First trimester serum biomarkers to predict gestational diabetes in a high-risk cohort: Striving for clinically useful thresholds

The effect of circulating adiponectin levels on incident gestational diabetes mellitus: systematic review and meta‑analysis

BACKGROUND

To quantitatively synthesize evidence from prospective observational studies regarding the mean levels of circulating adiponectin in patients with gestational diabetes mellitus (GDM) and the association between adiponectin levels and GDM risk.

METHODS

PubMed, EMBASE and Web of Science were searched from their inception until November 8th, 2022, for nested case-control studies and cohort studies. Random-effect models were applied to the synthesized effect sizes. The difference in circulating adiponectin levels between the GDM and control groups was measured using the pooled standardized mean difference (SMD) and 95% confidence interval (CI). The relationship between circulating adiponectin levels and GDM risk was examined using the combined odds ratio (OR) and 95% CI. Subgroup analyses were performed according to the study continent, GDM risk in the study population, study design, gestational weeks of circulating adiponectin detection, GDM diagnostic criteria, and study quality. Sensitivity and cumulative analyses were performed to evaluate the stability of the meta-analysis. Publication bias was assessed by funnel plots and Egger's test.

RESULTS

The 28 studies included 13 cohort studies and 15 nested case-control studies, containing 12,256 pregnant women in total. The mean adiponectin level in GDM patients was significantly lower than in controls (SMD = -1.514, 95% CI = -2.400 to -0.628, p = .001, I² = 99%). The risk of GDM was significantly decreased among pregnant women with increasing levels of circulating adiponectin (OR = 0.368, 95% CI = 0.271-0.500, p < .001, I²=83%). There were no significant differences between the subgroups.

CONCLUSIONS

Our findings indicate that increasing circulating adiponectin levels were inversely associated with the risk of GDM. Given the inherent heterogeneity and publication bias of the included studies, further well-designed large-scale prospective cohort or intervention studies are needed to confirm our finding.

The Association of the Triglyceride and Muscle to Fat Ratio During Early Pregnancy with the Development of Gestational Diabetes Mellitus

Objective

This study explored the association between metabolic factors and body composition during the first trimester of gestational diabetes mellitus (GDM).

Methods

This prospective study recruited pregnant women in their first trimester. Clinical information and glucose and lipid measurements were collected, and body composition was assessed using multifrequency bioelectrical impedance analysis. GDM was diagnosed on the basis of an oral glucose tolerance test at 24-28 gestational week. Factors related to GDM were investigated using correlation, and risk ratios (RRs) and 95% CIs of potential risk factors with GDM were estimated using Poisson regression. The area under the receiver operating characteristic (ROC) curve was used to determine predictive effects.

Results

59/302 women (19.5%) developed GDM. Older (RR 1.076, 95% CI 1.005-1.152), higher body mass index (BMI) before pregnancy (pre-BMI) (RR 1.012, 95% CI 1.005-1.063), triglycerides (RR 4.052, 95% CI 1.641-6.741), and lower skeletal muscle mass (SMM) to fat mass (FM) ratio (SMM/FM) (RR 0.213, 95% CI 0.051-0890) in the first trimester, and family history of type 2 diabetes (RR 1.496, 95% CI 1.014-2.667) significantly associated with the risk of GDM, but neither fasting plasma glucose nor glycated albumin was associated with GDM. The combined multivariate prediction model achieved good discrimination with an AUC of 0.806 (95% CI 0.737-0.895, P<0.001). According to ROC curve, the cut-off values of TG and SMM/FM were 0.925 mmol/L and 1.305.

Conclusion

Reduced SMM/FM and elevated triglyceride (TG) levels in the first trimester are associated with GDM development, and should be screened in early pregnancy to identify high-risk subjects for GDM.

Sex-specific and sex-independent steroid-related biomarkers in early second trimester maternal serum associated with autism

BACKGROUND

Prenatal exposure to maternal metabolic conditions associated with inflammation and steroid dysregulation has previously been linked to increased autism risk. Steroid-related maternal serum biomarkers have also provided insight into the in utero steroid environment for offspring who develop autism.

OBJECTIVE

This study examines the link between autism among offspring and early second trimester maternal steroid-related serum biomarkers from pregnancies enriched for prenatal metabolic syndrome (PNMS) exposure.

STUDY DESIGN

Early second trimester maternal steroid-related serum biomarkers (i.e., estradiol, free testosterone, total testosterone, and sex hormone binding globulin) were compared between pregnancies corresponding to offspring with (N = 68) and without (N = 68) autism. Multiple logistic regression analyses were stratified by sex and gestational duration. One-way ANCOVA with post hoc tests was performed for groups defined by autism status and PNMS exposure.

