A genome-wide association study of gestational diabetes mellitus in Korean women

Understanding the Genetic Landscape of Gestational Diabetes: Insights into the Causes and Consequences of Elevated Glucose Levels in Pregnancy

Background/Objectives: During pregnancy, physiological changes in maternal circulating glucose levels and its metabolism are essential to meet maternal and fetal energy demands. Major changes in glucose metabolism occur throughout pregnancy and consist of higher insulin resistance and a compensatory increase in insulin secretion to maintain glucose homeostasis. For some women, this change is insufficient to maintain normoglycemia, leading to gestational diabetes mellitus (GDM), a condition characterized by maternal glucose intolerance and hyperglycaemia first diagnosed during the second or third trimester of pregnancy. GDM is diagnosed in approximately 14.0% of pregnancies globally, and it is often associated with short- and long-term adverse health outcomes in both mothers and offspring. Although recent studies have highlighted the role of genetic determinants in the development of GDM, research in this area is still lacking, hindering the development of prevention and treatment strategies. Methods: In this paper, we review recent advances in the understanding of genetic determinants of GDM and glycaemic traits during pregnancy. Results/Conclusions: Our review highlights the need for further collaborative efforts as well as larger and more diverse genotyped pregnancy cohorts to deepen our understanding of the genetic aetiology of GDM, address research gaps, and further improve diagnostic and treatment strategies.

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.

Integrating polygenic risk scores in the prediction of gestational diabetes risk in China

Background

Polygenic risk scores (PRS) serve as valuable tools for connecting initial genetic discoveries with clinical applications in disease risk estimation. However, limited studies have explored the association between PRS and gestational diabetes mellitus (GDM), particularly in predicting GDM risk among Chinese populations.

Aim

To evaluate the relationship between PRS and GDM and explore the predictive capability of PRS for GDM risk in a Chinese population.

Methods

A prospective cohort study was conducted, which included 283 GDM and 2,258 non-GDM cases based on demographic information on pregnancies. GDM was diagnosed using the oral glucose tolerance test (OGTT) at 24-28 weeks. The strength of the association between PRS and GDM odds was assessed employing odds ratios (ORs) with 95% confidence intervals (CIs) derived from logistic regression. Receiver operating characteristic curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were employed to evaluate the improvement in prediction achieved by the new model.

Results

Women who developed GDM exhibited significantly higher PRS compared to control individuals (OR = 2.01, 95% CI = 1.33-3.07). The PRS value remained positively associated with fasting plasma glucose (FPG), 1-hour post-glucose load (1-h OGTT), and 2-hour post-glucose load (2-h OGTT) (all p < 0.05). The incorporation of PRS led to a statistically significant improvement in the area under the curve (0.71, 95% CI: 0.66-0.75, p = 0.024) and improved discrimination and classification (IDI: 0.007, 95% CI: 0.003-0.012, p < 0.001; NRI: 0.258, 95% CI: 0.135-0.382, p < 0.001).

Conclusions

This study highlights the increased odds of GDM associated with higher PRS values and modest improvements in predictive capability for GDM.

Functional genetic variants and susceptibility and prediction of gestational diabetes mellitus

The aetiological mechanism of gestational diabetes mellitus (GDM) has still not been fully understood. The aim of this study was to explore the associations between functional genetic variants screened from a genome-wide association study (GWAS) and GDM risk among 554 GDM patients and 641 healthy controls in China. Functional analysis of single nucleotide polymorphisms (SNPs) positively associated with GDM was further performed. Univariate regression and multivariate logistic regression analyses were used to screen clinical risk factors, and a predictive nomogram model was established. After adjusting for age and prepregnancy BMI, rs9283638 was significantly associated with GDM susceptibility (P < 0.05). Moreover, an obvious interaction between rs9283638 and clinical variables was detected (Pinteraction < 0.05). Functional analysis confirmed that rs9283638 can regulate not only target gene transcription factor binding, but it also regulates the mRNA levels of SAMD7 (P < 0.05). The nomogram model constructed with the factors of age, FPG, 1hPG, 2hPG, HbA1c, TG and rs9283638 revealed an area under the ROC curve of 0.920 (95% CI 0.902-0.939). Decision curve analysis (DCA) suggested that the model had greater net clinical benefit. Conclusively, genetic variants can alter women's susceptibility to GDM by affecting the transcription of target genes. The predictive nomogram model constructed based on genetic and clinical variables can effectively distinguish individuals with different GDM risk factors.

Metabolomic and genetic architecture of gestational diabetes subtypes

AIMS/HYPOTHESIS

Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes.

METHODS

This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM).

RESULTS

Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM.

CONCLUSIONS/INTERPRETATION

This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

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.

Serum Folate and Vitamin B12 Modify the Associations of N6AMT1 Genetic Variants with Gestational Diabetes Mellitus: A Cross-Sectional Study in Chinese Pregnant Women

Purpose

This study aimed to explore the association between N-6 adenine-specific DNA methyltransferase 1 (N6AMT1) single nucleotide polymorphisms (SNPs) and gestational diabetes mellitus (GDM) and the modification of the relationship by folate and vitamin B12.

Methods

A cross-sectional study involving 1303 pregnant women (262 GDM and 1041 non-GDM) was performed in Tianjin, China. Nine SNPs in N6AMT1 were genotyped, and serum folate, vitamin B12, and homocysteine (Hcy) levels were measured. The logistic regression models determined the odds ratios (ORs) for SNPs in N6AMT1 and the gene-nutrition interactions on GDM.

Results

N6AMT1 rs7282280, rs1048546, and rs1997605 were related to GDM under the dominant model after adjusting for multiple covariates. Individuals carrying the N6AMT1 rs7282280 TC/TT genotypes had a lower risk of developing GDM, regardless of serum folate and vitamin B12 levels. However, rs1048546 TG/GG genotypes were associated with lower GDM risk when serum folate ≥ 6.0 ng/mL. Pregnancies with the risk genotypes in N6AMT1 and higher serum folate or lower vitamin B12 are more prone to GDM. The study also showed a statistically significant additive interaction between N6AMT1 rs1997605 GG genotypes and lower vitamin B12 (RERI: 2.54; 95% CI: 0.17, 4.92).

Conclusion

SNPs in N6AMT1 were found to be associated with GDM, and serum folate and vitamin B12 levels can modify their associations.

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.

Genome-wide association and Mendelian randomisation analysis among 30,699 Chinese pregnant women identifies novel genetic and molecular risk factors for gestational diabetes and glycaemic traits

AIMS/HYPOTHESIS

Gestational diabetes mellitus (GDM) is the most common disorder in pregnancy; however, its underlying causes remain obscure. This study aimed to investigate the genetic and molecular risk factors contributing to GDM and glycaemic traits.

METHODS

We collected non-invasive prenatal test (NIPT) sequencing data along with four glycaemic and 55 biochemical measurements from 30,699 pregnant women during a 2 year period at Shenzhen Baoan Women's and Children's Hospital in China. Genome-wide association studies (GWAS) were conducted between genotypes derived from NIPTs and GDM diagnosis, baseline glycaemic levels and glycaemic levels after glucose challenges. In total, 3317 women were diagnosed with GDM, while 19,565 served as control participants. The results were replicated using two independent cohorts. Additionally, we performed one-sample Mendelian randomisation to explore potential causal associations between the 55 biochemical measurements and risk of GDM and glycaemic levels.

