Associations between insulin resistance and adverse pregnancy outcomes in women with gestational diabetes mellitus: a retrospective study

Gestational glucose intolerance among pregnant women at the Cape Coast Teaching Hospital

BACKGROUND

Malaria in pregnancy can have adverse outcomes if untreated. Both malaria and pregnancy are associated with insulin resistance and diabetes. Although malaria is treated prophylactically with gestational diabetes mellitus (GDM) screened for in pregnancy as part a routine antenatal care, their impacts have not been examined in terms of other forms of dysglycaemia. This cross-sectional study examined insulin resistance and its relationship with dysglycaemia and malaria among pregnant women in the Cape Coast Teaching Hospital (CCTH).

METHODS

Using a structured questionnaire, demographic and clinical information were obtained from 252 pregnant women aged 18-42 years. Weight and height were measured for computation of body mass index (BMI). Measurement of insulin, lipid profile and glucose were taken under fasting conditions followed by oral glucose tolerant test. Insulin resistance and beta-cell function were assessed by the homeostatic model as malaria was diagnosed by microscopy.

RESULTS

The respective prevalence of GDM, gestational glucose intolerance (GGI) and insulin resistance were 0.8% (2/252), 19.44% (49/252) and 56.75% (143/252). No malaria parasite or dyslipidaemia was detected in any of the participants. Apart from BMI that increased across trimesters, no other measured parameter differed among the participants. Junior High School (JHS) education compared with no formal education increased the odds (AOR: 2.53; CI: 1.12-5.71; P = 0.03) but 2nd trimester of pregnancy compared to the 1st decreased the odds (AOR: 0.32; CI: 0.12-0.81; P = 0.02) of having insulin resistance in the entire sample. In a sub-group analysis across trimesters, pregnant women with JHS education in their 3rd trimester had increased odds (AOR: 4.41; CI: 1.25-15.62; P = 0.02) of having insulin resistance.

CONCLUSION

Prevalence of GDM and GGI were 0.8% and 19.44% respectively. The odds of insulin resistance increased in pregnant women with JHS education in the 3rd trimester. Appropriate measures are needed to assuage the diabetogenic risk posed by GGI in our setting.

Triglyceride-glucose index: A promising biomarker for predicting risks of adverse pregnancy outcomes in Hangzhou, China

Introduction

The triglyceride-glucose (TyG) index has been recommended as an alternative indicator of insulin resistance (IR). However, the association between the TyG index and adverse pregnancy outcomes remains to be elucidated.

Methods

The present retrospective study was conducted at Women's Hospital, Zhejiang University School of Medicine and involved a total of 8,514 participants. Maternal fasting lipid profiles and glucose concentrations were measured. Based on the TyG index, the participants were categorized into quartiles. Logistic regression analysis was used to calculate odds ratios (ORs) for each quartile with reference to the first quartile, while receiver operating characteristic (ROC) curve analysis, Hosmer-Lemeshow test, and calibration curve analysis were employed to evaluate the predictive ability of the TyG index for adverse pregnancy outcomes.

Results

The TyG index was higher in patients with preeclampsia, preterm birth, and macrosomia. On univariate analysis, there was an increased risk of developing adverse pregnancy outcomes with increasing quartiles of the TyG. After adjusting for potential confounders in multivariable logistic regression analysis, a positive independent correlation was found between the TyG index and preeclampsia, preterm birth, and macrosomia. In ROC curve analysis for predicting the risks of preeclampsia, preterm birth, and macrosomia, the area under the curve (AUC) could reach 0.665, 0.588, and 0.606, respectively. These predictive models demonstrated good calibration (all P > 0.05).

Conclusions

The TyG index showed a good predictive capacity for assessing the risk of adverse pregnancy outcomes, and it should receive sufficient clinical attention.

Triglyceride-glucose index in early pregnancy predicts the risk of gestational diabetes: a prospective cohort study

OBJECTIVE

This study aimed to investigate the association between the triglyceride-glucose (TyG) index in early pregnancy and the development of gestational diabetes mellitus (GDM) in the second trimester. The primary objectives were to evaluate the predictive potential of the TyG index for GDM, determine the optimal threshold value of the TyG index for GDM assessment, and compare the predictive performance of the TyG index alone versus its combination with maternal age and pre-pregnancy body mass index on GDM. Moreover, the study explored the association between the TyG index in early pregnancy and the risk of other pregnancy-related complications (PRCs), such as placental abruption and gestational hypertension.

