Inflammatory Bowel Disease (IBD), which includes Ulcerative colitis (UC) and Crohn's disease (CD), is a lifelong condition that affects more than 7 million people worldwide posing a substantial healthcare burden. Patients with IBD have extensive inflammation in the gastrointestinal (GI) tract, severe abdominal pain, rectal bleeding, and frequently require major surgical intervention such as resections and intestinal anastomosis. Among the known pathogenic factors of IBD, dysbiosis in the gut microbiota is reported to be strongly associated with disease onset, progression, and severity. Restoration of a healthy microbiota through fecal microbiota transplantation (FMT) has been clinically demonstrated to improve outcomes in UC. However, FMT lacks specificity and yields inconsistent outcomes due to the inadvertent transfer of pathogens, drug-resistant bacteria, lack of engraftment, and large donor to donor variation. To develop better more specific and safer treatment strategies targeting the microbiota we will identify specific microbial genes that provide valuable insights linked to disease. In this study, we propose to use our in-house computational pipeline (developed on ~721 samples from the HMP2 database) to identify microbial genes linked to IBD and high disease activity flares versus periods of disease remission. This process involves analyzing metagenomics data using our established bioinformatic pipeline to identify microbial genes of interest, and then applying our neural network modelling to identify top priority microbial genes based on network patterning that predict which microbial genes are probable drivers of disease. Following this we will use tools for protein functional prediction in order to characterize those microbial genes-proteins that are of greatest functional relevance to the homeostasis of the intestinal mucosal barrier and may be dysregulated in IBD pathology. We aim to use available and existing metagenomic samples from IBD and non-IBD subjects from different cohorts across continents given the strong influence of geography on microbiota composition.
Why Lifelines cohort: This is a highly rigorously assembled cohort with carefully clinically characterized metadata linked to microbiome sequencing and gut health data. We aim to use this cohort as a control for our other IBD cohorts with similar data collected from Crohn’s and ulcerative colitis patients. Then combine this with our novel microbial gene identification platform to identify key microbial gene drivers of disease.