Elevated placental growth factor concentrations at 11-14 weeks of gestation to predict gestational diabetes mellitus

Fatty acids, inflammation and angiogenesis in women with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a metabolic disorder in pregnancy whose prevalence is on the rise. Reports suggest a likely association between inflammation and maternal GDM. A balance between pro and anti-inflammatory cytokines is necessary for the regulation of maternal inflammation system throughout pregnancy. Along with various inflammatory markers, fatty acids also act as pro-inflammatory molecules. However, studies reporting the role of inflammatory markers in GDM are contradictory, suggesting the need of more studies to better understand the role of inflammation in pregnancies complicated by GDM. Inflammatory response can be regulated by angiopoietins suggesting a link between inflammation and angiogenesis. Placental angiogenesis is a normal physiological process which is tightly regulated during pregnancy. Various pro and anti-angiogenic factors influence the regulation of the feto-placental vascular development. Studies evaluating the levels of angiogenic markers in women with GDM are limited and the findings are inconsistent. This review summarizes the available literature on fatty acids, inflammatory markers and angiogenesis in women with GDM. We also discuss the possible link between them and their influence on placental development in GDM.

Placental Growth Factor and Pregnancy-Associated Plasma Protein-A as Potential Early Predictors of Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and one of the main causes of adverse pregnancy outcomes. An early diagnosis of GDM is of fundamental importance in clinical practice. However, the major professional organizations recommend universal screening for GDM, using a 75 g oral glucose tolerance test at 24-28 weeks of gestation. A selective screening at an early stage of pregnancy is recommended only if there are maternal risk factors for diabetes. As a result, the GDM diagnosis is often delayed and established after the appearance of complications. The manifestation of GDM is directly related to insulin resistance, which is closely associated with endothelial dysfunction. The placenta, the placental peptides and hormones play a pivotal role in the manifestation and progression of insulin resistance during pregnancy. Recently, the placental growth factor (PlGF) and plasma-associated protein-A (PAPP-A), have been shown to significantly affect both insulin sensitivity and endothelial function. The principal function of PAPP-A appears to be the cleavage of circulating insulin-like growth factor binding protein-4 while PlGF has been shown to play a central role in the development and maturation of the placental vascular system and circulation. On one hand, these factors are widely used as early predictors (11-13 weeks of gestation) of complications during pregnancy, such as preeclampsia and fetal aneuploidies, in most countries. On the other hand, there is increasing evidence for their predictive role in the development of carbohydrate disorders, but some studies are rather controversial. Therefore, this review aims to summarize the available literature about the potential of serum levels of PlGF and PAPP-A as early predictors in the diagnosis of GDM.

Circulating angiotensin II type I receptor - autoantibodies in diabetic pregnancies

Pregnant women with either pre-existing or gestational diabetes mellitus are at increased risk of preeclampsia as well as future cardiovascular disease. The renin-angiotensin system is dysregulated in both diabetes mellitus and preeclampsia. In preeclampsia, maternal levels of circulating agonistic autoantibodies against the angiotensin II Type I receptor (AT₁-AAs) are increased. Circulating AT₁-AAs are thought to contribute to both the pathophysiology of preeclampsia and the increased risk of future cardiovascular disease. Studies exploring AT₁-AA in diabetes outside pregnancy suggest their potential for both metabolic and cardiovascular pathogenicity. No studies have investigated AT₁-AAs in diabetic pregnancies. We hypothesized elevated maternal circulating AT₁-AA levels in pregnancies complicated by any type of diabetes mellitus. Third-trimester maternal serum from 39 women (controls: n = 10; type 1 diabetes: n = 9; type 2 diabetes: n = 10; gestational diabetes=10) were analyzed for AT₁-AA using an established bioassay method. Circulating AT₁-AAs were present in 70% (7/10) of the controls and 83% (24/29) of the diabetes group (P = 0.399). Presence of AT₁-AA was correlated to hsCRP levels (P = 0.036), but neither with maternal circulating angiogenic factors (soluble fms-like tyrosine kinase-1 and placental growth factor), nor with maternal or fetal characteristics indicative of metabolic disease or placental dysfunction. Our study is the first to demonstrate presence of circulating AT₁-AAs in pregnant women with any type of diabetes. Our findings suggest AT₁-AAs presence in pregnancy independently of placental dysfunction, nuancing the current view on their pathogenicity. Whether AT₁-AAs per se contribute to increased risk of adverse pregnancy outcomes and future cardiovascular disease remains currently unanswered.

A Clinical Update on Gestational Diabetes Mellitus

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

Cardiovascular Disease-Associated MicroRNAs as Novel Biomarkers of First-Trimester Screening for Gestational Diabetes Mellitus in the Absence of Other Pregnancy-Related Complications

We assessed the diagnostic potential of cardiovascular disease-associated microRNAs for the early prediction of gestational diabetes mellitus (GDM) in singleton pregnancies of Caucasian descent in the absence of other pregnancy-related complications. Whole peripheral venous blood samples were collected within 10 to 13 weeks of gestation. This retrospective study involved all pregnancies diagnosed with only GDM (n = 121) and 80 normal term pregnancies selected with regard to equality of sample storage time. Gene expression of 29 microRNAs was assessed using real-time RT-PCR. Upregulation of 11 microRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, and miR-574-3p) was observed in pregnancies destinated to develop GDM. Combined screening of all 11 dysregulated microRNAs showed the highest accuracy for the early identification of pregnancies destinated to develop GDM. This screening identified 47.93% of GDM pregnancies at a 10.0% false positive rate (FPR). The predictive model for GDM based on aberrant microRNA expression profile was further improved via the implementation of clinical characteristics (maternal age and BMI at early stages of gestation and an infertility treatment by assisted reproductive technology). Following this, 69.17% of GDM pregnancies were identified at a 10.0% FPR. The effective prediction model specifically for severe GDM requiring administration of therapy involved using a combination of these three clinical characteristics and three microRNA biomarkers (miR-20a-5p, miR-20b-5p, and miR-195-5p). This model identified 78.95% of cases at a 10.0% FPR. The effective prediction model for GDM managed by diet only required the involvement of these three clinical characteristics and eight microRNA biomarkers (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, and miR-574-3p). With this, the model identified 50.50% of GDM pregnancies managed by diet only at a 10.0% FPR. When other clinical variables such as history of miscarriage, the presence of trombophilic gene mutations, positive first-trimester screening for preeclampsia and/or fetal growth restriction by the Fetal Medicine Foundation algorithm, and family history of diabetes mellitus in first-degree relatives were included in the GDM prediction model, the predictive power was further increased at a 10.0% FPR (72.50% GDM in total, 89.47% GDM requiring therapy, and 56.44% GDM managed by diet only). Cardiovascular disease-associated microRNAs represent promising early biomarkers to be implemented into routine first-trimester screening programs with a very good predictive potential for GDM.

