Identification of novel drug targets for mental disorders through genetic, colocalization, and network pharmacology approaches.

Abstract

Background: Schizophrenia, bipolar disorder, and PTSD are prevalent psychiatric conditions with overlapping genetic and environmental risk factors. Current treatments often fall short due to issues like treatment resistance, side effects, and variable patient adherence. This study investigates shared molecular mechanisms and actionable therapeutic targets across these disorders.

Methods: We integrated genetic data from over 500,000 individuals in the Psychiatric Genomics Consortium and FinnGen biobank. A multi-step framework combined protein quantitative trait loci analysis, Mendelian randomization for causal inference, cross-disorder meta-analyses, and colocalization to prioritize protein targets.

Results: Genetic correlations confirmed pleiotropic links among the three disorders. Cross-disorder analyses identified ITIH1 and TIMP4 as consistently associated proteins. Colocalization revealed four high-confidence targets: IGLON5 (synaptic plasticity, OR = 0.69), PTK7 (apoptosis regulation, OR = 0.71), LIMA1 (lipid metabolism, OR = 0.52), and HBEGF (neurotrophic signaling, OR = 1.21). These proteins converge on glycosphingolipid biosynthesis and stress-response pathways. Molecular docking confirmed druggable potential, with binding energies below -7.0 kcal/mol.

Conclusions: IGLON5, PTK7, LIMA1, and HBEGF emerge as mechanistically grounded targets for transdiagnostic therapies. HBEGF's bidirectional effects highlight its potential for personalized treatment strategies. Our integrative approach-combining causal inference, multi-omics data, and computational validation-provides a scalable framework for neuropsychiatric drug discovery.