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Association between functional genetic variants in retinoid X receptor-α/γ and the risk of gestational diabetes mellitus in a southern Chinese population.

ABSTRACT: To clarify the effect of retinoid X receptor-α/γ (RXR-α/γ) genes functional genetic variants (RXR-α rs4842194 G>A, RXR-γ rs100537 A>G and rs2134095 T>C) on the risk of gestational diabetes mellitus (GDM), a case-control study with 573 GDM patients and 740 pregnant women with normal glucose tolerance was performed in Guangxi area of China. An odds ratio (OR) with its corresponding 95% confidence interval (CI) was used to assess the strengths of the association between genetic variation and GDM. After adjustment of age and pre-BMI, the logistic regression analysis showed that the rs2134095 was significantly associated with GDM risk (CC vs. TT/TC: adjusted OR = 0.71, 95% CI = 0.56-0.90) in all subjects, and this result remained highly significant after Bonferroni's correction for multiple testing (P=0.004). The stratified analysis showed that rs2134095 was significantly associated with the risk of GDM among age > 30 years (adjusted OR = 0.61, 95% CI = 0.39-0.97), BMI > 22 kg/m2 (adjusted OR = 0.46, 95% CI = 0.30-0.70), systolic blood pressure (SBP) > 120 mmHg (adjusted OR = 1.96, 95% CI = 1.14-3.36), glycosylated hemoglobin A1c (HbA1c) < 6.5% (adjusted OR = 1.41, 95% CI = 1.11-1.78), TG ≤ 1.7 mmol/l (adjusted OR = 2.57, 95% CI = 1.45-4.53), TC ≤ 5.18 mmol/l (adjusted OR = 1.58, 95% CI = 1.13-2.22), high-density lipoprotein cholesterol (HDL-c) ≤ 1.5 mmol/l (adjusted OR = 1.70, 95% CI = 1.16-2.49) and low-density lipoprotein cholesterol (LDL-c) > 3.12 mmol/l (adjusted OR = 1.47, 95% CI = 1.08-2.00) subjects, under the recessive genetic model. We also found that rs2134095 interacted with age (Pinteraction=0.039), pre-BMI (Pinteraction=0.040) and TG (Pinteraction=0.025) influencing individual's genetic susceptibility to GDM. The rs2134095 T>C is significantly associated with the risk of GDM by effect of a single locus and/or complex joint gene-gene and gene-environment interactions. Larger sample-size and different population studies are required to confirm the findings.

SUBMITTER: Yu XY

PROVIDER: S-EPMC8529336 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo explore the relationship between angiotensin-converting enzyme 2 (ACE2) genetic variants and gestational diabetes mellitus (GDM) in a southern Chinese population.MethodsPotential functional variants (rs2106809, rs6632677, and rs2074192) of ACE2 were selected and genotyped in 566 GDM patients and 710 normal pregnaõncies in Guilin, China. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were used to evaluate the association between genetic variant and GDM risk, and then the false positive report probability, multifactor dimensional reduction (MDR), and bioinformatics tools were used to confirm the significant association in the study.ResultsAfter adjusting for age and prepregnancy body mass index, logistic regression analysis showed that ACE2 rs6632677 was significantly associated with a decreased risk of GDM (CC vs. GG: adjusted OR = 0.09, 95% CI: 0.01 - 0.71, P = .023; GC/CC vs. GG: adjusted OR = 0.68, 95% CI = 0.46 - 0.99, P = .048; and CC vs. GG/GC: adjusted OR = 0.09, 95% CI = 0.01 - 0.72, P = .024), whereas rs2074192 was associated with increased GDM risk (TT vs. CC/CT: adjusted OR = 1.38, 95% CI = 1.08 - 1.75, P = .009). Furthermore, we found that rs6632677 interacted with SBP (P interaction = .043) and FPG (P interaction = .021) and rs2074192 interacted with HDL-c (P interaction = .029) and LDL-c (P interaction = .035) to influence the GDM risk of the individual. In the MDR analysis, the rs6632677 was the best one-locus model, and the three-loci model was the best interaction model to predict GDM risk. In addition, functional analysis confirmed that rs2074192 may regulate the splicing process of ACE2 gene.ConclusionACE2 gene variants are significantly associated with the risk of GDM via gene-gene and gene-environment combinations. The rs2074192 C > T affects the splicing of the ACE2 gene, which may be a potential mechanism leading to the changed susceptibility of an individual female during pregnancy to GDM.

Project description:BackgroundGlyoxalase 1 (GLO1) plays a crucial role in defending against glycation. Single nucleotide polymorphism (SNP) variants in the GLO1 gene may affect gene expression and alter enzyme activity. However, there have been limited studies evaluating the association between GLO1 and diabetes, especially gestational diabetes mellitus (GDM). Therefore, this study is the first to explore the association of GLO1 SNPs and GDM risk.MethodsThe study included a total of 500 GDM patients and 502 control subjects. The SNPscan™ genotyping assay was used to genotype rs1781735, rs4746 and rs1130534. To assess the disparities in genotype, allele, and haplotype distributions and their correlation with GDM risk, the independent sample t-test, logistic regression, and chi-square test were employed during the data processing phase. Furthermore, one-way ANOVA was conducted to determine the differences in genotype and blood glucose and methylglyoxal(MG) levels.ResultsSignificant differences were observed in prepregnancy body mass index (pre-BMI), age, systolic blood pressure (SBP), diastolic blood pressure (DBP), and parity between GDM and healthy subjects (P < 0.05). After adjusting for these factors, GLO1 rs1130534 TA remained associated with an increased risk of GDM (TA vs. TT + AA: OR = 1.320; 95% CI: 1.008-1.728; P = 0.044), especially in the pre-BMI ≥ 24 subgroup (TA vs. TT + AA: OR = 2.424; 95% CI: 1.048-5.607; P = 0.039), with fasting glucose levels being significantly elevated in the TA genotype compared to the TT genotype (P < 0.05). Conversely, the GLO1 rs4746 TG was associated with a decreased risk of GDM (TG vs. TT: OR = 0.740; 95% CI: 0.548-0.999; P = 0.049; TG vs. TT + GG: OR = 0.740; 95% CI: 0.548-0.998; P = 0.048). Additionally, the haplotype T-G-T of rs1781735, rs4746 and rs1130534 was associated with a decreased risk of GDM among individuals with a pre-BMI ≥ 24 (OR = 0.423; 95% CI: 0.188-0.955; P = 0.038). Furthermore, the rs1781735 GG genotype was found to be more closely related to maternal MG accumulation and neonatal weight gain (P < 0.05).ConclusionOur findings suggested that GLO1 rs1130534 was associated with an increased susceptibility to GDM and higher blood glucose levels, but GLO1 rs4746 was associated with a decreased risk of GDM. The rs1781735 has been associated with the accumulation of maternal MG and subsequent weight gain in neonates.

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.

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Association between functional genetic variants in retinoid X receptor-α/γ and the risk of gestational diabetes mellitus in a southern Chinese population.

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