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576 results for “Gestational Diabetes”
Vitamin B12 deficiency anaemia and gestational diabetes mellitus: a two-sample Mendelian randomization study
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Topological Overlap Matrices for DNA Methylation data of Gestational Diabetes Cohort with BMI and Exposure Status
<p>DNA methylation in placenta was measured with the Infinium HumanMethylation450 BeadChip (Illumina, Inc) microarray, in a sample of 28 women, 20 of whom had a gestational diabetes (GD)-affected pregnancy and 8 who did not. We used GD status as our exposure variable, assuming that this has widespread effects on DNA methylation and on its correlation patterns. Our response, Y, is the standardized body mass index (BMI) in the offspring at the age of 5. For the 10,000 most variable probes, we provide 3 topological overlap matrices (TOM), which are used in our analysis (note that each of the following TOM matrices are a 10,000 by 10,000 symmetric matrix with row names and column names corresponding to the CpG probe IDs:</p> <ol> <li>TOM_Methylation_All_10k.rds: based on all 28 subjects, </li> <li>TOM_Methylation_E0_10k.rds: based on the 8 subjects without a GD-affected pregnancy</li> <li>TOM_Methylation_E1_10k.rds: based on the 20 subjects with a GD-affected pregnancy </li> </ol> <p>The BMI (phenotype) and GD status (exposure) are given in the following dataset:</p> <ol> <li>BMI_and_Exposure_Status.rds: 28 x 2 matrix of the phenotype and exposure. each row is a subject.</li> </ol> <p>Using our ECLUST method (preprint available at http://sahirbhatnagar.com/slides/manuscript1_SB_v4.pdf), we derive 77 clusters, and here we provide the 1st principal component of each cluster:</p> <ol> <li>Cluster_Summary_1stPC.rds: 28 x 77 matrix, where each row is a subject, in the same order as the BMI_and_Exposure_Status.rds data</li> <li>Cluster_CpGs_names.rds: a list of length 77, where each element of the list contains the list of CpG probe IDs contained in each of the clusters</li> </ol> <p>To read in the data use the readRDS function, e.g.:</p> <p>TOM_All <- readRDS(file = "TOM_Methylation_All_10k.rds")</p>
Raw data for the association of genetic variants of ErbB4 gene and gestational diabetes mellitus
<div>Gestational diabetes (GDM) is one of the common complications of female pregnancy, which seriously affects the health of patients and their offspring. So far, the etiology has not yet been fully clarified. To clarify the relationship of Erb-b2 receptor tyrosine kinase 4 (ErbB4) genetic variants and GDM risk in a Chinese population, ErbB4 variants (rs1595064, rs1595065, rs1595066 and rs6719645) were selected and genotyped in 554 GDM cases and 641 healthy controls. The associations between variants and GDM risk were evaluated with the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). The false-positive reporting probability (FPRP), multi-factor dimension reduction (MDR) and bioinformatics analysis were adopted to confirm the significant associations. A nomogram model was constructed to predict the risk of GDM. Association analysis demonstrated that the rs1595066 genotype performed a protective effect on GDM risk among whole subjects. Meanwhile, stratified analysis showed that rs1595066 was significantly associated with GDM risk in various subgroups, such as age>30.09 years old, pre-pregnancy BMI>22.23 Kg/m<sup>2</sup> ,SBP≤110.08 mmHg, etc. Further, interactions between rs1595066 and DBP (Pinteraction=0.01), FPG (Pinteraction<0.001) and HbA1c (Pinteraction< 0.001) were detected. The FPRP analysis confirmed that association of rs1595066 and GDM risk in subjects of FPG≤4.79 mmol/L (P=0.199) is true at a prior probability of 0.1. The MDR analysis suggested that rs1595066 was the best single locus model, while the 4-loci model was considered the best multiple factors model to predict GDM risk. Functional prediction revealed that rs1595066 may disturb the microRNA binding sites to influence the stability of miRNA-mRNA binding. The predictive nomogram model has a good consistency and acceptable discriminative ability with a diagnosed AUC of 0.813.ErbB4 rs1595066 was significantly associated with GDM risk and underlying mechanism causing GDM may be the interaction of gene-gene, gene-environment and the changes in the regulatory effects of miRNAs on ERBB4 expression. The nomogram model has a good prospect for GDM prediction.</div>
