Genetic determinants for gestational diabetes mellitus and related metabolic traits in Mexican women

Genome-Wide Polygenic Risk Score Predicts Incident Type 2 Diabetes in Women With History of Gestational Diabetes

OBJECTIVE

Women with a history of gestational diabetes mellitus (GDM) are at increased risk of developing type 2 diabetes (T2D). It remains unclear whether genetic information improves prediction of incident T2D in these women.

RESEARCH DESIGN AND METHODS

Using five independent cohorts representing four different ancestries (n = 1,895), we investigated whether a genome-wide T2D polygenic risk score (PRS) is associated with increased risk of incident T2D. We also calculated the area under the receiver operating characteristics curve (AUROC) and continuous net reclassification improvement (NRI) following the incorporation of T2D PRS into clinical risk models to assess the diagnostic utility.

RESULTS

Among 1,895 women with previous history of GDM, 363 (19.2%) developed T2D in a range of 2 to 30 years. T2D PRS was higher in those who developed T2D (-0.08 vs. 0.31, P = 2.3 × 10-11) and was associated with an increased risk of incident T2D (odds ratio 1.52 per 1-SD increase, 95% CI 1.05-2.21, P = 0.03). In a model that includes age, family history of diabetes, systolic blood pressure, and BMI, the incorporation of PRS led to an increase in AUROC for T2D from 0.71 to 0.74 and an intermediate improvement of NRI (0.32, 95% CI 0.15-0.49, P = 3.0 × 10-4). Although there was variation, a similar trend was observed across study cohorts.

CONCLUSIONS

In cohorts of GDM women with diverse ancestry, T2D PRS was significantly associated with future development of T2D. A significant but small improvement was observed in AUROC when T2D PRS was integrated into clinical risk models to predict incident T2D.

Genetics of glucose homeostasis in pregnancy and postpartum

AIMS/HYPOTHESIS

Pregnancy is accompanied by maternal metabolic adaptations to ensure fetal growth and development, including insulin resistance, which occurs primarily during the second and third trimesters of pregnancy, and a decrease in fasting blood sugar levels over the course of pregnancy. Glucose-related traits are regulated by genetic and environmental factors and modulated by physiological variations throughout the life course. We addressed the hypothesis that there are both overlaps and differences between genetic variants associated with glycaemia-related traits during and outside of pregnancy.

METHODS

Genome-wide SNP data were used to identify genetic variations associated with glycaemia-related traits measured during an OGTT performed at ~28 weeks' gestation in 8067 participants in the Hyperglycaemia and Adverse Pregnancy Outcome (HAPO) Study. Associations outside of pregnancy were determined in 3977 individuals who also participated in the HAPO Follow-Up Study at 11-14 years postpartum. A Bayesian classification algorithm was used to determine whether SNPs associated with fasting and 2 h glucose and fasting C-peptide during pregnancy had a pregnancy-predominant effect vs a similar effect during pregnancy and postpartum.

RESULTS

SNPs in six loci (GCKR, G6PC2, GCK, PPP1R3B, PCSK1 and MTNR1B) were significantly associated with fasting glucose during pregnancy, while SNPs in CDKAL1 and MTNR1B were associated with 1 h glucose and SNPs in MTNR1B and HKDC1 were associated with 2 h glucose. Variants in CDKAL1 and MTNR1B were associated with insulin secretion during pregnancy. Variants in multiple loci were associated with fasting C-peptide during pregnancy, including GCKR, IQSEC1, PPP1R3B, IGF1 and BACE2. GCKR and BACE2 were associated with 1 h C-peptide and GCKR, IQSEC1 and BACE2 with insulin sensitivity during pregnancy. The associations of MTNR1B with 2 h glucose, BACE2 with fasting and 1 h C-peptide and insulin sensitivity, and IQSEC1 with fasting C-peptide and insulin sensitivity that we identified during pregnancy have not been previously reported in non-pregnancy cohorts. The Bayesian classification algorithm demonstrated that the magnitude of effect of the lead SNP was greater during pregnancy compared with 11-14 years postpartum in PCSK1 and PPP1R3B with fasting glucose, in three loci, including MTNR1B, with 2 h glucose, and in six loci, including IGF1, with fasting C-peptide.

CONCLUSIONS/INTERPRETATION

Our findings support the hypothesis that there are both overlaps and differences between the genetic architecture of glycaemia-related traits during and outside of pregnancy. Genetic variants at several loci, including PCSK1, PPP1R3B, MTNR1B and IGF1, appear to influence glycaemic regulation in a unique fashion during pregnancy. Future studies in larger cohorts will be needed to replicate the present findings, fully characterise the genetics of maternal glycaemia during pregnancy and determine similarities to and differences from the non-gravid state.

Association of BDNF polymorphism with gestational diabetes mellitus risk: a novel insight into genetic predisposition

OBJECTIVES

Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder during pregnancy with potential long-term health implications for the mother and child. The interplay between genetics and GDM susceptibility remains an area of active research. Recently, brain-derived neurotrophic factor (BDNF) was investigated in relation to obesity and impaired glucose metabolism and pathogenesis. We aimed to investigate the association of common BDNF polymorphisms, with GDM risk in Israeli females.

METHODS

A cohort of 4,025 Israeli women data for BDNF common SNPs was analyzed for potential association with GDM using binary logistic regressions analysis (SPSS 29.0 and R) adjusted for confounding variables (age, T1DM, T2DM, PCOS) under different genetic models.

RESULTS

The GDM and Non-GDM genetic frequencies for the BDNF rs925946 Tag-SNP were significantly different. The genetic frequencies were 54.16 %, and 66.91 % for the wild type (GG), 38.88 and 29.64 % for the heterozygotes (TC), and 6.94 and 3.48 % for the risk allele homozygotes (TT) for the GDM non-GDM populations, respectively. Carriers of BDNF rs925946 were significantly associated with higher risk for GDM, following the dominant genetic model (OR=1.7, 95 % CI 1.21-2.39, p=0.002), the recessive genetic model (OR=2.05, 95 % CI 1.04-4.03, p=0.03), and the additive genetic model (OR=1.62, 95 % CI 1.13-2.3, p=0.008). This association persisted after adjusting for age, T1DM, T2DM, and polycystic ovary syndrome (PCOS).

CONCLUSIONS

Carrying BDNF rs925946 polymorphism predisposes to a higher risk of GDM pathogenesis. Its role and implications warrant further investigation, especially when considering preventive measures for GDM development.

Epistasis Between HLA-DRB1*16:02:01 and SLC16A11 T-C-G-T-T Reduces Odds for Type 2 Diabetes in Southwest American Indians

We sought to identify genetic/immunologic contributors of type 2 diabetes (T2D) in an indigenous American community by genotyping all study participants for both high-resolution HLA-DRB1 alleles and SLC16A11 to test their risk and/or protection for T2D. These genes were selected based on independent reports that HLA-DRB1*16:02:01 is protective for T2D and that SLC16A11 associates with T2D in individuals with BMI <35 kg/m2. Here, we test the interaction of the two loci with a more complete data set and perform a BMI sensitivity test. We defined the risk protection haplotype of SLC16A11, T-C-G-T-T, as allele 2 of a diallelic genetic model with three genotypes, SLC16A11*11, *12, and *22, where allele 1 is the wild type. Both earlier findings were confirmed. Together in the same logistic model with BMI ≥35 kg/m2, DRB1*16:02:01 remains protective (odds ratio [OR] 0.73), while SLC16A11 switches from risk to protection (OR 0.57 [*22] and 0.78 [*12]); an added interaction term was statistically significant (OR 0.49 [*12]). Bootstrapped (b = 10,000) statistical power of interaction, 0.4801, yielded a mean OR of 0.43. Sensitivity analysis demonstrated that the interaction is significant in the BMI range of 30-41 kg/m2. To investigate the epistasis, we used the primary function of the HLA-DRB1 molecule, peptide binding and presentation, to search the entire array of 15-mer peptides for both the wild-type and ancient human SLC16A11 molecules for a pattern of strong binding that was associated with risk and protection for T2D. Applying computer binding algorithms suggested that the core peptide at SLC16A11 D127G, FSAFASGLL, might be key for moderating risk for T2D with potential implications for type 1 diabetes.

