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Empowering consumers to PREVENT diet-related diseases through OMICS sciences

Periodic Reporting for period 1 - PREVENTOMICS (Empowering consumers to PREVENT diet-related diseases through OMICS sciences)

Reporting period: 2018-11-01 to 2020-04-30

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, glucose and proteins 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.
The aim of PREVENTMICS is to build a Nutrition Recommender System (NRS) to guide consumers to healthy food choices based on scientific inputs. The project has two main pillars the first pillar is the design of the application platform (decision support system) and the second pillar is the design of a health knowledge infrastructure, including wet-lab analytics. Lessons learned from the individual business case analyses, market consultations and consumer alignment as well as conclusions derived from the analysis of key project and service assumptions will support efforts in the PREVENTOMICS exploitation strategy.

The knowledge infrastructure departs from five health biomarker clusters that are associated with metabolic dysregulation. Experimental quantification to quantify their usual ranges found in the European population have been done based on previous cohorts from different European locations. Experimental data has been integrated with evidence from clinical guidelines, meta-analyses and top-quality clinical trials to model the relationships among biomarkers and between clusters. This information has been used to develop the algorithms for calculating the score of each of the metabolic clusters per subject. This will also deliver a final biomarker-based model as key result of the developed health knowledge infrastructure by integrating the feedback of human interventional studies. Complete characterization of users is based on combining these data with user habits in order to characterize the user at the physical and metabolic level and for modelling their nutritional and behavioural habits.

PREVENTOMICS Decision Support System (DSS), the model that feeds the application(s) and combines analysis of multilevel user data and scientific knowledge, identifies the health/metabolic profile of a user and assigns them to a specific metabolic group for food choice recommendation. The generation of a personalized recommendation based on health biomarker cluster aims to achieve an improvement in the metabolic status of the user by means of promoting personalized healthy dietary habits. Protocols for data protection, anonymization and secure data sharing were defined. A continuous interaction channel between clinical partners, nutrition experts and pilot leaders was established in order to define the data modelling strategy and the algorithms to be implement in the DSS. This has included explorative analyses of existing datasets of clinical and omics biomarkers aimed at identifying indicators of different metabolic profiles and the elaboration of models that, processing the aforementioned indicators, are able to predict potential metabolic alterations. In parallel final calculations of the genetic contribution in defining the metabolic profile of the user have been developed. The preliminary actionable DSS made it possible to advance the design of the personalized nutrition engine (the NRS). This system integrates the DSS model’s outcomes, expert knowledge and additional user information (eating habits, preferences, etc. to be collected during the pilots) needed to conceive the final recommendation. To facilitate the interoperability of the system and the communication with partners leading the business cases a centralized data storage and web platform (PREVENTOMICS Platform) has been developed.

Regarding the integration of PREVENTOMICS DSS into the different platform and digital channels of the three companies to assure the delivery of personalized recommendations, it has included creating the communication protocols and interfaces. PREVENTOMICS platform architecture enabling the communication among the different components was defined and the PREVENTOMICS DSS has been integrated into the new ALDI’s microsite; in Simple Feast back-end server, as well as in METADIETA’s novel software. Moreover, the personalized behavioural change programme (Do-omics) has been created and it is personalized based on user reports and inputs from the genetic and nutritional data insights from the PREVENTOMICS NRS.
The different human studies to be conducted in the four countries (Denmark, Poland, Spain, and UK) have been carefully reviewed among the consortium and final ethical approvals submitted. Finally, a systematic literature review of the cost-effectiveness of personalized interventions with a nutrition component in adults was conducted. Moreover, preparations to carry out the volunteer survey have started.
PREVENTOMICS project will deliver the following main results:

1. A modular predictive DSS integrating different disease-inducing metabolic signatures as well as genotype and other phenotypic information to correlate health status and personalized nutrition.
2. Functional ingredients adapted to personalized nutrition needs (Food products manufacturers).
3. Personalization of the shopping experience through the use of Big Data and Artificial Intelligence technologies for diet customization based on phenotypic characterization, retailer’s product catalogue, digital interactions and context-aware recommender systems with the aim to provide a personalised user experience.
4. A new service of personalized food manufacturing and delivery levering on the power of omics sciences for the food industry.
5. A changing behaviour programme based on small behavioural steps to expand behavioural flexibility and people to do new things.
6. A dynamic software platform designed to elaborate and deliver personalized nutritional advices in constant evolution with the user (User experience).

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 (especially metabolomics). 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.
PREVENTOMICS project overview