Molecular Psychiatry (2007) 12, 167–189 & 2007 Nature Publishing Group All rights reserved 1359-4184/07 $30.00 www.nature.com/mp ORIGINAL ARTICLE Region-specific transcriptional changes following the three treatments electro convulsive therapy, sleep deprivation and fluoxetine B Conti1, R Maier2, AM Barr1,3, MC Morale1,4,XLu1, PP Sanna1, G Bilbe2, D Hoyer2 and T Bartfai1 1Molecular and Integrative Neuroscience Department, The Harold L Dorris Neurological Research Institute, The Scripps Research Institute, La Jolla, CA, USA and 2Neuroscience Research, Novartis Institutes for Biomedical Research, Basel, Switzerland

The significant proportion of depressed patients that are resistant to monoaminergic drug therapy and the slow onset of therapeutic effects of the selective serotonin reuptake inhibitors (SSRIs)/serotonin/noradrenaline reuptake inhibitors (SNRIs) are two major reasons for the sustained search for new . In an attempt to identify common underlying mechanisms for fast- and slow-acting antidepressant modalities, we have examined the transcriptional changes in seven different regions of the rat brain induced by three clinically effective antidepressant treatments: electro convulsive therapy (ECT), sleep deprivation (SD), and fluoxetine (FLX), the most commonly used slow-onset antidepressant. Each of these antidepressant treatments was applied with the same regimen known to have clinical efficacy: 2 days of ECT (four sessions per day), 24 h of SD, and 14 days of daily treatment of FLX, respectively. Transcriptional changes were evaluated on RNA extracted from seven different brain regions using the Affymetrix rat genome microarray 230 2.0. The chip data were validated using in situ hybridization or autoradiography for selected . The major findings of the study are: 1. The transcriptional changes induced by SD, ECT and SSRI display a regionally specific distribution distinct to each treatment. 2. The fast-onset, short-lived antidepressant treatments ECT and SD evoked transcriptional changes primarily in the catecholaminergic system, whereas the slow-onset antidepressant FLX treatment evoked transcriptional changes in the serotonergic system. 3. ECT and SD affect in a similar manner the same brain regions, primarily the locus coeruleus, whereas the effects of FLX were primarily in the dorsal raphe and hypothalamus, suggesting that both different regions and pathways account for fast onset but short lasting effects as compared to slow-onset but long-lasting effects. However, the similarity between effects of ECT and SD is somewhat confounded by the fact that the two treatments appear to regulate a number of transcripts in an opposite manner. 4. Multiple transcripts (e.g. brain-derived neurotrophic factor (BDNF), serum/- regulated kinase (Sgk1)), whose level was reported to be affected by antidepressants or behavioral manipulations, were also found to be regulated by the treatments used in the present study. Several novel findings of transcriptional regulation upon one, two or all three treatments were made, for the latter we highlight homer, erg2, HSP27, the proto oncogene ret, sulfotransferase family 1A (Sult1a1), glycerol 3-phosphate dehydrogenase (GPD3), the G -coupled receptor 88 (GPR88) and a large number of expressed sequence tags (ESTs). 5. Transcripts encoding involved in in the were strongly affected by ECT and SD, but not by FLX. The novel transcripts, concomitantly regulated by several antidepressant treatments, may represent novel targets for fast onset, long-duration antidepressants. Molecular Psychiatry (2007) 12, 167–189. doi:10.1038/sj.mp.4001897; published online 10 October 2006 Keywords: electroconvulsive; sleep; fluoxetine; ; antidepressant; microarray

Correspondence: Dr T Bartfai, Molecular and Integrative Neuroscience Department, The Harold L Dorris Neurological Research Institute, The Scripps Research Institute, 10550 N Torrey Pines Rd, SR-307, La Jolla, CA 92037, USA. E-mail: [email protected] 3Current address: Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada. 4Current address: Dipartimento di Neurofarmacologia, OASI (IRCCS), Troina, Italy. Received 14 April 2006; revised 13 July 2006; accepted 5 August 2006; published online 10 October 2006 Region-specific transcriptional changes B Conti et al 168 Introduction transcriptional changes associated with antidepres- sant treatment in multiple brain regions. Several The most commonly employed pharmacological treat- studies have been recently reported including those ments of Major Depression (MD) aim at the manipula- investigating transcriptional changes following treat- tion of the monoaminergic systems.1,2 For the past 30 ment with an SSRI24,25 and lithium25,26 with respect to years, the prominent theories of mood disorders major depression and bipolar disorders,27 respec- pointed to the pathological evidence of decreased tively. monoamine levels, including the low 5-HIAA found In order to develop a strategy that would enable in suicide victims.3,4 Indeed, the monoamine oxidase identification of molecular mechanisms suitable for inhibitors since iproniazide, the tricyclic antidepres- pharmacotherapy for major depression, we compared sants (TCAs), the selective serotonin reuptake inhibi- the transcriptional changes occurring in seven rat tors (SSRIs) and the serotonin/noradrenaline reuptake brain regions implicated in control of mood and inhibitors (SNRIs) are all causing elevation of synaptic anxiety upon treatment with the two fast-onset/short- monoamine levels.5,6 Such pharmacological treat- lived antidepressant paradigms, ECT and SD and the ments are widely and successfully used in alleviating late-onset/prolonged-lasting SSRI fluoxetine (FLX). the symptoms in ca 70% of patients with MD, but The major weaknesses of today’s gene chipping remain ineffective in ca 30% of them. In addition, studies, the overwhelming amount of information that treating MD with these drugs can require several needs to be verified and organized, the experimental months of therapy but, most importantly, commonly problems of control tissues and of dissection artefacts used antidepressants have a slow onset of action.7 For were uppermost in the design and execution of the instance, the SSRIs and SNRIs require treatment for study. Further separate control groups were used for 14–21 days (or longer) before the Hamilton score each treatment. Inclusion of three different treatment returns towards normal values. Clinically, this slow paradigms permits analysis of common transcrip- onset of action can be problematic, especially as MD is tional changes and indeed resulted in a remarkable a severely debilitating disorder whose symptoms focusing/narrowing of the number of transcripts should be treated promptly once diagnosis is made requiring verification, and subsequent follow up in to reduce the high suicide risk, common in depressed behavioral models to validate the functional signifi- patients. In terms of mechanistic understanding of the cance of the transcriptional change in mood regula- current drugs’ antidepressant action, this delay in the tion. onset of clinical improvements is in strong contrast to The results show that ECT and SD cause larger-scale the rapid change in synaptic monoamine levels transcriptional changes and affect similar brain achieved upon the first or second dose of SSRIs/ regions, different from those found for SSRI treat- SNRIs. This has been interpreted as an indication of ment. Transcripts commonly regulated by two or all the need for large, multiple changes in several three treatments were identified and relevance as signaling systems in order to achieve therapeutic possible pharmacological targets for MD is discussed. effect,6,8,9 although neuroprotection and mechanisms may be targeted by antidepressants Materials and methods contributing to the slow onset of action.10–14 Thus, the existence of a large group of depressed Animals and treatment patients resistant to monoaminergic therapy and the All procedures were approved by the Institutional slow onset of therapeutic effects of the SSRIs/SNRIs Animal Care and Use Committee of the Scripps are two major reasons for the sustained search for new Research Institute and were carried out on adult male antidepressant mechanisms. In contrast to drugs Sprague–Dawley rats (250–300 g). Animals were affecting the monoaminergic system, sleep depriva- housed two per cage, food and water were ad libitum tion (SD) and electro convulsive therapy (ECT) are and the light/dark cycle was of 12/12 h with light on two clinically well-documented, robust, fast-acting at 0700 hours. The experimental design is summar- methods for treatment of severely depressed pa- ized in Figure 1. tients.15–20 Both treatments require hospitalization For electroconvulsive shock (ECT) animals received and have been extensively used over the past century. four shock applications daily (70 pulses/s; pulse However, the molecular and cellular mechanisms width of 0.5 ms; current of 90 mA; shock duration underlying their antidepressant effects are poorly up to 8 s delivered with a 1 h time interval between understood. Many studies have examined the effects applications) for 2 days and were killed 1 h after final of ECT on the CSF or serum level of selected markers treatment. Only animals exhibiting full tonic/clonic including neurotransmitters, neuropeptide and hor- seizure after each application were utilized. The mones.20–23 Similar work has been carried out on SD. control group underwent the same manipulation of Yet, no molecular and/or cellular mechanism has the ECT group with electrode application at same been identified that satisfactorily explains the rapid, time and time intervals over 2 days, but did not although transient, antidepressant effects of ECT receive electric shock. Instead, they received four and/or SD. sham applications per day for 2 days. Microarray analysis of presents an For SD, animals were kept awake by investigators opportunity to conduct an unbiased search for the by gentle disturbances during a 24 h cycle until they

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 169

Figure 1 Schematic representation of experimental design. (a) The study was carried out using six groups of nine rats/group treated with ECT, SD and FLX; each treatment group was paralleled by its specific control. Following dissection and RNA extraction, samples were pooled into groups of three and used for microarray experiments in triplicate. (b) Representation of the brain regions dissected and (c) of the analysis of the microarray data. Abbreviations: E, electroconvulsive therapy; S, sleep deprivation; F, fluoxetine. PFC, prefrontal cortex; FC, frontal cortex; Amy, amygdala; Hypo, hypothalamus; Hipp, hippocampus; DR, dorsal raphe; LC, locus coeruleus.