PATIENTS AND METHODS

This prospective cohort study recruited 1,624 pregnant women who underwent early pregnancy antenatal counseling and comprehensive assessments with continuous monitoring until delivery. To calculate the TyG index, health indicators, including maternal triglycerides and fasting plasma glucose, were measured in early pregnancy (< 14 weeks of gestation). The predictive power of the TyG index for evaluating GDM in Chinese pregnant women was determined using multifactorial logistic regression to derive the odds ratios and 95% confidence interval (CI). Subgroup analyses were conducted, and the efficacy of the TyG index in predicting PRCs was assessed via receiver operating characteristic (ROC) curve analysis and restricted cubic spline, with the optimal cutoff value calculated.

RESULTS

Logistic regression analyses revealed a 2.10-fold increase in the GDM risk for every 1-unit increase in the TyG index, after adjusting for covariates. The highest GDM risk was observed in the group with the highest TyG index compared with the lowest quintile group (odds ratios: 3.25; 95% CI: 2.23-4.75). Subgroup analyses indicated that exceeding the recommended range of gestational weight gain and an increased GDM risk were significantly associated (P = 0.001). Regarding predictive performance, the TyG index exhibited the highest area under the curve (AUC) value in the ROC curve for GDM (AUC: 0.641, 95% CI: 0.61-0.671). The optimal cutoff value was 8.890, with both sensitivity and specificity of 0.617.The combination of the TyG index, maternal age, and pre-pregnancy body mass index proved to be a superior predictor of GDM than the TyG index alone (AUC: 0.672 vs. 0.641, P < 0.01). After adjusting for multiple factors, the analyses indicated that the TyG index was associated with an increased risk of gestational hypertension. However, no significant association was noted between the TyG index and the risk of preeclampsia, placental abruption, intrauterine distress, or premature rupture of membranes.

CONCLUSION

The TyG index can effectively identify the occurrence of GDM in the second trimester, aligning with previous research. Incorporating the TyG index into routine clinical assessments of maternal health holds significant practical implications. Early identification of high-risk groups enables healthcare providers to implement timely interventions, such as increased monitoring frequency for high-risk pregnant women and personalized nutritional counseling and health education. These measures can help prevent or alleviate potential maternal and infant complications, thereby enhancing the overall health outcomes for both mothers and babies.

The influence of Chinese culture and customs on the beliefs and health-related behaviours of Chinese women with gestational diabetes mellitus: A qualitative study

OBJECTIVE

The study aimed to explore the influence of Chinese culture and customs on the beliefs and health-related behaviours of Chinese women with gestational diabetes mellitus (GDM).

METHODS

This descriptive qualitative study conducted semi-structured interviews with 15 Chinese women between November 2022 and January 2023. The interview data were analysed using thematic analysis.

RESULTS

Three major themes are found: (1) beliefs in health, (2) beliefs in illness and GDM and (3) beliefs in health-related behaviours. They worried about the negative effects of GDM on the infant and family, so they actively sought medical advice to maintain health. However, it is challenging for them to balance adhering to healthcare professionals' advice and avoiding practical difficulties in the impact of the Chinese sociocultural context.

CONCLUSION

This study emphasizes the influence of Chinese culture and customs on the beliefs and health-related behaviours of women with GDM. Healthcare providers should recognize the influence of Chinese culture, customs and beliefs on women with GDM and their families, in order to provide individualized education to help them maintain health-related behaviours.

Association of maternal insulin resistance with neonatal insulin resistance and body composition/size: a prospective cohort study in a sub-Saharan African population

PURPOSE

We prospectively evaluated the association of the insulin resistance of third-trimester Nigerian pregnant women with their newborn infants' insulin resistance and birth size. Pregnancy-associated insulin resistance (IR), often assessed with homeostatic model assessment of IR (HOMA-IR), is associated, especially among women with gestational diabetes (GDM), with abnormal neonatal birth size and body composition, predisposing the baby to metabolic disorders like diabetes and obesity. The associations of maternal IR with neonatal IR, birth size and body composition are less studied in nondiabetic pregnant women, especially in sub-Saharan settings like Nigeria.

