P073 Changes in gut microbial signatures differentiate behavioural Crohn’s disease phenotypes; an in silico approach

Crohn’s disease (CD) is an inflammatory bowel disease (IBD) of idiopathic nature with a heavy burden on the quality of patient life. In 2005 the Montreal World Congress of Gastroenterology introduced the behavioural B1 non‐stricturing non‐penetrating, B2 stricturing and B3 penetrating phenotypes. Today these phenotypes have been properly examined and validated clinically via their respective observations of inflammation, endoscopic fibrostenosis and fistulas. The differential behaviour of CD, is still under investigation with several research teams focusing on different genetic, serological and histological cofounding factors. This work studies the role of the human gut microbiome and its correlation with these specific phenotypes. In recent years microbiota dysbiosis has been linked to IBD. Many researchers have studied the quantifiable and qualitative microbiota population and metabolic changes in CD but have not focused on the behavioural phenotypes. A metagenomic in silico pipeline, consisting of diversity, taxonomic, biomarker, and microbial gene analyses was implemented using the QIIME, Calypso, LEfSe, PICRUSt, and STAMP tools. The pipeline detects changes in microbial 16s rRNA sequencing within the three behavioural phenotypes of CD (B1 non‐stricturing non‐penetrating, B2 stricturing and B3 penetrating) vs. healthy patient samples. The data for our investigations were obtained via publicly available datasets from the QIITA microbial study management platform. The initial identification of microbial populations, taxonomic and diversity analyses via QIIME and Calypso revealed the known loss of α-Diversity within all CD samples with the added effect of statistically significant reductions in the B2 and B3 sample groups vs. B1. There was no statistical significance between the B2 and B3 samples. β-Diversity analysis pointed to microbial compositions similar in the B2 and B3 samples, different from both B1 and healthy controls. Analysis of the abundance of genera in our groups highlighted populations that exhibit reduced or increased abundances in CD, but additionally statistically significant differences in the B2 and B3 compared with B1 samples. Finally, the same pattern was detected in our microbial gene analysis where certain microbial gene abundances were reduced or increased in CD vs. healthy controls, but the B2 and B3 samples had statistically significant changes vs. the B1 group. Our results reveal unique microbial insights into these three phenotypes. Our findings point to a distinct signature of the microbiome’s behaviour in the CD phenotypes and provide the basis for further investigation of CD from a different perspective.

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