ARTICLE HIGHLIGHTS

Genetic and inflammatory factors underlying gestational diabetes mellitus: a review

Gestational diabetes mellitus (GDM) poses a significant global health concern, impacting both maternal and fetal well-being. Early detection and treatment are imperative to mitigate adverse outcomes during pregnancy. This review delves into the pivotal role of insulin function and the influence of genetic variants, including SLC30A8, CDKAL1, TCF7L2, IRS1, and GCK, in GDM development. These genetic variations affect beta-cell function and insulin activity in crucial tissues, such as muscle, disrupting glucose regulation during pregnancy. We propose a hypothesis that this variation may disrupt zinc transport, consequently impairing insulin production and secretion, thereby contributing to GDM onset. Furthermore, we discussed the involvement of inflammatory pathways, such as TNF-alpha and IL-6, in predisposing individuals to GDM. Genetic modulation of these pathways may exacerbate glucose metabolism dysregulation observed in GDM patients. We also discussed how GDM affects cardiovascular disease (CVD) through a direct correlation between pregnancy and cardiometabolic function, increasing atherosclerosis, decreased vascular function, dyslipidemia, and hypertension in women with GDM history. However, further research is imperative to unravel the intricate interplay between inflammatory pathways, genetics, and GDM. This understanding is pivotal for devising targeted gene therapies and pharmacological interventions to rectify genetic variations in SLC30A8, CDKAL1, TCF7L2, IRS1, GCK, and other pertinent genes. Ultimately, this review offers insights into the pathophysiological mechanisms of GDM, providing a foundation for developing strategies to mitigate its impact.

A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Caucasian and Latin American Pregnant Women

The pathophysiology of gestational diabetes mellitus (GDM) comprises clinical and genetic factors. In fact, GDM is associated with several single nucleotide polymorphisms (SNPs). This study aimed to build a prediction model of GDM combining clinical and genetic risk factors. A total of 1588 pregnant women from the San Carlos Cohort participated in the present study, including 1069 (67.3%) Caucasian (CAU) and 519 (32.7%) Latin American (LAT) individuals, and 255 (16.1%) had GDM. The incidence of GDM was similar in both groups (16.1% CAU and 16.0% LAT). Genotyping was performed via IPLEX Mass ARRAY PCR, selecting 110 SNPs based on literature references. SNPs showing the strongest likelihood of developing GDM were rs10830963, rs7651090, and rs1371614 in CAU and rs1387153 and rs9368222 in LAT. Clinical variables, including age, pre-pregnancy body mass index, and fasting plasma glucose (FPG) at 12 gestational weeks, predicted the risk of GDM (AUC 0.648, 95% CI 0.601-0.695 in CAU; AUC 0.688, 95% CI 0.628-9.748 in LAT), and adding SNPs modestly improved prediction (AUC 0.722, 95%CI 0.680-0.764 in CAU; AUC 0.769, 95% CI 0.711-0.826 in LAT). In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women.

Glucose metabolism in gestational diabetes and their relationship with fat mass / muscle mass index

Introduction

During pregnancy, women experience metabolic changes that may induce insulin resistance, which can be traced to the blood glucose levels A number of factors may intervene in the metabolism of glucose in pregnant women; one of them is body composition. This factor is useful for studying metabolic diseases, for which the identification of the fat mass/muscle mass index (FMMMI) considered an especially relevant factor. Owing to their nature, techniques such as bioimpedance have been sparsely used for analysis during pregnancy.

Aim

This study aimed to identify the relationship between fat mass / muscle mass index and glucose metabolism in pregnant women.

Methods

This descriptive cross-sectional study included 231 women between the ages of 18 and 35 years and 24-28 weeks of gestation, who attended a state hospital for regular check-ups and exhibited risk factors for the development of gestational diabetes (GD) according to the Current Practice Guidelines in Primary Care. The participants underwent a physical examination, anthropometric measurements bio impedance were obtained, and oral glucose tolerance curves were constructed. FMMMI was calculated.

Results

The prevalence of gestational diabetes was observed to be 13.4%. Women with a GD diagnosis had a significantly higher FMMMI than in those with no GD (0.746 ± 0.168 vs 0.567 ± 0.167;p < 0.005). The assessment of the FMMMI tertiles revealed that GD prevalence was higher in tertile 3 than in tertiles 1 and 2 (tertile 1: 2.6%; tertile 2: 9.1%; tertile 3: 24%).

Conclusion

FMMMI is associated with glucose tolerance test response in pregnant women and a higher prevalence of GD.

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.

An early prediction model for gestational diabetes mellitus based on metabolomic biomarkers

BACKGROUND

Gestational diabetes mellitus (GDM) represents the main metabolic alteration during pregnancy. The available methods for diagnosing GDM identify women when the disease is established, and pancreatic beta-cell insufficiency has occurred.The present study aimed to generate an early prediction model (under 18 weeks of gestation) to identify those women who will later be diagnosed with GDM.

METHODS

A cohort of 75 pregnant women was followed during gestation, of which 62 underwent normal term pregnancy and 13 were diagnosed with GDM. Targeted metabolomics was used to select serum biomarkers with predictive power to identify women who will later be diagnosed with GDM.

RESULTS

Candidate metabolites were selected to generate an early identification model employing a criterion used when performing Random Forest decision tree analysis. A model composed of two short-chain acylcarnitines was generated: isovalerylcarnitine (C5) and tiglylcarnitine (C5:1). An analysis by ROC curves was performed to determine the classification performance of the acylcarnitines identified in the study, obtaining an area under the curve (AUC) of 0.934 (0.873-0.995, 95% CI). The model correctly classified all cases with GDM, while it misclassified ten controls as in the GDM group. An analysis was also carried out to establish the concentrations of the acylcarnitines for the identification of the GDM group, obtaining concentrations of C5 in a range of 0.015-0.25 μmol/L and of C5:1 with a range of 0.015-0.19 μmol/L.

CONCLUSION

Early pregnancy maternal metabolites can be used to screen and identify pregnant women who will later develop GDM. Regardless of their gestational body mass index, lipid metabolism is impaired even in the early stages of pregnancy in women who develop GDM.

Saudi Community-Based Screening Study on Genetic Variants in β-Cell Dysfunction and Its Role in Women with Gestational Diabetes Mellitus

BACKGROUND

Diabetes (hyperglycemia) is defined as a multifactorial metabolic disorder in which insulin resistance and defects in pancreatic β-cell dysfunction are two major pathophysiologic abnormalities that underpin towards gestational diabetes mellitus (GDM). TCF7L2, KCNQ1, and KCNJ11 genes are connected to the mechanism of β-cell dysfunction. The purpose of this study was to investigate the genes associated with β-cell dysfunction and their genetic roles in the rs7903146, rs2237892, and rs5219 variants in Saudi women diagnosed with type 2 diabetes mellitus and GDM.

MATERIALS AND METHODS

In this case-control study, 100 women with GDM and 100 healthy volunteers (non-GDM) were recruited. Genotyping was performed using polymerase chain reaction (PCR), followed by restriction fragment length analysis. Validation was performed using Sanger sequencing. Statistical analyses were performed using multiple software packages.

RESULTS

Clinical studies showed a β-cell dysfunction positive association in women with GDM when compared to non-GDM women (p < 0.05). Both rs7903146 (CT vs. CC: OR-2.12 [95%CI: 1.13-3.96]; p = 0.01 & T vs. C: (OR-2.03 [95%CI: 1.32-3.11]; p = 0.001) and rs5219 SNPs (AG vs. AA: OR-3.37 [95%CI: 1.63-6.95]; p = 0.0006 & G vs. A: OR-3.03 [95%CI: 1.66-5.52]; p = 0.0001) showed a positive association with genotype and allele frequencies in women with GDM. ANOVA analysis confirmed that weight (p = 0.02), BMI (p = 0.01), and PPBG (p = 0.003) were associated with rs7903146 and BMI (p = 0.03) was associated with rs2237892 SNPs.

CONCLUSIONS

This study confirms that the SNPs rs7903146 (TCF7L2) and rs5219 (KCNJ11) are strongly associated with GDM in the Saudi population. Future studies should address the limitations of this study.

Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms

INTRODUCTION

Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables.

RESEARCH DESIGN AND METHODS

Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort.

RESULTS

Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively.

CONCLUSIONS

We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

Genetic predisposition to gestational diabetes mellitus in the Kazakh population

BACKGROUND AND AIMS

The purpose of the study was to conduct a comparative analysis of population frequencies of alleles and genotypes of polymorphic variants of genes for impaired insulin synthesis and associated with insulin signal transduction.

