Prediction of gestational diabetes mellitus in the first trimester: comparison of maternal fetuin-A, N-terminal proatrial natriuretic peptide, high-sensitivity C-reactive protein, and fasting glucose levels

Analysis of Risk Factors Associated with Gestational Diabetes Mellitus: A Retrospective Case-Control Study

Objective

Gestational diabetes mellitus (GDM) is a complication of abnormal glucose tolerance during pregnancy, with incidence is on the rise. There are inconsistent results on the risks of GDM and it has not been reported in our region. The purpose of this study is to explore the risk factors of GDM.

Methods

A total of 383 pregnant women were analyzed, including 67 (17.5%) pregnant women with GDM and 316 (82.5%) with normal glucose tolerance (NGT). The relationship of personal history, family history and reproductive history of pregnant women, the levels of alpha-fetoprotein (AFP), human chorionic gonadotropin (HCG), inflammatory markers in blood cell analysis at the first prenatal examination, and fetal ultrasound indices and the risk of GDM were analyzed.

Results

The fetal biparietal diameter, head circumference, and femur length were negatively correlated with HCG level, but not inflammatory markers. The proportion of pregnant women aged ≥30 years old, body mass index (BMI) in early pregnancy≥24.0 kg/m2, history of polycystic ovary syndrome (PCOS), cesarean section, adverse pregnancy, and oral contraceptive use, and pregnant women who conceived through assisted reproduction in GDM group were higher than those in NGT group. Logistic regression analysis showed that age of pregnant woman ≥30 years old (≥30 vs <30 years old, odds ratio (OR): 2.142, 95% confidence interval (CI): 1.183-3.878, p=0.012), BMI≥24.0 kg/m2 (≥24.0 kg/m2 vs 18.5-23.9 kg/m2, OR: 1.887, 95% CI: 1.041-3.420, p=0.036), history of adverse pregnancy (yes vs no, OR: 1.969, 95% CI: 1.022-3.794, p=0.043), and history of oral contraceptive use (yes vs no, OR: 2.868, 95% CI: 1.046-7.863, p=0.041) were associated with GDM.

Conclusion

Age of pregnant woman ≥30 years old, BMI≥24.0 kg/m2, history of adverse pregnancy and oral contraceptive use were independent risk factors for GDM.

Prediction of gestational diabetes mellitus by multiple biomarkers at early gestation

BACKGROUND

It remains unclear which early gestational biomarkers can be used in predicting later development of gestational diabetes mellitus (GDM). We sought to identify the optimal combination of early gestational biomarkers in predicting GDM in machine learning (ML) models.

METHODS

This was a nested case-control study including 100 pairs of GDM and euglycemic (control) pregnancies in the Early Life Plan cohort in Shanghai, China. High sensitivity C reactive protein, sex hormone binding globulin, insulin-like growth factor I, IGF binding protein 2 (IGFBP-2), total and high molecular weight adiponectin and glycosylated fibronectin concentrations were measured in serum samples at 11-14 weeks of gestation. Routine first-trimester blood test biomarkers included fasting plasma glucose (FPG), serum lipids and thyroid hormones. Five ML models [stepwise logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, support vector machine and k-nearest neighbor] were employed to predict GDM. The study subjects were randomly split into two sets for model development (training set, n = 70 GDM/control pairs) and validation (testing set: n = 30 GDM/control pairs). Model performance was evaluated by the area under the curve (AUC) in receiver operating characteristics.

RESULTS

FPG and IGFBP-2 were consistently selected as predictors of GDM in all ML models. The random forest model including FPG and IGFBP-2 performed the best (AUC 0.80, accuracy 0.72, sensitivity 0.87, specificity 0.57). Adding more predictors did not improve the discriminant power.

CONCLUSION

The combination of FPG and IGFBP-2 at early gestation (11-14 weeks) could predict later development of GDM with moderate discriminant power. Further validation studies are warranted to assess the utility of this simple combination model in other independent cohorts.

Fetal pancreas size and maternal serum biomarkers glycated albumin and insulin-regulated aminopeptidase provide no potential for early prediction of gestational diabetes mellitus

PURPOSE

We aimed to determine the predictive values of fetal pancreas size and maternal serum biomarkers glycated albumin (GA) and insulin-regulated aminopeptidase (IRAP) for gestational diabetes mellitus (GDM).

