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.

TGFß1, SNAIL2, and PAPP-A Expression in Placenta of Gestational Diabetes Mellitus Patients.

Background: Gestational diabetes mellitus (GDM) is a pregnancy-related diabetic condition that may cause serious complications. However, its pathogenesis remains unclear. Placental damage due to GDM may lead to several health issues that cannot be ignored. Thus, we aimed to identify the mechanisms underlying GDM by screening differentially expressed genes (DEGs) related to vascular endothelial cells in the GDM databases and verify the expression of these DEGs in the placentas of women afflicted by GDM. Methods: We used GDM microarray datasets integrated from the Gene Expression Omnibus (GEO) database. Functional annotation and protein-protein interaction (PPI) analyses were used to screen DEGs. Placental tissues from 20 pregnant women with GDM and 20 healthy pregnant women were collected, and differential gene expression in the placental tissues was verified via qRT-PCR, western blotting, and immunofluorescence. Results: Bioinformatics analysis revealed three significant DEGs: SNAIL2, PAPP-A, and TGFß1. These genes were all predicted to be underexpressed in patients with GDM. The results of qRT-PCR, western blot, and immunofluorescence analyses indicated that SNAIL2 and PAPP-A in the placenta tissue of patients with GDM were significantly underexpressed. However, TGFß1 in the placenta tissues of GDM was significantly overexpressed. Conclusion: SNAIL2, TGFß1, and PAPP-A may affect the placentas of pregnant women with GDM, warranting further investigation.

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.

Risk cycling in diabetes and autism spectrum disorder: a bidirectional Mendelian randomization study.

Objective: The relationship between diabetes mellitus (DM) and autism spectrum disorder (ASD) remains controversial. This study aimed to analyze the causal relationship between different types of DM and ASD by bidirectional Mendelian randomization (MR). Methods: Single nucleotide polymorphisms for type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), gestational diabetes mellitus (GDM), and ASD were obtained from genome-wide association studies. Subsequently, inverse variance weighted, MR-Egger, and weighted median were used to test the exposure-outcome causality. Finally, MR-Egger's intercept, Cochran's Q, and leave-one-out method were used to assess horizontal pleiotropy, heterogeneity, and sensitivity of the results, respectively. Results: The positive analysis showed that T2DM was associated with an increased risk of ASD, whereas neither T1DM nor GDM was associated with the risk of ASD. The reverse analysis showed that ASD was associated with an increased risk of T2DM, while it was not associated with the risk of either T1DM or GDM. MR-Egger intercept showed no horizontal pleiotropy (p > 0.05) for these results. Cochran's Q showed no heterogeneity expect for the results of T1DM on the risk of ASD, and leave-one-out sensitivity analysis showed these results were robust. Conclusion: This MR analysis suggests that T2DM and ASD are reciprocal risk factors and that they may create an intergenerational risk cycling in female patients. Aggressive prevention and treatment of T2DM and ASD help to break the trap of this risk cycling. Additionally, this study does not support a causal relationship between T1DM and ASD, as well as GDM and ASD. And more studies are needed in the future to continue to explore the interactions and underlying mechanisms between different types of DM and ASD.

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.

Association between frailty and gestational diabetes mellitus: a bidirectional and multivariable Mendelian randomization study.

Background: The causality between frailty and gestational diabetes mellitus (GDM) has not yet been fully explored. A potential bidirectional causality was also needed to be confirmed. Methods: A bidirectional two-sample Mendelian randomization (MR) was conducted, with frailty-related data was collected from UK Biobank and TwinGen and GDM-related data was collected from the FinnGen consortium. We performed univariable and multivariable-adjusted MR with adjustments for body mass index (BMI). Several methodologies of MR were conducted to confirm the robustness of results. Results: Frailty was significantly associated with elevated risks of GDM (OR, 3.563; 95% CI, 1.737 to 7.309; P< 0.001) and GDM was also significantly associated with elevated risks of frailty ( ß , 0.087; 95% CI, 0.040 to 0.133; P< 0.001). There is no evidence demonstrating the existence of horizontal pleiotropy and heterogeneity. This association was robust after adjustments for BMI. The sensitivity analyses with Weighted median, Maximum likelihood, Penalised weighted median, MR Egger and MR PRESSO methods indicated consistent results. Conclusion: Our study provides evidence of the bidirectional causal association between frailty and GDM from genetic perspectives, signaling that the identification and assessment of frailty should become a standard strategy during the early stages and care of gestational diabetes.

