Child microbes predict how to stay away from obesity- CLIMB-OUT. EIT-Food. Coordinator: Prof. Yolanda Sanz
CLIMB-OUT will generate and validate a microbiome-based algorithm, with high sensitivity and specificity to predict the risk of developing obesity in children of EU Mediterranean/RIS regions.
Objectives
- Develop and validate predictive tools (biomarkers/algorithm) of the development of obesity in children based on data from a previous European initiative and new data from a larger cohort of Southern European children, by applying the latest advances in omics (strain-level metagenomics), rich metadata and artificial intelligence (machine learning/deep learning)
- Co-design an ad hoc education and training program to facilitate the adoption and implementation of predictive tools by children, families, and professionals.
Strategy
- Prospective study of obesity development in a large children cohort
- Gut microbiome, metabolome and immune analysis in biological samples
- Generation of a microbiome-informed model for predicting childhood obesity
- Communication and educational activities to support the visibility of the project to raise awareness among HCP and families about microbiome role in obesity onset.
Impact
About 40% of children (aged 6-9 y) of Mediterranean countries suffer from overweight or obesity. This is the highest rate in the EU and, of these, over 60% will be overweight or obese in adulthood, increasing the rates of chronic comorbidities (CVD, T2D) and placing enormous pressure on healthcare system. The creation of an actionable predictive tool will aid in early disease risk detection in children and, thereby, facilitate the timely implementation of lifestyle measures to prevent obesity.