Predicting gestational diabetes mellitus during the first trimester using anthropometric measurements and HOMA-IR

Metabolic pathways mediating insulin resistance and gestational diabetes mellitus discovered by high-dimensional systematic Mendelian randomization

BACKGROUND

Gestational diabetes mellitus (GDM), characterized by insulin resistance (IR) and β-cell dysfunction, is one of the most common complications of pregnancy with unmet needs of prevention methods.

OBJECTIVE

To investigate the causal role of insulin resistance and metabolic pathways in the pathogenesis of GDM with our proposed high-dimensional systematic Mendelian randomization (hdsMR) framework.

METHODS

Cases with GDM and controls with normal glucose tolerance were recruited at the University of Hong Kong-Shenzhen Hospital from 2015 to 2018. A total of 566 participants (aged > 18 years), including 274 with GDM, were enrolled after excluding subjects with major chronic diseases or long-term use of medications affecting glycolipid metabolism. Clinical characteristics and serum samples were collected during the GDM screening stage, and the genome and metabolome were tested. A novel hdsMR framework was proposed to estimate the causal role of IR index (Homeostasis Model Assessment of Insulin Resistance, HOMA-IR) and metabolic pathways in the pathogenesis of GDM.

RESULTS

Our hdsMR method confirmed that HOMA-IR was causal to GDM (odds ratio, 1.17; 95% confidence interval, 1.04-1.32) and revealed that two metabolic pathways (glyoxylate and dicarboxylate metabolism pathway and lysine degradation pathway) mediated 14.6% and 8.4%, respectively, between HOMA-IR and GDM. In an independent validation cohort comprising 255 pre-diabetic individuals, we showed that both pathways could be intervened through diet (P < 0.05). Furthermore, glyoxylate and dicarboxylate metabolism pathway was significantly associated with adverse pregnancy outcomes in GDM.

CONCLUSIONS

These results indicated that targeting specific metabolic pathways through dietary intervention is worth exploring as a possible GDM prevention approach, and hdsMR is more efficient in finding causal mediating metabolic pathways than traditional MR methods.

Gestational diabetes severity stratification during pregnancy: role of plasma oleic acid as a possible early marker

Normal pregnancy is characterized by changes in lipid metabolism with significant implications for the health of both mother and offspring. When these changes develop into maternal dyslipidemia, a significant association with adverse pregnancy outcomes has been observed, including the development of gestational diabetes (GD), modulation of the inflammatory response, and excessive fetal growth. In the present study, we performed a lipidomic assessment of patients at GD diagnosis (24-28 weeks of gestation) and 12 weeks after diagnosis. We found higher levels of esterified oleic acid in plasma at the time of GD diagnosis in women who subsequently required pharmacological therapy to control blood glucose levels compared to those who did not require additional treatment, suggesting that the measurement of plasma oleic acid might be an additional tool for the early identification of patients with a more severe form of gestational diabetes. Moreover, plasma oleic acid levels showed a positive correlation with fetal growth in the context of adequate glycemic control, supporting a metabolic dysregulation of other pathways whose identification could help clinicians to discriminate different cases within the spectrum of severity of the disease. Finally, the correlation between plasma oleic acid and circulating BAFF levels at the time of diagnosis and 12 weeks later adds a possible mechanism to support the pro-inflammatory and pro-diabetic state in the metabolic set of GD. Overall, these findings strongly support the role of plasma oleic acid as a possible early marker for GD severity stratification during pregnancy.

The waist-to-height ratio is a good predictor for insulin resistance in women with polycystic ovary syndrome

Objective

This study aimed to explore the role of the waist-to-height ratio (WHtR) in assessing insulin resistance (IR) in patients with polycystic ovary syndrome (PCOS).

Materials and methods

We enrolled 882 PCOS-afflicted women in a cross-sectional analysis to evaluate the association of the WHtR with IR. Their demographic characteristics, anthropometric parameters, and fasting blood samples were collected and measured. Moreover, IR was evaluated by homeostatic model assessment of insulin resistance (HOMA-IR). We estimated the relationship between the WHtR and IR and the cut-off thresholds of the WHtR for IR using multivariable linear regression and logistic regression models, respectively.

Results

The prevalence rate of IR was 51.9%. The patients with PCOS and IR displayed significantly increased values for body mass index (BMI), waist circumference (WC), WHtR, systolic blood pressure (SBP), diastolic blood pressure (DBP), free androgen index (FAI), HOMA-IR, total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein B (ApoB). However, the patients with PCOS and IR showed a reduction in estradiol (E2), luteinizing hormone (LH), LH/FSH ratio, sex hormone binding globulin (SHBG), and high-density lipoprotein (HDL-C) values than those without IR. Moreover, BMI (log-transformed), WC, and HOMA-IR (log-transformed) were positively correlated with the WHtR. When adjusting for potential confounding variables, the WHtR was significantly associated with HOMA-IR (log-transformed), with a standardized regression coefficient of 0.271. Furthermore, the WHtR was significantly associated with an increased risk of IR, with the adjusted odds ratio (OR) of 3.15 (WHtR multiplied by 10). Additionally, the WHtR helped to identify IR in women with PCOS with an optimal cut-off point of 0.519 (Youden index = 0.433).

Conclusions

The WHtR had a positive association with IR in women with PCOS. Hence, we suggest that the WHtR, as a simple, practical, and reliable anthropometric measure, can be used to predict the risk of IR in patients with PCOS.

Effects of household air pollution and healthy lifestyle associated with gestational diabetes mellitus

This study investigated the effect of household air pollution on pregnant women with GDM, and assessed the modifying effect of a healthy lifestyle on this relationship. Household solid fuel exposure was defined as using solid fuels (coal, crop residue, and wood) for cooking and heating. Four individually modifiable lifestyle factors were assessed in early pregnancy: body mass index, diet, sleep, and vitamin D supplementation. Multifactorial logistic regression modeling was used to assess the relationship between household air pollution and GDM. A stratified analysis and additive interaction tested the effects of healthy lifestyle scores. After adjusting for potential confounders, we found that using solid fuels for heating was significantly associated with an increased risk of GDM (adjusted OR = 1.60, 95% CI 1.18-2.18). GDM risk showed a decreasing trend in the medium versus the high score group when compared to the low score group, with a consistent trend regardless of household fuel type used (adjusted OR = 0.39, 95% CI 0.27-0.57) (adjusted OR = 0.12, 95% CI 0.05-0.28), respectively. Importantly, when the healthy lifestyle score increased, exposure to household air pollution was no longer associated with a higher GDM risk. There was a negative additive interaction between exposure to household solid fuels exposure and a healthy lifestyle (FERI: -5.10 [-16.48, -2.04]; AP: -1.29 [-2.80, -0.39]; SI: -0.37 [-0.20, -0.67]). We determined that exposure to household air pollution may be an important GDM risk factor. In addition, A healthy lifestyle may have a protective effect on women with GDM exposed to indoor fuel air pollution.