Circular RNA hsa_circ_0002268 (PHACTR1) Is Specific to Gestational Diabetes Mellitus in a Polish Pregnant Population.

Gestational diabetes mellitus (GDM) is an intolerance of carbohydrate of any degree, which appears for the first time or is diagnosed during pregnancy. The objective of this study is to assess the differences in circular RNA (circRNA) in a Polish pregnant population with and without GDM. A total of 62 pregnant women, 34 with GDM and 28 controls, were enrolled in the study. Total RNAs were extracted from plasma and reverse transcription to complementary DNA (cDNA) was performed. A panel covering 271 amplicons, targeting both linear and circular as well as negative control gene transcripts, was used. Next-generation sequencing was used to evaluate the circRNA quantity. Data analysis was performed using the Coverage Analysis plugin in the Torrent Suite Software (Torrent Suite 5.12.3). A two-step normalization was performed by dividing each transcript read count by the total number of reads generated for the sample, followed by dividing the quantity of each transcript by ß-actin gene expression. Both circular and linear forms of RNAs were independently evaluated. A total of 57 transcripts were dysregulated between pregnant women with GDM and controls. Most of the targets (n = 25) were downregulated (cut-off ratio below 0.5), and one target showed a trend toward strong upregulation (ratio 1.45). A total of 39 targets were positively correlated with fasting plasma glucose (FPG), but none of the tested targets were correlated with insulin, CRP or HOMA-IR levels. Among the pregnant women with gestational diabetes, the relative quantity of hsa_circ_0002268 (PHACTR1) was approximately 120% higher than among healthy pregnant women: 0.046 [0.022-0.096] vs. 0.021 [0.007-0.047], respectively, (p = 0.0029). Elevated levels of hsa_circ_0002268 (PHACTR1) might be specific to the Polish population of pregnant women with GDM, making it useful as a potential molecular biomarker in the management of GDM in Poland.

Pre-gestational diabetes mellitus, gestational diabetes mellitus, and its association with the MTHFR C677T polymorphism.

Gestational diabetes mellitus (GDM) is a common condition during pregnancy and is associated with an increased risk of pre-eclampsia. The methylenetetrahydrofolate reductase (MTHFR) gene plays a crucial role in folate metabolism and has been implicated in GDM. To investigate the relationship between the MTHFR C677T gene polymorphism and the conditions of GDM and gestational prediabetes in pregnant women. A case-control study was conducted in 114 pregnant women with GDM and 96 pregnant women without GDM, from the first trimester to the prenatal examination at Can Tho Obstetrics Hospital. The pregnant women underwent a 1-hour (G1) and 2-hour (G2) oral glucose tolerance test (OGTT) and genetic polymorphism analysis based on real-time PCR technique. In pregnant women with GDM, weight, concentrations of G0, G1, G2, and folic acid were higher than those in the non-GDM group, with P < .05. When analyzing the subgroup without gestational diabetes, we found that the rate of prediabetes was 16.6% (16/96 pregnant women). In this group, blood glucose levels at 1 hour and 2 hours during the OGTT were higher compared to the normal glucose group (P < .05). A 2-hour post-OGTT glucose level of 7.78 mmol/L had a sensitivity of 93.8%, a specificity of 100%, and an area under the curve of 0.987 for diagnosing gestational prediabetes (P < .001). However, there were no statistically significant differences in the CC, CT, and TT polymorphisms of the MTHFR C677T gene among pregnant women with or without pre-gestational and GDM. Both fasting blood glucose and 2-hour glucose concentrations during the OGTT, as well as folic acid concentrations, were higher in both the pre-gestational and GDM groups compared to the non-gestational diabetes cohort. However, the analysis of MTHFR C677T polymorphisms revealed no statistically significant differences among the groups, highlighting the necessity for more extensive investigations to gain deeper insights into this relationship.

