Health
Diet is one of the most influential environmental factors, and there are a number of diseases whose origin is nutritional or metabolic. Given the increase in certain diet-related cancers, obesity and associated pathologies such as diabetes and cardiovascular diseases, there is a clear need to develop effective strategies for their prevention and control.
Recent scientific advances in nutrition, nutrigenomics and nutrigenetics demonstrate the importance of food on people’s health, quality of life and physical and emotional well-being. Thus, the design of personalised diets can contribute to prevention-based wellness.
We define dietary strategies to resolve metabolic imbalances in order to improve people’s quality of life.
There are many factors to consider when designing personalised diets: the new knowledge about the microbiome, the functioning of the microbiota and the gut, and the genetic information of each person. Such knowledge helps us to understand the influence that diet really has on the body.
We contribute our knowledge in nutrigenetics and nutrigenomics to study how diet interacts with gene expression and the development of certain pathologies. By using genomic Big Data and Artificial Intelligence, we can efficiently handle the high volume of genomic data and thus decipher the information contained in genes. Accurate interpretation provides us with a powerful source of highly relevant biological information in areas such as health, metabolism and nutrition.
We have experience using cellular models in our laboratories. This diagnostic tool allows us to experimentally evaluate different physiological processes in different scenarios. This, in turn, enables us to test the benefits of compounds and products and to design health enhancing strategies and products.
Moreover, based on our experience in studying gut microbiota behaviour, we are able to develop new products that enhance their role in protecting the body against pathogens.
The use of molecular tools may be useful when characterising the different metabolic profiles of obesity in order to provide more accurate nutritional recommendations.
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