Genetic predictors of metabolic responses to dairy

Tufts University Boston, Boston MA

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Abstract

DESCRIPTION (provided by applicant): The longterm objectives of the proposed five year career development project are to 1) investigate relationships between dairy food intake and genetic variants for cardiovascular disease risk factors and 2) to gain specific training, form collaborative relationships and obtain funding in order to facilitate transition to an independent investigator. The research objectives will be achieved through analysis of data from studies participating in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. The training objectives will be met through formal training in genetics, advanced statistical analysis and nutritional epidemiology, participation in seminars and meetings, and guidance by exceptional scientists in nutrigenomics, cardiovascular epidemiology and statistical genetics. The candidate's primary mentor is Dr. Jose Ordovas, a pioneer and international leader in the field of gene-environment interactions for cardio- metabolic risk. To enhance the career development of the candidate, the co-mentor team includes Dr. David Siscovick, Cardiovascular Health Study leader and physician-researcher, and Dr. Adrienne Cupples, Framingham Heart Study leader and genetics statistician. Metabolic responses to dairy foods, including satiety, energy balance, body weight and protection from diabetes, are inconsistent, and this inconsistency likely reflects genetic variability. In spite of this variability, current detary recommendations for this unique food group are universal for adults. The specific aims of the proposed study are to 1) investigate genetic factors that interact with dairy intake to modify body weight and glucose metabolism and 2) to investigate potential functionality of these genetic variants. To achieve these aims, we will use a genome-wide approach to detect relevant genetic variants. Exomic analyses and bioinformatics will be applied to identify a subset of potentially functional variants that will be replicated in independent populations. Analyses will be conducted in cohorts of European origin and in African Americans participating in CHARGE, an international consortium for which a wealth of genotypes, deep phenotypes and detailed dietary data are available. Comprehensive career development and training will be carried out at Tufts University, a collaborative research environment with expertise in obesity, genetics, diabetes, epidemiology and biostatistics. The candidate and primary mentor are located at the Jean Mayer USDA Human Nutrition Center on Aging at Tufts. Courses will include Meta- analysis, Microarray Data Analysis, Gene Expression, and Epigenomics. The pursuit of the specific aims of the research project and the training plan in genetics and advanced data analysis will facilitate transition to independent research. Substantial gains from studying gene-environment interactions, for dairy and similarly widely-consumed foods, lie in their potential for clarifying disease mechanisms, and also in their translation to genetically informed dietary recommendations that prevent disease through targeted lifestyle modification.