P166 MICROBIOME AND EPIGENETIC PREDICTORS OF RESPONSE TO BIOLOGIC THERAPY IN PATIENTS WITH ULCERATIVE COLITIS

Abstract

Abstract Introduction Current ulcerative colitis (UC) treatments have variable efficacy and may take several weeks to assess improvement. Emerging data suggest the intestinal microbiota may serve as a biomarker and mechanistically may influence immune system activity through epigenetic regulation of host gene expression. The aim of this pilot project was to examine whether the colonic mucosal microbiota and mucosal DNA methylation patterns are associated with a response to treatment in UC. Methods We conducted a retrospective cross-sectional study of patients with active UC. Fresh frozen colon biopsy samples were obtained from the Texas Medical Center IBD Tissue Bank. Patients were included if they had a colonoscopy performed to assess disease activity and follow up through 14 weeks to assess response. Disease activity was defined using the Partial Mayo Score and response was defined as a 2 point or greater decrease in the score after 14 weeks of follow up. 16s rRNA gene sequencing and DNA methylation pyrosequencing were used to define the microbiome and quantify DNA methylation. Comparisons were performed of alpha and beta diversity, taxonomy and DNA methylation between responders and non-responders at 14 weeks. Additionally, a random forest machine learning model was developed to identify predictors of response. Results We identified 16 patients with tissue samples from the cecum/ascending, transverse and rectum/sigmoid available for analysis. After excluding patients with limited rectal disease, recent antibiotic use and inadequate follow up, 4 patients (2 per group) were included and thus provided 12 tissue samples for analysis. The mean age of responders was 38 and non-responders was 24. 50% of patients were male and all were Caucasian. Responders had a numerically lower alpha diversity, though this did not reach statistical significance (p=0.18). Responders and non-responders separated in unweighted (p=0.001) and weighted (p=0.001) beta diversity analysis. Responders had a greater abundance of Firmicutes and Bacteroidetes and lower abundance of Proteobacteria compared to non-responders. This corresponded to responders having a greater abundance of genera for Bifidobacterium, Faecalibacterium and Roseburia. Additionally, we saw increased methylation in the P16, HOXC5 and B4GALNT1 genes of responders compared to non-responders. Finally, in a random forest machine learning model, predictors of response included left sided disease extent and OTUs for the genus Roseburia. Discussion Patients with UC and response to therapy had a significantly different pre-treatment microbiome and methylation of genes related to intestinal barrier function, including B4GALNT1. Larger studies will be needed to validate these findings, but these results suggest the microbiome and DNA methylation changes may be effective biomarkers of response to therapy and warrant further study.