PTH-075 Identification of IBD immunopathotypes

Introduction Currently only 1/3 of inflammatory bowel disease (IBD) patients respond to the frontline therapies, but recent successes in stratification of Crohn’s disease (CD) and ulcerative colitis (UC) patients into responders and non-responders have been reported. However, little is known about the molecular mechanisms underlying these different treatment responses, and research is still far from developing cost-effective and feasible approaches to predict these responses. Methods Using peripheral blood samples and colonic biopsies, we aim to stratify CD patients into different immunopathotypes. We quantified frequencies of leukocyte populations and cytokines in peripheral blood of patients and healthy controls, using flow cytometry analysis and ELISAs. Cytokine and leukocyte population levels were correlated using Sparse PLS Discriminant Analysis. Additionally, gene expression data was generated by RNAseq from colonic biopsies to identify genes that were differentially expressed between active and remission CD samples, and healthy controls. Results Our initial analyses have identified 3 distinct clusters of CD patients based on expression patterns of peripheral blood mononuclear cells (PBMCs) and cytokines. Patient clusters were found to either upregulate pro-inflammatory cytokine only (Cluster A), upregulate pro-inflammatory cytokines with altered frequencies of leukocyte populations (Cluster C) or solely display altered leukocyte frequencies (Cluster C). In order to further understand potential distinct disease mechanisms, significantly differentially expressed genes from the RNAseq data were analysed identifying genes that varied in expression in the CD cohort, resulting in 13 targets. These gene targets are currently validated in additional CD colonic biopsies using qPCR. Together with clinical information about treatment response and disease severity, these data will be used to investigate the capacity of the blood phenotyping and biopsy gene expression signatures to act as biomarkers to predict treatment responses in CD. Conclusions Based on our results it can be suggested that CD patients have different immunopathotypes, which might be associated with distinct treatment responses. Our ongoing work will assess these potential associations. Should strong associations be identified, their prognostic value will be assessed. Our eventual aim is to help ensure that CD patients receives the most appropriate treatment soon after diagnosis. This is likely to be crucial in limiting damage caused by ongoing inflammation.