Predictive Utility of Biochemical Markers for the Diagnosis and Prognosis of Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a common complication during pregnancy with an increasing prevalence worldwide. Early prediction of GDM and its associated adverse outcomes is crucial for timely intervention and improved maternal and fetal health. The objective of this review is to provide a comprehensive summary of contemporary evidence on biomarkers, focusing on their potential to predict the development of GDM and serve as predictors of maternal, fetal, and neonatal outcomes in women with GDM. A literature search was conducted in the PubMed database using relevant terms. Original research articles published in English between 1 January 2015, and 30 June 2024, were included. A two-stage screening process was employed to identify studies on biomarkers for GDM diagnosis and prognosis and to evaluate the evidence for each biomarker's diagnostic performance and its potential prognostic correlation with GDM. Various biochemical markers, including adipokines, inflammatory markers, insulin resistance markers, glycemic markers, lipid profile markers, placenta-derived markers, and other related markers, have shown promise in identifying women at risk of developing GDM and predicting adverse pregnancy outcomes. Several promising markers with high predictive performance were identified. However, no single biomarker has demonstrated sufficient accuracy to replace the current diagnostic criteria for GDM. The complexity of multiple pathways in GDM pathogenesis highlights the need for a multi-marker approach to improve risk stratification and guide personalized management strategies. While significant progress has been made in GDM biomarker research, further studies are required to refine and validate these markers for clinical use and to develop a comprehensive, evidence-based approach to GDM prediction and management that can improve maternal and child health outcomes.

Serum progesterone, glycosylated hemoglobin and insulin levels with the risk of premature rupture of membranes in gestational diabetes mellitus

OBJECTIVE

To discuss the correlation between serum progesterone, glycosylated Hemoglobin (HbA1c), and insulin levels in pregnant women with Gestational Diabetes Mellitus (GDM) and the risk of Premature Rupture of Membranes (PROM).

METHODS

A retrospective analysis was conducted on 52 patients diagnosed with GDM who also presented with PROM (Observation group) and compared with 89 patients diagnosed with GDM but not complicated with PROM (Control group). Progesterone, insulin, and HbA1c were detected. Risk factors for PROM in GDM patients were analyzed.

RESULTS

The observation group had higher HbA1c and fasting blood glucose levels. Poor blood glucose control and GWG are risk factors for PROM in GDM patients. PROM increases adverse pregnancy outcomes in GDM. HbA1c, insulin, and HOMA-IR can predict the risk of PROM in GDM.

CONCLUSIONS

The effective prediction of preterm PROM can be achieved through the monitoring of serum HbA1c, insulin levels, and insulin resistance in patients with GDM.

MTNR1B gene variations and high pre-pregnancy BMI increase gestational diabetes mellitus risk in Chinese women

AIM

To investigate the association of melatonin receptor 1B (MTNR1B) gene variations and pre-pregnancy body mass index (BMI) with gestational diabetes mellitus (GDM).

MATERIALS AND METHOD

In this study, 1566 Chinese Han pregnant women were enrolled and multiple genetic models were used to evaluate the association between MTNR1B gene polymorphisms and the risk of GDM. The clinical value of pre-pregnancy BMI in predicting GDM was analyzed and evaluated using receiver operating characteristic (ROC) curves. Several methods of analysis were used to examine the impact of gene-gene and gene-BMI interactions on the incidence of GDM influence.

RESULTS

For the MTNR1B gene, rs1387153 (C > T), rs10830962 (C > G), rs4753426 (T > C), and rs10830963 (C > G) are all risk mutations associated with the susceptibility of GDM. The ROC curve analysis indicated that the BMI demonstrated an area under the curve (AUC) of 0.595. Alongside, the sensitivity and specificity stood at 0.676 and 0.474 respectively. The maximum Joden index was found to be 0.150, with a corresponding critical BMI value of 20.5691 kg/m2. Interaction analysis revealed that gene-gene and gene-BMI interactions had no significant effect on GDM occurrence.

CONCLUSION

MTNR1B genetic variations confers the risk to GDM in Chinese women. Furthermore, the high pre-pregnancy BMI (≥20.5691 kg/m2) significantly increases the risk of GDM in Chinese women.

Evaluation of insulin secretion and insulin sensitivity in pregnant women: Application value of simple indices

The prevalence of gestational diabetes mellitus (GDM) is increasing annually, which poses substantial harm to the health of both mothers and children. Therefore, selection of clinically applicable and easily detectable indicators in the assessment of maternal insulin secretory function and insulin sensitivity in pregnant women undoubtedly holds great importance in evaluating the risk of GDM, guiding the choice of GDM therapy modalities, and improving the ability to provide early warning of adverse pregnancy outcomes. Compared with the classic clamp technique, many simple indices are more suited for use among pregnant women due to the low frequency of blood sampling and simple administration involved. While indices derived from fasting blood glucose and fasting insulin levels are most readily available, they are unable to provide information on the ability of insulin to manage the glucose load during pregnancy. Although the indices derived from the insulin and glucose values at each time point of the oral glucose tolerance test can provide a more comprehensive picture of the insulin sensitivity and insulin secretory function of the body, their application is constrained by the complexity of the procedure and associated high costs. Concomitantly, the findings from different studies are influenced by a variety of confounding factors, such as the gestational age during testing, race, and detection method. Furthermore, insulin secretory function and insulin sensitivity in pregnant women differ from those in non-pregnant women in that they change significantly with prolonged pregnancy; hence, there is an urgent need to develop a pregnancy-specific reference range. This article reviews the progress in the application of simple indices to help clinicians better understand their potential application in detecting GDM.

Epigenome wide association study in peripheral blood of pregnant women identifies potential metabolic pathways related to gestational diabetes

Gestational diabetes mellitus (GDM) increases the risk of developing metabolic disorders in both pregnant women and their offspring. Factors such as nutrition or the intrauterine environment may play an important role, through epigenetic mechanisms, in the development of GDM. The aim of this work is to identify epigenetic marks involved in the mechanisms or pathways related to gestational diabetes. A total of 32 pregnant women were selected, 16 of them with GDM and 16 non-GDM. DNA methylation pattern was obtained from Illumina Methylation Epic BeadChip, from peripheral blood samples at the diagnostic visit (26-28 weeks). Differential methylated positions (DMPs) were extracted using ChAMP and limma package in R 2.9.10, with a threshold of FDR <0.05, deltabeta >|5|% and B >0. A total of 1.141 DMPs were found, and 714 were annotated in genes. A functional analysis was performed, and we found 23 genes significantly related to carbohydrate metabolism. Finally, a total of 27 DMPs were correlated with biochemical variables such as glucose levels at different points of oral glucose tolerance test, fasting glucose, cholesterol, HOMAIR and HbA1c, at different visits during pregnancy and postpartum. Our results show that there is a differentiated methylation pattern between GDM and non-GDM. Furthermore, the genes annotated to the DMPs could be implicated in the development of GDM as well as in alterations in related metabolic variables.

Combined healthy lifestyle in early pregnancy and risk of gestational diabetes mellitus: A prospective cohort study

OBJECTIVE

To examine the association of a combined healthy lifestyle in early pregnancy with gestational diabetes mellitus (GDM) risk.

DESIGN, SETTING AND POPULATION

A Chinese prospective cohort study with 6980 pregnant women.

METHODS

Individual modifiable lifestyle factors were assessed in early pregnancy and a combined lifestyle score was derived from the sum of the lifestyle factors, with a higher score indicating a healthier lifestyle. The association of a combined healthy lifestyle with GDM risk was examined.

MAIN OUTCOME MEASURES

Gestational diabetes mellitus was diagnosed in middle pregnancy according to the International Association of Diabetes and Pregnancy Study Group criteria or diagnoses in medical records.