The Role of Placental Growth Factor in the Prediction of Carbohydrate and Thyroid Disorders during Pregnancy

Background and objectives: To assess whether placental growth factor (PlGF) levels may have a predictive value for the onset of gestational diabetes mellitus (GDM) and thyroid dysfunction during pregnancy. Materials and Methods: This single-center retrospective analysis was conducted at the Specialized Hospital for Active Treatment in Obstetrics and Gynecology “Dr. Shterev”, Sofia, Bulgaria, from December 2017 to December 2019. Using pregnant women’s electronic records, we analyzed and compared the data of 412 women diagnosed with GDM and 250 women without evidence for carbohydrate disorders. Thyroid function was tested in all patients at the time of performing GDM screening. The following measurements were compared and assessed: body mass index (BMI), fasting blood glucose levels, thyroid-stimulating hormone levels (TSH), free thyroxine, and triiodothyronine (FT4 and FT3) levels, and serum placental growth factor (PlGF). The sensitivity and specificity of PlGF as a predictive marker for GDM and thyroid dysfunction were analyzed using receiver operating characteristic (ROC) curves. Results: There were no significant differences between GDM and control groups in terms of age and BMI (p > 0.05). In patients with established GDM, the PlGF corrected multiple of the median (MoM) was significantly higher compared to the control group (0.9 vs. 0.7, p < 0.001). The ROC-AUC for the prediction of GDM and thyroid dysfunction during pregnancy was 0.68 (95% CI 0.64–0.72) and 0.61 (95% CI 0.57–0.65), respectively. Conclusions: Our results underscore the potential role of PlGF as a biomarker in the prediction and diagnosis of GDM and thyroid dysfunction during pregnancy.

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.

Performance of early risk assessment tools to predict the later development of gestational diabetes

BACKGROUND

Several prognostic models for gestational diabetes mellitus (GDM) are provided in the literature; however, their clinical significance has not been thoroughly evaluated, especially with regard to application at early gestation and in accordance with the most recent diagnostic criteria. This external validation study aimed to assess the predictive accuracy of published risk estimation models for the later development of GDM at early pregnancy.

METHODS

In this cohort study, we prospectively included 1132 pregnant women. Risk evaluation was performed before 16 + 0 weeks of gestation including a routine laboratory examination. Study participants were followed-up until delivery to assess GDM status according to the IADPSG 2010 diagnostic criteria. Fifteen clinical prediction models were calculated according to the published literature.

RESULTS

Gestational diabetes mellitus was diagnosed in 239 women, that is 21.1% of the study participants. Discrimination was assessed by the area under the ROC curve and ranged between 60.7% and 76.9%, corresponding to an acceptable accuracy. With some exceptions, calibration performance was poor as most models were developed based on older diagnostic criteria with lower prevalence and therefore tended to underestimate the risk of GDM. The highest variable importance scores were observed for history of GDM and routine laboratory parameters.

CONCLUSIONS

Most prediction models showed acceptable accuracy in terms of discrimination but lacked in calibration, which was strongly dependent on study settings. Simple biochemical variables such as fasting glucose, HbA1c and triglycerides can improve risk prediction. One model consisting of clinical and laboratory parameters showed satisfactory accuracy and could be used for further investigations.

Effects of Maternal Obesity and Gestational Diabetes Mellitus on the Placenta: Current Knowledge and Targets for Therapeutic Interventions

Obesity and gestational diabetes mellitus (GDM) are becoming more common among pregnant women worldwide and are individually associated with a number of placenta-mediated obstetric complications, including preeclampsia, macrosomia, intrauterine growth restriction and stillbirth. The placenta serves several functions throughout pregnancy and is the main exchange site for the transfer of nutrients and gas from mother to fetus. In pregnancies complicated by maternal obesity or GDM, the placenta is exposed to environmental changes, such as increased inflammation and oxidative stress, dyslipidemia, and altered hormone levels. These changes can affect placental development and function and lead to abnormal fetal growth and development as well as metabolic and cardiovascular abnormalities in the offspring. This review aims to summarize current knowledge on the effects of obesity and GDM on placental development and function. Understanding these processes is key in developing therapeutic interventions with the goal of mitigating these effects and preventing future cardiovascular and metabolic pathology in subsequent generations.

Machine Learning Prediction Models for Gestational Diabetes Mellitus: A meta- analysis (Preprint)

Background

Gestational diabetes mellitus (GDM) is a common endocrine metabolic disease, involving a carbohydrate intolerance of variable severity during pregnancy. The incidence of GDM-related complications and adverse pregnancy outcomes has declined, in part, due to early screening. Machine learning (ML) models are increasingly used to identify risk factors and enable the early prediction of GDM.

Objective

The aim of this study was to perform a meta-analysis and comparison of published prognostic models for predicting the risk of GDM and identify predictors applicable to the models.

Methods

Four reliable electronic databases were searched for studies that developed ML prediction models for GDM in the general population instead of among high-risk groups only. The novel Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias of the ML models. The Meta-DiSc software program (version 1.4) was used to perform the meta-analysis and determination of heterogeneity. To limit the influence of heterogeneity, we also performed sensitivity analyses, a meta-regression, and subgroup analysis.

