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RATIONALE: Lithium and valproate (VPA) are drugs used in the management of bipolar disorder. Even though they reportedly act on various pathways, the transcriptional targets relevant for disease mechanism and therapeutic effect remain unclear. Furthermore, multiple studies used lymphoblasts of bipolar patients as a cellular proxy, but it remains unclear whether peripheral cells provide a good readout for the effects of these drugs in the brain. OBJECTIVES: We used Drosophila culture cells and adult flies to analyze the transcriptional effects of lithium and VPA and define mechanistic pathways. METHODS: Transcriptional profiles were determined for Drosophila S2-cells and adult fly heads following lithium or VPA treatment. Gene ontology categories were identified using the DAVID functional annotation tool with a cut-off of p < 0.05. Significantly enriched GO terms were clustered using REVIGO and DAVID functional annotation clustering. Significance of overlap between transcript lists was determined with a Fisher's exact hypergeometric test. RESULTS: Treatment of cultured cells and adult flies with lithium and VPA induces transcriptional responses in genes with similar ontology, with as most prominent immune response, neuronal development, neuronal function, and metabolism. CONCLUSIONS: (i) Transcriptional effects of lithium and VPA in Drosophila S2 cells and heads show significant overlap. (ii) The overlap between transcriptional alterations in peripheral versus neuronal cells at the single gene level is negligible, but at the gene ontology and pathway level considerable overlap can be found. (iii) Lithium and VPA act on evolutionarily conserved pathways in Drosophila and mammalian models.

Original publication

DOI

10.1007/s00213-016-4223-z

Type

Journal article

Journal

Psychopharmacology (Berl)

Publication Date

05/2016

Volume

233

Pages

1751 - 1762

Keywords

Bipolar disorder, Drosophila, Immune, Lithium, Transcriptional profiling, Valproate, Animals, Antimanic Agents, Cell Line, Drosophila, Head, Immune System, Lithium Chloride, Metabolic Networks and Pathways, Microarray Analysis, Neurons, Transcription, Genetic, Valproic Acid