Higher dietary vitamin C intake is associated with a lower risk of gestational diabetes mellitus: A longitudinal cohort study.
较高的膳食维生素c 摄入量与较低的妊娠期糖尿病风险相关: 一项纵向队列研究。
- 作者列表："Liu C","Zhong C","Chen R","Zhou X","Wu J","Han J","Li X","Zhang Y","Gao Q","Xiao M","Hu X","Xiong G","Han W","Yang X","Hao L","Yang N
BACKGROUND & AIMS:Oxidative stress has been implicated in the pathogenesis of gestational diabetes mellitus (GDM). Vitamin C as natural antioxidant may help to increase the body's antioxidant capacity. The study is aimed to determine whether vitamin C intake during pregnancy is associated with lower risk of GDM. METHODS:Women with singleton pregnancy and without any history of diabetes were drawn from the ongoing Tongji Maternal and Child Health Cohort (TMCHC). Oral glucose tolerance tests (OGTT) were conducted during weeks 24-28 of gestation to screen for GDM. A validated food frequency questionnaire (FFQ) was used to assess dietary intake during mid pregnancy. Use of multivitamins and specific supplements of vitamin C was assessed by questionnaires. Odds ratios (ORs) of GDM risk were calculated by logistic regression models, adjusted for potential confounders. RESULTS:344 (11.4%) of the 3009 women were diagnosed with GDM. Dietary vitamin C intake was inversely associated with the risk of GDM. Women with above adequate dietary vitamin C intake (more than 200 mg/day) experienced lower odds of GDM (OR 0.68, 95% CI: 0.49-0.95) than those with adequate intake (115-200 mg/day). There was no association between the total consumption of vitamin C and the risk of GDM (OR 1.04, 95% CI: 0.71-1.53). CONCLUSION:This data suggests that higher dietary consumption of vitamin C during pregnancy is independently associated with lower odds of GDM. Above 200 mg/day of dietary vitamin C intake may help reduce the odds of GDM. However, no such association between total vitamin C intake and the risk of GDM was found. Hence, sufficient vegetables and fruits rich in vitamin C should be recommended to protect pregnant women from developing gestational diabetes.
背景与目的: 氧化应激与妊娠期糖尿病 (GDM) 的发病机制有关。维生素c 作为天然抗氧化剂可能有助于提高身体的抗氧化能力。该研究旨在确定孕期摄入维生素c 是否与 GDM 风险降低有关。 方法: 从正在进行的同济妇幼健康队列 (TMCHC) 中抽取单胎妊娠且无任何糖尿病史的妇女。在妊娠 24-28 周进行口服葡萄糖耐量试验 (OGTT)，以筛查 GDM。使用经验证的食物频率问卷 (FFQ) 评估妊娠中期的饮食摄入量。通过问卷调查评估多种维生素的使用和维生素c 的特定补充剂。通过 logistic 回归模型计算 GDM 风险的比值比 (or)，校正潜在混杂因素。 结果: 344 例妇女中 11.4% 例 (3009) 被诊断为 GDM。膳食维生素c 摄入量与 GDM 风险呈负相关。饮食维生素c 摄入量充足 (超过 200 毫克/天) 以上的女性患 GDM 的几率较低 (OR 0.68，95% CI: 0.49-0.95) 比那些有足够的摄入量 (115-200 毫克/天)。维生素c 的总消耗量与 GDM 的风险之间没有关联 (OR 1.04，95% CI: 0.71-1.53)。 结论: 这些数据表明，孕期较高的维生素c 饮食摄入量与 GDM 的发生率较低独立相关。超过 200 毫克/天的膳食维生素c 摄入量可能有助于降低 GDM 的几率。然而，未发现总维生素c 摄入量与 GDM 风险之间存在这种关联。因此，应该推荐足够的富含维生素c 的蔬菜和水果来保护孕妇免受妊娠糖尿病的发生。
METHODS:Aims We aimed to develop a prediction model based on clinical and biochemical variables for gestational diabetes mellitus (GDM) based on the 2013 World Health Organization (WHO) criteria. Methods A total of 1843 women from a Belgian multi-centric prospective cohort study underwent universal screening for GDM. Using multivariable logistic regression analysis, a model to predict GDM was developed based on variables from early pregnancy. The performance of the model was assessed by receiver-operating characteristic (AUC) analysis. To account for over-optimism, an eightfold cross-validation was performed. The accuracy was compared with two validated models (van Leeuwen and Teede). Results A history with a first degree relative with diabetes, a history of smoking before pregnancy, a history of GDM, Asian origin, age, height and BMI were independent predictors for GDM with an AUC of 0.72 [95% confidence interval (CI) 0.69–0.76)]; after cross-validation, the AUC was 0.68 (95% CI 0.64–0.72). Adding biochemical variables, a history of a first degree relative with diabetes, a history of GDM, non-Caucasian origin, age, height, weight, fasting plasma glucose, triglycerides and HbA_1c were independent predictors for GDM, with an AUC of the model of 0.76 (95% CI 0.72–0.79); after cross-validation, the AUC was 0.72 (95% CI 0.66–0.78), compared to an AUC of 0.67 (95% CI 0.63–0.71) using the van Leeuwen model and an AUC of 0.66 (95% CI 0.62–0.70) using the Teede model. Conclusions A model based on easy to use variables in early pregnancy has a moderate accuracy to predict GDM based on the 2013 WHO criteria.
