Comparative study between different biomarkers for early prediction of gestational diabetes mellitus

Advancement in predictive biomarkers for gestational diabetes mellitus diagnosis and related outcomes: a scoping review

OBJECTIVE

Gestational diabetes mellitus (GDM) is a metabolic disorder associated with adverse maternal and neonatal outcomes. While GDM is diagnosed by oral glucose tolerance testing between 24-28 weeks, earlier prediction of risk of developing GDM via circulating biomarkers has the potential to risk-stratify women and implement targeted risk reduction before adverse obstetric outcomes. This scoping review aims to collate biomarkers associated with GDM development, associated perinatal outcome and medication requirement in GDM.

DESIGN

The Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews was used to guide the study.

DATA SOURCES

This review searched for articles on PubMed, Embase, Scopus, Cochrane Central Register of Controlled Trials, the Cumulative Index to Nursing and Allied Health Literature and the Web of Science from January 2013 to February 2023.

ELIGIBILITY CRITERIA

The eligibility criteria included analytical observational studies published in English, focusing on pregnant women with maternal plasma or serum biomarkers collected between 6 and 24 weeks of gestation. Studies were excluded if they evaluated drug effects, non-GDM diabetes types or involved twin pregnancies, microbiota, genetic analyses or non-English publications.

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers extracted data. One reviewer extracted data from papers included in the scoping review using Covidence. From the 8837 retrieved records, 137 studies were included.

RESULTS

A total of 278 biomarkers with significant changes in individuals with GDM compared with controls were identified. The univariate predictive biomarkers exhibited insufficient clinical sensitivity and specificity for predicting GDM, perinatal outcomes, and the necessity of medication. Multivariable models combining maternal risk factors with biomarkers provided more accurate detection but required validation for use in clinical settings.

CONCLUSION

This review recommends further research integrating novel omics technology for building accurate models for predicting GDM, perinatal outcome, and the necessity of medication while considering the optimal testing time.

Inflammatory indices-Systemic Immune-Inflammation Index (SII) and Systemic Inflammatory Response Index (SIRI)-during Pregnancy and Associations with Gestational Diabetes Mellitus

Purpose

Gestational diabetes mellitus (GDM) is a prevalent complication during pregnancy. This study aimed to explore the associations between inflammatory indices during pregnancy and the development of GDM.

Methods

Data from the Fujian Birth Cohort Study between March 2019 and December 2022 were used. Participants who delivered a live-born singleton were included and categorized into GDM and non-GDM groups. Two inflammatory indices, the systemic immune-inflammation index (SII) and systemic inflammatory response index (SIRI), were calculated for each trimester of pregnancy via hematological parameters from complete blood count tests. The distributions of inflammatory indicators across trimesters were compared between the GDM and non-GDM groups. Additionally, multivariable logistic regression models were employed to investigate the associations between inflammatory indices and the incidence of GDM.

Results

A total of 17297 participants were included, 21.2% of whom were diagnosed with GDM. In the first trimester, the median SIIs for the GDM and non-GDM groups were 817.7×109/L and 756.9×109/L, respectively, whereas the median SIRIs were 1.6×109/L and 1.5×109/L, respectively. In both groups, the SII increased to its peak in the second trimester before declining, whereas the SIRI progressively increased throughout pregnancy. The SII and SIRI were greater in the GDM group than in the non-GDM group during the first two trimesters but lower in the third trimester. Nonlinear positive associations between first-trimester SII and SIRI levels and GDM were observed, with extreme quartile odds ratios of 1.32 (95% CI: 1.19, 1.48) and 1.39 (95% CI: 1.24, 1.55), respectively.

Conclusion

The SII and SIRI increased and reached their peak values in the second and third trimesters of pregnancy, respectively. Elevated levels of the SII and SIRI in early pregnancy were linked to an increased risk of GDM, suggesting their potential utility as screening tools for GDM.

Glycated CD59 is a potential biomarker for gestational diabetes mellitus

Objective

To explore the diagnostic value of glycated CD59 (gCD59) in gestational diabetes mellitus (GDM).

Methods

A total of 707 pregnant women who underwent the first visit in the obstetric outpatient clinic of the Affliated Suqian Hospital of Xuzhou Medical University from January 2022 to July 2023 were included, and were grouped according to the International Association of the Diabetes and Pregnancy Study Groups(IADPSG) diagnostic criteria, and finally 113 cases in the GDM group and 559 cases in the normal glucose tolerance (NGT) group were included, and the concentration of gCD59 was determined by enzyme-linked immunosorbent assay (ELISA). The baseline data characteristics of the two groups were compared, the risk factors for GDM were explored by multivariate binary logistic analysis, and the diagnostic value of gCD59 in predicting GDM was explored by receiver operating characteristic (ROC) curve analysis.

Results

The level of gCD59 in the GDM group was significantly higher than that in the NGT group (1.49 SPU vs 0.87 SPU). Multivariate regression analysis showed that gCD59, diastolic blood pressure (DBP) and thyroid stimulating hormone (TSH) were independent risk factors for GDM.The area under the curve (AUC) of gCD59 for the diagnosis of GDM was 0.681 (95% CI: 0.583-0.717), with a sensitivity of 71.7% and a specificity of 58.3%. In combination with fasting glucose, gCD59 effectively diagnosed GDM with higher AUC of 0.871 (95% CI: 0.708-1.000).

Conclusion

gCD59 is an independent risk factor for GDM and a good biomarker for the diagnosis of GDM.

Uric acid and risk of gestational diabetes mellitus: an observational study and mendelian randomization analysis

OBJECTIVE

Our aim was to explore the relationship between serum uric acid (UA) levels in early pregnancy and the development of gestational diabetes mellitus (GDM), and to further explore whether there is a causal relationship.

METHODS

684 pregnant women with GDM and 1162 pregnant women without GDM participated in this study. 311 pregnant women with GDM and 311 matched controls were enrolled in a 1:1 case-control study. We used conditional logistic regression to explore the relationship between UA levels and the risk of developing GDM. The causal relationship between the two was examined by two-sample Mendelian randomization (MR) analysis.

RESULTS

In the 1:1 matched population, the odds ratio (OR) of developing GDM compared with the extreme tertiles of UA levels was 1.967 (95% confidence interval [CI]: 1.475-2.625; P < 0.001). Restricted cubic spline analyses showed a linear relationship between UA and GDM when UA exceeded 222 µmol/L. GDM and UA levels maintained a statistically significant positive correlation in different stratified regression analyses (P < 0.001). However, no evidence of a causal relationship between uric acid and GDM was found by MR analyses with an OR of 1.06 (95% CI: 0.91-1.25) per unit increase in UA.

CONCLUSION

There is a positive correlation between UA levels in early pregnancy and the subsequent risk of developing GDM. However, no genetic evidence was found to support a cause-effect relationship between UA and GDM.

The application of plasma circRAD18 in the prediction of gestational diabetes mellitus (GDM) and its adverse effects

BACKGROUND

In cancer biology, circRAD18 promotes glucose metabolism, potentially indicating its involvement in glucose metabolism-related disorders, such as gestational diabetes mellitus (GDM). The present study investigated the predictive role of circRAD18 in GDM and its potential adverse effects.

METHODS

A total of 482 women who intended to get pregnant in short-term were enrolled. For those who successfully conceived, plasma samples were collected and followed up until delivery to monitor the occurrence of GDM and its associated adverse events. The accumulation of circRAD18 in plasma was analyzed using RT-qPCR. GDM-free curves and ROC curves were plotted to assess the predictive value of plasma circRAD18 for GDM.

RESULTS

After admitting 482 female patients, 388 of them achieved pregnancy within half a year. During the follow-up period, 52 cases were diagnosed with GDM. Compared to non-GDM group (n = 336), the GDM group (n = 52) had a lower accumulation level of circRAD18 on the day of pregnancy confirmation. In addition, low levels of circRAD18 accumulation on that day distinguished potential GDM patients from non-GDM cases. The 388 cases were divided into high and low circRAD18 level groups (n = 194). GDM-free curve analysis showed that patients in the low circRAD18 level group had a higher incidence of GDM compared to the high level group (43/194 vs. 9/194). A close association was found between low levels of plasma circRAD18 and hypertension, but not premature delivery, intrauterine death, malformation, intrauterine infection, miscarriage, macrosomia or intrauterine distress.