METHODS

This investigation uses a genomic database of 1800 conditionally healthy individuals of Kazakh ethnicity, who underwent full genome genotyping using OmniChip 2.5-8 Illumina chips of ∼2.5 million Single Nucleotide Polymorphism at deCODE Iceland Genomic Centre.

RESULTS

The highest frequency of carriage of minor A allele - 17.6% rs4607517 polymorphism of Glucokinase gene, unfavorable genotypes A/G - 29.5% and A/A - 3.0% in comparison with European and Asian populations, indicates a contribution of hereditary family forms of Maturity-onset diabetes of the young type 2 to gestational diabetes mellitus in Kazakh population.

CONCLUSIONS

The study of the associations of genetic markers of gestational diabetes mellitus will allow timely identification of high-risk groups before and at an early stage of pregnancy, carrying out the necessary effective preventive measures and, in the case of gestational diabetes mellitus development, optimizing the correction of carbohydrate metabolism disorders and predicting outcomes for the mother and the fetus.

Evolution of Gestational Diabetes Mellitus across Continents in 21st Century

Over the last few decades, several definitions of gestational diabetes mellitus (GDM) have been described. There is currently not enough research to show which way is the best to diagnose GDM. Opinions differ in terms of the optimal screening and diagnostic measures, in part due to the differences in the population risks, the cost-effectiveness considerations, and the lack of an evidence base to support large national screening programs. The basic method for identifying the disease is the measurement of glucose plasma levels which may be determined when fasting, two hours after a meal, or simply at any random time. The currently increasing incidence of diabetes in the whole population, the altering demographics and the presence of lifestyle changes still require better methods of screening for hyperglycemia, especially during pregnancy. The main aim of this review is to focus on the prevalence and modifications to the screening criteria for GDM across all continents in the 21st century. We would like to show the differences in the above issues and correlate them with the geographical situation. Looking at the history of diabetes, we are sure that more than one evolution in GDM diagnosis will occur, due to the development of medicine, appearance of modern technologies, and the dynamic continuation of research.

Genetic Risk Factors and Gene-Lifestyle Interactions in Gestational Diabetes

Paralleling the increasing trends of maternal obesity, gestational diabetes (GDM) has become a global health challenge with significant public health repercussions. In addition to short-term adverse outcomes, such as hypertensive pregnancy disorders and fetal macrosomia, in the long term, GDM results in excess cardiometabolic morbidity in both the mother and child. Recent data suggest that women with GDM are characterized by notable phenotypic and genotypic heterogeneity and that frequencies of adverse obstetric and perinatal outcomes are different between physiologic GDM subtypes. However, as of yet, GDM treatment protocols do not differentiate between these subtypes. Mapping the genetic architecture of GDM, as well as accurate phenotypic and genotypic definitions of GDM, could potentially help in the individualization of GDM treatment and assessment of long-term prognoses. In this narrative review, we outline recent studies exploring genetic risk factors of GDM and later type 2 diabetes (T2D) in women with prior GDM. Further, we discuss the current evidence on gene-lifestyle interactions in the development of these diseases. In addition, we point out specific research gaps that still need to be addressed to better understand the complex genetic and metabolic crosstalk within the mother-placenta-fetus triad that contributes to hyperglycemia in pregnancy.

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.

KCNJ11 and KCNQ1 Gene Polymorphisms and Placental Expression in Women with Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) represents carbohydrate intolerance in pregnant women. The pathogenesis of GDM is very complex, but abnormalities in insulin production and secretion underlie the disease. Potassium channels play an important role in insulin production and secretion. The family of potassium channels includes (among others) the potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) and voltage-gated K+ channel (KCNQ1). The aim of the study was to examine the distribution of the KCNJ11 rs5219 and KCNQ1 rs151290 and rs2237892 gene polymorphisms in women with GDM and pregnant women with normal carbohydrate tolerance, to verify whether these polymorphisms are risk factors for GDM. This study included 204 Caucasian pregnant women with GDM and 207 pregnant women with normal glucose tolerance (NGT) from the West Pomeranian region of Poland. The diagnosis of GDM was based on a 75 g oral glucose tolerance test (OGTT) at 24–28 weeks gestation. There were no statistically significant differences in distribution of the KCNJ11 rs5219 and KCNQ1 rs151290 and rs2237892 gene polymorphisms between women with GDM and pregnant women with normal carbohydrate tolerance. Moreover, there were no statistically significant associations between the studied genotypes and the selected clinical parameters in women with GDM. The results of our study suggest that the KCNJ11 rs5219 and KCNQ1 rs2237892 and rs151290 gene polymorphisms are not significant risk factors associated with the development of GDM in our population. There were also no differences in the expression of KCNJ11 and KCNQ1 genes in the placenta of women with GDM and normal carbohydrate tolerance. However, an association between KCNJ11 gene expression in placenta and APGAR score in newborns was found.

Downregulation of SLC16A11 is Present in Offspring of Mothers with Gestational Diabetes

BACKGROUND

Studies have identified that diseases in pregnancy affect fetal growth and development of the newborn. In Mexican population, the gene SLC16A11 has been identified as a factor that increases the risk of developing type 2 diabetes mellitus. To date, information is scarce about its expression in gestational diabetes mellitus (GDM); epigenetic modifications due to maternal hyperglycemic state could be identified early in fetal development.

PURPOSE

This study aimed to determine the SLC16A11 expression and methylation status in umbilical cord blood of newborns offspring of mothers with or without GDM.

METHODS

Cross-sectional, analytic study. Pregnant patients undergoing caesarean delivery with and without GDM in the Unidad Medica de Alta Especialidad Hospital de Gineco-obstetricia #4 Luis Castelazo Ayala, Instituto Mexicano del Seguro Social, were invited to participate. DNA was extracted from the mothers' blood cells, or umbilical cord blood cells of their newborns, and subjected to methylation status. Total RNA was used to evaluate the SLC16A11 expression by endpoint RT-PCR. Variables were analyzed with Student t. Values of p <0.05 were considered statistically significant.

RESULTS

A SLC16A11 downregulation was observed for newborns, while methylation status was found in only 1 of 68 mother-child pairs. Somatometry of newborns showed no differences between groups. Differences were found in total cholesterol, triglycerides, ALT, glucose, and HbA1c.

CONCLUSIONS

For the first time, a differential expression for SLC16A11 was observed in offspring. Downregulation in this gene expression could characterize the offspring from GDM. No difference was found in somatometry of newborns of mothers with and without GDM.

Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks

An emerging area of interest in understanding disease phenotypes is systems genomics. Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations. A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful, but understanding the candidate genes harboring those mutations is an unmet goal. In this perspective, using systems genomic approaches, we highlight the application of phenome-interactome networks in diabetes and provide deep insights. LINC01128, which we previously described as candidate for diabetes, is shown as an example to discuss the approach.

Pathophysiological Role of Genetic Factors Associated With Gestational Diabetes Mellitus

Gestational Diabetes Mellitus (GDM) is a highly prevalent maternal pathology characterized by maternal glucose intolerance during pregnancy that is, associated with severe complications for both mother and offspring. Several risk factors have been related to GDM; one of the most important among them is genetic predisposition. Numerous single nucleotide polymorphisms (SNPs) in genes that act at different levels on various tissues, could cause changes in the expression levels and activity of proteins, which result in glucose and insulin metabolism dysfunction. In this review, we describe various SNPs; which according to literature, increase the risk of developing GDM. These SNPs include: (1) those associated with transcription factors that regulate insulin production and excretion, such as rs7903146 (TCF7L2) and rs5015480 (HHEX); (2) others that cause a decrease in protective hormones against insulin resistance such as rs2241766 (ADIPOQ) and rs6257 (SHBG); (3) SNPs that cause modifications in membrane proteins, generating dysfunction in insulin signaling or cell transport in the case of rs5443 (GNB3) and rs2237892 (KCNQ1); (4) those associated with enzymes such as rs225014 (DIO2) and rs9939609 (FTO) which cause an impaired metabolism, resulting in an insulin resistance state; and (5) other polymorphisms, those are associated with growth factors such as rs2146323 (VEGFA) and rs755622 (MIF) which could cause changes in the expression levels of these proteins, producing endothelial dysfunction and an increase of pro-inflammatory cytokines, characteristic on GDM. While the pathophysiological mechanism is unclear, this review describes various potential effects of these polymorphisms on the predisposition to develop GDM.