Results

A total of 25 studies that included women older than 18 years without a history of vital disease were analyzed. The pooled area under the receiver operating characteristic curve (AUROC) for ML models predicting GDM was 0.8492; the pooled sensitivity was 0.69 (95% CI 0.68-0.69; P<.001; I²=99.6%) and the pooled specificity was 0.75 (95% CI 0.75-0.75; P<.001; I²=100%). As one of the most commonly employed ML methods, logistic regression achieved an overall pooled AUROC of 0.8151, while non–logistic regression models performed better, with an overall pooled AUROC of 0.8891. Additionally, maternal age, family history of diabetes, BMI, and fasting blood glucose were the four most commonly used features of models established by the various feature selection methods.

Conclusions

Compared to current screening strategies, ML methods are attractive for predicting GDM. To expand their use, the importance of quality assessments and unified diagnostic criteria should be further emphasized.

Care of Infants Born to Women with Diabetes

PURPOSE OF REVIEW

Infants of women with diabetes are at risk for specific morbidities including congenital anomalies, abnormalities of fetal growth, neonatal hypoglycemia, electrolyte abnormalities, polycythemia, hyperbilirubinemia, and respiratory distress syndrome. Recent studies have shed light on long-term outcomes of these infants and presented advances in treatment. The purpose of this review is to outline the most common neonatal morbidities affecting infants of women with diabetes, the pathophysiology and prevalence of these conditions, and contemporary approaches to treatment.

RECENT FINDINGS

Recent investigative findings have led to advances in treatment approaches for these infants, particularly regarding risks of neonatal hypoglycemia. Optimizing maternal glycemic control during pregnancy is imperative to improving infant outcomes. However, on a population level, maternal diabetes still poses significant risks to the infant. Timely and appropriate treatment of infants of women with diabetes is imperative to decrease short- and long-term morbidity.

Placental growth factor as a predictive marker of preeclampsia - PREBIO study - PREeclampsia BIOchemical study

INTRODUCTION

To evaluate the clinical utility of placental growth factor (PlGF) for the prediction of preeclampsia (PE).

MATERIALS AND METHODS

This prospective cohort study included women divided into three groups: (1) pregnancies without preconceptional risk of developing PE; (2) pregnancies with a preconceptional and/or current risk of developing PE; (3) PE-complicated pregnancies (control group). Blood samples were collected every 4-5 weeks or during hospitalization from early second trimester until delivery in the group 1 and 2, at the diagnosis of PE in the group 3. Plasma levels of PlGF were measured using The Triage PlGF test (Alere) and considered pathological under the 5th centile for gestational age. Sensitivity (Sn), specificity (Sp), positive and negative predictive value (PPV, NPV) were calculated.

RESULTS

In group 1, 30% of women (3/10) had pathological test but none of them developed PE (Sp 70%, NPV 100%). In group 2 (n = 75), none of the patients with normal test developed PE (0/24), while 39% of women with PlGF < 5th centile (20/51) developed PE (Sn 100%, Sp 44%, PPV 39%, NPV 100%). In group 3 (n = 11) all women except one had a pathological PlGF test (Sn 90%, PPV 100%).

CONCLUSIONS

Our data support recent studies which identify PlGF as a biochemical marker not only of PE, but also of placental dysfunction. In fact, it is useful for ruling out PE in women at risk because of the high Sn and high NPV: a normal PlGF is related with a positive pregnancy outcome. Therefore, the measurement of this biomarker would simplify PE clinical management and would reduce costs.

Early pregnancy prediction of gestational diabetes mellitus risk using prenatal screening biomarkers in nulliparous women

AIMS

To evaluate the clinical utility of first and second trimester prenatal screening biomarkers for early pregnancy prediction of gestational diabetes mellitus (GDM) risk in nulliparous women.

METHODS

We conducted a population-based cohort study of nulliparous women participating in the California Prenatal Screening Program from 2009 to 2011 (n = 105,379). GDM was ascertained from hospital discharge records or birth certificates. Models including maternal characteristics and prenatal screening biomarkers were developed and validated. Risk stratification and reclassification were performed to assess clinical utility of the biomarkers.

RESULTS

Decreased levels of first trimester pregnancy-associated plasma protein A (PAPP-A) and increased levels of second trimester unconjugated estriol (uE₃) and dimeric inhibin A (INH) were associated with GDM. The addition of PAPP-A only and PAPP-A, uE₃, and INH to maternal characteristics resulted in small, yet significant, increases in area under the receiver operating characteristic curve (AUC) (maternal characteristics only: AUC 0.714 (95% CI 0.703-0.724), maternal characteristics + PAPP-A: AUC 0.718 (95% CI 0.707-0.728), maternal characteristics + PAPP-A, uE₃, and INH: AUC 0.722 (0.712-0.733)); however, no net improvement in classification was observed.

CONCLUSIONS

PAPP-A, uE₃, and INH have limited clinical utility for prediction of GDM risk in nulliparous women. Utility of other readily accessible clinical biomarkers in predicting GDM risk warrants further investigation.

External validation and clinical utility of prognostic prediction models for gestational diabetes mellitus: A prospective cohort study

Introduction

We performed an independent validation study of all published first trimester prediction models, containing non‐invasive predictors, for the risk of gestational diabetes mellitus. Furthermore, the clinical potential of the best performing models was evaluated.

Material and methods

Systemically selected prediction models from the literature were validated in a Dutch prospective cohort using data from Expect Study I and PRIDE Study. The predictive performance of the models was evaluated by discrimination and calibration. Clinical utility was assessed using decision curve analysis. Screening performance measures were calculated at different risk thresholds for the best model and compared with current selective screening strategies.

Results

The validation cohort included 5260 women. Gestational diabetes mellitus was diagnosed in 127 women (2.4%). The discriminative performance of the 12 included models ranged from 68% to 75%. Nearly all models overestimated the risk. After recalibration, agreement between the observed outcomes and predicted probabilities improved for most models.

