SOURCE-LINKED INTELLIGENCE

Metabolomics-driven Molecular Source Analysis for personalized medicine in children

CORDIS · observation · Publication date unknown

inically applicable ambient ionization metabotyping, will be developed. Second, molecular fingerprints of our unique deeply phenotyped pediatric cohorts (1.5k children) will be generated and advanced machine learning algorithms will be used to predict metabolite abundances based on their sources, i.e., diet, lifestyle, anthropometrics, microbiome, drug intake, psychological factors, clinical markers, etc. Third, a combination of in vitro digestions, in vivo humanized mice, and in silico experiments with selected source variables will be designed to contribute to our understanding of source-metabolite causality. These mechanistic insights will be used to build dedicated intervention trials in children with specific source-dominated metabotypes. MeMoSA will lay the foundation for integrating metabolomics into personalized and preventive medicine in children through (i) better prediction of individual metabotypes in relation to health; (ii) in-depth insight into metabolite sources, which will foster a framework for biomarker qualification and unraveling disease etiology; (iii) greater t

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recordType

award

status

SIGNED

region

EU

value

1999763

unit

EUR