The GCKR Gene Polymorphism rs780094 is a Risk Factor for Gestational Diabetes in a Brazilian Population

Genetic and epigenetic alterations associated with gestational diabetes mellitus and adverse neonatal outcomes

Gestational diabetes mellitus (GDM) is a metabolic disorder, recognised during 24-28 weeks of pregnancy. GDM is linked with adverse newborn outcomes such as macrosomia, premature delivery, metabolic disorder, cardiovascular, and neurological disorders. Recent investigations have focused on the correlation of genetic factors such as β-cell function and insulin secretary genes (transcription factor 7 like 2, potassium voltage-gated channel subfamily q member 1, adiponectin etc.) on maternal metabolism during gestation leading to GDM. Epigenetic alterations like DNA methylation, histone modification, and miRNA expression can influence gene expression and play a dominant role in feto-maternal metabolic pathways. Interactions between genes and environment, resulting in differential gene expression patterns may lead to GDM. Researchers suggested that GDM women are more susceptible to insulin resistance, which alters intrauterine surroundings, resulting hyperglycemia and hyperinsulinemia. Epigenetic modifications in genes affecting neuroendocrine activities, and metabolism, increase the risk of obesity and type 2 diabetes in offspring. There is currently no treatment or effective preventive method for GDM, since the molecular processes of insulin resistance are not well understood. The present review was undertaken to understand the pathophysiology of GDM and its effects on adverse neonatal outcomes. In addition, the study of genetic and epigenetic alterations will provide lead to researchers in the search for predictive molecular biomarkers.

Generating pregnant patient biological profiles by deconvoluting clinical records with electronic health record foundation models

Translational biology posits a strong bi-directional link between clinical phenotypes and a patient's biological profile. By leveraging this bi-directional link, we can efficiently deconvolute pre-existing clinical information into biological profiles. However, traditional computational tools are limited in their ability to resolve this link because of the relatively small sizes of paired clinical-biological datasets for training and the high dimensionality/sparsity of tabular clinical data. Here, we use state-of-the-art foundation models (FMs) for electronic health record (EHR) data to generate proteomics profiles of pregnant patients, thereby deconvoluting pre-existing clinical information into biological profiles without the cost and effort of running large-scale traditional omics studies. We show that FM-derived representations of a patient's EHR data coupled with a fully connected neural network prediction head can generate 206 blood protein expression levels. Interestingly, these proteins were enriched for developmental pathways, while proteins not able to be generated from EHR data were enriched for metabolic pathways. Finally, we show a proteomic signature of gestational diabetes that includes proteins with established and novel links to gestational diabetes. These results showcase the power of FM-derived EHR representations in efficiently generating biological states of pregnant patients. This capability can revolutionize disease understanding and therapeutic development, offering a cost-effective, time-efficient, and less invasive alternative to traditional methods of generating proteomics.

Mechanisms and Physiological Roles of Polymorphisms in Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a significant pregnancy complication linked to perinatal complications and an elevated risk of future metabolic disorders for both mothers and their children. GDM is diagnosed when women without prior diabetes develop chronic hyperglycemia due to β-cell dysfunction during gestation. Global research focuses on the association between GDM and single nucleotide polymorphisms (SNPs) and aims to enhance our understanding of GDM's pathogenesis, predict its risk, and guide patient management. This review offers a summary of various SNPs linked to a heightened risk of GDM and explores their biological mechanisms within the tissues implicated in the development of the condition.

Gestational diabetes mellitus: genetic factors, epigenetic alterations, and microbial composition

Gestational diabetes mellitus (GDM) is a common metabolic disorder, usually diagnosed during the third trimester of pregnancy that usually disappears after delivery. In GDM, the excess of glucose, fatty acids, and amino acids results in foetuses large for gestational age. Hyperglycaemia and insulin resistance accelerate the metabolism, raising the oxygen demand, and creating chronic hypoxia and inflammation. Women who experienced GDM and their offspring are at risk of developing type-2 diabetes, obesity, and other metabolic or cardiovascular conditions later in life. Genetic factors may predispose the development of GDM; however, they do not account for all GDM cases; lifestyle and diet also play important roles in GDM development by modulating epigenetic signatures and the body's microbial composition; therefore, this is a condition with a complex, multifactorial aetiology. In this context, we revised published reports describing GDM-associated single-nucleotide polymorphisms (SNPs), DNA methylation and microRNA expression in different tissues (such as placenta, umbilical cord, adipose tissue, and peripheral blood), and microbial composition in the gut, oral cavity, and vagina from pregnant women with GDM, as well as the bacterial composition of the offspring. Altogether, these reports indicate that a number of SNPs are associated to GDM phenotypes and may predispose the development of the disease. However, extrinsic factors (lifestyle, nutrition) modulate, through epigenetic mechanisms, the risk of developing the disease, and some association exists between the microbial composition with GDM in an organ-specific manner. Genes, epigenetic signatures, and microbiota could be transferred to the offspring, increasing the possibility of developing chronic degenerative conditions through postnatal life.

