Dataset Information

Association between Gene Polymorphisms of Vitamin D Receptor and Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.

ABSTRACT: (1) Background: Studies on the association between Vitamin D receptor gene polymorphism and gestational diabetes mellitus have been inconsistent. The aim of this study was to summarize available evidence on the association between polymorphisms of Vitamin D receptor genes and susceptibility to gestational diabetes mellitus. (2) Methods: We searched databases of PubMed, Web of Science, Embase, China national knowledge infrastructure (CNKI), China science and technology journal database (VIP), and Wanfang Data for relevant articles. A systematic review and a meta-analysis were done to compare the distribution of Vitamin D receptor gene polymorphisms in gestational diabetes mellitus patients with those in controls using allelic, codominant, dominant, and recessive models. (3) Results: A total of eight eligible articles were included in the systematic review and of them, six articles were included in the meta-analysis. The vitamin D receptor gene rs7975232 polymorphism was associated with gestational diabetes mellitus under the allelic model (odds ratio = 1.28, 95% confidence interval 1.06-1.56), codominant model (CC vs. AA odds ratio = 1.97, 95% confidence interval 1.28-3.05), and recessive model (odds ratio = 1.83, 95% confidence interval 1.27-2.64) in the case of low heterogeneity. High heterogeneity existed in studies on the association of vitamin D receptor genes rs1544410, rs2228570, and rs731236 with gestational diabetes mellitus, and the most common sources of heterogeneity were the year of publication and matching. (4) Conclusion: Polymorphism of the vitamin D receptor gene rs7975232 may be associated with risk of developing gestational diabetes mellitus. Future studies should be designed to include standardized data collection and matching for important confounding factors such as body mass index, age, and race.

SUBMITTER: Zhou Q

PROVIDER: S-EPMC7794905 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association between Gene Polymorphisms of Vitamin D Receptor and Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Zhou Qian Q Wen Shiwu S Liu Miao M Zhang Sulei S Jin Xin X Liu Aizhong A

International journal of environmental research and public health 20201229 1

(1) Background: Studies on the association between Vitamin D receptor gene polymorphism and gestational diabetes mellitus have been inconsistent. The aim of this study was to summarize available evidence on the association between polymorphisms of Vitamin D receptor genes and susceptibility to gestational diabetes mellitus. (2) Methods: We searched databases of PubMed, Web of Science, Embase, China national knowledge infrastructure (CNKI), China science and technology journal database (VIP), and ...[more]

PMID: 33383970

Similar Datasets

Project description:BackgroundGestational diabetes mellitus (GDM) increased risk of perinatal complications for both the women and the fetuses. The association between the vitamin D receptor (VDR) gene polymorphism and GDM has not been thoroughly investigated in Chinese pregnant women. Therefore, we aimed to determine whether VDR gene single nucleotide polymorphisms (SNPs) rs154410, rs7975232, rs731236, rs2228570 and rs739837 contribute to GDM risk in Wuhan, China. Moreover, we aimed to explore their combined effects on the risk of GDM.MethodsPregnant women who had prenatal examinations at 24 to 28 weeks' gestation in our hospital from January 15, 2018 to March 31, 2019 were included in this case-control study. After exclusion, a total of 1684 pregnant women (826 GDM patients and 858 non-diabetic controls) were recruited. The clinical information and blood samples were collected by trained interviewers and nurses. Genotyping of candidate SNPs was conducted on the Sequenom MassARRAY platform. Statistical analyses including t-test, ANOVA, chi-square test and logistic regression were performed to the data with SPSS Software to evaluate differences in genotype distribution and associations with GDM risk. Multifactor dimensionality reduction method was used to explore the gene-gene interactions on the risk of GDM.ResultsDifferences in age, pre-pregnancy BMI, family history of diabetes and previous history of GDM between the case and control groups were statistically significant (P?<?0.05), whereas no significant differences were found in height, gravidity, parity, and age of menarche (P?>?0.05). There were no significant differences at genotype distributions of the examined VDR gene SNPs (P?>?0.05). After adjusting by age, pre-pregnancy BMI, family history of diabetes, the results of logistic regression analysis showed no associations of the five SNPs with GDM in all the four genotype models(P?>?0.05). Furthermore, there were no gene-gene interactions on the GDM risk among the five examined VDR gene SNPs.ConclusionsThe VDR gene SNPs rs154410, rs7975232, rs731236, rs2228570 and rs739837 showed neither significant associations nor gene-gene interactions with GDM in Wuhan, China.