CONCLUSION

The reduction in the accumulation of plasma circRAD18 is predictive of GDM and hypertension in pregnant women.

Assessment of potential risk factors associated with gestational diabetes mellitus: evidence from a Mendelian randomization study

Background

Previous research on the association between risk factors and gestational diabetes mellitus (GDM) primarily comprises observational studies with inconclusive results. The objective of this study is to investigate the causal relationship between 108 traits and GDM by employing a two-sample Mendelian randomization (MR) analysis to identify potential risk factors of GDM.

Methods

We conducted MR analyses to explore the relationships between traits and GDM. The genome-wide association studies (GWAS) for traits were primarily based on data from the UK Biobank (UKBB), while the GWAS for GDM utilized data from FinnGen. We employed a false discovery rate (FDR) of 5% to account for multiple comparisons.

Results

The inverse-variance weighted (IVW) method indicated that the genetically predicted 24 risk factors were significantly associated with GDM, such as "Forced expiratory volume in 1-second (FEV1)" (OR=0.76; 95% CI: 0.63, 0.92), "Forced vital capacity (FVC)" (OR=0.74; 95% CI: 0.64, 0.87), "Usual walking pace" (OR=0.19; 95% CI: 0.09, 0.39), "Sex hormone-binding globulin (SHBG)" (OR=0.86; 95% CI: 0.78, 0.94). The sensitivity analyses with MR-Egger and weighted median methods indicated consistent results for most of the trats.

Conclusion

Our study has uncovered a significant causal relationship between 24 risk factors and GDM. These results offer a new theoretical foundation for preventing or mitigating the risks associated with GDM.

Platelet-to-lymphocyte ratio and serum hsCRP levels in third trimester and adverse pregnancy outcomes in women with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a major complication of pregnancy. GDM is associated with a higher risk of adverse pregnancy outcomes (APO). The purpose of this study was to assess the association between third-trimester platelet to lymphocyte ratio (PLR) and high-sensitivity C-reactive protein (hsCRP) concentration and the risk of APO in GDM pregnant women. This study selected 406 non-elderly gestational diabetes patients diagnosed in the Renmin Hospital of Wuhan University from May 2021 to February 2023 as the research objects. According to the presence or absence of APO, they were divided into an APO group (n = 171) and a non-APO group (n = 235). Logistic regression model to evaluate the correlation between PLR and hsCRP and APO in women with GDM; Restricted cubic spline analyses was used to explore nonlinear correlations between PLR or hsCRP and the risk of APO; ROC curve analysis of the diagnostic performance of PLR and hsCRP for APO in women with GDM. APO occurred in 171 of the 406 included participants. Compared with the non-APO group, patients in the APO group had higher PLR and hsCRP levels. The incidence of APO was positively associated with PLR and the hsCRP level in each logistic regression model (P < 0.05). After adjusting for all the risk factors included in this study, restricted cubic spline analyses found that the PLR and the hsCRP level were positively associated with the risk of APO. The levels of PLR and hsCRP in the third trimester are related to the occurrence of APO in women with GDM, and high levels of PLR and hsCRP may indicate the occurrence of APO.

Associations of early pregnancy serum uric acid levels with risk of gestational diabetes and birth outcomes: a retrospective cohort study

BACKGROUND

Previous evidence suggests that higher blood uric acid (UA) levels are associated with adverse cardiovascular outcomes during pregnancy and subsequent birth outcomes. However, it has been relatively unclear whether these associations persist in normotensive pregnant women.

METHODS

The study was based on a retrospective analysis of 18,250 mother-infant pairs in a large obstetric center in China. Serum UA concentrations in early pregnancy (median: 17.6, IQR: 16.3, 18.6 gestational weeks) were assessed. Hyperuricemia was defined as ≥ one standard deviation (SD) of the reference value for the corresponding gestational age. Outcomes of gestational diabetes mellitus (GDM), preterm birth (PB), low birth weight (LBW), macrosomia, small for gestational age (SGA) and large for gestational age (LGA) were extracted from the medical records.

RESULTS

The mean maternal UA level was 0.22 ± 0.05 mmol/L, and 2,896 (15.9%) subjects had hyperuricemia. After adjustment for several covariates, UA was associated with several adverse outcomes. The ORs (95%CI) per one SD increase in serum UA concentration were 1.250 (1.136, 1.277) for GDM, 1.137 (1.060, 1.221) for PB, 1.134 (1.051, 1.223) for LBW, and 1.077 (1.020, 1.137) for SGA, respectively. Similar adverse associations were found between hyperuricemia and GDM, PB (ORs: 1.394 and 1.385, P < 0.001), but not for LBW, macrosomia, SGA, and LGA. Adverse associations tended to be more pronounced in subjects with higher BMI for outcomes including PB, LBW, and SGA (P interaction = 0.001-0.028).

CONCLUSION

Higher UA levels in early pregnancy were associated with higher risk of GDM, PB, LBW, and SGA in normotensive Chinese women.

Untargeted metabolomics of saliva in pregnant women with and without gestational diabetes mellitus and healthy non-pregnant women

Objective

The aim of this study was to compare the differences in salivary metabolites between pregnant women with gestational diabetes mellitus (GDM), healthy pregnant women (HPW), and healthy non-pregnant women (HNPW), and analyze the possible associations between the identified metabolites and gingivitis.

Method

The study included women with GDM (n = 9, mean age 28.9 ± 3.6 years, mean gestational age 30.1 ± 3.2 weeks), HPW (n = 9, mean age 27.9 ± 3.0 years, mean gestational age 28.6 ± 4.7 weeks), and HNPW (n = 9, mean age 27.7 ± 2.1 years). Saliva samples were collected from all participants and were analyzed with LC-MS/MS-based untargeted metabolomic analysis. Metabolite extraction, qualitative and semi-quantitative analysis, and bioinformatics analysis were performed to identify the differential metabolites and metabolic pathways between groups. The identified differential metabolites were further analyzed in an attempt to explore their possible associations with periodontal health and provide evidence for the prevention and treatment of periodontal inflammation during pregnancy.

Results

In positive ion mode, a total of 2,529 molecular features were detected in all samples, 166 differential metabolites were identified between the GDM and HPW groups (89 upregulated and 77 downregulated), 823 differential metabolites were identified between the GDM and HNPW groups (402 upregulated and 421 downregulated), and 647 differential metabolites were identified between the HPW and HNPW groups (351 upregulated and 296 downregulated). In negative ion mode, 983 metabolites were detected in all samples, 49 differential metabolites were identified between the GDM and HPW groups (29 upregulated and 20 downregulated), 341 differential metabolites were identified between the GDM and HNPW groups (167 upregulated and 174 downregulated), and 245 differential metabolites were identified between the HPW and HNPW groups (112 upregulated and 133 downregulated). A total of nine differential metabolites with high confidence levels were identified in both the positive and negative ion modes, namely, L-isoleucine, D-glucose 6-phosphate, docosahexaenoic acid, arachidonic acid, adenosine, adenosine-monophosphate, adenosine 5'-monophosphate, xanthine, and hypoxanthine. Among all pathways enriched by the upregulated differential metabolites, the largest number of pathways were enriched by four differential metabolites, adenosine, adenosine 5'-monophosphate, D-glucose 6-phosphate, and adenosine-monophosphate, and among all pathways enriched by the downregulated differential metabolites, the largest number of pathways were enriched by three differential metabolites, L-isoleucine, xanthine, and arachidonic acid.

