Identification of Potential Therapeutic Targets and Drugs for Depression: A Genome-Wide Druggable Mendelian Randomization and Molecular Docking Study
Zehua Luo, Jiaqian Ma, Fan Wu, Tingting Li, Changlan Gao, Mei Sun, Qian Du, Songqing Liu, Wenjun LiIntroduction:
Depression is a common and complex mental health condition. It is shaped by many genetic, environmental, and social factors that influence when it starts and how it progresses. The main biological changes behind depression are still not well understood. Current treatments help some patients, but many only experience partial or unstable benefits. There is a clear need for treatments that are both more effective and more precise for depression. In this study, up-to-date genetic and pharmacogenomic data were used to identify genes targeted by drugs and potential therapy targets for depression. Information from several independent resources was brought together, and these datasets were combined in a stepwise way. With this strategy, the aim was to provide a practical starting point for the development of more targeted antidepressant therapies.
Methods:
Cross-tissue expression quantitative trait loci (eQTL) were first used to analyze data, and these data were combined with Genome-Wide Association Study (GWAS) summary statistics for depression. Then Mendelian Randomization (MR) was applied to identify candidate druggable genes. Colocalization analyses were also performed to check whether the eQTL and depression signals were likely to share the same causal variants. To further assess biological and therapeutic relevance, Phenome-Wide Association Studies (PheWAS), functional enrichment analyses, computational drug prediction, molecular docking, and molecular dynamics simulations were carried out
Results:
Using Mendelian randomization, 34 blood-derived genes and 25 brain-derived genes were identified that showed evidence of association with depression. Colocalization further supported causal roles for 23 blood-and 14 brain-derived genes, with SNRK, MANF, and P4HTM showing significant signals in both tissues. Enrichment analyses implicated immune-related pathways. Docking and dynamics confirmed stable binding between key targets and compounds such as quercetagetin and myricetin.
Conclusion:
These findings provide new therapeutic candidates and help establish a mechanistic framework for the development of targeted antidepressants.