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.

First-trimester hemoglobin, haptoglobin genotype, and risk of gestational diabetes mellitus in a retrospective study among Chinese pregnant women.

BACKGROUND: This study aimed to assess whether the Haptoglobin (Hp) genotype influences the relationship between hemoglobin (Hb) levels and the development of gestational diabetes mellitus (GDM). Additionally, it sought to evaluate the interaction and joint association of Hb levels and Hp genotype with GDM risk. METHODS: This retrospective study involved 358 women with GDM and 1324 women with normal glucose tolerance (NGT). Peripheral blood leukocytes were collected from 360 individuals at 14-16 weeks' gestation for Hp genotyping. GDM was diagnosed between 24-28 weeks' gestation. Interactive moderating effect, joint analysis, and mediation analysis were performed to evaluate the crosslink of Hb levels and Hp genotype with GDM risk. RESULTS: Women who developed GDM had significantly higher Hb levels throughout pregnancy compared to those with NGT. Increase first-trimester Hb concentration was associated with a progressive rise in GDM incidence, glucose levels, glycosylated hemoglobin levels, Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) values, cesarean delivery rates, and composite neonatal outcomes. Spline regression showed a significant linear association of GDM incidence with continuous first-trimester Hb level when the latter exceeded 122 g/L. Increased first-trimester Hb concentration was an independent risk factor for GDM development after adjusting for potential confounding factors in both the overall population and a matched case-control group. The Hp2-2 genotype was more prevalent among pregnant women with GDM when first-trimester Hb exceeded 122 g/L. Significant multiplicative and additive interactions were identified between Hb levels and Hp genotype for GDM risk, adjusted for age and pre-pregnancy BMI. The odds ratio (OR) for GDM development increased incrementally when stratified by Hb levels and Hp genotype. Moreover, first-trimester Hb level partially mediated the association between Hp genotype and GDM risk. CONCLUSION: Increased first-trimester Hb levels were closely associated with the development of GDM and adverse pregnancy outcomes, with this association moderated by the Hp2-2 genotype.

The association between dietary, physical activity and the DNA methylation of PPARGC1A, HLA-DQA1 and ADCY3 in pregnant women with gestational diabetes mellitus: a nest case-control study.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with DNA methylation and lifestyle. The effects of DNA methylation on GDM, and the interaction between DNA methylation and lifestyle factors are not well elucidated. The objective of this study was to explore the association between GDM, DNA methylation and lifestyle factors. METHODS: A nest case-control design was performed. Sociodemographic data, dietary intake and daily physical activity information of pregnant women were collected. Bisulfate pyrosequencing was used to detect the DNA methylation level of PPARGC1A, HLA-DQA1, and ADCY3 genes. The differences of DNA methylation levels between the GDM group and the control group were compared. The correlation between clinical characteristics, dietary, physical activity and DNA methylation level was analyzed. RESULTS: A total of 253 pregnant women were enrolled, of which, 60 participants (GDM: 30; control: 30) were included in the final analysis. There were no significant differences in DNA methylation levels of six methylated sites between the two groups in this study (P > 0.05). Daily intake of potato and poultry were associated with DNA methylation level of the CpG 1 site of the ADCY3 gene in all participants and the control group (P < 0.05). Duration of folic acid intake before pregnancy was correlated with the methylation level of the CpG 1 site of the ADCY3 gene in all participants (r = 0.341, P = 0.04) and the control group (r = 0.431, P = 0.025). Daily oil intake was correlated with the methylation level of CpG 2 (r = 0.627, P = 0.016) and CpG 3 (r = 0.563, P = 0.036) of PPARGC1A in the GDM group. CONCLUSION: The association between the DNA methylation levels and GDM wasn't validated. There were associations between dietary and DNA methylation in pregnant women. A large-sample-sized and longitudinal study is warranted to further investigate the impacts of lifestyle on DNA methylation.