Conclusion

Untargeted metabolomic analysis of saliva samples from pregnant women with GDM, HPW, and HNPW identified nine differential metabolites with high confidence. The results are similar to findings from previous metabolomics studies of serum and urine samples, which offer the possibility of using saliva for regular noninvasive testing in the population of pregnant women with and without GDM. Meanwhile, the associations between these identified differential metabolites and gingivitis need to be further validated by subsequent studies.

Serum uric acid and the risk of gestational diabetes mellitus: a systematic review and meta-analysis

AIMS

Serum uric acid (SUA) is considered as a risk factor for gestational diabetes mellitus (GDM). However, current studies showed inconsistent results. This study aimed to explore the relationship between SUA levels and GDM risk.

METHODS

Eligible studies were retrieved from PubMed, Web of Science, Embase, China National Knowledge Infrastructure, and Wanfang databases up to November 1, 2022. The pooled standardized mean difference (SMD) and 95% confidence interval (CI) were used to represent the difference in SUA levels between GDM women and controls. The combined odds ratios (OR) and 95% CI were applied to assess association between SUA levels and GDM risk. Subgroup analyses were conducted on study continents, design, and quality, detection time of SUA, and GDM diagnostic criteria.

RESULTS

Totally 11 studies including five case-control and six cohort studies, in which 80,387 pregnant women with 9815 GDM were included. The overall meta-analysis showed that the mean SUA level in GDM group was significantly higher than in controls (SMD = 0.423, 95%CI = 0.019-0.826, p = .040, I² = 93%). Notably, pregnant women with elevated levels of SUA had a significantly increased risk of GDM (OR = 1.670, 95%CI = 1.184-2.356, p = .0035, I² = 95%). Furthermore, subgroup analysis performed on the detection time of SUA showed a significant difference in the association between SUA and GDM risk within different trimesters (1st trimester: OR = 3.978, 95%CI = 2.177-7.268; 1st to 2nd trimester: OR = 1.340, 95%CI = 1.078-1.667; p between subgroups <.01).

CONCLUSIONS

Elevated SUA was positively associated with GDM risk, particularly in the 1st trimester of pregnancy. Further studies with high quality are required to validate the findings of this study.

Associations of low sex hormone-binding globulin and androgen excess in early pregnancy with fasting and post-prandial hyperglycaemia, gestational diabetes, and its severity

AIMS

We studied whether androgen excess and low sex hormone-binding globulin (SHBG) measured in early pregnancy are independently associated with fasting and post-prandial hyperglycaemia, gestational diabetes (GDM), and its severity.

MATERIALS AND METHODS

This nationwide case-control study included 1045 women with GDM and 963 non-diabetic pregnant controls. We measured testosterone (T) and SHBG from biobanked serum samples (mean 10.7 gestational weeks) and calculated the free androgen index (FAI). We first studied their associations with GDM and secondly with the type of hyperglycaemia (fasting, 1 and 2 h glucose concentrations during the oral glucose tolerance test), early-onset GDM (<20 gestational weeks) and the need for anti-diabetic medication.

RESULTS

After adjustments for gestational weeks at sampling, pre-pregnancy BMI, and age, women with GDM had 3.7% (95% CI 0.1%-7.3%) lower SHBG levels, 3.1% (95% CI 0.1%-6.2%) higher T levels, and 4.6% (95% CI 1.9%-7.3%) higher FAI levels than controls. SHBG was inversely associated with fasting glucose, whereas higher FAI and T were associated with higher post-prandial glucose concentrations. Women with early-onset GDM had 6.7% (95% CI 0.7%-12.7%) lower SHBG levels and women who needed insulin for fasting hyperglycaemia 8.7% (95% CI 1.8%-14.8%) lower SHBG levels than other women with GDM.

CONCLUSIONS

Lower SHBG levels were associated especially with early-onset GDM, higher fasting glucose and insulin treatment, whereas androgen excess was associated with higher post-prandial glucose values. Thus, a low SHBG level may reflect the degree of existing insulin resistance, while androgen excess might impair post-prandial insulin secretion.

First trimester sex hormone-binding globulin predicts gestational diabetes mellitus in a population of Nigerian women

There has been a steady rise in the disease burden of Gestational Diabetes Mellitus (GDM) in the sub-Saharan African region over time. Diagnostic testing for GDM is currently recommended at 24 - 28 weeks of gestation, leaving a narrow window for intervention before delivery. Hence the need for early prediction and preventive intervention. The performance of first trimester serum sex hormone-binding globulin (SHBG) assay as a predictor of GDM was determined by binary logistic regression. Women with GDM (n = 49) had a significantly lower mean first trimester SHBG level (104.7 ± 61.6 nmol/L) than did those without GDM (n = 180; 265.2 ± 141.5 nmol/L; p < .001). First trimester SHBG was significantly negatively correlated (r_pb = -0.460, p value = <.001) with subsequent development of GDM and an area under receiver operator characteristics (ROC) curve of 0.874 (p < .001). A cut-off value of 158.0 nmol/L predictive of GDM had a diagnostic sensitivity of 81.5%, a specificity of 80.1%, and an overall diagnostic efficiency of 80.3%.IMPACT STATEMENTWhat is already known on this subject? GDM is associated with high risk of various complications and is commonly diagnosed at 24-28 weeks of gestation, leaving a narrow window for intervention. The performance of current maternal clinical and demographic risk factor-based prediction approaches is unreliable. Thus, more favourable prediction approaches need to be developed. Previous studies have suggested that SHBG, a readily assessable marker, has potential to predict GDM; however, these studies have mostly involved Caucasian and other non-African populations.What the results of this study add? SHBG may serve as a reliable first trimester screening tool for GDM development in Nigerian women with singleton pregnancies. This study demonstrates that first trimester SHBG can predict GDM development in sub-Saharan African women despite racial, ethnic and geographical differences.What are the implications of these findings for clinical practice and/or further research? Effective first trimester prediction of GDM using SHBG may enable preventive interventions, thereby mitigating the high burden of the disease in the sub-Saharan African region. It may also provide relevant information that may guide adaptation of current management guidelines to ensure effective management of GDM in the region.

Deep Insight of the Pathophysiology of Gestational Diabetes Mellitus

Diabetes mellitus is a severe metabolic disorder, which consistently requires medical care and self-management to restrict complications, such as obesity, kidney damage and cardiovascular diseases. The subtype gestational diabetes mellitus (GDM) occurs during pregnancy, which severely affects both the mother and the growing foetus. Obesity, uncontrolled weight gain and advanced gestational age are the prominent risk factors for GDM, which lead to high rate of perinatal mortality and morbidity. In-depth understanding of the molecular mechanism involved in GDM will help researchers to design drugs for the optimal management of the condition without affecting the mother and foetus. This review article is focused on the molecular mechanism involved in the pathophysiology of GDM and the probable biomarkers, which can be helpful for the early diagnosis of the condition. The early diagnosis of the metabolic disorder, most preferably in first trimester of pregnancy, will lead to its effective long-term management, reducing foetal developmental complications and mortality along with safety measures for the mother.

Molecular biomarkers for gestational diabetes mellitus and postpartum diabetes

ABSTRACT

Gestational diabetes mellitus (GDM) is a growing public health problem worldwide that threatens both maternal and fetal health. Identifying individuals at high risk for GDM and diabetes after GDM is particularly useful for early intervention and prevention of disease progression. In the last decades, a number of studies have used metabolomics, genomics, and proteomic approaches to investigate associations between biomolecules and GDM progression. These studies clearly demonstrate that various biomarkers reflect pathological changes in GDM. The established markers have potential use as screening and diagnostic tools in GDM and in postpartum diabetes research. In the present review, we summarize recent studies of metabolites, single-nucleotide polymorphisms, microRNAs, and proteins associated with GDM and its transition to postpartum diabetes, with a focus on their predictive value in screening and diagnosis.

