Role of brain imaging in disorders of brain-gut interaction: a Rome Working Team Report

Emeran A Mayer, Jennifer Labus, Qasim Aziz, Irene Tracey, Lisa Kilpatrick, Sigrid Elsenbruch, Petra Schweinhardt, Lukas Van Oudenhove, David Borsook, Emeran A Mayer, Jennifer Labus, Qasim Aziz, Irene Tracey, Lisa Kilpatrick, Sigrid Elsenbruch, Petra Schweinhardt, Lukas Van Oudenhove, David Borsook

Abstract

Imaging of the living human brain is a powerful tool to probe the interactions between brain, gut and microbiome in health and in disorders of brain-gut interactions, in particular IBS. While altered signals from the viscera contribute to clinical symptoms, the brain integrates these interoceptive signals with emotional, cognitive and memory related inputs in a non-linear fashion to produce symptoms. Tremendous progress has occurred in the development of new imaging techniques that look at structural, functional and metabolic properties of brain regions and networks. Standardisation in image acquisition and advances in computational approaches has made it possible to study large data sets of imaging studies, identify network properties and integrate them with non-imaging data. These approaches are beginning to generate brain signatures in IBS that share some features with those obtained in other often overlapping chronic pain disorders such as urological pelvic pain syndromes and vulvodynia, suggesting shared mechanisms. Despite this progress, the identification of preclinical vulnerability factors and outcome predictors has been slow. To overcome current obstacles, the creation of consortia and the generation of standardised multisite repositories for brain imaging and metadata from multisite studies are required.

Keywords: brain/gut interaction; functional bowel disorder; irritable bowel syndrome; magnetic resonance imaging.

Conflict of interest statement

Competing interests: EAM is on the scientific advisory boards of Axial Biotherapeutics, Bloom Science, Danone, Viome, Whole Biome and Mahana Therapeutics.

© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Proposed integrative model for disorders of gut–brain Interactions. Replacing the conventional focus on individual brain regions and cell types in the gut, this integrative model posits reciprocal interactions between brain networks (brain connectome) and networks made up of multiple cells in the gut, including the gut microbiota (gut connectome). Gut-to-brain communication is mediated by neural, endocrine and inflammatory pathways, while brain-to-gut communication relies mainly on autonomic nervous system output to the gut. Modified with permission from Enck et al.
Figure 2
Figure 2
Brain networks involved in centrai processing and modulation of visceral pain. Shown are the default mode network (DMN) and four task-related brain networks that have been described in the literature, for which structural and functional alterations and correlations with clinical and behavioural measures have been reported in IBS subjects. Correlations of the listed clinical and behavioural measures have been reported for the salience network, sensorimotor network, emotional arousal network, central executive network, central autonomic network and DMN. Arrows indicate: (A) shift of activity from the DMN to the task-related networks in response to input from the salience network; (B) switching between DMN and central executive network depending on input from the salience network; (C) engagement of emotional arousal network in response to central executive network activation; (D) engagement of central autonomic network in response to emotional arousal network activation; (E) central autonomic network activation with output in the form of descending pain modulation and autonomic nervous system activity to GI tract; (F) ascending viscerosensory signals from gut to sensorimotor network; and (G) assessment of information from sensorimotor network by salience network. The functions of these networks are described in detail in the text. Modified with permission from Mayer et al.
Figure 3
Figure 3
Effect of the HTR3A polymorphism c. −42C>T on amygdala reactivity to emotional and non-emotional stimuli. C/C genotype subjects displayed greater amygdala responses during an emotion matching and form matching task, suggesting a role of this gene polymorphism in influencing the emotional response to different laboratory tasks. With permission from Kilpatrick et al.
Figure 4
Figure 4
Reduced neurokinin-1 receptor binding in IBD. Whole-brain voxel-wise statistical parametric mapping analysis shows regions with lower levels of neurokinin-1 receptor binding in several brain regions in subjects with IBD (A) and patients with IBS (B), relative to healthy controls (voxel extent threshold p20). With permission from Jarcho et al.
Figure 5
Figure 5
Schematic of workflow from multimodal brain image acquisition to multiomics integration of brain and metadata. Acquisition of structural, anatomical (DTI), functional (resting state oscillations) and metabolic (MR spectroscopy, not shown) is followed by image processing and parcellation into multiple regions of interest (ROIs). These parcellated data undergo multiomics integration of different image modalities and clinical, behavioural and non-brain metadata using machine learning approaches. Such data-driven analysis approaches are expected to reveal distinct patters of brain-gut interactions. DTI, diffusion tensor imaging.
Figure 6
Figure 6
Effect of a CRF-R1 antagonist on amygdala response and emotional arousal circuit. (A). Error plot showing standard mean errors for beta contrasts (threat – safe) following placebo (PLA) versus a 20 mg or a 200 mg dose of the CRF-R1 antagonist GW876008 for the left locus coeruleus complex in patients with IBS and healthy controls (HCs) during an experimental pain threat. Results show a dose-dependent reduction in the threat-induced amygdala response by the CRF-R1 antagonist. (B). Path coefficients for the effective connectivity analysis of an emotional-arousal circuit during a pain threat following placebo versus high dose of the CRF-R1 antagonist (200 mg GW876008) In healthy controls and IBS subjects. Significantly different parameter estimates are shown by green arrows, while those not significantly different are shown in black. With permission from Hubbard et al. alNS, anterior insula; aMCC, anterior midclngulate cortex; AMYG, amygdala; HPC, hippocampus; HT, hypothalamus; LCC, locus coeruleus complex; OFC, orbitomedial prefrontal cortex; sgACC, subgenual anterior cingulate cortex.

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Source: PubMed

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