Biliary Microbiota and Bile Acid Remodeling in Common Bile Duct Stone Patients: A Pilot Multi‐Omics Analysis of ERCP‐Acquired Human Bile
Wenxin Xia, Zhaolin Zhang, Yutao Fang, Dilong Fang, Dongya Chen, Feng PanABSTRACT
Background
Gallstone disease is increasingly recognized as involving host–microbe–metabolite interactions. Although biliary microbial communities have been detected in biliary obstruction, their relationship with bile acid remodeling in common bile duct (CBD) stone disease remains unclear.
Methods
ERCP‐acquired bile samples from 25 patients, including 12 with CBD stones and 13 patients with non‐stone pancreatobiliary diseases, including malignant and benign conditions, were analyzed using 16S rRNA sequencing and targeted bile acid metabolomics. Between‐group comparisons and exploratory microbe–bile acid correlation analyses were performed.
Results
Bile samples contained detectable microbial communities dominated by Pseudomonadota and Bacillota . Alpha diversity and overall community structure were comparable between groups, with no significant beta‐diversity separation (PERMANOVA R 2 = 0.0483, p = 0.259). No taxa remained significant after multiple‐testing correction, although several genera showed nominal between‐group differences. Targeted metabolomics showed only mild separation between groups. TUDCA/THDCA and UDCA were higher in the CBD stone group at the nominal p < 0.05 level, whereas 12‐O‐CDCA showed a nonsignificant increasing trend; none remained significant after FDR correction. Exploratory multi‐omics analysis suggested nominal microbe–bile acid associations, but these correlations were also not significant after FDR correction.
Conclusion
This pilot multi‐omics study identified detectable biliary microbial communities and exploratory bile acid remodeling trends in ERCP‐acquired bile from patients with CBD stones. However, key taxonomic, metabolomic, and association findings did not survive multiple‐testing correction and should be interpreted as hypothesis‐generating observations requiring validation in larger, well‐characterized cohorts.