Unique gut microbiota and metabolomic profiling as biomarker of post-transplant recovery in acute-on-chronic liver failure after liver transplantation.

Distinct microbiota and metabolic profiles were observed among ACLF, cirrhosis, and HCC patient groups after liver transplantation.

• 144 fecal samples from 69 patients were analyzed, including patients with ACLF, cirrhosis, or hepatocellular carcinoma (HCC).
• Patients underwent liver transplantation between October 2022 and June 2024 at a single center.
• Fecal samples were collected within 1 month post-LT for 16S rRNA and untargeted metabolomic sequencing.
• Beta diversity was significantly altered in ACLF patients compared to other groups.

ACLF patients exhibited significant depletion of g__Anaerostipes in gut microbiota after liver transplantation.

• Notable depletion of g__Anaerostipes was identified as a distinguishing microbiota feature in the ACLF group.
• Network analysis identified g__Anaerostipes as a key node linking differential taxa and metabolites.
• g__Anaerostipes was characterized as the prominent biomarker of ACLF's multi-omics signature.

Metabolomic analysis revealed enrichment of tangeritin and depletion of candesartan in the ACLF group compared to other patient groups.

• Untargeted metabolomic sequencing was used to identify differential metabolites.
• Tangeritin was enriched in ACLF patients relative to other groups.
• Candesartan was depleted in ACLF patients relative to other groups.
• Substantial metabolic differences were observed among the three patient groups.

A random forest model based on microbiota and metabolomic features effectively distinguished patient groups, with the highest classification accuracy observed in HCC.

• The random forest model incorporated features from both 16S rRNA microbiota profiling and untargeted metabolomics.
• The model was built to classify among ACLF, cirrhosis, and HCC groups.
• Highest classification accuracy was observed for the HCC group.
• The model demonstrates the potential of multi-omic signatures as diagnostic biomarkers.

Multi-omic signatures were associated with early allograft dysfunction (EAD) after liver transplantation, particularly g__Lachnoclostridium.

• g__Lachnoclostridium was identified as a prominent feature associated with EAD.
• Several microbial and metabolic features showed significant correlations with clinical indicators.
• g__Lachnoclostridium was described as 'a promising indicator of recovery after LT.'
• g__Lachnoclostridium showed significant correlations with clinical indicators relevant to post-transplant outcomes.