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Inflammatory bowel disease is a group of chronic, non-specific inflammatory diseases of the intestinal tract whose etiology has not yet been fully elucidated, including ulcerative colitis and Crohn's disease. Vedolizumab, a novel biologic agent, is a recombinant humanized monoclonal antibody that specifically antagonizes intestine-selective α4β7 integrins on the surface of leukocyte subsets, thereby preventing migration of leukocyte subsets from the blood to the intestinal mucosa and reducing local inflammation in the gut. In this study the investigators propose to build on an existing cohort and analyse, by means of a multi-omics approach, the baseline gut microbial composition and abundance, intestinal and serum metabolome characteristics of UC patients and their changes during treatment, to predict the functional mechanisms by which these changing characteristics influence the therapeutic response to vindolizumab.
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Stool and blood samples etc. were taken from a cohort of patients with ulcerative colitis treated with Vedolizum at the Department of Gastroenterology, Second Affiliated Hospital of Zhejiang University School of Medicine as well as from a cohort of normal volunteers. Stool and blood samples from UC patients were analyzed at baseline and at 14, 30, and 52 weeks after starting treatment. Analysis of changes in gut microbial composition and abundance, gut and serum metabolome characteristics during 52 weeks of treatment in patients with UC. A model for predicting the efficacy of vedolizumab treatment by baseline gut microbial composition and abundance, and gut and serum metabolomic characteristics in patients with ulcerative colitis was developed in conjunction with clinical information from patients in the cohort. Based on the model developed, clinical and gut microbial composition and abundance, gut and serum metabolomics data from other UC patients published in public databases were combined to confirm the results already found using the UC cohort at our center.
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30 participants in 2 patient groups
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Qiao Yu, phd
Data sourced from clinicaltrials.gov
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