RESULTS

Overall, 501 (7.2%) pregnant women were diagnosed with GDM. Being physically active (total energy expenditure in upper three quintiles, i.e. ≥100.1 metabolic equivalent of task [MET]-hours/week; odds ratio [OR] 0.76, 95% confidence interval [CI] 0.63-0.92), healthy diet (total intake of vegetables and fruits ≥5 times/day; OR 0.74, 95% CI 0.59-0.94), sufficient sleep (night-time sleep duration ≥7 hours/night; OR 0.66, 95% CI 0.48-0.90) and healthy weight (early-pregnancy BMI <24.0 kg/m2 ; OR 0.57, 95% CI 0.46-0.71) were associated with lower GDM risk. The GDM risk decreased linearly across the combined lifestyle score (Ptrend  <0.001): women with 2, 3 and 4 lifestyle factors compared with those with 0-1 factor had 38% (OR 0.62, 95% CI 0.46-0.84), 57% (OR 0.43, 95% CI 0.31-0.58) and 66% (OR 0.34, 95% CI 0.22-0.52) lower risks of GDM, respectively.

CONCLUSION

A healthy lifestyle in early pregnancy was associated with a substantially lower GDM risk.

The yield of early-pregnancy homeostasis of model assessment -insulin resistance (HOMA-IR) for predicting gestational diabetes mellitus in different body mass index and age groups

BACKGROUND

Early prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories.

MATERIALS AND METHODS

This study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018-2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24-28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM.

RESULTS

GDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6-6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI.

CONCLUSION

The present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM.

Association Between Plasma Asprosin Levels and Gestational Diabetes Mellitus

PURPOSE

This study sought to investigate whether asprosin can be used in the diagnosis of GDM or for diagnostic purposes in high-risk pregnancies, along with a review of other parameters that may be associated with serum asprosin levels.

PATIENTS AND METHODS

The study investigated the association between gestational diabetes mellitus (GDM) and asprosin levels. A total of 93 participants; 30 patients with GDM, 33 healthy pregnant women with normal glucose tolerance (NGT), and 30 healthy non-diabetic women (control group) at the Endocrinology and Metabolic Diseases outpatient clinic of a tertiary care university hospital were enrolled in the study. Patients with GDM and NGT were examined in terms of GDM between the 24th and 28th week of pregnancy (2nd trimester). Patient data were collected during routine examinations, and asprosin levels were measured using the ELISA method. All participants underwent testing for measurements of serum hemoglobin, insulin, C-peptide, fasting plasma glucose, and glycated hemoglobin (HbA1c) levels following a fasting period of at least eight hours.

RESULTS

Asprosin levels were higher in pregnant women with NGT and with GDM versus controls (Control-NGT asprosin, p = 0.001; Control-GDM asprosin, p = 0.001). Pregnant women with GDM had higher asprosin levels than those with NGT (p = 0.001). In detecting GDM in pregnant women, an asprosin cutoff value of >31.709 ng/mL yielded a sensitivity of 93.3%, specificity of 90.9%, positive predictive value of 90.3%, and negative predictive value of 93.75% (p < 0.001).

CONCLUSION

Serum asprosin levels can potentially be used as a marker in the diagnosis of GDM.

Associations between maternal metabolic parameters during pregnancy and fetal and child growth trajectories from 20 weeks' gestation to 5 years of age: Secondary analysis from the ROLO longitudinal birth cohort study

OBJECTIVE

To examine the association between maternal metabolic parameters in pregnancy and growth trajectories up to 5 years of age.

METHODS

Data from mother-child pairs who participated in the ROLO study, a randomized trial examining the impact of a low glycaemic index diet on the recurrence of macrosomia, were analysed. Fetal and child growth trajectories were developed from longitudinal measurements from 20 weeks gestation up to 5 years of age. We examined associations between maternal fasting glucose, insulin, HOMA-IR and leptin, taken in early pregnancy (14-16 weeks) and late pregnancy (28 weeks), and weight (kg) and abdominal circumference (cm) trajectories using linear spline multilevel models.

RESULTS

We found no strong evidence of associations between any maternal metabolic parameters and fetal to childhood weight and abdominal circumference trajectories from 20 weeks gestation to 5 years.

CONCLUSION

In a cohort of women with obesity with infants at risk of macrosomia, maternal metabolic markers were not strongly associated with trajectories of weight or abdominal circumference from 20 weeks gestation to 5 years of age.

Predictability of HOMA-IR for Gestational Diabetes Mellitus in Early Pregnancy Based on Different First Trimester BMI Values

Objective: To investigate the ability of homeostasis model assessment of insulin resistance (HOMA-IR) in early pregnancy for predicting gestational diabetes mellitus (GDM) in Chinese women with different first-trimester body mass index (FT-BMI) values. Methods: Baseline characteristics and laboratory tests were collected at the first prenatal visit (6−12 weeks of gestation). GDM was diagnosed by a 75 g oral glucose tolerance test (OGTT) at 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression were applied to identify the association between HOMA-IR and GDM. The cutoff points for predicting GDM were estimated using receiver operating characteristic (ROC) curve analysis. Results: Of the total of 1343 women, 300 (22.34%) were diagnosed with GDM in the 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression verified HOMA-IR as a significant risk factor for GDM in the normal weight subgroup (FT-BMI < 24 kg/m2) (adjusted OR 2.941 [95% CI 2.153, 4.016], P < 0.001), overweight subgroup (24.0 kg/m2 ≤ FT-BMI < 28.0 kg/m2) (adjusted OR 3.188 [95% CI 2.011, 5.055], P < 0.001), and obese subgroup (FT-BMI ≥ 28.0 kg/m2) (adjusted OR 9.415 [95% CI 1.712, 51.770], p = 0.01). The cutoff values of HOMA-IR were 1.52 (area under the curve (AUC) 0.733, 95% CI 0.701−0.765, p < 0.001) for all participants, 1.43 (AUC 0.691, 95% CI 0.651−0.730, p < 0.001) for normal weight women, 2.27 (AUC 0.760, 95% CI 0.703−0.818, p < 0.001) for overweight women, and 2.31 (AUC 0.801, 95% CI 0.696−0.907, p < 0.001) for obese women. Conclusions: Increased HOMA-IR in early pregnancy is a risk factor for GDM, and HOMA-IR can be affected by body weight. The cutoff value of HOMA-IR to predict GDM should be distinguished by different FT-BMI values.

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

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

Association of body composition in early pregnancy with gestational diabetes mellitus: A meta-analysis

INTRODUCTION

Body composition as dynamic indices constantly changes in pregnancy. The use of body composition indices in the early stages of pregnancy has recently been considered. Therefore, the current meta-analysis study was conducted to investigate the relationship between body composition in the early stages of pregnancy and gestational diabetes.

METHOD

Valid databases searched for papers published from 2010 to December 2021 were based on PRISMA guideline. Newcastle Ottawa was used to assess the quality of the studies. For all analyses, STATA 14.0 was used. Mean difference (MD) of anthropometric indices was calculated between the GDM and Non-GDM groups. Pooled MD was estimated by "Metan" command, and heterogeneity was defined using Cochran's Q test of heterogeneity, and I 2 index was used to quantify heterogeneity.

