MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK.
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Diabetologia. 2024 Jan;67(1):74-87. doi: 10.1007/s00125-023-06019-x. Epub 2023 Oct 25.
AIMS/HYPOTHESIS: High-throughput metabolomics technologies in a variety of study designs have demonstrated a consistent metabolomic signature of overweight and type 2 diabetes. However, the extent to which these metabolomic patterns can be reversed with weight loss and diabetes remission has been weakly investigated. We aimed to characterise the metabolomic consequences of a weight-loss intervention in individuals with type 2 diabetes.
We analysed 574 fasted serum samples collected within an existing RCT (the Diabetes Remission Clinical Trial [DiRECT]) (N=298). In the trial, participating primary care practices were randomly assigned (1:1) to provide either a weight management programme (intervention) or best-practice care by guidelines (control) treatment to individuals with type 2 diabetes. Here, metabolomics analysis was performed on samples collected at baseline and 12 months using both untargeted MS and targeted H-NMR spectroscopy. Multivariable regression models were fitted to evaluate the effect of the intervention on metabolite levels.
Decreases in branched-chain amino acids, sugars and LDL triglycerides, and increases in sphingolipids, plasmalogens and metabolites related to fatty acid metabolism were associated with the intervention (Holm-corrected p<0.05). In individuals who lost more than 9 kg between baseline and 12 months, those who achieved diabetes remission saw greater reductions in glucose, fructose and mannose, compared with those who did not achieve remission.
CONCLUSIONS/INTERPRETATION: We have characterised the metabolomic effects of an integrated weight management programme previously shown to deliver weight loss and diabetes remission. A large proportion of the metabolome appears to be modifiable. Patterns of change were largely and strikingly opposite to perturbances previously documented with the development of type 2 diabetes.
The data used for analysis are available on a research data repository ( https://researchdata.gla.ac.uk/ ) with access given to researchers subject to appropriate data sharing agreements. Metabolite data preparation, data pre-processing, statistical analyses and figure generation were performed in R Studio v.1.0.143 using R v.4.0.2. The R code for this study has been made publicly available on GitHub at: https://github.com/lauracorbin/metabolomics_of_direct .
目的/假设：在各种研究设计中，高通量代谢组学技术已经证明超重和 2 型糖尿病存在一致的代谢组学特征。然而，这些代谢模式在多大程度上可以通过减肥和糖尿病缓解来逆转还没有得到充分研究。我们旨在描述 2 型糖尿病患者减肥干预的代谢后果。
我们分析了现有的 RCT（糖尿病缓解临床试验[DiRECT]）中收集的 574 份空腹血清样本（N=298）。在该试验中，参与的初级保健机构被随机分配（1:1）接受体重管理计划（干预）或根据指南（对照）提供最佳实践护理。在这里，使用非靶向 MS 和靶向 H-NMR 光谱法，在基线和 12 个月时对收集的样本进行代谢组学分析。使用多变量回归模型评估干预对代谢物水平的影响。
与干预相关的是支链氨基酸、糖和 LDL 甘油三酯的减少，鞘脂、血浆类和与脂肪酸代谢相关的代谢物的增加（经 Holm 校正的 p<0.05）。在基线至 12 个月期间体重减轻超过 9 公斤的个体中，与未达到缓解的个体相比，达到糖尿病缓解的个体的葡萄糖、果糖和甘露糖降低幅度更大。
结论/解释：我们已经描述了先前证明可实现减肥和糖尿病缓解的综合体重管理计划的代谢效应。大部分代谢组似乎是可调节的。变化模式与以前记录的 2 型糖尿病发展所引起的紊乱基本相反。
用于分析的数据可在研究数据存储库（https://researchdata.gla.ac.uk/）上获得，经过适当的数据共享协议的研究人员可以访问。代谢物数据准备、数据预处理、统计分析和图形生成均在 R Studio v.1.0.143 中使用 R v.4.0.2 完成。本研究的 R 代码已在 GitHub 上公开：https://github.com/lauracorbin/metabolomics_of_direct。
