Better understanding and new insight of genetic risk loci for gestational diabetes mellitus.
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ABSTRACT:
SUBMITTER: Cho NH
PROVIDER: S-EPMC4019240 | biostudies-literature | 2012 Oct
REPOSITORIES: biostudies-literature
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Better understanding and new insight of genetic risk loci for gestational diabetes mellitus.
Journal of diabetes investigation 20120821 5
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Project description:Gestational diabetes mellitus (GDM) is the most common metabolic complication of pregnancy, with a prevalence that has increased significantly in the last decade, coming to affect 12-18% of all pregnancies. GDM is believed to be the result of a combination of genetic, epigenetic and environmental factors. Following the identification of susceptibility genes for type 2 diabetes by means of genome-wide association studies, an association has also been demonstrated between some type 2 diabetes susceptibility genes and GDM, suggesting a partial similarity of the genetic architecture behind the two forms of diabetes. More recent genome-wide association studies, focusing on maternal metabolism during pregnancy, have demonstrated an overlap in the genes associated with metabolic traits in gravid and non-gravid populations, as well as in genes apparently unique to pregnancy. Epigenetic changes-such as DNA methylation, histone modifications and microRNA gene silencing-have also been identified in GDM patients. Metabolomics has been used to profile the metabolic state of women during pregnancy, based on the measurement of numerous low-molecular-weight metabolites. Measuring amino acids and conventional metabolites has revealed changes in pregnant women with a higher insulin resistance and high blood glucose levels that resemble the changes seen in non-gravid, insulin-resistant populations. This would suggest similarities in the metabolic profiles typical of insulin resistance and hyperglycemia whether individuals are pregnant or not. Future studies combining data obtained using multiple technologies will enable an integrated systems biology approach to maternal metabolism during a pregnancy complicated by GDM. This review highlights the recent knowledge on the impact of genetics and epigenetics in the pathophysiology of GDM and the maternal and fetal complications associated with this pathology condition.
| S-EPMC7736606 | biostudies-literature
Project description:Hundreds of common genetic variants acting through distinguishable physiologic pathways influence the risk of type 2 diabetes (T2D). It is unknown to what extent the physiology underlying gestational diabetes mellitus (GDM) is distinct from that underlying T2D. In this study of >5,000 pregnant women from three cohorts, we aimed to identify physiologically related groups of maternal variants associated with GDM using two complementary approaches that were based on Bayesian nonnegative matrix factorization (bNMF) clustering. First, we tested five bNMF clusters of maternal T2D-associated variants grouped on the basis of physiology outside of pregnancy for association with GDM. We found that cluster polygenic scores representing genetic determinants of reduced β-cell function and abnormal hepatic lipid metabolism were associated with GDM; these clusters were not associated with infant birth weight. Second, we derived bNMF clusters of maternal variants on the basis of pregnancy physiology and tested these clusters for association with GDM. We identified a cluster that was strongly associated with GDM as well as associated with higher infant birth weight. The effect size for this cluster's association with GDM appeared greater than that for T2D. Our findings imply that the genetic and physiologic pathways that lead to GDM differ, at least in part, from those that lead to T2D.
| S-EPMC7876560 | biostudies-literature
Project description:Genome-wide association studies (GWASs) showed that two single nucleotide polymorphisms (SNPs) (rs17584499 and rs649891) in the protein tyrosine phosphatase receptor type D (PTPRD) were associated with type 2 diabetes (T2D). We sought to determine the influence of the PTPRD variants on the gestational diabetes mellitus (GDM) risk. In this research, two SNPs in PTPRD reported in T2D GWASs and six PTPRD expression-related SNPs were genotyped in 964 GDM cases and 1,021 controls using the Sequenom platform. Logistic regression analyses in additive models showed consistently significant associations of PTPRD rs10511544 A>C, rs10756026 T>A and rs10809070 C>G with a decreased risk of GDM [adjusted OR (95% CI) = 0.83 (0.72-0.97) for rs10511544; adjusted OR (95% CI) = 0.81 (0.70-0.94) for rs10756026; adjusted OR (95% CI) = 0.78 (0.65-0.92) for rs10809070]. Furthermore, the risk of GDM was significantly decreased with an increasing number of variant alleles of the three SNPs in a dose-dependent manner (Ptrend = 0.008). Moreover, the haplotype containing variant alleles of the three SNPs were significantly associated with a decreased risk of GDM [adjusted OR (95% CI) = 0.77 (0.64-0.92), P = 0.005], when compared with the most frequent haplotype. However, there were no significant associations for the SNPs reported in the T2D GWASs. Altogether, these findings indicate that the variants of rs10511544, rs10756026 and rs10809070 in PTPRD may contribute to a decreased susceptibility to GDM. Further validation in different ethnic backgrounds and biological function analyses are needed.
