Plasma Levels of the Interleukin-1-Receptor Antagonist Are Lower in Women with Gestational Diabetes Mellitus and Are Particularly Associated with Postpartum Development of Type 2 Diabetes

[Exploring the Causal Relationship Between Coagulation Function and Gestational Diabetes Mellitus Through Mendelian Randomization]

Objective

To explore the causal association between coagulation function, including von Willebrand factor (vWF), a disintegrin and metalloproteinase with thrombospondin type 1 motif, member 13 (ADAMTS13), activated partial thromboplastin time (aPTT), coagulation factor Ⅷ (FⅧ), coagulation factor Ⅺ (FⅪ), coagulation factor Ⅶ (FⅦ), coagulation factor Ⅹ (FⅩ), endogenous thrombin potential (ETP), plasminogen activator inhibitor-1 (PAI-1), protein C, and plasmin, and gestational diabetes mellitus (GDM) using two-sample two-way Mendelian randomization (MR), and to provide genetic evidence for the association between coagulation function and the pathogenesis of GDM.

Methods

The IEU OpenGWAS database was accessed using the R package TwoSampleMR (v 0.5.6) to obtain the statistical data of the genome-wide association study (GWAS) summary of GDM. MR analysis of the causal association between 11 coagulation function and GDM was performed by the inverse-variance weighted method (IVW), the MR-Egger method, and the weighted median method (WM).

Results

In this study, the GWAS summary statistics of GDM (covering 5 687 cases and 117 892 controls) were used for MR analysis. It was found that there was a causal relationship between the predicted plasma FⅧ level and the risk for GDM (IVW: [odds ratio, OR]=0.28, 95% confidence interval [CI]: 0.10-0.75, P<0.001; WM: OR=0.30, 95% CI: 0.09-0.98, P<0.001). There was no causal relationship between other coagulation function and the risk for GDM (P>0.05).

Conclusion

There is a significant causal relationship between the plasma FⅧ level and the risk for GDM. This finding highlights the complex interaction between coagulation function and glucose metabolism during pregnancy, but further research on this finding is warranted.

The role of machine learning algorithms in detection of gestational diabetes; a narrative review of current evidence

Gestational Diabetes Mellitus (GDM) poses significant health risks to mothers and infants. Early prediction and effective management are crucial to improving outcomes. Machine learning techniques have emerged as powerful tools for GDM prediction. This review compiles and analyses the available studies to highlight key findings and trends in the application of machine learning for GDM prediction. A comprehensive search of relevant studies published between 2000 and September 2023 was conducted. Fourteen studies were selected based on their focus on machine learning for GDM prediction. These studies were subjected to rigorous analysis to identify common themes and trends. The review revealed several key themes. Models capable of predicting GDM risk during the early stages of pregnancy were identified from the studies reviewed. Several studies underscored the necessity of tailoring predictive models to specific populations and demographic groups. These findings highlighted the limitations of uniform guidelines for diverse populations. Moreover, studies emphasised the value of integrating clinical data into GDM prediction models. This integration improved the treatment and care delivery for individuals diagnosed with GDM. While different machine learning models showed promise, selecting and weighing variables remains complex. The reviewed studies offer valuable insights into the complexities and potential solutions in GDM prediction using machine learning. The pursuit of accurate, early prediction models, the consideration of diverse populations, clinical data, and emerging data sources underscore the commitment of researchers to improve healthcare outcomes for pregnant individuals at risk of GDM.

