Multiplexed targeted mRNA profiling of alcohol-related liver disease reveals stage-specific dysregulation of signaling pathways.

INTRODUCTION

Alcohol-related liver disease (ALD) remains a leading indication for liver transplantation and a major cause of alcohol-attributable deaths worldwide. The molecular events driving extracellular matrix (ECM) accumulation are incompletely understood. In this study, we aimed to investigate stage-specific gene expression signatures in ALD.

METHODS AND

RESULTS

Liver biopsies from 50 adults with prior alcohol overuse were selected: No fibrosis (controls (F0), n = 10), mild/moderate fibrosis (F1-F2, n = 19), and advanced fibrosis/cirrhosis (F3-F4, n = 21). We performed multiplexed targeted profiling of 760 mRNAs, followed by analysis of differentially expressed genes (DEGs) and gene set enrichment analysis. Selected targets were validated on the protein level using immunohistochemistry. Mild/moderate fibrosis versus controls showed 80 DEGs (p < 0.01), 63 of which were downregulated. MLXIPL and FURIN, both involved in glucose and lipid metabolism, were downregulated. Pathways involved in ECM formation were enriched. Advanced fibrosis vs. controls showed 187 DEGs (p < 0.01), of which 94 were upregulated. These included fibrogenic and inflammatory mediators such as TGFB1, COL1A1/2, TIMP1, LGALS3, and S100A4. Genes involved in fatty acid, steroid, and lipid metabolism were significantly repressed. Advanced versus mild/moderate fibrosis showed 211 DEGs (p < 0.01), with an increase in TGF-β-driven ECM remodeling and inhibition of lipid and fatty-acid metabolism pathways. LGALS3 and S100A4 mRNA levels correlated with protein expression (R ≥ 0.41, p < 0.01).

CONCLUSION

ALD is characterized by early downregulation of metabolic genes and upregulation of ECM formation, followed by coordinated induction of the TGF-β-centered fibrogenic pathway and further suppression of metabolic pathways. We identified stage-specific molecular alterations associated with ALD progression and LGALS3 and S100A4 as candidate biomarkers.