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.

Genetic variants for prediction of gestational diabetes mellitus and modulation of susceptibility by a nutritional intervention based on a Mediterranean diet

HYPOTHESIS

Gestational diabetes mellitus (GDM) entails a complex underlying pathogenesis, with a specific genetic background and the effect of environmental factors. This study examines the link between a set of single nucleotide polymorphisms (SNPs) associated with diabetes and the development of GDM in pregnant women with different ethnicities, and evaluates its potential modulation with a clinical intervention based on a Mediterranean diet.

METHODS

2418 women from our hospital-based cohort of pregnant women screened for GDM from January 2015 to November 2017 (the San Carlos Cohort, randomized controlled trial for the prevention of GDM ISRCTN84389045 and real-world study ISRCTN13389832) were assessed for evaluation. Diagnosis of GDM was made according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Genotyping was performed by IPLEX MassARRAY PCR using the Agena platform (Agena Bioscience, SanDiego, CA). 110 SNPs were selected for analysis based on selected literature references. Statistical analyses regarding patients' characteristics were performed in SPSS (Chicago, IL, USA) version 24.0. Genetic association tests were performed using PLINK v.1.9 and 2.0 software. Bioinformatics analysis, with mapping of SNPs was performed using STRING, version 11.5.

RESULTS

Quality controls retrieved a total 98 SNPs and 1573 samples, 272 (17.3%) with GDM and 1301 (82.7%) without GDM. 1104 (70.2%) were Caucasian (CAU) and 469 (29.8%) Hispanic (HIS). 415 (26.4%) were from the control group (CG), 418 (26.6%) from the nutritional intervention group (IG) and 740 (47.0%) from the real-world group (RW). 40 SNPs (40.8%) presented some kind of significant association with GDM in at least one of the genetic tests considered. The nutritional intervention presented a significant association with GDM, regardless of the variant considered. In CAU, variants rs4402960, rs7651090, IGF2BP2; rs1387153, rs10830963, MTNR1B; rs17676067, GLP2R; rs1371614, DPYSL5; rs5215, KCNJ1; and rs2293941, PDX1 were significantly associated with an increased risk of GDM, whilst rs780094, GCKR; rs7607980, COBLL1; rs3746750, SLC17A9; rs6048205, FOXA2; rs7041847, rs7034200, rs10814916, GLIS3; rs3783347, WARS; and rs1805087, MTR, were significantly associated with a decreased risk of GDM, In HIS, variants significantly associated with increased risk of GDM were rs9368222, CDKAL1; rs2302593, GIPR; rs10885122, ADRA2A; rs1387153, MTNR1B; rs737288, BACE2; rs1371614, DPYSL5; and rs2293941, PDX1, whilst rs340874, PROX1; rs2943634, IRS1; rs7041847, GLIS3; rs780094, GCKR; rs563694, G6PC2; and rs11605924, CRY2 were significantly associated with decreased risk for GDM.

CONCLUSIONS

We identify a core set of SNPs in their association with diabetes and GDM in a large cohort of patients from two main ethnicities from a single center. Identification of these genetic variants, even in the setting of a nutritional intervention, deems useful to design preventive and therapeutic strategies.

Are single nucleotide polymorphisms rs7903146 and rs12255372 in transcription factor 7-like 2 gene associated with an increased risk for gestational diabetes mellitus in Egyptian women?

BACKGROUND

Genetic variants in the transcription factor 7-like 2 (TCF7L2) gene are related with type 2 diabetes (T2D) and gestational diabetes mellitus (GDM) in various populations, but there are not enough statistics regarding GDM among Egyptian women. We aimed by this study to evaluate the effect of two polymorphisms of rs7903146 and rs12255372 in the TCF7L2 gene with the development of GDM among Egyptian women.

RESULTS

We enrolled 114 pregnant women with normal glucose tolerance and 114 with GDM according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) guidelines. We gathered records on blood pressure, body mass index (BMI), blood glucose level, hemoglobin A1C (HbA1c), and lipid profile. The genotyping of rs7903146 and rs12255372 polymorphisms was carried out using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). The statistical significance of prepregnancy BMI, fasting blood sugar (FBS), HbA1c, low-density lipoprotein (LDL), and total cholesterol (Tch) was higher, P < 0.001, in GDM women in comparison to pregnant women without GDM. CT and TT genotypes in rs7903146 SNP were 46.5% vs. 54%, P <0.04, OR; CI = 1.9 (1.0 to 3.78); TT carriers were 37.7% vs. 9.6%, P <0.001, OR (CI) = 8.9 (3.7-21.1), respectively. For the TCFL2 gene rs12255372 SNP, GT carriers were 48.2% vs. 39.5%, P= 0.004, OR (CI) = 2.3 (1.3-4.2), while TT carriers were 24.6% vs. 7.9%, P < 0.001, OR (CI) = 6 (2.5-14.3).

CONCLUSION

The study showed there is a significantly higher incidence of CT/TT genotypes in rs7903146 SNP and GT/TT genotypes in rs12255372 SNP in TCF7L2 gene among GDM women in comparison to healthy pregnant women (controls).

Effect of KCNQ1 rs2237892 polymorphism on the predisposition to type 2 diabetes mellitus: An updated meta-analysis

OBJECTIVES

Previous studies have analyzed the potential effect of KCNQ1 rs2237892 polymorphism on the predisposition to type 2 diabetes mellitus, but the findings are inconclusive and the subject of debate. The purpose of our study was to provide further insight into the potential association between KCNQ1 rs2237892 polymorphism and the risk of type 2 diabetes mellitus.

METHODS

In total, 50 articles (60 studies) with 77,276 cases and 76,054 controls were utilized in our analysis. The pooled odds ratio (OR), 95% confidence interval (95% CI), and p value were used to evaluate the significance of our findings. Funnel plots and Beggar's regression tests were utilized to determine the presence of publication bias.

RESULTS

Our meta-analysis results indicated that KCNQ1 rs2237892 polymorphism could be correlated with the risk of type 2 diabetes mellitus under the C allelic, recessive, and dominant genetic models (OR = 1.25, 95% 1.19-1.32, p < 0.001; OR = 1.50, 95% CI 1.34-1.68, p < 0.001; OR = 1.26, 95% CI 1.14-1.40, p < 0.001, respectively). Additionally, ethnicity analysis revealed that the source of control, case size, and Hardy-Weinberg Equilibrium status were correlated to the polymorphism in the three genetic models.

CONCLUSIONS

Our meta-analysis demonstrated significant evidence to support the association between KCNQ1 rs2237892 polymorphism and predisposition to type 2 diabetes mellitus.

Deletion of the diabetes candidate gene Slc16a13 in mice attenuates diet-induced ectopic lipid accumulation and insulin resistance

Genome-wide association studies have identified SLC16A13 as a novel susceptibility gene for type 2 diabetes. The SLC16A13 gene encodes SLC16A13/MCT13, a member of the solute carrier 16 family of monocarboxylate transporters. Despite its potential importance to diabetes development, the physiological function of SLC16A13 is unknown. Here, we validate Slc16a13 as a lactate transporter expressed at the plasma membrane and report on the effect of Slc16a13 deletion in a mouse model. We show that Slc16a13 increases mitochondrial respiration in the liver, leading to reduced hepatic lipid accumulation and increased hepatic insulin sensitivity in high-fat diet fed Slc16a13 knockout mice. We propose a mechanism for improved hepatic insulin sensitivity in the context of Slc16a13 deficiency in which reduced intrahepatocellular lactate availability drives increased AMPK activation and increased mitochondrial respiration, while reducing hepatic lipid content. Slc16a13 deficiency thereby attenuates hepatic diacylglycerol-PKCε mediated insulin resistance in obese mice. Together, these data suggest that SLC16A13 is a potential target for the treatment of type 2 diabetes and non-alcoholic fatty liver disease.

Genetic variants of TCF7L2 gene and its coherence with metabolic parameters in Lithuanian (Kaunas district) women population with previously diagnosed gestational diabetes mellitus compared to general population

OBJECTIVE

To determine the association of genetic variants rs7901695, rs7903146, rs7895340, rs11196205, rs12255372 of transcription factor 7 like 2 (TCF7L2) gene and its coherence with metabolic parameters in Lithuanian (Kaunas district) women population with previously diagnosed gestational diabetes mellitus (GDM) and to compare the prevalence of TCF7L2 single nucleotide polymorphism (SNP) results to general population.