were killed. The regular light/dark cycle was not facilitate the transfer of the dissected tissue was used interrupted during experimental procedure, a dim red to collect the locus coeruleus (LC) and a similarly light was used to facilitate experimenters work during constructed 14-gauge needle for the dorsal raphe dark. Control animals were kept undisturbed in a nucleus (DRN). Tissues were immediately frozen and separate room with same light/dark cycle of SD group. stored at À801C until further analysis. For FLXtreatment, animals received daily intraper- itoneal injections of a 10 mg/kg FLX HCl solution for Preparation of RNA and chipping 14 days and were killed 1 h after the last treatment. Total RNA was isolated and purified individually Control animals underwent the same regimen of daily from the seven dissected brain areas obtained from a intraperitoneal injection of saline (phosphate-buf- total of nine animals per condition using the Quiagen fered saline (PBS)) solution for 14 days and were RNAeasy purification kit (total of 378 samples). killed 1 h after the last injection. Chipping analysis for each brain region and condition was performed in triplicate on pools of RNA from Dissections three animals per chipping sample. Specifically, were always dissected by the same investiga- pools of RNA were generated for each condition and tor, using a wire brain slicer (Research Instruments & brain area by randomly combining three equal MFG, Corvallis, OR, USA) with the assistance of a amounts of total RNA isolated from individual brain atlas28 (Figure 1b). The frontal and medial animals. This resulted in a total of 126 RNA pools, prefrontal cortices, the amygdaloid complex, the which were subjected to microarray profiling (Figure 1a). hippocampus (Hipp) and hypothalamus (Hypo) were In total, 5 mg total RNA was used for cDNA dissected free-handedly using established anatomical synthesis and cRNA amplification and chips were landmarks.28 A 16-gauge needle constructed from a hybridized to Rat Genome 230 2.0 arrays (Affymetrix) spinal tap needle and equipped with a plunger to according to standard Affymetrix protocols (Affy-

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 170 metrix Expression Analysis Technical Manual, http:// supplemented with 0.25% (v/v) acetic anhydride for www.affymetrix.com/support/technical/manuals.affx). 10 min. After washing two times for 2 min in 2 Â SSC Data were first processed with MAS5 (Affymetrix) by (0.3 M NaCl, 0.03 M sodium citrate pH 7), the sections global scaling to a target intensity of 150 for quality were dehydrated in 50, 70, 95 and 100% ethanol, air assessment. From a total of 126 microarrays, 121 met dried and used the same day for hybridization. our quality criteria and the data were used for further Antisense and sense [35S]UTP-labeled RNA probes analysis. were synthesized by in vitro transcription using T7 or SP6 RNA polymerase ([35S]UTP-specific activity Evaluation of the chipping data, algorithms and cut offs 1000 Ci/mmol; Amersham, UK). 35S-labeled antisense The analysis of differential gene expression was riboprobe detected mRNA, hybridizing adjacent sec- performed using Robust Multichip Average (RMA)- tions with the corresponding [35S]-labeled sense processed data.29 A combined expression value for riboprobe and did not reveal any mRNA signal and each probe set was calculated as the 66th percentile of served as a control. The riboprobes were purified by the respective expression values from the three data using G-50 Sephadex Quick spin columns (Roche, sets which were available for each condition. This Basel, Switzerland), diluted to 107 c.p.m./ml in strategy was chosen to obtain a data set that is more hybridization buffer (50% formamide, 10% dextran robust, less sensitive to outliers and subsequently sulfate, 1 Â Denhardt’s solution, 10 mM Tris-HCl pH provides a better estimate of differential expression. 8, 0.3 M NaCl, 2 mM EDTA, 500 mg/ml t-RNA) and then In the few cases where only two data sets were were applied to the tissue sections and overlaid with available, the mean value was used instead. coverslips. Slides were hybridized in an incubator at For finding gene-expression differences between 551C for 16–22 h. After hybridization, the slides were conditions, fold changes were calculated by dividing cooled down in 4 Â SSC and the coverslips were the expression value for the treated by the value of the removed, washed again four times for 4 min in 4 Â respective control condition. Fold-change values < 1 SSC. The sections were treated with RNase A (20 mg/ were inversed and negated. Therefore, positive values ml) for 30 min at 301C, washed in decreasingly indicated a higher, whereas negative values indicated stringent solutions of SSC (down to 0.1 Â SSC at a reduced expression in the treated group. 651C for 30 min), dehydrated in 70, 95 and 100% The data were subsequently filtered and patterns ethanol and air dried. Slides were exposed to Biomax determined according to the following criteria: (1) MR film (Eastman Kodak Company, Rochester, NY, absolute fold change values were required to be X1.8; USA) at 41C, 1 day for Cplx2, 3 days for Ntrk2, 2 days (2) expression values in at least one of the compared for BDNF and Camk2a. conditions (treated or control) were required to be 3 above the estimated background value of 70; (3) the Autoradiography of [ H]MPPI binding to 5-HT1A set criteria had to be met in at least one of the seven receptor sites brain areas in order for a given probe set (gene) to [3H]MPPI-binding sites ([3H]4-(20-methoxyphenyl)-1- remain listed. [20-[N-(200-pyridinyl)-iodobenzamido] ethyl] pipera- zine, NEN Life Science Products, Boston, MA, USA) In situ hybridization (ISH) analysis were determined by an autoradiographic assay as Six groups of brains were processed: sleep-deprived described previously.30 The assay was performed in rats (SD), control for SD, electroshock (ECT), control 10-mm brain sections of rats subjected to the three for ECT, FLX-treated rats, and control for FLX (saline). different antidepressant treatments. The brain sec- The brains from three controls and three treated tions were pre-incubated for 30 min at room tempera- animals were removed, frozen in isopentane and ture in assay buffer (170 mM Tris-HCl, pH 7.6). The stored at À801C. Rat brains were then sent by courier slides were then incubated with [3H]MPPI (10 nM in to NIBR, Basel, where they were processed upon assay buffer) for 90 min at room temperature. Non- arrival. Coronal tissue sections were cut in 10 mm- specific binding was defined using 10 mM thick slices with a microtome-cryostat and were thaw- WAY100,635 (Anawa, Wangen, Switzerland). The mounted on silane-coated microscope slides. slides were then washed twice with assay buffer at

In situ probes were generated from cDNA fragments 41C and rinsed with cold double distilled H2O of the respective genes that were amplified by PCR (ddH2O). After air blow-drying, the slides were from rat whole brain cDNA and cloned into pGEM-T exposed to 3H Hyperfilm (Amersham, Arlington Easy vector (Promega, Madison, WI, USA). Probes Heights, IL, USA) for 4–8 weeks. 125I microscales were generated for Cplx2 (NM_053878, bp 456–713), (Amersham) were exposed with each slide film to Ntrk2 (NM_012731, bp 2671–3135), BDNF (NM_012513, calibrate the absorbance in the fmol/mg tissue bp 249–580) and Camk2a (NM_012920, bp 962–1492) equivalent. and confirmed by sequencing. ISH was performed using sections fixed in 4% Data and statistical analysis (w/v) ice-cold paraformaldehyde for 5 min and washed Sections were finally counterstained with 0.5% four times for 1 min in 1 Â PBS at room temperature. Cresyl violet and nuclei localized according to The slides were then incubated for 2 min in Paxinos and Watson.28 Data from hybridization 0.1 M triethanolamine pH 8 and in the same buffer signals were analyzed by optic densitometry of

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 171 Biomax MR films using a computerized image ana- 1.8-fold higher or lower than controls, with the lysis system (MCID, Imaging Research, St Catherines, exception of a few selected gene transcripts showing Ontario, Canada). wide variation of regulation throughout brain regions and across treatments. Changes in the expression levels of BDNF tran- Results scripts found by microarray analysis were confirmed The Rat Genome 230 2.0 chip utilized in our studies by quantitative ISH that was extended to 19 brain provides information on over 31 000 probe sets, regions for each antidepressant treatment (see which combined with the number of treatments Figure 2). Similarly, the expression profile of the investigated (three plus respective controls) and the neurotropin receptor NTRK2 was confirmed by ISH seven brain regions analyzed results in a set of and the quantification was extended to 21 brain information equivalent to over 3.7 million transcript regions (Figure 3). The levels of serotonin 1A (5-HT1A) levels. This provided the opportunity to search for receptors determined by receptor autoradiography in transcripts/genes of interest as encoding possible new six brain regions were not affected by any of the three antidepressant drug targets and to analyze the extent treatments (Figure 4). of the region-specific action of each different anti- depressant treatment. Number of transcriptional changes caused by ECT, SD and FLX treatment Quality and validation of the gene-chipping data All three antidepressant treatments resulted in both Seven brain areas were dissected, RNA extracted and increases and decreases in the levels of a large used for chipping: prefrontal cortex (PFC), frontal number of transcripts (Figure 5a). The treatment cortex (FC), amygdala (Amy), hippocampus (Hipp), causing overall the largest cumulative number of hypothalamus (Hypo), locus coeruleus (LC) and changes in all brain regions was ECT (3285 genes dorsal raphe (DR) (Figure 1b). Reproducibility was affected) followed by FLX (520 genes affected) and SD facilitated by dissecting each region from the same (440 genes affected). ECT induced the largest number selected brain slice obtained with a custom-made of changes in all brain regions with the exception of brain slicer. All dissections were performed by the the Hypo where the highest number of changes was same investigator and were straightforward for PFC, induced by FLX (294 by FLX, 148 by ECT and 73 by FC Amy, Hippo and Hypo. The presence of mRNA for SD). Each treatment induced a larger number of the specific catecholaminergic marker dopamine beta upregulated (Figure 5b) than downregulated tran- hydroxylase (DBH) in all LC samples was used to scripts (Figure 5c) with the exception of FLX in the demonstrate that LC dissections were consistent and Hypo (ECT: 2544 up and 741 down; FLX: 186 up and reproducible (not shown). Similarly, the presence of 336 down; SD: 281 up and 159 down). tryptophan beta hydroxylase (TPH) mRNA was used as an indication for the quality of DRN dissections Brain areas preferentially affected by ECT, SD and FLX (not shown). treatment Chip hybridization reactions were performed uti- We evaluated the relative efficacy of each treatment in lizing three pooled tissue samples from a total of nine inducing changes in each brain region. To do so, we animals for each condition, a strategy that reduced compared the percentage of genes affected relative to the number of chips to be used and minimized the the total number of genes modulated in all regions possibility that differences observed could reflect the (Table 1). Each treatment affects each brain area quality of dissections rather than actual changes differently. As summarized in Table 1, ECT affects (Figure 1). To minimize differences that could arise the largest number of transcripts in the LC and the from specific manipulation of the animals, each lowest number of transcripts in the DRN, with experimental group was compared to its own specific the following order: LC > FC > PFC > Amy > Hipp > control as specified in the Materials and methods Hypo > DRN. SD was found to induce most changes section. For electroconvulsive shock, animals that did in LC and least in FC: LC > Hypo > Hipp > PFC > not show seizures upon ECT were not used for DRN > Amy > FC. FLX mostly affected Hypo and analysis. For the 121 microarrays analyzed, the DRN, but had little effect on PFC: Hypo > DRN > A- average 30/50 glyceraldehydes 3-phosphate dehydro- my > LC > FC > Hipp > PFC. genase (GAPDH) ratio was 1.1570.13 and 5772.5% Interesting differences were found by comparing of the probe sets (genes) indicated as presented by the percentage of transcript changes by the fast-onset MAS5. antidepressant treatments SD and ECT and the slow- Evaluation of the expression profile of different onset antidepressant FLX. Specifically, SD and ECT probe sets for the same transcripts across the study appear similarly effective in producing changes in the was carried out on gene chip data filtered for a ‘cutoff’ LC compared to FLX (SD, ECT, FLX: 44, 31 and 8%, of 1.3-fold change above or below control. The respectively). In contrast, FLX appeared more effec- analysis revealed a high degree of reproducibility. In tive than SD and ECT in inducing changes in the DRN total, over 3900 genes were affected by one or more (FLX, SD, ECT: 14, 7 and 3%, respectively) and in treatments. Thus, subsequent analysis of the chipping Hypo (FLX, SD, ECT: 56, 16 and 4%, respectively). data was carried out using the higher cutoff criteria of By contrast, FLX and SD were poorly effective in FC