Hormonal regulation in diabetes: Special emphasis on sex hormones and metabolic traits

Diabetes constitutes a significant global public health challenge that is rapidly reaching epidemic proportions. Among the non-communicable diseases, the incidence of diabetes is rising at an alarming rate. The International Diabetes Federation has documented a 9.09% prevalence of diabetes among individuals aged between 20 and 79 years. The interplay of gonadal hormones and gender differences is critical in regulating insulin sensitivity and glucose tolerance, and this dynamic is particularly crucial because of the escalating incidence of diabetes. Variations in insulin sensitivity are observed across genders, levels of adiposity, and age groups. Both estrogen and testosterone are seen to influence glucose metabolism and insulin sensitivity. This chapter surveys the present knowledge of sex differences, sex hormones, and chromosomes on insulin imbalance and diabetes development. It further highlights the influence of metabolic traits in diabetes and changes in sex hormones during diabetic pregnancy. Notably, even stressful lifestyles have been acknowledged to induce hormonal imbalances. Furthermore, it discusses the potential of hormonal therapy to help stabilize sex hormones in diabetic individuals and focuses on the most recent research investigating the correlation between sex hormones and diabetes.

Indenoquinoxaline-phenylacrylohydrazide hybrids as promising drug candidates for the treatment of type 2 diabetes: In vitro and in silico evaluation of enzyme inhibition and antioxidant activity

Existing drugs that are being used to treat type-2 diabetes mellitus are associated with several side effects; thus, exploring potential drug candidates is still an utter need these days. Hybrids of indenoquinoxaline and hydrazide have never been explored as antidiabetic agents. In this study, a series of new indenoquinoxaline-phenylacrylohydrazide hybrids (1-30) were synthesized, structurally characterized, and evaluated for α-amylase and α-glucosidase inhibitory activities, as well as for their antioxidant properties. All scaffolds exhibited varying degrees of inhibitory activity against both enzymes, with IC50 values ranging from 2.34 to 61.12 μM for α-amylase and 0.42 to 54.72 μM for α-glucosidase. Particularly, compounds 10, 16, 17, 18, 24, and 25 demonstrated the highest efficacy in inhibiting α-amylase, while compounds 6, 7, 8, 10, 12, 14, 13, 16, 17, 18, 24, and 25 were the most effective α-glucosidase inhibitors, compared to standard acarbose. Moreover, most of these compounds displayed substantial antioxidant potential compared to standard butylated hydroxytoluene (BHT). Kinetics studies revealed competitive inhibition modes by compounds. Furthermore, a comprehensive in silico study and toxicity prediction were also conducted, further validating these analogs as potential drug candidates. The structured compounds demonstrated enhanced profiles, underscoring their potential as primary candidates in drug discovery.

Second trimester cytokine profiles associated with gestational diabetes and hypertensive disorders of pregnancy

Healthy pregnancy requires a coordinated immune response, yet complications can arise, putting both the mother's and child's health at risk. Hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) are pregnancy-related complications that account for most maternal morbidity and mortality. Cytokines are proteins released as part of the immune response to disease or infection and regulate inflammation. Certain pregnancy complications cause localized and systemic inflammation; however, cytokine profiles specific to such complications are not well understood. This study aims to examine associations between pregnancy complications of HDP and GDM and cytokine profiles in the second trimester of pregnancy. Data was obtained from the All Our Families birth cohort in Calgary, Alberta, Canada. The cohort collected questionnaires at the time of participant enrollment and maternal blood samples at 17-23 weeks gestation. Cases of HDP (n = 27) and GDM (n = 31) were matched to controls on BMI, maternal age, and smoking status in the preconception period at a 1:3 ratio. Cytokine levels were measured in blood samples using Luminex xMAP technology using a panel of 42 cytokines. Using R software, a Classification and Regression Tree (CART) analysis was conducted to identify cytokine profiles and levels associated with each complication. Four cytokines were identified in the HDP CART (in descending order of importance): Monocyte Chemoattractant Protein-1 (cut-off: <480pg/mL), Macrophage Inflammatory Protein-1β (cut-off: ≥26pg/mL), Eotaxin (cut-off: <27/≥27&<36/≥36pg/mL), and Soluble Cluster of Differentiation 40 Ligand (cut-off: <1342pg/mL). Six cytokine levels were identified in the GDM CART: Interleukin-1 Receptor Antagonist (IL-1Ra; cut-off: <25pg/mL), Interleukin-5 (cut-off: ≥0.4pg/mL), Interferon-γ (cut-off: <4.9pg/mL), IL-1Ra (cut-off: ≥111pg/mL), Eotaxin (cut-off: ≥21pg/mL), and Interleukin-18 (cut-off: ≥155pg/mL). By examining the complex inter-relationships between cytokines, findings of cytokine profiles guide further research in identifying biomarkers of pregnancy complications relevant to the design of the future management or prevention of these conditions.

