Circulating multi-omic signature of disease severity and cholangiocarcinoma in primary sclerosing cholangitis
Hepatology Communications, 2026
Nouairia G., Schumacher A., Bergquist A., Cornillet M.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Immunological & Inflammatory Diseases Hepatology | Pathophysiology | Plasma |  Olink Target 96 |
Abstract
Background:
Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease often associated with inflammatory bowel disease (IBD) that can progress to cirrhosis or cholangiocarcinoma (CCA), both carrying a poor prognosis. The mechanisms driving disease progression remain poorly understood. We aimed to identify circulating multi-omic signatures linked to PSC severity (alkaline phosphatase, bilirubin, fibrosis), IBD, and CCA to elucidate underlying biology and discover potential biomarkers for risk stratification and disease monitoring.
Methods:
We quantified 737 proteins, 1083 metabolites, and 4573 miRNAs using plasma from 33 patients with PSC with various clinical presentations. We applied machine learning-driven analysis and network-based modeling for the data integration and analysis of associations. Parameters robustly identified in both methods were considered for tailored pathway enrichment analysis.
Results:
We identified circulating multi-omic profiles associated with PSC disease severity, IBD, and CCA. IBD-specific alterations were subtle; however, we noted associations between microbial-derived metabolites and colorectal cancer-related miRNAs. Severe PSC shared molecular features with PSC-CCA, indicating early activation of malignant pathways in PSC. Severe PSC was characterized by immune-interacting and epithelial-interacting proteins, bile acid and glutathione-related metabolites, and miRNAs regulating fibrosis, inflammation, extracellular matrix remodeling, and cell cycle control, overlapping with PSC-CCA. In established PSC-CCA, we observed coordinated alterations in oncogenic miRNAs, growth factor-related proteins, and depletion of sulfated phenolics and methylxanthines, reflecting extracellular matrix remodeling, inflammatory microenvironment reprogramming, and impaired hepatic detoxification. Overall, pathway enrichment analysis revealed an infection-like and cancer-associated signature defining PSC pathogenesis.
Conclusions:
Circulating multi-omic profiles capture the key features of PSC severity and associated CCA. These findings provide mechanistic insights and identify potential biomarkers for cancer risk stratification and disease monitoring using PSC.