Nutrition customization

Theme 4

Refine to better prevent diet-related diseases.


Personalizing nutrition, at all stages of life, considers the entire person in order to develop comprehensive, dynamic, and relevant nutritional recommendations for both individual and population health. Nutritional personalization takes into account in this research paradigm multiple factors, such as genetics, epigenetics, metabolomics, microbiome, dietary habits, food environment, physical activity level, environmental exposures, etc., which interact with others to influence the link between nutrition and health.

The exploration of these complex interactions involves, among others, experts from the areas of nutrition, omics, data science, computational biology, and artificial intelligence. The spinoffs and translational applications will help optimize the benefits of healthy eating for individuals and various population subgroups as well as better prevent and treat diet-related chronic diseases.


Nutrigenetics – Nutrigenomics

Research in nutrigenetics and nutrigenomics aimed at getting a better sense of the relationship between genes and diet by focusing, respectively, on the impact of genetic variations on the response to diet and that of the latter on the gene expression. An improved knowledge of the one between genes and diet is essential for the development of personalized nutrition interventions.

Host-Environment Interactions

The study of host-environment interactions is an important element of research in personalized nutrition. For example, the study of the role gut microbiota has in the response to diet, and its impact on the risk factors of lifestyle-related chronic diseases, was booming significantly in the last few years mainly due to the availability of powerful analytical tools, such as high-throughput DNA sequencing.


Application of Omic Sciences, Mega Data and AI to the Food Supply

Omic sciences, including proteomics and metabolomics, help identify the food biomarkers that can be used to assess the nutritional and functional properties of foods. The use of artificial intelligence (AI) to integrate the massive data set (mega data) generated by omics or even to recognize, for example, images of foods in order to assess dietary intakes is an emerging area of research that can greatly assist in developing personalized nutrition.

Development of Personalized Nutrition Interventions

Developing personalized nutrition interventions relies on the use of genetic, phenotypic, behavioural, or environmental information specific to the individual or subgroups of individuals, in order to favour the adoption of healthy eating habits and prevent diet-related chronic diseases.


Areas of Expertise

  • Metabolomics, proteomics, and genomics
  • Epigenomics and epigenetics
  • Gut microbiota and health
  • Nutrition in pregnancy
  • Nutrition and aging
  • Sports nutrition
  • Bioinformatics and machine learning

Research chairs

Canada Excellence Research Chair in the Microbiome-Endocannabinoidome Axis in Metabolic Health

Holder: Vincenzo Di Marzo
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Research Chair in Insulin Resistance and Cardiovascular Complications

Holder: André Marette
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Research Chair in Bariatric and Metabolic Surgery

Holder: André Tchernof
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Canada Research Chair in Genomics Applied to Nutrition and Metabolic Health

Holder: Marie-Claude Vohl
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Canada Research Chair in Animal Reproductive Applied Functional Genomics

Holder: Marc-André Sirard
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Canada Research Chair in Medical Genomics

Holder: Jacques Corbeil
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Canada Research Chair in Bacteriophages

Holder: Sylvain Moineau
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NSERC/Diana Food Industrial Research Chair on the Effects of Polyphenol Prebiotics from Fruits and Vegetables (PhenoBio)

Holder: Yves Desjardins
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See all the themes

Our scientific program revolves around six major unifying themes.