Pathophysiological Role of Genetic Factors Associated With Gestational Diabetes Mellitus

Polymorphisms Involved in Insulin Resistance and Metabolic Inflammation: Influence of Nutrients and Dietary Interventions

Insulin resistance (IR) is a metabolic disorder characterized by an impaired response to insulin. This condition is associated with excess adiposity and metabolic inflammation, contributing to an increased risk for related chronic diseases. Single-nucleotide polymorphisms (SNPs) can affect genes related to metabolic pathways which are related to IR and the individual response to nutrients and dietary patterns, affecting metabolic inflammation and insulin sensitivity. This narrative review explores the current evidence on interactions between genetic variants and dietary factors, specifically their effects in modulating IR and metabolic inflammation. A comprehensive search of the literature was conducted in PubMed, Google Scholar, and Web of Science, and a total of 95 articles were reviewed. The key findings reveal that SNPs in the TCF7L2, ADIPOQ, and TNF genes significantly influence metabolic responses and modulate the effects of the Mediterranean diet on biomarkers of inflammation and IR. Genotype-dependent variations in IR and inflammation biomarkers were observed in the response to different diets for SNPs in the TCF7L2, ADIPOQ, and TNF genes. Additionally, polygenic risk scores (PRSs) can also predict the response to the intake of nutrients and specific diets, and offer a promising tool for assessing genetic predisposition to IR. This review underscores the pivotal role of an individual's genetic background in the effects of their nutrient intake and in the responses to dietetic interventions, thereby laying the foundation for personalized and effective nutritional strategies tailored to each individual's necessity in mitigating IR and its associated risk factors for chronic diseases.

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

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

A risk prediction model of gestational diabetes mellitus based on traditional and genetic factors

BACKGROUND

Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication during pregnancy. We aimed to evaluate a risk prediction model of GDM based on traditional and genetic factors.

METHODS

A total of 2744 eligible pregnant women were included. Face-to-face questionnaire surveys were conducted to gather general data. Serum test results were collected from the laboratory information system. Independent risk factors for GDM were identified using univariate and multivariate logistic regression analyses. A GDM risk prediction model was constructed and evaluated with the Hosmer-Lemeshow goodness-of-fit test, goodness-of-fit calibration plot, receiver operating characteristic curve and area under the curve.

RESULTS

Among traditional factors, age ≥30 years, family history, GDM history, impaired glucose tolerance history, systolic blood pressure ≥116.22 mmHg, diastolic blood pressure ≥74.52 mmHg, fasting plasma glucose ≥5.0 mmol/L, 1-hour postprandial blood glucose ≥8.8 mmol/L, 2-h postprandial blood glucose ≥7.9 mmol/L, total cholesterol ≥4.50 mmol/L, low-density lipoprotein ≥2.09 mmol/L and insulin ≥11.5 mIU/L were independent risk factors for GDM. Among genetic factors, 11 single nucleotide polymorphisms (SNPs) (rs2779116, rs5215, rs11605924, rs7072268, rs7172432, rs10811661, rs2191349, rs10830963, rs174550, rs13266634 and rs11071657) were identified as potential predictors of the risk of postpartum DM among women with GDM history, collectively accounting for 3.6% of the genetic risk.

CONCLUSIONS

Both genetic and traditional factors contribute to the risk of GDM in women, operating through diverse mechanisms. Strengthening the risk prediction of SNPs for postpartum DM among women with GDM history is crucial for maternal and child health protection.

Association between genetic polymorphisms and gestational diabetes mellitus susceptibility in a Chinese population

Background

Although the association between HHEX, IGF2BP2, and FTO polymorphisms and the risk of GDM has been investigated in several studies, the findings have been inconsistent across different populations. The study aimed to investigate the association between genetic polymorphisms and GDM risk in a Chinese population.

Methods

502 control volunteers and 500 GDM patients were enrolled. IGF2BP2 rs11705701 and rs4402960, FTO rs9939609, and HHEX rs1111875 and rs5015480 were all genotyped using the SNPscan™ genotyping assay. The independent sample t-test, logistic regression, and chi-square test were used to assess the variations in genotype and allele and their relationships with the risk of GDM. The blood glucose level, gestational week of delivery, and newborn weight were compared using a one-way ANOVA.

