Integrative nutrigenomic and metabolomic analyses of Africans with variable diets

对饮食多样化的非洲人进行综合营养基因组学和代谢组学分析

• 批准号: 8825139
• 负责人: Sarah Anne Tishkoff
• 金额: $ 36.97万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2018-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8825139
• 关键词: Affect; Africa; African; African American; Agriculture; Biological Markers; Botswana; Cardiovascular Diseases; Cardiovascular system; Clinical; Comparative Study; Complex; Data; Data Set; Diet; Disease; Environment; Environmental Risk Factor; Ethiopia; Food; Frequencies; Genetic; Genetic Variation; Genomics; Geography; Health; Human; Human Genetics; Indigenous; Individual; Intake; Macronutrients Nutrition; Mass Spectrum Analysis; Meta-Analysis; Metabolic; Metabolic Diseases; Metabolic Pathway; Metabolism; Non-Insulin-Dependent Diabetes Mellitus; Nutritional; Obesity; Pathway interactions; Pattern; Phenotype; Plasma; Play; Population; Research; Risk; Role; Sampling; Single Nucleotide Polymorphism; Site; Source; Tanzania; Technology; Testing; Variant; cardiometabolic risk; data integration; disorder risk; exome; genetic variant; genome sequencing; genome-wide; genomic variation; insight; metabolomics; nutrition; nutrition related genetics; nutritional genomics; public health relevance; tool; trait

 DESCRIPTION (provided by applicant): Most studies of human genomic variation, nutrition, and metabolic traits have focused on non- African populations. However, Africa is an important region to study as it is the site of origin of modern humans. Africa contains the greatest levels o human genetic variation and is the source of the worldwide range expansion of modern humans to regions outside of Africa. Several common complex diseases of metabolic origin, such as obesity, type 2 diabetes and certain cardiovascular diseases occur at higher frequency in African Americans, and are on the rise in urban centers in Africa. It has been postulated that this is due to genetic variants adaptive for past environments with intermittent access to food but maladaptive in nutritionally replete "Westernized" environments. Metabolomics technology has begun to provide insight into metabolic processes and can be used for biomarker identification for disease risk and provide insight into metabolic pathways associated with risk. Given the intimate relationship between nutrition and metabolism and subsequent disease risk, metabolomics provides a unique and powerful tool in nutritional research. In this proposal, we will exploit metabolomic profiling to interrogate extant plasma from a unique set of ethnically diverse, well phenotyped indigenous African populations who practice different subsistence patterns (agriculture, pastoralism, agro- pastoralism, and hunting-gathering) who vary markedly in markers of cardiometabolic risk. We will perform untargeted metabolomics profiling in a sample of 365 individuals and will do targeted profiling of informative metabolites in a sample of 1500 ethnically diverse Africans to identify differences in metabolites and metabolic pathways that correlate with diet and anthropometric and cardiovascular phenotypes associated with disease risk. We will integrate these data with a large genome-wide Single Nucleotide Polymorphism (SNP) and whole genome sequence dataset collected in the same individuals to gain insight into how genetic, nutritional and other environmental factors contribute to variation in cardiometabolic risk traits in ethnically diverse African populations.

 描述（由申请人提供）：大多数人类基因组变异、营养和代谢特征的研究都集中在非非洲人群。然而，非洲是一个重要的研究地区，因为它是现代人类的起源地。非洲包含了最大程度的人类遗传变异，是现代人类向非洲以外地区扩张的源头。几种常见的代谢性复杂疾病，如肥胖症、2型糖尿病和某些心血管疾病，在非洲裔美国人中发生频率较高，在非洲的城市中心也呈上升趋势。据推测， 是由于遗传变异适应过去的环境与间歇性获得食物，但不适应营养丰富的“西化”环境。代谢组学技术已开始提供对代谢过程的洞察，并可用于疾病风险的生物标志物识别，并提供对与风险相关的代谢途径的洞察。鉴于营养和代谢以及随后的疾病风险之间的密切关系，代谢组学为营养研究提供了独特而强大的工具。在本提案中，我们将利用代谢组学分析来询问来自一组独特的种族多样性、良好表型的土著非洲人群的现存血浆，这些人群实行不同的生存模式（农业、畜牧业、农牧和狩猎采集），其心脏代谢风险标志物显著不同。我们将在365名个体的样本中进行非靶向代谢组学分析，并将在1500名种族多样的非洲人样本中进行信息代谢物的靶向分析，以确定与饮食和人体测量相关的代谢物和代谢途径的差异以及与疾病风险相关的心血管表型。我们将这些数据与在同一个体中收集的大型全基因组单核苷酸多态性（SNP）和全基因组序列数据集相结合，以深入了解遗传，营养和其他环境因素如何导致种族多样的非洲人群中心脏代谢风险特征的变化。