| S-EPMC5340179 | biostudies-literature
Project description:Diabetes mellitus is a severe metabolic disorder, which consistently requires medical care and self-management to restrict complications, such as obesity, kidney damage and cardiovascular diseases. The subtype gestational diabetes mellitus (GDM) occurs during pregnancy, which severely affects both the mother and the growing foetus. Obesity, uncontrolled weight gain and advanced gestational age are the prominent risk factors for GDM, which lead to high rate of perinatal mortality and morbidity. In-depth understanding of the molecular mechanism involved in GDM will help researchers to design drugs for the optimal management of the condition without affecting the mother and foetus. This review article is focused on the molecular mechanism involved in the pathophysiology of GDM and the probable biomarkers, which can be helpful for the early diagnosis of the condition. The early diagnosis of the metabolic disorder, most preferably in first trimester of pregnancy, will lead to its effective long-term management, reducing foetal developmental complications and mortality along with safety measures for the mother.
| S-EPMC9455072 | biostudies-literature
Project description:Diabetes mellitus is a chronic disease caused by the interaction of genetics and the environment that can lead to chronic damage to many organ systems. Genome-wide association studies have identified accumulating single-nucleotide polymorphisms related to type 2 diabetes mellitus and gestational diabetes mellitus. Genetic risk score (GRS) has been utilized to evaluate the incidence risk to improve prediction and optimize treatments. This article reviews the research progress in the use of the GRS in diabetes mellitus in recent years and discusses future prospects.
| S-EPMC9627198 | biostudies-literature
Project description:BackgroundSeveral studies have examined associations between genetic variants and the risk of gestational diabetes mellitus (GDM). However, inferences from these studies were often hindered by limited statistical power and conflicting results. We aimed to systematically review and quantitatively summarize the association of commonly studied single nucleotide polymorphisms (SNPs) with GDM risk and to identify important gaps that remain for consideration in future studies.MethodsGenetic association studies of GDM published through 1 October 2012 were searched using the HuGE Navigator and PubMed databases. A SNP was included if the SNP-GDM associations were assessed in three or more independent studies. Two reviewers independently evaluated the eligibility for inclusion and extracted the data. The allele-specific odds ratios (ORs) and 95% confidence intervals (CIs) were pooled using random effects models accounting for heterogeneity.ResultsOverall, 29 eligible articles capturing associations of 12 SNPs from 10 genes were included for the systematic review. The minor alleles of rs7903146 (TCF7L2), rs12255372 (TCF7L2), rs1799884 (-30G/A, GCK), rs5219 (E23K, KCNJ11), rs7754840 (CDKAL1), rs4402960 (IGF2BP2), rs10830963 (MTNR1B), rs1387153 (MTNR1B) and rs1801278 (Gly972Arg, IRS1) were significantly associated with a higher risk of GDM. Among them, genetic variants in TCF7L2 showed the strongest association with GDM risk, with ORs (95% CIs) of 1.44 (1.29-1.60, P < 0.001) per T allele of rs7903146 and 1.46 (1.15-1.84, P = 0.002) per T allele of rs12255372.ConclusionsIn this systematic review, we found significant associations of GDM risk with nine SNPs in seven genes, most of which have been related to the regulation of insulin secretion.