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.

We aimed to evaluate a risk prediction model of gestational diabetes mellitus (GDM) based on traditional and genetic factors. A total of 2744 eligible pregnant women were included. Face-to-face questionnaire surveys were conducted to collect general data. Among traditional factors, age ≥30 years old, 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 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. Both genetic and traditional factors increase the risk of GDM in women.

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.

Variations in the LINGO2 and GLIS3 Genes and Gene-Environment Interactions Increase Gestational Diabetes Mellitus Risk in Chinese Women.

Gestational diabetes mellitus (GDM) has been found to be a common complication in pregnant women, known to escalate the risk of negative obstetric outcomes. In our study, we genotyped 1,566 Chinese pregnant women for two single nucleotide polymorphisms (SNPs) in the LINGO2 gene and one SNP in the GLIS3 gene, utilizing targeted next-generation sequencing. The impact of two interacting genes, and the interaction of genes with the environment─including exposure to particulate matter (PM2.5), ozone (O3), and variations in prepregnancy body mass index (BMI)─on the incidence of GDM were analyzed using logistic regression. Our findings identify the variants LINGO2 rs10968576 (P = 0.022, OR = 1.224) and rs1412239 (P = 0.018, OR = 1.231), as well as GLIS3 rs10814916 (P = 0.028, OR = 1.172), as risk mutations significantly linked to increased susceptibility to GDM. Further analysis underscores the crucial role of gene-gene and gene-environment interactions in the development of GDM among Chinese women (P < 0.05). Particularly, the individuals carrying the rs10968576 G-rs1412239 G-rs10814916 C haplotype exhibit increased susceptibility to GDM during the prepregnancy period when interacting with PM2.5, O3, and BMI (P = 8.004 × 10-7, OR = 1.206; P = 6.3264 × 10-11, OR = 1.280; P = 9.928 × 10-7, OR = 1.334, respectively). In conclusion, our research emphasizes the importance of the interaction between specific gene variations─LINGO2 and GLIS3─and environmental factors in influencing GDM risk. Notably, we found significant associations between these gene variations and GDM risk across various environmental exposure periods.

The associations of maternal liver biomarkers in early pregnancy with the risk of gestational diabetes mellitus: a prospective cohort study and Mendelian randomization analysis.

Background: Associations of liver function with the risk of gestational diabetes mellitus (GDM) remain unclear. This study aimed to examine the relationship and the potential causality between maternal liver biomarkers and the risk of subsequent GDM, as well as to evaluate the interaction between liver biomarkers and lipids on GDM risk. Methods: In an ongoing Zhoushan Pregnant Women Cohort, pregnant women who finished the first prenatal follow-up record, underwent liver function tests in early pregnancy, and completed the GDM screening were included in this study. Logistic regression models were used to investigate the association, and the inverse-variance weighted method supplemented with other methods of two-sample Mendelian randomization (MR) analysis was applied to deduce the causality. Results: Among 9,148 pregnant women, 1,668 (18.2%) developed GDM. In general, the highest quartile of liver function index (LFI), including ALT, AST, GGT, ALP, and hepatic steatosis index, was significantly associated with an increased risk of GDM (OR ranging from 1.29 to 3.15), especially an elevated risk of abnormal postprandial blood glucose level. Moreover, the causal link between ALT and GDM was confirmed by the MR analysis (OR=1.28, 95%CI:1.05-1.54). A significant interaction between AST/ALT and TG on GDM risk was observed (P interaction = 0.026). Conclusion: Elevated levels of LFI in early pregnancy were remarkably associated with an increased risk of GDM in our prospective cohort. Besides, a positive causal link between ALT and GDM was suggested.

