Dietary effects on type 2 diabetes risk – Using metabolomics networks to elucidate the underlying mechanisms

饮食对 2 型糖尿病风险的影响 â 使用代谢组学网络阐明潜在机制

• 批准号: 423863258
• 负责人: Dr. Clemens Wittenbecher
• 金额: --
• 依托单位: Department of Nutrition
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/423863258?language=en
• 关键词: Dietary; effects; type; diabetes; risk

A healthful diet protects against type 2 diabetes but the underlying mechanisms are poorly understood. This project aims to identify metabolic pathways that mediate the effects of dietary exposures on diabetes risk.The Nurses‘ Health Study is a prospective cohort study including 121 700 nurses. In this population study conducted by the Harvard University, dietary habits and disease incidence were continuously assessed over the last 40 years. Nowadays, new metabolomics techniques cover a broad spectrum of metabolites in blood specimens and generate accurate snapshots of metabolism. Recently, metabolomics profiles were assessed in a case-control sample nested within the Nurses‘ Health Study, including baseline-healthy women who developed type 2 diabetes in course of the study and a control group that remained disease-free. Such detailed longitudinal information on metabolism, dietary habits and disease incidence implies the unique possibility to observe diet-dependent mechanisms of diabetes development under real-life conditions.This systems epidemiology study comprises four work packages. First, data-driven metabolomics networks will be constructed based on the correlation between metabolites. Then, metabolites will be linked to type 2 diabetes risk. Next, for diabetes-related metabolites, it will be investigated whether they are influenced by dietary exposures that are known to be related to type 2 diabetes risk. The metabolomics networks will be used to differentiate between direct effects on type 2 diabetes risk and indirect effects that merely reflect the correlation with other metabolites. The repeated measurements and the long follow-up time imply the possibility to model change, e.g. relating change in dietary habits to subsequent change in metabolomics profiles. Finally, hypotheses will be generated based on the results of the first three work packages and will then be further investigated with modern causal inference tools. Genetic variants will be used to validate the links between metabolites and diabetes risk in Mendelian randomization studies, and to identify subgroup-specific effects of diet on metabolism in gen-diet interaction analyses. Effects of hypothetical dietary interventions on metabolism and type 2 diabetes risk will be predicted based on the repeated measurements.The expected results will support dietary interventions to prevent type 2 diabetes on the population level and will inform personalized dietary recommendations.

健康的饮食可以预防2型糖尿病，但其潜在机制尚不清楚。该项目旨在确定代谢途径，介导饮食暴露对糖尿病风险的影响。护士健康研究是一项前瞻性队列研究，包括12700名护士。在哈佛大学进行的这项人口研究中，饮食习惯和疾病发病率在过去的40年里不断被评估。如今，新的代谢组学技术涵盖了血液样本中广泛的代谢物，并产生了准确的代谢快照。最近，对护士健康研究中的病例对照样本进行了代谢组学分析，包括在研究过程中出现2型糖尿病的基线健康女性和未患病的对照组。这些关于新陈代谢、饮食习惯和疾病发病率的详细的纵向信息意味着在现实生活条件下观察糖尿病发展的饮食依赖机制的独特可能性。本系统流行病学研究包括四个工作包。首先，基于代谢物之间的相关性，构建数据驱动的代谢组学网络。然后，代谢产物将与2型糖尿病风险有关。接下来，对于糖尿病相关代谢物，将研究它们是否受到已知与2型糖尿病风险相关的饮食暴露的影响。代谢组学网络将用于区分对2型糖尿病风险的直接影响和仅反映与其他代谢物相关的间接影响。重复的测量和长时间的随访意味着模型变化的可能性，例如，将饮食习惯的变化与随后代谢组学谱的变化联系起来。最后，假设将根据前三个工作包的结果生成，然后将用现代因果推理工具进一步研究。在孟德尔随机化研究中，遗传变异将用于验证代谢物与糖尿病风险之间的联系，并在基因-饮食相互作用分析中确定饮食对代谢的亚组特异性影响。假设饮食干预对代谢和2型糖尿病风险的影响将基于重复测量来预测。预期的结果将支持在人群水平上进行预防2型糖尿病的饮食干预，并将为个性化的饮食建议提供信息。

项目成果

Lipid Profiles and Heart Failure Risk: Results From Two Prospective Studies.

• DOI: 10.1161/circresaha.120.317883
• 发表时间: 2021-02-05
• 期刊: Circulation research
• 影响因子: 20.1
• 作者: Wittenbecher C;Eichelmann F;Toledo E;Guasch-Ferré M;Ruiz-Canela M;Li J;Arós F;Lee CH;Liang L;Salas-Salvadó J;Clish CB;Schulze MB;Martínez-González MÁ;Hu FB
• 通讯作者: Hu FB

Immunoglobulin G N-Glycosylation Signatures in Incident Type 2 Diabetes and Cardiovascular Disease.

• DOI: 10.2337/dc22-0833
• 发表时间: 2022-11-01
• 期刊: Diabetes care
• 影响因子: 16.2