Dr. Guasch-Ferré is a Research Scientist in the Department of Nutrition at Harvard T.H. Chan School of Public Health and Instructor of Medicine at Harvard Medical School, Boston, MA. Dr. Guasch-Ferré earned her PhD in Nutrition and Metabolism from the Rovira i Virgili University, Spain. She previously earned a BS and Master in Human Nutrition and Dietetics from the same university. Her research interests include the role of Mediterranean diet on type 2 diabetes, cardiovascular diseases (CVD) and mortality. Her thesis work was aimed at evaluating the effects of key components of the Mediterranean diet ‘olive oil and nuts’ and the risk of CVD in a high-risk population participating in the PREDIMED Study. She conducted several detailed analyses on dietary factors, type 2 diabetes, CVD, and mortality in three large cohort studies, namely the Nurse’s Health Study I and II and the Health Professionals’ Follow-up Study. Her ongoing research aims include incorporating high-throughput –omics techniques, metabolomics and genetics, into traditional epidemiological analysis to gain insights into underlying mechanisms that could explain the associations between diet, lifestyle, and cardiometabolic diseases. Her current research is also aimed at identifying objective biomarkers of dietary intake and lifestyle factors through metabolomics. She is the PI of a project entitled ‘Metabolomics, dietary interventions and type 2 diabetes risk’ granted by the American Diabetes Association. In addition, she is currently working on two NIH-funded projects to study Mediterranean dietary interventions, plasma metabolites, and risk of diabetes and CVD in the PREDIMED Study.
Background: Nutritional metabolomics is evolving to integrate nutrition with complex metabolomics data to discover new biomarkers of nutritional exposure and status. Learning objectives: In this presentation, I will describe the current knowledge from epidemiologic studies identifying metabolite profiles associated with the intake of individual nutrients, foods, and dietary patterns. In addition, I will briefly describe the findings from our recent publications identifying metabolomic fingerprints of several food groups in the PREDIMED Study. Findings: A wide range of technologies, databases, and computational tools are available to integrate nutritional metabolomics with dietary and phenotypic information. Biomarkers identified with the use of high-throughput metabolomics techniques include amino acids, acylcarnitines, carbohydrates, several lipids, etc. The most extensively studied food groups include fruits, vegetables, meat, fish, whole grain cereals, nuts, wine, coffee, tea, and cocoa. Several studies have evaluated metabolite signatures associated with different dietary patterns. Using data from the PREDIMED Study, we have identified a metabolite profile including 19 metabolites that was associated with walnut consumption and with a lower risk of incident T2D and CVD in a population at high cardiovascular risk. In addition, we have also identified a metabolic signature that robustly reflects adherence and metabolic response to a Mediterranean diet, and predicts future CVD risk, in Spanish and US cohorts. Nutritional metabolomics holds promise for the development of a robust and unbiased strategy for measuring diet. Still, this technology is intended to be complementary, rather than a replacement, to traditional well validated dietary assessment methods such as food frequency questionnaires.