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

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

Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis

Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as pre-eclampsia and stillbirth. Further, women with GDM have approximately 10 times higher risk of diabetes later in life. Children born to mothers with GDM also face a higher risk of childhood obesity and diabetes later in life. Early prediction/diagnosis of GDM leads to early interventions such as diet and lifestyle, which could mitigate the maternal and fetal complications associated with GDM. However, no biomarkers identified to date have been proven to be effective in the prediction/diagnosis of GDM. Proteomic approaches based on mass spectrometry have been applied in various fields of biomedical research to identify novel biomarkers. Although a number of proteomic studies in GDM now exist, a lack of a comprehensive and up-to-date meta-analysis makes it difficult for researchers to interpret the data in the existing literature. Thus, we undertook a systematic review and meta-analysis on proteomic studies and GDM. We searched MEDLINE, EMBASE, Web of Science and Scopus from inception to January 2022. We searched Medline, Embase, CINHAL and the Cochrane Library, which were searched from inception to February 2021. We included cohort, case-control and observational studies reporting original data investigating the development of GDM compared to a control group. Two independent reviewers selected eligible studies for meta-analysis. Data collection and analyses were performed by two independent reviewers. The PROSPERO registration number is CRD42020185951. Of 120 articles retrieved, 24 studies met the eligibility criteria, comparing a total of 1779 pregnant women (904 GDM and 875 controls). A total of 262 GDM candidate biomarkers (CBs) were identified, with 49 CBs reported in at least two studies. We found 22 highly replicable CBs that were significantly different (nine CBs were upregulated and 12 CBs downregulated) between women with GDM and controls across various proteomic platforms, sample types, blood fractions and time of blood collection and continents. We performed further analyses on blood (plasma/serum) CBs in early pregnancy (first and/or early second trimester) and included studies with more than nine samples (nine studies in total). We found that 11 CBs were significantly upregulated, and 13 CBs significantly downregulated in women with GDM compared to controls. Subsequent pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resources found that these CBs were most strongly linked to pathways related to complement and coagulation cascades. Our findings provide important insights and form a strong foundation for future validation studies to establish reliable biomarkers for GDM.

Preconceptual leptin levels in gestational diabetes and hypertensive pregnancy

Pregnancy - induced hypertension (PIH), preeclampsia (PE), and gestational diabetes (GDM) are common adverse outcomes in pregnancy.

OBJECTIVE

To find out whether preconceptual leptin levels differ in subsequent pregnancy between control vs. GDM and hypertensive pregnancy groups.

MATERIALS AND METHODS

Data was from The Cardiovascular Risk in Young Finns Study and The Medical Birth Register of Finland. Of 293 subjects 71 developed GDM, 27 PIH/PE and 201 were controls.

RESULTS

Leptin was higher in GDM (p < 0.0001) and PIH/PE (p = 0.0002) groups compared to control. GDM group was robust to BMI matching (p = 0,0081).

CONCLUSION

Leptin was higher in GDM (p < 0.0001) and PIH/PE (p = 0.0002) groups compared to control. GDM group was robust to BMI matching (p = 0,0081).

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.

Predictive value of circulating sex hormone-binding globulin for gestational diabetes: a meta-analysis

Aim: To detect predictive value of preconception or early pregnancy sex hormone-binding globulin (SHBG) for subsequent gestational diabetes mellitus (GDM). Materials & methods: We searched Embase, Medline, PubMed, Web of Science and Cochrane library up to January 2020. Studies assessing diagnostic performance of SHBG for GDM diagnosed by well-defined diagnostic criteria using oral glucose tolerance test. Results: Totally seven studies with 1947 women were included and 247 were diagnosed as GDM. SHBG had a combined diagnostic odds ratio of 6.68 (95% CI: 4.58-9.74), sensitivity of 0.70 (95% CI: 0.51-0.84), specificity of 0.74 (95% CI: 0.52-0.88), positive likelihood ratio of 2.49 (95% CI: 1.73-3.57) and negative likelihood ratio of 0.37 (95% CI: 0.23-0.61). The area under the summary receiver operating characteristic curve was 0.78 (95% CI: 0.74-0.82). Conclusion: SHBG had a predictive value for GDM and might improve GDM screening. However, heterogeneity between studies warrants more research into this topic.

The relationship between fasting plasma glucose in the first trimester of pregnancy and the incidence of gestational diabetes in Iran

AIMS

This study aimed to investigate the relationship between fasting plasma glucose in the first trimester of pregnancy and the incidence of gestational diabetes.

METHODS

This descriptive-analytical study was conducted using the merging data from two prospective cohort studies that were carried out from 2015 to 2018 in Ahvaz, southwest of Iran. Logistic regression and ROC curves were used to evaluate the predictive power of risk factors.

RESULTS

Of all 1270 pregnant women studied, 454 (35.75%) had gestational diabetes who were compared with the other 816 (64.25%) healthy women. The area under the curve (AUC) of fasting glucose for the first pregnancy visit was 0.80 (95% CI: 0.76-83), and the optimum fasting glucose cut-off point was 85.5 mg/dL with a sensitivity of 71% and a specificity of 69%. AUC of the combination of fasting glucose at the first visit with body mass index ≥25 kg/m2 and family history of diabetes was calculated to be 0.85 (CI, 0.82-0.88) and 0.84 (CI, 0.79-0.89) respectively.

CONCLUSION

Fasting plasma glucose in the first trimester of pregnancy is a relatively good predictor of gestational diabetes. If this factor is combined with other risks, its diagnostic value will increase.

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.

Inflammatory and Adipokine Status from Early to Midpregnancy in Arab Women and Its Associations with Gestational Diabetes Mellitus

Objective

To examine differences in maternal serum levels of adipokines (adiponectin, leptin, and resistin) and inflammatory markers (tumor necrosis factor-alpha (TNF-α) and interlukin-6 (IL-6)) from early to midpregnancy among Arab women with or without gestational diabetes mellitus (GDM), along with their links to GDM risk.

Methods

This is a multicenter prospective study involving 232 Saudi women attending obstetric care. Both circulating adipokine and markers of inflammation were observed at the first (eight to 12 weeks) and second trimesters (24 to 28 weeks). GDM was screened at 24 to 28 weeks using the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria.

Results

Age and body mass index- (BMI-) matched circulating TNF-α was significantly higher in women with GDM in comparison to non-GDM women (p = 0.01). Adiponectin and resistin significantly decreased from the first to second trimester in women without GDM (p = 0.002 and 0.026, respectively). Leptin presented a significant rise from the first to second trimester in both groups, with a higher increase in women with GDM (p = 0.013). Multivariate logistic regression analysis revealed that TNF-α was significantly correlated with GDM (p = 0.03). However, significance was lost after adjustments for maternal and lifestyle risk factors (OR 23.58 (0.50 to 1119.98), p = 0.11).

Conclusion

Inflammatory and adipocytokine profiles are altered in Arab women with GDM, TNF-α in particular. Further studies are needed to establish whether maternal inflammatory and adipocytokine profile influence fetal levels in the same manner.

Prevalence of Gestational Diabetes Mellitus in the Middle East and North Africa, 2000-2019: A Systematic Review, Meta-Analysis, and Meta-Regression

Women in the Middle East and North Africa (MENA) region are burdened with several risk factors related to gestational diabetes mellitus (GDM) including overweight and high parity. We systematically reviewed the literature and quantified the weighted prevalence of GDM in MENA at the regional, subregional, and national levels. Studies published from 2000 to 2019 reporting the prevalence of GDM in the MENA region were retrieved and were assessed for their eligibility. Overall and subgroup pooled prevalence of GDM was quantified by random-effects meta-analysis. Sources of heterogeneity were investigated by meta-regression. The risk of bias (RoB) was assessed by the National Heart, Lung, and Blood Institute's tool. One hundred and two research articles with 279,202 tested pregnant women for GDM from 16 MENA countries were included. Most of the research reports sourced from Iran (36.3%) and Saudi Arabia (21.6%), with an overall low RoB. In the 16 countries, the pooled prevalence of GDM was 13.0% (95% confidence interval [CI], 11.5-14.6%, I² , 99.3%). Nationally, GDM was highest in Qatar (20.7%, 95% CI, 15.2-26.7% I² , 99.0%), whereas subregionally, GDM was highest in Gulf Cooperation Council (GCC) countries (14.7%, 95% CI, 13.0-16.5%, I² , 99.0%). The prevalence of GDM was high in pregnant women aged ≥30 years (21.9%, 95% CI, 18.5-25.5%, I² , 97.1%), in their third trimester (20.0%, 95% CI, 13.1-27.9%, I² , 98.8%), and who were obese (17.2%, 95% CI, 12.8-22.0%, I² , 93.8%). The prevalence of GDM was 10.6% (95% CI, 8.1-13.4%, I² , 98.9%) in studies conducted before 2009, whereas it was 14.0% (95% CI, 12.1-16.0%, I² , 99.3%) in studies conducted in or after 2010. Pregnant women in the MENA region are burdened with a substantial prevalence of GDM, particularly in GCC and North African countries. Findings have implications for maternal health in the MENA region and call for advocacy to unify GDM diagnostic criteria.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42018100629.

