Gestational diabetes mellitus is associated with TCF7L2 gene polymorphisms independent of HLA-DQB1*0602 genotypes and islet cell autoantibodies

Investigating the Role of Skin Autofluorescence in Gestational Diabetes Mellitus: A Systematic Review

Gestational diabetes mellitus (GDM) is a pregnancy-specific condition that can cause serious complications for both the mother and the fetus. Preventing these complications requires optimum glycemic control. Skin autofluorescence (SAF) is a non-invasive and innovative method that evaluates the levels of advanced glycation end products, markers of hyperglycemia, that could aid in the optimum management of GDM-complicated pregnancies. This systematic review aims to assess SAF's potential utility in the prediction of short-term and long-term outcomes in GDM. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, with the protocol identifier CRD42024559012, we used "(skin autofluorescence OR SAF) AND (gestational diabetes mellitus OR GDM)" as a search criterion on the PubMed, Scopus, and Web of Science databases. After a rigorous selection process, we included five articles, which evaluated SAF values and GDM, SAF and pregnancies complicated by diabetes mellitus, and SAF and macrosomia. GDM diagnosis varies due to the different approaches among the major guidelines, leading to variations in interpretation and diagnostic thresholds. Across studies, this variability contributes to inconsistent SAF values. As a standardized and objective marker, SAF could provide a uniform criterion, improving GDM management. Further research is needed to validate its clinical utility.

Unveiling Gestational Diabetes: An Overview of Pathophysiology and Management

Gestational diabetes mellitus (GDM) is characterized by an inadequate pancreatic β-cell response to pregnancy-induced insulin resistance, resulting in hyperglycemia. The pathophysiology involves reduced incretin hormone secretion and signaling, specifically decreased glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), impairing insulinotropic effects. Pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), impair insulin receptor substrate-1 (IRS-1) phosphorylation, disrupting insulin-mediated glucose uptake. β-cell dysfunction in GDM is associated with decreased pancreatic duodenal homeobox 1 (PDX1) expression, increased endoplasmic reticulum stress markers (CHOP, GRP78), and mitochondrial dysfunction leading to impaired ATP production and reduced glucose-stimulated insulin secretion. Excessive gestational weight gain exacerbates insulin resistance through hyperleptinemia, which downregulates insulin receptor expression via JAK/STAT signaling. Additionally, hypoadiponectinemia decreases AMP-activated protein kinase (AMPK) activation in skeletal muscle, impairing GLUT4 translocation. Placental hormones such as human placental lactogen (hPL) induce lipolysis, increasing circulating free fatty acids which activate protein kinase C, inhibiting insulin signaling. Placental 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) overactivity elevates cortisol levels, which activate glucocorticoid receptors to further reduce insulin sensitivity. GDM diagnostic thresholds (≥92 mg/dL fasting, ≥153 mg/dL post-load) are lower than type 2 diabetes to prevent fetal hyperinsulinemia and macrosomia. Management strategies focus on lifestyle modifications, including dietary carbohydrate restriction and exercise. Pharmacological interventions, such as insulin or metformin, aim to restore AMPK signaling and reduce hepatic glucose output. Emerging therapies, such as glucagon-like peptide-1 receptor (GLP-1R) agonists, show potential in improving glycemic control and reducing inflammation. A mechanistic understanding of GDM pathophysiology is essential for developing targeted therapeutic strategies to prevent both adverse pregnancy outcomes and the progression to overt diabetes in affected women.

Multigenerational diabetes mellitus

Gestational diabetes (GDM) changes the maternal metabolic and uterine environment, thus increasing the risk of short- and long-term adverse outcomes for both mother and child. Children of mothers who have GDM during their pregnancy are more likely to develop Type 2 Diabetes (T2D), early-onset cardiovascular disease and GDM when they themselves become pregnant, perpetuating a multigenerational increased risk of metabolic disease. The negative effect of GDM is exacerbated by maternal obesity, which induces a greater derangement of fetal adipogenesis and growth. Multiple factors, including genetic, epigenetic and metabolic, which interact with lifestyle factors and the environment, are likely to contribute to the development of GDM. Genetic factors are particularly important, with 30% of women with GDM having at least one parent with T2D. Fetal epigenetic modifications occur in response to maternal GDM, and may mediate both multi- and transgenerational risk. Changes to the maternal metabolome in GDM are primarily related to fatty acid oxidation, inflammation and insulin resistance. These might be effective early biomarkers allowing the identification of women at risk of GDM prior to the development of hyperglycaemia. The impact of the intra-uterine environment on the developing fetus, "developmental programming", has a multisystem effect, but its influence on adipogenesis is particularly important as it will determine baseline insulin sensitivity, and the response to future metabolic challenges. Identifying the critical window of metabolic development and developing effective interventions are key to our ability to improve population metabolic health.

Correlation between TCF7L2 and CAPN10 gene polymorphisms and gestational diabetes mellitus in different geographical regions: a meta-analysis

BACKGROUND

The association between TCF7L2 and CAPN10 gene polymorphisms and gestational diabetes mellitus (GDM) has been explored in diverse populations across different geographical regions. Yet, most of these studies have been confined to a limited number of loci, resulting in inconsistent findings. In this study, we conducted a comprehensive review of published literature to identify studies examining the relationship between TCF7L2 and CAPN10 gene polymorphisms and the incidence of GDM in various populations. We specifically focused on five loci that were extensively reported in a large number of publications and performed a meta-analysis.

