Alterations of gut microbiome in autoimmune hepatitis. Issue 3 (14th June 2019) - Wei, Yiran; Li, Yanmei; Yan, Li; Sun, Chunyan; Miao, Qi; Wang, Qixia; Xiao, Xiao; Lian, Min; Li, Bo; Chen, Yong; Zhang, Jun; Li, You; et al.
Abstract : Objective: The significance of the liver-microbiome axis has been increasingly recognised as a major modulator of autoimmunity. The aim of this study was to take advantage of a large well-defined corticosteroids treatment-naïve group of patients with autoimmune hepatitis (AIH) to rigorously characterise gut dysbiosis compared with healthy controls. Design: We performed a cross-sectional study of individuals with AIH (n=91) and matched healthy controls (n=98) by 16S rRNA gene sequencing. An independent cohort of 28 patients and 34 controls was analysed to validate the results. All the patients were collected before corticosteroids therapy. Results: The gut microbiome of steroid treatment-naïve AIH was characterised with lower alpha-diversity (Shannon and observed operational taxonomic units, both p<0.01) and distinct overall microbial composition compared with healthy controls (p=0.002). Depletion of obligate anaerobes and expansion of potential pathobionts including Veillonella were associated with disease status. Of note, Veillonella dispar, the most strongly disease-associated taxa (p=8.85E–8), positively correlated with serum level of aspartate aminotransferase and liver inflammation. Furthermore, the combination of four patients with AIH-associated genera distinguished AIH from controls with an area under curves of approximately 0.8 in both exploration and validation cohorts. In addition, multiple predicted functional modules were altered in the AIH gut microbiome, including lipopolysaccharide biosynthesis as well as metabolism of amino acids that can be processed by bacteria to produce immunomodulatory metabolites. Conclusion: Our study establishes compositional and functional alterations of gut microbiome in AIH and suggests the potential for using gut microbiota as non-invasive biomarkers to assess disease activity.