METHODS

Women with previously diagnosed GDM participated in the study. Anthropometric measurements were taken. Carbohydrate and fat metabolism were evaluated. TCF7L2 SNP common variants (rs7901695, rs7903146, rs7895340, rs11196205, rs12255372) were set. The prevalence of TCF7L2 the same SNP alleles were also evaluated for women of the general population. The results were compared to the main study group (women with previously diagnosed GDM). The results were calculated in a ratio of 1:2. General population group comprised 300 women who were selected from the random sample of the Kaunas city population. Statistical analysis was made with the statistical package IBM SPSS Statistics version 21. Quantitative parametric variables presented as mean and standard deviation, qualitative variables - as absolute numbers and percentage. ANOVA test was used, for the comparison between three or more groups. Quantitative variables were compared using Student's t-test. Categorical variables were compared using chi-square test. Correlation analysis of parametrical data was performed by Pearson's correlation. Odds ratios (OR) with 95% CIs were presented. The results were considered statistically significant at p < 0.05.

RESULTS

158 women with previously (15-47 years ago) diagnosed GDM participated in the study. The mean age of participants was 53.0 ± 8.2 years and 60.2 ± 7.5 years (p < 0.001), BMI - 31.4 ± 7.9 kg/m2 and 29.9 ± 5.8 kg/m2 (p < 0.001) in GDM group and general population respectively. GDM group women had significantly larger waist, hip circumference and waist to hip ratio compared to general population women: 98.9 ± 18.1 cm vs. 89.2 ± 13.3 (p < 0.001), 112.5 ± 14.8 cm vs. 105.6 ± 10.9 cm (p < 0.001), 0.87 ± 0.08 vs. 0.84 ± 0.07 (p < 0.001). There was no significant difference in blood pressure results between groups (p > 0.05). Carbohydrate dysmetabolism was set for 57.6% women with previously diagnosed GDM: 11 (7.0%) were diagnosed with impaired fasting glycemia (IFG), 14 (8.9%) with impaired glucose tolerance (IGT), type 2 Diabetes Mellitus (DM) was diagnosed for 58 (36.7%), DM type 1 for 7 (4.4%), MODY2 (maturity onset diabetes of the young) - 1 (0.6%) patients. TCF7L2 SNPs in women with previously diagnosed GDM and various carbohydrate metabolism groups did not differed (p > 0.05). Body weight, body mass index (BMI), waist and hip circumference in GDM group participants with different TCF7L2 SNP alleles did not differ (p > 0.05). There was no statistically significant difference in fasting plasma glucose (FPG), oral glucose tolerance test (OGTT) results, cholesterol levels and different TCF7L2 SNP alleles in GDM group (p > 0.05). We found higher prevalence of TCF7L2 SNP rs7901695 CC/CT, rs7903146 CT/TT and rs12255372 GT/TT alleles in women previously diagnosed GDM compared to general population women's group. The OR of being in GDM group with TCF7L2 SNP: rs7901695 CC/CT alleles, was 1.703 (95% CI 1.153-2.515); rs7903146 CT/TT - 1.708 (95% CI 1.149-2.538); rs12255372 GT/TT - 1.575 (95% CI 1.058-2.343).

CONCLUSIONS

No statistically significant difference in glucose, cholesterol levels and different TCF7L2 SNP alleles in GDM group was found. TCF7L2 SNPs did not differed in women with previously diagnosed GDM and various carbohydrate metabolism groups, though a significantly higher incidence of TCF7L2 rs7901695 SNP CC/CT, rs7903146 SNP CT/TT, rs12255372 GT/TT alleles in study subjects compared to the general population women were observed.

Relationship between melatonin and high-risk pregnancy: A review of investigations published between the years 2010 and 2020

The purpose of this review was to search for articles on human studies investigating the relationship between melatonin and high-risk pregnancy. An electronic search was conducted in the MEDLINE and PubMed databases from September 2010 to October 2020. The initial search produced 441 articles in PubMed and 407 in MEDLINE. After sorting the titles and abstracts, and removing duplicates, we had nine articles in PubMed and three in Medline. The results of these studies mainly show that the association between melatonin receptor 1B polymorphisms and gestational diabetes mellitus is the most common physiological mechanism relating to melatonin and high-risk pregnancy in this review. In addition, the circadian rhythm, decreased melatonin production, and anti-inflammatory and antioxidant effects were explored. The findings of our review of the literature suggest that this indoleamine is essential in high-risk pregnancy for its potent anti-inflammatory and antioxidant effects, regulation of the circadian rhythm, and genic receptor expression.

TCF7L2 rs7903146 polymorphism modulates the association between adherence to a Mediterranean diet and the risk of gestational diabetes mellitus

OBJECTIVE

There is sparse evidence for the impact of gene-diet interaction on gestational diabetes mellitus (GDM) onset. Recent findings have shown that late first-trimester high adherence to a Mediterranean diet (MedDiet) pattern is associated with a GDM risk reduction. The aim of this study was to investigate if this effect could be modulated by TCF7L2 rs7903146 polymorphism.Research design and methods: A total of 874 pregnant women participants in the St Carlos GDM prevention study, were stratified into three groups defined as "High,5-6 on targets", "Moderate, 2-4 on targets" or "Low, 0-1 on targets" adherence to Mediterranean diet according to late first-trimester compliance with six food targets: >12 servings/week of vegetables, >12 pieces/week of fruits, <2 servings/week of juice, >3 servings/week of nuts, >6 days/week and >40 mL/day consumption of extra virgin olive oil. All patients were genotyped for rs7903146 using Taqman technology.

RESULTS

Logistic regression analysis revealed that the risk of developing GDM in those with high adherence versus low adherence was significantly reduced only in carriers of the T-allele (CT + TT), with an adjusted odds ratio of 0.15 (95% CI:0.05-0.48). This effect was not observed in CC carriers. Interaction analysis yielded significant rs7903146-MedDiet interaction in GDM risk (p < 0.03).

CONCLUSIONS

Women carrying the rs7903146 T-allele who highly adhere to a MedDiet early in pregnancy have lower risk of developing GDM than CC carriers. This reinforces the importance of identifying patients at risk of GDM who would be especially sensitive to nutritional interventions based on their genetic characteristics.

Genetic Studies of Gestational Diabetes and Glucose Metabolism in Pregnancy

PURPOSE OF REVIEW

In this review, we summarize studies investigating genetics of gestational diabetes mellitus (GDM) and glucose metabolism in pregnancy. We describe these studies in the context of the larger body of literature on type 2 diabetes (T2D) and glycemic trait genomics.

RECENT FINDINGS

We reviewed 23 genetic association studies for GDM and performed a meta-analysis, which revealed variants at eight T2D loci significantly associated with GDM after the Bonferroni correction. These studies suggest that GDM and T2D share a number of genetic risk loci. Only two unbiased genome-wide association studies (GWASs) have successfully revealed genetic associations for GDM and related glycemic traits in pregnancy. A GWAS for GDM in Korean women identified two loci (near CDKAL1 and MTNR1B) known to be associated with T2D, though the association of the MTNR1B locus with GDM appears to be stronger than that for T2D. A multi-ethnic GWAS for glycemic traits in pregnancy identified two novel loci (near HKDC1 and BACE2) which appear to be associated with post-load glucose and fasting c-peptide specifically in pregnant women. There are ongoing efforts to use this genetic information, in the form of polygenic scores, to predict risk of GDM and postpartum T2D. The body of literature examining genetic associations with GDM is limited, especially when compared to the available literature on T2D and glycemic trait genomics. Additional genetic discovery for glucose metabolism in pregnant women will require larger pregnancy cohorts and international collaborative efforts. Studies on the clinical implications of these findings are also warranted.

Chronological Age Interacts with the Circadian Melatonin Receptor 1B Gene Variation, Determining Fasting Glucose Concentrations in Mediterranean Populations. Additional Analyses on Type-2 Diabetes Risk

Gene-age interactions have not been systematically investigated on metabolic phenotypes and this modulation will be key for a better understanding of the temporal regulation in nutrigenomics. Taking into account that aging is typically associated with both impairment of the circadian system and a decrease in melatonin secretion, we focused on the melatonin receptor 1B (MTNR1B)-rs10830963 C>G variant that has been associated with fasting glucose concentrations, gestational diabetes, and type-2 diabetes. Therefore, our main aim was to investigate whether the association between the MTNR1B-rs10830963 polymorphism and fasting glucose is age dependent. Our secondary aims were to analyze the polymorphism association with type-2 diabetes and explore the gene-pregnancies interactions on the later type-2 diabetes risk. Three Mediterranean cohorts (n = 2823) were analyzed. First, a cross-sectional study in the discovery cohort consisting of 1378 participants (aged 18 to 80 years; mean age 41 years) from the general population was carried out. To validate and extend the results, two replication cohorts consisting of elderly individuals were studied. In the discovery cohort, we observed a strong gene-age interaction (p = 0.001), determining fasting glucose in such a way that the increasing effect of the risk G-allele was much greater in young (p = 5.9 × 10^-10) than in elderly participants (p = 0.805). Consistently, the association of the MTNR1B-rs10830963 polymorphism with fasting glucose concentrations in the two replication cohorts (mean age over 65 years) did not reach statistical significance (p > 0.05 for both). However, in the elderly cohorts, significant associations between the polymorphism and type-2 diabetes at baseline were found. Moreover, in one of the cohorts, we obtained a statistically significant interaction between the MTNR1B polymorphism and the number of pregnancies, retrospectively assessed, on the type-2 diabetes risk. In conclusion, the association of the MTNR1B-rs10830963 polymorphism with fasting glucose is age-dependent, having a greater effect in younger people. However, in elderly subjects, associations of the polymorphism with type-2 diabetes were observed and our exploratory analysis suggested a modulatory effect of the number of past pregnancies on the future type-2 diabetes genetic risk.

Defining Heterogeneity Among Women With Gestational Diabetes Mellitus

Attention to precision medicine in type 2 diabetes (T2D) has provided two favored approaches to subclassifying affected individuals and parsing heterogeneity apparent in this condition: phenotype-based and genotype-based. Gestational diabetes mellitus (GDM) shares phenotypic characteristics with T2D. However, unlike T2D, GDM emerges in the setting of profound pregnancy-related physiologic changes in glucose metabolism. T2D and GDM also share common genetic architecture, but there are likely to be unique genetic influences on pregnancy glycemic regulation that contribute to GDM. In this Perspective, we describe efforts to decipher heterogeneity in T2D and detail how we and others are applying approaches developed for T2D to the study of heterogeneity in GDM. Emerging results reveal the potential of phenotype- and genotype-based subclassification of GDM to deliver the promise of precision medicine to the obstetric population.

A Data-Driven Review of the Genetic Factors of Pregnancy Complications

Over the recent years, many advances have been made in the research of the genetic factors of pregnancy complications. In this work, we use publicly available data repositories, such as the National Human Genome Research Institute GWAS Catalog, HuGE Navigator, and the UK Biobank genetic and phenotypic dataset to gain insights into molecular pathways and individual genes behind a set of pregnancy-related traits, including the most studied ones—preeclampsia, gestational diabetes, preterm birth, and placental abruption. Using both HuGE and GWAS Catalog data, we confirm that immune system and, in particular, T-cell related pathways are one of the most important drivers of pregnancy-related traits. Pathway analysis of the data reveals that cell adhesion and matrisome-related genes are also commonly involved in pregnancy pathologies. We also find a large role of metabolic factors that affect not only gestational diabetes, but also the other traits. These shared metabolic genes include IGF2, PPARG, and NOS3. We further discover that the published genetic associations are poorly replicated in the independent UK Biobank cohort. Nevertheless, we find novel genome-wide associations with pregnancy-related traits for the FBLN7, STK32B, and ACTR3B genes, and replicate the effects of the KAZN and TLE1 genes, with the latter being the only gene identified across all data resources. Overall, our analysis highlights central molecular pathways for pregnancy-related traits, and suggests a need to use more accurate and sophisticated association analysis strategies to robustly identify genetic risk factors for pregnancy complications.

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.

MTNR1B genetic polymorphisms as risk factors for gestational diabetes mellitus: a case-control study in a single tertiary care center

BACKGROUND

Gestational diabetes mellitus (GDM) is a metabolic disease in pregnancy that causes carbohydrate intolerance and hyper-glycemia. Genome-wide association studies and meta-analyses have found that the single nucleotide polymorphisms (SNPs) rs1387153 and rs10830963 of the melatonin receptor 1B ( MTNR1B) gene are associated with GDM. No studies on the MTNR1B gene effect on GDM have been performed in Saudis, other Arabs, or other Middle Eastern populations.

OBJECTIVES

Investigate the association of genotype or allele frequencies of the two SNPs with GDM and with clinical parameters related to GDM.

DESIGN

Case-control study.

SETTINGS

Tertiary care center, Riyadh.

PATIENTS AND METHODS

We recruited 400 pregnant Saudi women ages 18-45 years (200 were diagnosed with GDM, and 200 were healthy controls). Biochemical assays were performed, and rs1387153 and rs10830963 polymorphisms were analyzed by polymerase chain reaction-restriction fragment length polymorphism analysis and real-time polymerase chain reaction with TaqMan genotyping.

MAIN OUTCOME MEASURES

The association of MTNR1B gene (rs1387153 and rs10830963 polymorphisms) with GDM and with biochemical parameters related to GDM.

SAMPLE SIZE

200 GDM cases and 200 non-GDM controls.

RESULTS

Differences in allele frequencies for GDM vs non-GMD were statistically significant or nearly significant for both SNPs after adjustment for age and body mass index. In a logistic regression analysis, genotype TT was positively associated with post-prandial blood glucose (P=.018), but other associations were not statistically significant.

CONCLUSION

The odds ratios for the associations between the rs1387153 and rs10830963 SNPs and GDM exceeded 1.5-fold, which is higher than typically reported for diseases with complex genetic background. These effect sizes for GDM suggest pregnancy-specific factors related to the MTNR1B risk genotypes.

LIMITATIONS

Only two SNPs were studied.

CONFLICT OF INTEREST

None.

Short-term health and economic burden of gestational diabetes mellitus in Mexico: A modeling study

AIM

To estimate the annual burden of gestational diabetes mellitus (GDM) in Mexico.

METHODS

A model was built to conduct estimates from a healthcare system perspective, namely, the incremental costs of GDM pregnancy compared with non-GDM pregnancy from the first trimester until childbirth. The model used probabilities from the literature and surveys, and costs obtained from the Ministry of Health and national healthcare institutions. Scenario analyses were performed to estimate the GDM burden at different levels of incidence.

RESULTS

Although a non-GDM pregnancy cost on average USD 1880.6 (low risk was USD 1043.9 and high risk was USD 1673.5), a pregnancy with GDM cost USD 2934.9. Therefore, the total additional cost was USD 1576.2 per case. Given the considerable variability of the GDM incidence in Mexico, the total burden could range from USD 86.8 to USD 827.4 million per year.

CONCLUSIONS

GDM is one of the most frequent complications of pregnancy, but research has been insufficient regarding its epidemiological and economic burden in Latin America. This paper shows that the GDM economic burden in Mexico is substantial despite only accounting for short-term medical costs. Further research to assess the GDM incidence and evaluate its long-term consequences from a broader societal perspective in Mexico is recommended.

Adeno-Associated Virus-Mediated Knockdown of SLC16A11 Improves Glucose Tolerance and Hepatic Insulin Signaling in High Fat Diet-Fed Mice

BACKGROUND

SLC16A11, a member of the SLC16 family, is associated with lipid metabolism, causing increased intracellular triacylglycerol (TAG) levels. In the current study, our primary goal was to determine if an SLC16A11 knockdown would improve glucose tolerance and hepatic insulin signaling in high fat diet (HFD)-fed mice. Additionally, the mechanism for exercise-improved insulin sensitivity remains unclear, and there is no mechanistic insight into SLC16A11's role in insulin sensitivity under exercise stress. Therefore, we also examined the impact of endurance exercise on the abundance of SLC16A11.

METHODS

C57BL/6 J male mice were fed either regular chow (Control) or HFD for 8 weeks and then injected with adeno-associated virus (AAV). Plasma parameters, tissue lipid contents, glucose tolerance, and expression profiles of hepatic insulin signaling were detected. Also, other mice were divided randomly into sedentary and exercise groups. We assessed hepatic expression of SLC16A11 after 8 weeks of endurance exercise.

