Molecular Biomarkers for Gestational Diabetes Mellitus.
Ontology highlight
ABSTRACT:
SUBMITTER: Dias S
PROVIDER: S-EPMC6213110 | biostudies-literature | 2018 Sep
REPOSITORIES: biostudies-literature
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Project description:Gestational diabetes mellitus (GDM) is defined as any degree of carbohydrate intolerance, with onset or first recognition during second or third trimester of gestation. It is estimated that approximately 7% of all pregnancies are complicated by GDM and that its prevalence is rising all over the world. Thus, the screening for abnormal glucose levels is generally recommended as a routine component of care for pregnant women. However, additional biomarkers are needed in order to predict the onset or accurately monitor the status of gestational diabetes. Recently, microRNAs, a class of small noncoding RNAs demonstrated to modulate gene expression, have been proven to be secreted by cells of origin and can be found in many biological fluids such as serum or plasma. Such feature renders microRNAs as optimal biomarkers and sensors of in situ tissue alterations. Furthermore, secretion of microRNAs via exosomes has been reported to contribute to tissue cross talk, thus potentially represents, if disrupted, a mechanistic cause of tissue/cell dysfunction in a specific disease. In this review, we summarized the recent findings on circulating microRNAs and gestational diabetes mellitus with particular focus on the potential use of microRNAs as putative biomarkers of disease as well as a potential cause of GDM complications and β cell dysfunction.
| S-EPMC5924999 | biostudies-other
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:This study aimed to identify key circulating long non-coding RNAs (lncRNAs) as novel biomarkers for diagnosis of GDM at the early stages. First, lncRNA microarray analysis was conducted for plasma samples of GDM women before delivery and 48 h after delivery. The expression of differentially expressed lncRNAs in clinical samples at different trimesters was randomly validated by quantitative PCR. Moreover, the correlation between lncRNA expression and oral glucose tolerance test (OGTT) level in GDM women during the second trimester was analyzed, and the diagnostic value of key lncRNAs for GDM during different trimesters was evaluated by receiver operating characteristic (ROC) curve. The plasma level of NONHSAT054669.2 and ENST00000525337 may be used as novel diagnostic biomarkers for early diagnosis of GDM.
2022-11-07 | GSE217299 | GEO
Project description:BACKGROUND:Gestational diabetes mellitus (GDM) is one of the most common problems during pregnancy. Lack of international consistent diagnostic procedures has limit improvement of current therapeutic effectiveness. Here, we aimed to screen potential gene biomarkers that might play vital roles in GDM progression for assistance of its diagnostic and treatment. METHODS:Gene expression profiles in four GDM placentae at first trimester, four GDM placentae at second trimester, and four normal placentae were obtained from the publicly available Gene Expression Omnibus (GEO). Weighted gene coexpression network analysis (WGCNA) indicated two gene modules, that is, black and brown module, that was significantly positively and negatively correlated with GDM progression time points, respectively. Additionally, a significant positive correlation between module membership (MM) and degree in protein-protein interaction network of brown module genes was observed. RESULTS:KIF2C, CENPE, CCNA2, AURKB, MAD2L1, CCNB2, CDC20, PLK1, CCNB1, and CDK1 all have degree larger than 50 and MM larger than 0.9, so they might be valuable biomarkers in GDM. Gene set enrichment analysis inferred tight relations between carbohydrate metabolism or steroid biosynthesis-related processes and GDM progression. CONCLUSIONS:All in all, our study should provide several novel references for GDM diagnosis and therapeutic.
