PREVENTOMICS H2020
Published April 19, 2023 | Version v1
Journal article Open

Omics biomarkers and an approach for their practical implementation to delineate health status for personalized nutrition strategies

Creators

  • 1. Human and Animal Physiology, Wageningen University, Wageningen, the Netherlands
  • 2. EURECAT, Centre Tecnològic de Catalunya, Nutrition and Health, Reus, Spain
  • 3. Laboratory of Molecular Biology, Nutrition and Biotechnology (Group of Nutrigenomics, Biomarkers and Risk Evaluation – NuBE), University of the Balearic Islands, Palma, Spain;d Health Research Institute of the Balearic Islands (IdISBa), Palma, Spain;e Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain;f Spin-off n.1 of the University of the Balearic Islands, Alimentómica S.L, Palma, Spain
  • 4. Department of Nutrition, Exercise, and Sports, University of Copenhagen, Copenhagen, Denmark;h Department of Clinical Nutrition, College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
  • 5. School of Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
  • 6. Department of Clinical Biochemistry, Jagiellonian University Medical College, Krakow, Poland
  • 7. Digital Health, Eurecat, Centre Tecnològic de Catalunya, Barcelona, Spain
  • 8. Centre for Omic Sciences (COS), Joint Unit URV-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), Eurecat, Centre Tecnològic de Catalunya, Reus, Spain
  • 9. Health and Biomedicine, LEITAT Technological Centre, Barcelona, Spain
  • 10. Applied Microbiology and Biotechnologies, LEITAT Technological Centre, Terrassa, Spain
  • 11. Human Nutrition Unit, Department of Food & Drug, University of Parma, Parma, Italy
  • 12. Eurecat, Centre Tecnològic de Catalunya, Biotechnology area, Reus, Spain
  • 13. Eurecat, Centre Tecnològic de Catalunya, Reus, Spain

Description

Personalized nutrition (PN) has gained much attention as a tool for empowerment of consumers to promote changes in dietary behavior, optimizing health status and preventing diet related diseases. Generalized implementation of PN faces different obstacles, one of the most relevant being metabolic characterization of the individual. Although omics technologies allow for assessment the dynamics of metabolism with unprecedented detail, its translatability as affordable and simple PN protocols is still difficult due to the complexity of metabolic regulation and to different technical and economical constrains. In this work, we propose a conceptual framework that considers the dysregulation of a few overarching processes, namely Carbohydrate metabolism, lipid metabolism, inflammation, oxidative stress and microbiota-derived metabolites, as the basis of the onset of several non-communicable diseases. These processes can be assessed and characterized by specific sets of proteomic, metabolomic and genetic markers that minimize operational constrains and maximize the information obtained at the individual level. Current machine learning and data analysis methodologies allow the development of algorithms to integrate omics and genetic markers. Reduction of dimensionality of variables facilitates the implementation of omics and genetic information in digital tools. This framework is exemplified by presenting the EU-Funded project PREVENTOMICS as a use case.

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