Proteome profiling of gestational diabetes mellitus at 16-18 weeks revealed by LC-MS/MS

BACKGROUND

The practices used to diagnose gestational diabetes mellitus (GDM) could only be carried out around the time of detectable symptoms, and predictive capacity is little.

METHODS

LC-MS/MS was conducted to explore overview proteomics for GDM complicated pregnant woman at 16-18 gestation weeks, while normal pregnant for control. Enzyme-linked immunosorbent assay was further applied in an independent cohort of 15 GDM cases and 15 controls for verification.

RESULTS

The results indicated that 24 protein expression levels were significantly changed in GDM group samples, and inflammation, oxidative stress, insulin resistance, blood coagulation, and lipid homeostasis were associated with GDM. The abnormal expression of CRP and IGFBP2 was verified in the first-trimester maternal plasma in women who subsequently developed GDM.

CONCLUSIONS

This study not only identified 24 potential predictive biomarkers for GDM also provided a global overview of protein rearrangements induced by GDM.

Hypovitaminosis D Is Associated with Some Metabolic Indices in Gestational Diabetes Mellitus

BACKGROUND

Gestational diabetes mellitus (GDM), a pregnancy complication, is defined as any degree of glucose intolerance with onset or first recognition during pregnancy. Vitamin D deficiency and insufficiency has recently been recognized as a contributing factor to the pathogenesis of GDM, and this link might be associated with hyperglycemia, insulin resistance, and inflammation, which are implicated in GDM.

OBJECTIVES

This study aims at investigating the relationship between vitamin D, fasting plasma glucose (FPG), insulin, zinc, ferritin, and high-sensitivity C-reactive protein (CRP) in GDM.

METHOD

A case-control study in which 80 women attending the antenatal clinic of University College Hospital (UCH), Ibadan, Nigeria, were recruited; the women were grouped into controls (40 nondiabetic pregnant women) and cases (40 pregnant women with GDM). Blood samples were taken at the second trimester, and metabolites were quantified by standard laboratory methods. Student's t test and Pearson correlation were used to compare variables and determine the relationship between variables, respectively.

RESULTS

Results showed significant (p < 0.05) low levels of serum vitamin D and zinc, and significant (p < 0.05) higher levels of FPG and serum insulin, ferritin, and CRP in the GDM group compared to the control group. In the GDM group, a positive weak relationship was observed between vitamin D and zinc (r = 0.18, p < 0.05), while vitamin D was inversely correlated with FPG, serum insulin, ferritin, and CRP (r = -0.23, -0.21, -0.20, -0.46, respectively, p < 0.05).

CONCLUSION

This study suggests that hypovitaminosis D might be associated with glucose intolerance, insulin insensitivity, and inflammation, which are factors implicated in the development and progression of GDM.

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

BACKGROUND AND AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Sex Hormone-binding Globulin, Cardiometabolic Biomarkers, and Gestational Diabetes: A Longitudinal Study and Meta-analysis

Objective

This study investigated the prospective associations of circulating levels of sex hormone-binding globulin (SHBG) levels with cardiometabolic biomarkers and risk of gestational diabetes (GDM) during pregnancy. It also examines the longitudinal trajectory of SHBG in women with and without GDM.

Methods

We conducted a nested case-control study of 107 incident GDM cases and 214 matched controls within the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Singleton Cohort. The cohort enrolled non-obese and obese women aged 18-40 years with a singleton pregnancy between 8 and 13 weeks of gestation from 2009 to 2013. GDM was ascertained via medical records review. Blood samples were drawn four times at gestational weeks 10-14, 15-26, 23-31, and 33-39. The prospective associations between SHBG levels and cardiometabolic biomarkers were examined using the Spearman partial correlation among the controls. The longitudinal trajectories of SHBG levels were examined among the cases and the controls. Meta-analysis of prospective studies were performed to examine the association between SHBG levels and GDM risk.

Results

SHBG levels at gestational weeks 10-14 were significantly inversely associated with fasting insulin (r = -0.17, P = 0.01) and insulin resistance as measured by HOMA-IR (r = -0.17, P = 0.01) at gestational week 15-26. SHBG at gestational weeks 10-14 and 15-26 was lower in cases than controls (mean ± standard deviation: (204.0 ± 97.6) vs. (220.9 ± 102.5) nmol/L, P = 0.16 and (305.6 ± 124.3) vs. (322.7 ± 105.1) nmol/L, P = 0.14, respectively), yet the differences were not significant. In the meta-analysis, SHBG was 41.5 nmol/L (95% confidence interval: 23.9, 59.1, P < 0.01) significantly lower among women with GDM than without, and each 50 nmol/L increase in SHBG was significantly associated with an odds ratio of 0.85 (95% confidence interval: 0.76-0.95, P = 0.01) for GDM.

Conclusion

Lower SHBG levels in early pregnancy were prospectively associated with higher high insulin levels and insulin resistance in mid-pregnancy and subsequent risk of GDM, independent of adiposity. SHBG may serve as a marker for the identification of high-risk pregnancies during early pregnancy.

Association of Serum Uric Acid, Urea Nitrogen, and Urine Specific Gravity Levels at 16-18 Weeks of Gestation with the Risk of Gestational Diabetes Mellitus

OBJECTIVE

To evaluate the associations of serum uric acid (UA), urea nitrogen (UN), and urine specific gravity (USG) levels in the first trimester of pregnancy with the risk of gestational diabetes mellitus (GDM).

PATIENTS AND METHODS

A retrospective cohort study was conducted in 1,769 pregnant women aged 31.55 ± 3.91 years. UA, UN, and USG levels were measured during the 16-18th week of gestation. GDM was diagnosed by an oral 75 g glucose tolerance test during the 24-28th week of gestation.

RESULTS

A multivariate adjusted logistic regression analysis showed that UA levels in the highest quartile increased the risk of GDM by 55.7% (odds ratio [OR]: 1.557, 95% confidence interval [CI]: 1.055-2.298; p = 0.026) compared to those in the lowest quartile. USG levels in the second, third, and fourth quartiles increased the risk of GDM by 67.6% (95% CI: 1.090-2.421), 112.4% (95% CI: 1.446-3.119), and 94.5% (95% CI: 1.314-2.880), respectively, compared to those in the first quartile (p trend = 0.001). No significant association between UN levels and the GDM risk was observed. When the extreme composite biomarker score quartiles were compared, the adjusted OR (95% CI) for GDM was 1.909 (95% CI: 1.332-2.736). Age-stratified analyses revealed similar results in women aged ≤35 years only, but not in those aged >35 years.

CONCLUSION

Higher levels of UA and USG and a higher composite kidney function biomarker score during the 16-18th week of gestation were positively and independently associated with an increased risk of GDM.

Omics-based biomarkers in the diagnosis of diabetes

Diabetes mellitus (DM) is a group of metabolic diseases related to the dysfunction of insulin, causing hyperglycaemia and life-threatening complications. Current early screening and diagnostic tests for DM are based on changes in glucose levels and autoantibody detection. This review evaluates recent studies on biomarker candidates in diagnosing type 1, type 2 and gestational DM based on omics classification, whilst highlighting the relationship of these biomarkers with the development of diabetes, diagnostic accuracy, challenges and future prospects. In addition, it also focuses on possible non-invasive biomarker candidates besides common blood biomarkers.

