Assessment of Causal Direction Between Gut Microbiota and Inflammatory Bowel Disease: A Mendelian Randomization Analysis.

Background: Recent studies have shown that the gut microbiota is closely related to the pathogenesis of Inflammatory Bowel Disease (IBD), but the causal nature is largely unknown. The purpose of this study was to assess the causal relationship between intestinal bacteria and IBD and to identify specific pathogenic bacterial taxa via the Mendelian randomization (MR) analysis.
Materials and Methods: MR analysis was performed on genome-wide association study (GWAS) summary statistics of gut microbiota and IBD. Specifically, the TwinsUK microbiota GWAS ( N = 1,126 twin pairs) was used as exposure. The UK inflammatory bowel disease (UKIBD) and the Understanding Social Program (USP) study GWAS ( N = 48,328) was used as discovery outcome, and the British IBD study ( N = 35,289) was used as replication outcome. SNPs associated with bacteria abundance at the suggestive significance level (α = 1.0 × 10 ^-5 ) were used as instrumental variables. Bacteria were grouped into families and genera.
Results: In the discovery sample, a total of 30 features were available for analysis, including 15 families and 15 genera. Three features were nominally significant, including one family ( Verrucomicrobiaceae , 2 IVs, beta = -0.04, p = 0.05) and two genera ( Akkermansia , 2 IVs, beta = 0.04, p = 0.05; Dorea , 2 IVs, beta = -0.07, p = 0.04). All of them were successfully replicated in the replication sample ( Verrucomicrobiaceae and Akkermansia P _replication = 0.02, Dorea P _replication = 0.01) with consistent effect direction.
Conclusion: We identified specific pathogenic bacteria features that were causally associated with the risk of IBD, thus offering new insights into the prevention and diagnosis of IBD.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2021 Zhang, Qu, Zhao, Wang, Wang, Hai and Li.)