Conclusions

The best performing prediction models showed acceptable performance measures and may enable more personalized medicine‐based antenatal care for women at risk of developing gestational diabetes mellitus compared with current applied strategies.

Nomogram for prediction of gestational diabetes mellitus in urban, Chinese, pregnant women

Background

This study sought to develop and validate a nomogram for prediction of gestational diabetes mellitus (GDM) in an urban, Chinese, antenatal population.

Methods

Age, pre-pregnancy body mass index (BMI), fasting plasma glucose (FPG) in the first trimester and diabetes in first degree relatives were incorporated as validated risk factors. A prediction model (nomogram) for GDM was developed using multiple logistic regression analysis, from a retrospective study conducted on 3956 women who underwent their first antenatal visit during 2015 in Shanghai. Performance of the nomogram was assessed through discrimination and calibration. We refined the predicting model with t-distributed stochastic neighbor embedding (t-SNE) to distinguish GDM from non-GDM. The results were validated using bootstrap resampling and a prospective cohort of 6572 women during 2016 at the same institution.

Results

Advanced age, pre-pregnancy BMI, high first-trimester, fasting, plasma glucose, and, a family history of diabetes were positively correlated with the development of GDM. This model had an area under the receiver operating characteristic (ROC) curve of 0.69 [95% CI:0.67–0.72, p < 0.0001]. The calibration curve for probability of GDM showed good consistency between nomogram prediction and actual observation. In the validation cohort, the ROC curve was 0.70 [95% CI: 0.68–0.72, p < 0.0001] and the calibration plot was well calibrated. In exploratory and validation cohorts, the distinct regions of GDM and non-GDM were distinctly separated in the t-SNE, generating transitional boundaries in the image by color difference. Decision curve analysis showed that the model had a positive net benefit at threshold between 0.05 and 0.78.

Conclusions

This study demonstrates the ability of our model to predict the development of GDM in women, during early stage of pregnancy.

Periodontitis and placental growth factor in oral fluids are early pregnancy predictors of gestational diabetes mellitus

BACKGROUND

Gestational diabetes mellitus (GDM) affects around 7% to 10% of all pregnancies. Early detection of predisposition to GDM is the first step in developing efficacious preventive treatment. The objective of the present study was to establish the utility of placental proteins presents in oral fluids (gingival crevicular fluid [GCF] and saliva), and periodontal disease status as early pregnancy predictors of GDM.

METHODS

A nested case control within a prospective cohort was conducted. Pregnant systemically healthy women, aged between 18 and 40 years at 11 to 14 weeks gestation were included. Samples of oral fluids were collected and a complete maternal/obstetric and periodontal history was obtained. The concentration of placental growth factor (PlGF) and soluble Fms-like tyrosine kinase 1 (sFlt-1) were measured by enzyme-linked immunosorbent assay in a nested case control sample of the prospective cohort. Multiple logistic regression models assessed the association. The evaluation of the diagnostic accuracy of the biomarkers was performed through receiver operating characteristic (ROC) curves by calculating the area under the curve (AUC).

RESULTS

There were recruited 212 pregnant women at 11 to 14 weeks of pregnancy, of these, 14 women (i.e., 6.6%) developed GDM, and displayed significant greater bleeding on probing (BOP) [P = 0.0003]; periodontal probing depth (PD) [P = 0.0028]; clinical attachment level (AL) [P = 0.0008] and periodontal inflamed surface area (PISA) [P = 0.0001]. Similarly, initial glycemia and GCF-PlGF concentrations were significantly greater in women with GDM [P = 0.0012, and P = 0.0019, respectively]. When data were subjected to ROC curve analysis, the combination of initial glycemia and GCF-PlGF concentration delivered an area under the ROC curve of 0.897. Multiple logistic regression analyses demonstrate an association between glycemia (OR 1.21, 95% confidence interval [CI] 1.06 to 1.38; P = 0.005) and GCF-PlGF concentrations in women who developed GDM (OR 1.68, CI 1.05 to 2.68 P = 0.03).

CONCLUSIONS

Within the limitations of the present study, the results support that first trimester maternal glycemia combined with GCF-PlGF concentrations could be a surrogate biomarker for the future development of GDM in pre-symptomatic women.

Maternal and neonatal serum expression of the vascular growth factors in hyperglycemia in pregnancy

INTRODUCTION

Hyperglycemia in pregnancy (HIP) occurs in up to 8-17% of pregnancies. Unfavorable impact of the pregnancy induced hyperglycemia on both maternal and fetal tissues is associated with adverse pregnancy outcomes. Vascular growth factors, especially in the early phase of gestation, are considered as one of the most significant molecules that regulate pregnancy course and their serum expression may be altered in patients affected with HIP.

MATERIAL AND METHODS

Fifty-five consecutive pregnant patients who underwent elective cesarean section were incorporated into this study. During the surgery, maternal and cord blood samples were collected. Serum expression levels of vascular growth factors: PlGF, VEGF, THBS-2 and Ang-2 were compared among non-HIP and pregnancies affected by gestational diabetes. Subsequently, laboratory results were correlated with obstetric outcomes.

RESULTS

There were no statistical differences in maternal characteristics, neonatal outcomes and maternal or neonatal serum levels between study and control groups. However, our results revealed significant differences between fetal and maternal levels of VEGF (p = .028 and .0001), THBS-2 (p = .013 and .0014) and Ang-2 (p = .035 and .048) for HIP and non-HIP group, respectively.

CONCLUSIONS

Similar serum expressions of vascular growth factors in and non-HIP and HIP pregnancies point that normal glycemia due to thorough prenatal surveillance may result in normal angio- and vasculogenesis associated with good pregnancy outcomes.

