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Integrative Analyses of Transcriptomes to Explore Common Molecular Effects of Antipsychotic Drugs

Abstract

There is little understanding of the underlying molecular mechanism(s) involved in the clinical efficacy of antipsychotics for schizophrenia. This study integrated schizophrenia-associated transcriptional perturbations with antipsychotic-induced gene expression profiles to detect potentially relevant therapeutic targets shared by multiple antipsychotics. Human neuronal-like cells (NT2-N) were treated for 24 h with one of the following antipsychotic drugs: amisulpride, aripiprazole, clozapine, risperidone, or vehicle controls. Drug-induced gene expression patterns were compared to schizophrenia-associated transcriptional data in post-mortem brain tissues. Genes regulated by each of four antipsychotic drugs in the reverse direction to schizophrenia were identified as potential therapeutic-relevant genes. A total of 886 genes were reversely expressed between at least one drug treatment (versus vehicle) and schizophrenia (versus healthy control), in which 218 genes were commonly regulated by all four antipsychotic drugs. The most enriched biological pathways include Wnt signaling and action potential regulation. The protein-protein interaction (PPI) networks found two main clusters having schizophrenia expression quantitative trait loci (eQTL) genes such as , and , suggesting further investigation on these genes as potential novel treatment targets.

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References
1.
Nakatani K, Sakaue H, Thompson D, Weigel R, Roth R . Identification of a human Akt3 (protein kinase B gamma) which contains the regulatory serine phosphorylation site. Biochem Biophys Res Commun. 1999; 257(3):906-10. DOI: 10.1006/bbrc.1999.0559. View

2.
King E, Davis J, Degner J . Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval. PLoS Genet. 2019; 15(12):e1008489. PMC: 6907751. DOI: 10.1371/journal.pgen.1008489. View

3.
Cai L, Huang T, Su J, Zhang X, Chen W, Zhang F . Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia. Mol Ther Nucleic Acids. 2018; 12:433-442. PMC: 6041437. DOI: 10.1016/j.omtn.2018.05.026. View

4.
Yu G, Wang L, Han Y, He Q . clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012; 16(5):284-7. PMC: 3339379. DOI: 10.1089/omi.2011.0118. View

5.
Chen B, Ma L, Paik H, Sirota M, Wei W, Chua M . Reversal of cancer gene expression correlates with drug efficacy and reveals therapeutic targets. Nat Commun. 2017; 8:16022. PMC: 5510182. DOI: 10.1038/ncomms16022. View