RESULTS

We identified four genetic loci significantly associated with GDM susceptibility. Among these, MTNR1B exhibited the highest significance (rs10830963-G, OR [95% CI] 1.57 [1.45, 1.70], p=4.42×10-29), although its effect on type 2 diabetes was modest. Furthermore, we found 31 genetic loci, including 14 novel loci, that were significantly associated with the four glycaemic traits. The replication rates of these associations with GDM, fasting plasma glucose levels and 0 h, 1 h and 2 h OGTT glucose levels were 4 out of 4, 6 out of 9, 10 out of 11, 5 out of 7 and 4 out of 4, respectively. Mendelian randomisation analysis suggested that a genetically regulated higher lymphocytes percentage and lower white blood cell count, neutrophil percentage and absolute neutrophil count were associated with elevated glucose levels and an increased risk of GDM.

CONCLUSIONS/INTERPRETATION

Our findings provide new insights into the genetic basis of GDM and glycaemic traits during pregnancy in an East Asian population and highlight the potential role of inflammatory pathways in the aetiology of GDM and variations in glycaemic levels.

DATA AVAILABILITY

Summary statistics for GDM; fasting plasma glucose; 0 h, 1 h and 2h OGTT; and the 55 biomarkers are available in the GWAS Atlas (study accession no.: GVP000001, https://ngdc.cncb.ac.cn/gwas/browse/GVP000001) .

Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes

Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1-3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1-7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8-10, and the three prior genome-wide association studies of GDM11-13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.

Review of Genetic and Artificial Intelligence approaches to improving Gestational Diabetes Mellitus Screening and Diagnosis in sub-Saharan Africa

Background: Adverse outcomes from gestational diabetes mellitus (GDM) in the mother and newborn are well established. Genetic variants may predict GDM and Artificial Intelligence (AI) can potentially assist with improved screening and early identification in lower resource settings. There is limited information on genetic variants associated with GDM in sub-Saharan Africa and the implementation of AI in GDM screening in sub-Saharan Africa is largely unknown. Methods: We reviewed the literature on what is known about genetic predictors of GDM in sub-Saharan African women. We searched PubMed and Google Scholar for single nucleotide polymorphisms (SNPs) involved in GDM predisposition in a sub-Saharan African population. We report on barriers that limit the implementation of AI that could assist with GDM screening and offer possible solutions. Results: In a Black South African cohort, the minor allele of the SNP rs4581569 existing in the PDX1 gene was significantly associated with GDM. We were not able to find any published literature on the implementation of AI to identify women at risk of GDM before second trimester of pregnancy in sub-Saharan Africa. Barriers to successful integration of AI into healthcare systems are broad but solutions exist. Conclusions: More research is needed to identify SNPs associated with GDM in sub-Saharan Africa. The implementation of AI and its applications in the field of healthcare in the sub-Saharan African region is a significant opportunity to positively impact early identification of GDM.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

MTNR1B gene variations and high pre-pregnancy BMI increase gestational diabetes mellitus risk in Chinese women

AIM

To investigate the association of melatonin receptor 1B (MTNR1B) gene variations and pre-pregnancy body mass index (BMI) with gestational diabetes mellitus (GDM).

MATERIALS AND METHOD

In this study, 1566 Chinese Han pregnant women were enrolled and multiple genetic models were used to evaluate the association between MTNR1B gene polymorphisms and the risk of GDM. The clinical value of pre-pregnancy BMI in predicting GDM was analyzed and evaluated using receiver operating characteristic (ROC) curves. Several methods of analysis were used to examine the impact of gene-gene and gene-BMI interactions on the incidence of GDM influence.

RESULTS

For the MTNR1B gene, rs1387153 (C > T), rs10830962 (C > G), rs4753426 (T > C), and rs10830963 (C > G) are all risk mutations associated with the susceptibility of GDM. The ROC curve analysis indicated that the BMI demonstrated an area under the curve (AUC) of 0.595. Alongside, the sensitivity and specificity stood at 0.676 and 0.474 respectively. The maximum Joden index was found to be 0.150, with a corresponding critical BMI value of 20.5691 kg/m2. Interaction analysis revealed that gene-gene and gene-BMI interactions had no significant effect on GDM occurrence.

CONCLUSION

MTNR1B genetic variations confers the risk to GDM in Chinese women. Furthermore, the high pre-pregnancy BMI (≥20.5691 kg/m2) significantly increases the risk of GDM in Chinese women.

Genome-wide analysis study of gestational diabetes mellitus and related pathogenic factors in a Chinese Han population

BACKGROUND

Gestational diabetes mellitus (GDM) affects the metabolism of both the mother and fetus during and after pregnancy. Genetic factors are important in the pathogenesis of GDM, and associations vary by ethnicity. However, related studies about the relationship between the susceptibility genes and glucose traits remain limited in China. This study aimed to identify genes associated with GDM susceptibility in Chinese Han women and validate those findings using clinical data during pregnancy and postpartum period.

METHODS

A genome-wide association study (GWAS) of 398 Chinese Han women (199 each with and without GDM) was conducted and associations between single nucleotide polymorphisms (SNPs) and glucose metabolism were identified by searching public databases. Relationships between filtered differential SNPs and glucose metabolism were verified using clinical data during pregnancy. The GDM group were followed up postpartum to evaluate the progression of glucose metabolism.

RESULTS

We identified five novel SNPs with genome-wide significant associations with GDM: rs62069863 in TRPV3 gene and rs2232016 in PRMT6 gene were positive correlated with 1 h plasma glucose (1hPG) and 2 h plasma glucose (2hPG), rs1112718 in HHEX/EXOC6 gene and rs10460009 in LPIN2 gene were positive associated with fasting plasma glucose, 1hPG and 2hPG, rs927316 in GLIS3 gene was negative correlated with 2hPG. Of the 166 GDM women followed up postpartum, rs62069863 in TRPV3 gene was positively associated with fasting insulin, homoeostasis model assessment of insulin resistance.

CONCLUSIONS

The variants of rs62069863 in TRPV3 gene, rs2232016 in PRMT6 gene, rs1112718 in HHEX/EXOC6 gene, rs927316 in GLIS3 gene, and rs10460009 in LPIN2 gene were newly-identified susceptibility loci for GDM in the Chinese Han population. TRPV3 was associated with worse insulin resistance postpartum.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trial Registry.

TRIAL REGISTRATION NUMBER

ChiCTR2100043762. Date of first registration: 28/02/2021.

