Gut microbiome pattern impacts treatment response in primary biliary cholangitis.

Abstract

Background: Primary biliary cholangitis (PBC) is a progressive autoimmune liver disease. An inadequate response to ursodeoxycholic acid (UDCA) poses a high risk of progression toward end-stage liver disease. Gut dysbiosis has been implicated in PBC. Here, we aimed to investigate microbial signatures that permit risk stratification and provide mechanistic insights into novel therapies for PBC.

Methods: We prospectively recruited UDCA treatment-naive patients with PBC and performed metagenomic sequencing and metabolomic profiling using stool and serum samples obtained before (n = 132) and after (n = 59) treatment. PBC microbiome subtypes were identified using unsupervised machine learning methods and validated in two independent cohorts.

Findings: PBC baseline metagenomes clustered into two community subtypes characterized by varying abundances of Clostridia taxa. Compared with Clostridia^low microbiomes, Clostridia^high microbiomes were more similar to healthy controls. Notably, patients in the Clostridia^low subtype exhibited a 2-fold higher UDCA non-response rate compared to those in the Clostridia^high subtype (41% vs. 20%, p = 0.015). Integrative analysis of metagenomic and metabolomic data revealed divergent functional modules and metabolic activities between the two metacommunities. In particular, anaerobic fermentation and the production of bioactive metabolites, including tryptophan derivatives and secondary bile acids, crucial for immune regulation and gut barrier maintenance, were markedly diminished in the Clostridia^low subtype. Moreover, UDCA administration reconfigured the fecal microbial and metabolic profiles only in the Clostridia^high group. Importantly, the microbiome subtypes and their associations with UDCA response were reproducible in two independent treatment-naive PBC cohorts.

Conclusions: Characterizing baseline microbiota patterns may enable the prediction of treatment outcomes in PBC and facilitate personalized treatment strategies.

Funding: This research was mainly supported by the National Natural Science Foundation of China.