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Neurophenotype Predicts CD Disease Progression

NCT06452550 · First Affiliated Hospital, Sun Yat-Sen University
In plain English

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Official title
Multimodal MRI-based Neurophenotype Reflecting Brain-gut Interactions to Predict Intestinal Disease Progression in Patients With Crohn's Disease
About this study
Brain-gut axis plays a crucial role in the pathogenesis of Crohn's disease (CD); however, CD neurophenotype and its impact on intestinal disease progression remain unclear. We aimed to develop a novel multimodal neuroimaging-based model to characterize the neurophenotype of CD patients and assess its ability for predicting disease progression, using multiomics data to interpret the model. This study enrolled CD patients who underwent baseline testing (including neuroimaging, psychological scales, MR enterography, and ileocolonoscopy) and faecal/blood samples collection. The neurophenotypes of patients were characterized using a neuroimaging-based model. The predictive ability of neurophenotype model for disease progression was evaluated using Cox regression analysis. Multiomics data (including faecal microbiome, faecal/blood metabolomics, intestinal permeability, blood-brain-barrier permeability, and blood neurotransmitter levels) were used to elucidate how neurophenotypes reflect brain-gut interactions.
Eligibility criteria
Inclusion Criteria: * (a) CD patients aged 18-45 years; (b) the completion of multimodal brain MRI and administration of psychological questionnaires; (c) MR enterography (MRE), ileocolonoscopy, and blood or faecal samples, collection within one week of brain MRI; (d) a follow-up of at least six months for patients without disease progression; and (e) right-handedness. Exclusion Criteria: * (a) recent use of antibiotics, probiotics, or prebiotics within three months prior to inclusion; (b) history of neurosurgery, cerebrovascular disease, or brain trauma; (c) use of central nervous system drugs or antidepressants within three months prior to inclusion; (d) identification of brain lesions on MR scan; (e) claustrophobia; or (f) presence of metal implants.
Study design
Enrollment target: 500 participants
Age groups: adult
Timeline
Starts: 2021-05-01
Estimated completion: 2025-06-01
Last updated: 2024-06-11
Interventions
Diagnostic Test: Logistic regression (LR) prediction models
Primary outcomes
  • The area under the ROC curve (AUC) to assess the performance of diagnostic model (6 months)
Sponsor
First Affiliated Hospital, Sun Yat-Sen University · other
Contacts & investigators
ContactXuehua Li · contact · lxueh@mail.sysu.edu.cn · 13580364103
ContactRuonan Zhang · contact · zhangrn25@mail2.sysu.edu.cn · 15124748450
InvestigatorXuehua Li · principal_investigator, Sun Yat-sen University First Affiliated Hospital Department of Radiology
All locations (1)
XploreMET v3.0 systemRecruiting
Shanghai, China
Neurophenotype Predicts CD Disease Progression · TrialPath