Using clinical and genetic factors to stratify patients and predict drug response for three commonly used inflammatory bowel disease treatments

Summary

Despite the growing number of treatments available to inflammatory bowel disease (IBD) patients, there are important differences in how well individuals respond to particular drugs, making it difficult for doctors to choose the best option for each patient. Our hypothesis is that this is partly due to inherited genetic differences between patients. For many traits, including IBD, some of the differences between individuals can be explained by the combined effects of many thousands of common genetic variants. We call this combination a polygenic risk score (PRS). For three of the most common IBD drugs, we will search for genetic variants which act in a way which is most relevant to that drug, then use this information to develop a PRS to predict who may respond well to that treatment. We will extend this approach to include other types of biological information which could further improve the prediction. In this project, we will build models to predict response to IBD drugs, based on our current understanding of IBD genetics, together with additional data from the IBD Bioresource. In a separate subset of the IBD BioResource, and in other datasets, we will test how well these models predict drug response.