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.

A simple model to predict risk of gestational diabetes mellitus from 8 to 20 weeks of gestation in Chinese women

Background

Gestational diabetes mellitus (GDM) is associated with adverse perinatal outcomes. Screening for GDM and applying adequate interventions may reduce the risk of adverse outcomes. However, the diagnosis of GDM depends largely on tests performed in late second trimester. The aim of the present study was to bulid a simple model to predict GDM in early pregnancy in Chinese women using biochemical markers and machine learning algorithm.

Methods

Data on a total of 4771 pregnant women in early gestation were used to fit the GDM risk-prediction model. Predictive maternal factors were selected through Bayesian adaptive sampling. Selected maternal factors were incorporated into a multivariate Bayesian logistic regression using Markov Chain Monte Carlo simulation. The area under receiver operating characteristic curve (AUC) was used to assess discrimination.

Results

The prevalence of GDM was 12.8%. From 8th to 20th week of gestation fasting plasma glucose (FPG) levels decreased slightly and triglyceride (TG) levels increased slightly. These levels were correlated with those of other lipid metabolites. The risk of GDM could be predicted with maternal age, prepregnancy body mass index (BMI), FPG and TG with a predictive accuracy of 0.64 and an AUC of 0.766 (95% CI 0.731, 0.801).

Conclusions

This GDM prediction model is simple and potentially applicable in Chinese women. Further validation is necessary.

Electronic supplementary material

The online version of this article (10.1186/s12884-019-2374-8) contains supplementary material, which is available to authorized users.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Role of mean platelet volume in pregnancy to predict gestational diabetes mellitus in the first trimester

Objectives: Gestational diabetes mellitus (GDM) is defined as glucose intolerance detected for the first time in pregnancy or identified during pregnancy. Mean platelet volume (MPV) is a marker of activation and function of platelet. Several studies investigated the relation between MPV and GDM. The purpose of the present study is to predict GDM in the first trimester by using MPV value.Materials and methods: Two hundred pregnant women with GDM and 200 normal pregnant women were enrolled in the study. The first trimester MPV values of GDM and control groups were compared to predict GDM in the first trimester.Results: Women with GDM had higher MPV value compared with the control group (p < .001). The area under the receiver-operator curve was 0.70 for MPV. The cutoff value of MPV was 7.38 fl with 70% sensitivity and 60% specificity. According to the ages, MPV value was higher in GDM group in the individuals who were above 28-year-old (p < .001).Conclusion: MPV can be used to predict GDM in the first trimester.

First-trimester proteomic profiling identifies novel predictors of gestational diabetes mellitus

Background

Gestational diabetes mellitus (GDM) is a common pregnancy complication associated with adverse outcomes including preeclampsia, caesarean section, macrosomia, neonatal morbidity and future development of type 2 diabetes in both mother and child. Current selective screening strategies rely on clinical risk factors such as age, family history of diabetes, macrosomia or GDM in a previous pregnancy, and they possess a relatively low specificity. Here we hypothesize that novel first trimester protein predictors of GDM can contribute to the current selective screening strategies for early and accurate prediction of GDM, thus allowing for timely interventions.

Methods

A proteomics discovery approach was applied to first trimester sera from obese (BMI ≥27 kg/m²) women (n = 60) in a nested case-control study design, utilizing tandem mass tag labelling and tandem mass spectrometry. A subset of the identified protein markers was further validated in a second set of serum samples (n = 210) and evaluated for their contribution as predictors of GDM in relation to the maternal risk factors, by use of logistic regression and receiver operating characteristic analysis.

Results

Serum proteomic profiling identified 25 proteins with significantly different levels between cases and controls. Three proteins; afamin, serum amyloid P-component and vitronectin could be further confirmed as predictors of GDM in a validation set. Vitronectin was shown to contribute significantly to the predictive power of the maternal risk factors, indicating it as a novel independent predictor of GDM.

Conclusions

Current selective screening strategies can potentially be improved by addition of protein predictors.

An Approach to Enhance Dissolution Rate of Tamoxifen Citrate

We tested the solubility and dissolution of tamoxifen citrate to ascertain the optimal conditions for faster dissolution. Using the solvent evaporation method and hydrophilic carriers, we formulated tamoxifen citrate (TC) that contained solid dispersions (SDs). We increased the solubility and dissolution rate of TC with a solid dispersion system that consisted of polyethylene glycol (PEG-6000), beta-cyclodextrin (β-CD), and a combination of carriers. Physicochemical characteristics of solubility (mg/ml) were found to be 0.987±0.04 (water), 1.324±0.05 (6.8pH PBS), and 1.156±0.03 (7.4 pH PBS) for F5 formulation, percentage yield was between 98.74 ± 1.11% and 99.06 ± 0.58%, drug content was between 98.06±0.58 and 99.06±1.10, and dissolution studies binary complex showed a faster release of TC as compared to a single polymer and pure drug. Furthermore, thermal properties, physicochemical drug and polymer interaction, crystal properties, and morphology were determined using differential scanning calorimetry (DSC), infrared spectroscopy (FT-IR), X-ray differential studies, and scanning electron microscopy. We used the same proportion of carrier concentrations of the formulations to calculate the solubility of TC. Our results demonstrated that increased concentrations of β-C yielded an improved solubility of TC, which was two times higher than pure TC. The uniformity in drug content was 97.99 %. A quicker drug release occurred from the binary complex formulation as seen in the dissolution profile. FTIR demonstrated an absence in the physicochemical interaction between the drug and carriers. The drug was also found to be dispersed in the amorphous state as revealed by DSC and XRD. The drug concentration did not vary during various storage conditions. Our in vivo studies demonstrated that SD displayed significantly higher values of C_max (p < 0.05) and AUC_0-24 (p < 0.05) as compared to free TC. Furthermore, T_max in SD was significantly lower (p < 0.05), as compared to free TC.

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

OBJECTIVES

Screening and diagnosis of gestational diabetes (GDM) has been a source of controversy. The prevalence has increased in line with an obesity epidemic and a trend towards delayed child-bearing. Treatment of even modest glycaemic impairment in pregnancy has been shown to be beneficial in preventing its clinical sequalae. However the cumbersome nature and timing of the oral glucose tolerance test coupled with debate around universal versus risk factor based screening have been problematic. This group aimed to investigate a panel of biomarkers which have shown promise in the literature to predict GDM from the first trimester in a group of high risk women.

METHODS

Serum samples were drawn on 248 women deemed at risk of GDM before 15 weeks' gestation to measure C-reactive protein, sex hormone binding globulin, adiponectin and 1,5 anhydroglucitol. Patients underwent an oral glucose tolerance test as per IADPSG criteria at 28 weeks' gestation. Multiple logistic regression was used to examine the link between incidence of GDM and early pregnancy serum biomarkers.

RESULTS

Adiponectin levels in the first trimester are independently linked to the risk of GDM. Serum adiponectin <8.9 μg/ml gives an odds ratio of 3.3 for GDM.Mean 1,5 AG levels are significantly lower in those that go on to develop GDM. SHBG levels measured in the first trimester were linked to the risk of GDM. However, this was no longer statistically significant once BMI, ethnicity and family history were taken into consideration. First trimester measurement of CRP is not a useful indicator of GDM risk.

CONCLUSIONS

First trimester measurement of Adiponectin and 1,5 Anhydroglucitol are potential early biomarkers for the later onset of GDM. Risk stratification using these biomarkers may facilitate early diagnosis and management of GDM to mitigate against its complications.

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.

Osteocalcin Serum Levels in Gestational Diabetes Mellitus and Their Intrinsic and Extrinsic Determinants: Systematic Review and Meta-Analysis

BACKGROUND

Undercarboxylated osteocalcin (ucOC) increases insulin release and insulin resistance in mice. In humans, evidence is scarce but a correlation of ucOC and total osteocalcin (tOC) with glycemic status markers has been demonstrated. The relationship of ucOC and tOC with gestational diabetes mellitus (GDM) has been even less characterized.

