Leveraging Gene Expression Data for Drug Repurposing in Schizophrenia: A Signature Reversion Approach

Background/Objectives: Despite continuous pharmacological advances, the treatment of schizophrenia remains challenging, and suboptimal outcomes are still too frequent. There are currently limited new approved drugs without resistance. Methods: For this reason, drug repurposing presents a promising solution for identifying existing drugs with therapeutic effects for schizophrenia. In this study, we provide a workflow of signature-based drug repurposing methodology. We initially utilized a dataset from Gene Expression Omnibus which consists of RNA sequence data from blood-derived leukocyte samples from individuals with schizophrenia and control subjects, and conducted an analysis. Results: This analysis identified 1205 statistically significant differentially expressed genes, of which 150 upregulated and 150 downregulated genes were used in the CMap and L1000CDS2 tools. Then, each database generated a list of potential compounds that could reverse the disease’s signature and potentially have therapeutic effects for schizophrenia. Subsequently, the compounds associated with the disease, as identified in the research, were chemically clustered, and then their modes of action were predicted. In the last stage, we conducted a literature review to evaluate the relationship of these modes of action with the disease. Conclusions: This systematic analysis provided a list of potential drugs for schizophrenia treatment so that their efficacy can be evaluated in the wet-lab experiments, which is the next stage of drug repurposing.