RESULTS

Increased estradiol was significantly associated with autism only in males (AOR = 1.13 per 100 pg/ml, 95% CI 1.01-1.27, p = 0.036) and only term pregnancies (AOR = 1.17 per 100 pg/ml, 95% CI 1.04-1.32, p = 0.010). Autism status was significantly associated with decreased sex hormone binding globulin (AOR = 0.65 per 50 nmol/L, 95% CI 0.55-0.78, p < 0.001) overall and when stratified by sex and term pregnancy status. The inverse association between sex hormone binding globulin and autism was independent of PNMS exposure.

LIMITATIONS

The relative racial and ethnic homogeneity of Utah's population limits the generalizability of study results. Although significant differences by autism status were identified in concentrations of sex hormone binding globulin overall and of estradiol in participant subgroups, differences by PNMS exposure failed to reach statistical significance, which may reflect insufficient statistical power.

CONCLUSION

Both elevated maternal serum estradiol in males only and low maternal serum sex hormone binding globulin in both sexes are associated with increased autism risk. Further investigation is merited to identify how steroid, metabolic, and inflammatory processes can interact to influence neurodevelopment in early second trimester.

Influence of Adipose Tissue on Early Metabolic Programming: Conditioning Factors and Early Screening

BACKGROUND

Obesity and being overweight have become one of the world's most severe health issues, not only because of the pathology but also because of the development of related comorbidities. Even when children reach adulthood, the mother's environment during pregnancy has been found to have a significant impact on obesity prevention in children. Thus, both maternal dietary habits and other factors such as gestational diabetes mellitus, excessive weight gain during pregnancy, smoking, or endocrine factors, among others, could influence newborn growth, adiposity, and body composition at birth, in childhood and adolescence, hence programming health in adulthood.

METHODS

The aim of this review is to analyze the most recent human studies on the programming of fetal adipose tissue to determine which modifiable factors may influence adiposity and thus prevent specific disorders later in life by means of a bibliographic review of articles related to the subject over the last ten years.

CONCLUSIONS

The importance of a healthy diet and lifestyle not only during pregnancy and the first months of life but also throughout childhood, especially during the first two years of life as this is a period of great plasticity, where the foundations for optimal health in later life will be laid, preventing the emergence of noncommunicable diseases including obesity, diabetes mellitus type 2, hypertension, being overweight, and any other pathology linked to metabolic syndrome, which is so prevalent today, through health programs beginning at a young age.

Biochemical and molecular biomarkers: unraveling their role in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is the most prevalent metabolic disorder during pregnancy, causing short- and long-term complications for both mother and baby. GDM is a multifactorial disease, and it may be affected by interactions between genetic, epigenetic, and environmental factors. However, the exact etiology is poorly understood. Despite the high prevalence of GDM, there is still debate regarding the optimal time for screening, the diagnostic threshold to apply, and the best strategies for treatment. Identifying effective strategies for therapeutic purposes as well as accurate biomarkers for prognostic and diagnostic purposes will reduce the GDM incidence and improve its management. In recent years, new biochemical and molecular biomarkers such as microRNAs, single-nucleotide polymorphisms, and DNA methylation have received great interest in the diagnosis of GDM. In this review, we discuss current and future diagnostic approaches for the detection of GDM and evaluate lifestyle and pharmacological strategies for GDM prevention.

Metabolic Profiling of Pregnant Women with Obesity: An Exploratory Study in Women at Greater Risk of Gestational Diabetes

Gestational diabetes mellitus (GDM) is one of the most prevalent obstetric conditions, particularly among women with obesity. Pathways to hyperglycaemia remain obscure and a better understanding of the pathophysiology would facilitate early detection and targeted intervention. Among obese women from the UK Pregnancies Better Eating and Activity Trial (UPBEAT), we aimed to compare metabolic profiles early and mid-pregnancy in women identified as high-risk of developing GDM, stratified by GDM diagnosis. Using a GDM prediction model combining maternal age, mid-arm circumference, systolic blood pressure, glucose, triglycerides and HbA1c, 231 women were identified as being at higher-risk, of whom 119 women developed GDM. Analyte data (nuclear magnetic resonance and conventional) were compared between higher-risk women who developed GDM and those who did not at timepoint 1 (15+0−18+6 weeks) and at timepoint 2 (23+2−30+0 weeks). The adjusted regression analyses revealed some differences in the early second trimester between those who developed GDM and those who did not, including lower adiponectin and glutamine concentrations, and higher C-peptide concentrations (FDR-adjusted p < 0.005, < 0.05, < 0.05 respectively). More differences were evident at the time of GDM diagnosis (timepoint 2) including greater impairment in β-cell function (as assessed by HOMA2-%B), an increase in the glycolysis-intermediate pyruvate (FDR-adjusted p < 0.001, < 0.05 respectively) and differing lipid profiles. The liver function marker γ-glutamyl transferase was higher at both timepoints (FDR-adjusted p < 0.05). This exploratory study underlines the difficulty in early prediction of GDM development in high-risk women but adds to the evidence that among pregnant women with obesity, insulin secretory dysfunction may be an important discriminator for those who develop GDM.