METHODS

We prioritized the selection of SNPs with well-documented correlations established in existing literature on GDM. We searched eight Chinese and English databases: Cochrane, Elton B. Stephens. Company (EBSCO), Embase, Scopus, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang, and China Science and Technology Journal Database and retrieved all relevant articles published between the inception of the database and July 2022. The Newcastle Ottawa Scale (NOS) was used to evaluate the selected articles, and the odds ratio (OR) was used as the combined effect size index to determine the association between genotypes, alleles, and GDM using different genetic models. Heterogeneity between the studies was quantified and the I2 value calculated. Due to large heterogeneities between different ethnic groups, subgroup analysis was used to explore the correlation between genetic polymorphisms and the incidence of GDM in the different populations. The stability of the results was assessed using sensitivity analysis. Begg's and Egger's tests were used to assess publication bias.

RESULTS

A total of 39 articles reporting data on 8,795 cases and 16,290 controls were included in the analysis. The frequency of the rs7901695 genotype was statistically significant between cases and controls in the European population (OR = 0.72, 95% CI: 0.65-0.86) and the American population (OR = 0.61, 95% CI: 0.48-0.77). The frequencies of rs12255372, rs7901695, rs290487, and rs2975760 alleles were also considerably different between the cases and controls in the populations analyzed.

CONCLUSIONS

rs7903146, rs12255372, rs7901695, rs290487, and rs2975760 were associated with the incidence of GDM in different populations.

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.

Maternal diabetes negatively impacts fetal health

Diabetes is a chronic metabolic disease affecting an increasing number of people. Although diabetes has negative health outcomes for diagnosed individuals, a population at particular risk are pregnant women, as diabetes impacts not only a pregnant woman's health but that of her child. In this review, we cover the current knowledge and unanswered questions on diabetes affecting an expectant mother, focusing on maternal and fetal outcomes.

Molecular biomarkers for gestational diabetes mellitus and postpartum diabetes

ABSTRACT

Gestational diabetes mellitus (GDM) is a growing public health problem worldwide that threatens both maternal and fetal health. Identifying individuals at high risk for GDM and diabetes after GDM is particularly useful for early intervention and prevention of disease progression. In the last decades, a number of studies have used metabolomics, genomics, and proteomic approaches to investigate associations between biomolecules and GDM progression. These studies clearly demonstrate that various biomarkers reflect pathological changes in GDM. The established markers have potential use as screening and diagnostic tools in GDM and in postpartum diabetes research. In the present review, we summarize recent studies of metabolites, single-nucleotide polymorphisms, microRNAs, and proteins associated with GDM and its transition to postpartum diabetes, with a focus on their predictive value in screening and diagnosis.

Prognostic Gene Predictors of Gestational Diabetes in Endometrium and Follicular Fluid of Women after Infertility

Background and objectives. Gestational diabetes mellitus is an increasingly diagnosed metabolic disorder during pregnancy with unknown pathological pathways. Taking into account the growing numbers of women who are conceiving after assisted reproductive technologies, they comprise an engaging target group for gestational diabetes mellitus etiopathogenesis research. In terms of metabolism and genetics, as the evidence shows, both unexplained infertility and gestational diabetes mellitus pose challenges for their interpretation due to the complex bodily processes. Materials and Methods. Our study examined the expression of genes (IGF2, GRB10, CRTC2, HMGA2, ESR1, DLK1, SLC6A15, GPT2, PLAGL1) associated with glucose metabolism in unexplained infertility patients who conceived after in vitro fertilization procedure, were diagnosed with GDM and their findings were compared with control population. Results. There were no significant differences in gene expression of endometrium stromal cells between healthy pregnant women and women with gestational diabetes, although the significant downregulation of CRTC2 was observed in the follicular fluid of women with gestational diabetes mellitus. Moreover, expression of HMGA2 and ESR1 was significantly reduced in FF cells when compared to endometrial cells. Conclusions. These findings may indicate about the importance of follicular fluid as an indicator for gestational diabetes and should be explored more by further research.

Genomics and Epigenomics of Gestational Diabetes Mellitus: Understanding the Molecular Pathways of the Disease Pathogenesis

One of the most common complications during pregnancy is gestational diabetes mellitus (GDM), hyperglycemia that occurs for the first time during pregnancy. The condition is multifactorial, caused by an interaction between genetic, epigenetic, and environmental factors. However, the underlying mechanisms responsible for its pathogenesis remain elusive. Moreover, in contrast to several common metabolic disorders, molecular research in GDM is lagging. It is important to recognize that GDM is still commonly diagnosed during the second trimester of pregnancy using the oral glucose tolerance test (OGGT), at a time when both a fetal and maternal pathophysiology is already present, demonstrating the increased blood glucose levels associated with exacerbated insulin resistance. Therefore, early detection of metabolic changes and associated epigenetic and genetic factors that can lead to an improved prediction of adverse pregnancy outcomes and future cardio-metabolic pathologies in GDM women and their children is imperative. Several genomic and epigenetic approaches have been used to identify the genes, genetic variants, metabolic pathways, and epigenetic modifications involved in GDM to determine its etiology. In this article, we explore these factors as well as how their functional effects may contribute to immediate and future pathologies in women with GDM and their offspring from birth to adulthood. We also discuss how these approaches contribute to the changes in different molecular pathways that contribute to the GDM pathogenesis, with a special focus on the development of insulin resistance.

The correlation between transcription factor 7-like 2 gene polymorphisms and susceptibility of gestational diabetes mellitus in the population of central China: A case-control study

OBJECTIVE

To investigate the correlation between transcription factor 7-like 2 (TCF7L2) gene polymorphisms and gestational diabetes mellitus (GDM) risk in the central Chinese population.

METHODS

This case-control study examined the association of seven TCF7L2 gene single-nucleotide polymorphisms (SNPs) (rs11196218, rs4506565, rs7895340, rs7901695, rs11196205, rs12243326, and rs290487) with GDM risk in the central Chinese population (843 GDM and 877 controls). The clinical information and blood samples were collected by trained interviewers and nurses. Genotyping of SNPs was conducted on the Sequenom MassARRAY platform. Statistical analyses including t-test, ANOVA, chi-square test, Fisher's exact test, and logistic regression were performed.

RESULTS

Differences in age, pre-pregnant body mass index (BMI), and family history of type 2 diabetes mellitus (T2DM) between the case and control groups were significant (p < 0.05). Compared with the wild-type genotype, pregnant women with genotypes of rs4506565-AT (OR = 1.89, 95%CI: 1.18-3.02), rs7895340 GA (OR = 1.93, 95%CI: 1.06-3.54), rs7901695-TC (OR = 1.79, 95%CI: 1.11-2.88), and rs11196205-GC (OR = 2.15, 95%CI: 1.16-3.98) had a significantly higher risk of GDM, adjusted by age, pre-pregnant BMI, and family history of T2DM. Functional annotation showed that all these four SNPs fell in the functional elements of human pancreatic islets. Further cumulative effects analysis concluded that when participants carried all these four risk genotypes, the risk of GDM was 3.51 times (OR = 3.51, 95%CI: 1.38-8.90) than that of those without any risk genotypes.

CONCLUSIONS

The findings of this study suggested that rs4506565, rs7895340, rs7901695, and rs11196205 were the genetic susceptibility SNPs of GDM in the central Chinese population. Further studies are needed to validate our findings and clarify the underlying mechanisms.

The role of transcription factor 7-like 2 in metabolic disorders

Transcription factor 7-like 2 (TCF7L2), a member of the T cell factor/lymphoid enhancer factor family, generally forms a complex with β-catenin to regulate the downstream target genes as an effector of the canonical Wnt signalling pathway. TCF7L2 plays a vital role in various biological processes and functions in many organs and tissues, including the liver, islet and adipose tissues. Further, TCF7L2 down-regulates hepatic gluconeogenesis and promotes lipid accumulation. In islets, TCF7L2 not only affects the insulin secretion of the β-cells but also has an impact on other cells. In addition, TCF7L2 influences adipogenesis in adipose tissues. Thus, an out-of-control TCF7L2 expression can result in metabolic disorders. The TCF7L2 gene is composed of 17 exons, generating 13 different transcripts, and has many single-nucleotide polymorphisms (SNPs). The discovery that these SNPs have an impact on the risk of type 2 diabetes (T2D) has attracted thorough investigations in the study of TCF7L2. Apart from T2D, TCF7L2 SNPs are also associated with type 1, posttransplant and other types of diabetes. Furthermore, TCF7L2 variants affect the progression of other disorders, such as obesity, cancers, metabolic syndrome and heart diseases. Finally, the interaction between TCF7L2 variants and diet also needs to be investigated.

Gestational Diabetes Mellitus: A Harbinger of the Vicious Cycle of Diabetes

Gestational diabetes mellitus (GDM), characterized by a transitory form of diabetes induced by insulin resistance and pancreatic β-cell dysfunction during pregnancy, has been identified as one of the major obstacles in achieving improved maternal and child health. Approximately 9-25% of pregnancies worldwide are impacted by the acute, long-term, and transgenerational health complications of this disease. Here, we discuss how GDM affects longstanding maternal and neonatal outcomes, as well as health risks that likely persist into future generations. In addition to the current challenges in the management and diagnosis of and the complications associated with GDM, we discuss current preclinical models of GDM to better understand the underlying pathophysiology of the disease and the timely need to increase our scientific toolbox to identify strategies to prevent and treat GDM, thereby advancing clinical care.

Fine-tuning of Genome-Wide Polygenic Risk Scores and Prediction of Gestational Diabetes in South Asian Women

Gestational diabetes Mellitus (GDM) affects 1 in 7 births and is associated with numerous adverse health outcomes for both mother and child. GDM is suspected to share a large common genetic background with type 2 diabetes (T2D). The aim of our study was to characterize different GDM polygenic risk scores (PRSs) and test their association with GDM using data from the South Asian Birth Cohort (START). PRSs were derived for 832 South Asian women from START using the pruning and thresholding (P + T), LDpred, and GraBLD methods. Weights were derived from a multi-ethnic and a white Caucasian study of the DIAGRAM consortium. GDM status was defined using South Asian-specific glucose values in response to an oral glucose tolerance test. Association with GDM was tested using logistic regression. Results were replicated in South Asian women from the UK Biobank (UKB) study. The top ranking P + T, LDpred and GraBLD PRSs were all based on DIAGRAM's multi-ethnic study. The best PRS was highly associated with GDM in START (AUC = 0.62, OR = 1.60 [95% CI = 1.44-1.69]), and in South Asian women from UKB (AUC = 0.65, OR = 1.69 [95% CI = 1.28-2.24]). Our results highlight the importance of combining genome-wide genotypes and summary statistics from large multi-ethnic studies to optimize PRSs in South Asians.

Targeted deletion of Tcf7l2 in adipocytes promotes adipocyte hypertrophy and impaired glucose metabolism

OBJECTIVE

Activation of the Wnt-signaling pathway is known to inhibit differentiation in adipocytes. However, there is a gap in our understanding of the transcriptional network regulated by components of the Wnt-signaling pathway during adipogenesis and in adipocytes during postnatal life. The key intracellular effectors of the Wnt-signaling pathway occur through TCF transcription factors such as TCF7L2 (transcription factor-7-like 2). Several genetic variants in proximity to TCF7L2 have been linked to type 2 diabetes through genome-wide association studies in various human populations. Our work aims to functionally characterize the adipocyte specific gene program regulated by TCF7L2 and understand how this program regulates metabolism.

METHODS

We generated Tcf7l2^F/F mice and assessed TCF7L2 function in isolated adipocytes and adipose specific knockout mice. ChIP-sequencing and RNA-sequencing was performed on the isolated adipocytes with control and TCF7L2 knockout cells. Adipose specific TCF7L2 knockout mice were challenged with high fat diet and assessed for body weight, glucose tolerance, and lipolysis.

RESULTS

Here we report that TCF7L2 regulates adipocyte size, endocrine function, and glucose metabolism. Tcf7l2 is highly expressed in white adipose tissue, and its expression is suppressed in genetic and diet-induced models of obesity. Genome-wide distribution of TCF7L2 binding and gene expression analysis in adipocytes suggests that TCF7L2 directly regulates genes implicated in cellular metabolism and cell cycle control. When challenged with a high-fat diet, conditional deletion of TCF7L2 in adipocytes led to impaired glucose tolerance, impaired insulin sensitivity, promoted weight gain, and increased adipose tissue mass. This was accompanied by reduced expression of triglyceride hydrolase, reduced fasting-induced free fatty acid release, and adipocyte hypertrophy in subcutaneous adipose tissue.

CONCLUSIONS

Together our studies support that TCF7L2 is a central transcriptional regulator of the adipocyte metabolic program by directly regulating the expression of genes involved in lipid and glucose metabolism.

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.

Allelic variant in the glucagon-like peptide 1 receptor gene associated with greater effect of liraglutide and exenatide on gastric emptying: A pilot pharmacogenetics study

BACKGROUND

Weight loss in response to the long-acting GLP-1 receptor (GLP1R) analog, liraglutide, is correlated with delay in gastric-emptying (GE). The aim of this pilot study was to assess whether specific genetic variants in GLP1R or TCF7L2 are associated with delayed GE and weight loss in obese patients treated with liraglutide or the short-acting GLP-1 agonist, exenatide.

METHODS

We evaluated in obese individuals the associations of genetic variations of GLP1R (rs6923761) and TCF7L2 (rs7903146) on GE T1/2 and weight from two trials that evaluated separately exenatide, 5 μg BID for 30 days, or liraglutide, 3 mg daily for 5 weeks. Data were analyzed using the dominant genetic model and intention-to-treat analysis.

KEY RESULTS

There was a significant correlation between changes in weight and GE T1/2 (rs  = -.382, P = .004). GLP1R rs6923761 minor allele A (AA_AG) carriers who received either exenatide or liraglutide had greater delay in GE T1/2 relative to baseline (117.9 ± 27.5 [SEM] minutes and 128.9 ± 38.32 minutes) compared to GG genotype (95.8 ± 30.4 minutes and 61.4 ± 21.4 minutes, respectively; P = .11). There was a non-significant difference in weight loss based on GLP1R rs6923761 genotype after 5 weeks of treatment. There were no significant correlations with TCF7L2 (rs7903146) genotype.

CONCLUSIONS & INFERENCES

The minor A allele of GLP1R (rs6923761) is associated with greater delay in GE T1/2 in response to liraglutide and exenatide. These studies provide data to plan pharmacogenetics testing of the hypothesis that GLP1R (rs6923761) influences weight loss in response to GLP1R agonists.

Type 2 diabetes-associated genetic variants of FTO, LEPR, PPARg, and TCF7L2 in gestational diabetes in a Brazilian population

Objective

Gestational diabetes mellitus (GDM) is a metabolic disorder that shares pathophysiologic features with type 2 diabetes mellitus. The aim of this study was to investigate the association of the polymorphisms fat mass and obesity-associated (FTO) rs1421085, leptin receptor (LEPR) rs1137100, rs1137101, peroxisome proliferator-activated receptor gamma (PPARg) rs1801282, and transcription factor 7-like 2 (TCF7L2) rs7901695 with GDM.

Subjects and methods

252 unrelated Euro-Brazilian pregnant women were classified into two groups according to the 2015 criteria of the American and Brazilian Diabetes Association: healthy pregnant women (n = 125) and pregnant women with GDM (n = 127), matched by age. The polymorphisms were genotyped using fluorescent probes (TaqMan®).

Results

All groups were in Hardy-Weinberg equilibrium. The genotype and allele frequencies of the studied polymorphisms did not show significant differences between the groups (P > 0.05). In the healthy and GDM groups, the C allele frequencies (95% CI) of the FTO rs1421085 polymorphism were 36.8% [31-43%] and 35.0% [29-41%]; the G allele frequencies (95% CI) of the LEPR rs1137100 polymorphism were 24.8% [19-30%] and 22.8% [18-28%]; the G allele frequencies (95% CI) of the LEPR rs1137101 polymorphism were 43.6% [37-50%] and 42.9% [37-49%]; the G allele frequencies (95% CI) of the PPARg rs1801282 polymorphism were 7.6% [4-11%] and 8.3% [5-12%]; and the C allele frequencies (95% CI) of the TCF7L2 rs7901695 polymorphism were 33.6% [28-39%] and 39.0% [33-45%], respectively.

Conclusion

The studied polymorphisms were not associated with GDM in a Brazilian population.

Association between TCF7L2 polymorphisms and gestational diabetes mellitus: A meta-analysis

AIMS/INTRODUCTION

Studies have been carried out to evaluate the correlation between TCF7L2 genetic polymorphisms and gestational diabetes mellitus (GDM) risk. However, the conclusions from these studies are incomplete, because partial single nucleotide polymorphisms (SNPs) were analyzed. We carried out a meta-analysis aimed to systematically evaluate TCF7L2 gene polymorphisms and GDM susceptibility in all population and racial/ethnic subgroups to afford a foundation for future research.

MATERIALS AND METHODS

Published studies censoring TCF7L2 variants and GDM risk were captured from the EMBASE, PubMed, CNKI and Wanfang databases. The meta-analysis was processed using software of RevMan 5.2 and Stata13. The relationship between TCF7L2 polymorphism and GDM occurrence was evaluated by pooled odds ratios. Stratified analysis based on race/ethnicity was also carried out. The allele-specific odds ratios and 95% confidence intervals were counted, and based on homogeneity evaluated using the I² -test, fixed- or random-effects pooled measures were selected.

RESULTS

A total of 22 studies were covered, capturing eight TCF7L2 SNPs and involving 5,573 cases and 13,266 controls. Six of eight SNPs showed significant relationships with GDM occurrence, of which the SNPs rs7903146, rs12255372 and rs7901695 were the most powerful. Stratified analysis by race/ethnicity showed discrepant results in these three SNPs. In Caucasians and other races, all these SNPs were found to have a significant association with GDM risk, but in Asians, only SNP rs7903146 showed a significant association.

CONCLUSIONS

Six of eight SNPs were found to have significant associations between TCF7L2 variants and GDM risk in the overall population, with the most powerful in SNPs being rs7903146, rs12255372 and rs7901695, but the contribution of these SNPs to GDM risk were variable among different racial/ethnic groups.

Molecular Analysis of a Genetic Variants Panel Related to Nutrients and Metabolism: Association with Susceptibility to Gestational Diabetes and Cardiometabolic Risk in Affected Women

Gestational diabetes mellitus (GDM) is the most frequent metabolic disorder in pregnancy. Women with a GDM history are at increased risk of developing diabetes and cardiovascular diseases. Studies have demonstrated a significant correlation between several genes involved in the metabolic pathway of insulin and environmental factors. The aim of this study was to investigate the relationship between clinical parameters in GDM and variants in genes involved with nutrients and metabolism. Several variants PPARG2 rs1801282 (C>G); PPARGC1A rs8192678 (C>T); TCF7L2 rs7903146 (C>T); LDLR rs2228671 (C>T); MTHFR rs1801133 (C>T); APOA5 rs662799 (T>C); GCKR rs1260326 (C>T); FTO rs9939609 (T>A); MC4R rs17782313 (T>C) were genotyped in 168 pregnant Caucasian women with or without GDM by High Resolution Melting (HRM) analysis. A significant correlation was observed between TT genotype of TCF7L2 gene and increased risk of GDM (OR 5.4 [95% CI 1.5-19.3]). Moreover, a significant correlation was observed between lipid parameters and genetic variations in additional genes, namely, PPARG2 [p = 0,02], APOA5 [p = 0,02], MC4R [p = 0,03], LDLR [p = 0,01], and FTO [p = 0,02]. Our findings support the association between TCF7L2 rs7903146 variant and an increased GDM risk. Results about the investigated genetic variants provide important information about cardiometabolic risk in GDM and help to plan future prevention studies.