The Role of the FGF19 Family in the Pathogenesis of Gestational Diabetes: A Narrative Review

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications. Understanding the pathogenesis and appropriate diagnosis of GDM enables the implementation of early interventions during pregnancy that reduce the risk of maternal and fetal complications. At the same time, it provides opportunities to prevent diabetes, metabolic syndrome, and cardiovascular diseases in women with GDM and their offspring in the future. Fibroblast growth factors (FGFs) represent a heterogeneous family of signaling proteins which play a vital role in cell proliferation and differentiation, repair of damaged tissues, wound healing, angiogenesis, and mitogenesis and also affect the regulation of carbohydrate, lipid, and hormone metabolism. Abnormalities in the signaling function of FGFs may lead to numerous pathological conditions, including metabolic diseases. The FGF19 subfamily, also known as atypical FGFs, which includes FGF19, FGF21, and FGF23, is essential in regulating metabolic homeostasis and acts as a hormone while entering the systemic circulation. Many studies have pointed to the involvement of the FGF19 subfamily in the pathogenesis of metabolic diseases, including GDM, although the results are inconclusive. FGF19 and FGF21 are thought to be associated with insulin resistance, an essential element in the pathogenesis of GDM. FGF21 may influence placental metabolism and thus contribute to fetal growth and metabolism regulation. The observed relationship between FGF21 and increased birth weight could suggest a potential role for FGF21 in predicting future metabolic abnormalities in children born to women with GDM. In this group of patients, different mechanisms may contribute to an increased risk of cardiovascular diseases in women in later life, and FGF23 appears to be their promising early predictor. This study aims to present a comprehensive review of the FGF19 subfamily, emphasizing its role in GDM and predicting its long-term metabolic consequences for mothers and their offspring.

Genetic contributions to risk of adverse pregnancy outcomes

Purpose of Review

Adverse pregnancy outcomes (APOs), including hypertensive disorders of pregnancy (HDP), low birthweight (LBW), and preterm birth (PTB), along with peripartum cardiomyopathy (PPCM) are associated with short- and long-term maternal and fetal cardiovascular risks. This review focuses on the genetic contributions to the risk of APOs and PPCM.

Recent Findings

The expansion of genome-wide association studies (GWAS) has led to better understanding of the biologic mechanisms underpinning APO, PPCM, and the predisposition to cardiovascular disease across the life course. Genetic loci known to be involved with the risk of hypertension (FTO, ZNF831) have been associated with the development of overall HDP and preeclampsia. Additionally, four loci significantly associated with type 2 diabetes have been associated with GDM (CDKAL1, MTNR1B, TCF7L2, CDK2NA-CDKN2B). Variants in loci known to affect genes coding for proteins involved in immune cell function and placental health (EBF1, EEFSEC, AGTR2, 2q13) have been implicated in the development of PTB and future cardiovascular risks for both the mother and the offspring. Genetic similarities in rare variants between PPCM and dilated cardiomyopathy have been described suggesting shared pathophysiologic origins as well as predisposition for future risk of heart failure, highlighting the need for the development PPCM genetic counseling guidelines.

Summary

Genetics may inform mechanisms, risk, and counseling for individuals after an APO or PPCM. Through recent advances in genetic techniques and analytic approaches, new insights into the underlying biologic mechanisms and genetic variants leading to these risks have been discovered.

Insulin requiring Gestational Diabetes: Risk factors and correlation with postpartum diabetes and prediabetes

Objective

A2 gestational diabetes mellitus (A2GDM) is a more severe form of GDM that requires additional medical intervention, such as insulin or oral antidiabetic drug (OAD). The present study explored the determinants of A2GDM and analyzed the associated risk of post-partum diabetes or prediabetes.

Methods

This retrospective study included 247 pregnant women, diagnosed with GDM and followed up until delivery at the Obstetric Medicine Clinic of King Abdulaziz University Hospital, Jeddah, Saudi Arabia, between January 2014 and January 2018. Women with personal history of diabetes or prediabetes were excluded. Collected data included patient's age, body mass index, personal history of thyroid dysfunction and GDM, HbA1c level at diagnosis, management of GDM (diet only, insulin, or OAD), and postpartum metabolic assessment.

Results

The prevalence of A2GDM was 29.6%, of which 21.5% were insulin-requiring and 8.1% were OAD-requiring cases. The risk of A2GDM was independently associated with a positive history of GDM (OR=3.19, 95% CI = 1.41-7.20) and HbA1c >7% (OR=8.66, 95%CI = 2.15- 34.94); the model explained 20% of the variance of A2GDM. The postpartum assessment showed that 10.1% have developed prediabetes, while no one developed overt diabetes. Postpartum prediabetes was independently predicted by age category ≥45 years (OR=39.94, 95%CI = 4.62-345.06), history of GDM (OR=0.18, 95%CI = 0.03 - 0.97), and A2GDM (OR=6.96, 95%CI = 1.91-25.42).

Conclusion

Approximately one-third of GDM patients in our institution require insulin or OAD for glycemic control and are at high risk of developing prediabetes postpartum. Adherence to and effectiveness of medical nutrition therapy should be further explored among GDM patients to improve their glycemic control and both maternal and fetal prognosis.

Genetics of diabetes

Diabetes mellitus is a complicated disease characterized by a complex interplay of genetic, epigenetic, and environmental variables. It is one of the world's fastest-growing diseases, with 783 million adults expected to be affected by 2045. Devastating macrovascular consequences (cerebrovascular disease, cardiovascular disease, and peripheral vascular disease) and microvascular complications (like retinopathy, nephropathy, and neuropathy) increase mortality, blindness, kidney failure, and overall quality of life in individuals with diabetes. Clinical risk factors and glycemic management alone cannot predict the development of vascular problems; multiple genetic investigations have revealed a clear hereditary component to both diabetes and its related complications. In the twenty-first century, technological advancements (genome-wide association studies, next-generation sequencing, and exome-sequencing) have led to the identification of genetic variants associated with diabetes, however, these variants can only explain a small proportion of the total heritability of the condition. In this review, we address some of the likely explanations for this "missing heritability", for diabetes such as the significance of uncommon variants, gene-environment interactions, and epigenetics. Current discoveries clinical value, management of diabetes, and future research directions are also discussed.

Integration of nutrigenomics, melatonin, serotonin and inflammatory cytokines in the pathophysiology of pregnancy-specific urinary incontinence in women with gestational diabetes mellitus

Gestational diabetes mellitus is an important public health problem and has been associated with the development of pregnancy-specific urinary incontinence. The interaction is related to hyperglycemia, and inflammatory and hormonal patterns, which favor functional alterations in different organs and systems. Several genes associated with human diseases have been identified and partially characterized. Most of these genes are known to cause monogenic diseases. However, about 3 % of diseases do not fit the monogenic theory due to the complex interactions between multiple genes and environmental factors, as in chronic metabolic diseases such as diabetes. The nutritional, immunological, and hormonal patterns associated with changes in maternal metabolism may influence and contribute to greater susceptibility to urinary tract disorders. However, early systematic reviews have not yielded consistent findings for these associations. This literature review summarizes important new findings from integrating nutrigenomics, hormones, and cytokines in women with Gestational diabetes mellitus and pregnancy-specific urinary incontinence. Changes in maternal metabolism due to hyperglycemia can generate an inflammatory environment with increased inflammatory cytokines. This environment modulated by inflammation can alter tryptophan uptake through food and thus influence the production of serotonin and melatonin. As these hormones seem to have protective effects against smooth muscle dysfunction and to restore the impaired contractility of the detrusor muscle, it is assumed that these changes may favor the onset of urinary incontinence specific to pregnancy.