Gestational Diabetes Mellitus—Recent Literature Review

Gestational diabetes mellitus (GDM), which is defined as a state of hyperglycemia that is first recognized during pregnancy, is currently the most common medical complication in pregnancy. GDM affects approximately 15% of pregnancies worldwide, accounting for approximately 18 million births annually. Mothers with GDM are at risk of developing gestational hypertension, pre-eclampsia and termination of pregnancy via Caesarean section. In addition, GDM increases the risk of complications, including cardiovascular disease, obesity and impaired carbohydrate metabolism, leading to the development of type 2 diabetes (T2DM) in both the mother and infant. The increase in the incidence of GDM also leads to a significant economic burden and deserves greater attention and awareness. A deeper understanding of the risk factors and pathogenesis becomes a necessity, with particular emphasis on the influence of SARS-CoV-2 and diagnostics, as well as an effective treatment, which may reduce perinatal and metabolic complications. The primary treatments for GDM are diet and increased exercise. Insulin, glibenclamide and metformin can be used to intensify the treatment. This paper provides an overview of the latest reports on the epidemiology, pathogenesis, diagnosis and treatment of GDM based on the literature.

Role of Serotonin (5-HT) in GDM Prediction Considering Islet and Liver Interplay in Prediabetic Mice during Gestation

Gestational diabetes (GDM) is characterized by a glucose tolerance disorder. This may first appear during pregnancy or pre-exist before conception as a form of prediabetes, but there are few data on the pathogenesis of the latter subtype. Female New Zealand obese (NZO) mice serve as a model for this subpopulation of GDM. It was recently shown that GDM is associated with elevated urinary serotonin (5-hydroxytryptamine, 5-HT) levels, but the role of the biogenic amine in subpopulations with prediabetes remains unclear. 5-HT is synthesized in different tissues, including the islets of Langerhans during pregnancy. Furthermore, 5-HT receptors (HTRs) are expressed in tissues important for the regulation of glucose homeostasis, such as liver and pancreas. Interestingly, NZO mice showed elevated plasma and islet 5-HT concentrations as well as impaired glucose-stimulated 5-HT secretion. Incubation of isolated primary NZO islets with 5-HT revealed an inhibitory effect on insulin and glucagon secretion. In primary NZO hepatocytes, 5-HT aggravated hepatic glucose production (HGP), decreased glucose uptake (HGU), glycogen content, and modulated AKT activation as well as cyclic adenosine monophosphate (cAMP) increase, indicating 5-HT downstream modulation. Treatment with an HTR2B antagonist reduced this 5-HT-mediated deterioration of the metabolic state. With its strong effect on glucose metabolism, these data indicate that 5-HT is already a potential indicator of GDM before conception in mice.

First trimester screening for gestational diabetes mellitus with maternal factors and biomarkers

Introduction: This study aimed to identify risk factors among maternal characteristics, obstetric history and first trimester preeclampsia-specific biomarkers that were associated with subsequent development of gestational diabetes mellitus (GDM) and evaluate the performance of the prediction models. Methods: Secondary analysis of a prospective cohort study. The performance of the prediction models was assessed by area under receiver operating characteristic curve (AUROC). Results: A total of 837 (8.9%) cases of GDM and 8535 (91.1%) unaffected cases were included. The AUROC of the prediction model combining maternal characteristics and obstetric history (0.735) was better than that of the model utilizing maternal characteristics (AUROC 0.708) and preeclampsia-specific biomarkers (AUROC 0.566). Amongst the preeclampsia-specific biomarkers, the mean arterial pressure (MAP) contributed to the increasing risk of GDM, however, its addition did not improve the AUROC of the model combining maternal characteristics and obstetric history (0.738). Conclusion: The first trimester prediction model for GDM with maternal characteristics and obstetric history achieves moderate predictability. The inclusion of MAP in the model combining maternal characteristics and obstetric history does not improve the screening performance for GDM. Future studies are needed to explore the effect of blood pressure control from early pregnancy on preventing GDM.