Identification of human placenta-derived circular RNAs and autophagy related circRNA-miRNA-mRNA regulatory network in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a metabolic and reproductive disease with serious risks and adverse health effects. However, the pathophysiological mechanism of GDM, especially the roles of circRNAs in its pathogenesis, is largely unknown. The objective of this study was to identify and investigate the roles of circRNAs in GDM. In the current study, placental circRNA expression profiles of normal controls and GDM patients were analyzed using high-throughput sequencing. Bioinformatics analysis identified a total of 4,955 circRNAs, of which 37 circRNAs were significantly deregulated in GDM placentas compared with NC placentas. GO and KEGG enrichment analyses demonstrated that metabolic process-associated terms and metabolic pathways that may be related to GDM were significantly enriched. The biological characteristics of placenta-derived circRNAs, such as their stability and RNase R resistance, were also validated Bioinformatics prediction. Moreover, we constructed the autophagy related circRNA-miRNA-mRNA regulatory network and further functional analysis revealed that the circCDH2-miR-33b-3p-ULK1 axis may be associated with autophagy in the placentas of GDM patients. Our study indicates that aberrant expression of circRNAs may play roles in autophagy in GDM placentas, providing new insights into GDM.

Genetic polymorphism of interleukin-1 receptor antagonist in Type 1 diabetic children

BACKGROUND

Interleukin-1 receptor antagonist (IL1RN) variable number tandem repeats (VNTRs) are not fully understood in Type 1 diabetes mellitus (T1DM). It may affect IL1RN level and modify the disease risk. We aimed to study IL1RN VNTR polymorphism in Egyptian children with T1DM to clarify its potential role as a risk factor for T1DM and its effect on plasma IL1RN level.

METHODS

A case-controlled study including 200 children (120 T1DM and 80 controls) was carried on. All children were subjected to genotyping of IL1RN VNTR. Plasma IL1RN was estimated by ELISA.

RESULTS

The A1A2 and LS genotypes and A2 allele were significantly higher among cases compared to controls with increased T1DM risk (OR = 5.35, 2.56 and 3.13, respectively). The S allele was significantly elevated in cases compared to controls with 2.09-fold increased risk of having T1DM. The median plasma IL1RN significantly decreased in cases compared to controls. Within cases, IL1RN was significantly decreased in LS versus LL genotype.

CONCLUSIONS

There is a strong relationship between IL1RN VNTR and T1DM in Egyptian children. A1A1 genotype, LL genotype, A1 allele, and L allele were protective. A1A2 and LS genotypes, short (S), and A2 alleles were risk factors. IL1RN was decreased in T1DM, especially in LS genotype.

IMPACT

The relationship between IL1RN gene polymorphism and risk for T1DM among Egyptian children. Plasma IL1RN protein level in T1DM. Low IL1RN protein level in T1DM patients could be therapeutic targets for IL1RN medications in the future.

AST-to-ALT ratio in the first trimester and the risk of gestational diabetes mellitus

BACKGROUND

Aspartate aminotransferase-to-alanine transaminase ratio (AST/ALT) has been reported affect the risk of type 2 diabetes (T2DM), but it is uncertain if it has relationship with gestational diabetes mellitus (GDM).

OBJECTIVES

Our study aimed to investigate the association between AST/ALT ratio in the first trimester and the risk of subsequent development of GDM.

METHOD

This prospective cohort study enrolling 870 pregnant women, 204 pregnant women with missing data or liver diseases were excluded, 666 pregnant women were included in this study containing 94 GDM women. Blood samples were collected in the first trimester. Univariate analysis and multivariate logistic regression were used to evaluate the association between AST/ALT and GDM. Nomogram was established based on the results of multivariate logistic analysis. Receiver Operating Characteristic (ROC) curves and calibration curves were used to evaluate the predictive ability of this nomogram model for GDM. Decision curve analysis (DCA) was used to examine the clinical net benefit of predictive model.