| S-EPMC3682671 | biostudies-literature
Project description:Many common genetic polymorphisms are associated with glycemic traits and type 2 diabetes (T2D), but knowledge about genetic determinants of glycemic traits in pregnancy is limited. We tested genetic variants known to be associated with glycemic traits and T2D in the general population for associations with glycemic traits in pregnancy and gestational diabetes mellitus (GDM). Participants in two cohorts (Genetics of Glucose regulation in Gestation and Growth [Gen3G] and Hyperglycemia and Adverse Pregnancy Outcome [HAPO]) underwent oral glucose tolerance testing at 24-32 weeks' gestation. We built genetic risk scores (GRSs) for elevated fasting glucose and insulin, reduced insulin secretion and sensitivity, and T2D, using variants discovered in studies of nonpregnant individuals. We tested for associations between these GRSs, glycemic traits in pregnancy, and GDM. In both cohorts, the fasting glucose GRS was strongly associated with fasting glucose. The insulin secretion and sensitivity GRSs were also significantly associated with these traits in Gen3G, where insulin measurements were available. The fasting insulin GRS was weakly associated with fasting insulin (Gen3G) or C-peptide (HAPO). In HAPO (207 GDM case subjects), all five GRSs (T2D, fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity) were significantly associated with GDM. In Gen3G (43 GDM case subjects), both the T2D and insulin secretion GRSs were associated with GDM; effect sizes for the other GRSs were similar to those in HAPO. Thus, despite the profound changes in glycemic physiology during pregnancy, genetic determinants of fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity discovered outside of pregnancy influence GDM risk.
| S-EPMC6245229 | biostudies-literature
Project description:OBJECTIVES/SPECIFIC AIMS: This study aims to identify genetic biomarkers of GDM and facilitate the understanding of its molecular underpinnings. METHODS/STUDY POPULATION: We identified a cohort of mothers diagnosed with GDM in our longitudinal birth study by mining Electronic Health Records of participants utilizing PheCode map with ICD-9 and ICD-10 codes. We verified each case using ACOG’s GDM diagnosis criteria. RESULTS/ANTICIPATED RESULTS: Whole genome sequencing (WGS) data were available for 111 confirmed cases (out of 205) and 706 controls (out of 1,429) from different ancestries (412 EUR, 256 AMR, 56 EAS, 26 SAS and 18 AFR; 49 OTHER). SAS had the highest incidence of GDM at 38.46% and EUR had the lowest at 6.55%. We performed logistic regression using computed ancestry, age and BMI as covariates to determine if any variants are associated with GDM. The top variant (rs139014401) was found in an intron of DFFB gene, which is p53-bound and regulates DNA fragmentation during apoptosis. We will investigate the robustness of 49 identified variants and will separate the cohort by ancestry to detect population-specific differences in the top loci. DISCUSSION/SIGNIFICANCE OF IMPACT: Identification of molecular biomarkers in GDM across different ancestral backgrounds will address a gap in current GDM research. Findings may enhance screening and enable clinicians to identify those at risk for developing GDM earlier in the pregnancy. Early management of mothers at risk may lead to better health outcomes for mother and baby.
| S-EPMC6808337 | biostudies-literature
Project description:We compared the plasma miRNA expression profiles between healthy and GDM women by microarray analysis.Our study offers new insights into circulating biomarkers of GDM and thus provides a valuable resource for future investigations.
2017-04-22 | GSE98043 | GEO
Project description:Vitamin D (VD) deficiency during pregnancy has been repeatedly linked to an increased gestational diabetes mellitus (GDM) risk. We sought to determine the influences of genetic variants in vitamin D signaling pathways on the risk of GDM. In this study, we genotyped 15 single nucleotide polymorphisms (SNPs) within 8 representative genes (CYP27A1, CYP27B1, CYP24A1, VDR, RXRA, RXRB, RXRG and GC) of the vitamin D signaling pathways in a case-control study with 964 GDM cases and 1,021 controls using the Sequenom MassARRAY iPLEX platform. Logistic regression analyses in additive model showed that GC rs16847024 C>T, RXRG rs17429130 G>C and RXRA rs4917356 T>C were significantly associated with the increased risk of GDM (adjusted OR = 1.31, 95% CI = 1.10-1.58 for rs16847024; adjusted OR = 1.28, 95% CI = 1.04-1.57 for rs17429130; adjusted OR = 1.28, 95% CI = 1.06-1.54 for rs4917356). And GDM risk significantly increased with the increasing number of variant alleles of the three SNPs in a dose-dependent manner (P for trend < 0.001). Moreover, the combined effect of the three SNPs on GDM occurrence was more prominent in older women (age > 30). Further interactive analyses also detected a significantly multiplicative interaction between the combined variant alleles and age on GDM risk (P = 0.035). Together, these findings indicate that GC rs16847024, RXRG rs17429130 and RXRA rs4917356 were candidate susceptibility markers for GDM in Chinese females. Further validation studies with different ethnic background and biological function analyses were needed.
| S-EPMC5356519 | biostudies-literature