Development and validation of a clinical model for preconception and early pregnancy risk prediction of gestational diabetes mellitus in nulliparous women

Implementation of dietary and lifestyle interventions prior to and early in pregnancy in high risk women has been shown to reduce the risk of gestational diabetes mellitus (GDM) development later in pregnancy. Although numerous risk factors for GDM have been identified, the ability to accurately identify women before or early in pregnancy who could benefit most from these interventions remains limited. As nulliparous women are an under-screened population with risk profiles that differ from their multiparous counterparts, development of a prediction model tailored to nulliparous women may facilitate timely preventive intervention and improve maternal and infant outcomes. We aimed to develop and validate a model for preconception and early pregnancy prediction of gestational diabetes mellitus based on clinical risk factors for nulliparous women. A risk prediction model was built within a large California birth cohort including singleton live birth records from 2007–2012. Model accuracy was assessed both internally and externally, within a cohort of women who delivered at University of Iowa Hospitals and Clinics between 2009–2017, using discrimination and calibration. Differences in predictive accuracy of the model were assessed within specific racial/ethnic groups. The prediction model included five risk factors: race/ethnicity, age at delivery, pre-pregnancy body mass index, family history of diabetes, and pre-existing hypertension. The area under the curve (AUC) for the California internal validation cohort was 0.732 (95% confidence interval (CI) 0.728, 0.735), and 0.710 (95% CI 0.672, 0.749) for the Iowa external validation cohort. The model performed particularly well in Hispanic (AUC 0.739) and Black women (AUC 0.719). Our findings suggest that estimation of a woman’s risk for GDM through model-based incorporation of risk factors accurately identifies those at high risk (i.e., predicted risk >6%) who could benefit from preventive intervention encouraging prompt incorporation of this tool into preconception and prenatal care.

Relationship between elevated serum level of placental growth factor and status of gestational diabetes mellitus

Objective: As only limited and confusing evidence about serum placental growth factor (PlGF) level in gestational diabetes mellitus (GDM) exist in the known literature, the aim of this study was to evaluate the association of maternal serum PlGF level with GDM status.Methods: The pregnant women attending the Obstetrics Outpatient Unit of Hitit University Hospital were screened at 24 and 28 weeks of gestation for GDM according to the suggestions of the American College of Obstetricians and Gynecologists (ACOG). Concisely, all of the low-risk pregnant women were evaluated with a 50 g glucose challenge test (GCT). Women with serum glucose ≥140 mg/dL at 1 h after GCT were subjected to a 100 g oral glucose tolerance test (OGTT). According to the criteria of Carpenter and Coustan, the GDM diagnosis was confirmed. Consequently, a total of 158 pregnant women eligible for inclusion criteria were categorized into two main groups; 76 of the GDM group, 82 of the control group. The demographic characteristic and biochemical parameters of the study population including age, body mass index (BMI), gestational age were recorded at the second trimester. The assays for glucose, insulin, and PlGF were carried out.Results: The mean maternal age of control and GDM groups were 27.9 and 30.5 years, respectively. The parameters such as age, BMI, and gestational age were statistically similar in both groups (p>.05, for all). As expected, serum insulin level and homeostasis model assessment-insulin resistance (HOMA-IR) value were significantly elevated in women with GDM (p<.001, for both). Moreover, maternal PlGF concentration was found to be higher in the GDM group compared to the control group (p=.029). Pearson's correlation analysis of PlGF with other study parameters revealed that there was a negative moderate and significant correlation in only control group (r= -0.416, p<.05). However, this correlation was not detected in the GDM group (r = 0.099, p>.05). None of the variables including maternal age, BMI, insulin, and HOMA-IR showed significant correlations in GDM and control groups.Conclusion: Our findings revealed that maternal serum PlGF level is increased in pregnant women complicated with GDM. Early identification of pregnant women who subsequently will pose GDM risk could improve the pregnancy outcomes.

Prediction of gestational diabetes mellitus in the Born in Guangzhou Cohort Study, China

OBJECTIVE

To assess potential risk factors in identifying women at risk for gestational diabetes mellitus (GDM).

METHODS

The present study included data collected as part of a prospective cohort study, and included women with singleton pregnancies who underwent initial prenatal examination at a tertiary women and children's hospital in Guangzhou, China between February 1, 2012, and December 31, 2015. Maternal characteristics and medical history were investigated to evaluate associations with GDM. A risk factor scoring system for the prediction of GDM was generated using logistic regression.

RESULTS

Overall, 1129 (13.5%) of 8381 women were diagnosed with GDM. Women older than 35 years had a 3.95-fold increased risk of GDM (95% confidence interval 2.80-5.58) compared with women aged 16-25 years; obese women had a 6.54-fold higher risk (95% confidence interval 3.50-12.23) compared with underweight women. A risk scoring system was established based on age, body mass index, family history of diabetes, weight gain, and history of GDM. Screening for women with a score of 12 or more would have reduced the number undergoing oral glucose tolerance testing by 2131 (25.4%) patients with a sensitivity of 87% for GDM detection.

CONCLUSION

The assessment of risk factors for GDM could provide a foundation for improving risk-based screening strategies in this and similar populations.

Sex hormone-binding globulin levels during the first trimester may predict gestational diabetes mellitus development

Aim: To investigate the association of sex hormone-binding globulin (SHBG) levels of early pregnancy with gestational diabetes mellitus (GDM) development. Methods: A total of 443 pregnant women during the first trimester (<12 weeks) were enrolled. SHBG levels were measured. Results: SHBG level was lower in women with GDM than in women without GDM (93.9 ± 34.4 nmol/l vs 128.1 ± 60.3 nmol/l; p = 0.001). Among the four quartiles (Q1–Q4) according to SHBG levels, GDM incidences were 17.5, 27.8, 5.1 and 2.6%, respectively. No differences were found between Q1 and Q2, and Q3 and Q4. The risk of developing GDM among women in Q1 + Q2 compared with Q3 + Q4 was 5.7. Conclusion: Decreased SHBG concentrations during the first trimester may predict GDM development.

