Review study of alteration functional activities and networks in ulcerative colitis using resting-state fMRI - Alyami, Ali S. (Frontiers in Neurology, 2025)
BackgroundUlcerative colitis (UC), a chronic inflammatory bowel disease (IBD), is linked to neuropsychiatric comorbidities and changes in brain connectivity through the brain-gut axis. Resting-state functional MRI (RS-fMRI) offers a non-invasive approach to examining these neural alterations; however, no comprehensive review has compiled findings specific to UC.ObjectiveThis review summarizes RS-fMRI studies to characterize functional connectivity (FC) alterations and methodological approaches in UC patients compared to healthy controls (HCs) and other inflammatory bowel disease (IBD) subtypes.MethodsLiterature searches were performed in Ovid, PubMed, Google Scholar, and EMBASE (up to July 2025) using keywords: resting-state fMRI, RS-FMRI, ulcerative colitis, and UC. Few studies meeting the inclusion criteria (human participants, UC diagnosis, RS-fMRI analysis) were reviewed.Key findingsSeven studies were included in this review. UC patients show disrupted FC in the salience, cerebellar, visual, default mode, and dorsal attention networks. Reduced hippocampal activity is linked to working memory deficits, while increased FC in corticolimbic areas (e.g., caudate anterior, cingulate) correlates with active inflammation. Grey matter volume decreases in cerebellar regions and increases in parahippocampal regions. Sex-specific differences in FC are observed, especially in the visual and attention networks. Altered FC patterns are associated with the severity of anxiety, depression, and stress. UC exhibits distinct neural signatures compared to CD.ImplicationsRS-fMRI uncovers UC-specific neural phenotypes, advancing the mechanistic understanding of brain-gut interactions. These findings highlight potential biomarkers for neuropsychiatric comorbidities and support the use of integrated fMRI in clinical assessments. Future research should focus on longitudinal studies, larger cohorts, and AI-enhanced analytics to clarify causality and identify therapeutic targets.