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The objective of this project is to validate, through high-throughput advanced metabolomics techniques, the nutritional assessment tools to be used in the IMPaCT cohort. At the same time, the ability of metabolomics fingerprints of nutritional patterns to discriminate between patients with and without major cardiovascular disease will be identified. Finally, the modification of these predictions will be evaluated based on the genetic profiles. The main hypothesis holds that the integration of metabolomics, genomic and nutritional information will serve to personalize the approach to cardiovascular disease, both in prevention and treatment, and that these tools, in turn, will be valid enough to be applied systematically and efficiently in the IMPaCT cohort.
Full description
In two independent samples, one of 600 subjects free of cardiovascular disease (control group) and the other of 600 subjects with a history of ischemic heart disease (established heart disease group) eating habits will be evaluated using Food Frequency Questionnaire, based on those repeatedly used in epidemiological studies carried out in Spain, as well as other nutritional evaluation tools. Each participant will undergo a complete plasma metabolomics profile with identification of > 300 metabolites and a complete genome-wide association analysis. Artificial intelligence models and elastic net regression self-learning algorithms will be applied to select the metabolomics fingerprint of eating patterns.
The objectives are:
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1,200 participants in 2 patient groups
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Estefania A Toledo Atucha, Doctor; Pilar Buil-Cosiales, Doctor
Data sourced from clinicaltrials.gov
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