Results

After adjusting for confounding factors, the results show that the rs1111875 heterozygous (OR=1.370; 95% CI: 1.040-1.805; P = 0.025) and overdominant (OR=1.373; 95% CI: 1.049-1.796; P = 0. 021) models are significantly associated with an increased risk of GDM, especially for the age ≥ 30 years group: heterozygote (OR=1.646; 95% CI: 1.118-2.423; P=0.012) and overdominant (OR=1.553; 95% CI: 1.064-2.266; P = 0.022) models. In the age ≥ 30 years, the rs5015480 overdominant model (OR=1.595; 95% CI: 1.034-2.459; P = 0.035) and the rs9939609 heterozygote model (OR=1.609; 95% CI: 1.016-2.550; P=0.043), allele (OR=1. 504; 95% CI: 1.006-2.248; P = 0.047), dominant model (OR=1.604; 95% CI: 1.026-2.505; P = 0.038), and overdominant model (OR=1.593; 95% CI: 1.007-2.520; P = 0.047) were associated with a significantly increased risk of GDM; Additionally, people with the TC genotype of rs1111875 had a substantially higher 1-hour blood glucose level than TT genotype (P < 0.05). The results of the meta-analysis showed that the A allele of rs11705701 was associated with an increased risk of diabetes mellitus (P < 0.05).

Conclusion

The study indicates that the TC genotype of rs1111875 is linked to a higher risk of GDM, particularly in women aged 30 years or older. Additionally, rs5015480 and rs9939609 were significantly associated with GDM in the same age group. These SNPs may therefore be more closely linked to GDM in older mothers.

SHBG and Insulin resistance - Nexus revisited

Sex hormone binding globulin (SHBG) is a liver-synthesized glycoprotein. Low SHBG levels are associated with insulin resistance (IR). Specific single nucleotide polymorphisms (SNPs) in the SHBG gene are linked to IR. Therefore, it is of interest to provide a review on the comprehensive overview for SHBG related to IR.

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.

Investigation of missense mutation-related type 1 diabetes mellitus through integrating genomic databases and bioinformatic approach

Though genes are already known to be responsible for type 1 diabetes mellitus (T1DM), the knowledge of missense mutation of that disease gene has still to be under covered. A genomic database and a bioinformatics-based approach are integrated in the present study in order to address this issue. Initially, nine variants associated with T1DM were retrieved from the GWAS catalogue. Different genomic algorithms such as PolyPhen2.0, SNPs and GTEx analyser programs were used to study the structural and functional effects of these mutations. Subsequently, SNPnexus was also employed to understand the effect of these mutations on the function of the expressed protein. Nine missense variants of T1DM were identified using the GWAS catalogue database. Among these nine SNPs, three were predicted to be related to the progression of T1DM disease by affecting the protein level. TYK2 gene variants with SNP rs34536443 were thought to have a probably damaging effect. Meanwhile, both COL4A3 and IFIH1 genes with SNPs rs55703767 and rs35667974, respectively, might alter protein function through a possibly damaging prediction. Among the variants of the three genes, the TYK2 gene with SNP rs34536443 had the strongest contribution in affecting the development of T1DM, with a score of 0.999. We sincerely hope that the results could be of immense importance in understanding the genetic basis of T1DM.

Perinatal Outcomes of Diet Therapy in Gestational Diabetes Mellitus Diagnosed before 24 Gestational Weeks

To evaluate perinatal outcomes and risk factors for large for gestational age (LGA; birth weight over 90 percentile) in gestational diabetes diagnosed before 24 gestational weeks and treated with diet therapy alone until delivery (Diet Early gestational diabetes mellitus (Diet Early GDM)), we assessed the maternal characteristics and perinatal outcomes of patients with early GDM (n = 309) and normal glucose tolerance (NGT; n = 309) at Keio University Hospital. The gestational weight gain (GWG) expected at 40 weeks was significantly lower in the Diet Early GDM group than in the NGT group. The Diet Early GDM group exhibited a significantly lower incidence of low birth weight (<2500 g) and higher Apgar score at 5 min than the NGT group. Multiple logistic regression analysis revealed that the pre-pregnancy body mass index and GWG expected at 40 weeks were significantly associated with LGA for Diet Early GDM. No differences were observed in random plasma glucose levels in the first trimester, 75 g oral glucose tolerance test values, and initial increase or subsequent decrease between the two groups. Dietary early GDM did not exhibit a worse prognosis than NGT. To prevent LGA, it might be important to control maternal body weight not only during pregnancy but also before conception.

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.

Recent progress in metabolic reprogramming in gestational diabetes mellitus: a review

Gestational diabetes mellitus is a prevalent metabolic disease that can impact the normal course of pregnancy and delivery, leading to adverse outcomes for both mother and child. Its pathogenesis is complex and involves various factors, such as insulin resistance and β-cell dysfunction. Metabolic reprogramming, which involves mitochondrial oxidative phosphorylation and glycolysis, is crucial for maintaining human metabolic balance and is involved in the pathogenesis and progression of gestational diabetes mellitus. However, research on the link and metabolic pathways between metabolic reprogramming and gestational diabetes mellitus is limited. Therefore, we reviewed the relationship between metabolic reprogramming and gestational diabetes mellitus to provide new therapeutic strategies for maternal health during pregnancy and reduce the risk of developing gestational diabetes mellitus.