MATERIALS AND METHODS

In this prospective observational study including 109 pregnant women, the fetal pancreas size and maternal serum biomarkers GA and IRAP were measured at the gestational age of 20-22 weeks and later at the gestational age of 24-28 weeks, in 19 participants of them, GDM was confirmed with the 75-g oral glucose tolerance test (OGTT) and the fetal pancreas size was measured in all the participants again.

RESULTS

The median fetal pancreas sizes were significantly higher in women with or without GDM when measured at the 24-28 weeks of pregnancy compared to those at the 20-22 weeks of pregnancy (p < 0.05). At both of the 20-22 and 24-28 weeks of pregnancy, the median values of fetal pancreas sizes in the women with or without GDM were found comparable (p > 0.05). There were no significant differences between pregnant women with or without GDM regarding maternal serum biomarkers GA and IRAP (p > 0.05). Multivariate logistic regression analysis revealed no meaningful association of study parameters with the development of GDM.

CONCLUSION

The fetal pancreas size and maternal serum biomarkers GA and IRAP provide no potential for early prediction of GDM at the 20-22 weeks of gestation. Further studies, including serial measurement of these parameters during the second and third trimesters of GDM pregnancies, may clarify their role in the antenatal care of women with GDM.

CLINICAL TRIALS

NCT05392231.

Impact of inflammatory factors, hemoglobin A1c, and platelet parameters in gestational diabetes mellitus

PURPOSE

The aim of this study was to evaluate the relationship among inflammatory cytokines including hypersensitive C-reactive protein (hs-CRP) and interleukin-6 (IL-6), glycated hemoglobin A1c (HbA1c), and platelet distribution width (PDW) in women with gestational diabetes mellitus (GDM).

METHODS

Data on 191 pregnant women (96 women with GDM; 95 healthy controls) were extracted from routine prenatal examination records in Nanjing, China. Fasting concentrations of hs-CRP, IL-6, HbA1c, blood cell indices, and glucose at 24-28th gestational weeks were determined.

RESULTS

The levels of hs-CRP, IL-6, FPG, PG1h, PG2h, HbA1c, RBC, and PDW significantly were increased (P < 0.05) in GDM group. hs-CRP had a positive correlation with HbA1c and PLT (P < 0.05). The odds ratios of HbA1c and PDW were 7.817 (95% CI 1.921-31.816, P = 0.004) and 1.523 (95% CI 1.158-2.002, P = 0.003), respectively. Furthermore, AUC of the combined diagnosis of GDM including HbA1c, FPG, and PDW reached 0.754, with specificity of 80.0% and sensitivity of 60.4%.

CONCLUSION

Our findings support that elevated levels of hs-CRP, IL-6, HbA1c, and PDW at 24-28th gestational weeks even within the conventional normal range, may be implicated in the pathogenesis of GDM and their evaluation should be part of prenatal care routine.

Use of oral glucose tolerance testing and HbA1c at 6-14 gestational weeks to predict gestational diabetes mellitus in high-risk women

PURPOSE

To study the prediction of gestational diabetes mellitus (GDM) in high-risk pregnant women by testing fasting blood glucose, 1-h(1hPG) and 2-h plasma glucose (2hPG) after an oral glucose tolerance test, and glycated hemoglobin (HbA1c) in early pregnancy (6-14 weeks).

METHODS

We recruited 1311 pregnant women at high risk for diabetes from the Obstetrics Clinic of Daxing District People's Hospital between June 2017 and December 2019. The tests performed during the first trimester included fasting blood glucose (FPG), HbA1c, and 75-g oral glucose tolerance test (OGTT) with 1hPG and 2hPG. Seventy-three pregnant women diagnosed with pregestational diabetes mellitus (PGDM) early in pregnancy and 36 who were missed in the second trimester were excluded. A total of 1202 women were followed up until 24-28 weeks for GDM. The receiver operating characteristic (ROC) and area under the ROC curve (AUC) were calculated to determine the predictive values of FPG, 1hPG, 2hPG, and HbA1c for GDM in early pregnancy in high-risk pregnant women.

RESULTS

The AUC for 1hPG for the prediction of GDM in high-risk pregnant women was greater than those for FPG, 2hPG, and HbA1c. All differences were significant. The AUCs for the predictive values of FPG, 1hPG, 2hPG, and HbA1c in high-risk pregnant women were 0.63, 0.76, 0.71, and 0.67, respectively. The prevalence of PGDM among pregnant women at high risk of diabetes was 5.6%.

