背景:T2DM异质性影响对生活方式治疗的反应性。β细胞衰竭和非酒精性脂肪性肝病(NAFLD)独立预测T2DM,但NAFLD不一致地预测对生活方式干预的代谢反应。
目的:我们试图通过评估类似的代谢因子来复制从Tübinger生活方式干预计划中扣除的预测模型,以预测在可比的生活方式干预试验中转化为正常的葡萄糖调节(NGR)。
方法:在最佳光纤试验(OptiFiT)中,131名患有糖尿病前期的白种人参与者完成了为期一年的生活方式干预计划,并接受了纤维或安慰剂补充剂。我们比较了应答者和非应答者的基线参数,评估主要代谢变化的相关性,并对NGR缓解的预测因子进行逻辑回归分析。
结果:33名参与者获得了NGR,分别。在基线,仅对于安慰剂组,1小时和2小时的葡萄糖水平,葡萄糖AUC和Cederholm指数预测转化为NGR。HOMA-beta,安慰剂组或纤维组的应答者和非应答者之间的HOMA-IR或肝脏脂肪指数没有差异。腰围或脂肪肝指数的变化与血糖和胰岛素抵抗的变化相关,但不是胰岛素分泌的变化。胰岛素抵抗NAFLD不能预测无应答。依从性的差异并不能解释结果。
结论:在我们的队列中,较高的挑战后葡萄糖水平强烈预测了对复杂生活方式干预的代谢无反应。根据具体的干预措施和调查的队列,空腹血糖水平和胰岛素敏感性可能与该风险模式有关.β细胞功能没有根据其他代谢改善而改善,符合无反应的潜在风险因素。我们无法复制以前的数据,表明胰岛素抗性脂肪肝是治疗失败的特定风险因素。需要进行复制研究。
BACKGROUND: T2DM heterogeneity affects responsiveness to lifestyle treatment. Beta-cell failure and nonalcoholic fatty liver disease (NAFLD) independently predict T2DM, but NAFLD inconsistently predicts metabolic response to lifestyle intervention.
OBJECTIVE: We attempt to replicate a prediction model deducted from the Tübinger Lifestyle Intervention Program by assessing similar metabolic factors to predict conversion to normal glucose regulation (NGR) in a comparable lifestyle intervention
trial.
METHODS: In the Optimal Fiber
Trial (OptiFiT), 131 Caucasian participants with prediabetes completed a one-year lifestyle intervention program and received a fiber or placebo supplement. We compared baseline parameters for responders and non-responders, assessed correlations of major metabolic changes and conducted a logistic regression analysis for predictors of remission to NGR.
RESULTS: NGR was achieved by 33 participants, respectively. At baseline, for the placebo group only, 1 h and 2 h glucose levels, glucose AUC and Cederholm index predicted conversion to NGR. HOMA-beta, HOMA-IR or liver fat indices did not differ between responders and non-responders of the placebo or the fiber group. Changes in waist circumference or fatty liver index correlated with changes in glycemia and insulin resistance, but not with changes in insulin secretion. Insulin-resistant NAFLD did not predict non-response. Differences in compliance did not explain the results.
CONCLUSIONS: Higher post-challenge glucose levels strongly predicted the metabolic non-response to complex lifestyle intervention in our cohort. Depending on the specific intervention and the investigated cohort, fasting glucose levels and insulin sensitivity might contribute to the risk pattern. Beta-cell function did not improve in accordance with other metabolic improvements, qualifying as a potential risk factor for non-response. We could not replicate previous data suggesting that an insulin-resistant fatty liver is a specific risk factor for treatment failure. Replication studies are required.