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Human Nutrition Unit

Zone de texte éditable et éditée et rééditée

MetAMob

MetAMob
In collaboration with La Charité Hospital BERLIN

Scientific background, hypothesis(s) and objective(s) of the project.

Frailty is a complex clinical state characterized by the loss of physiological homeostasis and capability to handle modifications of its environment . It is now well established that frailty challenges the capacity of aged individuals to handle exposure to stressors and results in an increased risk of adverse outcomes, including lowered quality of life, long term institutionalization and death (4). To minimize risks, optimize outcomes for aged patients, and maintain their independency at home, it is important to identify the level of frailty of patients rapidly and accurately before discharge.

Multiple screening tools have been developed to identify frailty. This process explores in detail functional and nutritional status, cognition, emotional status, comorbidities, polypharmacy, socio-economic status and other geriatric syndromes (sensory impairment, urinary incontinence, …) and leads to the development of a coordinated and multidisciplinary plan for treatment and long-term follow-up (5). However, this essential assessment is time consuming and needs to be conducted by geriatricians or specialist nurses (6) making it unsystematic in the general population. However, many frail aged patients are never referred to a geriatric team and then are never screened.

Two particular determinants of the frailty, mobility and nutritional status are essential to be identified as gait speed has been shown to be associated with survival among older adults in cohort studies (7-12) and has been shown to globally reflect health and functional status. (13). By consequence, geriatric syndromes such as loss of muscle mass and function (sarcopenia), in addition of the frailty syndrome impair the physical foundation of an active mobile life. Unfortunately, mobility and nutritional status are too complex to be deeply assessed at the admission/discharge, and therefore often a superficial screening based on a few markers is performed (see reviews of the  European JPI “Manuel Consortium”). Therefore, more accurate and faster diagnosis tools are required to evaluate the improvement of mobility capacity and nutritional status in frail patients from admission and then assess the future of such patients in term of discharge modalities. For a tool to be deemed useful and feasible to be implemented in the clinical context, it is essential that it does not take too much time to be completed and can be carried out easily by different healthcare professionals. It should be also integrative at the biological level.

Over the past decade, ‘omics’ tools have transformed clinical and nutritional research. In particular, advances in the precision and accessibility of metabolomics tools have permitted the simultaneous characterization of thousands of compounds in biological matrices (14). Comprehensive metabolite profiling defines the metabolic phenotype (metabotype) of a given organism and enables to determine biomarkers that characterize and predict disease incidence and progression. Measuring and modelling the profile of all metabolites (metabolome) can provide insights into disease risk factors and aetiology, which could be useful for personalized medicine (15). This approach is then best suited as a discovery tool rather than providing the exact concentration of a known metabolite. Finally, the exploration of the metabolome can provide unique insights into mechanisms underlying development of a given chronic disease, leading to a comprehensive metabolic phenotyping of individuals.

Taken all this together, metabolomics could provide a valuable insight into the metabotype of aged patients by helping to stratify the patients in function of their frailty, nutrition and mobility levels

The objectiveof MetaMob is:

to obtain a metabolomics-based signature able to identify at the hospitalisation discharge those elderly patients with medium-term (3-6 mo) negative health outcomes and a potentially responsive metabotype to a future (at home) nutritional and/or physical activity intervention.

This will be achieved by applying a metabolomics-based research strategy on blood samples from old patients (German Wonder cohort) with different mobility and nutritional statuses. By comparing the major clinical characteristics at the admission and discharge, different metabotypes clusters (metabolomics-based) will be built in function of the modified profile after 3 weeks of hospitalisation. The metabotypes will be then classified on the basis of the further discharge success (low, medium, high). Those metabotypes showing a receptive profile (medium discharge success) to a nutritional and/or physical activity intervention after discharge will be thereby identified and their biomarkers extracted.

The expected benefits are a more accurate identification of the nutritional and mobility status of hospitalised patients at discharge, a more efficient and personalised care pathway at home and reduced rehospitalisation rate thanks to a more targeted intervention.