CONCLUSION

First-trimester levels of FPG, 1hPG, 2hPG, and HbA1c in high-risk women are significant predictors of GDM, with 1hPG having the most significant predictive value.

COVID-19 pandemic: Impact on gestational diabetes mellitus prevalence

AIM

Although an increased risk of gestational diabetes mellitus (GDM) has been noted in women exposed to stressful conditions and traumatic events, limited information is available about such risk in the context of the COVID-19 pandemic.

METHODS

The study was designed as a non-concurrent case-control study on the prevalence of GDM, defined according to IADPSG 2010, in women giving birth during the COVID-19 pandemic in the hot spot of Northeast Italy from March 9th to May 18th, 2020, with an antecedent puerperae-matched group whose women had given birth in 2019.

RESULTS

Analysis revealed that during the COVID-19 pandemic in 2020, GDM prevalence was significantly higher than in 2019 (GDM, 48/533, 9 vs 86/637, 13.5%, p = 0.01), as illustrated by a higher GDM prevalence in 5/6 months of the final semester of 2020. In addition, logistic regression analysisconfirmed a statistically significant temporal relationship between experiencing the lockdown during the first trimester of gestation and later GDM incidence (t = 2.765, P = 0.012), with an 34% increase in mean number of GDM diagnoses per month (antilog of the parameter = 1.34).

CONCLUSION

The COVID-19 pandemic negatively impacted GDM prevalence in 2020 compared to 2019, especially for pregnant women in the 1st trimester of gestation.

The Role of Afamin and Other Trace Elements in the Prediction of GDM: a Tertiary Center Experience

The objective of this study was to evaluate the utility of first trimester maternal serum afamin levels together with vitamin E and various elements (zinc, copper, selenium, and magnesium) for the prediction of gestational diabetes mellitus (GDM). All pregnant women between 11th and 14th weeks of gestation admitted for combined test were asked to participate in the study. A total of 797 women gave permission to participate in the study between January and September 2019. Serum was obtained by centrifugation and samples were frozen and kept at - 80 °C. For final analysis, forty-three GDM patients and forty-four healthy controls were selected. Levels of afamin, vitamin E, zinc, copper, selenium, and magnesium were compared between groups. The mean levels of afamin were found to be higher in women with GDM without statistical significance (63.69 ± 82.33 vs 44.25 ± 32.25 mg/L, p = 0.149). Vitamin E levels were found to be higher in women with GDM compared to controls without any statistical significance (5.04 ± 5.33 vs 4.47 ± 3.83 μg/mL, p = 0.568). While first trimester copper concentrations were higher among diabetic women (187.26 ± 34.78 vs 175.17 ± 30.40 μg/L, p = 0.088), this was not statistically significant. The other element levels (zinc, selenium, and magnesium) were found to be similar between the two groups (p = 0.624, p = 0.088, p = 0.254, p = 0.872, respectively). The results of our study demonstrated that mean levels of afamin, vitamin E, and copper were higher in women with GDM compared to controls. Additionally, first trimester maternal zinc, selenium, and magnesium levels were similar between diabetic and healthy pregnant women. However, more studies are needed to clarify the relationship between blood trace concentrations and GDM.

Early markers of gestational diabetes mellitus: what we know and which way forward?

Women's metabolism during pregnancy undergoes numerous changes that can lead to gestational diabetes mellitus (GDM). The cause and pathogenesis of GDM, a heterogeneous disease, are not completely clear, but GDM is increasing in prevalence and is associated with the modern lifestyle. Most diagnoses of GDM are made via the guidelines from the International Association of Diabetes and Pregnancy Study Groups (IADSPG), which involve an oral glucose tolerance test (OGTT) between 24 and 28 weeks of pregnancy. Diagnosis in this stage of pregnancy can lead to short- and long-term implications for the mother and child. Therefore, there is an urgent need for earlier GDM markers in order to enable prevention and earlier treatment. Routine GDM biomarkers (plasma glucose, insulin, C-peptide, homeostatic model assessment of insulin resistance, and sex hormone-binding globulin) can differentiate between healthy pregnant women and those with GDM but are not suitable for early GDM diagnosis. In this article, we present an overview of the potential early biomarkers for GDM that have been investigated recently. We also present our view of future developments in the laboratory diagnosis of GDM.