RESULTS

1) Hepatic SLC16A11 expression was greater in HFD-fed mice compared to Control mice. 2) AAV-mediated knockdown of SLC16A11 improved glucose tolerance, prevented TAG accumulation in serum and liver, and increased phosphorylation of protein kinase B (Akt) and glycogen synthesis kinase-3β (GSK3β) in HFD-fed mice. 3) Endurance exercise decreased hepatic SLC16A11 expression.

CONCLUSIONS

Inactivation of SLC16A11, which is robustly induced by HFD, improved glucose tolerance and hepatic insulin signaling, independent of body weight, but related to TAG. Additionally, SLC16A11 might mediate the health benefits of endurance exercise.

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.

Single Nucleotide Polymorphisms in CDKAL1 Gene Are Associated with Risk of Gestational Diabetes Mellitus in Chinese Population

Gestational diabetes mellitus (GDM) is a growing public health concern for many reasons, and its etiology remains unclear. Due to the similarity of its pathophysiology with type 2 diabetes (T2DM), we evaluated the relationship between published T2DM susceptibility genes and the risk of GDM. A total of 303 SNPs from genes including IRS1, IGF2BP2, CDKAL1, GCK, TCF7L2, KCNQ1, and KCNJ11 and the risk of GDM were examined in a nested case-control study with 321 GDM cases and 316 controls. The odds ratios (ORs) and their 95% confidence interval (95% CI) were estimated by unconditional logistical regression as a measure of the associations between genotypes and GDM in additive, recessive, dominant, and codominant models adjusting for maternal age, maternal BMI, parity, and family history of diabetes. At the gene level, CDKAL1 was associated with GDM risk. SNPs in the CDKAL1 gene including rs4712527, rs7748720, rs9350276, and rs6938256 were associated with reduced GDM risk. However, SNPs including rs9295478, rs6935599, and rs7747752 were associated with elevated GDM risk. After adjusting for multiple comparisons, rs9295478 and rs6935599 were still significant across the additive, recessive, and codominant models; rs7748720 and rs6938256 were significant in dominant and codominant models; and rs4712527 was only significant in the codominant model. Our study provides evidence for an association between the CDKAL1 gene and risk of GDM. However, its role in the GDM pathogenesis still needs to be verified by further studies.

Replication of previous genome-wide association studies of HKDC1, BACE2, SLC16A11 and TMEM163 SNPs in a gestational diabetes mellitus case-control sample from Han Chinese population

Background: Four novel glucose metabolism risk loci (HKDC1 rs4746822, BACE2 rs6517656, SLC16A11 rs13342232 and TMEM163 rs998451) were identified in recent genome-wide association studies (GWAS) of Afro-Caribbean, European, Hispanic, Thai, Mexican, Latin American and Indian populations. None of the abovementioned SNPs has been reported in a Han Chinese population. Aim: To replicate the relationships between HKDC1 rs4746822, BACE2 rs6517656, SLC16A11 rs13342232 and TMEM163 rs998451 with gestational diabetes mellitus (GDM) in a Han Chinese population. Methods: This was a case-control study which enrolled 334 pregnant women with GDM and 367 pregnant women with normal glucose tolerance. The linear regression and logistic regression were used to estimate the association between SNPs with the risk of GDM, HOMA-IR and fasting insulin levels. The fasting insulin concentration and HOMA-IR were log10 transformed before analysis. Results: No significant differences in the alleles and genotypes of SLC16A11 rs13342232, HKDC1 rs4746822 and BACE2 rs6517656 were observed between cases and controls. After adjusting the weekly BMI growth, pre-pregnancy BMI and maternal age, under the additive model, SLC16A11 rs13342232 was associated with log₁₀fasting serum insulin (Beta=0.046, p=0.016), log₁₀HOMA-IR level (Beta=0.061, p=0.003) and fasting plasma glucose level (Beta=0.164, p=0.011); HKDC1 rs4746822 was associated with OGTT 2-hr plasma glucose level (Beta=0.239, p=0.016); and BACE2 rs6517656 was associated with log₁₀fasting serum insulin (Beta=-0.053, p=0.044) and log₁₀HOMA-IR level (Beta=-0.060, p=0.048). After correction for multiple testing, the associations of SLC16A11 and HKDC1 with glucose metabolism remained statistically significant. The A allele of TMEM163 rs998451 was not detected in this population. Conclusion: HKDC1 rs4746822, BACE2 rs6517656 and SLC16A11 rs13342232 are associated with glucose metabolism in pregnant women of Han Chinese.

Ethnic Disparities in Gestational Diabetes

PURPOSE OF REVIEW

Ethnicity has long been described as a major risk factor for the development of gestational diabetes mellitus (GDM), and it is widely recognised that women from ethnicities other than Europids are at higher risk of developing GDM. There are also described differences between ethnicities in key GDM pregnancy outcomes. This review describes some of the factors that relate to the ethnic disparities in GDM.

RECENT FINDINGS

The global prevalence of GDM has been steadily increasing and estimated to be 16.2% from the International Diabetes Federation extrapolation. Reported prevalence rates may understate the true prevalence, due to factors of access and attitudes to GDM diagnosis and screening in low resource settings for foreign-born women and indigenous populations. Other factors may relate to genes associated with specific ethnicities, obesity, body composition and gestational weight gain. Various factors such as access to screening, body composition, genetics and gestational weight gain may result in ethnic disparities in the prevalence and outcomes of GDM.

Screening and management of gestational diabetes in Mexico: results from a survey of multilocation, multi-health care institution practitioners

PURPOSE

To identify the most common practices implemented for the screening and treatment of gestational diabetes mellitus (GDM) and to estimate the GDM clinician-reported proportion as a proxy of the incidence in Mexico.

MATERIALS AND METHODS

Three hundred fifty-seven physicians in four major cities were asked about their practices regarding GDM screening, treatment, clinical exams, and health care staff involved in case of GDM diagnosis, as well as the percentage of women with GDM they care for. Data management and statistical analyses were done with Stata 13.

RESULTS

The overall GDM clinician-reported proportion was 23.7%. Regional differences were expected and consistent with the data on the epidemiology of the obesity in the country. The most common screening test was the oral glucose tolerance test 75 g one step (46.6% of total cases). Diet and exercise were sufficient to treat GDM in 40.6% of cases; the rest of the sample relied on some form of medication, especially oral hypoglycemic agents (63.0% of cases), insulin (22.0%), or a combination of these (13.0%). To educate women on how to measure glycemia and eventually take medications, an average of 2-3 hours were necessary. The three most common prenatal screening tests were the "no stress", the "Doppler ultrasound", and the "biophysical profile", respectively, taken at least once by 70%, 60%, and 45% of women. Among women who were prescribed insulin, only 37% managed to keep the initial prescribed dose during the whole pregnancy.

CONCLUSION

The survey confirmed the expected incidence and gave interesting results on the treatment of GDM. The current Mexican guidelines seem to have been partially implemented in practice, and a coherent national strategy for GDM is still missing. More studies are encouraged to investigate this topic, with the aim to better understand the importance of the monetary cost of GDM, which is currently underestimated.

From Sea to Shining Sea and the Great Plains to Patagonia: A Review on Current Knowledge of Diabetes Mellitus in Hispanics/Latinos in the US and Latin America

The past two decades have witnessed many advances in the prevention, treatment, and control of diabetes mellitus (DM) and its complications. Increased screening has led to a greater recognition of type 2 diabetes mellitus (type 2 DM) and prediabetes; however, Hispanics/Latinos, the largest minority group in the US, have not fully benefited from these advances. The Hispanic/Latino population is highly diverse in ancestries, birth places, cultures, languages, and socioeconomic backgrounds, and it populates most of the Western Hemisphere. In the US, the prevalence of DM varies among Hispanic/Latino heritage groups, being higher among Mexicans, Puerto Ricans, and Dominicans, and lower among South Americans. The risk and prevalence of diabetes among Hispanics/Latinos are significantly higher than in non-Hispanic Whites, and nearly 40% of Hispanics/Latinos with diabetes have not been formally diagnosed. Despite these striking facts, the representation of Hispanics/Latinos in pharmacological and non-pharmacological clinical trials has been suboptimal, while the prevalence of diabetes in these populations continues to rise. This review will focus on the epidemiology, etiology and prevention of type 2 DM in populations of Latin American origin. We will set the stage by defining the terms Hispanic, Latino, and Latin American, explaining the challenges identifying Hispanics/Latinos in the scientific literature and databases, describing the epidemiology of diabetes-including type 2 DM and gestational diabetes mellitus (GDM)-and cardiovascular risk factors in Hispanics/Latinos in the US and Latin America, and discussing trends, and commonalities and differences across studies and populations, including methodology to ascertain diabetes. We will discuss studies on mechanisms of disease, and research on prevention of type 2 DM in Hispanics/Latinos, including women with GDM, youth and adults; and finalize with a discussion on lessons learned and opportunities to enhance research, and, consequently, clinical care oriented toward preventing type 2 DM in Hispanics/Latinos in the US and Latin America.