Lessons from other disciplines for setting management thresholds for biodiversity conservation

Successful, state-dependent management, in which the goal of management is to maintain a system in a desired state, involves defining the boundaries between different states. Once these boundaries have been defined, managers require a strategic action plan with thresholds that initiate management interventions to either maintain or return the system to a desired state. This approach to management is widely used across diverse industries from agriculture, to medicine, to information technology, but it has only been adopted in conservation management relatively recently. Conservation practitioners have expressed a willingness to integrate this structured approach in their management systems, but they have also voiced concerns, including lack of a robust process for doing so. Given the widespread use of state-dependent management in other fields, we conducted an extensive review of the literature on threshold-based management to gain insight into how and where it is applied and identify potential lessons for conservation management. We identified 22 industries using 75 different methods for setting management thresholds in 843 studies. Methods spanned six broad approaches, including expert driven, statistical, predictive, optimization, experimental, and artificial intelligence methods. The objectives of each of these studies influenced the approaches used, including the methods for setting thresholds and selecting actions, and the number of thresholds set. The role of value judgments in setting thresholds was clear; studies across all industries frequently involved experts in setting thresholds, often accompanied by computational tools to simulate the consequences of proposed thresholds under different conditions. Of the 30 conservation studies examined, two-thirds used expert-driven methods, consistent with prior evidence that experience-based information often drives conservation management decisions. The methods we identified from other disciplines could help conservation decision makers set thresholds for management interventions in different contexts, linking monitoring to management actions and ensuring that conservation interventions are timely and effective.

Circulating exosomal hsa_circRNA_0039480 is highly expressed in gestational diabetes mellitus and may be served as a biomarker for early diagnosis of GDM

Background

Gestational diabetes mellitus (GDM) seriously affects the health of mothers and babies, and there are still no effective early diagnostic markers. Therefore, it is necessary to find diagnostic biomarkers for screening GDM in early pregnancy. Circular RNA (circRNA) is more stable than linear RNA, and can be encapsulated in exosomes and participate in the pathological process of various diseases, which makes it a better candidate biomarker for various diseases. In this study, we attempted to identify the exosomal circRNA biomarkers for detecting early GDM.

Methods

We performed microarray analysis to compare the plasma exosomal circRNA expression profiles of three GDM patients 48 h before and 48 h after delivery. The repeatability of the expression of circRNAs were randomly validated by RT-PCR analysis. Pearson correlation analysis was applied to evaluate the correlation between circRNAs and OGTT level. ROC curve was established to assess the diagnostic value of circRNAs for GDM at different stages.

Results

Plasma exosomal hsa_circRNA_0039480 and hsa_circRNA_0026497 were highly expressed in GDM patients before delivery (P < 0.05). The hsa_circRNA_0039480 expression was higher for GDM group than NGT group at different stages, and was also positively correlated with OGTT during the second trimester (P < 0.05). The expression of hsa_circRNA_0026497 was higher for GDM group during the third, and second trimesters. And there was a strong correlation between two circRNAs in GDM patients during the first-trimester (r = 0.496, P = 0.014). Hsa_circRNA_0039480 showed significant diagnostic value in the first, second, and third trimesters of pregnancy (AUC = 0.704, P = 0.005; AUC = 0.898, P < 0.001 and AUC = 0.698, P = 0.001, respectively). Notably, the combination of hsa_circRNA_0039480 and hsa_circRNA_0026497 exhibited promising discriminative effect on GDM in the first trimesters (AUC = 0.754, P < 0.001).

Conclusion

Plasma exosomal hsa_cirRNA_0039480 is highly expressed in GDM patients at different stages and may be served as a candidate biomarker for early detection of GDM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03195-5.

Early Identification of the Maternal, Placental and Fetal Dialog in Gestational Diabetes and Its Prevention

Gestational diabetes mellitus (GDM) complicates between 5 and 12% of pregnancies, with associated maternal, fetal, and neonatal complications. The ideal screening and diagnostic criteria to diagnose and treat GDM have not been established and, currently, diagnostic use with an oral glucose tolerance test occurs late in pregnancy and produces poor reproducibility. Therefore, in recent years, significant research has been undertaken to identify a first-trimester biomarker that can predict GDM later in pregnancy, enable early intervention, and reduce GDM-related adverse pregnancy outcomes. Possible biomarkers include glycemic markers (fasting glucose and hemoglobin A1c), adipocyte-derived markers (adiponectin and leptin), pregnancy-related markers (pregnancy-associated plasma protein-A and the placental growth factor), inflammatory markers (C-reactive protein and tumor necrosis factor-α), insulin resistance markers (sex hormone-binding globulin), and others. This review summarizes current data on first-trimester biomarkers, the advantages, and the limitations. Large multi-ethnic clinical trials and cost-effectiveness analyses are needed not only to build effective prediction models but also to validate their clinical use.