GCKR and ADIPOQ gene polymorphisms in women with gestational diabetes mellitus

AIMS

To investigate the associations of GCKR and ADIPOQ variants with the risk of gestational diabetes mellitus (GDM) in Chinese women.

METHODS

GCKR rs1260326, ADIPOQ rs266729, and rs1501299 were selected and genotyped in 519 GDM patients and 498 controls. Candidate SNPs were genotyped using multiplex polymerase chain reaction (PCR) combined with next-generation sequencing methods, and the association of these SNPs with GDM was analyzed.

RESULTS

We found that GCKR rs1260326 was significantly associated with an increased risk of GDM in the allele model, the codominant model (CC vs. TT), the dominant model, the recessive model, and the genotypic model distributions (p = 0.0029, p = 0.0022, p = 0.0402, p = 0.0038, and p = 0.0028, respectively). The rs1260326 polymorphism was shown to be associated with 1 h-OGTT level and gravidity in GDM patients (CC vs. TT: p = 0.0475 and p = 0.0220, respectively). Diastolic blood pressure (DBP) was significantly higher in the GDM patients with the rs266729 GG genotype compared to those with the CC or CG genotype (p = 0.0444 and p = 0.0339, respectively). The DBP of the GDM patients with the rs1501299 GT genotype was lower than that of those with the GG genotype (p = 0.0197). There was a weak linkage disequilibrium value between the GCKR and ADIPOQ SNPs.

CONCLUSIONS

The genes GCKR and ADIPOQ may be involved in the pathophysiology of GDM.

The Association between CDKAL1 Gene rs10946398 Polymorphism and Post-Transplant Diabetes in Kidney Allograft Recipients Treated with Tacrolimus

Post-transplant diabetes mellitus (PTDM) is a common complication that occurs in kidney transplant patients, increasing the risk of infection, cardiovascular disease and loss of graft function. Currently, factors that increase the risk of this complication are being sought, among them polymorphisms in genes that regulate carbohydrate metabolism and influence pancreatic β-cell function. The aim of this study was to evaluate the association of selected polymorphisms of genes affecting carbohydrate metabolism, such as CDKAL1 rs10946398, GCK rs1799884, GCKR rs780094 and DGKB/TMEM195 rs2191349, with the development of post-transplant diabetes in kidney transplant patients. This study included 201 Caucasian patients after kidney transplantation treated with tacrolimus. An association was observed between the CDKAL1 rs10946398 gene polymorphism and PTDM. Among patients with PTDM, there was an increased prevalence of the CC genotype in the PTDM group compared to the group without PTDM. The chance of PTDM in those with the CC genotype was 2.60 times higher compared to those with the AC + AA genotypes (CC vs. AC + AA OR (95% CI): 2.60 (1.02-6.61), p = 0.040). Multivariate logistic regression analysis showed that advanced age and the CC genotype (rare homozygote) of CDKAL1 rs10946398 were risk factors for the development of PTDM at 1 year after transplantation. There was no statistically significant association between GCK rs1799884, GCKR rs780094 or DGKB/TMEM195 rs2191349 polymorphisms and the development of post-transplant diabetes mellitus in kidney transplant patients. The results of this study suggest that the CDKAL1 rs10946398 CC genotype is associated with the increased risk of PTDM development in patients after kidney graft transplantation treated with tacrolimus.

Association of glucokinase gene and glucokinase regulatory protein gene polymorphisms with gestational diabetes mellitus: A case-control study

OBJECTIVES

The aim of this study was to investigate the association of glucokinase (GCK) gene, glucokinase regulatory protein (GCKR) gene polymorphisms with the susceptibility to GDM in Chinese population.