Association of the CDKAL1 gene polymorphism with gestational diabetes mellitus in Chinese women

INTRODUCTION

To identify the association of the cyclin-dependent kinase 5 regulatory subunit associated protein 1-like 1 (CDKAL1) gene polymorphism with gestational diabetes mellitus (GDM) in the Chinese population.

RESEARCH DESIGN AND METHODS

This case-control study enrolled 835 pregnant women with GDM and 870 pregnant women without diabetes who underwent antenatal examination during 24 to 28 gestational weeks at the Maternal and Child Health Hospital of Hubei Province from January 15, 2018 to March 31, 2019. Trained nurses collected their clinical information and blood samples. CDKAL1 gene rs10440833, rs10946398, rs4712523, rs4712524, rs7754840, rs7756992 and rs9465871 loci were genotyped by Agena MassARRAY system. SPSS V.26.0 software and online SHesis were used to analyze the relationship between CDKAL1 gene polymorphism and GDM susceptibility.

RESULTS

After being adjusted for maternal age, prepregnancy body mass index (BMI), parity and family history of type 2 diabetes mellitus (T2DM), CDKAL1 gene rs10440833 (AA vs TT, OR=1.631, 95% CI 1.192 to 2.232), rs10946398 (CC vs AA, OR=1.400, 95% CI 1.028 to 1.905), rs4712523 (GG vs AA, OR=1.409, 95% CI 1.038 to 1.913), rs4712524 (GG vs AA, OR=1.418, 95% CI 1.043 to 1.929) and rs7754840 (CC vs GG, OR=1.407, 95% CI 1.036 to 1.911) polymorphisms were all associated with the increased risk of GDM. In addition, there was a powerful linkage disequilibrium (LD) among rs10946398, rs4712523, rs4712524 and rs7754840 (D'>0.900, r²>0.900). And there were significant differences in haplotype CGGC (OR=1.207, 95% CI 1.050 to 1.387) and AAAG (OR=0.829, 95% CI 0.721 o 0.952, p=0.008) between the GDM group and the control group.

CONCLUSIONS

rs10440833, rs10946398, rs4712523, rs4712524 and rs7754840 of CDKAL1 gene are associated with GDM susceptibility in central Chinese population.

Genetics and Epigenetics: Implications for the Life Course of Gestational Diabetes

Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course of affected women. Advances in genetics and epigenetics have not only provided new insight into the pathophysiology of GDM but have also provided new approaches to identify women at high risk for progression to postpartum cardiometabolic disease. GDM and type 2 diabetes share similarities in their pathophysiology, suggesting that they also share similarities in their genetic architecture. Candidate gene and genome-wide association studies have identified susceptibility genes that are shared between GDM and type 2 diabetes. Despite these similarities, a much greater effect size for MTNR1B in GDM compared to type 2 diabetes and association of HKDC1, which encodes a hexokinase, with GDM but not type 2 diabetes suggest some differences in the genetic architecture of GDM. Genetic risk scores have shown some efficacy in identifying women with a history of GDM who will progress to type 2 diabetes. The association of epigenetic changes, including DNA methylation and circulating microRNAs, with GDM has also been examined. Targeted and epigenome-wide approaches have been used to identify DNA methylation in circulating blood cells collected during early, mid-, and late pregnancy that is associated with GDM. DNA methylation in early pregnancy had some ability to identify women who progressed to GDM, while DNA methylation in blood collected at 26-30 weeks gestation improved upon the ability of clinical factors alone to identify women at risk for progression to abnormal glucose tolerance post-partum. Finally, circulating microRNAs and long non-coding RNAs that are present in early or mid-pregnancy and associated with GDM have been identified. MicroRNAs have also proven efficacious in predicting both the development of GDM as well as its long-term cardiometabolic complications. Studies performed to date have demonstrated the potential for genetic and epigenetic technologies to impact clinical care, although much remains to be done.

Distinct and shared genetic architectures of Gestational diabetes mellitus and Type 2 Diabetes Mellitus

Gestational diabetes mellitus (GDM) affects more than 16 million pregnancies annually worldwide and is related to an increased lifetime risk of Type 2 diabetes (T2D). The diseases are hypothesized to share a genetic predisposition, but there are few GWAS studies of GDM and none of them is sufficiently powered to assess whether any variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen Study and identified 13 GDM-associated loci including 8 novel loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into two distinct categories - one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis, and placental expression. These results pave the way for an improved biological understanding of GDM pathophysiology and its role in the development and course of T2D.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Lipolysis and gestational diabetes mellitus onset: a case-cohort genome-wide association study in Chinese

BACKGROUND

Genetic knowledge of gestational diabetes mellitus (GDM) in Chinese women is quite limited. This study aimed to identify the risk factors and mechanism of GDM at the genetic level in a Chinese population.

METHODS

We conducted a genome-wide association study (GWAS) based on single nucleotide polymorphism (SNP) array genotyping (ASA-CHIA Bead chip, Illumina) and a case-cohort study design. Variants including SNPs, copy number variants (CNVs), and insertions-deletions (InDels) were called from genotyping data. A total of 2232 pregnant women were enrolled in their first/second trimester between February 2018 and December 2020 from Anqing Municipal Hospital in Anhui Province, China. The GWAS included 193 GDM patients and 819 subjects without a diabetes diagnosis, and risk ratios (RRs) and their 95% confidence intervals (CIs) were estimated by a regression-based method conditional on the population structure. The calling and quality control of genotyping data were performed following published guidelines. CNVs were merged into CNV regions (CNVR) to simplify analyses. To interpret the GWAS results, gene mapping and overexpression analyses (ORAs) were further performed to prioritize the candidate genes and related biological mechanisms.

RESULTS

We identified 14 CNVRs (false discovery rate corrected P values < 0.05) and two suggestively significant SNPs (P value < 0.00001) associated with GDM, and a total of 19 candidate genes were mapped. Ten genes were significantly enriched in gene sets related to lipase (triglyceride lipase and lipoprotein lipase) activity (LIPF, LIPK, LIPN, and LIPJ genes), oxidoreductase activity (TPH1 and TPH2 genes), and cellular components beta-catenin destruction complex (APC and GSK3B genes), Wnt signalosome (APC and GSK3B genes), and lateral element in the Gene Ontology resource (BRCA1 and SYCP2 genes) by two ORA methods (adjusted P values < 0.05).

CONCLUSIONS

Genes related to lipolysis, redox reaction, and proliferation of islet β-cells are associated with GDM in Chinese women. Energy metabolism, particularly lipolysis, may play an important role in GDM aetiology and pathology, which needs further molecular studies to verify.