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 pregnancy risk factors and future gestational diabetes mellitus

PURPOSE

Gestational diabetes mellitus (GDM) affect about 17% of all pregnancies and is associated with significant short- and long-term health consequences for the mother and her offspring. Early diagnosis and prompt interventions may reduce these adverse outcomes. We aimed to identify first pregnancy characteristics as risk factors for GDM in subsequent pregnancy.

MATERIALS AND METHODS

A population-based nested case-control study was conducted in a large tertiary hospital. The study population included all women with two singleton consecutive pregnancies and deliveries, without GDM in the first pregnancy. Characteristics and complications of the first pregnancy were compared among cases and controls. A multivariable logistic regression model was used to study the association between pregnancy complications (in the first pregnancy) and GDM in the subsequent pregnancy, while adjusting for confounding variables.

RESULTS

A total of 38,750 women were included in the study, of them 1.9% (n = 728) had GDM in their second pregnancy. Mothers with GDM in their second pregnancy were more likely to have the following first pregnancy complications: hypertensive disorders, perinatal mortality, maternal obesity and fetal macrosomia. Results remained significant after adjustment for maternal age and inter-pregnancy interval. Having either one of the complications increased the risk for GDM by 2.33 (adjusted OR = 2.33; 95% CI 1.93-2.82) while a combination of two complications increased GDM risk by 5.38 (adjusted OR = 5.38; 95% CI 2.85-10.17).

CONCLUSIONS

First pregnancy without GDM complicated by hypertensive disorders, perinatal mortality, maternal obesity and fetal macrosomia was associated with an increased risk for GDM in the subsequent pregnancy. Women with these complications may benefit from early detection of GDM in their subsequent pregnancy.

Screening and identification of endometrial proteins as novel potential biomarkers for repeated implantation failure

Inadequate endometrial receptivity may be responsible for the low implantation rate of transferred embryos in in vitro fertilization (IVF) treatments. Patients with repeated implantation failure (RIF) impact the clinical pregnancy rate for IVF. We collected endometrial tissue during the implantation window of hysteroscopy biopsies from September 2016 to December 2019 and clinical data were collected simultaneously. Patients were divided into RIF and pregnant controls group according to pregnancy outcomes. A total of 82 differentially expressed endometrial proteins were identified, including 55 up-regulated proteins (>1.50-fold, P < 0.05) and 27 down-regulated proteins (<0.67-fold, P < 0.05) by iTRAQ labeling coupled with the 2D LC MS/MS technique in the RIF group. String analysis found interactions between these proteins which assembled in two bunches: ribosomal proteins and blood homeostasis proteins. The most significant enriched Gene Ontology terms were negative regulation of hydrolase activity, blood microparticle, and enzyme inhibitor activity. Our results emphasized the corticosteroid-binding globulin and fetuin-A as the specific proteins of endometrial receptivity by Western-blot. Our study provided experimental data to establish the objective indicator of endometrial receptivity, and also provided new insight into the pathogenesis of RIF.

Effects of structured exercise regime on Glycosylated Hemoglobin and C reactive protein in patients with Gestational Diabetes Mellitus - A randomized controlled trial

OBJECTIVES

To evaluate the effects of structured exercise regime on Glycosylated hemoglobin and C reactive protein in patients with gestational diabetes mellitus.

METHODS

This two arm parallel randomized controlled trial was conducted at Fauji Foundation Hospital, Rawalpindi from November 2018 till December 2019 on the 54 diagnosed gestational diabetes mellitus patients (Dropped out=4 Analyzed= 50) with age 20 to 40 years and gestational age from 20 to 36 weeks. Selection was done via convenient sampling technique and randomized into two groups (n=25) by sealed envelope method. Structured exercise regime group received combination of moderate intensity aerobics, stabilization and pelvic floor muscles exercises twice a week for 5 weeks (40 min per session) along with dietary and medical interventions while control group received only medical and dietary interventions with postural education. Demographics, glycosylated hemoglobin and C reactive protein were recorded at baseline then after 5 weeks of intervention. Analysis was done by SPSS 20.

RESULTS

Mean age was 35.92 ± 5.24 years in control group while 34.36 ± 5.21 years in interventional group. Between group analysis for HbA1c showed no significant difference at base line (p >0.05) but showed significant difference (p <0.05) after five weeks' interventions. Similarly, for C reactive protein both groups showed no significant difference (p >0.05) at baseline but after five weeks of interventions showed significant difference (p<0.05).

CONCLUSION

Structured exercise regime helps in reducing values of glycosylated hemoglobin and C reactive protein in patients with gestational diabetes mellitus.