Gas Chromatography-Mass Spectroscopy-Based Metabolomics Analysis Reveals Potential Biochemical Markers for Diagnosis of Gestational Diabetes Mellitus

Due to many adverse effects of gestational diabetes mellitus (GDM) on the mother and fetus, its diagnosis is crucial. The presence of GDM can be confirmed by an abnormal fasting plasma glucose level (aFPG) and/or oral glucose tolerance test (OGTT) performed mostly between 24 and 28 gestational week. Both aFPG and abnormal glucose tolerance (aGT) are used to diagnose GDM. In comparison to measurement of FPG, OGTT is time-consuming, usually inconvenient for the patient, and very often needs to be repeated. Therefore, it is necessary to seek tests that will be helpful and convenient to diagnose GDM. For this reason, we investigated the differences in fasting serum metabolites between GDM women with abnGM and normal FPG (aGT-GDM group), with aFPG and normal glucose metabolism (aFPG-GDM group) as well as pregnant women with normal glucose tolerance (NGT) being a control group. Serum metabolites were measured by an untargeted approach using gas chromatography–mass spectrometry (GC–MS). In the discovery phase, fasting serum samples collected from 79 pregnant women (aFPG-GDM, n = 24; aGT-GDM, n = 26; NGT, n = 29) between 24 and 28 weeks of gestation (gwk) were fingerprinted. A set of metabolites (α–hydroxybutyric acid (α–HB), β–hydroxybutyric acid (β–HB), and several fatty acids) significant in aGT-GDM vs NGT but not significant in aFPG-GDM vs NGT comparison in the discovery phase was selected for validation. These metabolites were quantified by a targeted GC–MS method in a validation cohort consisted of 163 pregnant women (aFPG-GDM, n = 51; aGT-GDM, n = 44; and NGT, n = 68). Targeted analyses were also performed on the serum collected from 92 healthy women in the first trimester (8–14 gwk) who were NGT at this time, but in the second trimester (24–28 gwk) they were diagnosed with GDM. It was found that α–HB, β–HB, and several fatty acids were associated with aGT-GDM. A combination of α–HB, β–HB, and myristic acid was found highly specific and sensitive for the diagnosis of GDM manifested by aGT-GDM (AUC = 0.828) or to select women at a risk of aGT-GDM in the first trimester (AUC = 0.791). Our findings provide new potential markers of GDM and may have implications for its early diagnosis.

A risk-prediction model using parameters of maternal body composition to identify gestational diabetes mellitus in early pregnancy

BACKGROUND

Accurate early risk-prediction for gestational diabetes mellitus (GDM) would target intervention and prevention in women at the highest risk. We evaluated maternal risk-factors and parameters of body-composition to develop a prediction model for GDM in early gestation.

METHODS

A prospective observational study was undertaken. Pregnant women aged between 18 and 50 y of age with gestational age between 10 and 16 weeks were included in the study. Women aged ≤18 y, twin-pregnancies, known foetal anomaly or pre-existing condition affecting oedema status were excluded. 8-point-skinfold thickness (SFT), mid-upper-arm-circumference (MUAC), waist, hip, weight and ultrasound measurements of subcutaneous (SAT) and visceral abdominal-adipose (VAT) were measured. Oral-glucose-tolerance-test (OGTT) for GDM diagnosis was undertaken at 28 weeks gestation. Binomial logistic-regression models were used to predict GDM. ROC-analysis determined discrimination and concordance of model and individual variables.

RESULTS

188 women underwent OGTT at ~28 weeks gestation. 20 women developed GDM. BMI (24.7 kg m^-2 (±6.1), 29.9 kg m^-2 (±7.8), p = 0.022), abdominal SAT(1.32 cm (CI 1.31, 1.53), 1.99 cm (CI 1.64, 2.31), p = 0.027), abdominal VAT(0.78 cm (CI 0.8, 0.96), 1.41 cm (CI 1.11, 1.65), p = 0.002), truncal SFT (84.8 mm (CI 88.2, 101.6), 130.4 mm (CI 105.1, 140.1), p = 0.010), waist (79.8 cm (CI 80.3, 84.1), 90.3 cm (CI 85.9, 96.2), p = 0.006) and gluteal hip (94.3 cm (CI 93.9, 98.0), 108.6 cm (CI 99.9, 111.6), p = 0.023) were higher in GDM vs. non-GDM. After screening variables for inclusion into the multivariate model, family history of diabetes, previous perinatal death, overall insulin resistant condition, abdominal SAT and VAT, 8-point SFT, MUAC and weight were included. The combined multivariate prediction model achieved an excellent level of discrimination, with an AUC of 0.860 (CI 0.774, 0.945) for GDM.

CONCLUSIONS

An early gestation risk prediction model, incorporating known risk-factors, and parameters of body-composition, accurately identify pregnant women in their first-trimester who developed GDM later on in gestation. This methodology could be used clinically to identify at-risk pregnancies, and target specific treatment through referred services to those mothers who would most benefit.