Role of Placental VDR Expression and Function in Common Late Pregnancy Disorders

Vitamin D, besides its classical role in bone metabolism, plays a distinct role in multiple pathways of the feto-maternal unit. Calcitriol is the major active ligand of the nuclear vitamin D receptor (VDR). The vitamin D receptor (VDR) is expressed in different uteroplacental parts and exerts a variety of functions in physiologic pregnancy. It regulates decidualisation and implantation, influences hormone secretion and placental immune modulations. This review highlights the role of the vitamin D receptor in physiologic and disturbed pregnancy, as preeclampsia, fetal growth restriction, gestational diabetes and preterm birth. We discuss the existing literature regarding common VDR polymorphisms in these pregnancy disorders.

IL-6 variant is associated with metastasis in breast cancer patients

INTRODUCTION

Although tumor metastases remain significant drivers of mortality, the genetic factors that increase the risks of metastases are not fully identified. Interleukin 6 (IL-6) has emerged as an important factor in breast cancer progression with IL-6 single nucleotide polymorphism (SNP) variants shown to affect survival. We hypothesized that SNPs of the IL-6 promoter at rs1800795 in breast cancer patients are associated with distant metastases.

METHODS

We performed an initial case-control study using Vanderbilt University Medical Center's BioVU, a genomic biobank linked to de-identified electronic medical records in the Synthetic Derivative database, to identify germline SNPs that may predict the development of metastatic disease to any site from any solid tumor including breast cancer. We identified a SNP in IL-6: rs1800795 to be of significance and evaluated this finding using a separate, matched-pair cohort of breast cancer patients with and without metastases from The Ohio State University Wexner Medical Center.

RESULTS

The initial study suggested that GG relative to CG at rs1800795 (OR 1.52; 95% CI 1.14-2.02; p = 0.004) was significantly associated with the development of metastases. This association was also observed in the Ohio State University cohort (OR 2.23; 95% CI 1.06-4.71; p = 0.001). There were no significant relationships between rs1800795 status and any patient or tumor characteristics, including estrogen receptor status.

CONCLUSIONS

These findings suggest that GG SNP at IL-6: rs1800795 may indicate an increased risk of metastasis of primary breast cancer. Further studies in larger population sets are warranted as advanced screening and prophylactic intervention might be employed in GG carriers.

Genetic variants and clinical relevance associated with gestational diabetes mellitus in Chinese women: a case-control study

PURPOSE

Gestational diabetes mellitus (GDM) may share similar mechanisms with type 2 diabetes and obesity. In the current study, we aimed to verify twenty genes reported to be associated with type 2 diabetes and obesity in the Chinese GDM population.

METHODS

Pregnant women aged 20-49 years at 24-28 gestational weeks were recruited and 556 cases and 445 controls were enrolled in the study. The genotyping of single nucleotide polymorphisms (SNPs) was performed on peripheral blood samples.

RESULTS

We discovered that GDM was associated with rs945508 (OR = 1.368, 95% CI = 1.080-1.732, p = .009), rs10804591 (OR = 1.446, 95% CI = 1.192-1.754, p < .001), rs10245353 (OR = 1.204, 95% CI = 1.006-1.441, p = .043) and rs1552224 (OR = 1.451, 95% CI = 1.071-1.964, p = .016).

CONCLUSIONS

We found that four SNPs associated with type 2 diabetes and obesity may also increase the risk of developing GDM in the Chinese population. Among these SNPs, we report for the first time that rs945508 in ARHGEF11, rs10804591 in PLXND1 and rs10245353 in NFE2L3 were associated with GDM.

Subtypes of Native American ancestry and leading causes of death: Mapuche ancestry-specific associations with gallbladder cancer risk in Chile

Latin Americans are highly heterogeneous regarding the type of Native American ancestry. Consideration of specific associations with common diseases may lead to substantial advances in unraveling of disease etiology and disease prevention.

Here we investigate possible associations between the type of Native American ancestry and leading causes of death. After an aggregate-data study based on genome-wide genotype data from 1805 admixed Chileans and 639,789 deaths, we validate an identified association with gallbladder cancer relying on individual data from 64 gallbladder cancer patients, with and without a family history, and 170 healthy controls. Native American proportions were markedly underestimated when the two main types of Native American ancestry in Chile, originated from the Mapuche and Aymara indigenous peoples, were combined together. Consideration of the type of Native American ancestry was crucial to identify disease associations. Native American ancestry showed no association with gallbladder cancer mortality (P = 0.26). By contrast, each 1% increase in the Mapuche proportion represented a 3.7% increased mortality risk by gallbladder cancer (95%CI 3.1–4.3%, P = 6×10⁻²⁷). Individual-data results and extensive sensitivity analyses confirmed the association between Mapuche ancestry and gallbladder cancer. Increasing Mapuche proportions were also associated with an increased mortality due to asthma and, interestingly, with a decreased mortality by diabetes. The mortality due to skin, bladder, larynx, bronchus and lung cancers increased with increasing Aymara proportions. Described methods should be considered in future studies on human population genetics and human health. Complementary individual-based studies are needed to apportion the genetic and non-genetic components of associations identified relying on aggregate-data.

A lot of attention has been paid to Latino heterogeneity related to individual proportions of Native American, European and African ancestry. The importance of the type of Native American ancestry for health, however, has hardly been studied. Here we examined genetic data from 2,039 admixed Chileans to investigate possible associations between top causes of death and the two major types of Native American ancestry in Chile. Our findings demonstrate the necessity of suitable surrogates for ancestry estimation which mirror the actual composition of the study population, and the advantage of considering fine-scale Latino heterogeneity for unraveling of disease etiology and personalized healthcare.

Associations between a fetal imprinted gene allele score and late pregnancy maternal glucose concentrations

Aim

We hypothesised that some of the genetic risk for gestational diabetes (GDM) is due to the fetal genome affecting maternal glucose concentrations. Previously, we found associations between fetal IGF2 gene variants and maternal glucose concentrations in late pregnancy.

Methods

In the present study, we tested associations between SNP alleles from 15 fetal imprinted genes and maternal glucose concentrations in late pregnancy in the Cambridge Baby Growth and Wellbeing cohorts (1160 DNA trios).

Results

Four fetal SNP alleles with the strongest univariate associations: paternally-transmitted IGF2 rs10770125 (P-value = 2 × 10^–4) and INS rs2585 (P-value = 7 × 10^–4), and maternally-transmitted KCNQ1(OT1) rs231841 (P-value = 1 × 10^–3) and KCNQ1(OT1) rs7929804 (P-value = 4 × 10^–3), were used to construct a composite fetal imprinted gene allele score which was associated with maternal glucose concentrations (P-value = 4.3 × 10^–6, n = 981, r² = 2.0%) and GDM prevalence (odds ratio per allele 1.44 (1.15, 1.80), P-value = 1 × 10^–3, n = 89 cases and 899 controls). Meta-analysis of the associations including data from 1367 Hyperglycaemia and Adverse Pregnancy Outcome Study participants confirmed the paternally-transmitted fetal IGF2/INS SNP associations (rs10770125, P-value = 3.2 × 10^–8, rs2585, P-value = 3.6 × 10^–5) and the composite fetal imprinted gene allele score association (P-value = 1.3 × 10^–8), but not the maternally-transmitted fetal KCNQ1(OT1) associations (rs231841, P-value = 0.4; rs7929804, P-value = 0.2).

Conclusion

This study suggests that polymorphic variation in fetal imprinted genes, particularly in the IGF2/INS region, contribute a small but significant part to the risk of raised late pregnancy maternal glucose concentrations.

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.