Maternal Early Pregnancy Plasma Concentration of 25-Hydroxyvitamin D and Risk of Gestational Diabetes Mellitus

We examined whether 25-Hydroxyvitamin D [25(OH) D] concentrations, measured at the first prenatal visit, would be associated with risk of gestational diabetes mellitus (GDM). From July 2015 to June 2016, consecutive women who admitted to the two-obstetrics center in china were included. Relevant data were collected between 24 and 28 weeks of gestation, including fasting plasma glucose (FPG) and 25(OH) D concentrations at the first prenatal visit and the one-step GDM screened with 75-g oral glucose tolerance test (OGTT). Blood from women at first prenatal visit was available for 827 women and 101 of them developed GDM (12.2%). The GDM distribution across the 25(OH) D quartiles ranged between 3.9% (fourth quartile, Q4) and 26.1% (first quartile, Q1). The median plasma concentration of 25(OH) D at first prenatal visit was significantly lower in women who developed GDM compared with those not developed (p < 0.001). In multivariate models comparing the 25(OH) D of Q1, second (Q2) and third quartiles (Q3) against the Q4, it observed that concentrations of 25(OH) D in Q1 and Q2 were associated with later developed GDM, and risk of GDM was increased by 240 and 48%, respectively. The women group with combined vitamin D deficiency and obesity had an OR of 4.66 [95% CI (2.91-8.15); p < 0.001] for GDM compared to those without vitamin D deficiency and obesity. Low 25(OH) D concentrations at the first prenatal visit were associated with increased risk of GDM and might be useful in identifying women at risk of GDM for performing early prevention strategies.

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.

Human placental growth hormone in normal and abnormal fetal growth

Human placental growth hormone (PGH), encoded by the growth hormone (GH) variant gene on chromosome 17, is expressed in the syncytiotrophoblast and extravillous cytotrophoblast layers of the human placenta. Its maternal serum levels increase throughout pregnancy, and gradually replaces the pulsatile secreted pituitary GH. PGH is also detectable in cord blood and in the amniotic fluid. This placental-origin hormone stimulates glyconeogenesis, lipolysis and anabolism in maternal organs, and influences fetal growth, placental development and maternal adaptation to pregnancy. The majority of these actions are performed indirectly by regulating maternal insulin-like growth factor-I levels, while the extravillous trophoblast involvement indicates a direct effect on placental development, as it stimulates trophoblast invasiveness and function via a potential combination of autocrine and paracrine mechanisms. The current review focuses on the role of PGH in fetal growth. In addition, the association of PGH alterations in maternal circulation and placental expression in pregnancy complications associated with abnormal fetal growth is briefly reviewed.

Early Pregnancy Biochemical Predictors of Gestational Diabetes Mellitus

PURPOSE OF REVIEW

Universal oral glucose tolerance-based screening is employed to identify pregnant women with gestational diabetes mellitus (GDM), as treatment of this condition decreases the risk of associated complications. A simple and accurate blood test which identifies women at low or high risk for GDM in the first trimester would have the potential to decrease costs and improve outcomes through prevention or treatment. This review summarizes published data on early pregnancy biomarkers which have been tested as predictors of GDM.

RECENT FINDINGS

A large number of first-trimester biochemical predictors of GDM have been reported, mostly in small case-control studies. These include glycemic markers (fasting glucose, post-load glucose, hemoglobin A1C), inflammatory markers (C-reactive protein, tumor necrosis factor-alpha), insulin resistance markers (fasting insulin, sex hormone-binding globulin), adipocyte-derived markers (adiponectin, leptin), placenta-derived markers (follistatin-like-3, placental growth factor, placental exosomes), and others (e.g., glycosylated fibronectin, soluble (pro)renin receptor, alanine aminotransferase, ferritin). A few large studies suggest that first-trimester fasting glucose or hemoglobin A1C may be useful for identifying women who would benefit from early GDM treatment. To translate the findings from observational studies of first-trimester biomarkers for GDM to clinical practice, trials or cost-effectiveness analyses of screening and treatment strategies based on these novel biomarkers are needed.

Prediction models for the risk of gestational diabetes: a systematic review

BACKGROUND

Numerous prediction models for gestational diabetes mellitus (GDM) have been developed, but their methodological quality is unknown. The objective is to systematically review all studies describing first-trimester prediction models for GDM and to assess their methodological quality.

METHODS

MEDLINE and EMBASE were searched until December 2014. Key words for GDM, first trimester of pregnancy, and prediction modeling studies were combined. Prediction models for GDM performed up to 14 weeks of gestation that only include routinely measured predictors were eligible.Data was extracted by the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). Data on risk predictors and performance measures were also extracted. Each study was scored for risk of bias.

RESULTS

Our search yielded 7761 articles, of which 17 were eligible for review (14 development studies and 3 external validation studies). The definition and prevalence of GDM varied widely across studies. Maternal age and body mass index were the most common predictors. Discrimination was acceptable for all studies. Calibration was reported for four studies. Risk of bias for participant selection, predictor assessment, and outcome assessment was low in general. Moderate to high risk of bias was seen for the number of events, attrition, and analysis.

CONCLUSIONS

Most studies showed moderate to low methodological quality, and few prediction models for GDM have been externally validated. External validation is recommended to enhance generalizability and assess their true value in clinical practice.

Early Antenatal Prediction of Gestational Diabetes in Obese Women: Development of Prediction Tools for Targeted Intervention

All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 15+0-18+6 weeks' gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95%CI 0.68-0.74). This increased to 0.77 (95%CI 0.73-0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74-0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described which could enable targeted interventions for GDM prevention in women who will benefit the most.

