Genetic Control of Metabolic Flux in Response to Diet

对饮食反应的代谢流的遗传控制

• 批准号: 10440491
• 负责人: Alan D Attie
• 金额: $ 150万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-17 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10440491
• 关键词: Adipose tissue; Affect; American Heart Association; Animal Model; Automobile Driving; Biological Markers; Biological Models; Body Weight; Candidate Disease Gene; Carbohydrate Metabolism Pathway; Carbohydrates; Chromosome Mapping; Clinical; Clinical Markers; Clinical Research; Consensus; Data; Diet; Diet Research; Dietary Intervention; Distal; Eating; Fatty acid glycerol esters; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Determinism; Genetic Markers; Genetic Screening; Genetic Variation; Genetic study; Genomic Segment; Genotype; Goals; Health; Human; Inbred Strains Mice; Individual; Individual Differences; Insulin Resistance; Intestines; Isotope Labeling; Link; Lipids; Lipoproteins; Liver; Mammals; Maps; Mass Spectrum Analysis; Measurement; Measures; Mediating; Mediation; Mediator of activation protein; Metabolic; Metabolic Control; Metabolic Diseases; Metabolic Marker; Metabolic Pathway; Metabolism; Modeling; Molecular; Mouse Strains; Mus; Muscle; Nutrient; Obesity; Outcome; Pathway interactions; Persons; Phenotype; Physiological; Physiology; Plasma; Play; Population; Population Heterogeneity; Prevalence; Production; Quantitative Trait Loci; Research; Resolution; Role; SNP array; Skeletal Muscle; Small Intestines; Synteny; Testing; Time; Tissues; Tracer; Translating; Validation; Weight Gain; base; blood lipid; cardiometabolism; density; dietary; experimental study; gene discovery; genetic architecture; genetic variant; genome wide association study; genomic locus; glucose tolerance; gut microbiome; gut microbiota; human model; insulin secretion; insulin sensitivity; interest; ketogenic diet; lean body mass; lipid metabolism; metagenomic sequencing; microbiome; molecular marker; molecular phenotype; mouse model; personalized medicine; predictive marker; protein metabolism; response; stable isotope; trait; whole genome

PROJECT SUMMARY/ABSTRACT Despite many years of research in humans and model organisms, there remains no clear consensus about which diet is most compatible with human health. However, the premise of this statement is that a single diet is ideal for everyone. Yet, among humans, there is a wide range in metabolic response to various diets, including body weight, glucose tolerance, and plasma lipids. Genetically diverse mice show this same metabolic variability, suggesting that genetics plays a key role in driving diet-responsiveness. In addition, the microbiome in both humans and mice contributes to diet responsiveness through its metabolism of dietary nutrients and production of potent metabolites. The premise of this project is that genetic interactions with diet and the gut microbiome affect metabolic health. Using an outbred mouse model system that has as much genetic diversity as the entire human population, the Diversity Outbred population, we will genetically map the gene loci that interact with diet and the microbiome to affect cardiometabolic phenotypes. We will test two diets, a low-fat/high carbohydrate diet and a high-fat/low carbohydrate diet. The mice will be phenotyped for glucose tolerance, insulin resistance, weight gain, and circulating levels of lipids and metabolites. Using 15 stable isotope tracers, we will conduct metabolic flux measurements using mass spectrometry-based isotopomer analysis, enabling us to interrogate the major pathways of carbohydrate, lipid, and protein metabolism in multiple tissues. This will be the first time metabolic flux has been subjected to a genetic screen. We will also map gut microbial composition, and gene regulation in key metabolic tissues: liver, adipose, muscle and intestine. These studies will deliver comprehensive genetic maps of these phenotypes. Through the identification of phenotypes that co-map, we will perform mediation analysis to construct causal networks that link gene loci, metabolites, microbiome taxa and physiological phenotypes. We will prioritize loci that are syntenic to human loci with significant metabolic associations in GWAS. These results will provide metabolic markers that can help predict an individual’s metabolic response to specific diets, the first step towards matching diets to individuals.

项目总结/摘要 尽管在人类和模式生物中进行了多年的研究，但对于哪一个仍然没有明确的共识。 饮食最符合人体健康。不过，这种说法的前提是，单一的饮食是理想的 为大家然而，在人类中，对各种饮食的代谢反应范围很广，包括身体 体重、葡萄糖耐量和血浆脂质。遗传多样性的小鼠表现出相同的代谢变异性， 这表明遗传学在驱动饮食反应方面起着关键作用。此外，这两种情况下的微生物组 人类和小鼠通过其膳食营养素的代谢和生产来促进饮食反应性 有效代谢物的。该项目的前提是，饮食和肠道微生物组的遗传相互作用 影响代谢健康。使用一个远系繁殖的小鼠模型系统，该系统具有与整个系统一样多的遗传多样性。 我们将绘制与饮食相互作用的基因位点的遗传图谱， 和微生物组来影响心脏代谢表型。我们将测试两种饮食，低脂/高碳水化合物饮食 以及高脂肪/低碳水化合物饮食。将对小鼠进行葡萄糖耐量、胰岛素抵抗、 体重增加和循环水平的脂质和代谢物。使用15种稳定同位素示踪剂，我们将进行 代谢通量测量使用质谱为基础的同位素分析，使我们能够询问 多种组织中碳水化合物、脂质和蛋白质代谢的主要途径。这将是第一次 代谢流已经经过了基因筛选。我们还将绘制肠道微生物组成图， 调节关键代谢组织：肝脏、脂肪、肌肉和肠。这些研究将提供 这些表型的综合遗传图谱。通过鉴定共同映射的表型，我们 将进行中介分析，以构建连接基因位点、代谢物、微生物组分类群的因果网络。 和生理表型。我们将优先考虑与人类基因座同线的基因座， GWAS中的协会。这些结果将提供代谢标志物，可以帮助预测个人的 代谢反应的具体饮食，第一步匹配饮食的个人。