Project: Advancing Pediatric Precision Healthcare: Integrating Rapid Metabotyping as a Fundamental Component for 4P Medicine through Source-Driven Metabolome Predictions
2023-11-01 – 2027-10-31
- Abstract
The rising incidence of pediatric obesity and associated comorbidities has created an urgent need to identify effective therapeutic approaches. To address this problem, source-driven metabolite predictions (based on diet, microbiome, lifestyle and psychological parameters) are proposed, whereby links between metabolite sources and their biomarker signatures can be obtained as a basis towards individualization of treatments (4P principle). To build this framework, source data and metabolome signatures from 3 pediatric cohorts (MetaBEAse, FAME and ENVIRONAGE) compromising 1817 samples, will be included in a machine learning-based prediction model. To demonstrate the feasibility of moving 4P medicine to routine clinical practice, a patented sampler for optimal gut metabolome coverage (i.e. MetaSAMP®) will be further developed into a kit design and integrated into a rapid metabolomics workflow. This workflow will be cross-correlated with the conventional metabolomics workflow and a selection of source-relevant metabolites will be monitored during a 12-week individualized intervention, comprising dietary and lifestyle counselling, pro-, pre- and/or synbiotic supplementation and/or psychological therapy on a representative selection of children with overweight. Alterations in predicted metabolic signatures of source-relevant metabolites and clinical data will be used to assess the improvement of metabolic status, paving the way towards effective routinely applicable 4P medicine.
-
Determining the main drivers of childhood overweight using the salivary metabolome
-
Exploring the salivary metabolome : key drivers and insights from European 1,436 children
-
Exploring the salivary metabolome : key drivers and insights from 1,436 European children
-
- Journal Article
- A1
- open access
A repository of the salivary metabolome and its key drivers in 1436 European children
-
Integrated fecal metabolomics and lipidomics via 2D-UHPLC-HRMS : a design of experiments approach
-
The pediatric salivary metabolome : non-invasive insights into key drivers across 1,436 children
-
Towards automated integration and quality assessment of chromatographic peaks in targeted LC-MS data with TARDIS
-
Automated integration and quality assessment of chromatographic peaks in LC-MS data using TARDIS
-
Towards dual fecal metabolomics and lipidomics : design of experiments-driven optimization of biphasic extraction and two-dimensional UHPLC-HRMS
-
- Journal Article
- A1
- open access
Automated integration and quality assessment of chromatographic peaks in LC–MS-based metabolomics and lipidomics using TARDIS