Axis 1 - Precision Nutrition
The themes and objectives of Axis 1 are:
- Identify the genetic variations involved in the metabolic response to nutrients/food profiles in clinical trials by taking into account the environmental factors that could mediate these interactions.
- Understand the mechanisms by which genetic variations influence response to diet in functional genomic studies on cellular, animal and tissue models/metabolic samples collected from humans, including blood, feces as well as adipose, intestinal and liver tissues.
- Identify gene-diet interactions associated to metabolic health in the context of important population-based cross-sectional and prospective studies.
- Identify epigenetic factors involved in the adaptation process to the environment in the broadest sense of the term, with an emphasis on nutritional factors, in in vitro models, animal models and in cohort studies.
- Study the role of epigenetic factors in the metabolic response and adaptation to nutritional modifications in the context of clinical trials.
- Examine the potential of epigenetic factors as markers of observance for modifications in eating habits.
- Improve measures of food intake, evaluate exposure to nutrients or to specific components and quantify adherence to nutrition interventions and treatments.
- Develop and validate tools for food assessment
- Examine in a systematic way the usefulness of nutritional biomarkers as predictors of the interindividual variability of cardiometabolic response to dietary changes.
Intestinal microbiota and metabolic health
- Study the interrelations between intake of specific nutrients/bioactive components, the intestinal microbiota and the production of microbial metabolites derived from diet.
- Examine functional, bidirectional, and cause-effect relationships between changes in the intestinal microbiota and its derived metabolites, the endocannabinoidome, metabolic health and brain health.
- Test predictive models of the impact of eating and its components on the intestinal microbiota and metabolic health by exploiting artificial intelligence and big data.
- Study the ethical and legal issues associated with research on the microbiota.