Objectives: To assess whether recurrent gestational diabetes mellitus (GDM) and newly diagnosed GDM share similar risk factors. Methods: The study recruited a cohort of 10,151 multipara women with singleton pregnancy who delivered between 2016 and 2019 in Beijing, China. The prevalence of recurrent GDM and associated risk factors were analyzed between women with and without prior GDM history. Results: Eight hundred and seventy-five (8.6%) multipara women had a diagnosis of GDM during previous pregnancies. The prevalence of GDM and pre-gestational diabetes mellitus were 48.34% (423/875) and 7.89% (69/875) if the women were diagnosed with GDM during previous pregnancies, as compared to 16.00% (1484/9276) and 0.50% (46/9276) if the women were never diagnosed with GDM before. In women without a history of GDM, a variety of factors including older maternal age, higher pre-pregnancy body mass index (PPBMI), prolonged interval between the two pregnancies, higher early pregnancy weight gain, family history of type 2 diabetes mellitus (T2DM), maternal low birth weight, and higher early pregnancy glycemic and lipid indexes were generally associated with an increased risk of GDM at subsequent pregnancy. In women with a history of GDM, higher PPBMI, higher fasting glucose level and maternal birthweight ≥4000 g were independent risk factors for recurrent GDM. Conclusions: GDM reoccurred in nearly half of women with a history of GDM. Risk factors for recurrent GDM and newly diagnosed GDM were different. Identifying additional factors for GDM recurrence can help guide clinical management for future pregnancies to prevent GDM recurrence.

Background Insulin resistance (IR) is a significant factor in gestational diabetes mellitus (GDM) development. The triglyceride-glucose (TyG) index, triglyceride-glucose body mass index (TyG-BMI), atherogenic index of plasma (AIP), and metabolic score for insulin resistance (METS-IR) are simple and reliable surrogates for assessing IR, but their predictive potential for GDM remains unexplored. Methods Data from 46,992 singleton pregnancies delivered at Beijing Obstetrics and Gynecology Hospital between 2018 and 2022 were prospectively collected. IR indices were calculated using first-trimester blood lipid and glucose measurements. Participants were classified into GDM and non-GDM groups based on oral glucose tolerance test (OGTT) results at 24–28 weeks. Logistic regression and restricted cubic spline analyses assessed the associations between IR indices and GDM, with subgroup analyses to assess results robustness. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the predictive performance of the IR indices for GDM. Results Among the participants, 6,045 were diagnosed with GDM and 40,947 were not. Binary logistic regression showed a significant positive association between first-trimester IR indices and GDM (p < 0.001). AUCs for GDM prediction were 0.646 for TyG, 0.651 for TyG-BMI, 0.629 for AIP, and 0.641 for METS-IR. A basic model with maternal demographics achieved an AUC of 0.666. Adding TyG-BMI improved the AUC to 0.693. Conclusions All four surrogate IR indices measured in the first trimester were positively associated with GDM, with TyG-BMI emerging as the strongest predictor.

OBJECTIVE: To determine the association between maternal blood glucose patterns throughout pregnancy and neonatal amino acids and acylcarnitines. RESEARCH DESIGN AND METHODS: We conducted a prospective cohort study involving 11,457 singleton pregnant women without preexisting diabetes from the Beijing Birth Cohort Study, along with their neonates born between July 2021 and October 2022 in Beijing, China. Distinct maternal glucose trajectories were identified using a latent class model based on blood glucose levels across the three trimesters, and their association with neonatal circulating metabolites, including 11 amino acids and 33 acylcarnitines, was examined, adjusting for potential confounding factors. RESULTS: Three distinct groups of maternal glucose trajectories were identified: consistent normoglycemia (n = 8,648), mid-to-late gestational hyperglycemia (n = 2,540), and early-onset hyperglycemia (n = 269). Mid-to-late gestational hyperglycemia was associated with decreased levels of amino acids (alanine, arginine, ornithine, and proline) involved in the arginine and proline metabolism and urea cycle pathway, as well as increased levels of C4DC+C5-OH and decreased level of C6DC and C10:1. Early-onset hyperglycemia was associated with elevated levels of free acylcarnitine and C4DC+C5-OH and a decreased level of C10:1, involved in the fatty acid oxidation pathway. However, these associations were primarily observed in male neonates rather than in female neonates. CONCLUSIONS: Our findings revealed a significant link between maternal glucose trajectories throughout pregnancy and neonatal arginine and proline metabolism, urea cycle pathway, and fatty acid oxidation pathway. These results highlight the importance of maintaining optimal blood glucose levels throughout pregnancy to promote healthy neonatal metabolic outcomes.

Objective: Branched-chain amino acids (BCAAs) are closely associated with type 2 diabetes mellitus, but their roles in gestational diabetes mellitus (GDM) are still controversial. This study aims to explore the dynamic changes of BCAAs during pregnancy and identify potential early biomarkers for GDM.Methods: This study is a nested case-control study involved 49 women with GDM and 50 age- and body mass index (BMI)-matched healthy pregnant women. The dynamic changes of valine (Val), isoleucine (Ile), and leucine (Leu) were detected in the first (8-12 weeks) and second trimesters (24-28 weeks) by liquid chromatography-mass spectrometry.Results: Serum Val, Ile, and Leu were higher in GDM patients than in controls in the first trimester. Compared with the first trimester, the serum Val, Ile, and Leu in GDM patients were decreased in the second trimester. In addition, Val, Ile, and Leu in the first trimester were the risk factors for GDM, and Ile presented a high predictive value for GDM. Ile + age (≥ 35) + BMI (≥ 24) exhibited the highest predictive value for GDM (AUC = 0.902, sensitivity = 93.9%, specificity = 80%).Conclusion: Maternal serum Ile in the first trimester was a valuable biomarker for GDM. Ile combined with advanced maternal age and overweight may be used for the early prediction of GDM.

Objective: To establish suggested gestational weight gain (GWG) using several distinct methods in a Chinese population. Methods: This study analyzed data from the medical records of singleton pregnancy women during 2011–2017 in Beijing, China. Suggested GWG was calculated using four distinct methods. In method 1, suggested GWG was identified by the interquartile method. Subsequently, risk models for small for gestational age (SGA) and large for gestational age (LGA) with respect to GWG were constructed. GWG was treated as a continuous variable in method 2, and as a categorized variable in methods 3 and 4. Results: An average GWG of 15.78 kg with a prevalence of LGA at 19.34% and SGA at 2.12% was observed among the 34,470 participants. Methods 1 and 2 did not yield clinically applicable results. The suggested GWGs were 11–17/11–16 kg, 9–19/9–15 kg, 4–12/4–10 kg, and 0–12/0–6 kg by method 3/method 4 for underweight, normal-weight, overweight, and obese women, respectively. The GWG range suggested by method 3 resulted in a larger proportion of participants (62.03%) within range, while the suggested GWG range by method 4 was associated with a lower risk of LGA compared to that conferred by the Institute of Medicine (IOM) criteria. Conclusion: This study suggests a modest GWG goal compared to IOM recommendations based on a large Chinese cohort.