Development of Novel Fecal Microbial Biomarkers for Inflammatory Bowel Disease

Overview

Inflammatory bowel disease (IBD), including Crohn's disease (CD) and Ulcerative colitis (UC), is a chronic idiopathic inflammatory condition of the intestine. Endoscopy has been used to monitor the disease, but it is time-consuming, costly, invasive, and associated with certain risks of morbidity. Many patients are reluctant to undergo repeated endoscopic examinations, particularly when their disease is quiescent. Acute phase reactants have been used to monitor disease including C-reactive protein and stool leucocyte markers including fecal calprotectin, but their sensitivity and specificity in correlating to intestinal inflammation activity are low. Clinical challenge of patient heterogeneity in disease phenotype and response to therapy has compounded discovery of disease-related biomarkers. In IBD, altered fecal microbiota signatures have been consistently reported which included a reduction in biodiversity with lower proportions of Firmicutes and increases in Proteobacteria and Bacteroidetes phylum members. Moreover, overall bacterial diversity is consistently decreased in IBD patients compared to controls. Even though a number of fecal biomarkers have been evaluated for their utility for disease diagnosis in IBD, to date none has been accurate enough for clinical application. Therefore, identification and validation of a non-invasive biomarker which can be easily applied in disease diagnosis and prognosis is warranted to provide an earlier opportunity to intervene. In this study, it aims to develop a metagenomics-based model using fecal microbial biomarkers for differentiating IBD patients from healthy controls, and then validate these fecal microbial biomarkers in different populations.

Inflammatory bowel disease (IBD), including Crohn's disease (CD) and Ulcerative colitis (UC), is a chronic idiopathic inflammatory condition of the intestine, which results in diarrhea, rectal bleeding, urgency, weight loss and abdominal pain. The natural course of IBD is characterized by activity outbreaks and periods of remission. Endoscopy has been used to monitor the disease, but it is time-consuming, costly, invasive, and associated with certain risks of morbidity. Many patients are reluctant to undergo repeated endoscopic examinations, particularly when their disease is quiescent. Acute phase reactants have been used to monitor disease including C-reactive protein and stool leucocyte markers including fecal calprotectin, but their sensitivity and specificity in correlating to intestinal inflammation activity are low. Clinical challenge of patient heterogeneity in disease phenotype and response to therapy has compounded discovery of disease-related biomarkers. In IBD, altered fecal microbiota signatures have been consistently reported which included a reduction in biodiversity with lower proportions of Firmicutes and increases in Proteobacteria and Bacteroidetes phylum members. Moreover, overall bacterial diversity is consistently decreased in IBD patients compared to controls. Even though a number of fecal biomarkers have been evaluated for their utility for disease diagnosis in IBD, to date none has been accurate enough for clinical application. Therefore, identification and validation of a non-invasive biomarker which can be easily applied in disease diagnosis and prognosis is warranted to provide an earlier opportunity to intervene. In this study, it aims to develop a metagenomics-based model using fecal microbial biomarkers for differentiating IBD patients from healthy controls, and then validate these fecal microbial biomarkers in different populations. This is a cross-sectional multi-centre study. Two groups of subjects, IBD patients (cases) and healthy subjects (controls), will be recruited from each centre. Each center will provide fecal samples from 80-100 Crohn's disease, 80-100 ulcerative colitis, and 80-100 controls. We will collect clinical data and stool sample from each subject. Fecal microbiota composition will be compared between cases and controls. The abundance of bacterial biomarkers will be assessed, and the efficacy of a diagnostic model will be validated.