Emerging Protein Biomarkers for the Diagnosis or Prediction of Gestational Diabetes-A Scoping Review

Introduction: Gestational diabetes (GDM), defined as hyperglycemia with onset or initial recognition during pregnancy, has a rising prevalence paralleling the rise in type 2 diabetes (T2DM) and obesity. GDM is associated with short-term and long-term consequences for both mother and child. Therefore, it is crucial we efficiently identify all cases and initiate early treatment, reducing fetal exposure to hyperglycemia and reducing GDM-related adverse pregnancy outcomes. For this reason, GDM screening is recommended as part of routine pregnancy care. The current screening method, the oral glucose tolerance test (OGTT), is a lengthy, cumbersome and inconvenient test with poor reproducibility. Newer biomarkers that do not necessitate a fasting sample are needed for the prompt diagnosis of GDM. The aim of this scoping review is to highlight and describe emerging protein biomarkers that fulfill these requirements for the diagnosis of GDM. Materials and Methods: This scoping review was conducted according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for scoping reviews using Cochrane Central Register of Controlled Trials (CENTRAL), the Cumulative Index to Nursing & Allied Health Literature (CINAHL), PubMed, Embase and Web of Science with a double screening and extraction process. The search included all articles published in the literature to July 2020. Results: Of the 3519 original database citations identified, 385 were eligible for full-text review. Of these, 332 (86.2%) were included in the scoping review providing a total of 589 biomarkers studied in relation to GDM diagnosis. Given the high number of biomarkers identified, three post hoc criteria were introduced to reduce the items set for discussion: we chose only protein biomarkers with at least five citations in the articles identified by our search and published in the years 2017-2020. When applied, these criteria identified a total of 15 biomarkers, which went forward for review and discussion. Conclusions: This review details protein biomarkers that have been studied to find a suitable test for GDM diagnosis with the potential to replace the OGTT used in current GDM screening protocols. Ongoing research efforts will continue to identify more accurate and practical biomarkers to take GDM screening and diagnosis into the 21st century.

First trimester secreted Frizzled-Related Protein 4 and other adipokine serum concentrations in women developing gestational diabetes mellitus

Background

The aim of this study was to evaluate whether soluble frizzled-related protein 4 (sFRP4) concentration in the first trimester of pregnancy is individually, or in combination with Leptin, Chemerin and/or Adiponectin, associated with the development of gestational diabetes (GDM).

Methods

In a nested case-control study, 50 women with GDM who spontaneously conceived and delivered a live-born infant were matched with a total of 100 uncomplicated singleton control pregnancies based on body mass index (± 2 kg/m²), gestational age at sampling (exact day) and maternal age (± 2 years). In serum samples, obtained between 70–90 days gestational age, sFRP4, Chemerin, Leptin and Adiponectin concentrations were determined by ELISA. Statistical comparisons were performed using univariate and multi-variate logistic regression analysis after logarithmic transformation of the concentrations. Discrimination of the models was assessed by the area under the curve (AUC).

Results

First trimester sFRP4 concentrations were significantly increased in GDM cases (2.04 vs 1.93 ng/ml; p<0.05), just as Chemerin (3.19 vs 3.15 ng/ml; p<0.05) and Leptin (1.44 vs 1.32 ng/ml; p<0.01). Adiponectin concentrations were significantly decreased (2.83 vs 2.94 ng/ml; p<0.01) in GDM cases. Further analysis only showed a weak, though significant, correlation of sFRP4 with Chemerin (R² = 0.124; p<0.001) and Leptin (R² = 0.145; p<0.001), and Chemerin with Leptin (R² = 0.282; p<0.001) in the control group. In a multivariate logistic regression model of these four markers, only Adiponectin showed to be significantly associated with GDM (odds ratio 0.12, 95%CI 0.02–0.68). The AUC of this model was 0.699 (95%CI 0.605–0.793).

Conclusion

In the first trimester of pregnancy, a multi-marker model with sFRP4, Leptin, Chemerin and Adiponectin is associated with the development of GDM. Therefore, this panel seems to be an interesting candidate to further evaluate for prediction of GDM in a prospective study.

The Oral Glucose Tolerance Test-Is It Time for a Change?-A Literature Review with an Emphasis on Pregnancy

Globally, gestational diabetes (GDM) is increasing at an alarming rate. This increase is linked to the rise in obesity rates among women of reproductive age. GDM poses a major global health problem due to the related micro- and macro-vascular complications of subsequent Type 2 diabetes and the impact on the future health of generations through the long-term impact of GDM on both mothers and their infants. Therefore, correctly identifying subjects as having GDM is of utmost importance. The oral glucose tolerance test (OGTT) has been the mainstay for diagnosing gestational diabetes for decades. However, this test is deeply flawed. In this review, we explore a history of the OGTT, its reproducibility and the many factors that can impact its results with an emphasis on pregnancy.

