Genetically informed drug target prioritisation and repurposing for major depressive disorder

Abstract

Major depressive disorder (MDD) treatments have limited efficacy and target few mechanisms, highlighting the need for innovative drug discovery. Drugs targeting genetically supported proteins are 2.6 times more likely to succeed in drug development. Here, we use genetic methods to identify and prioritise MDD drug targets, leveraging genome-wide association study (GWAS) summary statistics from >525,000 MDD cases. We derived exposure data from 10 GWAS measuring protein quantitative trait loci (pQTLs) and gene expression levels (eQTLs) in blood, cerebrospinal fluid, and brain tissues. We performed cis- Mendelian randomisation (MR) on 3,469 druggable targets (genes encoding proteins targeted by existing compounds or experimentally predicted to be druggable). To strengthen causal inference, we implemented robust MR estimators, colocalisation, external replication, and assessed directional consistency across tissues. We integrated MR effect directions with drug mechanisms and clinical annotations to infer potential therapeutic effects. Validation analyses showed that 82% of drugs approved for depression/anxiety had [≥]1 significant MR target, compared to 51% for compounds in clinical trials. For repurposing, we prioritised 54 targets of compounds developed for other conditions with estimated beneficial effects on MDD (e.g., an inhibitor for a risk-increasing target). Ten high-priority targets of brain-penetrating compounds included ACE and NISCH (cardiovascular drugs), NDUFA2, NDUFB6, and NDUFS1 (metformin), CDK4, NTRK3, and MET (oncology inhibitors), and GLS and NOS2 (enzyme inhibitors). We found genetic evidence for established and novel MDD targets across the drug development pipeline. Novel targets point to mechanisms beyond monoaminergic systems, most with approved drugs for other conditions, offering immediate repurposing opportunities.