METHODS:Leveraging the availability of nationwide electronic health records from over 500,000 pregnancies in Israel, a machine-learning approach offers an alternative means of predicting gestational diabetes at high accuracy in the early stages of pregnancy. Gestational diabetes mellitus (GDM) poses increased risk of short- and long-term complications for mother and offspring^ 1 – 4 . GDM is typically diagnosed at 24–28 weeks of gestation, but earlier detection is desirable as this may prevent or considerably reduce the risk of adverse pregnancy outcomes^ 5 , 6 . Here we used a machine-learning approach to predict GDM on retrospective data of 588,622 pregnancies in Israel for which comprehensive electronic health records were available. Our models predict GDM with high accuracy even at pregnancy initiation (area under the receiver operating curve (auROC) = 0.85), substantially outperforming a baseline risk score (auROC = 0.68). We validated our results on both a future validation set and a geographical validation set from the most populated city in Israel, Jerusalem, thereby emulating real-world performance. Interrogating our model, we uncovered previously unreported risk factors, including results of previous pregnancy glucose challenge tests. Finally, we devised a simpler model based on just nine questions that a patient could answer, with only a modest reduction in accuracy (auROC = 0.80). Overall, our models may allow early-stage intervention in high-risk women, as well as a cost-effective screening approach that could avoid the need for glucose tolerance tests by identifying low-risk women. Future prospective studies and studies on additional populations are needed to assess the real-world clinical utility of the model.
METHODS::Repurposing of currently approved medications is an attractive option for the development of novel treatment strategies against physiological and infectious diseases. The antidiabetic sulfonylurea glyburide has demonstrated off-target capacity to inhibit activation of the NLRP3 inflammasome in a variety of disease models, including vaginal candidiasis, caused primarily by the fungal pathogen Candida albicans Therefore, we sought to determine which of the currently approved sulfonylurea drugs prevent the release of interleukin 1β (IL-1β), a major inflammasome effector, during C. albicans challenge of the human macrophage-like THP1 cell line. Findings revealed that the second-generation antidiabetics (glyburide, glisoxepide, gliquidone, and glimepiride), which exhibit greater antidiabetic efficacy than prior iterations, demonstrated anti-inflammatory effects with various degrees of potency as determined by calculation of 50% inhibitory concentrations (IC50s). These same compounds were also effective in reducing IL-1β release during noninfectious inflammasome activation (e.g., induced by lipopolysaccharide [LPS] plus ATP), suggesting that their anti-inflammatory activity is not specific to C. albicans challenge. Moreover, treatment with sulfonylurea drugs did not impact C. albicans growth and filamentation or THP1 viability. Finally, the use of ECE1 and Candidalysin deletion mutants, along with isogenic NLRP3-/- cells, demonstrated that both Candidalysin and NLRP3 are required for IL-1β secretion, further confirming that sulfonylureas suppress inflammasome signaling. Moreover, challenge of THP1 cells with synthetic Candidalysin peptide demonstrated that this toxin is sufficient to activate the inflammasome. Treatment with the experimental inflammasome inhibitor MCC950 led to similar blockade of IL-1β release, suggesting that Candidalysin-mediated inflammasome activation can be inhibited independently of potassium efflux. Together, these results demonstrate that the second-generation antidiabetic sulfonylureas retain anti-inflammatory activity and may be considered for repurposing against immunopathological diseases, including vaginal candidiasis.