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 172

Figure 2 Region-specific changes in BDNF transcript. (a) Representative autoradiographic photoemulsion of in situ hybridization for BDNF on sections comparing containing prefrontal cortex (PFC) and hippocampus (Hipp) from animals under different treatment and controls as indicated. (b, c and d) Histograms of quantification of BDNF mRNA in 19 different brain regions. Abbreviations: AO, anterior olfactory nucleus; PFC, prefrontal cortex; Pir2, piriform cortex, layer 2; Cl, claustrum; Den, dorsal endopiriform nucleus; PVP, paraventricular thalamic nucleus, posterior part; GrDG, granular layer of the dentate gyrus; PoDG, polymorph layer of the dentate gyrus; CA1py, CA2py, CA3py, pyriform layer of fields CA1-3 of Ammon’s horn; VMH, ventromedial hypothalamic nucleus; Me, medial amygdaloid nucleus; BL þ LA, basolateral þ lateral amygdaloid nuclei; PMC0 þ AHi, postero medial cortical amygdaloid nucleus and amygdalo hippocampal area; DR, dorsal raphe nucleus; Ent II, entorhinal cortex, layer II; GrCb, granule cell layer of the cerebellum. *P < 0.05, **P < 0.01, ***P < 0.001.

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 173

Figure 3 Region-specific changes in Ntrk2 transcript. (a) Representative autoradiographic photoemulsion of ISH for Ntrk2 on sections comparing containing prefrontal cortex (PFC), hippocampus (Hipp) and amygdala (Amy) from animals under different treatment and controls as indicated. (b, c and d) Histograms of quantification of Ntrk2 mRNA in 21 different brain regions. Abbreviations: OB, olfactory bulb; PreFr, prefrontal cortex; AO, anterior olfactory nucleus; Pir, piriform cortex; Cl, claustrum; Den, dorsal endopiriform nucleus; LS, lateral septum; MPO, medial preoptic nucleus; HDB þ MCPO, nucleus of the horizontal limb of the diagonal band þ magnocellular preoptic nucleus; AHypo, anterior hypothalamus; ATh, anterior thalamus; M þ Vth, medial þ ventral thalamus; MHypo, medial hypothalamus; CA1 þ 2 þ 3, fields CA1-3 of Ammon’s horn; GrDG, granular layer of the dentate gyrus; AHi þ PMCo, amygdalo hippocampal area and postero medial cortical amygdaloid nucleus; DR, dorsal raphe nucleus; LC, locus coeruleus; GrCb, granule cell layer of the cerebellum. **P < 0.01, ***P < 0.001.

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 174

Figure 5 Regional distribution of transcripts affected by each treatment. (a) Histogram showing the total number of transcripts whose level was changed more than 1.8-fold to the control by ECT, SD and FLX in the different brain regions investigated (ordered by anatomical rostral to caudal). (b) Number of transcripts upregulated and (c) downregulated.

in Table 2. The brain regions most affected by multiple transcriptional changes were, in decreasing order, LC, Hypo, Hipp, DRN, PFC, Amy and FC. The highest total number of changes was induced by the Figure 4 Measurement of 5-HT1A receptor level. Histo- two fast-acting antidepressant treatments, ECT and SD grams showing the autoradiographic quantification of the (136). Similarly, the number of transcripts decreased 5-HT1A receptor binding following (a) ECS, (b) SD and (c) to similar values when compared to transcript FLX, as indicated measured in the , the fields changes induced by FLX (50 for ECT/FLX and 57 for CA-1 and the CA1-CA3 of the hippocampus, the dentate gyrus (DG), the dorsal (DR) and the median (MeR) raphe SD/FLX). nuclei. In the LC, 83 transcripts were co-regulated by ECT and SD, many more than FLX. A similar pattern emerges in PFC and Hippo. In the DRN, Hypo or Amy, compared to ECT (ECT, SD, FLX: 17, 3 and 3%, FLX shows more co-regulation with either of the two respectively). other treatments. Of the total of 193 genes affected by two treatments, 24 or 12% were regulated in at least Transcripts commonly affected by two antidepressant two brain regions. Remarkably, with the exception of treatments the acidic nuclear phosphoprotein 32 (Anp32a), A summary of the number of changes of the levels of which was mildly upregulated by ECT and FLX in transcripts in two out of three treatments is presented the DRN and downregulated in PFC, the other 23

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 175 Table 1 Percentage of region-specific changes induced by to several treatments reduces dramatically the num- each treatment ber of transcripts to be validated. Of these, 13 (about 70%) occurred in the Hypo, three in LC, two in DRN ECS SD FLX and one in Amy, whereas no changes common to the three treatments were found in PFC, FC and HIPP. LC 31 LC 44 Hypo 57 However, when taking into account changes with a FC 18 Hypo 17 DRN 14 cutoff of 1.5-fold in one of the treatments, it was PFC 16 Hipp 17 Amy 13 found that serum/glucocorticoid regulated kinase Amy 14 PFC 10 LC 8 Hipp 12 DRN 7 FC 3 (Sgk1) was regulated by all treatments in LC and Hypo 5 Amy 3 Hipp 3 DRN, sulfotransferase family 1A (Sult1a1) in LC and DRN 4 FC 3 PFC 2 FC, and glycerol 3-phosphate dehydrogenase (GPD3) was upregulated in all regions by all three treatments. Abbreviations: AMY, amygdala; DRN, dorsal raphe; ECS, Further, we identified -coupled receptor 88 electroconvulsive shock; FC, frontal cortex; FLX, fluoxetine; (GPR88), an orphan GPCR, to be co-regulated by all Hipp, hippocampus; Hypo, hypothalamus; SD, sleep depri- three treatment modalities in the Hypo. vation; LC, locus coeruleus; PFC, prefrontal cortex. Percentage of genes affected by each treatment in each region investigated (sorted by descending values). Discussion The present study compared the changes in gene Table 2 Number of changes induced by multiple treatments expression profiles induced in rat brain by three different, clinically proven antidepressant treatments: PFC FC Amy Hypo Hipp DRN LC Total electroconvulsive shock (ECT), SD and the SSRI FLX. These treatments differ in the onset of their therapeu- ESF 0 0 1 13 0 2 3 19 tic action which is fast in ECT and SD (2 days and 1 ES 19 3 5 23 22 8 83 163 day, respectively) compared to FLX (14–21 days). EF 1 1 5 21 2 7 13 50 ECT, SD and FLX treatments were employed in rats SF 1 1 2 41 5 3 4 57 with the same therapeutic regimen used in Total 21 5 13 98 29 20 103 289 patients. The rationale for choosing FLX as the SSRI studied was the large amount of published data Abbreviations: Amy, amygdala; DRN, dorsal raphe nucleus; collected with this SSRI both clinically and pre- 31–33 ES, electroconvulsive shock; F, fluoxetine; FC, frontal clinically that would increase our ability to make cortex; Hipp, hippocampus; Hypo, hypothalamus; LC, locus comparisons with other SSRI-affected parameters. coeruleus; S, sleep deprivation. The brain regions investigated were selected based Number of transcripts affected by two or three treatments in on their presumed involvement in regulating mood each specific brain region investigated. states, fear and anxiety. There are no ‘control’ regions Total values for brain region and for treatments are in bold. in the sense that none of the treatments used was known to not affect specifically one brain region. Including a peripheral tissue in the study was not transcripts were all upregulated by both ECT and SD. considered to be meaningful to the study. Among those transcripts that were upregulated are those encoding the brain-derived neurotrophic factor Number of transcripts affected by single and multiple (BDNF), the neuronal immediate early gene homer treatments per brain region (Homer1), the early growth response 2 gene (Egr2), the The investigation of the comprehensive gene expres- activity and neurotransmitter-induced early gene sion profile in several different brain regions pro- protein 4 (Ania-4), the heat shock 27 kDa protein 1 vided the opportunity to use the microarray data as an (Hspb1) and the ret proto-oncogene (Ret). These indicator for the biological activity of each brain transcripts were all upregulated by ECT and SD, but region in response to each treatment. This approach not by FLX in two brain regions: PFC and HIPP (Table allows the ‘visualization’ of the brain regions affected 3). This list represents 25% of the genes regulated by by the treatment, information especially interesting two treatments in PFC. for ECT and SD, whose antidepressant mechanisms of A complete list of gene transcripts affected in two action are far less characterized than that of FLX. The out of three treatments is presented in Table 4. experimental model utilized was aimed at reducing the number of artefacts that could confound the Transcripts regulated by all three treatments results. The study was carried out by analyzing A summary of the number of changes in transcrip- triplicates of pools of tissues from three animals per tional levels evoked by all three treatments is treatment and by adopting a specific control for each presented in Table 2; the complete list is presented treatment, thus minimizing a possible confound by in Table 5. In total, only 19 gene transcripts were stress-dependent specific manipulation of the ani- found to be up- or downregulated X1.8-fold by all mals. Further, analysis with a 1.8-fold cutoff above or three antidepressant treatments in at least one brain below control values, similar to other microarray region. Thus, the strategy to identify common changes studies,34–37 greatly limited the number of genes

