¹College of Science, Al-Karkh University of Science, Baghdad, Iraq
²College of Science, University of Anbar, Ramadi, Anbar, Iraq

Abstract. Advanced fibrosis defines mortality risk in chronic liver disease. Current diagnostics fail to capture the molecular transition from early injury to permanent scarring. They often rely on binary classifications obscuring the biological drivers of disease progression. We mapped the gene expression profiles differentiating advanced (F3-F4) from early (F0-F2) fibrosis to determine their cellular origin and protein-level translatability across distinct disease etiologies. We analyzed public bulk RNA-sequencing data (E-MTAB-6863) to isolate genes distinguishing early from advanced fibrosis. We then deconvoluted these signals using single-nucleus RNA-sequencing (snRNA-seq; GSE179548) to identify specific cell types. We validated candidates proteomically in a multi-omics hepatocellular carcinoma dataset comparing viral versus metabolic etiologies. We identified a 105-gene signature associated with advanced fibrosis enriched for extracellular matrix organization and epithelial development. snRNA-seq localized this signal primarily to cholangiocytes rather than hepatic stellate cells indicating a ductular reaction. Proteomic validation showed a divergence. Structural markers (COL1A1, THY1) remained elevated regardless of etiology. Metabolic and ductular markers (AKR1B10, KRT23, SPP1) were specific to metabolic conditions (NAFLD alcoholic liver disease). Advanced fibrosis is fueled by a biliary epithelial response not just matrix deposition. The fibrotic scaffold is conserved across patients. The accompanying metabolic adaptations are etiology dependent. This suggests that effective biomarkers must be tailored to the specific metabolic context of the disease rather than relying on a universal fibrosis panel.

Key words: liver fibrosis, cholangiocytes, ductular reaction, multi-omics, etiology-specific biomarkers