RESEARCH DESIGN AND METHODS

This case-control study included 835 GDM patients and 870 non-diabetic pregnant women who had their prenatal examinations at 24-28 gestational weeks at the Maternal and Child Health Hospital of Hubei Province from January 15, 2018 to March 31, 2019. The nurses were trained to collect clinical information and blood samples. The candidate single nucleotide polymorphism (SNPs, GCK rs1799884, rs4607517, rs10278336, rs2268574, rs730497 and GCKR rs780094, rs1260326) were genotyped on Sequenom Massarray platform. Statistical analysis including independent sample t test, chi-square test, logistic regression and one-way ANOVA were performed to evaluate the differences in allele and genotype distributions and their correlations with the odds of GDM.

RESULTS

There were statistically significant differences in age, pre-gestational BMI, education level and family history of diabetes between case and control group (P < 0.05). After adjusting for these confounders, GCK rs1799884 was still significantly associated with GDM (P < 0.05), but there were no significant associations between rs4607517, rs10278336 and rs2268574, rs780094 and rs1260326 polymorphisms and GDM odds (P > 0.05). In addition, the pregnant women with rs4607517 TT genotype had the significantly higher fasting blood glucose level than CC genotype (P < 0.05).

CONCLUSION

GCK rs1799884 mutation is associated with higher GDM odds in Chinese population. Further larger studies are needed to explore the association between GCK and GCKR polymorphisms and GDM susceptibility.

Molecular Changes in the Glucokinase Gene (GCK) Associated with the Diagnosis of Maturity Onset Diabetes of the Young (MODY) in Pregnant Women and Newborns

BACKGROUND

Diabetes mellitus is the most common metabolic alteration in gestation. Monogenic diabetes or Maturity-Onset Diabetes of the Young (MODY) is a subtype caused by a primary defect in insulin secretion determined by autosomal dominant inheritance.

OBJECTIVES

This study aimed to analyze molecular changes of the Glucokinase gene (GCK) in pregnant women with hyperglycemia during gestation and in their neonates. Case Study and Methods: We collected 201 blood samples, 128 from pregnant patients diagnosed with hyperglycemia and 73 from umbilical cord blood from neonates of the respective patients. DNA extraction and polymerase chain reaction (PCR) were performed to identify molecular changes in the GCK gene.

RESULTS

In a total of 201 samples (128 from mothers and 73 from neonates), we found changes in 21 (10.6%), among which 12 were maternal samples (6.0%) and 9 were neonatal samples (4.5%). DNA sequencing identified two polymorphisms and one deleterious MODY GCK-diagnostic mutation.

CONCLUSION

The prevalence of molecular changes in the Glucokinase gene (GCK) and the deleterious MODY GCK-diagnostic mutation were 9.3% and 0.7%, respectively, in women with hyperglycemia during gestation and 12.5% and 1.3%, respectively, in their neonates. The deleterious MODY GCK mutation identified is associated with a reduction in GCK activity and hyperglycemia. In the other molecular changes identified, it was impossible to exclude phenotypic change despite not having clinical significance. Therefore, these changes may interfere with the management and clinical outcome of the patients.

Glucose metabolism-related gene polymorphisms as the risk predictors of type 2 diabetes

Type 2 diabetes mellitus (T2DM) is a complex polygenic metabolic disease characterized by elevated blood glucose. Multiple environmental and genetic factors can increase the risk of T2DM and its complications, and genetic polymorphisms are no exception. This review is mainly focused on the related genes involved in glucose metabolic, including G6PC2, GCK, GCKR and OCT3. In this review, we have summarized the results reported globally and found that the genetic variants of GCK and OCT3 genes is a risk factor for T2DM while G6PC2 and GCKR genes are controversial in different ethnic groups. Hopefully, this summary could possibly help researchers and physicians understand the mechanism of T2DM so as to diagnose and even prevent T2DM at early time.

Update on the genetic and epigenetic etiology of gestational diabetes mellitus: a review

Background

Many studies have been conducted on the genetic and epigenetic etiology of gestational diabetes mellitus (GDM) in the last two decades because of the disease’s increasing prevalence and role in global diabetes mellitus (DM) explosion. An update on the genetic and epigenetic etiology of GDM then becomes imperative to better understand and stem the rising incidence of the disease. This review, therefore, articulated GDM candidate genes and their pathophysiology for the awareness of stakeholders.