Prognostic models versus single risk factor approach in first-trimester selective screening for gestational diabetes mellitus: a prospective population-based multicentre cohort study

Objectives

To evaluate whether (1) first‐trimester prognostic models for gestational diabetes mellitus (GDM) outperform the currently used single risk factor approach, and (2) a first‐trimester random venous glucose measurement improves model performance.

Design

Prospective population‐based multicentre cohort.

Setting

Thirty‐one independent midwifery practices and six hospitals in the Netherlands.

Population

Women recruited before 14 weeks of gestation without pre‐existing diabetes.

Methods

The single risk factor approach (presence of at least one risk factor: BMI ≥30 kg/m², previous macrosomia, history of GDM, positive first‐degree family history of diabetes, non‐western ethnicity) was compared with the four best performing models in our previously published external validation study (Gabbay‐Benziv 2014, Nanda 2011, Teede 2011, van Leeuwen 2010) with and without the addition of glucose.

Main outcome measures

Discrimination was assessed by c‐statistics, calibration by calibration plots, added value of glucose by the likelihood ratio chi‐square test, net benefit by decision curve analysis and reclassification by reclassification plots.

Results

Of the 3723 women included, a total of 181 (4.9%) developed GDM. The c‐statistics of the prognostic models were higher, ranging from 0.74 to 0.78 without glucose and from 0.78 to 0.80 with glucose, compared with the single risk factor approach (0.72). Models showed adequate calibration, and yielded a higher net benefit than the single risk factor approach for most threshold probabilities. Teede 2011 performed best in the reclassification analysis.

Conclusions

First‐trimester prognostic models seem to outperform the currently used single risk factor approach in screening for GDM, particularly when glucose was added as a predictor.

Tweetable abstract

Prognostic models seem to outperform the currently used single risk factor approach in screening for gestational diabetes.

Prognostic models seem to outperform the currently used single risk factor approach in screening for gestational diabetes.

First-trimester fasting glycemia as a predictor of gestational diabetes (GDM) and adverse pregnancy outcomes

AIMS

Studies to prevent gestational diabetes (GDM) have shown the best results when lifestyle measures have been applied early in pregnancy. We aimed to investigate whether first-trimester fasting plasma glucose (FPG) could predict GDM risk and adverse pregnancy outcomes.

METHODS

A retrospective analysis of prospectively collected data from singleton pregnancies who were attended at our hospital between 2008 and 2018 (n = 27,198) was performed. We included patients with a recorded first-trimester FPG and complete pregnancy data (n = 6845). Patients under 18, with pregestational diabetes or reproductive techniques, were excluded. First-trimester FPG was evaluated as a continuous variable and divided into quartiles. GDM was diagnosed by NDDG criteria. The relationship between first- and second-trimester glucose > 92 mg/dL was also investigated. The relationship between FPG and pregnancy outcomes was assessed in 6150 patients who did not have GDM.

RESULTS

Maternal age was 34.2 ± 3.9 years, BMI 23.1 ± 3.7 kg/m² and mean FPG 83.0 ± 7.3 mg/dL. Glucose quartiles were: ≤ 78, 79-83, 84-87 and ≥ 88 mg/dL. First-trimester FPG predicted the risk of GDM (7%, 8%, 10.2% and 16% in each quartile, p < 0.001) and the risk of second-trimester glucose > 92 mg/dL (2.6%, 3.8%, 6.3% and 11.4% in each quartile, p < 0.001). FPG was significantly associated with LGA (8.2%, 9.3%, 10% and 11.7% in each quartile, p = 0.011) but not with other obstetrical outcomes. In a multivariate analysis including age, BMI, tobacco use, number of pregnancies and weight gained during pregnancy, first-trimester FPG was an independent predictor of LGA.

CONCLUSIONS

First-trimester FPG is an early marker of GDM and LGA.

Fetuin-A and fetal growth in gestational diabetes mellitus

OBJECTIVE

Fetuin-A is a glycoprotein produced by hepatocytes and has been associated with insulin resistance and bone growth in postnatal life. Gestational diabetes mellitus (GDM) is a condition characterized by insulin resistance. It is unclear whether GDM may affect cord blood fetuin-A levels and whether fetuin-A is associated with fetal growth.

RESEARCH DESIGN AND METHODS

In a nested case-control study of 153 matched pairs of neonates of mothers with GDM and euglycemic pregnancies in the Shanghai Birth Cohort, we evaluated cord blood fetuin-A in association with GDM and fetal growth.

