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Exercise improves metabolic function and alters the microbiome in rats with gestational diabetes.


  • 影响因子:4.32
  • DOI:10.1096/fj.201901424R
  • 作者列表:"Mahizir D","Briffa JF","Wood JL","Anevska K","Hill-Yardin EL","Jefferies AJ","Gravina S","Mazzarino G","Franks AE","Moritz KM","Wadley GD","Wlodek ME
  • 发表时间:2020-01-01

:Gestational diabetes mellitus (GDM) is a common pregnancy complication, particularly prevalent in obese women. Importantly, exercise has beneficial impacts on maternal glucose control and may prevent GDM in "at-risk" women. We aimed to determine whether a high-fat diet (HFD) exacerbates metabolic dysfunction and alters gut microbiome in GDM and whether endurance exercise prevents these changes. Uteroplacental insufficiency was induced by bilateral uterine vessel ligation (Restricted) or sham (Control) surgery on E18 in Wistar-Kyoto rats. Female offspring were fed a Chow or HFD (23% fat) from weaning (5 weeks) and at 16 weeks randomly allocated to remain Sedentary or to an exercise protocol of either Exercise prior to and during pregnancy (Exercise); or Exercise during pregnancy only (PregEx). Females were mated (20 weeks) and underwent indirect calorimetry (embryonic day 16; E16), glucose tolerance testing (E18), followed by 24-hr feces collection at E19 (n = 8-10/group). HFD consumption in female rats with GDM exacerbated the adverse metabolic adaptations to pregnancy and altered gut microbial populations. Specifically, the Firmicutes-to-Bacteroidetes ratio was increased, due to an underlying change in abundance of the orders Clostridiales and Bacteroidales. Maternal Exercise, but not PregEx, prevented the development of metabolic dysfunction, increased pancreatic β-cell mass, and prevented the alteration of the gut microbiome in GDM females. Our findings suggest that maternal exercise and diet influence metabolic and microbiome dysfunction in females with GDM, which may impact long-term maternal and offspring health.


: 妊娠期糖尿病 (GDM) 是一种常见的妊娠并发症,尤其常见于肥胖妇女。重要的是,运动对母体血糖控制有有益的影响,并可能预防 “高危” 妇女的 GDM。我们旨在确定高脂饮食 (HFD) 是否会加剧 GDM 的代谢功能障碍和改变肠道菌群,以及耐力运动是否会阻止这些变化。在 Wistar-Kyoto 大鼠 E18 上通过双侧子宫血管结扎 (限制性) 或假 (对照) 手术诱导子宫胎盘功能不全。雌性后代从断奶 (5 周) 开始喂食饲料或 HFD (23% 脂肪) 在 16 周时,随机分配保持久坐或在怀孕前和怀孕期间进行运动 (运动); 或仅在怀孕期间进行运动 (PregEx)。雌性交配 (20 周),进行间接测热法 (胚胎第 16 天; E16),葡萄糖耐量试验 (E18), 随后在 E19 收集 24 小时粪便 (n = 8-10/组)。GDM 雌性大鼠的 HFD 消耗加剧了对妊娠的不良代谢适应,改变了肠道微生物种群。具体而言,由于梭状芽胞杆菌和拟杆菌丰度的潜在变化,Firmicutes-to-bacterioidetes 比率增加。母体运动,而不是 PregEx,防止了 GDM 女性代谢功能障碍的发展,增加了胰腺 β 细胞量,并防止了肠道微生物组的改变。我们的研究结果表明,母体运动和饮食影响 GDM 女性的代谢和微生物组功能障碍,这可能会影响母体和后代的长期健康。



来源期刊:Acta Diabetologica
作者列表:["Benhalima, Katrien","Crombrugge, Paul","Moyson, Carolien","Verhaeghe, Johan","Vandeginste, Sofie","Verlaenen, Hilde","Vercammen, Chris","Maes, Toon","Dufraimont, Els","Block, Christophe","Jacquemyn, Yves","Mekahli, Farah","Clippel, Katrien","Den Bruel, Annick","Loccufier, Anne","Laenen, Annouschka","Minschart, Caro","Devlieger, Roland","Mathieu, Chantal"]

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.

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来源期刊:Nature Medicine
作者列表:["Artzi, Nitzan Shalom","Shilo, Smadar","Hadar, Eran","Rossman, Hagai","Barbash-Hazan, Shiri","Ben-Haroush, Avi","Balicer, Ran D.","Feldman, Becca","Wiznitzer, Arnon","Segal, Eran"]

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.

关键词: 暂无
翻译标题与摘要 下载文献
作者列表:["Lowes DJ","Hevener KE","Peters BM"]

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.