Periodic Reporting for period 2 - PREVENTOMICS (Empowering consumers to PREVENT diet-related diseases through OMICS sciences)
Berichtszeitraum: 2020-05-01 bis 2022-04-30
In recent years, expectation on personalized nutrition has been increasing but there has been a lack of adequate delivery tools, insufficient understanding of which individual and diet variables to personalize and finally, lack of consideration of the behavioural barriers that stop the individual from behaving in a healthier way. Targeted and individualized nutrition will not work unless these three conditions are optimized sufficiently. It is now known that many of the chronic diseases of high prevalence in our society have a multifactorial origin, being the result of chronic metabolic deregulations induced by several factors, which, in most of the cases, can be modulated or even corrected through diet and modification of nutritional habits. Among these disease-inducing factors, alterations of lipid and glucose metabolic mechanisms, chronic low-grade inflammation, oxidative stress and gut microbiome dysfunction stand out.
PREVENTOMICS main objective is to improve health status of individuals through developing personalized nutrition plans that combines phenotypic characterization at the metabolomic level with consumers’ genotype,
lifestyle, health status, preferences and physiological status. PREVENTOMICS will translate this information into personalized dietetic advice for the user, automatically generated and efficiently delivered with the use of ICT technologies.
PREVENTOMICS main objective is to improve health status of individuals through developing personalized nutrition plans that combines phenotypic characterization at the metabolomic level with consumers’ genotype,
lifestyle, health status, preferences and physiological status. PREVENTOMICS will translate this information into personalized dietetic advice for the user, automatically generated and efficiently delivered with the use of ICT technologies.
The framework for the integration of PREVENTOMICS exploitable results into known business models plus additional alternative models towards personalized nutrition has been assessed.
From the biomarker’s point of view, the analysis of 195 candidate biomarkers of food intake were completed for all the urine samples from the 4 PREVENTOMICS trials and a robust methodological approach for the assessment of dietary intake through spot, fasting urine samples analysed by targeted metabolomics has been validated, proving to be sensitive enough for providing an objective intake assessment, as well as to establish validated biomarkers for the European population.
The technical feasibility of analysing metabolic biomarkers was assessed and the relationships among biomarkers and between metabolic clusters were defined to provide the rules for defining the functional status. Moreover, the interaction between microbiome and personalized diet patterns to prevent obesity and overweight health issues was done following a two-steps approach: i) through characterizing volunteers’ gut microbiome from the intervention studies and ii) research into the effect of the post intervention microbiota compared to the initial timepoint microbiota in a pseudo-germ-free mouse model humanized with the gut microbiome using fecal transplantation from the human samples.
The Decision Support System (DSS) architecture and its components have reached its final version and the Nutrition Recommender System (NRS) integrates the data incomes (from participants’ questionaries and laboratory data) and outcomes (from DSS to the APIs) in a user-controlled environment.
Through the deployment of the four interventional studies, it has been demonstrated that the PREVENTOMICS system can be applied to the different business models and that can reach consumers and professionals in the three different cases.
Overall, the project has proved that personalized nutrition strategies were superior to standard recommendations and has highlighted the need to emphasize the importance of the scientific soundness behind the recommendations to increase user engagement and consequently, achieving long-lasting lifestyle changes.
PREVENTOMICS results have been classified in 4 main categories: products, software, models, and best practices – most of them interconnected. The main Key Exploitable Results are the following:
• PREVENTOMICS Platform: Platform to deliver personalised nutritional recommendations based on lifestyle habits, consumption, metabolomic and genomic information.
• Behavioural change programme: Do-omics sends out personalised Do's, or micro-behaviours, designed to encourage you to step out of your comfort zone and try new behaviours.
• PREVENTOMICS Decision Support System (DSS): Modular model composed of independent metabolic and genetic signatures to generate specific solutions for each user, grouping them according to their characteristics (metabolism and genetics).
• MètaDieta software: to complete food histories and formulate meal plans, and allow a real-time communication between the dietician and the user to provide a more personalised service.
• A web app, simulating a retailer e-commerce portal, to customize the shopping list at retailer level based on phenotypic characterization.
• Food consumption assessment methodology: a set of biomarkers of food intake allowing the identification of the actual diet of an individual or population.
• Functional products: for personalized nutrition adapted to the needs of specific clusters with health alterations.
• Improved service for personalized food manufacturing and delivery: a personalized plant-based diet though a convenience food delivery subscription.
From the biomarker’s point of view, the analysis of 195 candidate biomarkers of food intake were completed for all the urine samples from the 4 PREVENTOMICS trials and a robust methodological approach for the assessment of dietary intake through spot, fasting urine samples analysed by targeted metabolomics has been validated, proving to be sensitive enough for providing an objective intake assessment, as well as to establish validated biomarkers for the European population.