RESULTS

Comparing the newborns of GDM versus euglycemic mothers, cord blood fetuin-A concentrations were similar (mean±SD: 783.6±320.0 vs 754.8±281.9 µg/mL, p=0.53), while insulin-like growth factor (IGF)-I (76.6±27.8 ng/mL vs 68.1±25.1 ng/mL, p=0.008) and IGF-II (195.3±32.5 ng/mL vs 187.5±30.8 ng/mL, p=0.042) concentrations were higher. Cord blood fetuin-A was not correlated with insulin, IGF-I or IGF-II. Cord blood fetuin-A was negatively correlated with birth weight (r=-0.19, p=0.025) and birth length (r=-0.24, p=0.005) z scores in GDM pregnancies, while there were no significant correlations in euglycemic pregnancies (tests for interaction: p=0.014 for birth length, p=0.013 for birth length). Adjusting for maternal and neonatal characteristics, the differential associations remained.

CONCLUSIONS

GDM was not associated with cord blood fetuin-A levels. Fetuin-A was negatively associated with fetal growth in GDM but not in euglycemic pregnancies. This novel observation suggests a GDM-conditional negative correlation of fetuin-A with fetal growth.

Effects of dynamic change in fetuin-A levels from the first to the second trimester on insulin resistance and gestational diabetes mellitus: a nested case-control study

OBJECTIVE

To examine the effects of dynamic change in fetuin-A levels before the diagnosis of gestational diabetes mellitus (GDM) on insulin resistance and GDM.

RESEARCH DESIGN AND METHODS

A total of 135 women with GDM and 135 normal glucose tolerance (NGT) women with matched age (±2 years old) and gestational age at taking the oral glucose tolerance test (OGTT) were included in this nested case-control study. Fasting venous blood samples were collected at the prenatal visit of the first trimester and during OGTT of the second trimester. Plasma concentration of fetuin-A and insulin was determined.

RESULTS

The plasma fetuin-A concentration in women with GDM was significantly higher than NGT controls in both the first trimester (medians: 403.0 pg/mL vs 273.4 pg/mL; p<0.05) and the second trimester (medians: 475.7 pg/mL vs 290.8 pg/mL; p<0.05) and notably increased from the first to the second trimester. Multivariate linear regression analysis showed that the change in fetuin-A concentration was associated with the changes in fasting insulin, homeostasis model assessment (HOMA) of insulin resistance, and HOMA of β-cell function (HOMA-β) (p<0.05). The highest quartile of the increase in fetuin-A concentration from the first to the second trimester was associated with a higher risk of developing GDM compared with the lowest quartile (OR 2.14; 95% CI 1.05 to 4.37).

CONCLUSIONS

The dynamic change in fetuin-A levels was associated with the changes in insulin resistance and β-cell function from the first to the second trimester, and was associated with an increased risk of the development of GDM, indicating that fetuin-A could be a biomarker to predict the risk of GDM.

TRIAL REGISTRATION NUMBER

NCT03814395.

Changes of serum pentraxin-3 and hypersensitive CRP levels during pregnancy and their relationship with gestational diabetes mellitus

OBJECTIVE

To investigate the changes of inflammatory factors pentraxin 3 (PTX3) and hypersensitive C-reactive protein (hs-CRP) during pregnancy and their relationship with gestational diabetes mellitus (GDM).

METHODS

The nested case-control study method was used. Eighty non-obese single-pregnant women diagnosed with GDM were included into the case group (GDM, n = 80), together with another eighty pregnant women with normal glucose tolerance were matched in the same period and divided into the control group (CON, n = 80), for detecting multiple biochemical indicators in different pregnancy stages by ELISA.

RESULTS

The serum levels of PTX3 and hs-CRP in pregnant women increased with the increase of gestational age (p < 0.001, p < 0.001). The levels of PTX3 and hs-CRP in group GDM were significantly higher in the middle and late pregnancy stages than group CON (p < 0.01, p < 0.05; p < 0.05, p < 0.05). PTX3 was positively correlated with hs-CRP, body mass index (BMI), fasting plasma glucose (FPG), and homeostasis model assessment of insulin resistance (HOMAIR).

CONCLUSIONS

PTX3 and hs-CRP may be related to the pathogenesis of GDM, and they are significantly increased in the second trimester, which provides a new idea for early prevention and treatment of GDM and risk prediction of long-term cardiovascular diseases.

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.