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 176 Table 3 Functional cluster of transcripts affected by ECT and SD

Area ECT SD FLX

Ania-4, activity and neurotransmitter-induced early gene PFC 2.7 1.8 À1.0 protein 4 (NM_021584) Hipp 2.6 1.9 1.1

BDNF, brain-derived neurotrophic factor (NM_012513) PFC 7.1 2.6 1.0 Hipp 6.0 1.9 1.1 Amy 7.0 1.8 1.1

Egr2, early growth response 2 (NM_053633) PFC 4.8 2.3 À1.1 Hipp 11.1 2.7 À1.2

Homer1, homer, neuronal immediate early gene, 1 Amy 6.9 2.0 1.4 (AB003726) PFC 2.9 3.3 1.4 Hipp 6.1 4.1 1.0

Hspb1, heat shock 27 kDa protein 1 (NM_031970) PFC 21.2 2.1 1.0 Hipp 14.3 1.9 1.1

Ret, ret proto-oncogene (AI639318) PFC 2.8 2.0 À1.0 Hipp 2.8 1.9 1.2

Abbreviations: ECT, electroconvulsive shock therapy; FLX, fluoxetine; Hipp, hippocampus; PFC, prefrontal cortex; SD, sleep deprivation. List of the functional cluster of transcripts and relative affected by ECT and SD in the PFC and Hipp, but unaffected by fluoxetine. RefSeq and Genbank accession numbers are given in parenthesis, respectively. Numbers indicate fold change; those above the cutoff of 1.8 are in bold.

considered as differentially expressed and strongly evaluated at the same time points. However, as amply increased the stringency of the analysis. Combined discussed, the time points were chosen to mimic with some regional-specific markers, evaluation of the clinical conditions. results obtained with independent probes for the Despite such limitations, the data obtained collec- same transcripts across the study as well as indepen- tively reveal a very peculiar scenario demonstrating dent ISH validation for selected transcripts served to that ECT, SD and FLX induce changes in all seven validate the data set. Nevertheless, we are aware that brain regions investigated, albeit with a very distinct this study presents limitations that need to be pattern. Thus, while common molecular mechanisms considered for critical interpretation of the results. may exist for all these treatments, important differ- One limitation is that the three antidepressant ences were noticed. Most interesting is the finding treatments were used on naı¨ve rather than ‘depressed’ that treatment with the two fast-acting antidepres- animals. Thus, it was not possible to identify and sants, ECT and SD, is accompanied by large transcrip- eventually eliminate non-responders from the study. tional changes in the LC, a region barely affected by In addition, although equivalent treatment modalities chronic FLX treatment, which instead caused a large were applied to the animals in this study, transcrip- number of changes in the Hypo and the DRN. By tional changes caused by clinically effective antide- contrast, ECT and SD had little effects on the DRN. pressants may differ between patients and rodents. An important correlate to the stress of ECT and SD Thus, for the functional validation of some transcripts treatments is the large increase in CRF transcripts in identified as possible drug targets, further studies will the LC by ECT and SD, whereas the 14-day FLX be necessary to assess the effect of transcriptional downregulates the mRNA levels for CRF in the LC. regulation in one or more rodent models of depres- Thus, ECT and SD, the two openly stressful sion.38–43 Another apparent limitation is that tran- treatments, appear to be mostly effective on noradre- scriptional profiles for the different treatments were nergic , but poorly on serotonergic ones, compared only at the time points corresponding to which in turn are expectedly targeted by FLX. clinical efficacy, which differed for each treatment Although this finding is not novel, to the best of our being 2 days for ECT, 1 day for SD and 14 days for knowledge, it was never demonstrated in a compara- FLX. Thus, a comparative analysis of transcriptional tive study investigating several brain regions. Such an changes induced at the same time points for all analysis clearly indicates that fast-onset, but short- treatments is missing. This may be particularly lived, antidepressant action is associated with ‘acti- interesting for FLX, as its effects evaluated at 2 weeks vation’ of brain regions containing noradrenergic distance from ECS and SD may be different if neurons, whereas targeting of serotonergic neurons

Molecular Psychiatry Table 4 List of transcripts affected by two or three treatments

Probe ID Gene description GenBank no. Area Fold change

ECS SD FLX

1367577_at Hspb1, heat shock 27 kDa protein 1 NM_031970 PFC 21.2 2.1 1.0 1383486_at EST, AA926109 AA926109 PFC 13.9 2.5 1.0 1368677_at BDNF, brain-derived neurotrophic factor NM_012513 PFC 7.1 2.6 1.0 1375043_at c-fos, c-fos oncogene BF415939 PFC 5.9 À2.0 À1.2 1387306_a_at Egr2, early growth response 2, NM_053633, 20p11 NM_053633 PFC 4.8 2.3 À1.1 1389467_at EST, BM391248 BM391248 PFC 4.5 2.1 À1.1 1390391_at EST, BF283381 BF283381 PFC 4.2 1.8 1.1 1386995_at Btg2, B-cell translocation gene 2 BI288701 PFC 3.7 À2.9 À1.3 1397164_at EST, AI175779 AI175779 PFC 3.2 1.9 À1.0 1370454_at Homer1, homer, neuronal immediate early gene, 1 AB003726 PFC 2.9 3.3 1.4 1370989_at Ret, ret proto-oncogene AI639318 PFC 2.8 2.0 À1.0 1387276_at Ania-4, activity and neurotransmitter-induced early gene protein 4 NM_021584 PFC 2.7 1.8 À1.0 1367795_at Ifrd1, interferon-related developmental regulator 1 NM_019242 PFC 2.4 1.8 1.1 1393119_at EST, BM388725 BM388725 PFC 2.4 2.4 1.1 1368353_at Gfap, glial fibrillary acidic protein NM_017009 PFC 2.0 1.8 1.0 1371363_at Gpd3, glycerol 3-phosphate dehydrogenase BI277042 PFC 1.8 1.9 1.7 1369908_at Crhbp, corticotrophin-releasing hormone-binding protein NM_139183 PFC 1.8 2.3 1.0 1380329_at EST, AI717253 AI717253 PFC À1.9 À1.8 À1.4 1370991_at Cml3, camello-like 3 AF187814 PFC À2.1 À3.5 À1.0 1368398_at Cacna1h, Ca channel, voltage-dependent, T type, alpha 1H subunit NM_031601 PFC À1.9 1.1 À2.1 Conti B changes transcriptional Region-specific 1369063_at Anp32a, acidic nuclear phosphoprotein 32 family, member A NM_012903 PFC À1.4 3.4 À2.4 tal et 1373302_at EST, BM387041 FC 2.4 1.8 1.4 1388271_at Mt1a, Metallothionein BM383531 FC 3.6 1.8 1.4 1370019_at Sult1a1, sulfotransferase family 1A, phenol-preferring, member 1 AF394783 FC À2.5 1.8 1.7 1375043_at c-fos, c-fos oncogene BF415939 FC 9.6 À1.3 À1.9 1371363_at Gpd3, glycerol 3-phosphate dehydrogenase BI277042 FC 1.7 2.0 2.0

1371363_at Gpd3, glycerol 3-phosphate dehydrogenase BI277042 Amy 1.8 2.1 2.3 1377008_at EST, AA926109 AA926109 Amy 29.4 1.8 1.2 1383486_at BDNF, brain-derived neurotrophic factor NM_012513 Amy 7.0 1.8 1.1 1370454_at Homer1, homer, neuronal immediate early gene, 1 AB003726 Amy 6.9 2.0 1.4 1393119_at EST, BM388725 BM388725 Amy 2.6 1.8 1.1 1396101_at Stc1, stanniocalcin 1 BF552244 Amy 3.0 À1.1 1.9 1374626_at Similar to leucine-rich alpha-2-glycoprotein (LOC367455) BG371585 Amy 2.2 1.1 1.8 1368942_at Hes5, hairy and enhancer of split 5 NM_024383 Amy À2.5 À1.0 À1.8 1383161_a_at AI008646 AI008646 Amy À1.8 1.5 À1.9 1381920_at AI502118 AI502118 Amy 1.1 À2.2 À2.1

oeua Psychiatry Molecular 1392791_at EST, AA964492 AA964492 Hypo 27.5 À3.8 À5.5 1387442_at Egr4, early growth response 4 NM_019137 Hypo 10.6 À1.8 À2.0 1369750_at Tshb, thyroid-stimulating hormone, beta subunit M10902 Hypo 4.2 À2.7 2.4 1370074_at Baiap2, brain-specific angiogenesis inhibitor 1-associated protein 2 NM_057196 Hypo 2.6 ÀÀ1.5 À2.3 177 oeua Psychiatry Molecular 178

