- 作者列表："Ajjarapu AS","Hinkle SN","Wu J","Li M","Rawal S","Francis EC","Chen L","Pitsava G","Bjerregaard AA","Grunnet LG","Vaag A","Zhu Y","Ma RCW","Damm P","Mills JL","Olsen SF","Zhang C
OBJECTIVE:Nut intake has been associated with reduced cardiometabolic risk, but few studies have examined its association with renal function. We examined associations between nut intake and renal function among women with previous gestational diabetes mellitus (GDM), a population with an increased risk for renal dysfunction. DESIGN AND METHODS:This study included 607 women with a history of GDM who participated in the Diabetes & Women's Health Study (2012-2014) follow-up clinical examination in Denmark. At the clinic, biospecimens were collected, and habitual intake of nuts (9 types) in the past year was assessed using a food frequency questionnaire. A total of 330 women free of major chronic diseases were included in the analysis. Total nut intake was classified as none (≤1 serving/month), monthly (2-3 servings/month), weekly (1-6 servings/week), and daily (≥1 serving/day). One serving was defined as 28 g. Renal function markers included estimated glomerular rate (eGFR) and urinary albumin-to-creatinine ratio (UACR), calculated based on plasma creatinine (mg/dL), and urinary albumin (mg/L), and creatinine (mg/dL) measurements, respectively. We estimated percent differences with 95% confidence intervals for each outcome by nut intake, adjusted for current body mass index, age, physical activity, energy intake, alcohol consumption, and vegetables intake. RESULTS:We observed a nonlinear association between total nut intake and UACR with lowest UACR values among women with weekly intake. Compared to women with weekly intake (n = 222), the adjusted UACR values were higher by 86% [95% confidence interval: 15%, 202%], 24% [-1%, 54%], and 117% [22%, 288%] among women with no (n = 13), monthly (n = 86), and daily (n = 9) intake, respectively. Compared to weekly consumers, daily nut consumers also had 9% [0%, 19%] significantly higher eGFR values, but eGFR values were similar among women with no and monthly intake. CONCLUSION:Moderate nut consumption may be beneficial to kidney health among women with prior GDM.
目的: 坚果摄入与心脏代谢风险降低相关，但很少有研究检查其与肾功能的相关性。我们在既往有妊娠期糖尿病 (GDM) 的女性中检测了坚果摄入与肾功能之间的相关性，GDM 是肾功能不全风险增加的人群。 设计和方法: 本研究包括 607 名有 GDM 病史的女性，她们参加了丹麦糖尿病和妇女健康研究 (2012-2014) 的随访临床检查。在诊所，收集生物样本，并使用食物频率问卷评估过去一年中坚果 (9 种) 的习惯性摄入量。共有 330 名无重大慢性病的妇女纳入分析。坚果总摄入量分类为无 (≤ 1 份/月) 、每月 (2-3 份/月) 、每周 (1-6 份/周) 、和每日 (≥ 1 份/天)。1 份定义为 28g。肾功能标志物包括估计肾小球率 (eGFR) 和尿白蛋白/肌酐比值 (UACR)，根据血浆肌酐 (mg/dL) 计算, 分别测量尿白蛋白 (mg/L) 和肌酐 (mg/dL)。我们通过坚果摄入，校正当前体重指数、年龄、体力活动、能量摄入、饮酒和蔬菜摄入，估计每种结局的 95% 置信区间的百分比差异。 结果: 我们在每周摄入量的女性中观察到总坚果摄入量与 UACR 值最低的 UACR 之间存在非线性关联。与每周摄入的女性 (n = 222) 相比，调整后的 UACR 值高 86% [95% 置信区间: 15%，202%]，24% [-1%，54%], 117% [22%，288%] 在无 (n = 13) 、每月 (n = 86) 和每日的女性中(N = 9) 分别摄入。与每周消费者相比，每日坚果消费者的 eGFR 值也有 9% [0%，19%] 显著升高，但在无和每月摄入量的女性中，eGFR 值相似。 结论: 在既往 GDM 妇女中，适量食用坚果可能有利于肾脏健康。
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.