OBJECTIVE

To assess the mean difference of tOC and ucOC serum concentrations among nondiabetic pregnant women and women diagnosed as GDM in the second trimester of pregnancy and to determine the possible intrinsic and extrinsic contributors to this difference.

METHODS

A systematic search was performed to identify relevant studies published in English and Spanish using PubMed, SCOPUS, ISI Web of Knowledge, and PROSPERO database for meta-analysis. Observational studies measuring mean serum levels of osteocalcin among GDM, with at least 10 subjects analyzed in each group were selected. Mean difference (MD) by random effects model was used. Heterogeneity between studies was assessed using Cochran's Q, H, and I ² statistics.

RESULTS

From 38 selected studies, 5 were retained for analysis for a total of 1119 pregnant women. Serum concentrations of tOC were not significantly different among women with GDM and nondiabetic pregnant controls (MD: 1.56; 95% CI: -0.70 to 3.82; p = 0.175). Meanwhile, ucOC serum levels were significantly higher among women with GDM (MD: 1.17; 95% CI: 0.24 to 2.11; p = 0.013). The only factor influencing tOC was the UV index, showing a reduction in mean difference between GDM and controls when exposed to higher concentrations of UV rays.

CONCLUSIONS

This meta-analysis provides evidence to support the use of ucOC as a potential marker for GDM rather than tOC, yielding very little variability among studies and no difference among methods or brands used for its analysis.

Development of Multimarker Diagnostic Models from Metabolomics Analysis for Gestational Diabetes Mellitus (GDM)

Although metabolomics are desirable to understand the pathophysiology of gestational diabetes mellitus (GDM), comprehensive metabolomic studies of GDM are rare. We aimed to offer a holistic view of metabolites alteration in GDM patients and investigate the possible multimarker models for GDM diagnosis. Biochemical parameters and perinatal data of 131 GDM cases and 138 controls were collected. Fasting serum samples at 75 g oral glucose tolerance test were used for metabolites by ultra performance liquid chromatography-quadrupole-time of flight-mass spectrometry, ultra performance liquid chromatography-triple triple-quadrupole-mass spectrometry and gas chromatography- time-of- flight mass spectrometry platforms. Significant changes were observed in free fatty acids, bile acids, branched chain amino acids, organic acids, lipids and organooxygen compounds between two groups. In receiver operating characteristic (ROC) analysis, different combinations of candidate biomarkers and metabolites in multimarker models achieved satisfactory discriminative abilities for GDM, with the values of area under the curve (AUC) ranging from 0.721 to 0.751. Model consisting of body mass index (BMI), retinol binding protein 4 (RBP4), n-acetylaspartic acid and C16:1 (cis-7) manifested the best discrimination [AUC 0.751 (95% CI: 0.693-0.809), p < 0.001], followed by model consisting of BMI, Cystatin C, acetylaspartic acid and 6,7-diketoLCA [AUC 0.749 (95% CI: 0.691-0.808), p < 0.001]. Metabolites alteration reflected disorders of glucose metabolism, lipid metabolism, amino acid metabolism, bile acid metabolism as well as intestinal flora metabolism in GDM state. Multivariate models combining clinical markers and metabolites have the potential to differentiate GDM subjects from healthy controls.

The association between dysregulated adipocytokines in early pregnancy and development of gestational diabetes

BACKGROUND

To investigate the association of adipocytokines and other inflammatory markers with development of GDM.

METHODS

Serum adipocytokines and inflammatory markers were studied at 12 to 15 weeks gestation using biobanked control samples from a randomised trial. Study participants were identified as high risk for GDM using a validated clinical risk prediction tool. Markers were tested using commercial ELISA kits for high molecular weight (HMW) adiponectin, interleukin-6 (IL-6), plasminogen activator inhibitor-1, visfatin, omentin-1, sex-hormone binding globulin, monocyte chemoattractant protein, and asymmetrical dimethylarginine. The association between each biomarker and development of GDM at 24 to 28 weeks was evaluated using multivariable logistic regression analysis adjusted for maternal factors.

RESULTS

There were no differences in age, parity, country of birth, smoking, body mass index, or family history of diabetes in women with normal glucose tolerance (n = 78) and women who developed GDM (n = 25). Women with GDM were more likely to have a past history of GDM (P = 0.004). HMW adiponectin (odds ratio OR 0.37 [95% confidence interval 0.19-0.74]), omentin-1 (0.97 [0.94-0.99]), and IL-6 (1.87[1.03-3.37]) were associated with development of GDM, after adjustment for maternal age, body mass index, and past history of GDM. The other markers were not associated with GDM development.

CONCLUSIONS

Decreased high molecular weight adiponectin and omentin-1 and increased IL-6 may enhance sensitivity of early risk prediction tools for women at high risk of GDM. This may allow early identification and opportunities for prevention of GDM and adverse outcomes. Further research is required in large validation studies to confirm these results.

Roles of Inflammation and Depression in the Development of Gestational Diabetes

Inflammation, the body's response to harmful external agents, has long been found to be associated with depressive symptoms. The relationship between inflammation and depression is well established in the general population of people with depression, but is less so among perinatal women. Depression in the perinatal period is a common disorder, however available data do not indicate that there is a specific inflammatory picture associated with perinatal depression. We suggest that perinatal depression may be a heterogeneous construct, and that inflammation may be relevant to it in the context of other inflammatory morbidities of pregnancy. In this review we explore the available support for the hypothesis that inflammation associated with depression can represent a precipitating insult for the development of gestational diabetes, a known inflammatory morbidity of pregnancy.

Interleukin 6 (IL-6) and Tumor Necrosis Factor α (TNF-α) Single Nucleotide Polymorphisms (SNPs), Inflammation and Metabolism in Gestational Diabetes Mellitus in Inner Mongolia

BACKGROUND Gestational diabetes mellitus (GDM) is common all over the world. GDM women are with inflammatory and metabolisms abnormalities. However, few studies have focused on the association of IL-65-72C/G and TNF-α -857C/T single nucleotide polymorphisms (SNPs), inflammatory biomarkers, and metabolic indexes in women with GDM, especially in the Inner Mongolia population. The aim of this study was to investigate the associations of IL-65-72C/G and TNF-α -857C/T SNPs, and inflammation and metabolic biomarkers in women with GDM pregnancies. MATERIAL AND METHODS Blood samples and placentas from 140 women with GDM and 140 women with healthy pregnancies were collected. Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) and MassARRAY-IPLEX were performed to analyze IL-65-72C/G and TNF-α -857C/T SNPs. Enzyme linked immunosorbent assay (ELISA) was performed to analyze inflammatory biomarkers and adipokines. RESULTS Distribution frequency of TNF-α -857CT (OR=3.316, 95% CI=1.092-8.304, p=0.025) in women with GDM pregnancies were obviously higher than that in women with healthy pregnancies. Women with GDM were of older maternal age, had higher BMI, were more nulliparous, and had T2DM and GDM history, compared to women with healthy pregnancies (p<0.05). Inflammatory biomarkers in serum (hs-CRP, IL-6, IL-8, IL-6/IL-10 ratio) and placental (NF-κB, IL-6, IL-8, IL-6/IL-10 ratio, IL-1b, TNF-α) were significantly different (p<0.05) between women with GDM and women with healthy pregnancies. Differences were found for serum FBG, FINS, HOMA-IR, and HOMA-β, and placental IRS-1, IRS-2, leptin, adiponectin, visfatin, RBP-4, chemerin, nesfatin-1, FATP-4, EL, LPL, FABP-1, FABP-3, FABP-4, and FABP-5. CONCLUSIONS TNF-α -857C/T SNP, hs-CRP, IL-6, IL-8, and IL-6/IL-10 were associated with GDM in women from Inner Mongolia, as was serious inflammation and disordered lipid and glucose metabolisms.

