Approved Research

Identify New Drug Targets for Liver Diseases through Bioinformatics and Big Data Analysis

Lay summary

Liver diseases are a significant global health issue, and they represent one of the leading causes of death. The World Health Organization reports that more than 300 million people worldwide suffer from chronic liver disease, and liver-related diseases claim approximately one million lives each year. Although various drugs, such as antiviral, anti-inflammatory, and immunosuppressant drugs, are currently available to treat liver diseases, they have significant limitations and side effects. For example, some antiviral drugs are ineffective and prone to drug resistance, some anti-inflammatory drugs can cause gastrointestinal reactions, and some immunosuppressants can lead to immune function decline, increasing the risk of infection and cancer. Therefore, there is an urgent need to identify new drugs and target genes for liver diseases.

This study aims to explore the pathological mechanisms and drug targets of liver diseases and screen for potentially effective therapeutic targets and drugs by using bioinformatics analysis, Genome-Wide Association Studies (GWAS), and Phenome-Wide Association Studies (PheWAS). By analyzing vast amounts of clinical and basic research data from the UK Biobank and combining bioinformatics and artificial intelligence technologies, this study will investigate the pathogenesis of liver diseases deeply to identify new drug targets. Additionally, this study will collect and organize relevant information on liver disease case data, disease classification, and drug usage,conduct big data analysis and modeling to discover new treatment targets and drugs.

Ultimately, the research results of this study are expected to provide more treatment options for liver disease, with significant medical and social significance. The precision and effectiveness of liver disease treatment will improve, leading to better treatment outcomes for patients.