Table 4 Continued

Probe ID Gene description GenBank no. Area Fold change

ECS SD FLX

1369560_at Gpd3, glycerol 3-phosphate dehydrogenase NM_022215 Hypo 2.4 2.4 3.4 1377823_at EST, AW531363 AW531363 Hypo 2.4 1.9 1.9 1373081_at Baiap2, brain-specific angiogenesis inhibitor 1-associated protein 2 AI105000 Hypo 2.0 À1.8 À2.1 1387356_at Wfs1, Wolfram syndrome 1 NM_031823 Hypo 1.8 À2.0 À4.3 1384392_at Cyp26b1, cytochrome P450, family 26, subfamily b, polypeptide 1 BF397093 Hypo À1.8 À2.1 À2.1 1367700_at Fmod, fibromodulin NM_080698 Hypo À1.8 À1.9 À2.2 1367648_at Igfbp2, -like growth factor-binding protein 2 NM_013122 Hypo À2.0 À2.3 À2.7 1367571_a_at Igf2, insulin-like growth factor 2 NM_031511 Hypo À2.3 À2.2 À2.0 changes transcriptional Region-specific 1390532_at EST, AI013778 AI013778 Hypo À2.4 À1.8 À2.4 1368321_at Egr1, early growth response 1 NM_012551 Hypo 6.0 À2.1 À1.5 1369659_at Cga, glycoprotein hormones, alpha subunit NM_053918 Hypo 4.4 À2.1 1.2 1380306_at EST, AW435415 AW435415 Hypo 2.1 2.9 À1.1 1391680_at EST, BF410646 BF410646 Hypo 1.8 1.8 1.4 1392613_at EST, AA942745 AA942745 Hypo 1.8 2.2 À1.1 Conti B 1387241_at GPR88, G protein-coupled receptor 88 NM_031696 Hypo À1.8 À2.1 1.5 1379270_at EST, AI717163 AI717163 Hypo À1.8 À1.9 À1.2 1388116_at Col1a1, collagen, type 1, alpha 1 BI285575 Hypo À2.0 À1.9 À1.6 al et 1370959_at Col3a1, collagen, type III, alpha 1 BI275716 Hypo À2.0 À1.9 À1.3 1370544_at Eml2, echinoderm microtubule-associated protein like 2 AF335571 Hypo À2.3 À2.3 À1.2 1370454_at Homer1, homer, neuronal immediate early gene, 1 AB003726 Hypo 9.3 À1.3 À4.7 1387068_at Arc, activity-regulated cytoskeletal-associated protein NM_019361 Hypo 9.3 À1.2 À3.2 1368124_at Cpg21, MAP-kinase phosphatase (cpg21) NM_133578 Hypo 4.0 1.1 À2.0 1368527_at Ptgs2, prostaglandin-endoperoxide synthase 2 U03389 Hypo 2.7 À1.1 À2.5 1397185_at EST, BE102060 BE102060 Hypo 2.6 1.4 À3.8 1369067_at Nr4a3, nuclear receptor subfamily 4, group A, member 3 NM_031628 Hypo 2.1 1.1 À4.1 1373152_at Similar to RIKEN cDNA 2310046G15 AI177099 Hypo 1.9 1.0 À1.9 1391809_at BE106814 BE106814 Hypo À1.8 1.7 1.9 1396542_at BE106815 BE106815 Hypo À1.1 À1.8 À2.0 1384944_at BE106816 BE106816 Hypo À1.3 À1.8 À3.2 1369048_at Gabrd, gamma-aminobutyric acid A receptor, delta NM_017289 Hypo À1.3 À1.8 À1.9 1378362_at Similar to Gliacolin (LOC307144) BG374818 Hypo 1.1 À1.8 À2.2 1384093_at EST, AW523562 AW523562 Hypo À1.1 À1.8 À2.0 1391948_at EST, BM390227 BM390227 Hypo 1.1 À1.9 À3.3 1393708_at BE115766 BE115767 Hypo À1.2 À1.9 À10.6 1390999_at EST, BE108409 BE108409 Hypo À1.3 À1.9 À1.9 1369731_at Membrane-associated guanylate kinase-interacting protein AF102854 Hypo 1.2 À1.9 À6.0 1377492_at EST, BM387395 BM387395 Hypo 1.3 À1.9 À4.6 1393710_at Similar to telencephalin precursor (LOC313785) BE102418 Hypo 1.2 À2.0 À4.3 1370211_at Nrgn, neurogranin BE106940 Hypo À1.0 À2.0 À2.9 1394406_at EST, AW529108 AW529108 Hypo À1.3 À2.0 À4.0 1369688_s_at Ptk2b, protein tyrosine kinase 2 beta U69109 Hypo 1.3 À2.0 À6.1 1387032_at Cck, cholecystokinin NM_012829 Hypo À1.0 À2.1 À3.5 1390649_at znT3, solute carrier family 30 protein AW520784 Hypo 1.2 À2.1 À2.8 Table 4 Continued

Probe ID Gene description GenBank no. Area Fold change

ECS SD FLX

1387881_at Kcnv1, , subfamily V, member 1 BF391696 Hypo 1.0 À2.1 À2.9 1384869_at Similar to (3B446) (LOC289440) AW531594 Hypo À1.0 À2.1 À2.0 1369089_at Prkcc, protein kinase C, gamma NM_012628 Hypo À1.2 À2.2 À3.6 1397721_at EST, AW531134 AW531134 Hypo À1.3 À2.2 À1.8 1377828_at Similar to 11 ORF 25 (LOC311287) BG672090 Hypo À1.1 À2.3 À4.9 1386035_at EST, BG381661 BG381661 Hypo 1.0 À2.3 À8.3 1376328_at EST, BI278776 BI278776 Hypo À1.1 À2.4 À4.8 1368462_at Itpka, inositol 1,4,5-triphosphate 3-kinase, NM_031045 Hypo À1.2 À2.5 À8.6 1376734_at Nov, NOV protein BI279030 Hypo À1.3 À2.6 À3.5 1377767_at EST, AW526033 AW526033 Hypo À1.7 À2.7 À5.0 1388177_at Ddn, dendrin X96589 Hypo À1.5 À3.2 À5.8 1368987_at Slc17a7, solute carrier family 17, member 7 BF567766 Hypo À1.0 À8.4 À33.0

1383486_at EST, AA926109 AA926109 Hipp 23.2 3.9 À1.0 1373759_at EST, BF522317 BF522317 Hipp 19.6 2.3 À1.0 1367577_at Hspb1, heat shock 27 kDa protein 1 NM_031970 Hipp 14.3 1.9 1.1 1369012_at Inhba, inhibin beta-A NM_017128 Hipp 12.7 1.8 1.1 1375043_at c-fos, c-fos oncogene BF415939 Hipp 12.4 2.8 À1.5 1387306_a_at Egr2, early growth response 2 NM_053633 Hipp 11.1 2.7 À1.2 1373559_at LOC360765 AI228623 Hipp 6.8 1.9 À1.1 Conti B changes transcriptional Region-specific 1368527_at Ptgs2, prostaglandin-endoperoxide synthase 2 U03389 Hipp 6.2 2.3 1.3 1370454_at Homer1, homer, neuronal immediate early gene, 1 AB003726 Hipp 6.1 4.1 1.0 al et 1368677_at BDNF, brain-derived neurotrophic factor NM_012513 Hipp 6.0 1.9 1.1 1387068_at Arc, activity-regulated cytoskeletal-associated protein NM_019361 Hipp 4.7 2.0 À1.2 1392108_at BF390648 BF390649 Hipp 4.6 2.3 À1.2 1370989_at Ret, ret proto-oncogene AI639318 Hipp 2.8 1.9 1.2 1387276_at Ania-4, activity and neurotransmitter-induced early gene protein 4 NM_021584 Hipp 2.6 1.9 1.1 1387154_at Npy, neuropeptide Y NM_012614 Hipp 2.4 1.8 1.0 1368359_a_at Vgf, VGF nerve growth factor inducible NM_030997 Hipp 2.1 2.1 À1.3 1367939_at Rbp1, retinol-binding protein 1 NM_012733 Hipp 2.1 1.8 1.4 1372273_at Similar to glycophorin C isoform 2 AA944212 Hipp 2.0 1.8 1.1 1376749_at EST, AA945955 AA945956 Hipp À1.8 1.8 1.4 1387889_at Folr1, folate receptor 1 (adult) AI233882 Hipp À1.8 1.9 À1.1 1368395_at Gpc3, glypican 3 NM_012774 Hipp À2.1 À1.8 1.0 1387655_at Cxcl12, chemokine (C-X-C motif) ligand 12 AF189724 Hipp À2.2 1.8 À1.2 1387179_at Adcy8, adenylyl cyclase 8 NM_017142 Hipp 2.9 À1.4 À1.9 1381503_at EST, AI073168 AI073168 Hipp À2.1 1.1 2.1 1370849_at Bral1, brain link protein 1 AI145465 Hipp À1.3 2.7 À1.8 1371363_at Gpd3, glycerol 3-phosphate dehydrogenase BI277042 Hipp 1.6 2.4 3.1 oeua Psychiatry Molecular 1387317_at Avp, arginine vasopressin NM_016992 Hipp À1.0 À5.4 À6.4 1368802_at Pmch, pro-melanin-concentrating hormone NM_012625 Hipp À1.0 À7.8 À7.1 1368312_at Oxt, oxcytocin M25649 Hipp 1.1 À8.2 À9.4 179 oeua Psychiatry Molecular 180

Table 4 Continued

Probe ID Gene description GenBank no. Area Fold change

ECS SD FLX

1392613_at EST, AA942745 AA942745 DRN 3.0 1.9 1.9 1371363_at Gpd3, glycerol 3-phosphate dehydrogenase BI277042 DRN 1.8 1.9 4.1 1368912_at Trh, thyrotropin-releasing hormone M12138 DRN 7.2 3.7 1.2 1369063_at Anp32a, acidic nuclear phosphoprotein 32 family, member A NM_012903 DRN 4.2 À2.5 1.4 1391208_at EST, BG379836 BG379837 DRN 3.6 1.8 1.6 1383185_at EST, BE105131 BE105132 DRN À1.8 2.0 À1.3 1375629_at Lamp1, lysosomal membrane glycoprotein 1 AI230371 DRN À1.9 À2.1 À1.2 1379747_at EST, AA866443 AA866443 DRN À2.3 À2.1 1.3 changes transcriptional Region-specific 1373035_at AI031032 AI031033 DRN 3.0 1.6 1.8 1382186_a_at Similar to RIKEN cDNA 2610029K21 (LOC295228) AI136314 DRN 2.3 1.3 2.1 1389986_at EST, AI008409 AI008409 DRN 2.0 1.5 1.8 1389538_at Nfkbia, nuclear factor of kappa light chain gene enhancer in B-cells AW672589 DRN 1.8 À1.1 1.8 inhibitor, alpha 1393845_a_at Similar to Tmc4 protein (LOC308310) AI556940 DRN À1.8 1.1 À2.1 Conti B 1367802_at Sgk, serum/glucocorticoid-regulated kinase NM_019232 DRN 1.7 1.8 2.6

