Integrative nutrigenomic and metabolomic analyses of Africans with variable diets

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 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.