Multiomics based analysis of brain gut axis A search for gastrointestinal disea...
Multiomics based analysis of brain gut axis A search for gastrointestinal disease phenotypes
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 varia...
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Información proyecto BrainGutAnalytics
Duración del proyecto: 29 meses
Fecha Inicio: 2020-04-20
Fecha Fin: 2022-09-30
Líder del proyecto
HOGSKULEN PA VESTLANDET
No se ha especificado una descripción o un objeto social para esta compañía.
Presupuesto del proyecto
214K€
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
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.