1385569_at EST, BF559640 BF559640 LC 2.6 À2.4 À1.8 al et 1367802_at Sgk, serum/glucocorticoid-regulated kinase NM_019232 LC 2.3 2.3 2.0 1395249_at BF400750 BF400751 LC À2.7 2.7 À2.0 1369303_at Crh, corticotrophin-releasing hormone NM_031019 LC 3.1 1.9 À1.6 1382561_at Similar to 4921517L17Rik protein (LOC296311), mRNA BF285103 LC 2.8 À2.2 1.4 1368981_at Aqp4, aquaporin 4 U14007 LC 2.6 À1.8 1.4 1393119_at EST, BM388725 BM388725 LC 2.4 2.1 1.1 1387663_at Gmfb, maturation factor, beta NM_031032 LC 2.3 À1.8 1.2 1387420_at Clic4, chloride intracellular channel 4 NM_031818 LC 2.2 À2.0 1.5 1368462_at Itpka, inositol 1,4,5-triphosphate 3-kinase NM_031045 LC 2.0 1.9 À1.2 1370019_at Sult1a1, sulfotransferase family 1A, phenol-preferring, member 1 AF394783 LC 1.9 1.9 1.5 1398528_at EST, BE117514 BE117515 LC 1.9 À2.1 1.5 1392613_at EST, AA942745 AA942746 LC 1.8 2.6 1.0 1375707_at AA817993 AA817994 LC À1.8 À1.8 1.3 1393263_at EST, AW522530 AW522531 LC À1.8 1.8 À1.0 1386035_at EST, BG381661 BG381661 LC À1.8 2.0 1.2 1389564_at Similar to cyclin L1; cyclin L Ania-6a (LOC298686) AA892159 LC À1.8 2.2 1.3 1387482_at Grid2, , ionotropic, delta 2 NM_024379 LC À1.8 1.8 1.0 1397407_at EST, AI137564 AI137564 LC À1.8 2.0 1.2 1396696_at Gria4, glutamate receptor, ionotropic, 4 BF390683 LC À1.8 1.9 1.1 1379464_at Calb1, 1 AI233253 LC À1.8 2.1 1.1 1393308_at EST, BE110640 BE110641 LC À1.8 2.0 1.0 1397015_at EST, BF386238 BF386239 LC À1.8 2.4 1.0 1375957_at EST, AW434654 AW434655 LC À1.9 1.8 À1.2 1377934_at EST, BF387289 BF387290 LC À1.9 4.2 À1.1 1376737_at EST, BE110674 BE110675 LC À1.9 1.9 À1.1 1375987_at Similar to ceramide kinases (LOC300129) AW525194 LC À2.0 1.8 1.3 Table 4 Continued

Probe ID Gene description GenBank no. Area Fold change

ECS SD FLX

1368477_at Atp2a3, ATPase, Ca2 þ transporting, ubiquitous NM_012914 LC À2.0 2.3 À1.0 1372830_at EST, BM384116 BM384116 LC À2.0 2.2 1.2 1374204_at Similar to WSB-1 (LOC303336) BM388946 LC À2.0 2.3 1.0 1385573_at Similar to R27090_2 (LOC290660) AI070797 LC À2.1 2.3 À1.0 1398440_at Similar to SR-rich protein (LOC297942) BI292166 LC À2.1 2.0 1.3 1376267_at Slc16a6, solute carrier family 16, member 6 AA859652 LC À2.1 1.8 1.2 1390675_at EST, BE119856 BE119857 LC À2.2 1.9 1.0 1395711_at EST, AW526713 AW526714 LC À2.2 2.1 1.0 1393607_at EST, AI146247 AI146248 LC À2.2 2.3 1.0 1383363_at EST, BF418817 BF418818 LC À2.2 1.8 1.1 1399022_at Similar to protein kinase STY (EC 2.7.1.-) – mouse (LOC301434) AI177513 LC À2.2 2.4 1.2 1388357_at EST, BI282972 BI282972 LC À2.2 2.1 À1.1 1373534_at Similar to SR-rich protein (LOC297942) BE107209 LC À2.3 1.8 1.1 1384310_at EST, BM383081 BM383081 LC À2.3 2.2 1.1 1372823_at Similar to RIKEN cDNA 2310005N03 (LOC289278) BE117126 LC À2.3 2.1 1.0 1395335_at EST, BF544005 BF544005 LC À2.3 2.2 À1.1 1378065_at EST, BI274450 BI274450 LC À2.3 2.1 À1.1 1369093_at Reln, reelin NM_080394 LC À2.3 2.0 1.0 1382020_at Similar to JNK-associated leucine-zipper protein (LOC360600) BE105500 LC À2.4 2.3 À1.3 1385463_at EST, AI043627 AI043627 LC À2.4 2.3 À1.0 Conti B changes transcriptional Region-specific 1375305_at LOC362256 (LOC362256) BI282028 LC À2.4 2.0 À1.1 1393736_at EST, BE116820 BE116820 LC À2.4 2.1 1.0 al et 1383646_at EST, AI072798 AI072798 LC À2.5 2.5 1.1 1387907_at Itpr1, inositol 1,4,5-triphosphate receptor 1 J05510 LC À2.5 3.9 1.1 1378068_at EST, AW529368 AW529368 LC À2.5 2.5 À1.0 1381967_at Similar to RNP1, RRM; CC1.3; LOC362251 BE114972 LC À2.5 2.3 1.1 1384250_a_at EST, AA818098 AA818098 LC À2.6 3.7 À1.0 1383649_a_at BI291080 BI291080 LC À2.6 2.1 À1.1 1369048_at Gabrd, gamma-aminobutyric acid A receptor, delta NM_017289 LC À2.7 5.6 À1.1 1368770_at Gcnt1, enzymatic glycosylation-regulating gene NM_022276 LC À2.7 2.3 À1.0 1382918_at EST, AA956561 AA956562 LC À2.7 2.6 À1.2 1378531_at EST, AI555775 AI555776 LC À2.8 2.3 À1.2 1379594_at EST, AW524408 AW524409 LC À2.8 1.9 À1.1 1376169_at EST, BE104290 BE104290 LC À2.9 2.0 1.1 1392818_at BM384139 BM384139 LC À2.9 2.0 1.4 1375653_at EST, BE109405 BE109405 LC À2.9 1.9 À1.5 1382749_at EST, 5BI293987 5BI293987 LC À2.9 2.3 1.0 1385078_at AA957582 AA957582 LC À3.2 2.5 1.1 1369242_at Pax6, paired box gene 6 NM_013001 LC À3.3 2.0 1.1 oeua Psychiatry Molecular 1379588_at EST, AA874805 AA874805 LC À3.3 1.8 1.1 1378315_at EST, AI045116 AI045116 LC À3.5 3.9 1.1 1368459_at Gdf10, prepro bone inducing protein NM_024375 LC À3.7 2.6 1.1 1378674_at EST, BI293056 BI293056 LC À3.8 3.0 1.3 181 oeua Psychiatry Molecular 182

Table 4 Continued

Probe ID Gene description GenBank no. Area Fold change

ECS SD FLX einseii rncitoa changes transcriptional Region-specific 1368887_at Cdh22, cadherin 22 NM_019161 LC À4.0 1.8 1.1 1393018_at EST, AI071984 AI071984 LC À4.0 3.2 À1.1 1376895_at Il16, interleukin 16 AI137163 LC À4.3 2.7 1.2 1398431_at Similar to carbonic anhydrase VIII BI294910 LC À4.5 5.5 À1.2 1378101_at Gsbs, G substrate AI228404 LC À4.7 5.0 1.1 1368684_at Fat2, MEGF1 NM_022954 LC À6.5 5.2 À1.0

1394135_at AI639109 AI639109 LC À8.2 5.8 À1.2 Conti B 1387288_at Neurod1, neurogenic differentiation 1 NM_019218 LC À8.9 7.0 1.1

1382205_at EST, AW527509 AW527509 LC À9.8 6.5 1.3 al et 1372936_at Similar to Purkinje cell protein 2 – mouse (LOC304195) BF395833 LC À10.4 7.4 1.2 1385031_at EST, AI144913 AI144913 LC À10.9 6.0 À1.0 1369861_at Gabra6, gamma-aminobutyric acid A receptor, alpha 6 NM_021841 LC À11.9 9.3 1.1 1378341_at EST, AI101125 AI101125 LC À39.2 14.3 À1.5 1369560_at Gpd3, glycerol 3-phosphate dehydrogenase NM_022215 LC 4.5 1.5 4.3 1398664_at Similar to RIKEN cDNA 9130427A09 (LOC307288) C06752 LC 3.3 À1.2 1.8 1369248_a_at Birc4, baculoviral IAP repeat-containing 4 AF304333 LC 3.1 À1.3 1.8 1370760_a_at Gad1, glutamate decarboxylase 1 M38350 LC 2.9 1.5 2.0 1375625_at LOC363203 (LOC363203) BF405077 LC 2.8 À1.3 1.9 1385070_at EST, BE111420 BE111420 LC 2.5 1.1 1.8 1370955_at Adam10, a disintegrin and metalloprotease domain 10 BI300565 LC 2.3 À1.2 1.8 1392820_at Fgf1, fibroblast growth factor 1 BI285064 LC 2.2 1.1 1.8 1371003_at Map1b, microtubule-associated protein 1b BG378086 LC À2.0 1.0 1.8 1395714_at AT005664 AT005664 LC À2.0 1.3 2.1 1393389_at EST, BF396237 BF396237 LC 1.0 À1.9 À1.8

List of the transcripts affected more or less than 1.8-fold to their specific control by two or three treatments as indicated. The list is presented by anatomical brain region (rostral to caudal) sorted by changes common to ESF, ES, EF and ES in decreasing order of magnitude of the numbers indicating time fold change for the first listed treatment. Values above or below the cutoff of 71.8 are in bold. Region-specific transcriptional changes B Conti et al 183 Table 5 List of transcripts affected by all three treatments