Genetic variants of the GLP-1R gene affect the susceptibility and glucose metabolism of gestational diabetes mellitus: a two-center nested case‒control study

BACKGROUND

Gestational diabetes mellitus (GDM) is the most common complication during pregnancy, occurring under the combined action of environmental and genetic factors. Genetic variants of glucagon-like peptide-1 receptor (GLP-1R) have been reported to affect insulin secretion and susceptibility to type 2 diabetes. This study aimed to explore the role of GLP-1R polymorphisms in GDM and glucose metabolism.

METHODS

A two-center nested case‒control study was designed, including 200 pregnant women with GDM and 200 pregnant women without GDM genotyped for five tag SNPs of GLP-1R using Sanger sequencing. Logistic regression was used to evaluate the relationship between GLP-1R polymorphisms and GDM risk. Glucose and insulin concentrations were measured based upon the 75 g oral glucose tolerance test (OGTT). Beta cell function of different genotypes was estimated with the 60 min insulinogenic index (IGI₆₀) and OGTT-derived disposition index (DI).

RESULTS

Mutant genotype AG + GG of tag SNP rs6458093 nominally increased GDM risk (p = 0.049), especially among subjects younger than 35 years (p = 0.024) and with BMI no less than 24 (p = 0.041), after adjusting for confounders. Meanwhile, compared with subjects with wild genotype AA, subjects with genotype AG + GG of rs6458093 also showed nominally significantly lower IGI₆₀ (p = 0.032) and DI (p = 0.029), as well as significantly higher 75 g OGTT-based 1 h glucose load plasma glucose levels (p = 0.045). Moreover, the mutant heterozygous genotype GA of tag SNP rs3765467 nominally decreased GDM risk among subjects older than 35 years (p = 0.037) but showed no association with insulin secretion and glucose homeostasis.

CONCLUSIONS

Tag SNP rs6458093 of GLP-1R was nominally associated with increased GDM risk and affected beta cell function and postprandial glucose metabolism, while tag SNP rs3765467 of GLP-1R was nominally associated with decreased GDM risk, providing evidence for molecular markers and etiological study of GDM.

Construction of a novel miRNA regulatory network and identification of target genes in gestational diabetes mellitus by integrated analysis

Backgrounds: Given the roles of microRNA (miRNA) in human diseases and the high incidence of gestational diabetes mellitus (GDM), the aim of the study was to examine miRNA signatures and crucial pathways, as well as possible biomarkers for GDM diagnosis. Methods: We conducted a two-stage study to explore functional miRNA and those target genes. Twelve participants (6 GDM and 6 non-GDM) were first enrolled and performed RNA sequencing analysis. The overlapped candidate genes were further screened in combination with differentially expressed genes (DEGs) of GEO datasets (GSE87295, GSE49524 and GSE19649) and potential target genes of DEMs. Candidate genes, critical pathways, small molecular compounds and regulatory networks were identified using bioinformatic analysis. The potential candidate genes were then investigated using the GEO dataset (GSE103552) of 19 participants in the validation stage (11 GDM and 8 non-GDM women). Results: Briefly, blood samples were sequenced interrogating 50 miRNAs, including 20 upregulated and 30 downregulated differentially expressed microRNAs(DEMs) in our internal screening dataset. After screening GEO databases, 123 upregulated and 70 downregulated genes were overlapped through DEGs of GEO datasets and miRNA-target genes. MiR-29b-1-5p-TGFB2, miR-142-3p-TGFB2, miR-9-5p-FBN2, miR-212-5p-FBN2, miR-542-3p-FBN1, miR-9-5p-FBN1, miR-508-3p-FBN1, miR-493-5p-THBS1, miR-29b-3p-COL4A1, miR-432-5p-COL5A2, miR-9-5p-TGFBI, miR-486-3p-SLC7A5 and miR-6515-5p-SLC1A5 were revealed as thirteen possible regulating pathways by integrative analysis. Conclusion: Overall, thirteen candidate miRNA-target gene regulatory pathways representing potentially novel biomarkers of GDM diseases were revealed. Ten chemicals were identified as putative therapeutic agents for GDM. This study examined a series of DEGs that are associated with epigenetic alternations of miRNA through an integrated approach and gained insight into biological pathways in GDM. Precise diagnosis and therapeutic targets of GDM would be further explored through putative genes in the future.

Aggregation of Genome-Wide Association Data from FinnGen and UK Biobank Replicates Multiple Risk Loci for Pregnancy Complications

Complications endangering mother or fetus affect around one in seven pregnant women. Investigation of the genetic susceptibility to such diseases is of high importance for better understanding of the disease biology as well as for prediction of individual risk. In this study, we collected and analyzed GWAS summary statistics from the FinnGen cohort and UK Biobank for 24 pregnancy complications. In FinnGen, we identified 11 loci associated with pregnancy hypertension, excessive vomiting, and gestational diabetes. When UK Biobank and FinnGen data were combined, we discovered six loci reaching genome-wide significance in the meta-analysis. These include rs35954793 in FGF5 (p=6.1×10-9), rs10882398 in PLCE1 (p=8.9×10-9), and rs167479 in RGL3 (p=5.2×10-9) for pregnancy hypertension, rs10830963 in MTNR1B (p=4.5×10-41) and rs36090025 in TCF7L2 (p=3.4×10-15) for gestational diabetes, and rs2963457 in the EBF1 locus (p=6.5×10-9) for preterm birth. In addition to the identified genome-wide associations, we also replicated 14 out of 40 previously reported GWAS markers for pregnancy complications, including four more preeclampsia-related variants. Finally, annotation of the GWAS results identified a causal relationship between gene expression in the cervix and gestational hypertension, as well as both known and previously uncharacterized genetic correlations between pregnancy complications and other traits. These results suggest new prospects for research into the etiology and pathogenesis of pregnancy complications, as well as early risk prediction for these disorders.

Insight into genetic, biological, and environmental determinants of sexual-dimorphism in type 2 diabetes and glucose-related traits

There is growing evidence that sex and gender differences play an important role in risk and pathophysiology of type 2 diabetes (T2D). Men develop T2D earlier than women, even though there is more obesity in young women than men. This difference in T2D prevalence is attenuated after the menopause. However, not all women are equally protected against T2D before the menopause, and gestational diabetes represents an important risk factor for future T2D. Biological mechanisms underlying sex and gender differences on T2D physiopathology are not yet fully understood. Sex hormones affect behavior and biological changes, and can have implications on lifestyle; thus, both sex-specific environmental and biological risk factors interact within a complex network to explain the differences in T2D risk and physiopathology in men and women. In addition, lifetime hormone fluctuations and body changes due to reproductive factors are generally more dramatic in women than men (ovarian cycle, pregnancy, and menopause). Progress in genetic studies and rodent models have significantly advanced our understanding of the biological pathways involved in the physiopathology of T2D. However, evidence of the sex-specific effects on genetic factors involved in T2D is still limited, and this gap of knowledge is even more important when investigating sex-specific differences during the life course. In this narrative review, we will focus on the current state of knowledge on the sex-specific effects of genetic factors associated with T2D over a lifetime, as well as the biological effects of these different hormonal stages on T2D risk. We will also discuss how biological insights from rodent models complement the genetic insights into the sex-dimorphism effects on T2D. Finally, we will suggest future directions to cover the knowledge gaps.