RESULTS

AST/ALT ratio (RR:0.228; 95% CI:0.107-0.488) was associated with lower risk of GDM after adjusting for confounding factors. Indicators used in nomogram including AST/ALT, maternal age, preBMI, waist circumference, glucose, triglycerides, high density lipoprotein cholesterol and parity. The area under the ROC curve (AUC) value of this predictive model was 0.778, 95% CI (0.724, 0.832). Calibration curves for GDM probabilities showed acceptable agreement between nomogram predictions and observations. The DCA curve demonstrated a good positive net benefit in the predictive model.

CONCLUSIONS

The early AST/ALT level of pregnant women negatively correlated with the risk of GDM. The nomogram including AST/ALT at early pregnancy shows good predictive ability for the occurrence of GDM.

Postpartum circulating microRNA enhances prediction of future type 2 diabetes in women with previous gestational diabetes

AIMS/HYPOTHESIS

Type 2 diabetes mellitus is a major cause of morbidity and death worldwide. Women with gestational diabetes mellitus (GDM) have greater than a sevenfold higher risk of developing type 2 diabetes in later life. Accurate methods for postpartum type 2 diabetes risk stratification are lacking. Circulating microRNAs (miRNAs) are well recognised as biomarkers/mediators of metabolic disease. We aimed to determine whether postpartum circulating miRNAs can predict the development of type 2 diabetes in women with previous GDM.

METHODS

In an observational study, plasma samples were collected at 12 weeks postpartum from 103 women following GDM pregnancy. Utilising a discovery approach, we measured 754 miRNAs in plasma from type 2 diabetes non-progressors (n = 11) and type 2 diabetes progressors (n = 10) using TaqMan-based real-time PCR on an OpenArray platform. Machine learning algorithms involving penalised logistic regression followed by bootstrapping were implemented.

RESULTS

Fifteen miRNAs were selected based on their importance in discriminating type 2 diabetes progressors from non-progressors in our discovery cohort. The levels of miRNA miR-369-3p remained significantly different (p < 0.05) between progressors and non-progressors in the validation sample set (n = 82; 71 non-progressors, 11 progressors) after adjusting for age and correcting for multiple comparisons. In a clinical model of prediction of type 2 diabetes that included six traditional risk factors (age, BMI, pregnancy fasting glucose, postpartum fasting glucose, cholesterol and triacylglycerols), the addition of the circulating miR-369-3p measured at 12 weeks postpartum improved the prediction of future type 2 diabetes from traditional AUC 0.83 (95% CI 0.68, 0.97) to an AUC 0.92 (95% CI 0.84, 1.00).

CONCLUSIONS

This is the first demonstration of miRNA-based type 2 diabetes prediction in women with previous GDM. Improved prediction will facilitate early lifestyle/drug intervention for type 2 diabetes prevention.

Amnion and Umbilical Cord-Derived Products in Sports Medicine: From Basic Science to Clinical Application

BACKGROUND

Birth tissue products from amnion, chorion, umbilical cord, amniotic fluid, or cord blood are frequently marketed as viable sources of stem cells and growth factors. It can be difficult for health care professionals to differentiate implied from explicit conclusions in reported product analyses.

PURPOSE

To provide an educational platform for health care professionals to interpret data presented in the promotion of birth tissue products.

STUDY DESIGN

Descriptive laboratory study and expert opinion; Level of evidence, 5.

METHODS

A cord blood product was analyzed by 3 methods for cell viability, 2 methods for assessment of cell morphology and cell type, multicolor flow cytometry to identify stem cells, and enzyme-linked immunosorbent assay (ELISA) plus Western blot for analysis of interleukin 1 receptor antagonist protein (IL-1ra). These data were compared with analyses reported by the manufacturer.

RESULTS

Cell viability in the cord blood product was less than reported by the manufacturer, the cells were primarily leukocytes, no stem cells were present, and the concentration of IL-1ra was falsely increased due to nonspecific antibody binding in the sample.