METHODS

We originally recruited 401 third trimester, nondiabetic pregnant women to a prospective cohort study, followed up until birth. Blood samples of mothers and babies were obtained, respectively, at recruitment and within 24 hours postbirth for fasting serum glucose (FSG) and insulin (FSI) assays, and HOMA-IR was calculated as [(FSI × FSG)/22.5)].

RESULTS

Complete data for 150 mother-baby dyads was analysed: the mothers, with a mean (standard deviation [SD]) age of 31.6 (4.5) years, had live births at a mean (SD) gestational age of 39.2 weeks. The proportions of infants with wasting, stunting, impaired fetal growth (either wasting or stunted), small-for-gestation-age, large-for-gestational-age, low birthweight, and macrosomia were 4.2% (95% confidence interval, 1.1-10.3), 19.7% (12.9-28.0), 23.1% (15.8-31.8), 10.1% (5.3-17.0), 12.6% (7.2-19.9), 0.8% (0.02-4.5), and 5.0% (1.8-10.5), respectively. Maternal HOMA-IR was not associated with neonatal HOMA-IR (p=0.837), birth weight (p=0.416) or body composition measured with weight-length ratio (p=0.524), but birth weight was independently predicted by maternal weight (p=0.006), body mass index (p=0.001), and parity (p=0.012).

CONCLUSION

In this nondiabetic/non-GDM cohort, maternal HOMA-IR was not associated with neonatal IR, body size or body composition. Larger studies are required to confirm these findings, with addi-tional inclusion of mothers with hyperglycaemia for comparison.

Prevalence of Adverse Pregnancy Outcomes in Women With and Without Gestational Diabetes Mellitus in Al-Baha Region, Saudi Arabia

BACKGROUND

Gestational diabetes mellitus (GDM) is a condition characterized by glucose intolerance that develops during pregnancy. It is associated with adverse maternal and fetal outcomes and has long-term health implications for both the mother and the child. This study aimed to estimate the prevalence of adverse pregnancy outcomes in women with and without GDM in the Al-Baha region, Saudi Arabia.

METHODS

A cross-sectional study was conducted in the Al-Baha region from April 2023 to November 2023. The study included mothers residing in the Al-Baha region who were willing to participate and had access to a social media account. A simple random sampling technique was used, and the estimated sample size was 422. A self-administered electronic questionnaire was used to collect data on socio-demographic and lifestyle factors, as well as the pregnancy outcomes of diabetic and non-diabetic mothers. Descriptive and inferential statistical analyses were performed using IBM SPSS Statistics for Windows, Version 28.0 (Released 2012; IBM Corp., Armonk, New York, United States).

RESULTS

We included 422 women in the study with the majority of participants in the age group of 36-40 years(15.4%, n=74). Most participants (66.6%, n=321) had attained a university degree, and a significant proportion resided in Al-Baha City (52.3%, n=252). Maternal outcomes indicated a significant association between GDM and the development of eclampsia (OR = 8.296, 95%CI: 4.353-15.810, p < 0.001), as well as an increased risk of thyroid diseases (OR = 2.723, 95%CI: 1.428-5.193, p = 0.002). Fetal outcomes revealed a significant association between GDM and respiratory distress/lack of oxygen in newborns (OR = 2.032, 95%CI: 1.085-3.805, p = 0.024), and infants of GDM patients had a higher risk of hypoglycemia (OR = 8.099, 95%CI: 3.350-19.581, p < 0.001).

CONCLUSION

We found that GDM increased the risk of complications such as eclampsia, thyroid problems, and postpartum hemorrhage. GDM was also associated with shorter pregnancy durations, higher cesarean section rates, and an increased risk of developing type 2 diabetes post pregnancy. The study emphasized the importance of comprehensive GDM therapy and monitoring.

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM.

METHODS

Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA).

RESULTS

A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers.