Maternal TSH level and TPOAb status in early pregnancy and their relationship to the risk of gestational diabetes mellitus

Subclinical hypothyroidism is common in pregnant women and often related to adverse pregnancy outcomes, but its relationship with gestational diabetes remains controversial. In particular, the impact of thyroperoxidase antibodies status on the relationship between subclinical hypothyroidism and gestational diabetes is not clear. We investigated the association between combined thyroid stimulating hormone (TSH) level and thyroperoxidase antibodies status in early pregnancy (<20 weeks of gestation) and gestational diabetes mellitus. A total of 7084 pregnant women met the inclusion criteria, which included thyroperoxidase antibodies-positive subclinical hypothyroidism [TSH(H)TPOAb(+)] (n = 78), thyroperoxidase antibodies-negative subclinical hypothyroidism [TSH(H)TPOAb(-)] (n = 281), thyroperoxidase antibodies-positive euthyroidism [TSH(N)TPOAb(+)] (n = 648), and thyroperoxidase antibodies-negative euthyroidism [TSH(N)TPOAb(-)] (n = 6077). Of the 7084 cases included in our study, 1141 cases were diagnosed with gestational diabetes mellitus at 24-28 weeks of pregnancy. The prevalence of gestational diabetes mellitus in TSH(N)TPOAb(-), TSH(H)TPOAb(-), TSH(N)TPOAb(+), and TSH(H)TPOAb(+) was 14.65, 19.57, 24.85, and 46.15 %, respectively. Compared with TSH(N)TPOAb(-) women, the risk of gestational diabetes mellitus was increased in all other groups of women in early pregnancy. After dividing early pregnancy into first and second trimesters, we found that TSH(H)TPOAb(-) women in the first trimester do not show this increase. Our study suggests that subclinical hypothyroidism and thyroperoxidase antibodies-positive euthyroidism in early pregnancy are associated with an increased risk of gestational diabetes mellitus.

Assessment of body composition in Wistar rat offspring by DXA in relation to prenatal and postnatal nutritional manipulation

BACKGROUND

This experimental study aims to investigate the impact of combinations of prenatal and postnatal food manipulation on body composition in rat offspring.

METHODS

On day 12 of gestation, 100 timed pregnant rats were randomized into two nutritional groups: standard laboratory and 50% starved. Pups born to starved mothers were subdivided, based on birthweight (BiW), into fetal growth restricted (FGR) and non-FGR. Pups were born on day 21, cross-fostered, then left undisturbed lactating until the 26th postnatal day when they underwent dual-energy X-ray absorptiometry (DXA) examination.

RESULTS

Prenatally control-fed animals had a significantly greater body weight at 26 d postnatally than the prenatally starved groups, irrespective of their postnatal diet (P < 0.001). Postnatal control diet was associated with significantly increased abdominal and total fat in non-FGR compared to FGR rats (P < 0.001). non-FGR/CONTROL rats showed higher values of abdominal fat than prenatally starved animals that were starved postnatally irrespective of their birth weight (P < 0.001). Postnatal control diet significantly increased total bone mineral content (BMC), head BMC, head area, abdominal BMC in non-FGR compared to FGR rats (P < 0.001).

CONCLUSION

Interaction between prenatal and postnatal nutrition affects growth, abdominal adiposity, and bone accrual in Wistar rats' offspring at 26 d of life.

Positive Correlation between Enhanced Expression of TLR4/MyD88/NF-κB with Insulin Resistance in Placentae of Gestational Diabetes Mellitus

Insulin resistance (IR) is a critical factor of the pathophysiology of Gestational diabetes mellitus (GDM). Studies on key organs involved in IR, such as livers and adipose tissues, showed that Toll-like receptor 4 (TLR4) can regulate insulin sensitivity. As a maternal-fetal interface with multi-functions, placentae could contribute to the development of IR for GDM. Thus, we investigated the expressions of TLR4/Myeloid Differentiation factor 88 (MyD88)/Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-kB) in term placentae from 33 GDM women and 36 healthy pregnant women with normal glucose tolerance, evaluated local and systemic IR and furthermore identified the association between placental TLR4 and IR. TLR4 protein was expressed in various cells of term placenta, particularly in syncytiotrophoblast of villi. Compared with normal pregnancy, the expression of TLR4/MyD88/NF-kB pathway increased in the placenta of GDM (p<0.05), and these differences were more pronounced in the maternal section of the placenta and the syncytiotrophoblast of villi. In addition, more severe IR was observed in the placenta of GDM patients than the control group, evidenced with higher pIRS-1(ser312) (p<0.001) and lower IRS-1 (p<0.05) as well as pAkt proteins (p<0.01). The expression of TLR4 in placentae is positively correlated with local IR (pIRS-1: r = 0.76, p <0.001 and pAkt: r = -0.47, p <0.001) and maternal fasting (r = 0.42, p <0.01), one-hour (r = 0.52, p <0.01) and two-hour glucose (r = 0.54, p <0.01) at OGTT. We found an that enhanced expression of the TLR4-MyD88-NF-kB pathway occurs in GDM placentae, which positively correlates with heightened local IR in placentae and higher maternal hyperglycemia. The TLR4/MyD88/NF-kB pathway may play a potential role in the development of IR in placentae of GDM.

Thiol/disulfide homeostasis in predicting adverse perinatal outcomes at 24-28 weeks of pregnancy in gestational diabetes

OBJECTIVE

The main aim of this study was to investigate thiol/disulfide homeostasis at 24-28 weeks of pregnancy and to evaluate whether it is predictive for adverse perinatal outcomes or not in gestational diabetes mellitus (GDM).

METHODS

A total of 110 pregnant women at 24-28 weeks of pregnancy (74 GDM patients and 36 age- and BMI-matched healthy pregnant women) were enrolled in this prospective case-control study. Thiol/disulfide homeostasis was evaluated with a novel spectrophotometric method to determine if there is an association with adverse perinatal outcomes in GDM, by using logistic regression analysis.

RESULTS

GDM patients, with decreased native thiol levels at 24-28 weeks (OR: 4.890, 95% CI: 1.355-5.764, p = 0.015) and with higher pre-pregnancy BMI (OR: 1.280, 95% CI: 1.072-1.528, p = 0.006), were found to be at increased risk of adverse perinatal outcomes in GDM. There were no statistically significant differences in thiol/disulfide homeostasis between diet- and insulin-treated GDM subgroups. Additionally, 1-h and 2-h glucose levels on 100 g OGTT were found to be predictive for the insulin need in achieving good glycemic control in GDM (OR: 1.022, 95% CI: 1.005-1.038, p = 0.010 and OR: 1.019, 95% CI: 1.004-1.035, p = 0.015).