RESULTS

Finally, 29 studies with a sample size of 56438 met the criteria for entering the meta-analysis. Pooled MD of neck circumference, hip circumference, waist hip ratio, and visceral adipose tissue depth were, respectively, 1.00 cm (95% CI: 0.79 to 1.20) [N = 5; I^2: 0%; p: 0.709], 7.79 cm (95% CI: 2.27 to 13.31) [N = 5; I2: 84.3%; P<0.001], 0.03 (95% CI: 0.02 to 0.04) [N = 9; I2: 89.2%; P<0.001], and 7.74 cm (95% CI: 0.11 to 1.36) [N = 4; I^2: 95.8%; P<0.001].

CONCLUSION

Increased neck circumference, waist circumference, hip circumference, arm circumference, waist to hip ratio, visceral fat depth, subcutaneous fat depth, and short stature increased the possibility of developing gestational diabetes. These indices can accurately, cost-effectively, and affordably assess the occurrence of gestational diabetes, thus preventing many consequences with early detection of gestational diabetes.

The effects of prenatal dietary supplements on blood glucose and lipid metabolism in gestational diabetes mellitus patients: A systematic review and network meta-analysis protocol of randomized controlled trials

BACKGROUND

Several randomized controlled trials (RCT) investigated antenatal dietary supplements' effect on gestational diabetes mellitus patients' fasting plasma glucose levels, glycated hemoglobin levels, homeostasis model assessment of- insulin resistance and β-cell function, quantitative insulin sensitivity check index for glucose, high-, low-, and very-low-density lipoprotein cholesterol levels, total cholesterol levels, triglyceride levels, and triglyceride to high-density lipoprotein ratio. However, an efficacy comparison across various dietary supplements and their co-supplements are unavailable for these outcomes. Therefore, a systematic review protocol is proposed here to make a network meta-analysis (NMA)-based juxtaposition across the following dietary supplements- vitamins, Myo-inositol, choline, minerals, probiotics, prebiotics, synbiotics, and omega-3 fatty acids.

MATERIALS AND METHODS

A database search will ensue in the PubMed, Embase, and Scopus databases for RCTs testing the above, irrespective of their geographical origin. Data on population characteristics, compared interventions, and outcomes of interest will get abstracted from the studies included in the proposed review. Each of the reviewed studies will get appraised using the revised Cochrane tool. For each outcome, the comparative efficacy across interventions will be estimated in weighted or standardized mean difference using the frequentist method NMA and presented with their 95% confidence interval using league tables. By constructing network maps and comparison-adjusted funnel plots, a visual assessment of the inter-interventional relation and publication bias in each NMA model will happen, respectively. The best-ranked intervention prediction for respective outcomes will transpire using the surface under the cumulative ranking curve values. The Stata statistical software (version 16) will be used for analysis, and statistical significance will be determined at p<0.05 and 95% confidence interval.

TRIAL REGISTRATION

PROSPERO registration number: CRD42020214378.

Evaluation of quality of life in diabetic pregnant women

AIMS

Gestational diabetes is the most common clinical complication during pregnancy. Women with gestational diabetes face many problems in their personal, family and social lives that affect their quality of life. The aim of this study was to evaluate the quality of life of diabetic pregnant women.

METHODS

This study was a descriptive study and the study population was all diabetic pregnant women referred to health centers in Kermanshah, Iran in 2019-2020. The studied variables were collected using a short form of quality of life questionnaire (WHOQOL-BREF-26 items). Then, with the help of SPSS software version 25, data analysis was performed based on frequency table and independent t-test.

RESULTS

101 pregnant women with gestational diabetes were studied. Their mean age was 33.06 ± 05.05 years. The quality of life of all mothers participating in the study was above average. The average quality of life and psychological domains, social and environmental relationships of mothers were higher in people with higher incomes and employment, and also the average quality of life and psychological domains, social and environmental relationships were higher in mothers who had less than 6 months.

CONCLUSIONS

The majority of mothers were overweight (BMI = 25-29.9) and obese (BMI ≥ 30), which is one of the most important risk factors for gestational diabetes. Given the importance of quality of life of pregnant mothers, health policy makers are asked to provide more training for pregnant mothers on nutrition and increased physical activity to prevent gestational diabetes and improve their quality of life.

Longitudinal trends in lipid profiles during pregnancy: Association with gestational diabetes mellitus and longitudinal trends in insulin indices

OBJECTIVE

To investigate the correlation of trends in lipid profiles from first to second trimester with trends in insulin indices and gestational diabetes mellitus (GDM).

METHODS

Secondary analysis of an ongoing prospective cohort study was conducted on 1234 pregnant women in a single center. Lipid profiles, glucose metabolism and insulin indices were collected in the first and second trimesters. Trends in lipid profiles were divided into four subgroups: low-to-low, high-to-high, high-to-low and low-to-high group. Insulin indices including homeostasis model assessment of insulin resistance and quantitative insulin sensitivity check index were calculated to evaluate insulin resistance (IR). Trends in insulin indices were described as: no IR, persistent IR, first-trimester IR alone and second-trimester IR alone. Pearson correlation analysis and multivariate logistic regression were performed to assess the associations of lipid profiles subgroups with insulin indices and GDM.

RESULTS

First- and second-trimester total cholesterol (TC), triglycerides (TG) and high-density lipoprotein cholesterol were strongly correlated to first- and second-trimester insulin indices. Only TG had a sustained correlation with glucose metabolism indices. High-to-high low-density lipoprotein cholesterol (LDL-c) was an independent risk factor for GDM. High-to-high TG and high-to-low TG groups were independent risk factors for persistent IR. High-to-high TG and low-to-high TG groups were independent risk factors for second-trimester IR alone.

CONCLUSION

TG has a sustained correlation with insulin indices and glucose metabolism indices. Persistently high TG is an independent risk factor for persistent IR and second-trimester IR alone. Regardless of whether pregnant women have first-trimester IR, lower TG levels help reduce the risk for persistent IR or subsequent development of IR. These results highlight the benefit of lowering TG levels in early and middle pregnancy to prevent the development of IR.

The effects of pre-pregnancy obesity and gestational weight gain on maternal lipid profiles, fatty acids and insulin resistance

OBJECTIVES

Pregnancy is associated with physiological alterations in insulin sensitivity and lipid metabolism. This study investigates the associations between pregestational body mass index (pBMI) and the rate of gestational weight gain (rGWG) in the second trimester with the biomarkers of lipid, fatty acids metabolism and insulin resistance.

METHODS

Sixty nine pregnant women followed. The body weights of the pregnant women were measured and blood samples were obtained at 11-14th and 24-28th weeks of pregnancy. Glucose, total cholesterol, triglyceride, HDL cholesterol, LDL cholesterol, insulin levels and fatty acids were measured. Rate of GWG (kg/week) and The Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) were calculated. The pregnant women were stratified according to their pBMI and the 2nd trimester rGWG.

RESULTS

The rate of GWG was significantly higher for the group with pBMI<25, compared to the group with pBMI≥25 (p=0.024). Triglyceride, total cholesterol, LDL and HDL cholesterol were significantly increased in the second trimester compared with the first trimester. Palmitic acid, oleic acid, linoleic acid, myristic acid, docosahexaenoic acid (DHA), arachidonic acid (AA), total omega-6 (n - 6) and omega-3 (n - 3) fatty acid levels and n - 6/n - 3 ratio were significantly higher in the second trimester. Glucose was significantly decreased and insulin was increased in the second trimester. In the overweight/obese group; HOMA-IR, insulin, AA, palmitoleic acid and stearic acid were found to be high in comparison to the group with low/normal pBMI. No parameters were associated with rGWG.