Sex hormone-binding globulin regulates the activity of the ERK pathway in the placentas of patients with gestational diabetes mellitus

The sex hormone-binding globulin (SHBG) is involved in the onset and progression of insulin resistance and metabolic syndromes, with its expression downregulated in the placental tissues of patients with gestational diabetes mellitus (GDM). However, the underlying mechanisms for these effects remain unclear. In this study, we enrolled an equal number (30) of GDM and non-GDM puerperae who underwent cesarean section at Shengjing Hospital. After due approval by the ethics committee, the expression levels of SHBG and extracellular-signal-regulated kinase (ERK) pathway markers in the placental tissues of these individuals were measured via reverse transcription-polymerase chain reaction (RT-PCR) and Western blot assays. The correlation analysis of these genes revealed that the expression of SHBG in placental tissues was downregulated and negatively correlated with the expression of ERK pathway markers, which were upregulated in placental tissues. Further investigations using the HTR-8/SVneo trophoblast cell line revealed that the trophoblasts with small interfering RNA (siRNA)-silenced SHBG expression displayed increased mRNA and protein expression levels of ERK pathway markers, as well as reduced apoptosis and enhanced proliferation. In contrast, trophoblasts with high SHBG expression showed a downregulated expression of ERK pathway markers, increased apoptosis, reduced proliferation, and a shorter S phase. Therefore, we believe that SHBG may participate in the onset of insulin resistance and GDM by regulating the activity of the ERK pathway.

Role of C-reactive Protein(CRP) or high-sensitivity CRP in predicting gestational diabetes Mellitus:Systematic review

BACKGROUND AND AIMS

Gestational Diabetes Mellitus (GDM) is the most common disorder during pregnancy in 8-18% of pregnancies. Due to maternal and neonatal morbidity and mortality, early diagnosis and appropriate treatment have always been of interest to researchers. One of the recent cases for early diagnosis of GDM is the size of the C-reactive protein (CRP). The purpose of this review study was to investigate the role of CRP or its high sensitivity type in predicting GDM.

METHODS

Systematic searching of MEDLINE, ISI Web of Science, PubMed, Scopus, Google Scholar, and ProQuest databases between 2009 and 2019 using keywords 'Gestational Diabetes Mellitus','Screening', 'C-reactive protein',' High sensitivity CRP'was performed. The quality of articles was also assessed using the STROBE checklist.

RESULTS

After a thorough search of the mentioned databases, 31 articles with the desired quality were finally selected. Most of studies showed significant relationship between CRP or high-sensitivity CRP(hs-CRP) level with GDMbutthe relationship was not significant in fewstudies.

CONCLUSIONS

Blood levels of CRP or hs-CRP could be used as a potential indicator for GDM, but more studies are needed.

Maternal serum pentraxin 3 level in early pregnancy for prediction of gestational diabetes mellitus

Background

Our study aimed to reveal the relationship of maternal pentraxin 3 (PTX3)'s serum concentrations in early pregnancy with gestational diabetes mellitus (GDM) and to explore its potential in the prediction of GDM.

Methods

Totally 824 pregnant women were enrolled and divided into a GDM group and a normal glucose tolerance (NGT) group, whose maternal fasting serum PTX3 levels, plasma glucose and insulin were collected. The beta cell function index and quantitative insulin sensitivity check index (QUICKI) was calculated and a homeostatic model assessment of insulin resistance (HOMA-IR) was used with SPSS 22 software used for statistical analysis.

Results

Of all subjects, 13.59% developed GDM. Compared to the NGT group, the PTX3 level was increased in the GDM group (1.48 vs. 1.52 ng/mL, P<0.05), and independently associated with the prediction of GDM (4.209, 95% CI, 1.756-10.091) (P=0.001). The area under receiver operating characteristic curve (AUROC) of the combined screening of PTX3 for GDM was incremented to 0.657 by the addition of maternal characteristics, and it reached a maximum of 0.743 in further combination with biochemical markers.

Conclusions

Serum PTX3 levels in early pregnancy may provide a useful approach for early prediction of GDM.

Predictive and diagnostic biomarkers for gestational diabetes and its associated metabolic and cardiovascular diseases

Gestational diabetes mellitus (GDM) is defined as the presence of high blood glucose levels with the onset, or detected for the first time during pregnancy, as a result of increased insulin resistance. GDM may be induced by dysregulation of pancreatic β-cell function and/or by alteration of secreted gestational hormones and peptides related with glucose homeostasis. It may affect one out of five pregnancies, leading to perinatal morbidity and adverse neonatal outcomes, and high risk of chronic metabolic and cardiovascular injuries in both mother and offspring. Currently, GDM diagnosis is based on evaluation of glucose homeostasis at late stages of pregnancy, but increased age and body-weight, and familiar or previous occurrence of GDM, may conditionate this criteria. In addition, an earlier and more specific detection of GDM with associated metabolic and cardiovascular risk could improve GDM development and outcomes. In this sense, 1st-2nd trimester-released biomarkers found in maternal plasma including adipose tissue-derived factors such as adiponectin, visfatin, omentin-1, fatty acid-binding protein-4 and retinol binding-protein-4 have shown correlations with GDM development. Moreover, placenta-related factors such as sex hormone-binding globulin, afamin, fetuin-A, fibroblast growth factors-21/23, ficolin-3 and follistatin, or specific micro-RNAs may participate in GDM progression and be useful for its recognition. Finally, urine-excreted metabolites such as those related with serotonin system, non-polar amino-acids and ketone bodies, may complete a predictive or early-diagnostic panel of biomarkers for GDM.