Project description:IntroductionThe association between blood (serum or plasma) selenium concentrations and gestational diabetes mellitus (GDM) has been evaluated in some studies. However, the reported findings are debatable, and only case-control and cross-sectional studies were included.ObjectiveThis research aimed to assess the association between blood selenium levels and GDM by analyzing existing literature. To provide a reference for the prevention and treatment of GDM, we included prospective studies which are not included in previous studies to collate more high-quality evidence and better test the etiological hypothesis between blood Se concentrations and GDM.MethodsThe PubMed, EMBASE, and Web of Science databases were retrieved for literature up to September 2022, and relevant references were manually searched. Raw data from relevant studies were extracted, and a random effect model was adopted for meta-analysis. The total effects were reported as weighted mean differences. All data were analyzed using Stata 16.0 software.ResultsFourteen studies involving 890 pregnant women with GDM and 1618 healthy pregnant women were incorporated in the meta-analysis. Pregnancies with GDM had significantly lower blood selenium levels than those with normal glucose tolerance (weighted mean difference = -8.11; 95% confidence interval: -12.68 to -3.54, P = 0.001). Subgroup analyses showed that the association between blood selenium levels and GDM was consistent in the residents of Asia and Africa, but not in European. This trend was significant in the second and third trimester subgroups, but not in the first trimester subgroup. Articles published in 2006-2015 also showed this trend, but those published before 2005 and 2016-2019 did not show significant results. This difference was evident in non-prospective studies, but not significant in prospective studies. Studies using the Carpenter and Coustan diagnostic criteria were consistent with this trend, whereas studies using other diagnostic criteria found no differences. In addition, in terms of blood selenium measurement methods, atomic absorption spectrometry showed more significant differences than other methods. In the subgroup analysis based on the sample size of included studies and the quality of the studies, each subgroup showed statistical differences.ConclusionLower blood selenium concentrations are associated with GDM as shown in our study. Therefore, supplementing an appropriate amount of selenium may be helpful for GDM prevention and treatment.

Project description:BACKGROUND AND AIMS:Genetic variants involved in vitamin D metabolism have been associated with diabetes and related syndromes/diseases. We wanted to investigate possible associations of polymorphisms in genes involved in vitamin D metabolism with indices of insulin resistance and insulin secretion, and also with development of diabetes after gestational diabetes mellitus (GDM). MATERIALS AND METHODS:We have studied 376 women with previous GDM. Eight single nucleotide polymorphisms (SNPs) in the genes for vitamin D receptor (VDR) [rs731236, rs7975232, rs10735810, and rs1544410], vitamin D binding protein (DBP) [rs7041 and rs4588], and cytochrome P450 family 27 subfamily B member 1 (CYP27B1) [rs10877012 and rs4646536] were genotyped by TaqMan Allelic Discrimination Assay using the Quantstudio 7 Flex system. A 75-g oral glucose tolerance test (OGTT) was performed 1-2 years postpartum. The homeostasis model assessment of insulin resistance (HOMA-IR) and the disposition index [(insulinogenic index: I30/G30)/HOMA-IR] were used to calculate insulin resistance and insulin secretion, respectively. Serum samples for determination of 25(OH)D3 were collected at the time of the OGTT. Manifestation of diabetes was followed up to five years postpartum. RESULTS:After adjustment for BMI, age, and ethnicity, the A-allele of the VDR rs1544410 polymorphism was found to be associated with increased disposition index (difference per allele = 3.56, 95% CI: 0.4567-6.674; p = 0.03). The A-allele of the DBP rs7041 polymorphism was found to be associated with 25(OH)D3 levels (difference [in nmol/L] per allele = -5.478, 95% CI: -8.315 to -2.641; p = 0.0002), as was the T-allele of the DBP rs4588 polymorphism (OR = -6.319, 95% CI: -9.466 to -3.171; p = 0.0001). None of the SNPs were significantly associated with HOMA-IR or postpartum diabetes. CONCLUSIONS:This study provides evidence that the rs1544410 polymorphism of the VDR gene may be associated with increased insulin secretion in women after pregnancy complicated by GDM. Further studies in other populations are needed to confirm the results.

Dataset Information

Association between Gene Polymorphisms of Vitamin D Receptor and Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Publications

Association between Gene Polymorphisms of Vitamin D Receptor and Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets