Nowadays, common medical problems such as obesity, cancer, neurodegenerative and cardiovascular diseases are multifactorial diseases. These are called “multifactorial” diseases because they are caused by several risk factors such as lipid and carbohydrates metabolism dysfunction, chronic-low grade inflammation, microbiota alteration, psychological stress or oxidative stress, among others. Most of them can be modulated by diet and shifting the nutritional habits. Therefore, the knowledge of the exposition degree of these factor of one person is important in order to prevent them and so on, to prevent the onset of a multifactorial disease.
The main objective of this project is the development of a new tool, called PREVENTOMICS, which is based on omic technologies. It will allow the identification of factors that induce disease that are affecting the person’s metabolism in order to personalize the diet.
The strategy to develop PREVENTOMICS consists in isolating each of the factors that induce disease in animal models. Blood and urine samples will be obtained in each model in order to discover the metabolic mark of them. Finally, the different metabolic profiles will be integrated into a predictive model on which the metabolome of the person will be projected. Once the platform will be established, its efficiency will be tested by human samples with different physiological characteristics that have been exposed to nutritional interventions. The results of this characterization will allow to evaluate the possibility of considering a controlled intervention study to apply the PREVENTOMICS platform to real cases of nutrition personalization.