CONCLUSIONS

Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Association Between Maternal Glucose Levels in Gestational Diabetes Screening and Subsequent Hypertension

BACKGROUND

We assessed the association between maternal glucose levels in pregnancy and subsequent hypertension.

METHODS

This population-level, retrospective cohort study examined women aged 12 to 54 years with singleton pregnancies completed at ≥29 weeks of gestation from October 1, 2008 to December 1, 2018 followed until March 31, 2019 in Alberta, Canada. Women were stratified by results in the 50-gram glucose challenge test and by 75-gram oral glucose tolerance test subtypes (normal oral glucose tolerance test, elevated fasting plasma glucose only [elevated fasting], elevated postload glucose only, or both elevated fasting and postload glucose [combined]. Time to development of hypertension was modeled using Cox proportional hazards models.

RESULTS

Of 313 361 women, 231 008 (79.1%) underwent a glucose challenge test only while 60 909 (20.9%) underwent either an oral glucose tolerance test only or both. Nine thousand five hundred eighty (3.1%) developed hypertension, and 2824 (0.9%) developed cardiovascular disease over a median follow-up of 5.7 years. Every 1-mmol/L increase in glucose in the glucose challenge test increased the risk of subsequent hypertension by 15% (adjusted hazard ratio and 95% CI, 1.15 [1.14-1.16]). Among those who underwent the oral glucose tolerance test, the combined group conferred the highest risk of subsequent hypertension, followed by elevated fasting, then elevated postload glucose only (reference: glucose challenge test ≤7.1 mmol/L, adjusted hazard ratio [95% CI]: elevated postload glucose only, 1.83 [1.68-2.00]; elevated fasting 2.02 [1.70-2.40]; combined, 2.65 [2.33-3.01]). No significant associations between maternal glucose levels and cardiovascular disease were observed.

CONCLUSIONS

Increasing maternal glucose levels in pregnancy were associated with increasing risk of subsequent hypertension. These findings may help identify higher-risk women who should be targeted for earlier postpartum cardiovascular risk reduction.

The Effect of 2016 Chinese second-child policy and different maternal age on pregnancy outcomes in Hebei Province, China

OBJECTIVE

To explore the effect of the 2016 Chinese second child policy and different maternal ages on adverse perinatal outcomes.

METHODS

Clinical data were collected from 22 monitoring hospitals in Hebei Province from January 1, 2013, to December 31, 2021. A total of 413,892 parturient were divided into 3 groups based on delivery age: 20-34, 35-39, and 40-55 years old. The clinical data were analyzed to explore the relationship among the 2016 Chinese second-child policy, maternal age, and various pregnancy risks.

RESULTS

Pregnancy complications showed an upward trend from 2013 to 2021.The top 10 incidences of pregnancy complications in Hebei Province were anemia, small for gestational age (SGA), large for gestational age (LGA), macrosomia, gestational diabetes mellitus (GDM), premature delivery, preeclampsia (PE), postpartum hemorrhage (PPH), placenta previa, and placental abruption. The two-child policy was implemented in 2016. The incidence of pregnancy complications, anemia, GDM, PE, placental abruption, cesarean delivery, premature delivery, SGA, LGA, macrosomia in 2016-2021 was significantly higher than that in 2013-2015 (P<0.05), and the proportion of women of advanced maternal age (AMA, ≥ 35 years old) increased from 2013 to 2021. Advanced maternal age was a risk factor for most assessed adverse pregnancy outcomes, including GDM, PE, placenta previa, placenta abruption, cesarean delivery, PPH, premature delivery, SGA, LGA and macrosomia.

CONCLUSION

After the adjustment of the "second-child" policy, the incidence of pregnancy complications increased. Moreover, the risk of adverse pregnancy outcomes in AMA has increased. Early prevention and intervention should be implemented to cope with the occurrence of adverse perinatal outcomes.

Maternal circulating metabolic biomarkers and their prediction performance for gestational diabetes mellitus related macrosomia

INTRODUCTION

Gestational diabetes mellitus (GDM), a metabolism-related pregnancy complication, is significantly associated with an increased risk of macrosomia. We hypothesized that maternal circulating metabolic biomarkers differed between women with GDM and macrosomia (GDM-M) and women with GDM and normal neonatal weight (GDM-N), and had good prediction performance for GDM-M.

