Identifying Potential Drug Targets for Treating ADHD From a Genetic Perspective: A Mendelian Randomization Study

Attention-deficit/hyperactivity disorder (ADHD) is a chronic neurodevelopmental disorder. Current pharmacological treatments have limitations, highlighting the need for new therapeutic targets. Using two-sample Mendelian randomization with cis-expression quantitative trait loci from the eQTLGen Consortium (31,684 individuals), we performed genomewide analysis against ADHD genomewide association study summary statistics from European ancestry (20,183 cases; 35,191 controls) and FinnGen R10 (2,788 cases; 405,153 controls). Genetic instruments were selected at p < 5 × 10^-8 with F-statistic > 10 and linkage disequilibrium clumping (r² < .001). Mendelian randomization estimates were derived using inverse-variance weighted, weighted-median, and Mendelian randomization-Egger methods, with leave-one-out sensitivity analysis. Colocalization was performed to distinguish causality from linkage disequilibrium. From 5430 genes with valid instruments, we identified 10 ADHD-associated genes (inverse-variance weighted p < .01, consistent direction across methods): four risk-increasing genes (RRAGD, DTX2, HMOX1, AGAP3) and six protective genes (NUCKS1, CPSF1, MAU2, CLDN5, CYP4F12, ATP6V1E2). MAU2 demonstrated strong colocalization support (posterior probability for hypothesis 4 > .6). Pathway enrichment highlighted mechanistic target of rapamycin signaling as a priority mechanism. Computational in silico drug prioritization nominated candidate compounds (e.g., selenium, ketoconazole) predicted to modulate these targets. This study identifies genetically supported therapeutic targets for ADHD. MAU2 emerged as the most promising causal locus. Rapamycin signaling represents a key mechanistic pathway. Several repositioned candidates (e.g., selenium, ketoconazole) warrant further experimental evaluation as potential leads. These findings provide a hypothesis-generating foundation for drug target prioritization, and require functional confirmation in CNS models and clinical validation before therapeutic relevance can be established.