Unraveling the role of microRNAs: potential biomarkers for gestational diabetes mellitus revealed through RNA sequencing analysis.

BACKGROUND: Gestational diabetes mellitus (GDM) poses significant health risks for both mothers and children, contributing to long-term complications such as type 2 diabetes and cardiovascular disease. This study explores the potential of microRNAs (miRNAs) as biomarkers for GDM by analyzing peripheral blood samples from GDM patients. METHOD: Ten samples, including peripheral blood from 5 GDM patients and 5 controls, were collected to perform the RNA sequencing analysis. Differentially expressed miRNAs were further validated by quantitative real-time polymerase chain reaction. RESULTS: A total of 2287 miRNAs were identified, 229 of which showed differential expression. Validation by qRT-PCR confirmed significant up-regulation of miR-5193, miR-5003-3p, miR-3127-5p, novel-miR-96, miR-6734-5p, and miR-122-5p, while miR-10395-3p was down-regulated. Bioinformatics analyses revealed the involvement of these miRNAs in pathways associated with herpes simplex virus 1 infection. CONCLUSION: This study provides insights into the differential expression of miRNAs in GDM patients and their potential roles in disease pathogenesis. It suggests that the differentially expressed miRNAs could serve as potential biomarkers for GDM, shedding light on the complex molecular mechanisms involved.

The associations of IGF2, IGF2R and IGF2BP2 gene polymorphisms with gestational diabetes mellitus: A case-control study.

OBJECTIVE: To investigate the associations of Insulin-like growth factor-II (IGF2) gene, Insulin-like growth factor-II receptor (IGF2R) gene and Insulin-like growth factor-II binding protein 2 (IGF2BP2) gene polymorphisms with the susceptibility to gestational diabetes mellitus (GDM) in Chinese population. METHODS: A total of 1703 pregnant women (835 GDM and 868 Non-GDM) were recruited in this case-control study. All participants underwent prenatal 75 g oral glucose tolerance test (OGTT) examinations during 24-28 gestational weeks at the Maternal and Child Health Hospital of Hubei Province from January 15, 2018 to March 31, 2019. Genotyping of candidate SNPs (IGF2 rs680, IGF2R rs416572, IGF2BP2 rs4402960, rs1470579, rs1374910, rs11705701, rs6777038, rs16860234, rs7651090) was performed on Sequenom MassARRAY platform. Logistic regression analysis was conducted to investigate the associations between candidate SNPs and risk of GDM. In addition, multifactor dimensionality reduction (MDR) method was applied to explore the effects of gene-gene interactions on GDM risk. RESULTS: There were significant distribution differences between GDM group and non-GDM group in age, pre-pregnancy BMI, education level and family history of diabetes (P < 0.05). After adjusted for age, pre-pregnancy BMI, education level and family history of diabetes, there were no significant associations of the candidate SNPs polymorphisms and GDM risk (P > 0.05). Furthermore, there were no gene-gene interactions on the GDM risk among the candidate SNPs (P > 0.05). However, the fasting blood glucose (FBG) levels of rs6777038 CT carriers were significantly lower than TT carriers (4.69±0.69 vs. 5.03±1.57 mmol/L, P < 0.01), and the OGTT-2h levels of rs6777038 CC and CT genotype carriers were significantly lower than TT genotype carriers (8.10±1.91 and 8.08±1.87 vs. 8.99±2.90 mmol/L, P < 0.01). CONCLUSIONS: IGF2 rs680, IGF2R rs416572, IGF2BP2 rs4402960, rs1470579, rs11705701, rs6777038, rs16860234, rs7651090 polymorphisms were not significantly associated with GDM risk in Wuhan, China. Further lager multicenter researches are needed to confirm these results.

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

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

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.