Background: Human diseases are multi-factorial biological phenomena resulting from perturbations of numerous functional networks. The complex nature of human diseases explains frequently observed marginal or transitory efficacy of mono-therapeutic interventions. For this reason, combination therapy is being increasingly evaluated as a biologically plausible strategy for reversing disease state, fostering the development of dedicated methodological and experimental approaches. In parallel, genome-wide association studies (GWAS) provide a prominent opportunity for disclosing human-specific therapeutic targets and rational drug repurposing.
Objective: In this context, our objective was to elaborate an integrated computational platform to accelerate discovery and experimental validation of synergistic combinations of repurposed drugs for treatment of common human diseases.
Methods: The proposed approach combines adapted statistical analysis of GWAS data, pathway-based functional annotation of genetic findings using gene set enrichment technique, computational reconstruction of signaling networks enriched in disease-associated genes, selection of candidate repurposed drugs and proof-of-concept combinational experimental screening.
Results: It enables robust identification of signaling pathways enriched in disease susceptibility loci. Therapeutic targeting of the disease-associated signaling networks provides a reliable way for rational drug repurposing and rapid development of synergistic drug combinations for common human diseases.
Conclusion: Here we demonstrate the feasibility and efficacy of the proposed approach with an experiment application to Alzheimer's disease.
Keywords: Drug combination; drug repurposing; genetics; networks; neurodegeneration; pathways; systems biology.