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Personalized Metabolomics for Fitness and Training

Periodic Reporting for period 1 - PERMETFIT (Personalized Metabolomics for Fitness and Training)

Reporting period: 2017-09-01 to 2019-08-31

Increasing physical activity (PA) is currently widespread among the population. Interestingly, when consumers are directed to perform PA, either by self-initiative or as directed by providers, the dietary advice is often misleading, without profound knowledge of general metabolism or adaptation to exercise. Thus, the personalized dietary approaches, followed for weight control, have not been adopted in response to PA.
In this framework, the major goal of the present project is to generate scientific evidence for further development of nutrition tools towards PA.
The work carried out in this project has involved several actions, as indicated in the chronogram of activities present in the Annex 1 to the Grant Agreement. The MSCA fellow has been intensely devoted to several tasks essential for the development of the action. As such, he has been involved actively in all the activities as planned. Essentially, he has performed a thorough bibliometric and state-of-the-art technological vigilance over novelties in metabolomic’s guided activities and approaches to personalization of physical activity training. Consequently, he has followed a series of non-formal training activities, based on database management, in silico and wet laboratory setup, quality systems, reporting standards, bioinformatics –including artificial intelligence guided algorithms for personalization of training and nutritional support of physical activity-, bioethics, and obviously, metabolomics itself.
He initially carried out the setup of a bibliometric database encompassing the knowledge, in a systematic review (metanalytical)aided procedure, of changes of specific metabolites in several biological systems as a response to physical activity. This approach demonstrated a significantly high heterogeneity (see below WP2). The heterogeneity was based on very different exercise programs, metabolites, type of sampling, size of sample, location and biofluid, type of sports, and nutritional supplements employed. Despite this heterogeneity, and thanks to the continued feed-back with the rest of the scientific team, the applicant setup a series of different expert systems for evaluating the effects of given physical activity in metabolomics profile.
This was adopted in a continued development along the laboratory techniques. Several sample sizes and sampling methods were assayed. The host institution had a series of specific requisites for sample transport and logistics. These include the need to develop a self-administrable, point-of-care device for biological sampling, also encompassing a high thermic, microbiological, and oxidation-resistant profile. This was attained with the adoption of Volumetric Absorptive Microsampling (VAMS®). This device had already the RUO profile as well as the CE marking for obtaining clinical samples, but the adaptation of the specific procedures for metabolite extraction, stability, quantitation and workup were part of the specific tasks developed by the grantee (see WP3). As a result, a SOP was generated, which was subsequently used in all the analyses for setting up the expert system.
In this regard, the grantee was responsible for the setup of sample control and processing of several pilot programs, where blood was obtained after exercise performed in controlled condition. Not less than 5 different exercise programs, comprising team sports (in basketball), individual sports in controlled environment (treadmill running and controlled cycling), force and strength type physical activities (in controlled environment, to evaluate intra individual variability), and cycling in natural environment, together with trail running (samples already available) were obtained in this action. Due to time constraints, most of the work has been developed in the trail running, with confirmatory roles of treadmill running and controlled cycling. In all the cases, ethics committee permits were obtained and specific guidelines for human experimentation were followed.
All these case studies led to the adoption of the following characteristics of the product:
i) To be a self-deliverable product. Despite capillary blood obtention by finger prick is a very amenable and sustainable sampling procedure, it is more invasive than urinary sampling or other biofluids (e.g. saliva, tears, sweat). However, the lack of common trends of metabolomic signatures, as evaluated in the WP2-resulting database, supported our use of dry blood spots in VAMS device.
ii) To request from the user an ex-ante established type of physical activity. As discussed in the exploratory and implementation strategies (i.e. WP4 and WP5) there were common metabolite signatures after different exercises or sports (cycling, running, indoor fitness, basketball). However, the different length of measured physical activities and the profound effect in several parameters, made us to choose a fixed interval of physical exercise for initial characterization of metabolomics individual response to it.
iii) To offer the user an interactive platform of both physical activity traits and self-delivered questionaries’ on the delivered exercise. This involved the design of software for entering the questions in interplatform, web-based system, with security and privacy constraints.
iv) To generate, for the end-user and the host institution, a system for evaluating major nutrient traits. On pilot experiences, several questionnaires (7-day recall, dietary diaries, frequency intake records) were essayed. The final form delivered a short, although informative enough, close question system, for the definition of protein, lipid, carbohydrate and micronutrient intakes
v) To offer, in a before-after paired analyses, changes impinged by physical activity in the end-user. As discussed below (see WP5 delivered), the type of metabolites examined (which are only a minor fraction of overall measurable) still exceeds what it is present in market for personalized nutrition in physical activity. Thus, the type of information and deliveries, over several major traits, is informative and will help the end-user to adopt responsible and evidence-based measures
vi) To delimitate, across the different dimensions of physical activity and its individual traits, a short list of five major dimensions, comprising relevant aspects for the end-user’s wellbeing and health, such as overtraining, fitness, mental and physical tiredness, and performance.
vii) To generate a continuous and sustainable system. The end-user, when adopting the measures advised in the previous forms, will have a first-hand, personalized system for evaluating the specific changes impinged by adopted measures. This will lead to an overall history of metabolomic traits and responses to training and nutritional advices. For the host institution, this will generate a database to be communicated across society for the best measures and practices to deliver individually suited physical activities, thereby preventing side-effects of unadvised physical activity and sport (e.g. lesions, overtraining, and other well-known consequences of over exercise)
Approach adopted in this project