| S-EPMC6382444 | biostudies-literature
Project description:BackgroundGestational diabetes mellitus (GDM), one of the most common pregnancy complications, can lead to morbidity and mortality in both the mother and the infant. Metabolomics has provided new insights into the pathology of GDM and systemic analysis of GDM with metabolites is required for providing more clues for GDM diagnosis and mechanism research. This study aims to reveal metabolic differences between normal pregnant women and GDM patients in the second- and third-trimester stages and to confirm the clinical relevance of these new findings.MethodsMetabolites were quantitated with the serum samples of 200 healthy pregnant women and 200 GDM women in the second trimester, 199 normal controls, and 199 GDM patients in the third trimester. Both function and pathway analyses were applied to explore biological roles involved in the two sets of metabolites. Then the trimester stage-specific GDM metabolite biomarkers were identified by combining machine learning approaches, and the logistic regression models were constructed to evaluate predictive efficiency. Finally, the weighted gene co-expression network analysis method was used to further capture the associations between metabolite modules with biomarkers and clinical indices.ResultsThis study revealed that 57 differentially expressed metabolites (DEMs) were discovered in the second-trimester group, among which the most significant one was 3-methyl-2-oxovaleric acid. Similarly, 72 DEMs were found in the third-trimester group, and the most significant metabolites were ketoleucine and alpha-ketoisovaleric acid. These DEMs were mainly involved in the metabolism pathway of amino acids, fatty acids and bile acids. The logistic regression models for selected metabolite biomarkers achieved the area under the curve values of 0.807 and 0.81 for the second- and third-trimester groups. Furthermore, significant associations were found between DEMs/biomarkers and GDM-related indices.ConclusionsMetabolic differences between healthy pregnant women and GDM patients were found. Associations between biomarkers and clinical indices were also investigated, which may provide insights into pathology of GDM.
| S-EPMC8379750 | biostudies-literature
Project description:Circular RNA can regulate blood glucose levels by targeting mRNA expression, but the role of circRNA in GDM is still unknown. Therefore, a joint microarray analysis of circRNAs and their targeting mRNAs using the peripheral blood of GDM patients and healthy pregnant women was carried out for the first time. In our study, high-throughput microarray sequencing technique was used to analyze the expression profile of circRNA and transcripts mRNA in the peripheral blood of GDM patients, in order to comprehensively evaluate the role of circRNAs targets and their parents genes in the signal pathways related to the pathogenesis of GDM. Some of the discovered circRNAs and their linear transcript mRNAs related to T cell receptor signaling pathway were further verified in larger samples by droplet digital PCR(ddPCR) and quantitative real-time PCR(qRT-PCR), respectively. The verification results confirmed the initial microarray results.
2021-08-27 | GSE182737 | GEO
Project description:tsRNA profiles of gestational diabetes mellitus and healthy control groups were generated by deep sequencing using Illumina NextSeq 500.
2024-05-12 | GSE267259 | GEO
Project description:The hemochorial placenta provides a critical barrier at the maternal-fetal interface to modulate maternal immune tolerance and enable gas and nutrient exchange between mother and conceptus. Pregnancy outcomes are adversely affected by gestational diabetes mellitus (GDM); however, the effects of GDM on placental formation, and subsequently fetal development, are not fully understood. In this report, streptozotocin was used to induce hyperglycemia in pregnant rats for the purpose of investigating the impact of GDM on placental formation and fetal development. GDM caused placentomegaly and placenta malformation, decreasing placental efficiency and fetal size. Elevated glucose disrupted rat trophoblast stem (TS) cell differentiation in vitro. Evidence of altered trophoblast differentiation was also observed in vivo, as hyperglycemia affected the junctional zone transcriptome and interfered with intrauterine trophoblast invasion and uterine spiral artery remodeling. When exposed to hypoxia, rats with GDM showed decreased proliferation and ectoplacental cone development on gestation day (gd) 9.5 and complete pregnancy loss by gd 13.5. Furthermore, elevated glucose concentrations inhibited TS cell responses to hypoxia in vitro. Overall, these results indicate that alterations in placental development, efficiency, and plasticity could contribute to the suboptimal fetal outcomes in offspring from pregnancies complicated by GDM.