CONCLUSIONS

The changes in lipid parameters, free fatty acids, insulin and HOMA-IR in the second trimester were compatible with the changes in lipid metabolism and the development of insulin resistance. Pregestational BMI was shown to have a stronger influence on lipid profile, insulin resistance, and fatty acids than rGWG.

Maternal Adiposity and Energy Balance After Normotensive and Preeclamptic Pregnancies

BACKGROUND

Preeclampsia is a major pregnancy complication associated with long-term maternal cardiometabolic disease. Research generally is focused on metabolic and pathophysiological changes during pregnancy; however, there is much less focus on the early postpartum period in subjects who suffered preeclampsia. The aim of this study was to (1) characterize energy intake and expenditure 6 months following normotensive and preeclamptic pregnancies and (2) examine associations between energy balance, body composition, insulin resistance measures (HOMA-IR), and clinical characteristics.

DESIGN

A cross-sectional study 6 months following normotensive (n = 75) and preeclamptic (n = 22) pregnancies was performed. Metabolic measurements included anthropometrics measures, body composition via bioelectrical impedance analysis, 24-h energy expenditure via SenseWear Armbands, energy intake via a 3-day food diary, and serum metabolic parameters.

RESULTS

Six months following preeclampsia, women had a significantly higher weight (77.3 ± 20.9 kg vs 64.5 ± 11.4 kg, P = 0.01), fat mass percentage (FM%; 40.7 ± 7.4% vs 34.9 ± 8.1%, P = 0.004), and insulin resistance (HOMA-IR 2.2 ± 1.5 vs 1.0 ± 0.7, P = 0.003), as well as reduced HDL levels (1.5 ± 0.4 mmol/L vs 1.8 ± 0.4 mmol/L, P = 0.01) compared to normotensive women. Women post-preeclampsia had lower activity-related energy expenditure (P = 0.02) but a decreased total energy intake (P = 0.02), leading to a more negative energy balance compared to their normotensive counterparts (-1942 kJ/24 h vs -480 kJ/24 h, P = 0.02).

CONCLUSION

Increases in insulin resistance and FM%, reduced high-density lipoprotein, and more sedentary lifestyles characterize the postpartum period following preeclamptic compared with normotensive pregnancies. Early post-preeclampsia interventions, such as lifestyle behavior change, should be implemented and assessed to determine whether they reduce long-term cardiometabolic risk in women who experienced preeclampsia during pregnancy.

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.

Association of Common Genetic Risk Variants With Gestational Diabetes Mellitus and Their Role in GDM Prediction

OBJECTIVE

We aimed to explore the associations between common genetic risk variants with gestational diabetes mellitus (GDM) risk in Russian women and to assess their utility in the identification of GDM cases.

METHODS

We conducted a case-control study including 1,142 pregnant women (688 GDM cases and 454 controls) enrolled at Almazov National Medical Research Centre. The International Association of Diabetes and Pregnancy Study Groups criteria were used to diagnose GDM. A total of 11 single- nucleotide polymorphisms (SNPs), including those in HKDC1 (rs10762264), GCK (rs1799884), MTNR1B (rs10830963 and rs1387153), TCF7L2 (rs7903146 and rs12255372), KCNJ11 (rs5219), IGF2BP2 (rs4402960), IRS1 (rs1801278), FTO (rs9939609), and CDKAL1 (rs7754840) were genotyped using Taqman assays. A logistic regression model was used to calculate odds ratios (ORs) and their confidence intervals (CIs). A simple-count genetic risk score (GRS) was calculated using 6 SNPs. The area under the receiver operating characteristic curve (c-statistic) was calculated for the logistic regression model predicting the risk of GDM using clinical covariates, SNPs that had shown a significant association with GDM in our study, GRS, and their combinations.

RESULTS

Two variants in MTNR1B (rs1387153 and rs10830963) demonstrated a significant association with an increased risk of GDM. The association remained significant after adjustment for age, pre-gestational BMI, arterial hypertension, GDM in history, impaired glucose tolerance, polycystic ovary syndrome, family history of diabetes, and parity (P = 0.001 and P < 0.001, respectively). After being conditioned by each other, the effect of rs1387153 on GDM predisposition weakened while the effect of rs10830963 remained significant (P = 0.004). The risk of GDM was predicted by clinical variables (c-statistic 0.712, 95 % CI: 0.675 - 0.749), and the accuracy of prediction was modestly improved by adding GRS to the model (0.719, 95 % CI 0.682 - 0.755), and more by adding only rs10830963 (0.729, 95 % CI 0.693 - 0.764).

CONCLUSION

Among 11 SNPs associated with T2D and/or GDM in other populations, we confirmed significant association with GDM for two variants in MTNR1B in Russian women. However, these variants showed limited value in the identification of GDM cases.

β-Cell function or insulin resistance was associated with the risk of type 2 diabetes among women with or without obesity and a history of gestational diabetes

INTRODUCTION

To evaluate the single association of postpartum β-cell dysfunction and insulin resistance (IR), as well as different combinations of postpartum β-cell dysfunction, IR, obesity, and a history of gestational diabetes mellitus (GDM) with postpartum type 2 diabetes risk.

RESEARCH DESIGN AND METHODS

The study included 1263 women with prior GDM and 705 women without GDM. Homeostatic model assessment was used to estimate homeostatic model assessment of β-cell secretory function (HOMA-%β) and homeostatic model assessment of insulin resistance (HOMA-IR).

RESULTS

Multivariable-adjusted ORs of diabetes across quartiles of HOMA-%β and HOMA-IR were 1.00, 1.46, 2.15, and 6.25 (p_trend <0.001), and 1.00, 2.11, 5.59, and 9.36 (p_trend <0.001), respectively. Women with IR only had the same diabetes risk as women with β-cell dysfunction only. Obesity, together with IR or β-cell dysfunction, had a stronger effect on diabetes risk. This stronger effect was also found for a history of GDM with IR or β-cell dysfunction. Women with three risk factors, including obesity, a history of GDM and β-cell dysfunction/IR, showed the highest ORs of diabetes.

CONCLUSIONS

β-cell dysfunction or IR was significantly associated with postpartum diabetes. IR and β-cell dysfunction, together with obesity and a history of GDM, had the highest ORs of postpartum diabetes risk.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Pretransplant Homeostasis Model Assessment of Insulin Resistance and Fasting Plasma Glucose Predict New-Onset Diabetes After Renal Transplant in Chinese Patients

BACKGROUND AND AIM

The present study aims to determine if homeostasis model assessment of insulin resistance (HOMA-IR) index, fasting plasma glucose (FPG), and plasma insulin (Ins) are able to predict development of new onset diabetes after transplant (NODAT) for kidney recipients.

METHODS

We performed a single-center retrospective study of 123 nondiabetic patients receiving a first renal transplant. The NODAT was diagnosed between 1 month and 1 year post transplant. Both univariate and multivariable analyses, including logistic regression analysis and Cox proportional hazards model, were applied to dissect potential pretransplant risk factors of NODAT.