The genetic risk of gestational diabetes in South Asian women

South Asian women are at increased risk of developing gestational diabetes mellitus (GDM). Few studies have investigated the genetic contributions to GDM risk. We investigated the association of a type 2 diabetes (T2D) polygenic risk score (PRS), on its own, and with GDM risk factors, on GDM-related traits using data from two birth cohorts in which South Asian women were enrolled during pregnancy. 837 and 4372 pregnant South Asian women from the SouTh Asian BiRth CohorT (START) and Born in Bradford (BiB) cohort studies underwent a 75-g glucose tolerance test. PRSs were derived using genome-wide association study results from an independent multi-ethnic study (~18% South Asians). Associations with fasting plasma glucose (FPG); 2 hr post-load glucose (2hG); area under the curve glucose; and GDM were tested using linear and logistic regressions. The population attributable fraction (PAF) of the PRS was calculated. Every 1 SD increase in the PRS was associated with a 0.085 mmol/L increase in FPG ([95% confidence interval, CI=0.07-0.10], p=2.85×10^-20); 0.21 mmol/L increase in 2hG ([95% CI=0.16-0.26], p=5.49×10^-16); and a 45% increase in the risk of GDM ([95% CI=32-60%], p=2.27×10^-14), independent of parental history of diabetes and other GDM risk factors. PRS tertile 3 accounted for 12.5% of the population's GDM alone, and 21.7% when combined with family history. A few weak PRS and GDM risk factors interactions modulating FPG and GDM were observed. Taken together, these results show that a T2D PRS and family history of diabetes are strongly and independently associated with multiple GDM-related traits in women of South Asian descent, an effect that could be modulated by other environmental factors.

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.

Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

A Clinical Update on Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) traditionally refers to abnormal glucose tolerance with onset or first recognition during pregnancy. GDM has long been associated with obstetric and neonatal complications primarily relating to higher infant birthweight and is increasingly recognized as a risk factor for future maternal and offspring cardiometabolic disease. The prevalence of GDM continues to rise internationally due to epidemiological factors including the increase in background rates of obesity in women of reproductive age and rising maternal age and the implementation of the revised International Association of the Diabetes and Pregnancy Study Groups' criteria and diagnostic procedures for GDM. The current lack of international consensus for the diagnosis of GDM reflects its complex historical evolution and pragmatic antenatal resource considerations given GDM is now 1 of the most common complications of pregnancy. Regardless, the contemporary clinical approach to GDM should be informed not only by its short-term complications but also by its longer term prognosis. Recent data demonstrate the effect of early in utero exposure to maternal hyperglycemia, with evidence for fetal overgrowth present prior to the traditional diagnosis of GDM from 24 weeks' gestation, as well as the durable adverse impact of maternal hyperglycemia on child and adolescent metabolism. The major contribution of GDM to the global epidemic of intergenerational cardiometabolic disease highlights the importance of identifying GDM as an early risk factor for type 2 diabetes and cardiovascular disease, broadening the prevailing clinical approach to address longer term maternal and offspring complications following a diagnosis of GDM.

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.

Common single-nucleotide polymorphisms combined with a genetic risk score provide new insights regarding the etiology of gestational diabetes mellitus

AIMS

Few studies have constructed a genetic risk score (GRS) to predict the risk of gestaional diabetes mellitus (GDM). We tested the hypothesis that single-nucleotide polymorphisms (SNPs) confirmed for diabetes and obesity and the GRS are associated with GDM.

METHODS

We conducted a case-control study comprising 971 GDM cases and 1682 controls from the University of Hong Kong Shenzhen Hospital. A total of 1448 SNPs reported with type 2 diabetes (T2D), type 1 diabetes (T1D), and obesity were selected and the GRS based on SNPs associated with GDM was created.

RESULTS

We confirmed that rs10830963 (OR = 1.41,95% CI = 1.25, 1.59) in MTNR1B and rs2206734 (OR = 1.38, 95% CI = 1.22, 1.55) in CDKAL1 were strongly associated with the risk of GDM. Compared with participants with GRS based on T2D SNPs in the low tertile, the ORs of GDM across increasing GRS tertiles were 1.63 (95% CI 1.29, 2.06) and 2.72 (95% CI 2.18, 3.38) in the middle and high tertile, respectively. The positive associations between the GRS and the risk of GDM were also observed in GRS based on obesity/waist-to-hip ratio (WHR)/body mass index (BMI) SNPs. The resulting GRS for each allele increase was significantly associated with higher glycemic indices and lower HOMA-B values for GRS based on T2D SNPs, but not for GRS based on T1D SNPs and GRS based on obesity/WHR/BMI SNPs.

CONCLUSION

These findings indicate that GDM may share a common genetic background with T2D and obesity and that SNPs associated with insulin secretion defects have a vital role in the development of GDM.

Association of vitamin D receptor gene rs739837 polymorphism with type 2 diabetes and gestational diabetes mellitus susceptibility: a systematic review and meta-analysis

Background

Increasing evidence shows that genetic variants of genes in the diabetes mellitus (DM) metabolic pathway, such as the vitamin D receptor (VDR) gene rs739837 polymorphism, increase the risk of DM susceptibility. However, the findings have been inconsistent. The present study was performed to evaluate the association of VDR gene rs739837 and type 2 diabetes (T2DM) or gestational diabetes mellitus (GDM) risk.

Methods

A comprehensive meta-analysis and a subgroup analysis were conducted to assess the association between VDR rs739837 and T2DM or GDM among five genetic models (dominant, recessive, homozygote heterozygote, and allele models) using a fixed or random model.

Results

The meta-analysis included 9 studies. In the overall analysis, the results showed that VDR rs739837 was associated with an increased risk of T2DM or GDM in the allele model (T vs. G: OR = 1.088; 95% CI: 1.018–1.163; P = 0.012) and dominant model (TT + GT vs. GG: OR = 1.095; 95% CI: 1.001–1.197; P = 0.047). In the subgroup analysis, VDR rs739837 was also associated with an increased risk of T2DM in the allele model (T vs. G: OR = 1.159; 95% CI: 1.055–1.273; P = 0.002) and dominant model (TT + GT vs. GG: OR = 1.198; 95% CI: 1.048–1.370; P = 0.008). However, VDR rs739837 was not associated with GDM.

Conclusions

Significant associations were found between the VDR rs739837 polymorphism and T2DM susceptibility, but not with GDM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-022-00688-x.

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.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Interaction between rs10830962 polymorphism in MTNR1B and lifestyle intervention on maternal and neonatal outcomes: secondary analyses of the DALI lifestyle randomized controlled trial

BACKGROUND

Interactions between polymorphisms of the melatonin receptor 1B (MTNR1B) gene and lifestyle intervention for gestational diabetes have been described. Whether these are specific for physical activity or the healthy eating intervention is unknown.

OBJECTIVES

The aim was to assess the interaction between MTNR1B rs10830962 and rs10830963 polymorphisms and lifestyle interventions during pregnancy.