The technical feasibility of analysing metabolic biomarkers was assessed and the relationships among biomarkers and between metabolic clusters were defined to provide the rules for defining the functional status. Moreover, the interaction between microbiome and personalized diet patterns to prevent obesity and overweight health issues was done following a two-steps approach: i) through characterizing volunteers’ gut microbiome from the intervention studies and ii) research into the effect of the post intervention microbiota compared to the initial timepoint microbiota in a pseudo-germ-free mouse model humanized with the gut microbiome using fecal transplantation from the human samples.
The Decision Support System (DSS) architecture and its components have reached its final version and the Nutrition Recommender System (NRS) integrates the data incomes (from participants’ questionaries and laboratory data) and outcomes (from DSS to the APIs) in a user-controlled environment.
Through the deployment of the four interventional studies, it has been demonstrated that the PREVENTOMICS system can be applied to the different business models and that can reach consumers and professionals in the three different cases.
Overall, the project has proved that personalized nutrition strategies were superior to standard recommendations and has highlighted the need to emphasize the importance of the scientific soundness behind the recommendations to increase user engagement and consequently, achieving long-lasting lifestyle changes.
PREVENTOMICS results have been classified in 4 main categories: products, software, models, and best practices – most of them interconnected. The main Key Exploitable Results are the following:
• PREVENTOMICS Platform: Platform to deliver personalised nutritional recommendations based on lifestyle habits, consumption, metabolomic and genomic information.
• Behavioural change programme: Do-omics sends out personalised Do's, or micro-behaviours, designed to encourage you to step out of your comfort zone and try new behaviours.
• PREVENTOMICS Decision Support System (DSS): Modular model composed of independent metabolic and genetic signatures to generate specific solutions for each user, grouping them according to their characteristics (metabolism and genetics).
• MètaDieta software: to complete food histories and formulate meal plans, and allow a real-time communication between the dietician and the user to provide a more personalised service.
• A web app, simulating a retailer e-commerce portal, to customize the shopping list at retailer level based on phenotypic characterization.
• Food consumption assessment methodology: a set of biomarkers of food intake allowing the identification of the actual diet of an individual or population.
• Functional products: for personalized nutrition adapted to the needs of specific clusters with health alterations.
• Improved service for personalized food manufacturing and delivery: a personalized plant-based diet though a convenience food delivery subscription.
PREVENTOMICS goes beyond the state of the art as will deliver different nutritional recommendations in terms of recommended diet, recommended activities or recommended foods, based on people health status and exploiting the potential of omics (genetics, metabolomics and proteomics). The final objective is to empower individuals to meet their health goals through knowledge, autonomy and self-efficacy and to guide them on what to eat and what they required, all integrating behavioural and psychological messages as well.
Overall, participants accept the PREVENTOMICS technologies. However, it remains important to convince people that PREVENTOMICS is not just another tool that will be on the market. Moreover, it is important to pay attention to the fact that participants state that relative to other attributes, the total expenditure on nutrition was seen as most important. Moreover, there are no important legal issues that need to be resolved to use, reimburse or apply personalised nutrition on a wide scale. The idea of the PREVENTOMICS is that it could be used to prevent diet-related diseases in different target populations, either healthy or metabolically compromised. The cost-effectiveness analysis (CEA) together with the Health Technology Assessment (HTA) have served as a good foundation for future research.
Finally, it could be concluded that with a viable ecosystem a high level of personalisation can be a reality. A clear business model for the analytical part is needed (e.g. agreements with labs) but that it could be viable translating the research methodology into a profitable one by for instance, taking advantage of the technological advances since 2018: for instance, to improve cost-efficiency and reduce time NMR might be the standard tool for metabolites, avoiding other costly platforms such as Mass Spectrometry, and robotized multiplex technologies for assessing protein-like analytes.
Overall, participants accept the PREVENTOMICS technologies. However, it remains important to convince people that PREVENTOMICS is not just another tool that will be on the market. Moreover, it is important to pay attention to the fact that participants state that relative to other attributes, the total expenditure on nutrition was seen as most important. Moreover, there are no important legal issues that need to be resolved to use, reimburse or apply personalised nutrition on a wide scale. The idea of the PREVENTOMICS is that it could be used to prevent diet-related diseases in different target populations, either healthy or metabolically compromised. The cost-effectiveness analysis (CEA) together with the Health Technology Assessment (HTA) have served as a good foundation for future research.
Finally, it could be concluded that with a viable ecosystem a high level of personalisation can be a reality. A clear business model for the analytical part is needed (e.g. agreements with labs) but that it could be viable translating the research methodology into a profitable one by for instance, taking advantage of the technological advances since 2018: for instance, to improve cost-efficiency and reduce time NMR might be the standard tool for metabolites, avoiding other costly platforms such as Mass Spectrometry, and robotized multiplex technologies for assessing protein-like analytes.