METHODS

Plasma samples from 44 GDM-M and 44 GDM-N were analyzed using Olink Proseek multiplex metabolism assay targeting 92 biomarkers. Combined different clinical characteristics and Olink markers, LASSO regression was used to optimize variable selection, and Logistic regression was applied to build a predictive model. Nomogram was developed based on the selected variables visually. Receiver operating characteristic (ROC) curve, calibration plot, and clinical impact curve were used to validate the model.

RESULTS

We found 4 metabolism-related biomarkers differing between groups [CLUL1 (Clusterin-like protein 1), VCAN (Versican core protein), FCRL1 (Fc receptor-like protein 1), RNASE3 (Eosinophil cationic protein), FDR <  0.05]. Based on the different clinical characteristics and Olink markers, a total of nine predictors, namely pre-pregnancy body mass index (BMI), weight gain at 24 gestational weeks (gw), parity, oral glucose tolerance test (OGTT) 2 h glucose at 24 gw, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw, were identified by LASSO regression. The model constructed using these 9 predictors displayed good prediction performance for GDM-M, with an area under the ROC of 0.970 (sensitivity = 0.955, specificity = 0.886), and was well calibrated (P _{Hosmer-Lemeshow test} = 0.897).

CONCLUSION

The Model included pre-pregnancy BMI, weight gain at 24 gw, parity, OGTT 2 h glucose at 24 gw, HDL and LDL at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw had good prediction performance for predicting macrosomia in women with GDM.

Prediction model for gestational diabetes mellitus using the XG Boost machine learning algorithm

OBJECTIVE

To develop the extreme gradient boosting (XG Boost) machine learning (ML) model for predicting gestational diabetes mellitus (GDM) compared with a model using the traditional logistic regression (LR) method.

METHODS

A case-control study was carried out among pregnant women, who were assigned to either the training set (these women were recruited from August 2019 to November 2019) or the testing set (these women were recruited in August 2020). We applied the XG Boost ML model approach to identify the best set of predictors out of a set of 33 variables. The performance of the prediction model was determined by using the area under the receiver operating characteristic (ROC) curve (AUC) to assess discrimination, and the Hosmer-Lemeshow (HL) test and calibration plots to assess calibration. Decision curve analysis (DCA) was introduced to evaluate the clinical use of each of the models.

RESULTS

A total of 735 and 190 pregnant women were included in the training and testing sets, respectively. The XG Boost ML model, which included 20 predictors, resulted in an AUC of 0.946 and yielded a predictive accuracy of 0.875, whereas the model using a traditional LR included four predictors and presented an AUC of 0.752 and yielded a predictive accuracy of 0.786. The HL test and calibration plots show that the two models have good calibration. DCA indicated that treating only those women whom the XG Boost ML model predicts are at risk of GDM confers a net benefit compared with treating all women or treating none.

CONCLUSIONS

The established model using XG Boost ML showed better predictive ability than the traditional LR model in terms of discrimination. The calibration performance of both models was good.

Metabolic Characteristics of Gestational Diabetes Mellitus and the Effects on Pregnancy Outcomes

OBJECTIVE

To describe the metabolic characteristics of gestational diabetes mellitus (GDM) and assess their effects on perinatal outcomes.

METHODS

A two-center nested case‒control study was designed, including 192 pregnant women with GDM and 191 pregnant women with normal glucose tolerance (NGT). Serum glucose and insulin concentrations based upon the 75 g oral glucose tolerance test (OGTT) were measured. Several indices were calculated to describe the metabolic characteristics of the subjects. The relationship between glucose metabolism parameters and pregnancy outcomes was evaluated using stepwise linear regression and binary logistic regression.