Clinical Recommendations for the Use of Islet Cell Autoantibodies to Distinguish Autoimmune and Non-Autoimmune Gestational Diabetes

Gestational diabetes mellitus (GDM) is defined as carbohydrate intolerance that begins or is first recognized during pregnancy. The prevalence of GDM is highly variable, depending on the population studied, and reflects the underlying pattern of diabetes in the population. GDM manifests by the second half of pregnancy and disappears following delivery in most cases, but is associated with the risk of subsequent diabetes development. Normal pregnancy induces carbohydrate intolerance to favor the availability of nutrients for the fetus, which is compensated by increased insulin secretion from the maternal pancreas. Pregnancy shares similarities with adiposity in metabolism to save energy, and both conditions favor the development of insulin resistance (IR) and low-grade inflammation. A highly complicated network of modified regulatory mechanisms may primarily affect carbohydrate metabolism by promoting autoimmune reactions to pancreatic β cells and affecting insulin function. As a result, diabetes development during pregnancy is facilitated. Depending on a pregnant woman's genetic susceptibility to diabetes, autoimmune mechanisms or IR are fundamental to the development autoimmune or non-autoimmune GDM, respectively. Pregnancy may facilitate the identification of women at risk of developing diabetes later in life; autoimmune and non-autoimmune GDM may be early markers of the risk of future type 1 and type 2 diabetes, respectively. The most convenient and efficient way to discriminate GDM types is to assess pancreatic β-cell autoantibodies along with diagnosing diabetes in pregnancy.

Genetic variants associated with gestational diabetes mellitus: a meta-analysis and subgroup analysis

Previous studies have demonstrated that gestational diabetes mellitus (GDM) and Type 2 diabetes mellitus (T2D) share common genetic polymorphisms. We conducted meta-analysis and subgroup analysis of all available variants and determined the effects of confounding and experimental components on the genetic association of GDM. Any case-controlled or cohort studies with genotype distribution compared GDM cases with controls were included. In total, 28 articles including 8,204 cases and 15,221 controls for 6 polymorphisms were studied. rs10830963(MTNR1B), rs7903146(TCF7L2), and rs1801278(IRS1) were significantly associated with the increased GDM risk. The association of rs4402960(IGF2BP2) and rs1800629(TNF-α) was significant only when the studies with control allele frequency deviation and publication bias were excluded. Further subgroup analysis showed the risk alleles of rs7903146(TCF7L2) and rs1801282(PPARG) were significantly associated with the GDM risk only in Asian, but not in Caucasian population. The OGTT test using 100 g, but not 75 g; and genotype detection by other assays, but not Taqman method, were also significantly associated with increased GDM risk in rs1801278(IRS1) and rs7903146(TCF7L2). Overall GDM was associated with rs10830963(MTNR1B), rs7903146(TCF7L2), and rs1801278(IRS1), but only rs7903146(TCF7L2) and rs1801282(PPARG) were significant in Asian populations. While rs1801278(IRS1) and rs7903146(TCF7L2) were significantly affected by OGTT protocol and genotyping methods.

Transcription Factor 7-Like 2 (TCF7L2) rs7903146 Polymorphism as a Risk Factor for Gestational Diabetes Mellitus: A Meta-Analysis

Background

There are racial and ethnic differences in the prevalence of gestational diabetes mellitus (GDM). Prior meta-analyses included small samples and very limited non-Caucasian populations. Studies to determine the relationship between transcription factor 7 like-2 (TCF7L2) rs7903146 polymorphism and risk of GDM in Hispanics/Latinos are recently available. The present meta-analysis was to estimate the impact of allele variants of TCF7L2 rs7903146 polymorphism on GDM susceptibility in overall population and racial/ethnic subgroups.

Methods

Literature was searched in multiple databases including PubMed, Web of Science, EMBASE (Ovid SP), Airiti Library, Medline Complete, and ProQuest up to July 2015. Allelic frequency for TCF7L2 rs7903146 polymorphism in GDM and control subjects was extracted and statistical analysis was performed using Comprehensive Meta-Analysis (CMA) 2.0 statistical software. The association between TCF7L2 rs7903146 polymorphism and GDM risk was assessed by pooled odd ratios (ORs) using five gene models (dominant, recessive, homozygote, heterozygote, and allele). Stratified analysis based on race/ethnicity was also conducted. The between-study heterogeneity and contribution of each single study to the final result was tested by Cochran Q test and sensitivity analyses, respectively. Publication bias was evaluated using Egger’s linear regression test.

Results

A total of 16 studies involving 4,853 cases and 10,631 controls were included in this meta-analysis. Significant association between the T-allele of rs7903146 and GDM risk was observed under all genetic models, dominant model (OR = 1.44, 95% CI = 1.19–1.74), recessive model (OR = 1.35, 95% CI = 1.08–1.70), heterozygous model (OR = 1.31, 95% CI = 1.12–1.53), homozygous model (OR = 1.67, 95% CI = 1.31–2.12), and allele model (OR = 1.31, 95% CI = 1.12–1.53). Stratified analysis by race/ethnicity showed a statistically significant association between rs7903146 polymorphism and susceptibility to GDM under homozygous genetic model (TT versus CC) among whites, Hispanics/Latinos and Asians. Sensitivity analysis showed that the overall findings were robust to potentially influential decisions of the 16 studies included. No significant evidence for publication bias was observed in this meta-analysis for overall studies and subgroup studies.