Data from: Genetic susceptibility, Mendelian randomization and nomogram model construction of gestational diabetes mellitus
<p>The dataset contains subjects' basic information, including the Identification number of the test sample, fasting plasma glucose (FPG), oral glucose tolerance test 1h plasma glucose (1hPG), oral glucose tolerance test 2h plasma glucose (2hPG), glycated hemoglobin (HbA1c), Systolic blood pressure (SBP), Diastolic blood pressure (DBP), triglyceride (TG), total cholesterol (TC), High-density lipoprotein cholesterol (HDL-c), Low-density lipoprotein cholesterol (LDL-c), and also involves subjects' genetic variant information used for analysis of the association of functional polymorphisms and GDM. The variables including SBP_M, DBP_M, FPG_M, 1hPG_M, 2hPG_M, HbA1c_M, TG_M represent the mean value of SBP, DBP, FPG, 1hPG, 2hPG, HbA1c, TG, which are used for the stratification analysis. This study has obtained the support from the Ethics Committee of Guilin Medical University. All included subjects signed the informed consent.</p>
Data of Figure 5 from "Inhibition of IL-1beta improves Glycaemia in a Mouse Model for Gestational Diabetes"
<p>Data of Figure 5 from “Inhibition of IL-1beta improves Glycaemia in a Mouse Model for Gestational Diabetes”</p> <p>Dataset (doi: 10.1038/s41598-020-59701-0) contains the original publication as PDF-format (10.1038_s41598-020-59701-0). Corresponding raw data obtained from LC-MS/MS analysis provided as two files in CSV format (31003A-179400_10.1038_s41598-020-59701-0_DW_4-1.csv, 31003A-179400_10.1038_s41598-020-59701-0_DW_4-2.csv). All further experiment related information provided as three meta-data-files (31003A-179400_10.1038_s41598-020-59701-0_DW _4-1_M_1.PDF, 31003A-179400_10.1038_s41598-020-59701-0_DW _4-2_M_1.PDF, 31003A-179400_10.1038_s41598-020-59701-0_DW _4_1-2_M_2.pdf) as PDF format.</p>
Early Gestational Diabetes Screening in the Gravid Obese Woman
ClinicalTrials.gov study NCT01864564. IPD Sharing: NO. Countries: 1. Publications: 1.
Comparison of Two Screening Strategies for Gestational Diabetes (GDM2)
ClinicalTrials.gov study NCT02309138. IPD Sharing: YES. Countries: 1. Publications: 3.
Feasibility Testing of the "MyGlucoCare" Smartphone App for Women With Gestational Diabetes
ClinicalTrials.gov study NCT07372872. IPD Sharing: NO. Countries: 0. Publications: 2.
RCT Metformin for Reduction of Gestational Diabetes Mellitus Effects
ClinicalTrials.gov study NCT02980276. IPD Sharing: NO. Countries: 1. Publications: 3.
CAPO: Continuous Glucose Monitoring in A2 Gestational Diabetes and Pregnancy Outcomes
ClinicalTrials.gov study NCT04219085. IPD Sharing: NO. Countries: 1. Publications: 7.
Treatment of Mild Gestational Diabetes With Glyburide Versus Placebo
ClinicalTrials.gov study NCT00744965. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effect of Continuous Glucose Monitoring on Glycemic Control in Insulin-requiring Gestational Diabetes Mellitus
ClinicalTrials.gov study NCT02204657. IPD Sharing: NO. Countries: 1. Publications: 11.
Effectiveness of Metformin Compared to Insulin in Pregnant Women With Mild Preexisting or Early Gestational Diabetes
ClinicalTrials.gov study NCT00835861. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effects of Gestational Diabetes Mellitus on Children
ClinicalTrials.gov study NCT03997396. IPD Sharing: NO. Countries: 1. Publications: 8.
Effect of Conventional vs Intensive Management on Gestational Diabetes and Maternal Fetal Outcomes
ClinicalTrials.gov study NCT07336914. IPD Sharing: YES. Countries: 1. Publications: 6.
DECIDE: A Comparative Effectiveness Trial of Metformin Versus Insulin for the Treatment of Gestational Diabetes
ClinicalTrials.gov study NCT06445946. IPD Sharing: YES. Countries: 1. Publications: 4.
Metformin Compared to Glyburide in Gestational Diabetes
ClinicalTrials.gov study NCT00965991. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effects of Rhythm-Based Music on Pregnancies With Gestational Diabetes
ClinicalTrials.gov study NCT06970886. IPD Sharing: YES. Countries: 1. Publications: 55.
Randomized Translational Study to Examine the Effects of Shared Care in Management of Gestational Diabetes
ClinicalTrials.gov study NCT01565564. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Pre-pregnancy Lifestyle Intervention to Prevent the Recurrence of Gestational Diabetes in Overweight and Obese Women
ClinicalTrials.gov study NCT02763150. IPD Sharing: YES. Countries: 1. Publications: 2.
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