RESULTS

Compared with the NGT group, the GDM group showed significantly higher fasting and postprandial glucose parameters but significantly lower fasting and postprandial insulin responses. Meanwhile, the GDM group had significantly lower HOMA-β, DI and ISI_Matsuda but comparable HOMA-IR. The IFG subgroup showed significantly lower FINS/FPG only, while the IGT and IFSG subgroups showed deficiency in both fasting and postprandial insulin response. The IFSG subgroup had the highest glucose parameters and the lowest insulin parameters, as well as significantly lower ISI_Matsuda and HOMA-β than the NGT group. FPG had a significant effect on infants' birth weight, and 1hPG and FINS/FPG had a significant effect on delivery gestational age. AUC-INS, IGI₆₀ and DI were related to premature delivery risk after adjusting for confounders. The IFG subgroup of GDM was 2.319 times more likely to be subject to cesarean section than the NGT group. FPG, FINS/FPG, AUC-GLU, AUC-INS/AUC-GLU and HOMA-β were related to macrosomia risk.

CONCLUSION

Beta cell dysfunction rather than insulin resistance determines the occurrence of GDM in the central Chinese population. Women with predominant insulin secretion defects had a similar risk of adverse perinatal outcomes to women with NGT. Our study provided a basis for the selection of glucose metabolism monitoring indicators useful for the prevention of adverse perinatal outcomes.

Dietary Plant Protein Intake Can Reduce Maternal Insulin Resistance during Pregnancy

Evidence suggests that the source of dietary protein may have an impact on insulin resistance, but no studies have explored it in pregnant populations. In this study, we combined a population study and an animal experiment to explore this effect. The population study was conducted with data from NHANES. Multiple linear regression was used to observe the association of protein intake with outcomes, including fasting glucose (GLU), insulin (INS), and HOMA-IR. In the animal experiment, 36 pregnant SD rats in three groups were orally administered 100% animal protein, 50% animal protein and 50% plant protein, or 100% plant protein, respectively. The intervention continued throughout the whole pregnancy. On day 19.5, maternal plasma was collected after overnight fasting, and metabolomics was performed using UPLC-MS. We found plant protein intake was negatively correlated with INS and HOMA-IR in the whole population. During the third trimester, a similar correlation was also observed. The animal experiment also presented the same result. In metabolomic analysis, changes in various metabolites and related pathways including FoxO and mTOR signaling pathways were observed. In conclusion, we found a negative association between dietary plant protein intake and maternal insulin resistance during pregnancy. Changes in some active substances and related metabolic pathways may play an important role.

Insulin sensitivity, β cell function, and adverse pregnancy outcomes in women with gestational diabetes

BACKGROUND

The potential impact of β cell function and insulin sensitivity on adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM) remains uncertain. We aimed to investigate the association between β cell dysfunction, insulin resistance, and the composite adverse pregnancy outcomes.

METHODS

This observational study included 482 women diagnosed with GDM during pregnancy. Quantitative metrics on β cell function and insulin sensitivity during pregnancy were calculated using traditional equations. The association of β cell dysfunction and insulin resistance with the risk of the composite adverse pregnancy outcomes was investigated using multivariable-adjusted logistic regression models.

RESULTS

Multivariable-adjusted odds ratios (ORs) of adverse pregnancy outcomes across quartiles of homeostatic model assessment for insulin resistance (HOMA-IR) were 1.00, 0.95, 1.34, and 2.25, respectively (P for trend = 0.011). When HOMA-IR was considered as a continuous variable, the multivariable-adjusted OR of adverse pregnancy outcomes was 1.34 (95% confidence interval 1.16-1.56) for each 1-unit increase in HOMA-IR. Multivariable-adjusted ORs of adverse pregnancy outcomes across quartiles of homeostatic model assessment for β cell function (HOMA-β) were 1.00, 0.51, 0.60, and 0.53, respectively (P for trend = 0.068). When HOMA-β was considered as a continuous variable, the multivariable-adjusted OR of adverse pregnancy outcomes was 0.57 (95% CI 0.24-0.90) for each 1-unit increase in HOMA-β. However, other quantitative metrics were not associated with the composite adverse pregnancy outcomes.

CONCLUSIONS

We demonstrated a significant association of β cell function and insulin sensitivity with the risk of adverse pregnancy outcomes. We have provided additional evidence on the early identification of adverse pregnancy outcomes besides the glycemic values.