Association of HHEX and SLC30A8 Gene Polymorphisms with Gestational Diabetes Mellitus Susceptibility: A Meta-analysis

Genetics plays a role in the development of gestational diabetes mellitus (GDM), which poses serious risks to pregnant women and their children. Several studies have demonstrated a link between GDM susceptibility and rs13266634 C/T polymorphism in SLC30A8 gene and rs1111875 C/T and rs5015480 C/T, which are located near the linkage disequilibrium block containing the IDE, HHEX, and KIF11 genes. However, the results are conflicting. Therefore, we aimed to investigate the association between susceptibility to GDM and HHEX and SLC30A8 gene polymorphisms. PubMed, Web of Science, EBSCO, CNKI, Wanfang Data, VIP, and SCOPUS were used to search for research articles. The quality of the selected literature was evaluated using the Newcastle-Ottawa scale. A meta-analysis was performed using Stata 15.1. Allelic, dominant, recessive, homozygote, and heterozygote models were used for the analysis. Nine articles with 15 studies were included. (1) Four studies about HHEX rs1111875 showed that the C allele was associated with the susceptibility to GDM; (2) three studies on HHEX rs5015480 indicated that the C allele in rs5015480 was significantly associated with GDM; (3) eight studies about SLC30A8 rs13266634 showed that the C allele was significantly associated with the susceptibility to GDM; and (4) a subgroup analysis showed that the rs5015480 polymorphism in HHEX and rs13266634 polymorphism in SLC30A8 gene were associated with GDM susceptibility in Asians. The meta-analysis provided evidence that the C allele in rs1111875 and rs5015480 in HHEX and rs13266634 in SLC30A8 can increase the risk of GDM.PROSPERO registration number CRD42022342280.

The Association Between Serum Magnesium Levels and Gestational Diabetes Mellitus: a Systematic Review and Meta-Analysis

Observational studies suggest that the potential role of magnesium remains controversial in gestational diabetes mellitus (GDM). This meta-analysis aims to consolidate the available information from observational studies that have focused on the relationship between magnesium levels and GDM. A systematic and comprehensive literature search was conducted in PubMed, Embase, Web of Science, CNKI, and Wanfang databases. Data were extracted independently by two investigators. Standardized mean differences (SMD) and 95% confidence intervals (CIs) were used to summarize the circulating magnesium levels (CI). This meta-analysis included a total of 17 studies involving 2858 participants including 1404 GDM cases and 1454 healthy controls, which showed that magnesium levels were significantly lower in GDM compared to healthy controls (SMD: - 0.35; 95% CI: - 0.62, - 0.07, P = 0.013). Likewise, the same phenomenon was observed in the third trimester (SMD =  - 1.07; 95% CI: - 1.84 to - 0.29, P = 0.007). Other subgroup analyses revealed that this trend of decreasing magnesium concentration was only observed in Europeans (SMD =  - 0.64; 95% CI: - 0.90, - 0.38, P < 0.0001). This meta-analysis revealed that serum magnesium levels were lower in patients with GDM than in healthy pregnant women, and this discrepancy was most pronounced in European populations and during the third trimester. Nevertheless, current evidence suggests that circulating magnesium deficiency is associated with gestational diabetes; the challenge for the future is to further elucidate the possible benefits of preventing gestational diabetes through magnesium supplementation.

Potassium channels in behavioral brain disorders. Molecular mechanisms and therapeutic potential: A narrative review

Potassium channels (K+-channels) selectively control the passive flow of potassium ions across biological membranes and thereby also regulate membrane excitability. Genetic variants affecting many of the human K+-channels are well known causes of Mendelian disorders within cardiology, neurology, and endocrinology. K+-channels are also primary targets of many natural toxins from poisonous organisms and drugs used within cardiology and metabolism. As genetic tools are improving and larger clinical samples are being investigated, the spectrum of clinical phenotypes implicated in K+-channels dysfunction is rapidly expanding, notably within immunology, neurosciences, and metabolism. K+-channels that previously were considered to be expressed in only a few organs and to have discrete physiological functions, have recently been found in multiple tissues and with new, unexpected functions. The pleiotropic functions and patterns of expression of K+-channels may provide additional therapeutic opportunities, along with new emerging challenges from off-target effects. Here we review the functions and therapeutic potential of K+-channels, with an emphasis on the nervous system, roles in neuropsychiatric disorders and their involvement in other organ systems and diseases.

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.