2020-07-07 | GSE144276 | GEO
Project description:The relationship between gestational diabetes mellitus (GDM) and oxidative stress has not been fully elucidated. This study examined the association between biomarkers of oxidative stress and GDM.We conducted a case-control study which included 36 women presenting with GDM and 36 asymptomatic matched control subjects who visited Guangzhou Women and Children's Medical Centre, China, from June 2012 to December 2012. Pregnant women were prospectively recruited to the study, and blood samples were collected at the time of a routine oral glucose tolerance test. These samples were then analyzed for levels of endocrine and surrogate markers of oxidative stress.Compared to control subjects, women with GDM exhibited elevated values for plasma glucose, insulin, and insulin resistance (IR), and showed reduced HOMA pancreatic β-cell function (HOMA-B), insulin sensitivity index (ISI), insulinogenic index, and corrected insulin response at 24-28 weeks gestation. A bivariate logistic regression analysis showed that levels of high-sensitivity C reactive protein (hs-CRP) and high fluorescence reticulocytes at fasting, and hs-CRP in a 1-h OGTT, were significantly associated with GDM. A linear regression analysis showed that levels of hs-CRP (P = 0.003) and reticulocytes (P = 0.029) at fasting were associated with IR, and levels of hs-CRP (P = 0.002) and monocytes (P = 0.006) in a 1-h OGTT were associated with ISI.Pregnant women with GDM developed a pathological IR and exhibited β-cell dysfunction. Their decreased ability to compensate for oxidative stress was associated with increased IR and a reduced ISI, which might be important factors in GDM.
| S-EPMC4411158 | biostudies-other
Project description:Gestational diabetes mellitus (GDM) “program” an elevated risk of metabolic syndrome in the offspring. Epigenetic alterations are a suspected mechanism. GDM has been associated with placental DNA methylation changes in some epigenome-wide association studies. It remains unclear which genes or pathways are affected, and whether any placental differential gene methylations are correlated to fetal growth or circulating metabolic health biomarkers. In an epigenome-wide association study using the Infinium MethylationEPIC Beadchip, we sought to identify genome-wide placental differentially methylated genes and enriched pathways in GDM, and to assess the correlations with fetal growth and metabolic health biomarkers in cord blood. The study samples were 30 pairs of term placentas in GDM vs. euglycemic pregnancies (controls) matched by infant sex and gestational age at delivery in the Shanghai Birth Cohort. Cord blood metabolic health biomarkers included insulin, C-peptide, proinsulin, IGF-I, IGF-II, leptin and adiponectin. Adjusting for maternal age, pre-pregnancy BMI, parity, mode of delivery and placental cell type heterogeneity, 256 differentially methylated positions (DMPs,130 hypermethylated and 126 hypomethylated) were detected between GDM and control groups accounting for multiple tests with false discovery rate <0.05 and beta-value difference >0.05. WSCD2 was identified as a differentially methylated gene in both site- and region-level analyses. We validated 7 hypermethylated (CYP1A2, GFRA1, HDAC4, LIMS2, NAV3, PAX6, UPK1B) and 10 hypomethylated (DPP10, CPLX1, CSMD2, GPR133, NRXN1, PCSK9, PENK, PRDM16, PTPRN2, TNXB) genes reported in previous epigenome-wide association studies. We did not find any enriched pathway accounting for multiple tests. DMPs in 11 genes (CYP2D7P1, PCDHB15, ERG, SIRPB1, DKK2, RAPGEF5, CACNA2D4, PCSK9, TSNARE1, CADM2, KCNAB2) were correlated with birth weight (z score) accounting for multiple tests. There were no significant correlations between placental gene methylations and cord blood biomarkers. In conclusions, GDM was associated with DNA methylation changes in a number of placental genes, but these placental gene methylations were uncorrelated to the observed metabolic health biomarkers (fetal growth factors, leptin and adiponectin) in cord blood. We validated 17 differentially methylated placental genes in GDM, and identified 11 differentially methylated genes relevant to fetal growth.
2022-06-22 | GSE200659 | GEO