CONCLUSION

To assess birth tissue products, health care professionals should consider the following: (1) Understanding fluorescent dyes is important for assessing cell viability data-green does not always mean alive. (2) The report of "cells" in the product does not necessarily mean "stem cells"; microscopic images of at least ×20 or a hemogram should be evaluated to determine cell type (leukocyte, red blood cells, etc). (3) There is no single cluster of differentiation (CD) marker on flow cytometry to identify stem cells. (4) Biological tissues are complex substances, and inaccurately increased measurements of growth factors could be present in ELISA results because most ELISAs are not designed or validated for use in biologics. Furthermore, the reported measurement of growth factors should be considered relative to concentrations in native biological tissues and plasma.

CLINICAL RELEVANCE

Health care professionals should be able to interpret cell viability, cell morphology, stem cell analysis using CD markers, and growth factor analysis when considering use of a birth tissue product in patients.

Interleukin 1 Receptor 1 Knockout and Maternal High Fat Diet Exposure Induces Sex-Specific Effects on Adipose Tissue Adipogenic and Inflammatory Gene Expression in Adult Mouse Offspring

Background: The global incidence of obesity continues to rise, increasing the prevalence of metabolic diseases such as insulin resistance, dyslipidemia, and type 2 diabetes mellitus. Low-grade chronic inflammation, associated with the obese state, also contributes to the development of these metabolic comorbidities. Interleukin-1-receptor-1 (IL-1R1), a pro-inflammatory mediator, bridges the metabolic and inflammatory systems. In young male mice, deficiency of IL-1R1 (IL-1R1^-/-) paired with a high-fat diet (HFD) offered beneficial metabolic effects, however in female mice, the same pairing led to metabolic dysfunction. Therefore, we examined the contribution of maternal HFD in combination with IL1R1^-/- to metabolic health in adult offspring. Methods: Female C57BL/6 and IL-1R1^-/- mice were randomly assigned to a control diet (10% kcal from fat) or HFD (45% kcal from fat) 10 days prior to mating and throughout gestation and lactation. Male and female offspring were housed in same-sex pairs post-weaning and maintained on control diets until 16 weeks old. At 15 weeks, an oral glucose tolerance test (OGTT) was performed to assess glucose tolerance. Histological analysis was carried out to assess adipocyte size and gene expression of adipogenic and inflammatory markers were examined. Results: IL-1R1^-/- contributed to increased body weight in male and female adult offspring, irrespective of maternal diet. IL-1R1^-/- and maternal HFD increased adipocyte size in the gonadal fat depot of female, but not male offspring. In female offspring, there was reduced expression of genes involved in adipogenesis and lipid metabolism in response to IL1R1^-/- and maternal HFD. While there was an increase in inflammatory gene expression in response to maternal HFD, this appeared to be reversed in IL1R1^-/- female offspring. In male offspring, there was no significant impact on adipogenic or lipid metabolism pathways. There was an increase in inflammatory gene expression in IL1R1^-/- male offspring from HFD-fed mothers. Conclusion: This study suggests that IL-1R1 plays a complex and important role in the metabolic health of offspring, impacting adipogenesis, lipogenesis, and inflammation in a sex-specific manner.

Inhibition of IL-1beta improves Glycaemia in a Mouse Model for Gestational Diabetes

Gestational diabetes mellitus (GDM) is one of the most common diseases associated with pregnancy, however, the underlying mechanisms remain unclear. Based on the well documented role of inflammation in type 2 diabetes, the aim was to investigate the role of inflammation in GDM. We established a mouse model for GDM on the basis of its two major risk factors, obesity and aging. In these GDM mice, we observed increased Interleukin-1β (IL-1β) expression in the uterus and the placenta along with elevated circulating IL-1β concentrations compared to normoglycemic pregnant mice. Treatment with an anti-IL-1β antibody improved glucose-tolerance of GDM mice without apparent deleterious effects for the fetus. Finally, IL-1β antagonism showed a tendency for reduced plasma corticosterone concentrations, possibly explaining the metabolic improvement. We conclude that IL-1β is a causal driver of impaired glucose tolerance in GDM.