Main body (genetic and epigenetic etiology, GDM)

The search discovered 83 GDM candidate genes, of which TCF7L2, MTNR1B, CDKAL1, IRS1, and KCNQ1 are the most prevalent. Certain polymorphisms of these genes can modulate beta-cell dysfunction, adiposity, obesity, and insulin resistance through several mechanisms. Environmental triggers such as diets, pollutants, and microbes may also cause epigenetic changes in these genes, resulting in a loss of insulin-boosting and glucose metabolism functions. Early detection and adequate management may resolve the condition after delivery; otherwise, it will progress to maternal type 2 diabetes mellitus (T2DM) and fetal configuration to future obesity and DM. This shows that GDM is a strong risk factor for T2DM and, in rare cases, type 1 diabetes mellitus (T1DM) and maturity-onset diabetes of the young (MODY). This further shows that GDM significantly contributes to the rising incidence and burden of DM worldwide and its prevention may reverse the trend.

Conclusion

Mutations and epigenetic changes in certain genes are strong risk factors for GDM. For affected individuals with such etiologies, medical practitioners should formulate drugs and treatment procedures that target these genes and their pathophysiology.

The relationship among GNB3 rs5443, PNPLA3 rs738409, GCKR rs780094 gene polymorphisms, type of maternal gestational weight gain and neonatal outcomes (STROBE-compliant article)

The gestational weight gain is determined by food habits, environmental and genetic factors.The aims of this paper were to establish relationships between maternal gene polymorphisms (patatin-like phospholipase domain-containing protein 3 rs738409 [PNPLA3 rs738409], glucokinase regulatory protein rs780094 [GCKR rs780094], and guanine nucleotide-binding protein rs5443 [GNB3 rs5443]) and mothers' gestational weight gain, but also neonatal outcomes (birth weight, length, and ponderal index [PI]).We performed a cross-sectional study in a sample of 158 mothers and their product of conception' in an Obstetrics-Gynecology Clinic from Romania. We divided the pregnant women according to the Institute of Medicine recommendations into 3 subgroups: (1) insufficient gestational weight gain; (2) normal gestational weight gain; and (3) excessive gestational weight gain.The gestational weight gain among pregnant women included in this study was classified as insufficient (10.1%), normal (31%), and excessive (58.9%). We found a tendency towards statistical significance for mothers that were overweight or obese before pregnancy to present an excessive gestational weight gain as compared to the normal weight ones. Similarly, we identified a tendency for statistical significance regarding the association between the variant genotype of GNB3 rs5443 and excessive gestational weight gain. We noticed differences that tended to be statistical significant concerning aspartate aminotransferase values between the 3 subgroups, mothers with excessive gestational weight gain having higher values than mothers with normal gestational weight gain (median, IQR: 22.89[17.53; 31.59] for mothers with excessive gestational weight gain versus 22.71[18.58; 27.37] for mothers with normal gestational weight gain). In mothers with excessive gestational weight gain, we found a significant association between the variant genotype of PNPLA3 rs738409 polymorphism and neonatal PI noticing a decrease of this index in case of newborns from mothers carrying the variant genotype.Excessive gestational weight gain was noticed in pregnant women that were obese and overweight before pregnancy. We found a positive association between the variant genotype of GNB3 rs5443 polymorphism and excessive gestational weight gain. Similarly, the presence of variant genotype of PNPLA3 rs738409 in mothers was associated with a lower PI in their newborns. Our study pointed out the most important factors that influence gestational weight gain and related birth outcomes.

Heterogeneous impact of type 2 diabetes mellitus-related genetic variants on gestational glycemic traits: review and future research needs

Gestational glucose homeostasis influences mother's metabolic health, pregnancy outcomes, fetal development and offspring growth. To understand the genetic roles in pregnant glucose metabolism and genetic predisposition for gestational diabetes (GDM), we reviewed the recent literature up to Jan, 2018 and evaluated the influence of T2DM-related genetic variants on gestational glycemic traits and glucose tolerance. A total of 140 variants of 89 genes were integrated. Their associations with glycemic traits in and outside pregnancy were compared. The genetic circumstances underlying glucose metabolism exhibit a similarity between pregnant and non-pregnant populations. While, not all of the T2DM-associated genetic variants are related to pregnant glucose tolerance, such as genes involved in fasting insulin/C-peptide regulation. Some genetic variants may have distinct effects on gestational glucose homeostasis. And certain genes may be particularly involved in this process via specific mechanisms, such as HKDC1, MTNR1B, BACE2, genes encoding cell cycle regulators, adipocyte regulators, inflammatory factors and hepatic factors related to gestational glucose sensing and insulin signaling. However, it is currently difficult to evaluate these associations with quantitative synthesis due to inadequate data, different analytical methods, varied measurements for glycemic traits, controversies in diagnosis of GDM, and unknown ethnicity- and/or sex-related influences on pregnant maternal metabolism. In conclusion, different genetic associations with glycemic traits may exist between pregnant and non-pregnant conditions. Comprehensive research on specific genetic regulation in gestation is necessary.