RESULTS

A total of 26.8% (33/123) of recipients developed NODAT in the first year post transplant. The NODAT patients showed higher HOMA-IR index and increased levels of FPG and Ins than non-NODAT. Interestingly, we consistently revealed that both FPG (logistic: odds ratio [OR], 3.17 [1.41-6.45]; P = .01; Cox: OR, 2.75 [1.26-4.56]; P = .02) and HOMA-IR index (logistic: OR, 1.73 [1.21-2.87]; P = .02; Cox: OR, 1.72 [1.21-2.46]; P = .002) robustly predicted the development of NODAT. However, these analyses showed that neither plasma Ins nor hemoglobin A_1c was associated with NODAT.

CONCLUSION

Our findings suggest that pretransplant HOMA-IR and FPG are independent predictors for the development of NODAT in Chinese nondiabetic patients receiving a first renal transplant.

The association of quantitative insulin sensitivity indices (HOMA-IR and QUICKI) with anthropometric and cardiometabolic indicators in adolescents

Introduction

Homoeostasis model assessment (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI) are used to evaluate insulin resistance. The aim of this study was to investigate the association between quantitative insulin sensitivity indices and anthropometric and cardiometabolic indicators in adolescents.

Material and methods

This descriptive-analytic cross-sectional study was conducted on 80 adolescents aged 12 to 13 years in Isfahan, Iran. Anthropometric, cardiometabolic and QUICKI and HOMA-IR indicators were measured. In the results analysis, Pearson correlation coefficient and regression analysis were used.

Results

There was a significant positive correlation between most of the anthropometric indicators and the HOMA-IR index and a significant negative correlation with QUICKI (all p < 0.0001). Moreover, serum triglyceride level had a significant negative correlation with QUICKI index (R = –0.33, p = 0.002) and systolic blood pressure (R = 0.44, p < 0.0001), and triglyceride level (R = 0.66, p < 0.0001) had a significant positive correlation with HOMA index. The results of these two indices were highly correlated in most of the anthropometric and biochemical indices, except for the waist circumference to the neck circumference ratio and systolic blood pressure, which had a significant positive association with HOMA-IR, but did not show a significant association with QUICKI index.

Conclusions

A significant correlation between anthropometric and cardiometabolic indicators with insulin resistance indices (HOMA-IR and QUICKI) was found. Moreover, the results of these two indices were highly correlated in most of the anthropometric and biochemical indices, except for the waist circumference to the neck circumference ratio and systolic blood pressure.

First trimester prediction of gestational diabetes mellitus using plasma biomarkers: a case-control study

Objectives To evaluate the first trimester maternal biomarkers for early pregnancy prediction of gestational diabetes mellitus (GDM). Methods The study was a case-control study of healthy women with singleton pregnancies at the first trimester carried out at the Obstetrics and Gynecology Unit, Clinica Davila, Santiago, Chile. After obtaining informed consent, peripheral blood samples of pregnant women under 14 weeks of gestation were collected. At 24-28 weeks of pregnancy, women were classified as GDM (n=16) or controls (n=80) based on the results of a 75-g oral glucose tolerance test (OGTT). In all women, we measured concentrations of fasting blood glucose, insulin, glycated hemoglobin, uric acid, cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), triglycerides, aspartate aminotransferase (AST), alanine aminotransferase (ALT), γ-glutamyl transpeptidase (GGT), alkaline phosphatase (AP), sex hormone-binding globulin (SHBG), adiponectin, tissue plasminogen activator (t-PA), leptin and placental growth factor (PGF). Results The GDM group displayed an increased median concentration of cholesterol (P=0.04), triglycerides (P=0.003), insulin (P=0.003), t-PA (P=0.0088) and homeostatic model assessment (HOMA) (P=0.003) and an increased mean concentration of LDL (P=0.009) when compared to the control group. The receiver operating characteristic (ROC) curve for significant variables achieved an area under the curve (AUC) of 0.870, a sensitivity of 81.4% and a specificity of 80.0%. The OGTT was positive for GDM according to the IADPSG (International Diabetes in Pregnancy Study Group) criteria. Conclusion Women who subsequently developed GDM showed higher levels of blood-borne biomarkers during the first trimester, compared to women who did not develop GDM. These data warrant validation in a larger cohort.

Individual free fatty acids have unique associations with inflammatory biomarkers, insulin resistance and insulin secretion in healthy and gestational diabetic pregnant women

OBJECTIVE

We investigated the relationships of maternal circulating individual free fatty acids (FFA) with insulin resistance, insulin secretion and inflammatory biomarkers during mid-pregnancy.

RESEARCH DESIGN AND METHODS

The data were drawn from a prospective cohort of generally healthy pregnant women (n=1368, African-American 36%, Hispanic 48%, Caucasian 16%) in Camden, NJ. We quantitatively determined 11 FFAs, seven cytokine/adipokine, homeostatic model assessment of insulin resistance (HOMA-IR) and C-peptide levels from the fasting blood samples that were collected at 16 weeks of gestation. Multivariate analyses were performed along with separate analyses for each individual FFA.

RESULTS

High HOMA-IR (p<0.001) and C-peptide (p<0.0001) levels were positively associated with a twofold to fourfold increased risk for developing gestational diabetes mellitus (GDM). Negative relationships were found with specific FFAs (molecular percentage, palmitoleic, oleic, linolenic, myristic acids) and HOMA-IR and C-peptide levels (p<0.01 to p<0.0001). In contrast, palmitic, stearic, arachidonic, dihomo-γ-linolenic (DGLA) and docosahexaenoic acids were positively associated with HOMA-IR and C-peptide (p<0.01 to p<0.0001). The individual FFAs also predicted cytokine/adipokine levels. For example, women who had elevated DGLA (highest quartile) were twice as (adjusted OR 2.06, 95% CI 1.42 to 2.98) likely to have higher interleukin (IL)-8 (p<0.0001) levels. Conversely, women with high palmitoleic, oleic, and linolenic acid levels had reduced odds (≥2-fold, p<0.01 to p<0.001) for having higher IL-8, IL-6 or tumor necrosis factor-alpha levels.

CONCLUSION

Our results suggest that maternal individual FFAs uniquely affect insulin resistance and secretion. The effects are either direct or indirect via modulation of the inflammatory response. Modifying the composition of FFAs may help in reducing the risk of GDM.

Cod-Liver Oil Improves Metabolic Indices and hs-CRP Levels in Gestational Diabetes Mellitus Patients: A Double-Blind Randomized Controlled Trial

OBJECTIVE

To investigate the effects of cod-liver oil on metabolic status and high-sensitivity C-reactive protein (hs-CRP) in patients with gestational diabetes mellitus (GDM).

METHODS

This study was a randomized, double-blinded, placebo-controlled trial with the allocation ratio of 1 : 1. The contents of EPA and DHA in cod-liver oil were measured using a gas chromatograph. A total of 550 GDM patients were randomly divided into the intervention group (cod-liver oil) and the control group (placebo, mineral oil), and both groups were given regular dietary care. Glycosylated hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), 2-hour plasma glucose (2hPG), lipid profiles, homeostatic model assessment insulin resistance (HOMA-IR), and hs-CRP were measured. Primary outcomes were different in HbA1c, FPG, 2hPG, and HOMA-IR between the two groups after 4-week randomization. Secondary outcomes were the blood glucose levels and perinatal complications (pregnancy-induced hypertension, polyhydramnios, premature delivery, postpartum hemorrhage, postpartum infection, premature rupture of membranes, and cesarean section) between the two groups before and after 12-16 weeks of cod-liver oil intervention from middle pregnancy to late pregnancy.

