Gene Expression in the Brain from Fluoxetine‐Injected Mouse Using DNA Microarray

Abstract

Previously we have examined the effects of phencyclidine and clozapine upon the gene expression in the mouse brain. Recently, fluoxetine (Prozac) has been introduced for the therapeutic purpose as an antidepressant drug. Miledi et al. reported blockage of mouse muscle and neuronal nicotinic acetylcholine receptor by various concentrations of fluoxetine. Furthermore, Kobayashi et al. discovered that fluoxetine inhibits G protein activated inwardly rectifying G protein activated K(+) (GIRK) channels using Xenopus oocyte expression assay. From these experiments, we considered that it might be interesting to study the effects of fluoxetine on the gene expression in the mouse brain. After we have injected fluoxetine once a day into mouse for 20 days, we sacrificed mouse by decapitation and extracted RNA from mouse cerebral cortex. We used DNA microarray method for examining the gene expression in the brain. We found the downregulation of many spot signals in the fluoxetine-treated mouse, for example cholecystockinin and prostaglandin D2 synthase.

Evaluating genetic markers and neurobiochemical analytes for fluoxetine response using a panel of mouse inbred strains

“…This result is consistent with what others have found when performing global transcriptome analyses between control and antidepressant treatment groups (Bohm et al 2006; Lee et al 2010; Miller et al 2008; Takahashi et al 2006). Although other groups have found more genes that were up- or down-regulated following fluoxetine treatment, the filtering criteria we used to preprocess our microarray data are generally more stringent in comparison.…”

Corticolimbic Transcriptome Changes are State-Dependent and Region-Specific in a Rodent Model of Depression and of Antidepressant Reversal

“…Indeed, in the absence of formal control for false discovery and without independent confirmation in other cohorts and models, the microarray results will include false positives for individual genes. Rates of false discovery are difficult to assess due to the overall inter-dependence of genes in biological systems (Lee et al, 2003;Li et al, 2004) and since the observed effects of 'depression' and treatments are typically large in the numbers of genes being affected, but modest in the extent of transcript changes and statistical robustness for individual genes (see current results, and Landgrebe et al, 2002;Rausch et al, 2002;Newton et al, 2003;Drigues et al, 2003;Palotas et al, 2004;Altar et al, 2004;Wong et al, 2004;Ploski et al, 2006;Takahashi et al, 2006). In other words, controlling for false discovery would exclude large numbers of genes of interest, while maintaining medium statistical stringency will necessarily include false-positive results.…”

“…Several gene microarray studies have attempted to characterize the molecular correlates of antidepressant treatment in rodents (Landgrebe et al, 2002;Rausch et al, 2002;Newton et al, 2003;Drigues et al, 2003;Palotas et al, 2004;Altar et al, 2004;Wong et al, 2004;Ploski et al, 2006;Takahashi et al, 2006); however, differences in treatments, exposure time, and brain regions investigated have yielded no consensus. Moreover, Conti et al (2007) recently reported that changes in gene transcripts after three different antidepressant modalities in normal control rats were mostly brain region-specific.…”

Analysis of region-specific changes in gene expression upon treatment with citalopram and desipramine reveals temporal dynamics in response to antidepressant drugs at the transcriptome level

“…Studies based on microarray analyses of gene expression following antidepressant treatment usually compare region-specific gene expression changes either after different ADs treatment (Altar et al 2004; Boehm et al 2006; Conti et al 2007; Drigues et al 2003; Jungke et al 2011; Knuuttila et al 2004; Palotas et al 2004; Ploski et al 2006; Sillaber et al 2008; Takahashi et al 2006; Wong et al 2004) or in different animal models of depression (Andrus et al 2010; Bergstrom et al 2007; Orsetti et al 2008; Surget et al 2009). In our study, we broadened the perspective by evaluating the time-course of gene expression changes during antidepressant treatment.…”