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This study aimed to prioritize candidate druggable genes for major depressive disorder (MDD) using Mendelian randomization (MR) integrated with expression (eQTL) and protein quantitative trait loci (pQTL) data. We conducted a systematic MR analysis combining cis-eQTL and cis-pQTL data from blood and brain tissues to assess the causal effects of druggable genes on MDD, using FinnGen R9 GWAS summary statistics. Bayesian colocalization analysis confirmed shared genetic variants, while sensitivity analyses (MR-Egger, weighted median, MR-PRESSO) tested robustness. A phenome-wide MR (Phe-MR) assessed broader trait associations. To evaluate translational potential, we mapped candidate genes to known drugs using DrugBank, ChEMBL, and ClinicalTrials.gov.Six candidate druggable genes (MAPK3, PSMB9, SIGLEC9, MST1, BTN3A1, and TAPBP) showed significant associations with MDD across multiple eQTL and pQTL datasets. These genes are involved in biological processes related to neuroinflammation, immune regulation, and apoptosis. Colocalization analyses supported shared genetic signals between the identified genes and MDD, while phenome-wide analyses identified associations with additional diseases and traits that may be relevant for future translational research. Through MR analysis, six candidate druggable genes were prioritized from 6889 potential druggable genes as significantly associated with MDD. Among them, MAPK3, MST1, and SIGLEC9 showed consistent evidence across multiple analyses and emerged as genetically supported candidate targets for future investigation.
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周慧静 et al. (2026) studied this question.
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