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Approved Research

Dose - response relationship between nutrient intake and nutrient deficiency/sufficiency for genetic subgroups within the general population and their association with metabolic health

Principal Investigator: Dr Jorg Hager
Approved Research ID: 88163
Approval date: December 16th 2022

Lay summary

The food we eat contributes significantly to maintaining our health. It provides us with nutrients like vitamins, minerals, fatty and amino acids that are essential for ensuring the functioning of our body and metabolism and deficiencies in these nutrients can lead or contribute to diseases like type 2 diabetes and cardiovascular disease. On the other hand, the sufficient intake of these nutrients can help treat or even prevent diseases. The World Health Organization (WHO) recommends a diet balanced in terms of quantity, quality, and safety to prevent malnutrition in all its forms. However, while these guidelines are valid in general, they are not useful for individual recommendations. Indeed, the exact make-up of a balanced diet depends on the individual characteristics (e.g., age, gender, lifestyle, degree of physical activity, !) that influence the response of our body to the nutrients present in the food we eat. Importantly, over the past years it has been shown that the biological mechanisms involved in the utilization and function of nutrients are under the control of our genes. This means that each person has a different need for the amount and/or form of a nutrient depending on the genetic heritage. Although several studies focused on the genetics of the blood concentration of several nutrients, little is still known about the effect that the genome has in their dose-response relationship. In our project, we plan to combine food intake, metabolite, and genetic data in statistical models to quantify the genetic impact on the efficiency of nutrients in reaching their destination or their functional performance and how they relate to health. Understanding the genetics behind the variability in the response to specific nutrients has the potential to provide personalized nutrition recommendations based on the knowledge of an individual's genetic background. In other words, the mathematical models developed here might estimate how much every person may need to eat of a particular nutrient to reach sufficient levels in the body. Such recommendations will be crucial to provide guidelines for a personalized balanced diet to reduce the risk of developing metabolic diseases like type 2 diabetes and cardiovascular disease.