RESULTS

EPA and DHA were the main components of cod-liver oil with 76 mg/mL and 150 mg/mL, respectively. There was no significant difference for primary outcomes in the levels of HbA1c, FPG, 2hPG, HOMA-IR, and lipid profiles between the two groups (P > 0.05). For the secondary outcomes, the levels of HbA1c, FPG, 2hPG, triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol ratio (LDL-C), HOMA-IR, and hs-CRP in the intervention group were significantly lower than those in the control group (P < 0.05). The incidence of perinatal complications in the intervention group was lower than that in the control group too (P < 0.05).

CONCLUSIONS

Cod-liver oil consumption effectively reduced the levels of blood glucose, lipid levels, hs-CRP, and HOMA-IR and the incidence of perinatal complications.

Central Obesity Increases the Risk of Gestational Diabetes Partially Through Increasing Insulin Resistance

OBJECTIVE

This study examined the associations of central obesity measures, waist to hip ratio (WHR) and waist circumference (WC), in early pregnancy with subsequent risk of gestational diabetes mellitus (GDM) and evaluated the potential mediating role of insulin resistance markers.

METHODS

Within the prospective Pregnancy Environment and Lifestyle Study cohort of 1,750 women, WC and hip circumference were measured at gestational weeks 10 to 13. In a nested case-control study within the cohort, 115 GDM cases and 230 controls had fasting serum insulin, homeostatic model assessment of insulin resistance (HOMA-IR), and adiponectin measurements at gestational weeks 16 to 19. Poisson and conditional logistic regression models were used, adjusting for established risk factors for GDM, including prepregnancy overweight or obesity.

RESULTS

For women with WHR < 0.85, one or more established risk factors increased GDM risk 1.99-fold (95% CI: 0.99-4.02). For women with WHR ≥ 0.85 but no established risk factors, GDM risk increased 2.41-fold (95% CI: 1.14-5.06), and in those with established risk factors it increased 6.22-fold (95% CI: 3.49-11.10). Similar but attenuated results were observed for WC ≥ 88 cm. Insulin, HOMA-IR, and adiponectin levels mediated the WHR-GDM association by 9% to 11%; corresponding mediation proportions for the WC-GDM association were 35% to 41% (all P  < 0.04).

CONCLUSIONS

Central obesity in early pregnancy represented a high-risk phenotype for GDM independent of other risk factors, including overweight or obesity, and may inform early screening and prevention strategies.

Impact of risk factors for gestational diabetes (GDM) on pregnancy outcomes in women with GDM

PURPOSE

In this study, we evaluated the impact of risk factors for gestational diabetes on clinical/biochemical parameters and maternal/fetal outcomes.

METHODS

One hundred eighty-three (n 183) women (age 33.8 ± 5.5 years, 59% Caucasians, 41% non-Caucasians) with gestational diabetes were included in the study. Anamnestic information, anthropometric and laboratory parameters, and maternal and fetal outcomes at delivery were collected.

RESULTS

Insulin therapy prevalence was higher in Asians vs Caucasians (p = 0.006), despite lower pre-pregnancy BMI in Asians (p = 0.0001) and in pre-pregnancy overweight vs normal weight patients (p = 0.04). Insulin-treated patients had higher fasting OGTT glucose than patients on diet therapy (p = 0.003). In multivariate analysis, Asian ethnicity, age ≥ 35 years and pre-pregnancy BMI ≥ 25 kg/m² were independent predictors of insulin therapy. Cesarean section occurred more in women aged ≥ 35 years than < 35 years (p = 0.02). Duration of pregnancy and age showed inverse correlation (r - 0.3 p = 0.013). Week of delivery was lower in patients ≥ 35 years vs patients < 35 years (p = 0.013). Fasting OGTT glucose was higher in overweight than in normal weight patients (p = 0.016). 1-h OGTT glucose was lower in obese vs normal weight (p = 0.03) and overweight patients (p = 0.03). Prevalence of prior gestational diabetes was higher in overweight/obese women (p = 0.002).

CONCLUSIONS

Ethnicity, age, and BMI have the heaviest impact on pregnancy outcomes.

Group-based developmental BMI trajectories, polycystic ovary syndrome, and gestational diabetes: a community-based longitudinal study

BACKGROUND

Obesity is common in young women, increasing insulin resistance (IR) and worsening pregnancy complications, including gestational diabetes (GDM). Women with polycystic ovary syndrome (PCOS) are commonly obese, which aggravates the severity of PCOS clinical expression. Relationships between these common insulin-resistant conditions, however, remain unclear.

METHODS

We conducted a secondary analysis of the Australian Longitudinal Study on Women's Health (ALSWH) database, including data from 8009 women aged 18-36 years across six surveys. We used latent-curve growth modelling to identify distinct body mass index (BMI) trajectories and multinomial logistic regression to explore sociodemographic and health variables characterizing BMI group membership. Logistic regression was used to assess independent risk of GDM.

RESULTS

A total of 662 women (8.29%, 95% CI 7.68-8.89) reported PCOS. Three distinct BMI trajectories emerged, namely low stable (LSG) (63.8%), defined as an average trajectory remaining at ~25 kg/m²; moderately rising (MRG) (28.8%), a curvilinear trajectory commencing in a healthy BMI and terminating in the overweight range; and high-rising (HRG) (7.4%), a curvilinear trajectory starting and terminating in the obese range. A high BMI in early reproductive life predicted membership in higher trajectories. The HRG BMI trajectory was independently associated with GDM (OR 2.50, 95% CI 1.80-3.48) and was a stronger correlate than PCOS (OR 1.89, 95% CI 1.41-2.54), maternal age, socioeconomic status, or parity.

CONCLUSION

Our results suggest heterogeneity in BMI change among Australian women of reproductive age, with and without PCOS. Reducing early adult life weight represents an ideal opportunity to intervene at an early stage of reproductive life and decreases the risk of long-term metabolic complications such as GDM.

Mid-arm muscle circumference as a surrogate in predicting insulin resistance in non-obese elderly individuals

The homeostatic model assessment of insulin resistance (HOMA-IR) was used to measure the degree of insulin resistance (IR). Previous literature revealed that mid-arm muscle circumference (MAMC) is one of the anthropometric indicators for nutritional status and the relationship between MAMC and HOMA-IR remains uncertain in the obese and non-obese elderly individuals. The present study included 5,607 participants aged between 60 to 84 years old, using data from the 1999 to 2006 National Health and Nutrition Examination Survey (NHANES). To further explore the association between HOMA-IR and MAMC in the obese and non-obese elderly population using multivariate Cox regression analyses, we divided the participants into obese (BMI ≥ 30 kg/m²) group and non-obese (19 ≤ BMI < 30 kg/m²) group in this study; each group was then divided into quartiles based on their MAMC levels. A positive association was noted between the MAMC and HOMA-IR in all of the designed models initially. After adjusting for multiple covariates, a higher level of the MAMC was significantly associated with elevated HOMA-IR (P < 0.05) in the non-obesity group, which was not the case in the obesity group. Additionally, subjects in the higher quartiles of MAMC tended to have higher HOMA-IR with a significant association (P for trend = 0.003 in model 1; P for trend < 0.001 in model 2, 3, and 4). These results demonstrated that the MAMC can be an auxiliary indicator of HOMA-IR in non-obese elderly individuals and may have substantial additional value in screening for IR if well extrapolated.

