Description du projet
Mieux comprendre l’axe cerveau-intestin
De récentes découvertes révèlent une interaction réciproque entre l’intestin et le cerveau, certains troubles gastro-intestinaux présentant diverses altérations cérébrales et vice versa. Les scientifiques du projet BrainGutAnalytics, financé par l’UE, cherchent à mieux comprendre la nature et le fonctionnement de cet axe intestin-cerveau. En utilisant une approche multiomique qui combine la neuro-imagerie, le diagnostic clinique et le profilage microbien, ils identifieront les phénotypes gastro-intestinaux appropriés et les mettront en corrélation avec des biomarqueurs. Ces biomarqueurs serviront de base à un nouveau système de diagnostic, ainsi qu’à la conception de médicaments et de traitements de précision pour les troubles neurologiques et gastro-intestinaux.
Objectif
An intimate yet less known relation between human brain and gut is rapidly emerging as several recent studies have identified various alterations within brain as a result of gastrointestinal disorders and reported comparable variations in gastrointestinal system due to altered brain outputs. These relationships are collectively termed as brain-gut axis and a deeper understanding of its exact nature and operation can lead to development of novel diagnosis, drugs and precision treatment for both neurological and gastrointestinal disorders.
The first step towards establishing a comprehensive understanding of brain-gut axis is to identify suitable phenotypes that can be used to describe certain disease state and serve as basis for further investigations into operation of brain-gut axis. In this study, a multiomics based data analysis approach is proposed to search for exclusive and generalizable phenotypes of a certain gastrointestinal disorder. Our multiomics data consist of multimodal imagery of brain and gut, clinical diagnostics, microbial profiling, questionnaire based disease evaluations, genetic and molecular representations taken from carefully designed cohorts of patients and healthy controls. Our data analyses will employ a variety of techniques including digital image processing, computer vision, machine learning and statistical methods to determine covariate factors in omics, which will be then used to identify representative biomarkers for gastrointestinal disorders.
We also aim to develop a novel diagnosis system for gastrointestinal disease based on novel biomarkers through a combination of neuroimaging and digital image processing pipeline . Our research is expected to excel the existing knowledge on brain-gut axis by exposing critical phenotypes, employing them for early diagnostic and paving way towards deeper understanding of brain-gut axis.
Champ scientifique
- natural sciencescomputer and information sciencesdata science
- social sciencesmedia and communicationsgraphic design
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- medical and health sciencesclinical medicinegastroenterology
Programme(s)
Régime de financement
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinateur
5021 Bergen
Norvège