Increased intestinal permeability, measured by serum zonulin, is associated with metabolic risk markers in overweight pregnant women

BACKGROUND

Increased intestinal permeability with subsequent metabolic endotoxemia, i.e., elevated circulating levels of bacterial lipopolysaccharide, LPS, has been introduced as a novel initiator of obesity related metabolic disturbances in non-pregnant individuals. The objective was to investigate the extent to which intestinal permeability, measured by serum zonulin concentration, is related to metabolic endotoxemia and metabolic risk markers in overweight pregnant women.

METHODS

This was a cross-sectional study including 100 pregnant overweight women in early pregnancy. Serum zonulin was analyzed using ELISA, and markers for metabolic endotoxemia (LPS), inflammation (high-sensitive C-reactive protein and glycoprotein acetylation GlyA), glucose metabolism (fasting glucose and insulin), and lipid metabolism were measured.

RESULTS

Higher serum zonulin concentration associated positively with LPS (P=0.02), inflammatory markers (P<0.001), insulin (P<0.001), insulin resistance (P<0.001), and triglycerides (P=0.001), and negatively with insulin sensitivity (P=0.001) (ANOVA with Tukey's corrections or Kruskal-Wallis nonparametric test with Bonferroni correction for zonulin quartiles). All the observed associations were confirmed (P<0.015) in a linear regression model adjusted with potential confounding factors. Both LPS and GlycA showed positive relationship with insulin resistance, serum insulin, triglycerides, total and LDL-cholesterol and negative relationship with insulin sensitivity (P≤0.03) in the univariate linear regression. Positive relationship was also found between LPS and HDL-cholesterol (P=0.03).

CONCLUSIONS

Our findings suggest that increased serum zonulin concentration, i.e., increased intestinal permeability, contributes to metabolic endotoxemia, systemic inflammation, and insulin resistance in overweight pregnant women. By reinforcing intestinal barrier, it may be possible to manipulate maternal metabolism during pregnancy with subsequent health benefits.

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.

The prevalence of elevated high-sensitivity C-reactive protein in normal pregnancy and gestational diabetes mellitus

Objective:

The objective of this study is to determine the prevalence of elevated high-sensitivity C-reactive protein (hs-CRP) in normal pregnancy and gestational diabetes mellitus (GDM) and to compare the prevalence in both groups.

Materials and Methods:

We conducted a case–control study between April 2015 and April 2016. Statistical analysis was performed by the SPSS program version 17. Categorical variables were analyzed using either the Chi-square test or Fisher's exact test. Pregnant women who underwent oral glucose tolerance test at 24–28 weeks of gestation were enrolled. We took 25 women with GDM as cases and 25 normal pregnant as control. These patients were analyzed for the level of hs-CRP.

Results:

The prevalence of elevated hs-CRP in controls was 28% whereas in cases was 76%, with a P = 0.002 which is significant in this study. When compared to elevated hs-CRP in GDM with body mass index and gravid state a P = 0.430, 0.378 was obtained respectively which was not significant whereas age had a P = 0.049 which was significantly associated with elevated hs-CRP (≥3 mg/L).

Conclusion:

Our result shows an increased level of hs-CRP in GDM as compared to normal pregnant subjects. In this study, we also observed an association of increasing age with elevated level of hs-CRP in GDM. Therefore, hs-CRP can be used as a screening tool for early detection and risk assessment of GDM.

The potential role of biomarkers in predicting gestational diabetes

Gestational diabetes (GD) is a frequent complication during pregnancy and is associated with maternal and neonatal complications. It is suggested that a disturbing environment for the foetus, such as impaired glucose metabolism during intrauterine life, may result in enduring epigenetic changes leading to increased disease risk in adult life. Hence, early prediction of GD is vital. Current risk prediction models are based on maternal and clinical parameters, lacking a strong predictive value. Adipokines are mainly produced by adipocytes and suggested to be a link between obesity and its cardiovascular complications. Various adipokines, including adiponectin, leptin and TNF&, have shown to be dysregulated in GD. This review aims to outline biomarkers potentially associated with the pathophysiology of GD and discuss the role of integrating predictive biomarkers in current clinical risk prediction models, in order to enhance the identification of those at risk.

Association of first trimester serum uric acid levels gestational diabetes mellitus development

OBJECTIVE

To investigate the association of first trimester serum uric acid levels with the development of gestational diabetes mellitus (GDM) in low-risk pregnant women.

MATERIALS AND METHODS

In this retrospective data analysis, the results of pregnant women who completed both first trimester biochemical panel and two-step GDM screening were compared with an age-, body mass index, and gestational age-matched control group. The women were grouped as either GDM or impaired glucose tolerance (IGT) according to 100-g oral glucose challenge results. Uric acid levels were compared between the groups and diagnostic utility was tested with receiver-operating characteristics curves.

RESULTS

Sixty-six women in GDM group and 358 women in the IGT group were compared against 202 healthy pregnant women. The groups did not differ significantly in terms of parity, pre-gestational body mass index and gestational age. Serum samples for uric acid levels were obtained. The mean serum uric acid levels were significantly higher in the GDM and IGT groups (5.95 mg/dL (±0.97 mg/dL) and 4.76 mg/dL (±1.51 mg/dL), respectively) compared with the control group (3.76 mg/dL (±1.07 mg/dL) (p<0.001). The area under the curve for uric acid levels was 0.92 (95% confidence interval 0.88-0.95) for diagnosis of GDM. At a diagnostic threshold of 3.95 mg/dL, uric acid levels predicted development of GDM with 60% specificity and 100% sensitivity.

CONCLUSION

First trimester serum uric acid has a linear association with the development of GDM and IGT.

Is Uric Acid a Missing Link between Previous Gestational Diabetes Mellitus and the Development of Type 2 Diabetes at a Later Time of Life?

INTRODUCTION

A high level of uric acid (UA) is a strong, independent risk factor for type 2 diabetes mellitus. The relationship between UA levels and the development of type 2 diabetes in women with previous gestational diabetes mellitus (pGDM) remains unclear. The aim of study was to evaluate the UA levels in pGDM women in relation to their current nutritional status and carbohydrate metabolism.

MATERIAL AND METHODS

199 women with pGDM diagnoses based on oral glucose tolerance tests (OGTTs) 5-12 years previously and a control group of 50 women without pGDM. The assessment included anthropometric parameters, body composition (Tanita SC-330S), current OGTT, insulin resistance index (HOMA-IR), β-cell function (HOMA-%B), HbA1c, lipids, and uric acid.

RESULTS

No differences between groups were found in terms of age, time from the index pregnancy, anthropometric parameters, lipids or creatinine levels. The incidences of overweight and obesity were similar. Carbohydrate abnormalities were more frequent in the pGDM group than the control group (43.2% vs 12.0% p<0.001). The women with pGDM had significantly higher fasting glucose, HbA1c, glucose and insulin levels in the OGTTs, but similar HOMA-IR values. Their UA levels were significantly higher (258±58 vs 230±50 μmol/L, p<0.005) and correlated with BMI and the severity of carbohydrate disorders. The normal weight and normoglycemic pGDM women also demonstrated higher UA levels than a similar control subgroup (232±48 vs 208±48 μmol/L, p<0.05). Multivariate analysis revealed significant correlations of UA level with BMI (β = 0.38, 95% CI 0.25-0.51, p<0.0001), creatinine level (β = 0.23, 95% CI 0.11-0.35, p<0.0005), triglycerides (β = 0.20, 95% CI 0.07-0.33, p<0.005) and family history of diabetes (β = 0.13, 95% CI 0.01-0.25, p<0.05). In logistic regression analysis, the association between higher UA level (defined as value ≥297 μmol/L) and presence of any carbohydrate metabolism disorder (IFG, IGT or diabetes) was statistically significant (odds ratio 3.62 [95% CI 1.8-7.3], p<0.001).

CONCLUSIONS

Higher UA levels may be associated with the development of type 2 diabetes in pGDM women, also in these with normal body weights.