Probe ID Gene description GenBank no. Area Fold change

ECS SD FLX

1370019_at Sult1a1, sulfotransferase family 1A, phenol- AF394783 FC À2.5 1.8 1.7 preferring, member 1 1371363_at Gpd3, glycerol 3-phosphate dehydrogenase BI277042 Amy 1.8 2.1 2.3 1392791_at EST, AA964492 AA964492 Hypo 27.5 À3.8 À5.5 1387442_at Egr4, early growth response 4 NM_019137 Hypo 10.6 À1.8 À2.0 1369750_at Tshb, thyroid-stimulating hormone, beta M10902 Hypo 4.2 À2.7 2.4 subunit 1370074_at Baiap2, brain-specific angiogenesis inhibitor NM_057196 Hypo 2.6 À1.5 À2.3 1-associated protein 2 1369560_at Gpd3, glycerol 3-phosphate dehydrogenase NM_022215 Hypo 2.4 2.4 3.4 1377823_at EST, AW531363 AW531363 Hypo 2.4 1.9 1.9 1373081_at Baiap2, brain-specific angiogenesis inhibitor AI105000 Hypo 2.0 À1.8 À2.1 1-associated protein 2 1387356_at Wfs1, Wolfram syndrome 1 NM_031823 Hypo 1.8 À2.0 À4.3 1384392_at Cyp26b1, cytochrome P450, family 26, BF397093 Hypo À1.8 À2.1 À2.1 subfamily b, polypeptide 1 1367700_at Fmod, fibromodulin NM_080698 Hypo À1.8 À1.9 À2.2 1367648_at Igfbp2, insulin-like growth factor-binding NM_013122 Hypo À2.0 À2.3 À2.7 protein 2 1367571_a_at Igf2, insulin-like growth factor 2 NM_031511 Hypo À2.3 À2.2 À2.0 1390532_at EST, AI013778 AI013778 Hypo À2.4 À1.8 À2.4 1368321_at Egr1, early growth response 1 NM_012551 Hypo 6.0 À2.1 À1.5 1387241_at GPR88, G protein-coupled receptor 88 NM_031696 Hypo À1.8 À2.1 1.5 1388116_at Col1a1, collagen, type 1, alpha 1 BI285575 Hypo À2.0 À1.9 À1.6 1391809_at BE106814 BE106814 Hypo À1.8 1.7 1.9 1377767_at EST, AW526033 AW526033 Hypo À1.7 À2.7 À5.0 1388177_at Ddn, dendrin X96589 Hypo À1.5 À3.2 À5.8 1375043_at c-fos, c-fos oncogene BF415939 Hipp 12.4 2.8 À1.5 1371363_at Gpd3, glycerol 3-phosphate dehydrogenase BI277042 Hipp 1.6 2.4 3.1 1392613_at EST, AA942745 AA942745 DRN 3.0 1.9 1.9 1371363_at Gpd3, glycerol 3-phosphate dehydrogenase BI277042 DRN 1.8 1.9 4.1 1391208_at EST, BG379836 BG379837 DRN 3.6 1.8 1.6 1373035_at AI031032 AI031033 DRN 3.0 1.6 1.8 1389986_at EST, AI008409 AI008409 DRN 2.0 1.5 1.8 1367802_at Sgk, serum/glucocorticoid-regulated kinase NM_019232 DRN 1.7 1.8 2.6 1385569_at EST, BF559640 BF559640 LC 2.6 À2.4 À1.8 1367802_at Sgk, serum/glucocorticoid regulated kinase NM_019232 LC 2.3 2.3 2.0 1395249_at BF400750 BF400751 LC À2.7 2.7 À2.0 1369303_at Crh, corticotrophin-releasing hormone NM_031019 LC 3.1 1.9 À1.6 1387420_at Clic4, chloride intracellular channel 4 NM_031818 LC 2.2 À2.0 1.5 1370019_at Sult1a1, sulfotransferase family 1A, phenol- AF394783 LC 1.9 1.9 1.5 preferring, member 1 1398528_at EST, BE117514 BE117515 LC 1.9 À2.1 1.5 1375653_at EST, BE109405 BE109405 LC À2.9 1.9 À1.5 1378341_at EST, AI101125 AI101125 LC À39.2 14.3 À1.5 1369560_at Gpd3, glycerol 3-phosphate dehydrogenase NM_022215 LC 4.5 1.5 4.3 1370760_a_at Gad1, glutamate decarboxylase 1 M38350 LC 2.9 1.5 2.0

List of the transcripts affected more or less than 1.8-fold to their specific control by three treatments as indicated. The list is presented by anatomical brain region (Area). Values above or below the cutoff of 71.8 are in bold. The list includes changes with a cutoff of 71.5 for one treatment in some cases. is associated with late antidepressant onset. This have a more ‘robust’ effect than SSRIs, yet their time indicates that fast-onset and long-lasting antidepres- of onset is similar to that of SSRIs. The situation is sant effects may be achieved by targeting both similar for tricyclic antidepressants like chlorimipra- systems. However, that interesting concept may be mine which affect both NE and 5-HT uptake. Never- an oversimplification as it is not necessarily sup- theless, it is worth noting that in depression it is ported by existing clinical data. SNRIs are believed to assumed that the LC is overactive and thus targeting it

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 184 strongly with ECT and SD may achieve a paradoxical chronic treatment (reviewed in Lanfumey et al.,60 inhibition, with resulting reduction in the LC- Simansky,61 Hernandez et al.,62 and Fuller63). In the mediated inhibition of DRN 5HT-neurons. It is Hypo, FLX changes not only 5-HT but also noradrena- unclear why the robust and rapid antidepressant line and dopamine and these may jointly contribute effects of ECT and SD are lost rapidly, but it is likely to the large transcriptional changes in this brain area. that the very high level of transcriptional activation in A better understanding of the observed transcrip- the LC cannot be maintained. In addition, acute FLX tional profile in the Hypo might require mapping treatment was demonstrated to increase circulating them to specific hypothalamic nuclei, an analysis not dopamine and norepinephrine levels in rat PFC 44,45 contemplated in this study. and to elevate circulating levels of catecholamines in depressed individuals,46 yet without therapeutic Selected genes whose transcription was similarly effects. Further, it is reported that SSRIs affect sleep affected by two of the three treatments in one or several patterns and reduce rapid eye movement (REM) sleep brain regions during early phases of treatment, as are reports of The similarity between transcriptional effects of ECT increased anxiety and nervousness.47–51 and SDs and difference to the effects of FLX as revealed by investigating the number of changes, is A number of transcripts show up- and downregulation illustrated by a closer look at the following targets: depending on brain region and/or treatment BDNF, Homer1, Egr2 (Krox20), Ania-4, heat shock All three antidepressant treatments induced up- and 27 kDa protein 1 (Hspb1) (Hsp 27) and Ret, which downregulation of transcripts level. While upregula- forms a cluster of functionally correlated genes that tion was more frequent overall, downregulation was were found to be upregulated by both ECT and SD, but recorded with similar frequency in all brain regions not by FLX. following all three treatments. The only exception Homer1 is a scaffolding protein involved in the was the Hypo where FLX induced primarily down- activity-dependent alteration of synaptic structure regulation of gene expression. These observations and function modulating in glutama- suggest transcriptional suppression or change in tergic .64 Homer proteins also regulate sensi- mRNA stability as major mechanisms that may be tivity to and may be involved in the involved in antidepressant action, a finding consis- pathogenesis of .65,66 tent to that reported for treatments with imipramine Erg2, also known as Krox20, is a transcription factor and citalopram.52 The mechanisms mediating such which plays a role in peripheral myelination.67 and is changes may include chromatin remodeling through involved, together with homer and BDNF, in the histone modification as recently demonstrated in a stabilization of long-term potentiation (LTP).68–70 chronic model of ECT.53 Interestingly, Krox20 expression is upregulated ex- When comparing the three treatments, ECT and SD clusively during the dark phase in the cortex and affect transcription more robustly in the LC than does Hippo of rats exposed to an enriched environment.71 FLX. This is partly explained by the selectivity of The activity and neurotransmitter-induced early FLX, a serotonin reuptake blocker that can affect the gene protein 4 (Ania-4) shares high homology with serotonergic projections that are not the most im- doublecortin-like kinase, CaM-Kinase, the CaMK- portant drivers of neuronal activity for the noradre- related peptide (CARP) and the candidate plasticity nergic cells in the LC. ECT induces convulsions by gene 16 (CPG16), a protein serine/threonine ki- depolarization of neurons in several areas, including nase.72,73 Ania-4, together with Homer and Erg2, is the LC. The fact that both SD and ECT can affect the upregulated in the striatum by stimula- LC are in line with earlier observations on the effects tion.74 Ania-4 expression is also elevated in the of ECT54–56 and of sleep deprivation on LC.57–59 The cerebral cortex after traumatic brain injury and in strong stress generated by both treatments and the the striatum following treatment with the putative D1 similarly short duration of these two treatments as agonist/D2 antagonist LEK8829.75,76 compared to the 14-day long SSRI treatment also Hpb1, better known as Hsp27, is a heat shock suggest that of the three treatments, the two faster- protein with antiapoptotic effects believed to be acting stress-based treatments, ECT and SD, will bear important for neuronal survival following axotomy similarities and one of these similar features is the or trophic factor withdrawal. Hpb1 and BDNF strong effect on the LC, most likely on the noradre- expression are elevated following spinal cord injury77 nergic neurons of the LC. The strong upregulation of or in the CNS after cortical spreading depression,78 the early gene cFos by ECT and SD but not by the SSRI whereas it is reduced after BDNF treatment in retinal is reflecting the shorter time point for the former ganglion following axotomy.79 treatments as well as differences in the neurochem- The proto-oncogene Ret belongs to the receptor-like ical substrates. tyrosine kinase superfamily and is strongly elevated FLX induced a large number of transcriptional in motor neurons following axotomy and during changes in the Hypo. There is extensive literature on neuronal differentiation.80–82 the chronic FLX-mediated neuroendocrine changes Together with BDNF, these genes are involved in based on acute upregulation of serotonergic receptor synaptic plasticity and possibly in neurogenesis, two occupancy followed by desensitization during the mechanisms that have been proposed to participate in