CONCLUSIONS

GDM patients, with decreased native thiol levels at 24-28 weeks of pregnancy and with higher pre-pregnancy BMI, have an increased risk of possible adverse perinatal outcomes. Also, increased 1-h and 2-h glucose levels on 100 g OGTT can predict the need for insulin treatment for GDM.

First-trimester biochemical markers of placentation in screening for gestational diabetes mellitus

OBJECTIVE

To investigate whether first-trimester biochemical markers of placentation, including pregnancy-associated plasma protein-A (PAPP-A) and placental growth factor (PLGF), are altered in women that subsequently develop gestational diabetes mellitus (GDM) and to examine their potential value in improving the performance of screening for GDM by maternal characteristics and medical history.

METHODS

The study population of 31,225 singleton pregnancies, including 787 cases that developed GDM, was drawn from women undergoing routine prospective screening for pregnancy complications at 11-13 weeks' gestation. Maternal serum PAPP-A and PLGF were measured and the levels were expressed as multiples of the median (MoM) after adjustment for maternal characteristics and medical history. The performance of screening for GDM by maternal factors and MoM values of PAPP-A and PLGF was evaluated by receiver operating characteristic (ROC) curves.

RESULTS

In the GDM group, compared to the unaffected group, the median PAPP-A was reduced (0.949, 95% CI 0.913-0.987 MoM) (p=0.0009) and median PLGF was increased (1.053, 95% CI 1.023-1.083 MoM) (p=0.004). The performance of screening for GDM by maternal factors was not improved by the addition of PAPP-A and/or PLGF.

CONCLUSIONS

First trimester maternal serum PAPP-A and PLGF are not useful in screening for GDM.

Maternal serum osteocalcin at 11-14 weeks of gestation in gestational diabetes mellitus

BACKGROUND

Recent studies support that osteocalcin (OC), apart from its skeletal role, is implicated in glucose homoeostasis. Aims of this study were to examine the first-trimester maternal serum concentrations of OC in pregnancies that developed gestational diabetes mellitus (GDM) and to create a first-trimester prediction model for GDM.

DESIGN

Case-control study in a prospective cohort of pregnant women. Maternal serum levels of OC were measured in 40 cases that developed GDM and 94 unaffected controls. First-trimester biophysical parameters, biochemical indices, maternal-pregnancy characteristics, and OC concentrations were assessed in relation to GDM occurrence.

RESULTS

In the GDM group, first-trimester OC serum levels were increased compared to the control group (mean = 8·81 ng/mL, SD = 2·59 vs. mean = 7·34 ng/ml, SD = 3·04, P = 0·0058). Osteocalcin was independent of first-trimester biophysical and biochemical indices. Osteocalcin alone (OR = 1·21, CI: 1·02-1·43, P = 0·023) was a significant predictor of GDM [Model R(2) = 0·04, area under the curve (AUC) = 0·61, CI: 0·55-0·72, P < 0·001]. The combination of maternal and pregnancy characteristics with OC resulted in an improved prediction model for GDM (Model R(2) = 0·21, AUC = 0·80, CI: 0·71-0·88, P < 0·001). The combined model yields a sensitivity of 72·2% for 25% false-positive rate.

CONCLUSIONS

First-trimester maternal serum levels of OC are increased in GDM pregnancies. Osteocalcin combined with maternal and pregnancy characteristics provides an effective screening for GDM at 11-14 weeks.

First-Trimester Placental Growth Factor in Screening for Gestational Diabetes

OBJECTIVE

The aim of this study was first to assess whether first-trimester serum concentrations of placental growth factor (PlGF) differ between patients with and without gestational diabetes (GDM) and second to test whether there is a correlation between glycosylated hemoglobin (HbA1c), a factor recently shown to be useful in predicting GDM, and PlGF.

METHODS

PlGF was measured at 8-14 weeks with the Kryptor Immunoassay Analyzer (Brahms, Berlin, Germany). Absolute values were converted to multiples of the median using the software provided by the Fetal Medicine Foundation London. GDM was diagnosed using internationally accepted criteria. HbA1c levels were quantified using the TOSOH G7 automated hemoglobin analyzer.

RESULTS

From January to December 2014, 328 women were included in the study, 51 (15.5%) of whom developed GDM. First-trimester PlGF quantification does not discriminate between women at risk to develop GDM and controls, while HbA1c is able to do so. No correlation was found between PlGF and HbA1c.

CONCLUSION

Our findings do not lend support to the hypothesis that early PlGF values are different in women who later develop GDM.

Prediction of gestational diabetes mellitus by first trimester serum secreted frizzle-related protein-5 levels

OBJECTIVE

The main aim of this study was to investigate the first trimester maternal serum secreted frizzle-related protein-5 (Sfrp-5) levels and to evaluate the predictive value on the subsequently developed gestational diabetes mellitus (GDM).

METHODS

A total of 40 pregnant women who subsequently developed GDM and 44 age- and pre-pregnancy BMI-matched healthy pregnant women were enrolled in this prospective case-control study. First trimester serum Sfrp-5 levels were evaluated to determine if there is an association with the onset of GDM, by using logistic regression analysis.

RESULTS

Decreased first trimester serum Sfrp-5 levels (OR = 14.332, 95%CI: 4.166-49.301, p < 0.001) were found to be significantly associated with the increased risk of GDM. There were no statistically significant differences in serum Sfrp-5 levels between the diet- and insulin-treated GDM groups and also serum Sfrp-5 levels were not found to be predictive for adverse perinatal outcomes (p > 0.05).

CONCLUSIONS

Decreased first trimester serum Sfrp-5 levels are significantly associated with the increased risk of GDM.

The first trimester: prediction and prevention of the great obstetrical syndromes

A number of groups are currently examining the potential of screening for pre-eclampsia and gestational diabetes at 12 weeks' gestation. This can be performed at the time of combined first-trimester screening for aneuploidy using a similar method of regression analysis to combine multiple demographic and investigative factors. At present, research into the prediction of pre-eclampsia is more robust and is associated with the potential for therapeutic intervention that can reduce the prevalence of early-onset pre-eclampsia and improve maternal and neonatal outcomes.