Brain-Gut-Microbiota Interaction in IBS

Overview

Are you what you eat? How can dietary components influence microbial composition of the gut and function of the peripheral and central nervous system? The gut and brain is linked through complex mechanisms of sensorimotor functions of the immune system, the hypothalamic-pituitary-adrenal-axis, the enteric nervous system and microbiota. In this project, a multitude of factors contributing to the bidirectional neurobiological communication along the brain-but-axis will be investigated. No disease of the brain-gut axis has been elucidated, therefore our investigations involves approaching a large span of components and processes involved in the axis. This study is carried out as a case-report study (baseline, IBS n=100, healthy controls n=40) followed by a dietary intervention (IBS-D n=60). Through multivariate analyses, the investigators will identify patterns of factors contributing to patient symptomatology and pathology, followed by big data analysis leading to stratification of sub-classification of irritable bowel syndrome (IBS).

Data from deep phenotype characterization of 100 patients with IBS and 40 healthy age (between 18 and 65) and gender-matched controls will be collected between May 2019 and December 2021. Psychometric tests, questionnaires, biological samples (blood, faeces, saliva and GI biopsies from antrum, duodenum and sigmoid colon), assessment of gastric accommodation and emptying using transabdominal ultrasound, vagal activity, and functional and structural magnetic resonance imaging (MRI) of the brain, will be carried out. A subgroup of 60 patients with IBS-D will be further included in a 12-week low Fermentable Oligo-, Di-, Mono-saccharides And Polyols (FODMAP) dietary intervention-study to determine short and long-term effects of diet on symptoms, microbiota composition, molecular GI signatures, cognition and behavioural traits, and structural and functional brain signatures. Deep machine learning, prediction tools and big data analysis will be used for multivariate analysis allowing disease stratification and diagnostic biomarker detection.