Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus.

BACKGROUND: The birth of large-for-gestational-age (LGA) infants is associated with many short-term adverse pregnancy outcomes. It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus (GDM) is significantly higher than that born to healthy pregnant women. However, traditional methods for the diagnosis of LGA have limitations. Therefore, this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants. AIM: To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM, and provide strategies for the effective prevention and timely intervention of LGA. METHODS: The multivariable prediction model was developed by carrying out the following steps. First, the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses, for which the P value was < 0.10. Subsequently, Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations, and the optimal combination factors were selected by choosing lambda 1se as the criterion. The final predictors were determined by multiple backward stepwise logistic regression analysis, in which only the independent variables were associated with LGA risk, with a P value < 0.05. Finally, a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve, calibration curve and decision curve analyses. RESULTS: After using a multistep screening method, we establish a predictive model. Several risk factors for delivering an LGA infant were identified (P < 0.01), including weight gain during pregnancy, parity, triglyceride-glucose index, free tetraiodothyronine level, abdominal circumference, alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks. The nomogram's prediction ability was supported by the area under the curve (0.703, 0.709, and 0.699 for the training cohort, validation cohort, and test cohort, respectively). The calibration curves of the three cohorts displayed good agreement. The decision curve showed that the use of the 10%-60% threshold for identifying pregnant women with GDM who are at risk of delivering an LGA infant would result in a positive net benefit. CONCLUSION: Our nomogram incorporated easily accessible risk factors, facilitating individualized prediction of pregnant women with GDM who are likely to deliver an LGA infant.

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

PURPOSE: The aim of this study was to evaluate the relationship among inflammatory cytokines including hypersensitive C-reactive protein (hs-CRP) and interleukin-6 (IL-6), glycated hemoglobin A1c (HbA1c), and platelet distribution width (PDW) in women with gestational diabetes mellitus (GDM). METHODS: Data on 191 pregnant women (96 women with GDM; 95 healthy controls) were extracted from routine prenatal examination records in Nanjing, China. Fasting concentrations of hs-CRP, IL-6, HbA1c, blood cell indices, and glucose at 24-28th gestational weeks were determined. RESULTS: The levels of hs-CRP, IL-6, FPG, PG1h, PG2h, HbA1c, RBC, and PDW significantly were increased (P < 0.05) in GDM group. hs-CRP had a positive correlation with HbA1c and PLT (P < 0.05). The odds ratios of HbA1c and PDW were 7.817 (95% CI 1.921-31.816, P = 0.004) and 1.523 (95% CI 1.158-2.002, P = 0.003), respectively. Furthermore, AUC of the combined diagnosis of GDM including HbA1c, FPG, and PDW reached 0.754, with specificity of 80.0% and sensitivity of 60.4%. CONCLUSION: Our findings support that elevated levels of hs-CRP, IL-6, HbA1c, and PDW at 24-28th gestational weeks even within the conventional normal range, may be implicated in the pathogenesis of GDM and their evaluation should be part of prenatal care routine.

Current progress in metabolomics of gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders of pregnancy and can cause short- and long-term adverse effects in both pregnant women and their offspring. However, the etiology and pathogenesis of GDM are still unclear. As a metabolic disease, GDM is well suited to metabolomics study, which can monitor the changes in small molecular metabolites induced by maternal stimuli or perturbations in real time. The application of metabolomics in GDM can be used to discover diagnostic biomarkers, evaluate the prognosis of the disease, guide the application of diet or drugs, evaluate the curative effect, and explore the mechanism. This review provides comprehensive documentation of metabolomics research methods and techniques as well as the current progress in GDM research. We anticipate that the review will contribute to identifying gaps in the current knowledge or metabolomics technology, provide evidence-based information, and inform future research directions in GDM.

Persistently Upregulated Hippocampal mTOR Signals Mediated by Fecal SCFAs Impair Memory in Male Pups with SMM Exposure in Utero.

OBJECTIVE: To investigate the molecular mechanisms of the adverse effects of exposure to sulfamonomethoxin (SMM) in pregnancy on the neurobehavioral development of male offspring. METHODS: Pregnant mice were randomly divided into four groups: control- (normal saline), low- [10 mg/(kg•day)], middle- [50 mg/(kg•day)], and high-dose [200 mg/(kg•day)] groups, which received SMM by gavage daily during gestational days 1-18. We measured the levels of short-chain fatty acids (SCFAs) in feces from dams and male pups. Furthermore, we analyzed the mRNA and protein levels of genes involved in the mammalian target of rapamycin (mTOR) pathway in the hippocampus of male pups by RT-PCR or Western blotting. RESULTS: Fecal SCFA concentrations were significantly decreased in dams. Moreover, the production of individual fecal SCFAs was unbalanced, with a tendency for an increased level of total fecal SCFAs in male pups on postnatal day (PND) 22 and 56. Furthermore, the phosphatidylinositol 3-kinase (PI3k)/protein kinase B (AKT)/mTOR or mTOR/ribosomal protein S6 kinase 1 (S6K1)/4EBP1 signaling pathway was continuously upregulated until PND 56 in male offspring. In addition, the expression of Sepiapterin Reductase (SPR), a potential target of mTOR, was inhibited. CONCLUSION: In utero exposure to SMM, persistent upregulation of the hippocampal mTOR pathway related to dysfunction of the gut (SCFA)-brain axis may contribute to cognitive deficits in male offspring.