Lin Lin

Background: Gestational diabetes mellitus (GDM) is a complex metabolic disease that has short-term and long-term adverse effects on mothers and infants. However, the specific pathogenic mechanism has not been elucidated.Objective: The aim of this study was to confirm the associations between candidate genetic variants (rs4134819, rs720918, rs2034410, rs11109509, and rs12524768) and GDM risk and prediction in a southern Chinese population.Methods: Candidate variants were genotyped in 538 GDM cases and 626 healthy controls. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were calculated to assess the associations between genotypes and GDM risk. Then, the false-positive report probability (FPRP) analysis was adopted to confirm the significant associations, and bioinformatics tools were used to explore the potential biological function of studied variants. Finally, risk factors of genetic variants and clinical indicators identified by logistics regression were used to construct a nomogram model for GDM prediction.Results: It was shown that the XAB2 gene rs4134819 was significantly associated with GDM susceptibility (CT vs. CC: adjusted OR = 1.38, 95% CI: 1.01–1.87, p = 0.044; CT/TT vs. CC: crude OR = 1.42, 95% CI: 1.08–1.86, p = 0.013). Functional analysis suggested that rs4134819 can alter the specific transcription factors (CPE bind and GATE-1) binding to the promoter of the XAB2 gene, regulating the transcription of XAB2. The nomogram established with factors such as age, FPG, HbA1c, 1hPG, 2hPG, TG, and rs4134819 showed a good discriminated and calibrated ability with an area under the curve (AUC) = 0.931 and a Hosmer–Lemeshow test p-value > 0.05.Conclusion: The variant rs4134819 can significantly alter the susceptibility of the Chinese population to GDM possibly by regulating the transcription of functional genes. The nomogram prediction model constructed with genetic variants and clinical factors can help distinguish high-risk GDM individuals.

Background & Objective: The specific influence of the pre-pregnancy body mass index (PPBMI) on women with gestational diabetes mellitus (GDM) is unclear. Our objective was to investigate how PPBMI categories affect pregnancy and neonatal outcomes in women with GDM. Methods: A retrospective cohort study was conducted using data from patients attending the Fujian Maternity and Child Health Hospital (Fuzhou, China) from 2021 to 2023. The participant records were stratified into four groups according to their BMI values: underweight, normal-weight, overweight, and obese. The pregnancy and neonatal outcomes for these BMI categories were analyzed using multivariable logistic regression. Results: The study included data from 2,909 pregnant women diagnosed with GDM. Underweight women with GDM showed significantly lower risks of pregnancy-induced hypertension (PIH) (adjusted OR, 0.26) and cesarean sections (adjusted OR, 0.55) but higher risks of low body weight (LBW) infants (adjusted OR, 3.40). Overweight and obese women experienced higher risks of PIH (adjusted OR, 2.96), cesarean sections (adjusted OR, 1.62), and macrosomia (adjusted OR, 1.43). Conclusion: PPBMIs significantly impact pregnancy outcomes in women with GDM. Both underweight and overweight/obese categories are associated with adverse outcomes, highlighting the need for pre-pregnancy counseling and interventions to achieve and maintain a healthy BMI. doi: https://doi.org/10.12669/pjms.41.1.10920 How to cite this: Zheng L, Liao Q, Liu J, Shi J, Chen Z, Lin L. Association between Pre-pregnancy BMI and Pregnancy Outcomes in Women with Gestational Diabetes: A Retrospective Cohort Study. Pak J Med Sci. 2025;41(1):37-43. doi: https://doi.org/10.12669/pjms.41.1.10920 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Objective: This study examined the potential link between maternal pre-pregnancy body mass index (PPBMI) with neonatal outcomes in twin pregnancies. Methods: This retrospective analysis records of 1,270 women with twin pregnancies, delivered at the Fujian Maternity and Child Health Hospital between 2019 and 2021, were retrospectively analysed. Women were diagnosed as underweight, normal BMI, and overweight/obese according to their PPBMI. Neonatal outcomes included low birth weight (LBW), intrauterine growth retardation (IUGR), prematurity, neonatal intensive care unit (NICU) admission, neonatal mortality, and low APGAR scores. Univariate and multivariable regression analyses were performed. Results: The proportions of neonates with LBW, IUGR, prematurity, and NICU admission were 34.7%, 2.5%, 27%, and 30%, respectively. Five neonatal deaths occurred, all born to mothers with normal BMI. Low APGAR scores at five minutes were observed in one neonate in the maternal overweight/obese group and one neonate in the normal maternal BMI group. Multivariate regression analysis showed that underweight women had an approximately twice higher risk of delivering LBW twins (OR 1.88, 95% CI: 1.26, 2.89) than women with normal BMI. No statistically significant associations were found between maternal BMI and other neonatal outcomes. Conclusion: Low PPBMI increases the risk of delivering LBW twins, independent of other factors. Our findings emphasize the importance of pre-pregnancy nutritional status in optimizing neonatal outcomes in twin deliveries. doi: https://doi.org/10.12669/pjms.41.1.11135 How to cite this: Zheng L, Huang L, Liu J, Yao T, Liao Q, Lin L. Impact of pre-pregnancy maternal body mass index on neonatal outcomes in twin delivery: A retrospective cohort study. Pak J Med Sci. 2025;41(1):49-54. doi: https://doi.org/10.12669/pjms.41.1.11135 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The growing prevalence of assisted reproductive technology (ART) is leading to a continuous rise in twin pregnancies. This study assessed the influence of ART on neonatal outcomes of twin pregnancies. Clinical records of twin deliveries at Fujian Maternity and Child Health Hospital between 2019 and 2021 were retrospectively selected and grouped based on the method of conception: ART-conceived and naturally conceived. Neonatal outcomes of interest included low birth weight (LBW), intrauterine growth restriction (IUGR), prematurity, low Appearance, Pulse, Grimace, Activity and Respiration scores, and neonatal intensive care unit admission. Univariate and multivariable logistic regression analyses were conducted to adjust for potential confounders. The results were expressed as odds ratio (OR) with 95% confidence interval (CI). A total of 1270 pairs of twins were included in the analysis. ART-conceived twins had significantly lower odds of being born with LBW (adjusted OR 0.57, 95% CI: 0.43, 0.75), prematurity (adjusted OR 0.71, 95% CI: 0.55, 0.91), and IUGR (adjusted OR 0.21, 95% CI: 0.10, 0.39) compared to naturally conceived twins. Rates of other outcomes were comparable in both groups. Twins born through ART had reduced odds of LBW, prematurity, and IUGR, with no impact on other neonatal outcomes. These findings suggest that ART may have a protective effect on twin fetal growth, although the risks associated with multiple gestations remain. Further studies should explore the mechanisms and long-term effects of these outcomes.