Influence of exercise intervention on gestational diabetes mellitus: a systematic review and meta-analysis

AIMS

Exercise intervention might be a promising approach to prevent gestational diabetes mellitus. However, the results remained controversial. We conducted a systematic review and meta-analysis to explore the effect of exercise intervention on gestational diabetes mellitus.

METHODS

PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases were systematically searched. Randomized controlled trials (RCTs) assessing the effect of exercise intervention on gestational diabetes mellitus were included. Two investigators independently searched articles, extracted data, and assessed the quality of included studies. The primary outcome was the incidence of gestational diabetes mellitus, preterm birth, and gestational age at birth. Meta-analysis was performed using random-effect model.

RESULTS

Five RCTs involving 1872 patients were included in the meta-analysis. Overall, compared with control intervention, exercise intervention was found to significantly reduce the risk of gestational diabetes mellitus (std. mean difference 0.62; 95% CI 0.43-0.89; P = 0.01), but demonstrated no influence on preterm birth (OR 0.93; 95% CI 0.44-1.99; P = 0.86), gestational age at birth (std. mean difference -0.03; 95% CI -0.12 to 0.07; P = 0.60), glucose 2-h post-OGTT (std. mean difference -1.02; 95% CI -2.75 to 0.71; P = 0.25), birth weight (std. mean difference -0.10; 95% CI -0.25 to 0.04; P = 0.16), Apgar score less than 7 (OR 0.78; 95% CI 0.21-2.91; P = 0.71), and preeclampsia (OR 1.05; 95% CI 0.53-2.07; P = 0.88).

CONCLUSIONS

Compared to control intervention, exercise intervention was found to significantly reduce the incidence of gestational diabetes mellitus, but had no significant influence on preterm birth, gestational age at birth, glucose 2-h post-OGTT, birth weight, Apgar score less than 7, and preeclampsia.

Analysis of the main risk factors for gestational diabetes diagnosed with International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria in multiple pregnancies

INTRODUCTION

The aim is to investigate the proportion of multiple pregnancies with gestational diabetes mellitus (GDM) diagnosed using the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria and to identify the impact of age, body mass index (BMI), and mode of conception on incidence of GDM.

MATERIALS AND METHODS

This is a single center, retrospective cohort study on 656 multiple pregnancies screened for GDM with 75-g, 2-h oral glucose tolerance test at 24-28 weeks of gestation, between January 2010 and January 2016. The diagnosis of gestational diabetes mellitus (GDM) was reached through the IADPSG.

RESULTS

The incidence of GDM in our population was 15.1%. When patients who conceived through heterologous assisted reproduction technology were compared with those who conceived spontaneously, there was a significant difference for GDM (31.1 vs 13.6%, p < 0.001, OR 2.86). A similar finding was also observed comparing egg donation IVF/ICSI patients with homologous IVF/ICSI patients (31.1 vs 14.8%, p = 0.006, OR 2.59). Incidence of GDM was significantly higher in obese than in non-obese patients (42.5 vs 14.8%, p < 0.001, OR 4.88) and in women over 35 compared to younger patients (18.4 vs 11.1%, p = 0.01, OR 1.81). Logistic regression comparing the diabetes onset with conception mode gave a p = 0.07. The calculation of the Chi-square and odds ratio for single mode of conception showed that homologous vs conceived spontaneously p = 0.90, OR 0.97, heterologous vs homologous p = 0.01 with OR 2.46, and heterologous vs conceived spontaneously p = 0.01 with OR 2.39. Logistic regression showed that age and BMI are risk factors for developing GDM, respectively, p = 0.03 with OR 1.4 and p < 0.01 and OR 1.09.

DISCUSSION

The contribution our study can make is improved counseling about GDM risks for couples with multiple pregnancies. Our data support the role of age, BMI, and mode of conception as risk factors for GDM in multiple pregnancies.

Gestational diabetes mellitus: an updated overview

The clinical and public health relevance of gestational diabetes mellitus (GDM) is widely debated due to its increasing incidence, the resulting negative economic impact, and the potential for severe GDM-related pregnancy complications. Also, effective prevention strategies in this area are still lacking, and controversies exist regarding diagnosis and management of this form of diabetes. Different diagnostic criteria are currently adopted worldwide, while recommendations for diet, physical activity, healthy weight, and use of oral hypoglycemic drugs are not always uniform. In the present review, we provide an update of current insights on clinical aspects of GDM, by discussing the more controversial issues.

Quality of Life in Women with Gestational Diabetes Mellitus: A Systematic Review

Background and Objective. Diagnosis of Gestational Diabetes Mellitus (GDM) could significantly increase the likelihood of health problems concerning both potential risks for the mother, fetus, and child's development and negative effects on maternal mental health above all in terms of a diminished Quality of Life (QoL). The current systematic review study is aimed at further contributing to an advancement of knowledge about the clinical link between GDM and QoL. Methods. According to PRISMA guidelines, PubMed, Web of Science, Scopus, and Cochrane databases were searched for studies aimed at evaluating and/or improving levels of QoL in women diagnosed with GDM. Results. Fifteen research studies were identified and qualitatively analyzed by summarizing results according to the following two topics: GDM and QoL and interventions on QoL in patients with GDM. Studies showed that, in women with GDM, QoL is significantly worse in both the short term and long term. However, improvements on QoL can be achieved through different intervention programs by enhancing positive diabetes-related self-management behaviors. Conclusion. Future studies are strongly recommended to further examine the impact of integrative programs, including telemedicine and educational interventions, on QoL of GDM patients by promoting their illness acceptance and healthy lifestyle behaviors.

Molecular Analysis of a Genetic Variants Panel Related to Nutrients and Metabolism: Association with Susceptibility to Gestational Diabetes and Cardiometabolic Risk in Affected Women

Gestational diabetes mellitus (GDM) is the most frequent metabolic disorder in pregnancy. Women with a GDM history are at increased risk of developing diabetes and cardiovascular diseases. Studies have demonstrated a significant correlation between several genes involved in the metabolic pathway of insulin and environmental factors. The aim of this study was to investigate the relationship between clinical parameters in GDM and variants in genes involved with nutrients and metabolism. Several variants PPARG2 rs1801282 (C>G); PPARGC1A rs8192678 (C>T); TCF7L2 rs7903146 (C>T); LDLR rs2228671 (C>T); MTHFR rs1801133 (C>T); APOA5 rs662799 (T>C); GCKR rs1260326 (C>T); FTO rs9939609 (T>A); MC4R rs17782313 (T>C) were genotyped in 168 pregnant Caucasian women with or without GDM by High Resolution Melting (HRM) analysis. A significant correlation was observed between TT genotype of TCF7L2 gene and increased risk of GDM (OR 5.4 [95% CI 1.5-19.3]). Moreover, a significant correlation was observed between lipid parameters and genetic variations in additional genes, namely, PPARG2 [p = 0,02], APOA5 [p = 0,02], MC4R [p = 0,03], LDLR [p = 0,01], and FTO [p = 0,02]. Our findings support the association between TCF7L2 rs7903146 variant and an increased GDM risk. Results about the investigated genetic variants provide important information about cardiometabolic risk in GDM and help to plan future prevention studies.