Anti-inflammatory Gut Microbial Pathways Are Decreased During Crohn's Disease Exacerbations.

Background and Aims: Crohn's disease [CD] is a chronic inflammatory disorder of the gastrointestinal tract characterised by alternating periods of exacerbation and remission. We hypothesised that changes in the gut microbiome are associated with CD exacerbations, and therefore aimed to correlate multiple gut microbiome features to CD disease activity. Methods: Faecal microbiome data generated using whole-genome metagenomic shotgun sequencing of 196 CD patients were of obtained from the 1000IBD cohort [one sample per patient]. Patient disease activity status at time of sampling was determined by re-assessing clinical records 3 years after faecal sample production. Faecal samples were designated as taken 'in an exacerbation' or 'in remission'. Samples taken 'in remission' were further categorised as 'before the next exacerbation' or 'after the last exacerbation', based on the exacerbation closest in time to the faecal production date. CD activity was correlated with gut microbial composition and predicted functional pathways via logistic regressions using MaAsLin software. Results: In total, 105 bacterial pathways were decreased during CD exacerbation (false-discovery rate [FDR] <0.1) in comparison with the gut microbiome of patients both before and after an exacerbation. Most of these decreased pathways exert anti-inflammatory properties facilitating the biosynthesis and fermentation of various amino acids [tryptophan, methionine, and arginine], vitamins [riboflavin and thiamine], and short-chain fatty acids [SCFAs]. Conclusions: CD exacerbations are associated with a decrease in microbial genes involved in the biosynthesis of the anti-inflammatory mediators riboflavin, thiamine, and folate, and SCFAs, suggesting that increasing the intestinal abundances of these mediators might provide new treatment opportunities. These results were generated using bioinformatic analyses of cross-sectional data and need to be replicated using time-series and wet lab experiments.