Conclusions

This meta-analysis showed that the T allele of TCF7L2 rs7903146 polymorphism was associated with susceptibility of GDM in overall population in white, Hispanic/Latino and Asian sub-groups. Asians with homozygous TT allele of rs7903146 polymorphism have highest risk of GDM (OR = 2.08) followed by Hispanics/Latinos (OR = 1.80) and whites (OR = 1.51). The highest and lowest frequency of T allele of rs7903146 was found in Malaysia and South Korea, respectively. Future studies are needed to profile genetic risk for GDM among high risk Asian and Pacific Islander subgroups.

Identification of Genetic Variants of Gestational Diabetes in South Indians

BACKGROUND

This study examined the association in a South Indian population with gestational diabetes mellitus (GDM) of type 2 diabetes risk variants that have previously conferred susceptibility to GDM in other populations.

SUBJECTS AND METHODS

The study groups comprised 518 women with GDM and 910 pregnant women with normal glucose tolerance (NGT). Women with GDM were recruited from a tertiary diabetes center in Chennai, in south India, and NGT women were selected from antenatal clinics also in Chennai. Genomic DNA was isolated from whole blood using the phenol chloroform method. Twelve previously reported GDM-associated single nucleotide polymorphisms (SNPs) in or near nine loci were genotyped using the MassARRAY™ system (Sequenom, San Diego, CA).

RESULTS

Among the 12 SNPs genotyped, 11 SNPs were in Hardy-Weinberg equilibrium and had a call rate of >95%. Of the 11 SNPs previously associated with GDM in other populations, significant association was observed only with the rs7754840 and rs7756992 SNPs of the CDK5 regulatory subunit associated protein 1-like 1 (CDKAL1) gene in this population. The minor alleles of the SNPs rs7754840 and rs7756992 showed significant susceptibility to GDM with an odds ratio of 1.34 (95% confidence interval, 1.12-1.60; P = 0.0013) and 1.45 (95% confidence interval, 1.21-1.72; P = 0.00004), respectively.

CONCLUSIONS

The rs7754840 and rs7756992 SNPs of the CDKAL1 gene were found to be associated with GDM in this south Indian population. This is the first study describing genetic susceptibility of GDM in Asian Indians.

Metabolic, hormonal characteristics and genetic variants of TCF7L2 associated with development of gestational diabetes mellitus in Mexican women

BACKGROUND

Variation in TCF7L2 gene is associated with type 2 diabetes and with gestational diabetes mellitus in several populations, but there are no data in Mexican women with gestational diabetes mellitus. In this study, we examined metabolic and hormonal measurements as well as TCF7L2 genetic variants.

METHODS

We selected 108 pregnant women with normal glucose tolerance and 90 with gestational diabetes mellitus according to 2010 American Diabetes Association criteria matched for gestational week. We collected data on blood pressure, body mass index (BMI) and concentrations of blood glucose, HbA1c , lipids profile, insulin and glucagon-like peptide-1 (GLP-1). The genotyping of rs7903146 and rs12255372 polymorphisms were made with polymerase chain reaction-restriction fragment length polymorphism.

RESULTS

Actual and pre-gestational BMI, fasting glucose and HbA1c were higher (p < 0.001), and high-density lipoprotein cholesterol was lower (p < 0.02) in gestational diabetes mellitus women than euglycemic women. No significant differences were found for lipids, insulin and homeostasis model assessment-insulin resistance. Gestational diabetes mellitus women had high GLP-1 levels (32 vs 24, p < 0.004) and decreased β-cell function (266 vs 438, p < 0.001). The frequency of rs12255372 risk allele in gestational diabetes women was significantly higher than that in euglycemic women (χ²  = 8.96; p < 0.003) and confers a risk for gestational diabetes mellitus (OR = 9.1, 95% CI 2.8-29, p < 0.0002; and OR = 4.3, 95% CI 1.6-11.4, p < 0.003 based on dominant and co-dominant model, respectively). The generalized linear model showed that low beta function, high pre-gestational BMI and rs12255372 risk allele are independently associated with gestational diabetes.

CONCLUSIONS

The elevated GLP-1 levels in gestational diabetes women suggested some abnormality in insulin secretion. The low β-cell function, high pre-gestational BMI and rs12255372 risk allele are risk factors independently associated with the development of gestational diabetes.

Maternal genotype and gestational diabetes

OBJECTIVE

To determine whether genetic variants associated with glucose homeostasis are associated with gestational diabetes (GDM).

STUDY DESIGN

We genotyped 899 self-identified Caucasian women and 386 self-identified African-American women in the Pregnancy, Infection and Nutrition (PIN) Studies cohorts for 38 single-nucleotide polymorphisms (SNPs) associated with type II diabetes (T2DM) and/or glucose homeostasis in European populations.