Sex hormone binding globulin for prediction of gestational diabetes mellitus in pre-conception and pregnancy: A systematic review

AIM

The purpose of the present study was to assess the relationship of sex hormone binding globulin (SHBG) and gestational diabetes mellitus (GDM).

METHODS

The Cochrane Library, Medline, ScienceDirect, and Web of Science were searched for studies published from the inception of the databases up to February 2019. Our inclusion criteria were published observational full-text articles. All data were analyzed using Review Manager 5.3. Of 208 papers reviewed, 26 studies (n = 6668) were considered for meta-analysis.

RESULTS

The SHBG level was significantly lower in women with GDM compared to healthy women (MD = -11.86; 95% CI: [-13.02, -10.71]). Also, SHBG in women with PCOS and GDM and obesity was significantly lower than women with PCOS without GDM (MD = -38.14; 95% CI: [-56.79, -19.48]) and normal weight women (MD: -58.96; 95% CI: [-79.32, -38.59]). SHBG in the second trimester was lower than that in the first trimester and pre-conception.

CONCLUSIONS

This systematic review showed that the level of SHBG is significantly lower in GDM pregnant women than that in healthy women. The results of this systematic review about the relationship of GDM and SHBG and suggestion to assess this marker in early pregnancy should be considered with caution.

The first-trimester of pregnancy - A window of opportunity for prediction and prevention of pregnancy complications and future life

The International Federation of Gynecology and Obstetrics (FIGO) has identified non communicable maternal diseases (NCDs) as a new focus area. NCDs and exposures as related to pregnancy complications and later impairment of maternal and offspring health will form the basis for action in the forthcoming years. This paper summarizes recent advances, centered on the use of first-trimester testing, as a window of opportunity to predict and prevent many pregnancy complications; and for potential future prevention of NCDs in mother and offspring. Recent results from a large-scale randomized control trial have provided definitive proof that effective screening for preterm preeclampsia (preterm-PE), requiring delivery before 37 weeks' gestation, can be achieved with a combined test of maternal factors and biomarkers at 11-13 weeks and that aspirin, given to high-risk women, is effective in reducing the risk of preterm-PE and the length of stay in neonatal intensive care unit. This is the first successful example to illustrate that pregnancy complications is predictable and preventable in early pregnancy. Similar prediction and prevention strategies are being developed for hyperglycemia in pregnancy and preterm birth, with the intention for longer lasting interventions leading to significant downstream impact in improving long-term health in both mothers and babies.

The Emerging Role of Biomarkers in the Diagnosis of Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a common complication of pregnancy; its rising incidence is a result of increased maternal obesity and older maternal age together with altered diagnostic criteria identifying a greater proportion of pregnant women with GDM. Its consequences are far-reaching, associated with poorer maternal and neonatal outcomes compared to non-GDM pregnancies, and GDM has implications for metabolic health in both mother and offspring. Objective markers to identify women at high risk for the development of GDM are useful to target therapy and potentially prevent its development. Established clinical risk factors for GDM include overweight/obesity, age, ethnicity, and family history of diabetes, though they lack specificity for its development. The addition of biomarkers to predictive models of GDM may improve the ability to identify women at risk of GDM prior to its development. These biomarkers reflect the pathophysiologic mechanisms of GDM involving insulin resistance, chronic inflammation, and altered placental function. In addition, the role of epigenetic changes in GDM pathogenesis highlights the complex interplay between genetic and environmental factors, potentially offering further refinement of the prediction of GDM risk. In this review, we will discuss the clinical challenges associated with the diagnosis of GDM and its current pathophysiologic basis, giving rise to potential biomarkers that may aid in its identification. While not yet validated for clinical use, we explore the possible clinical role of biomarkers in the future. We also explore novel diagnostic tools, including high throughput methodologies, that may have potential future application in the identification of women with GDM.

Controversies in Screening and Diagnostic Criteria for Gestational Diabetes in Early and Late Pregnancy

This review serves to evaluate the screening and diagnostic strategies for gestational diabetes and overt diabetes in pregnancy. We focus on the different early screening and diagnostic approaches in first trimester including fasting plasma glucose, random plasma glucose, oral glucose tolerance test, hemoglobin A1c, risk prediction models and biomarkers. Early screening for gestational diabetes is currently not recommended since the potential benefits and harms of early detection and subsequent treatment need to be further evaluated in randomized controlled trials.