Interrogating mechanisms of liver fibrosis with omics

Important studies in 2021 demonstrated sophisticated developments in the study of liver fibrosis through omics. Cell-specific mapping, single-cell sequencing and deep-learning systems revealed complex intra-hepatic mechanisms and new computational platforms facilitating the research towards drug discovery in liver disease and in fibrosis. Key advances Cell-specific mapping of fibrosis-activated transcriptional networks controlling the pathogenic reprogramming of hepatocytes during the transition from nonalcoholic fatty liver disease to nonalcoholic steatohepatitis (NASH) illuminates new mechanisms of fibrogenic crosstalk within the injured liver4. The integration of single-cell RNA sequencing and flow cytometry studies identifies a subset of CD8+ tissue-resident memory T cells that attract and kill activated hepatic stellate cells via FAS-FAS ligand-mediated apoptosis during the resolution of NASH7. The development of a new computational platform, called deep learning-based efficacy prediction system (DLEPS), exploits disease-specific gene signatures to predict new therapies for the treatment of chronic diseases, including NASH9.

Automated summary

Important studies in 2021 demonstrated sophisticated developments in the study of liver fibrosis through omics, revealing complex intra-hepatic mechanisms and new computational platforms facilitating drug discovery. Key advances included cell-specific mapping of fibrosis-activated transcriptional networks and the integration of single-cell RNA sequencing and flow cytometry studies to identify potential therapies for chronic diseases like NASH.