METHODS

Women with a BMI (in kg/m2) of ≥29 (n = 436) received counseling on healthy eating (HE), physical activity (PA), or both. The control group received usual care. This secondary analysis had a factorial design with comparison of HE compared with no HE and PA compared with no PA. Maternal outcomes at 24-28 wk were gestational weight gain (GWG), maternal fasting glucose, insulin, insulin resistance (HOMA-IR), disposition index, and development of GDM. Neonatal outcomes were cord blood leptin and C-peptide and estimated neonatal fat percentage. The interaction between receiving either the HE or PA intervention and genotypes of both rs10830962 and rs10830963 was assessed using multilevel regression analysis.

RESULTS

GDM risk was increased in women homozygous for the G allele of rs10830962 (OR: 2.60; 95% CI: 1.34, 5.06) or rs10830963 (OR: 2.83; 95% CI: 1.24, 6.47). Significant interactions between rs10830962 and interventions were found: in women homozygous for the G allele but not in the other genotypes, the PA intervention reduced maternal fasting insulin (β: -0.16; 95% CI: -0.33, 0.02; P = 0.08) and HOMA-IR (β: -0.17; 95% CI: -0.35, 0.01; P = 0.06), and reduced cord blood leptin (β: -0.84; 95% CI: -1.42, -0.25; P = 0.01) and C-peptide (β: -0.62; 95% CI: -1.07, -0.17; P = 0.01). In heterozygous women, the HE intervention had no effect, whereas in women homozygous for the C allele, HE intervention reduced GWG (β: -1.6 kg; 95% CI: -2.4, -0.8 kg). No interactions were found.

CONCLUSIONS

In women homozygous for the risk allele of MTNR1B rs10830962, GDM risk was increased and PA intervention might be more beneficial than HE intervention for reducing maternal insulin resistance, cord blood C-peptide, and cord blood leptin.

CDKAL1 gene rs7756992 A/G and rs7754840 G/C polymorphisms are associated with gestational diabetes mellitus in a sample of Bangladeshi population: implication for future T2DM prophylaxis

BACKGROUND

Association of single nucleotide polymorphisms (SNP) rs7756992 A/G and rs7754840 G/C of cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 (CDKAL1) gene with the susceptibility of gestational diabetes mellitus (GDM) has been studied in a group of Bangladeshi women.

METHODS

In this case-control study, 212 GDM patients and 256 control subjects were genotyped for rs7756992 and rs7754840 by PCR-RFLP and TaqMan™ allelic discrimination assay method respectively. Genotyping results were confirmed by DNA sequencing and replicated TaqMan™ assay. The odds ratios and their 95% confidence interval were calculated by logistic regression to determine the associations between genotypes and GDM.

RESULTS

The genotype frequencies of rs7756992-AA/AG/GG in the GDM group and the control group were 37%/48%, 53%/45%, 10%/7% and those of rs7754840-CC/CG/GG were 51%/55%, 40.1%/39.8%, 9%/5% respectively. Under dominant and log additive models rs7756992 was revealed significantly associated with GDM after being adjusted for family history of diabetes (FHD) and gravidity. Conversely, rs7754840 was significantly associated (P = 0.047) with GDM only under the recessive model after the same adjustment. The risk allele frequency of both SNPs was higher in the GDM group but significantly (P = 0.029) increased prevalence was observed in the rs7756992 G allele. When positive FHD and risk alleles of these SNPs were synergistically present in any pregnant woman, the chance of developing GDM was augmented by many folds. The codominant model revealed 2.5 and 2.1 folds increase in odds by AG (rs7756992) and GC (rs7754840) genotypes and 3.7 and 4.5 folds by GG (rs7756992) and CC (rs7754840) genotypes respectively. A significant 2.7 folds (P = 0.038) increase in odds of GDM resulted from the interaction of rs7756992 and family history of diabetes under the dominant model. The cumulative effect of multigravidity and risk alleles of these SNPs increased the odds of GDM more than 1.5 folds in different genotypes.

CONCLUSION

This study not only revealed a significant association between rs7756992 and rs7754840 with GDM but also provided the possibility as potential markers for foretelling about GDM and type 2 diabetes mellitus in Bangladeshi women.

An early prediction model for gestational diabetes mellitus based on genetic variants and clinical characteristics in China

OBJECTIVES

To evaluate the influence of genetic variants and clinical characteristics on the risk of gestational diabetes mellitus (GDM) and to construct and verify a prediction model of GDM in early pregnancy.

METHODS

Four hundred seventy five women with GDM and 487 women without, as a control, were included to construct the prediction model of GDM in early pregnancy. Both groups had complete genotyping results and clinical data. They were randomly divided into a trial cohort (70%) and a test cohort (30%). Then, the model validation cohort, including 985 pregnant women, was used for the external validation of the GDM early pregnancy prediction model.

RESULTS

We found maternal age, gravidity, parity, BMI and family history of diabetes were significantly associated with GDM (OR > 1; P < 0.001), and assisted reproduction was a critical risk factor for GDM (OR = 1.553, P = 0.055). MTNR1B rs10830963, C2CD4A/B rs1436953 and rs7172432, CMIP rs16955379 were significantly correlated with the incidence of GDM (AOR > 1, P < 0.05). Therefore, these four genetic susceptible single nucleotide polymorphisms (SNPs) and six clinical characteristics were included in the construction of the GDM early pregnancy prediction model. In the trial cohort, a predictive model of GDM in early pregnancy was constructed, in which genetic risk score was independently associated with GDM (AOR = 2.061, P < 0.001) and was the most effective predictor with the exception of family history of diabetes. The ROC-AUC of the prediction model was 0.727 (95% CI 0.690-0.765), and the sensitivity and specificity were 69.9% and 64.0%, respectively. The predictive power was also verified in the test cohort and the validation cohort.

CONCLUSIONS

Based on the genetic variants and clinical characteristics, this study developed and verified the early pregnancy prediction model of GDM. This model can help screen out the population at high-risk for GDM in early pregnancy, and lifestyle interventions can be performed for them in a timely manner in early pregnancy.

Melatonin Receptor 1B Genetic Variants on Susceptibility to Gestational Diabetes Mellitus: A Hospital-Based Case-Control Study in Wuhan, Central China

PURPOSE

The aim of the study was to find out the associations of Melatonin receptor 1B (MTNR1B) genetic variants with gestational diabetes mellitus (GDM) in Wuhan of central China.

PATIENTS AND METHODS

A hospital-based case-control study that included 1679 women was carried out to explore the associations of MTNR1B single nucleotide polymorphisms (SNPs) with GDM risk, which were analyzed through logistic regression analysis by adjusting age, pre-pregnancy BMI and family history of diabetes. Multifactor dimensionality reduction was applied to determine gene-gene interactions between SNPs.

RESULTS

MTNR1B SNPs rs10830962, rs10830963, rs1387153, rs7936247 and rs4753426 were significantly associated with GDM risk (P<0.05). The rs10830962/G, rs10830963/G, rs1387153/T, and rs7936247/T were risk variants, whereas rs4753426/T was protective variant for GDM development. Fasting plasma glucose (FPG) and 1h-plasma glucose (PG) were significantly different among genotypes at rs10830962 and rs10830963, whereas 2h-PG levels were not. Gene-gene interactions were not found among the five SNPs on GDM risk.