RESULTS

GDM was diagnosed in 56 of 899 (6.2%) Caucasian and 24 of 386 (6.2%) African-American women. Among Caucasian women, GDM was associated with carriage of TCF7L2 rs7901695, MTNR1B rs10830963 and GCKR rs780094 alleles that are associated with T2DM and fasting glucose in nonpregnant populations. Among African-American participants, we found an increased risk among TSPAN8 rs7961581 C allele homozygotes and reduced risk among carriers of the JAZF1 rs864745 T allele.

CONCLUSION

We found several SNPs that are associated with GDM risk in the PIN cohorts. Maternal genotyping may identify women at risk for impaired gestational glucose tolerance.

Association of the rs7903146 polymorphism in transcription factor 7-like 2 (TCF7L2) gene with gestational diabetes mellitus: a meta-analysis

A meta-analysis was performed to assess the association between the transcription factor 7-like 2 (TCF7L2) gene polymorphism rs7903146 (IVS3C > T) and gestational diabetes mellitus (GDM). A comprehensive search was conducted to identify all case-control or cohort design studies of the above-mentioned associations. The fixed or random effect pooled measure was selected on the basis of homogeneity test among studies. Heterogeneity among studies was evaluated using the I(2). Meta-regression was used to explore the potential sources of between-study heterogeneity. Publication bias was estimated using Egger's linear regression test. A total of 10 studies including 3404 cases and 6473 controls were involved in this meta-analysis. Overall, after excluding articles that deviated from HWE in controls, and further the key contributors to between-study heterogeneity, significant associations between TCF7L2 rs7903146 genetic polymorphism and risk of gestational diabetes mellitus were observed in the dominant (OR 1.653, 95% CI 1.416-1.930) and codominant (OR 1.525, 95% CI 1.350-1.723) models. The meta-analysis suggests that TCF7L2 rs7903146 genetic polymorphism was associated with increased risk of gestational diabetes mellitus.

Genetic variants and the risk of gestational diabetes mellitus: a systematic review

BACKGROUND

Several 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.

METHODS

Genetic 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.

RESULTS

Overall, 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.

CONCLUSIONS

In 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.

Meta-analysis of the relationship between common type 2 diabetes risk gene variants with gestational diabetes mellitus

BACKGROUND

A number of case-control studies were conducted to investigate the association of common type 2 diabetes (T2D) risk gene polymorphisms with gestational diabetes mellitus (GDM). However, these studies have yielded contradictory results. We therefore performed a meta-analysis to derive a more precise estimation of the association between these polymorphisms and GDM, hence achieve a better understanding to the relationship between T2D and GDM.

METHODS

PubMed, EMBASE, ISI web of science and the Chinese National Knowledge Infrastructure databases were systematically searched to identify relevant studies. Data were abstracted independently by two reviewers. A meta-analysis was performed to examine the association between 9 polymorphisms from 8 genes and susceptibility to GDM. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Heterogeneity among articles and their publication bias were also tested.

RESULTS

We identified 22 eligible studies including a total of 10,336 GDM cases and 17,445 controls. We found 8 genetic polymorphisms were significantly associated with GDM in a random-effects meta-analysis. These polymorphisms were in or near the following genes: TCF7L2 (rs7903146), MTNR1B (rs10830963), IGF2BP2 (rs4402960), KCNJ11 (rs5219), CDKAL1 (rs7754840), KCNQ1 (rs2237892 and rs2237895) and GCK (rs4607517); while no association was found for PPARG with GDM risk. Similar results were also observed under dominant genetic model for these polymorphisms.

CONCLUSIONS

This meta-analysis found 8 genetic variants associated with GDM. The relative contribution and relevance of the identified genes in the pathogenesis of GDM should be the focus of future studies.

Genetic prediction of postpartum diabetes in women with gestational diabetes mellitus

AIMS

To examine whether genetic variants that predispose individuals to type 2 diabetes (T2D) could predict the development of diabetes after gestational diabetes mellitus (GDM).

METHODS

13 SNPs (FTO rs8050136, CDKAL1 rs7754840 and rs7756992, CDKN2A/2B rs10811661, HHEX rs1111875, IGF2BP2 rs1470579 and rs4402960, SLC30A8 rs13266634, TCF7L2 rs7903146, PPARG rs1801282, GCK rs1799884, HNF1A rs1169288, and KCNJ11 rs5219) were genotyped in 793 women with GDM after a median follow-up of 57 months.

RESULTS

After adjustment for age and ethnicity, the TCF7L2 rs7903146 and the FTO rs8050136 variants significantly predicted postpartum diabetes; hazard ratio (95% confidence interval 1.29 (1.01-1.66) and 1.36 (1.06-1.74), respectively (additive model) versus 1.45 (1.01-2.08) and 1.56 (1.06-2.29) (dominant model)). Adjusting for BMI attenuated the effect of the FTO variant, suggesting that the effect was mediated through its effect on BMI. Combining all risk alleles to a weighted risk score was significantly associated with the risk of postpartum diabetes (hazard ratio 1.11, 95% confidence interval 1.05-1.18, p=0.00016 after adjustment for age and ethnicity).

CONCLUSIONS

The TCF7L2 rs7903146 and FTO rs8050136 polymorphisms, and particularly a weighted risk score of T2D risk alleles, predict diabetes after GDM. Further studies in other populations are needed to confirm our results.