Immune–Metabolic Interactions and T Cell Tolerance in Pregnancy

Pregnancy depends on a state of maternal immune tolerance mediated by CD4+ regulatory T (Treg) cells. Uterine Treg cells release anti-inflammatory factors, inhibit effector immunity, and support adaptation of the uterine vasculature to facilitate placental development. Insufficient Treg cells or inadequate functional competence is implicated in infertility and recurrent miscarriage, as well as pregnancy complications preeclampsia, fetal growth restriction, and preterm birth, which stem from placental insufficiency. In this review we address an emerging area of interest in pregnancy immunology–the significance of metabolic status in regulating the Treg cell expansion required for maternal–fetal tolerance. We describe how hyperglycemia and insulin resistance affect T cell responses to suppress generation of Treg cells, summarize data that implicate a role for altered glucose metabolism in impaired maternal–fetal tolerance, and explore the prospect of targeting dysregulated metabolism to rebalance the adaptive immune response in women experiencing reproductive disorders.

Ramachandrayya, Suchetha Kumari N., Shilpa S. Shetty, D' Cunha P. Serum betatrophin levels and fatty acid profile in gestational diabetes mellitus: Correlation with insulin resistance

Introduction and Aim: Gestational diabetes mellitus (GDM) involves insulin resistance, altered levels of adipocytokines and inflammation. Interaction of various molecules in the pathogenesis of obesity and insulin resistance plays a major role in GDM. Angiopoietin-like protein 8, also named betatrophin is a hormone which is synthesized from liver and adipocytes. This molecule has beta cell-regenerating effect and is proposed to have therapeutic potential in obesity, insulin resistance and diabetes mellitus. The present study aimed to evaluate the role of betatrophin and free fatty acids (FFA) as markers of gestational diabetes mellitus (GDM). Materials and Methods: This study was conducted in Medical College Hospital on pregnant women with the normal body mass index. The study subjects were divided into 2 groups -one with healthy pregnant women and the other GDM and recruited for the study at 24 to 28 weeks of gestation. The levels of betatrophin, insulin and FFA were estimated in the serum and HOMA-IR was calculated. Results: Insulin resistance (IR), serum betatrophin level and plasma omega-6 fatty acid levels were higher, and plasma omega-3 fatty acid levels were lower among GDM subjects in comparison to healthy pregnant women.  Fasting plasma glucose, serum betatrophin level and dihomo gamma linolenic acid level showed significant positive correlation with IR while omega 3 fatty acid %, levels of alpha linolenic acid, gamma linolenic acid and lauric acid showed negative correlation with IR in GDM women.  Conclusion: Altered fatty acid profile in gestational diabetes mellitus indicated potential application of fatty acids as biomarkers of metabolic derangements which arise due to insulin resistance. The findings have diagnostic, prognostic, and therapeutic implications.

Study of serum miR-518 and its correlation with inflammatory factors in patients with gestational diabetes mellitus complicated with hypertensive disorder complicating pregnancy

OBJECTIVE

Gestational diabetes mellitus (GDM) and hypertensive disorder complicating pregnancy (HDCP) are common complications during pregnancy. This study estimated the correlation of serum miR-518 and inflammatory factors in GDM complicated with HDCP patients (GDM&HDCP).

METHODS

Total 240 pregnant women were enrolled, including 118 cases with GDM alone, 57 cases with GDM&HDCP, and 65 healthy pregnant women. The expressions of serum miR-518 and PPARα were detected by RT-qPCR. The clinical diagnostic efficacy of miR-518 for GDM and GDM&HDCP was analyzed via ROC curve. Pearson coefficient was used to analyze the correlation between miR-518 and serum inflammatory factors (hs-CRP, IL-6, and TNF-α), and the relevance between peroxisome proliferator-activated receptor α (PPARα) and serum inflammatory factors. The targeted binding of miR-518 and PPARα was verified using dual-luciferase assay.

RESULTS

Serum miR-518 was highly-expressed in GDM and GDM&HDCP patients, but far higher in GDM&HDCP patients. Serum miR-518 level > 1.815 could assist the diagnosis of GDM (81.53% sensitivity and 100% specificity). Serum miR-518 expression was positively-correlated with serum inflammatory factors. miR-518 targeted PPARα and PPARα was lowly-expressed in the serum of GDM and GDM&HDCP patients. PPARα was negatively-linked with serum inflammatory factors.