Association of type 2 diabetes susceptible genes GCKR, SLC30A8, and FTO polymorphisms with gestational diabetes mellitus risk: a meta-analysis

PURPOSE

Current studies have detected the correlation of polymorphisms in type 2 diabetes susceptible genes GCKR, SLC30A8 and FTO with gestational diabetes mellitus (GDM) risk. However, findings of these studies were incongruous. Hence, we performed an integrated review and meta-analysis for the researches regarding the association of single nucleotide polymorphisms (SNPs) in GCKR, SLC30A8 and FTO genes and GDM risk.

METHODS

Eligible publications were selected on the basis of several inclusion and exclusion criteria. Correlation between each SNP and GDM risk was estimated by computing odds ratios (ORs) with 95% confidence intervals (95%CIs).

RESULTS

Consequently, 19 case-control studies (from 16 citations) including 3636 GDM cases and 7229 GDM-free controls were participated in a meta-analysis of seven prevalent SNPs (GCKR rs1260326 and rs780094; SLC30A8 rs13266634 and rs11558471; FTO rs8050136, rs1421085 and rs9939609). Our results demonstrated that the rs780094, rs13266634 and rs9939609 SNPs were significantly associated with GDM risk. In stratified analysis, correlations of rs780094 and rs13266634 SNPs could be observed in Asian and Caucasian subgroups. Moreover, association between rs9939609 SNP and GDM risk was detected in Caucasian subgroup.

CONCLUSIONS

The GCKR rs780094, SLC30A8 rs13266634 and FTO rs9939609 SNPs were demonstrated to be the potential biomarkers for GDM risk prediction.

Molecular Biomarkers for Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a growing public health problem worldwide. The condition is associated with perinatal complications and an increased risk for future metabolic disease in both mothers and their offspring. In recent years, molecular biomarkers received considerable interest as screening tools for GDM. The purpose of this review is to provide an overview of the current status of single-nucleotide polymorphisms (SNPs), DNA methylation, and microRNAs as biomarkers for GDM. PubMed, Scopus, and Web of Science were searched for articles published between January 1990 and August 2018. The search terms included “gestational diabetes mellitus”, “blood”, “single-nucleotide polymorphism (SNP)”, “DNA methylation”, and “microRNAs”, including corresponding synonyms and associated terms for each word. This review updates current knowledge of the candidacy of these molecular biomarkers for GDM with recommendations for future research avenues.

FTO, GCKR, CDKAL1 and CDKN2A/B gene polymorphisms and the risk of gestational diabetes mellitus: a meta-analysis

PURPOSE

Studies had examined the associations between genetic polymorphisms and the risk of gestational diabetes mellitus (GDM). However, conclusions of these studies were controversial due to the smaller sample size and limited statistical power. We carried out a meta-analysis with the aim of providing a more comprehensive summary of the currently available research to evaluate the relationship between FTO, GCKR, CDKAL1 and CDKN2A/B gene polymorphisms and GDM risk.

METHODS

Literature search was carried out in the PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure and Wangfang databases up to November 2017. Data were extracted by two independent reviewers and statistical analyses were performed with STATA software. Pooled odds ratios and 95% confidence intervals were calculated by Z test to assess the association between genetic polymorphisms and GDM risk. Stratified analysis was performed based on ethnicity. Heterogeneity and publication bias between studies were evaluated by Cochran's Q test and Egger regression test, respectively.

RESULTS

14 eligible studies were included. CDKAL1 rs7754840 and rs7756992 showed significant correlation with GDM risk under the allele, recessive, dominant, homozygote and heterozygote models. GCKR rs780094 and CDKN2A/B rs10811661 also showed the same association under the allele, recessive and heterozygote models. No associations between FTO rs9939609 and rs8050136, GCKR rs1260326 and GDM risk were found.

CONCLUSIONS

Our meta-analysis showed that two SNPs in particular(rs7754840 and rs7756992 in CDKAL1) were very strongly associated with GDM risk. GCKR rs780094 and CDKN2A/B rs10811661 polymorphisms were moderately associated with GDM risk.