Signal Transduction and Molecular Regulation in Fatty Liver Disease.
Xiaocheng Charlie DongKushan ChowdhuryMenghao HuangHyeong Geug KimPublished in: Antioxidants & redox signaling (2021)
Significance: Fatty liver disease is a major liver disorder in the modern societies. Comprehensive understanding of the pathophysiology and molecular mechanisms is essential for the prevention and treatment of the disease. Recent Advances: Remarkable progress has been made in the recent years in basic and translational research in the field of fatty liver disease. Multiple signaling pathways have been implicated in the development of fatty liver disease, including AMP-activated protein kinase, mechanistic target of rapamycin kinase, endoplasmic reticulum stress, oxidative stress, inflammation, transforming growth factor β, and yes1-associated transcriptional regulator/transcriptional coactivator with PDZ-binding motif (YAP/TAZ). In addition, critical molecular regulations at the transcriptional and epigenetic levels have been linked to the pathogenesis of fatty liver disease. Critical Issues: Some critical issues remain to be solved so that research findings can be translated into clinical applications. Robust and reliable biomarkers are needed for diagnosis of different stages of the fatty liver disease. Effective and safe molecular targets remain to be identified and validated. Prevention strategies require solid scientific evidence and population-wide feasibility. Future Directions: As more data are generated with time, integrative approaches are needed to comprehensively understand the disease pathophysiology and mechanisms at multiple levels from population, organismal system, organ/tissue, to cell. The interactions between genes and environmental factors require deeper investigation for the purposes of prevention and personalized treatment of fatty liver disease. Antioxid. Redox Signal. 35, 689-717.
Keyphrases
- oxidative stress
- endoplasmic reticulum stress
- protein kinase
- transforming growth factor
- gene expression
- transcription factor
- fatty acid
- epithelial mesenchymal transition
- single molecule
- electronic health record
- mesenchymal stem cells
- stem cells
- single cell
- deep learning
- big data
- bone marrow
- combination therapy
- network analysis
- bioinformatics analysis