CONCLUSION

High expression of miR-518 assists the diagnosis of GDM and GDM&HDCP, and miR-518 regulates the serum inflammatory factors by inhibiting PPARα.

First-Trimester Triglyceride-Glucose Index and Risk of Pregnancy-Related Complications: A Prospective Birth Cohort Study in Southeast China

PURPOSE

To evaluate the relationships of the triglyceride-glucose (TyG) index with pregnancy-related complications (PRCs) and to clarify the predictability of the TyG index for PRCs.

PATIENTS AND METHODS

Totally of 11,387 women with a singleton pregnancy were prospectively followed until after delivery. Maternal fasting lipids and glucose concentration were measured in the first trimester (11 weeks gestation on average). The TyG index was calculated as ln [triglyceride (mg/dL) × fasting plasma glucose (mg/dL)/2]. We used generalized linear models to calculate the relative risks and 95% confidence intervals. Receiver-operating characteristic curve analysis was employed to assess the ability of the TyG index to predict the risks of PRCs.

RESULTS

Smooth spline reveals that the probability of gestational diabetes mellitus (GDM) is intensified with the increasing TyG index. Multivariate logistic regression adjusted for risk factors demonstrates a 1-unit and a 1-SD increment in the TyG index raises the risk of GDM by 3.63 and 1.57 times, respectively. Identically, the risk of GDM maximizes in the TyG quintile 5 (OR: 3.14; 95% CI: 2.55~3.85) relative to the lowest TyG index group. However, no association between TyG index and the risk of other PRCs was observed after full adjustment. The area under receiver operating characteristic curves is 0.647 (95% CI: 0.632-0.66) for GDM, and the optimal predictive cut-off is 8.55, with a specificity of 0.679 and sensitivity of 0.535.

CONCLUSION

The first-trimester TyG index is significantly associated with the risk of incident GDM, while the relationships between the TyG index and other PRCs need further exploration.

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.

Secular increase in the prevalence of gestational diabetes and its associated adverse pregnancy outcomes from 2014 to 2021 in Hebei province, China

OBJECTIVE

We aimed to investigate the secular prevalence of gestational diabetes mellitus (GDM) and evaluate its adverse pregnancy outcomes among pregnant women in Hebei province, China.

METHODS

We analyzed the data from the monitoring information management system for pregnant women in 22 hospitals of Hebei province, China. In this study, 366,212 individuals with singleton live births from 2014 to 2021 were included, of whom 25,995 were diagnosed with gestational diabetes. We described the incidence of common complications and further analyzed the clinical characteristics in GDM patients and the relationship between GDM and adverse pregnancy outcomes.

RESULTS

The top 3 pregnancy complications in Hebei province are anemia, gestational hypertension, and GDM. The average incidence of GDM was 7.10% (25,995/366,212). The incidence rate of GDM significantly increased from 2014 to 2021 (χ² _trend = 7,140.663, P < 0.001). The top 3 regions with GDM incidence were Baoding (16.60%), Shijiazhuang (8.00%), and Tangshan (3.80%). The incidence of GDM in urban pregnant women (10.6%) is higher than that in rural areas (3.7%).The difference between the GDM and Non-GDM groups was statistically significant in terms of maternal age, gravidity, parity, education level, and incidence of pregnancy complications (gestational hypertension, heart diseases, and anemia) (P < 0.05). GDM individuals were at significantly increased risk of most assessed adverse pregnancy outcomes, including premature delivery, Cesarean delivery, uterine inertia, neonatal intensive care unit (NICU) admission, Apgar (activity-pulse-grimace-appearance-respiration) score at 1 min, and macrosomia (P < 0.05). The multivariate logistic regression analysis showed that GDM was an independent risk factor in terms of premature birth, Cesarean delivery, uterine inertia, placental abruption, NICU admission, and macrosomia.

CONCLUSION

The risk of adverse pregnancy outcome in pregnant women with GDM is significantly increased. In order to reduce the occurrence of adverse pregnancy outcomes, effective interventions are needed.

Silent upsurge of gestational diabetes: Are we aware? A rural tertiary care experience of Central Gujarat

Background:

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