BMC Med:通过预测血糖反应制定个性化饮食对新诊断T2DM患者血糖控制和代谢健康的影响

2022-05-19 从医路漫漫 MedSci原创

糖化血红蛋白(HbA1c)是3个月平均血糖水平的标志,通常用于评估糖尿病管理中的血糖控制。

背景:2型糖尿病(T2DM)是一种进行性疾病,其特征是血糖水平升高,导致严重的大血管和微血管并发症。T2DM的患病率在全球范围内不断增加,影响了大约10%的全球人口。因此,为T2DM寻求有效的预防和治疗方案是当务之急。T2DM管理的主要目标是改善血糖控制,以降低健康并发症的风险。糖化血红蛋白(HbA1c)是3个月平均血糖水平的标志,通常用于评估糖尿病管理中的血糖控制。最近,连续血糖监测(CGM)设备已经成为研究和临床实践中评估血糖控制的另一个可靠工具。

饮食调整显著影响血糖控制,并在T2DM管理中发挥重要作用。此外,在新诊断的T2DM,他们可能会推迟引入糖尿病药物,甚至导致糖尿病缓解。特别是,餐后葡萄糖反应(PPGR)被认为是血糖控制的主要决定因素,在临床实践中通常以膳食“碳水化合物计数”方法为目标,尽管它对PPGR的预测不足。事实上,在T2DM管理中,对于膳食碳水化合物的理想量还没有达成共识,而且低碳水化合物饮食并没有被证明在影响长期血糖控制的能力方面优于高碳水化合物饮食。其他旨在估算PPGRs的方法是血糖指数和衍生的血糖负荷。然而,这些方法将ppgr量化为单一测试食品或膳食的消耗量,因此在评估实际膳食的ppgr时适用性有限。检查低血糖指数饮食对T2DM风险、体重减轻和心血管风险因素的影响的研究产生了喜忧参半的结果。改善T2DM血糖控制的其他策略包括饮食模式,如地中海式饮食,这对血糖控制和代谢健康具有有益的影响。然而,在临床实践中,许多患者仅靠饮食无法达到临床目标,这表明需要替代性和个性化的饮食策略来实现血糖控制。我们之前在一个800人的队列中报告了相同膳食的PPGR的个体差异,并开发了一种机器学习算法,利用临床和肠道微生物组特征预测任何给定膳食的个性化PPGR。

目的:在这里,我们试图评估与普遍推荐的地中海式饮食相比,基于我们算法的饮食干预是否能改善新诊断的T2DM患者和首次使用降糖药物的患者的PPGRs。我们进一步寻求评估基于算法的饮食对血糖控制和代谢健康的长期临床效果,以解决其在临床实践中的适用性及其对肠道微生物组组成的影响。

方法:我们招募了23名新诊断为T2DM的成年患者(年龄53.5±8.9岁,48%为男性)进行为期两周的饮食干预随机交叉试验。参与者不知道他们被分配到两个序列组中的哪一组:PPT-MED或MED-PPT饮食。PPT饮食依赖于一种机器学习算法,该算法集成了临床和微生物组特征,以预测个人餐后葡萄糖反应(PPGR)。我们通过额外的6个月PPT干预(n = 16)进一步评估了PPT饮食对血糖控制和代谢健康的长期影响。在整个研究过程中,参与者被连接到连续血糖监测(CGM ),并使用智能手机应用程序自我记录饮食摄入量。

结果:在交叉干预中,与MED饮食相比,PPT饮食导致显著较低的CGM水平,包括平均PPGR(饮食之间的平均差异,19.8±16.3mg/dl×h,p < 0.001)、平均葡萄糖(饮食之间的平均差异,7.8±5.5mg/dl,p < 0.001)和每日血糖水平> 140 mg/dl的时间(饮食之间的平均差异,2.42±1.7h/天,p < 0.001)与MED干预相比,血液果糖胺在PPT期间也显著降低(饮食之间的平均变化差异为16.4±37 μm ol/dl,p < 0.0001)。在6个月结束时,PPT干预导致多项代谢健康参数显著改善,其中包括HbA1c(平均标准差为0.39±0.48%,p < 0.001)、空腹血糖(16.4±24.2mg/dl,p = 0.02)和甘油三酯(49±46mg/dl,p < 0.001)。重要的是,根据HbA1c < 6.5%的测量,61%的参与者表现出糖尿病缓解。最后,一些临床改善与人均肠道菌群变化显著相关。

图1试验流程和研究大纲。A试验流程图。B实验设计说明,比较了2周的MED饮食与PPT饮食对血糖水平的影响,以及额外6个月的PPT干预计划对多个代谢参数的影响

图2  T2DM患者餐后葡萄糖反应的高人际变异性。先前研究[21]中新诊断为T2DM的受试者子集队列的餐后葡萄糖反应模式和预测(PPGR)。A食用标准化膳食(面包、面包和黄油、葡萄糖和果糖,每种由50克可用碳水化合物组成)后的葡萄糖反应。每条线代表不同的参与者;根据CGM测量的葡萄糖水平给参与者着色。PPGR的范围从0到100毫克/分升×小时。B PPGR的例子为两个ppgr相反的参与者的两次标准化膳食。每餐含碳水化合物50克。22名新诊断的T2DM参与者的PPGR预测。圆点代表预测的(x轴)和CGM测量的膳食PPGR (yaxis ),仅基于膳食的碳水化合物含量。d与C相同,但在这里,该模型基于我们的预测因子,该预测因子是在22名新诊断的T2DM参与者的留一人交叉验证中评估的

图3与MED饮食相比,PPT饮食改善了血糖结果。在所有参与者中比较基于CGM的葡萄糖测量和PPT饮食(绿色)与MED饮食(红色)中的果糖胺。A 所有参与者在MED饮食(红色)和PPT饮食(绿色)干预期间的膳食PPGRs箱线图。统计学显著性显著(曼-惠特尼U检验***p < 0.001,*p < 0.01,*p < 0.05,+p < 0.1;n.s .,不显著)。B和A一样,但所有参与者在每次节食期间的血糖波动(变异系数)不同。定义为每次饮食期间血糖水平的标准差和平均值之间的比率(LMM,p < 0.001)。C除了所有参与者在每次节食期间的平均膳食PPGR(LMM,p < 0.001)。D 在整个MED饮食(红色)和PPT饮食(绿色)干预期间,所有参与者的连续葡萄糖测量的PPGRs的百分位数。E .在MED饮食(红色)和PPT饮食(绿色)干预期间,所有参与者高于葡萄糖水平阈值(x轴)的每日小时数(y轴)。F在地中海饮食(红色)和PPT饮食(绿色)干预期间,所有参与者在一天(x轴)中的平均PPGR (y轴)。G除了所有参与者在每次饮食期间血液果糖胺的平均变化(LMM,p < 0.001)

结论:在这项对新诊断的T2DM患者的交叉试验中,PPT饮食比地中海式MED饮食更能显著改善基于CGM的血糖水平。额外的6个月PPT干预进一步改善了血糖控制和代谢健康参数,支持了这种方法的临床疗效。

原文出处:Rein M,  Ben-Yacov O,  Godneva A, et al.Effects of personalized diets by prediction of glycemic responses on glycemic control and metabolic health in newly diagnosed T2DM: a randomized dietary intervention pilot trial.BMC Med 2022 02 09;20(1)

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    2023-02-01 rgjl
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