Women with a predisposition for diabetes have an increased risk of pregnancy complications, especially in combination with pregestational overweight

BACKGROUND

Overweight and gestational diabetes are risk factors for pregnancy complications. We hypothesized that the metabolic impact of overweight on pregnancy outcome, would be different if it was combined with a predisposition for diabetes. The aim of this study was to compare the outcome of pregnancies in women with diabetes diagnosed later in life, to the outcome of pregnancies of women who did not develop diabetes.

METHODS

Women in a population-based cohort who also were registered in the Swedish Medical Birth Registry (n = 4738) were included. A predisposition for diabetes (GDM or diabetes after pregnancy) was found in 455 pregnancies. The number of pregnancies with maternal BMI ≥ 25 kg/m2 and without diabetes were 2466, and in 10,405 pregnancies the mother had a BMI < 25 kg/m2 without diabetes at any time. Maternal BMI, gestational length, gestational weight gain, frequency of caesarean section, infant birth weight, frequency of large for gestational age (LGA) and Apgar score were retrospectively compared.

RESULTS

Pregnancies with normal maternal BMI ≤25 kg/m2, with predisposition for diabetes had a higher frequency of LGA (11.6% vs. 2.9%; p < 0.001), a higher frequency of macrosomia (28.6% vs. 17.6%; p < 0.001), and a shorter gestational length (39.7 vs. 40 weeks; p = 0.08) when compared to pregnancies in women without a predisposition for diabetes. In addition, pregnancies with both maternal predisposition for diabetes and BMI ≥ 25 kg/m2 there was a higher frequency of LGA (23.3% vs. 7.1%; p < 0.001), caesarean section (24.0% vs. 14.9%, p = 0.031) compared to pregnancies in women who were only overweight. A predisposition for diabetes significantly increases the risk of macrosomia (OR1.5; 95% CI 1.07-2.15; p = 0.02).

CONCLUSIONS

In pregnancy, there is an increased frequency of LGA, macrosomia and caesarean section if the woman has a predisposition for diabetes. The frequency of overweight young women is increasing, and it is urgent to identify pregnant women with a predisposition to diabetes. How to distinguish the women with the highest risk for adverse pregnancy outcome and the highest risk of future disease, remains to be studied.

IL-1β and IL-10 gene polymorphisms in women with gestational diabetes

AIMS

Gestational diabetes (GDM) is carbohydrate intolerance occurring in pregnant women. In the GDM pathogenesis, the low-grade inflammation plays a significant role. Various inflammatory mediators are considered to be risk factors leading to GDM development including cytokines. Studies suggest that some cytokines such as: IL-1β and IL-10 play an important role in GDM pathogenesis. The aim of the study was to examine the associations between IL-1β rs16944, and IL-10 rs1800872 gene polymorphisms and GDM.

METHODS

This study included 204 pregnant women with GDM and 207 pregnant women with normal glucose tolerance. The diagnosis of GDM was based on a 75-g oral glucose tolerance test administered at 24-28 weeks' gestation. Among the pregnant women with GDM, 152 (75%) were treated with diet control alone throughout the pregnancy, whereas the remaining 52 (25%) were treated with diet control and insulin until delivery.

RESULTS

There were no statistically significant differences in the distribution of IL-1β rs16944 and IL-10 rs1800872 between GDM and healthy women. However among women treated with insulin, we observed the increased frequency of IL-1β rs16944 AA genotype carriers. Additionally, we observed increased daily insulin requirement in women with IL-1β rs16944 AA genotype. Moreover, women with IL-10 rs1800872 AA genotype had higher body mass and BMI before pregnancy as well as higher body mass and BMI increase during pregnancy.

CONCLUSIONS

The results of our study suggest the association between IL-1β rs16944 AA genotype and increased frequency of the need of insulin treatment as well as increased daily insulin requirement.