P125 MIG (CXCL9) and IL22 are key biomarkers that discriminates between paediatric IBD patients and non-IBD patients in a novel biomarker model

Abstract

Abstract Background The current gold standard for diagnosis of Inflammatory bowel disease (IBD) is based on clinical and endoscopic evaluation as well as histologic and radiologic evaluation. However, endoscopic evaluation can be uncomfortable and carry some risks, especially in the paediatric population that requires general anesthesia in order to perform the procedure. Our aim was to investigate whether serum biomarkers can differentiate between paediatric patients with and without IBD. Secondary aims were to determine whether there are biomarkers that can differentiate between Crohn's disease (CD) and Ulcerative colitis (UC), and whether we can predict progression to biologic treatment within one year from diagnosis using these biomarkers. Methods Paediatric patients undergoing a first diagnostic colonoscopy at British Columbia Children's Hospital (BCCH) between December 2019 and June 2022 were invited to participate in the study. A 2 ml blood sample was taken from each participant at the time of colonoscopy. Demographic and clinical data were collected from each patient. Blood samples were analyzed using the LegendplexTM flow cytometry kits investigating 12 different inflammatory cytokines and chemokines associated with IBD. Eleven of them were found most significant in an initial analysis performed on 100 patients using 50 biomarkers, and CCL7 was added due to significance in previous studies. A prediction model was built via a supervised learning method to determine how well we can predict the different groups. Results Two hundred and forty-six paediatric patients participated in the study. Median age was 13.03 years, 92 were females (37.4%) and 155 (63.01%) were diagnosed with IBD, with 103 (66.45%) diagnosed with Crohn's disease. The AUROC using SPLS-DA classification was 0.805. MIG and Il22 were found to be the key biomarkers to discriminate between pediatric IBD patients and non-IBD patients. In a random forest analysis MIG, Il8 and Il22 were found most important for discrimination. On a univariate analysis MIG and Il18 were found statistically significant as a predictor of CD (p=0.016 for both). CXCL1 was predictive to progression to biologic treatment within one year of diagnosis (p=0.039). However, the prediction model did not predict well the subclasses nor progression to biologic treatment. Conclusion Using serum biomarkers can predict the diagnosis of Paediatric IBD. MIG and Il22 were found to be the key biomarkers in the prediction model.