mitochondrial function and oxidative stress in hepatocytes. Moreover, experiments conducted in vivo on mice inoculated with GDM-EVs confirmed the development of glucose intolerance, insulin resistance, and downregulation of STAT3 and FAM3A.

CONCLUSIONS

These results provide insights into the role of miR-1299 derived from circulating GDM-EVs in the progression of insulin resistance in hepatic cells via the STAT3/FAM3A axis and downstream metabolic reprogramming.

Vitamin D and Gestational Diabetes Mellitus in the IEU OpenGWAS Project: A Two-Sample Bidirectional Mendelian Randomization Study

BACKGROUND

Gestational diabetes mellitus (GDM) is one of the most prevalent pregnancy problems, and there is still debate over the relationship between vitamin D and GDM.

OBJECTIVES

Our objective is to investigate the correlation between vitamin D and GDM by employing Mendelian randomization (MR) with summary data obtained from genome-wide association studies (GWAS).

METHODS

Data on exposures and outcomes, namely vitamin D, vitamin D insufficiency, and GDM, were acquired from the IEU OpenGWAS Project. Bidirectional MR analysis was performed utilizing the inverse variance weighted (IVW) method as the principal analytical approach. The complementary approaches employed in this study encompassed weighted median, simple mode, weighted mode, and MR-Egger regression. A series of sensitivity analysis were conducted in order to assess the reliability of the obtained results.

RESULTS

The data were acquired from the IEU OpenGWAS Project. Following the application of the three assumptions of MR, 13 single nucleotide polymorphisms (SNPs) were included in the MR analysis for vitamin D levels and vitamin D deficiency on GDM, and 10 and 26 SNPs were included for GDM on vitamin D levels and deficiency, respectively. The findings from the IVW analysis revealed a significant positive correlation between vitamin D levels and GDM (OR = 1.057, 95% CI: 1.011-1.104, p = 0.015). Conversely, a negative correlation was seen between vitamin D deficiency and GDM (OR = 0.979, 95% CI: 0.959-0.999, p = 0.039). The results of the reverse MR study revealed no evidence of reverse causation between GDM and vitamin D. The findings from multiple MR approaches were in line with the direction of IVW analysis. Sensitivity analysis revealed no evidence of heterogeneity, pleiotropy, or outliers, suggesting the robustness of the results.

CONCLUSIONS

There exists a causal association between vitamin D and GDM, whereby vitamin D levels serve as a risk factor for GDM.

Longitudinal integrative cell-free DNA analysis in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) presents varied manifestations throughout pregnancy and poses a complex clinical challenge. High-depth cell-free DNA (cfDNA) sequencing analysis holds promise in advancing our understanding of GDM pathogenesis and prediction. In 299 women with GDM and 299 matched healthy pregnant women, distinct cfDNA fragment characteristics associated with GDM are identified throughout pregnancy. Integrating cfDNA profiles with lipidomic and single-cell transcriptomic data elucidates functional changes linked to altered lipid metabolism processes in GDM. Transcription start site (TSS) scores in 50 feature genes are used as the cfDNA signature to distinguish GDM cases from controls effectively. Notably, differential coverage of the islet acinar marker gene PRSS1 emerges as a valuable biomarker for GDM. A specialized neural network model is developed, predicting GDM occurrence and validated across two independent cohorts. This research underscores the high-depth cfDNA early prediction and characterization of GDM, offering insights into its molecular underpinnings and potential clinical applications.

25-Hydroxyvitamin D, Vitamin D Binding Protein and Gestational Diabetes Mellitus: A Two-Sample Mendelian Randomization Study

BACKGROUND

Numerous studies have examined whether vitamin D is associated with gestational diabetes mellitus (GDM). Nevertheless, it is still challenging to determine the causality, due to a number of shortcomings in observational research and randomized controlled trials.

OBJECTIVE

Mendelian randomization (MR) with two samples was conducted to investigate the potential causative association between 25-hydroxyvitamin D (25(OH)D), vitamin D binding protein (VDBP) and GDM risk.

METHODS

Publicly accessible summary data from independent cohorts were used for two-sample MR. For 25(OH)D, we obtained data from UK Biobank, IEU and EBI, then performed a meta-analysis to enhance the statistical power (via METAL); for VDBP, data were obtained from the INTERVAL study; for GDM, data were obtained from FinnGen. The inverse variance weighted (IVW) approach was performed as the main analysis, together with several sensitivity analyses, such as MR-Egger, maximum likelihood, weighted median, and weighted mode.

RESULTS

The IVW results revealed a weak negative causal connection between 25(OH)D and GDM risk [OR (95% CI) = 0.71 (0.50, 0.99), p = 0.046]. However, the causal association was unstable according to sensitivity analyses, and Cochran's Q test revealed significant heterogeneity. After removing BMI-related IVs, the causal association between 25(OH)D and GDM disappeared [OR (95% CI) = 0.76 (0.55, 1.06), p = 0.101]. In addition, our study found no proof to support the assumption that VDBP level was related to GDM risk causally [OR (95% CI) = 0.98 (0.93, 1.03), p = 0.408].

CONCLUSIONS

According to this study, a weak negative causal association between 25(OH)D and GDM risk was found, while we had little proof to support the link between VDBP and GDM. To further explore whether total or free 25(OH)D levels and GDM are causally related, GWAS data with an emphasis on women of reproductive age and other ethnic groups are required.

