Microarray analysis in hippocampus of rats treated with escitalopram in the chronic escape deficit model of depression

Currently, the biological bases of depression and the molecular mechanisms underlying antidepressant action are not completely understood. Valuable tools to better understand the pathophysiology of this disease are behavioural models of depression eventually combined with genome-wide gene expression analysis. The Chronic Escape Deficit (CED) is a validated behavioural model of depression, based on the induction of an escape deficit after exposure of rats to an unavoidable stress. This model allows to evaluate the capacity of a treatment to revert the escape deficit. The antidepressant drugs tested in CED model need to be administered for at least 3−4 weeks in order to revert the escape deficit [1,2]. In this study, we demonstrated that already after one week of treatment with Escitalopram, a widely used SSRI, 50% of the animals responded reverting the escape deficit induced. Moreover, the other 50% of treated animals did not respond also after 3−4 weeks of treatment. Since in the CED model the behavioural alteration is induced by stress application and reverted by escitalopram treatment in only half of animals, the aims of our study were two fold: (i) to investigate transcriptional changes activated by stress; (ii) to study the different gene expression pattern involved into mechanisms of the response and not response to the pharmacological treatment. To address these issues we performed a microarray experiment in the rat hippocampus using Affymetrix GeneChip Rat Exon 1.0 ST evaluating both gene-level and exon-level expression profiling on the whole genome. Total RNA extracted from hippocampus of each animal was utilized to chip a single array using the Affymetrix protocols. 20 single arrays were utilized for data analysis and divided into five replicates for each experimental group (control, stress, stress-escitalopram responders and stress escitalopram-not responders). Using two parallel analyses (gene level and exon level) of raw data files carried out in Expression Console software using iterPLIER algorithms, we identified genes and exons that were differentially regulated in each pairwise comparison considered. The exons identified in this study were examinated for their biological association to gene ontology (GO) categories using eGOn software. Moreover, all exons differentially expressed were also uploaded into Ingenuity Pathways Analysis (Ingenuity® Systems, www.ingenuity.com) in order to identify molecular pathways and functions related to stress and escitalopram response. Our results suggest that stress may exert a negative effect on gene transcription since the largest number of genes was downregulated. Moreover from our data it seems that a different pattern of gene expression exhibits between animals that respond and that did not respond to escitalopram treatment. Functional analysis of exon dataset, arising from stress protocol and escitalopram treatment, reflects interesting different biological features. More specifically, the biological functions regard both molecular and cellular functions, such as cellular growth and proliferation, gene expression and signal transduction, as well as involvement of central neurotransmission and immune response. We believe that this pharmacogenomic approach will be helpful to understand the molecular mechanisms involved in the pathogenesis of depression as well as in the response to antidepressant drugs