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 185 antidepressant action.83 Such studies have focused expression of Sgk1 has been observed in the Hippo of mainly on the effects of BDNF gene upregulation fast-learning rats as compared with slow-learning following antidepressant treatment. Finally, a large rats.96 Enrichment-induced Sgk1 expression is speci- number of ESTs were found to be regulated by more fically mediated through alpha-amino-3-hydroxy-5- than one antidepressant treatment. methyl-4-isoxazolepropionic acid (AMPA) receptors97 and Sgk1 can directly phosphorylate the transcription Transcripts regulated by all three antidepressant factor cyclic AMP response element-binding protein treatments (CREB) on serine 133.98 Sgk1 expression level is Few transcripts were found to be consistently modu- increased by acute amphetamine36 and lysergic acid lated by all three antidepressant treatment. These diethylamide (LSD) treatment,36 and it is increased in include GPD3, Sgk1, Sult1a1 and GPR88. This is the brain and peripheral tissues following psycho- encouraging from an antidepressant drug target social stress.40 The upregulation of Sgk1 strongly search point of view, if one could show that non- correlates with the occurrence of cell death. In antidepressant psychoactive drugs do not affect Mecp2-null mice, a model for ,99 transcript levels, that is, that there is a selectivity to increased levels of Sgk1 mRNA are reported before the transcriptional changes in GPD3, Sgk1, Sult1a1 and after onset of neurological symptoms. Fear and GPR88. conditioning is accompanied by changes in Sgk1 GPD3, the mitochondrial flavoprotein-dependent expression.100 Sgk1 is also upregulated during lacta- glycerol-3-phosphate dehydrogenase is the only target tion as were Sult1a1 and GPR88.101 Taken together, in the present study which is consistently upregu- the published data and our own data strongly suggest lated by all three treatment modalities, in all seven a role for Sgk1 in stress, cell survival, and also brain regions studied. The activity of GPD3 is learning and consolidation and other central considered a reliable marker of thyroid status both functions, like reward and depression.96,102 in the liver, and in the brain and thyroid hormone Sulfotransferase 1a (Sult1a1) specifically catalyzes supplementation is a long-known adjunct therapy in the sulfonation of the catecholamines, dopamine, depression.84,85 The altered metabolic state in the adrenaline and noradrenaline as well as of drugs such brain regions examined during depression and anti- as apomorphine. Sult1a1 is involved in drug metabo- depressant treatments has been demonstrated by 18- lism, cancer, hormone regulation and neurotransmit- fluorodeoxyglucose PET studies.86,87 GPD3 was found ter synthesis/metabolism.103 Sult1a1 was also to be transcriptionally regulated in relation to changes upregulated during lactation as was Sgk1 and in neuronal activity and antidepressant drug treat- GPR88.101 Both Sgk1 and Sult1a1 are transcriptionally ment.88 Enhanced expression of GPD3 might reflect regulated in studies on bipolar disorder and lithium increased metabolic requirements and contribute to a treatment.37 The effects of Sult1a1 on thyroid hor- higher Na/K ATPase activity that can accelerate the mone metabolism are also compatible with involve- rate of neuronal repolarization. ment in antidepressant effects and altered metabolic The serum and glucocorticoid-regulated kinase 1 rates.104 Given the widespread and rather extensive (SGK, Sgk1) is upregulated consistently by all treat- regulation of Sult1a1 mRNA expression by all three ment modalities in six out of seven brain regions, antidepressant treatments applied in the present whereas in the PFC, ECT leads to reduced mRNA study, this appears to play a significant role expression, suggesting Sgk1 is involved not only in in mood states. Interestingly, FLX and SD promote stress but indeed also in mood regulation. Sgk1 upregulation in all brain regions tested, whereas ECT belongs to a family of serine/threonine kinases that induces upregulation in some and downregulation in is under acute transcriptional control by serum and other brain areas. , as well as by an expanding set of From a drug development perspective, one of the hormones, growth factors and cellular stress path- most interesting candidates to emerge from our study ways.89 Sgk1 is implicated in the regulation of ion is GPR88 (an orphan GPCR). GPCRs are attractive channel conductance, cell volume, cell cycle progres- drug targets and dozens of GPCRs have been targeted sion and .90 Sgk1 is activated through the for safe, chronic therapies of several disorders phosphatidylinositol 3 kinase (PI3-kinase) pathway including , allergy, acid secretion and by growth factors such as insulin, insulin-like growth schizophrenia. GPR88 is an orphan GPCR of the factor-1 (IGF1), fibroblast growth factor (FGF), plate- family A, which shows highest homology to 5HT1D- let-derived growth factor (PDGF) or tumor growth receptor and the beta 3 , respec- factor beta (TGF-beta), which activate extracellular tively. GPR88 was recently described to be selectively signal-regulated kinases (ERKs).91,92 Sgk1 is similar in expressed in the striatum;105 however, its mRNA is primary structure to protein kinase B (PKB), protein also present in cerebral cortex, nucleus accumbens, kinase C (PKC) and protein kinase A (PKA). In the Amy, Hippo, Hypo, thalamus, and LC (Allen Brain brain or in brain cells, transcription of Sgk1 is Atlas, GNF Atlas and our own unpublished data). increased in several animal models of Parkinson’s Several lines of evidence suggest that GPR88 mRNA is disease93 and a transgenic model of amyotrophic regulated in a variety of psychiatric conditions lateral sclerosis (ALS), following brain injury94 and including bipolar disorder and major depression. In after transient global cerebral .95 Increased an adult rat cortex slice model, inositol depletion by

Molecular Psychiatry Region-specific transcriptional changes B Conti et al 186 lithium (IMPase block) and carbachol (muscarinic that ECS and SD elevate the levels Ania-4, Erg-2, receptor agonist) co-treatment increased GPR88 tran- Homer1, Hspb and Ret may reflect the growing script levels B2.2-fold, whereas repletion of inositol assertion that antidepressant treatments are asso- decreased GPR88 transcripts in the same magnitude ciated with neuroprotection, neurogenesis and neu- (B2.3-fold). Lithium inhibits inositol monophospha- ronal plasticity.10–14 tase and downstream GSK3beta at therapeutically A very limited number of transcripts was found to effective concentrations, and it has been hypothe- be affected by all three antidepressant treatments and sized that depletion of brain inositol levels is an only functional validation will reveal their relevance important neurochemical change forming the mole- with respect to depression. Among them, three cular basis of lithium’s therapeutic efficacy in bipolar : GPD3, Sgk1 and Sult1a1 can be modulated disorder.106 GPR88 is upregulated by methampheta- by several hormonal states making them difficult drug mine and valproate, a clinically effective drug in targets in terms of specificity. GPD3 is distributed treatment of bipolar disorders, in mouse pharmaco- isotropically and its general metabolic role renders it genomic models for bipolar disorders.37 GPR88 an unlikely drug target. Sgk1 is activated by gluco- expression on the transcriptional level is lower in corticoids that are induced by the activation of HPA BDNF-deficient mice.107 GPR88 transcript levels were axis by chronic stress such as may underlie depressed increased in the arcuate/ventromedial nucleus of the states. It is likely that in a feedback regulatory Hypo during lactation (B1.7-fold). Removal of pups arrangement, many substrates of this protein kinase for 48 h decrease GPR88 mRNA levels. Incidentally, in may act to limit the effects of stress and thus may that study, similar observations were made for Sgk1 exert an antidepressant like effect. Thus, identifica- and Sult1a1 mRNA regulation during lactation.101 tion of Sgk1 substrates in key brain areas may be This observation is particularly interesting as lactat- important to determine its candidacy as drug target ing mothers can be considered to be in a non- for antidepression. The fact that Sult1a1 utilizes depressed state; it has been reported that withdrawal catecholamines as substrates renders it an interesting of pups from nursing mothers induces anhedonia, candidate for a possible significant involvement in whereas the presence of pups and maternal care antidepressant action. The simultaneous change in increase reward in a number of paradigms. Qualita- the levels of the three catecholamines adrenaline, tive trait linkage (QTL) analysis has resulted in high noradrenaline and dopamine may represent a set of logarithm of odds (LOD) scores on Chr1q, which is neurochemical stimuli in several brain regions not synthenic to that mapping rodent emotionality. Genes dissimilar to the effect of changes in monoamine of interest in these regions include GPR88.108 Taken oxidase (MAO) activity. The rise of this transcript together, our data and that reported in the literature upon treatment with all three antidepressant mod- suggest that GPR88 is regulated in a number of alities in the LC, the major noradrenergic nucleus conditions linked to reward, anhedonia, depression with significant dendritic release, may be important and bipolar disorders. Intriguingly, both down- and for the regulation of catecholamine levels in this upregulation was seen after the different treatments, nucleus. depending on the brain regions (Amy, Hippo, Hypo, LC and PFC). Acknowledgments Conclusion We acknowledge all our collagues for their help: In summary, the major conclusion of this unbiased colleagues in the Bartfai lab: Hedie Badieh, Marga search for molecular changes occurring during fast Behrens, Svetlana Gaidarova, Jeffrey Kinney, Janell and slower antidepressant treatments is that the faster Laca, Jacinta Lucero, Shuei Sugama, Iustin Tabarean acting ECT and SD predominantly affects the LC and and Sebastian Wirz all spent countless hours in much less the DRN. Not surprisingly, the SSRI FLX assisting us with the treatments described. Colleagues affects predominantly the DRN, but even more in the Hoyer lab: Dominique Fehlmann, Edi Schuep- profoundly the Hypo. bach, Sabine Leonhard and Deepak Thakker have As for the identification of new molecules or performed ISH, autoradiography and data analysis molecular pathways that may be of interest for thereof. Colleagues in the Maier lab: Jose Luis Crespo development of antidepressant treatments, this study and Doris Rueegg have performed the RNA isolations confirms transcriptional regulation of several genes and cloning of the in situ probes. We also thank known to be affected by more than one antidepressant Nicole Hartmann and her team from the Genomics treatment. These include BDNF whose transcription Factory at NIBR Basel for the microarray work. is upregulated by both ECT and SD as previously reported,13,21,109–111 although unlike other studies13,112 both microarray and ISH analysis demonstrated that BDNF transcription is not affected by FLX. 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