Predicting gestational diabetes mellitus risk at 11-13 weeks' gestation: the role of extrachromosomal circular DNA

BACKGROUND

Gestational diabetes mellitus (GDM) significantly impacts maternal and infant health both immediately and over the long term, yet effective early diagnostic biomarkers are currently lacking. Thus, it is essential to identify early diagnostic biomarkers for GDM risk screening. Extrachromosomal circular DNA (eccDNA), being more stable than linear DNA and involved in disease pathologies, is a viable biomarker candidate for diverse conditions. In this study, eccDNA biomarkers identified for early diagnosis and assessment of GDM risk were explored.

METHODS

Using Circle-seq, we identified plasma eccDNA profiles in five pregnant women who later developed GDM and five matched healthy controls at 11-13 weeks of gestation. These profiles were subsequently analyzed through bioinformatics and validated through outward PCR combined with Sanger sequencing. Furthermore, candidate eccDNA was validated by quantitative PCR (qPCR) in a larger cohort of 70 women who developed GDM and 70 normal glucose-tolerant (NGT) subjects. A ROC curve assessed the eccDNA's diagnostic potential for GDM.

RESULTS

2217 eccDNAs were differentially detected between future GDM patients and controls, with 1289 increased and 928 decreased in abundance. KEGG analysis linked eccDNA genes mainly to GDM-related pathways such as Rap1, MAPK, and PI3K-Akt, and Insulin resistance, among others. Validation confirmed a significant decrease in eccDNA PRDM16circle in the plasma of 70 women who developed GDM compared to 70 NGT women, consistent with the eccDNA-seq results. PRDM16circle showed significant diagnostic value in 11-13 weeks of gestation (AUC = 0.941, p < 0.001).

CONCLUSIONS

Our study first demonstrats that eccDNAs are aberrantly produced in women who develop GDM, including PRDM16circle, which can predict GDM at an early stage of pregnancy, indicating its potential as a biomarker.

TRIAL REGISTRATION

ChiCTR2300075971, http://www.chictr.org.cn . Registered 20 September 2023.

Integrating polygenic risk scores in the prediction of gestational diabetes risk in China

Background

Polygenic risk scores (PRS) serve as valuable tools for connecting initial genetic discoveries with clinical applications in disease risk estimation. However, limited studies have explored the association between PRS and gestational diabetes mellitus (GDM), particularly in predicting GDM risk among Chinese populations.

Aim

To evaluate the relationship between PRS and GDM and explore the predictive capability of PRS for GDM risk in a Chinese population.

Methods

A prospective cohort study was conducted, which included 283 GDM and 2,258 non-GDM cases based on demographic information on pregnancies. GDM was diagnosed using the oral glucose tolerance test (OGTT) at 24-28 weeks. The strength of the association between PRS and GDM odds was assessed employing odds ratios (ORs) with 95% confidence intervals (CIs) derived from logistic regression. Receiver operating characteristic curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were employed to evaluate the improvement in prediction achieved by the new model.

Results

Women who developed GDM exhibited significantly higher PRS compared to control individuals (OR = 2.01, 95% CI = 1.33-3.07). The PRS value remained positively associated with fasting plasma glucose (FPG), 1-hour post-glucose load (1-h OGTT), and 2-hour post-glucose load (2-h OGTT) (all p < 0.05). The incorporation of PRS led to a statistically significant improvement in the area under the curve (0.71, 95% CI: 0.66-0.75, p = 0.024) and improved discrimination and classification (IDI: 0.007, 95% CI: 0.003-0.012, p < 0.001; NRI: 0.258, 95% CI: 0.135-0.382, p < 0.001).

Conclusions

This study highlights the increased odds of GDM associated with higher PRS values and modest improvements in predictive capability for GDM.

Functional genetic variants and susceptibility and prediction of gestational diabetes mellitus

The aetiological mechanism of gestational diabetes mellitus (GDM) has still not been fully understood. The aim of this study was to explore the associations between functional genetic variants screened from a genome-wide association study (GWAS) and GDM risk among 554 GDM patients and 641 healthy controls in China. Functional analysis of single nucleotide polymorphisms (SNPs) positively associated with GDM was further performed. Univariate regression and multivariate logistic regression analyses were used to screen clinical risk factors, and a predictive nomogram model was established. After adjusting for age and prepregnancy BMI, rs9283638 was significantly associated with GDM susceptibility (P < 0.05). Moreover, an obvious interaction between rs9283638 and clinical variables was detected (Pinteraction < 0.05). Functional analysis confirmed that rs9283638 can regulate not only target gene transcription factor binding, but it also regulates the mRNA levels of SAMD7 (P < 0.05). The nomogram model constructed with the factors of age, FPG, 1hPG, 2hPG, HbA1c, TG and rs9283638 revealed an area under the ROC curve of 0.920 (95% CI 0.902-0.939). Decision curve analysis (DCA) suggested that the model had greater net clinical benefit. Conclusively, genetic variants can alter women's susceptibility to GDM by affecting the transcription of target genes. The predictive nomogram model constructed based on genetic and clinical variables can effectively distinguish individuals with different GDM risk factors.