Landscapes of gut microbiome and bile acid signatures and their interaction in HBV-associated acute-on-chronic liver failure - Bao, Zhiwei; Wei, Runan; Zheng, Xiaoping; Zhang, Ting; Bi, Yunjiao; Shen, Sijia; Zou, Pengfei; Zhang, Junjie; Yan, Huadong; Li, Ming D.; Yang, Zhongli; Gao, Hainv (Frontiers in Microbiology, 2023)
Distinguishing between acute on chronic liver failure (ACLF) and decompensated liver cirrhosis is difficult. A recent study reported that submassive hepatic necrosis (SMHN) is a likely characteristic pathological feature of ACLF in patients with hepatitis B cirrhosis. We aimed to comprehensively explore microbiome and bile acids patterns across enterhepatic circulation process and build well-performing machine learning models to predict SMHN. Based on the presence or absence of SMHN, 17 patients with HBV-related end-stage liver disease who received liver transplantation were eligible for inclusion. Serum, portal venous blood, and stool samples were collected for comparing differences of BA spectra and gut microbiome and their interactions between two groups. We adopted the random forest algorithm with recursive feature elimination (RF-RFE) to predict SMHN status. By comparing total BA spectrum between two groups, significant changes were detected only in fecal (P = 0.015). Compared with the SMHN (+) group, the SMHN (-) group displayed enrichment in 6 stool bile acids, 3 serum bile acids and 2 portal vein bile acids and depletion in TUDCA in stool. PCoA analysis showed significantly distinct overall microbial composition in two groups (P = 0.026). Co-abundance analysis showed that bacterial species formed strong and broad relationships with BAs. We further identified a combinatorial marker panel with a high AUC of 0.92. Our study demonstrated the changes and interactions of intestinal microbiome and BAs during enterohepatic circulation and revealed that Parabacteroides distasonis may play a role in the processes of ACLF and AD. In addition, we identified a combinatorial marker panel as non-invasive biomarkers to distinguish the SMHN status with high AUC.