Non-alcoholic fatty liver disease (NAFLD) is highly prevalent around the world and affects up to one third of the population. Yet no FDA-approved drugs are available. It is a disease with a spectrum of stages ranging from simple steatosis to nonalcoholic steatohepatitis (NASH), which could progress to cirrhosis and liver cancer in some cases. So far, the exact mechanism of NALFD development and progress is not fully understood. Live biopsy remains the gold standard for accurate diagnosis and detection of progression, which is unsuitable for population screen. So there is an urgent need to develop noninvasive tools for the diagnosis and evaluation of NAFLD.
Secreted proteins play a crucial role in coordinating metabolism and have a natural advantage for application in the diagnosis and treatment of clinical diseases. Currently, several secreted proteins-based drugs are available for the treatment of diabetes. New mass spectrometry (MS) technologies enable the profiling of liver secretome at a global level. The current interest in the secretome of NAFLD deals with not only metabolic crosstalks between different tissues., but also potential biomarker discovery and new therapeutic strategies.
This Research Topic aims at identifying novel secreted proteins that could either be used as serum biomarkers or potential pharmacological candidates. We want to highlight the cutting-edge technologies in profiling and visualizing secreted proteins. We also encourage translational studies incorporating deep learning in novel biomarker identification and secreted protein-based drug design.
We welcome Original Research articles, Reviews, Mini-reviews and Perspectives focusing on the following points:
- Recent advances in profiling liver secretome in health and NAFLD using emerging technologies.
- Studies of investigating secreted proteins in NAFLD and its related diseases.
- Crosstalk between metabolic tissues through secreted proteins.
- Potential application of secreted proteins and machine learning in the diagnosis and evaluation of NAFLD.
- Pre-clinical studies of targeting secreted proteins in NAFLD and its related diseases.
Non-alcoholic fatty liver disease (NAFLD) is highly prevalent around the world and affects up to one third of the population. Yet no FDA-approved drugs are available. It is a disease with a spectrum of stages ranging from simple steatosis to nonalcoholic steatohepatitis (NASH), which could progress to cirrhosis and liver cancer in some cases. So far, the exact mechanism of NALFD development and progress is not fully understood. Live biopsy remains the gold standard for accurate diagnosis and detection of progression, which is unsuitable for population screen. So there is an urgent need to develop noninvasive tools for the diagnosis and evaluation of NAFLD.
Secreted proteins play a crucial role in coordinating metabolism and have a natural advantage for application in the diagnosis and treatment of clinical diseases. Currently, several secreted proteins-based drugs are available for the treatment of diabetes. New mass spectrometry (MS) technologies enable the profiling of liver secretome at a global level. The current interest in the secretome of NAFLD deals with not only metabolic crosstalks between different tissues., but also potential biomarker discovery and new therapeutic strategies.
This Research Topic aims at identifying novel secreted proteins that could either be used as serum biomarkers or potential pharmacological candidates. We want to highlight the cutting-edge technologies in profiling and visualizing secreted proteins. We also encourage translational studies incorporating deep learning in novel biomarker identification and secreted protein-based drug design.
We welcome Original Research articles, Reviews, Mini-reviews and Perspectives focusing on the following points:
- Recent advances in profiling liver secretome in health and NAFLD using emerging technologies.
- Studies of investigating secreted proteins in NAFLD and its related diseases.
- Crosstalk between metabolic tissues through secreted proteins.
- Potential application of secreted proteins and machine learning in the diagnosis and evaluation of NAFLD.
- Pre-clinical studies of targeting secreted proteins in NAFLD and its related diseases.