CONCLUSION

MTNR1B genetic variants have significant associations but no gene-gene interactions with GDM risk in central Chinese population. Furthermore, MTNR1B SNPs have significant relationships with glycemic traits.

Membrane Melatonin Receptors Activated Cell Signaling in Physiology and Disease

The pineal hormone melatonin has attracted great scientific interest since its discovery in 1958. Despite the enormous number of basic and clinical studies the exact role of melatonin in respect to human physiology remains elusive. In humans, two high-affinity receptors for melatonin, MT1 and MT2, belonging to the family of G protein-coupled receptors (GPCRs) have been cloned and identified. The two receptor types activate Gi proteins and MT2 couples additionally to Gq proteins to modulate intracellular events. The individual effects of MT1 and MT2 receptor activation in a variety of cells are complemented by their ability to form homo- and heterodimers, the functional relevance of which is yet to be confirmed. Recently, several melatonin receptor genetic polymorphisms were discovered and implicated in pathology-for instance in type 2 diabetes, autoimmune disease, and cancer. The circadian patterns of melatonin secretion, its pleiotropic effects depending on cell type and condition, and the already demonstrated cross-talks of melatonin receptors with other signal transduction pathways further contribute to the perplexity of research on the role of the pineal hormone in humans. In this review we try to summarize the current knowledge on the membrane melatonin receptor activated cell signaling in physiology and pathology and their relevance to certain disease conditions including cancer.

Steroids, steroid associated substances and gestational diabetes mellitus

As gestational diabetes mellitus (GDM) is both a frequent and serious complication, steroid levels in pregnancy are extremely elevated and their role in pregnancy is crucial, this review focuses on the role of steroids and related substances in the GDM pathophysiology. Low SHBG levels are associated with insulin resistance and hyperinsulinemia, while also predicting a predisposition to GDM. Other relevant agents are placental hormones such as kisspeptin and CRH, playing also an important role beyond pregnancy, but which are synthesized here in smaller amounts in the hypothalamus. These hormones affect both the course of pregnancy as well as the synthesis of pregnancy steroids and may also be involved in the GDM pathophysiology. Steroids, whose biosynthesis is mainly provided by the fetal adrenal glands, placenta, maternal adrenal glands, and both maternal and fetal livers, are also synthesized in limited amounts directly in the pancreas and may influence the development of GDM. These substances involve the sulfated Δ5 steroids primarily acting via modulating different ion channels and influencing the development of GDM in different directions, mostly diabetogenic progesterone and predominantly anti-diabetic estradiol acting both in genomic and non-genomic way, androgens associated with IR and hyperinsulinemia, neuroactive steroids affecting the pituitary functioning, and cortisol whose production is stimulated by CRH but which suppresses its pro-inflammatory effects. Due to the complex actions of steroids, studies assessing their predominant effect and studies assessing their predictive values for estimating predisposition to GDM are needed.

Mechanisms of Melatonin in Obesity: A Review

Obesity and its complications have become a prominent global public health problem that severely threatens human health. Melatonin, originally known as an effective antioxidant, is an endogenous hormone found throughout the body that serves various physiological functions. In recent decades, increasing attention has been paid to its unique function in regulating energy metabolism, especially in glucose and lipid metabolism. Accumulating evidence has established the relationship between melatonin and obesity; nevertheless, not all preclinical and clinical evidence indicates the anti-obesity effect of melatonin, which makes it remain to conclude the clinical effect of melatonin in the fight against obesity. In this review, we have summarized the current knowledge of melatonin in regulating obesity-related symptoms, with emphasis on its underlying mechanisms. The role of melatonin in regulating the lipid profile, adipose tissue, oxidative stress, and inflammation, as well as the interactions of melatonin with the circadian rhythm, gut microbiota, sleep disorder, as well as the α7nAChR, the opioidergic system, and exosomes, make melatonin a promising agent to open new avenues in the intervention of obesity.

Genetic risk factors associated with gestational diabetes in a multi-ethnic population

AIMS

Genome-wide association studies have shown an increased risk of type-2-diabetes (T2DM) in patients who carry single nucleotide polymorphisms in several genes. We investigated whether the same gene loci confer a risk for gestational diabetes mellitus (GDM) in women from Hawaii, and in particular, Pacific Islander and Filipino populations.

METHODS

Blood was collected from 291 women with GDM and 734 matched non-diabetic controls (Pacific Islanders: 71 GDM, 197 non-diabetic controls; Filipinos: 162 GDM, 395 controls; Japanese: 58 GDM, 142 controls). Maternal DNA was used to genotype and show allele frequencies of 25 different SNPs mapped to 18 different loci.

RESULTS

After adjusting for age, BMI, parity and gravidity by multivariable logistic regression, several SNPs showed significant associations with GDM and were ethnicity specific. In particular, SNPs rs1113132 (EXT2), rs1111875 (HHEX), rs2237892 (KCNQ1), rs2237895 (KCNQ1), rs10830963 (MTNR1B) and rs13266634 (SLC30A8) showed significant associations with GDM in Filipinos. For Japanese, SNPs rs4402960 (IGFBP2) and rs2237892 (KCNQ1) were significantly associated with GDM. For Pacific Islanders, SNPs rs10830963 (MTNR1B) and rs13266634 (SLC30A8) showed significant associations with GDM. Individually, none of the SNPs showed a consistent association with GDM across all three investigated ethnicities.

CONCLUSION

Several SNPs associated with T2DM are found to confer increased risk for GDM in a multiethnic cohort in Hawaii.

The Association of Gene Variants in the Vitamin D Metabolic Pathway and Its Interaction with Vitamin D on Gestational Diabetes Mellitus: A Prospective Cohort Study

The present prospective study included 2156 women and investigated the effect of gene variants in the vitamin D (VitD) metabolic and glucose pathways and their interaction with VitD levels during pregnancy on gestational diabetes mellitus (GDM). Plasma 25(OH)D concentrations were measured at the first and second trimesters. GDM subtype 1 was defined as those with isolated elevated fasting plasma glucose; GDM subtype 2 were those with isolated elevated postprandial glucose at 1 h and/or 2 h; and GDM subtype 3 were those with both elevated fasting plasma glucose and postprandial glucose. Six Gc isoforms were categorized based on two GC gene variants rs4588 and rs7041, including 1s/1s, 1s/2, 1s/1f, 2/2, 1f/2 and 1f/1f. VDR-rs10783219 and MTNR1B-rs10830962 were associated with increased risks of GDM and GDM subtype 2; interactions between each other as well as with CDKAL1-rs7754840 were observed (P_interaction < 0.05). Compared with the 1f/1f isoform, the risk of GDM subtype 2 among women with 1f/2, 2/2, 1s/1f, 1s/2 and 1s/1s isoforms and with prepregnancy body mass index ≥24 kg/m² increased by 5.11, 10.01, 10, 14.23, 19.45 times, respectively. Gene variants in VitD pathway interacts with VitD deficiency at the first trimester on the risk of GDM and GDM subtype 2.