Advertisement

Riluzole Attenuates L-DOPA-Induced Abnormal Involuntary Movements Through Decreasing CREB1 Activity: Insights from a Rat Model

  • Luca Pagliaroli
  • Joanna Widomska
  • Ester Nespoli
  • Tobias Hildebrandt
  • Csaba Barta
  • Jeffrey Glennon
  • Bastian Hengerer
  • Geert PoelmansEmail author
Open Access
Original Paper
  • 202 Downloads

Abstract

Chronic administration of L-DOPA, the first-line treatment of dystonic symptoms in childhood or in Parkinson’s disease, often leads to the development of abnormal involuntary movements (AIMs), which represent an important clinical problem. Although it is known that Riluzole attenuates L-DOPA-induced AIMs, the molecular mechanisms underlying this effect are not understood. Therefore, we studied the behavior and performed RNA sequencing of the striatum in three groups of rats that all received a unilateral lesion with 6-hydroxydopamine in their medial forebrain bundle, followed by the administration of saline, L-DOPA, or L-DOPA combined with Riluzole. First, we provide evidence that Riluzole attenuates AIMs in this rat model. Subsequently, analysis of the transcriptomics data revealed that Riluzole is predicted to reduce the activity of CREB1, a transcription factor that regulates the expression of multiple proteins that interact in a molecular landscape involved in apoptosis. Although this mechanism underlying the beneficial effect of Riluzole on AIMs needs to be confirmed, it provides clues towards novel or existing compounds for the treatment of AIMs that modulate the activity of CREB1 and, hence, its downstream targets.

Keywords

AIMs Dyskinesia 6-OHDA-lesioned rats Riluzole CREB1 

Introduction

Chronic administration of the dopamine precursor L-DOPA—the first-line treatment of dystonic symptoms manifesting in childhood or in Parkinson’s disease (PD) [1]—often leads to the development of so-called abnormal involuntary movements (AIMs). In humans, L-DOPA-induced AIMs are referred to as L-DOPA-induced dyskinesia (LID) [2], which represents an important clinical problem as approximately 90% of PD patients develop LID within 10 years of starting L-DOPA treatment. As a result, the prescription of L-DOPA to PD patients is often delayed to minimize the risk of developing LID [3].

The pathogenic mechanisms underlying AIMs and clinical LID are still largely unclear. Literature evidence indicates that chronic L-DOPA administration affects multiple neurotransmitter systems [4, 5, 6], but mainly the dopaminergic system, i.e., L-DOPA activates striatal dopamine 1 receptors (D1Rs), resulting in the overstimulation of the “direct” nigrostriatal pathway [7, 8]. In turn, this hypersensitivity of D1Rs in striatal neurons triggers a number of downstream signaling cascades involving—among others—cyclic AMP (cAMP)-activated protein kinase A (PKA) [9, 10], the phosphatase inhibitor DARPP-32 [10, 11], and the ERK1 and ERK2 (ERK1/2) kinases [12, 13] that are subsequently implicated in the development of LID through modulating gene expression and function [14, 15]. In this respect, previous transcriptomic and methylation studies in rodent models indeed indicate that AIMs/LID are associated with aberrant gene expression through transcription factors, such as CREB1, proteins from the AP-1 complex [9, 16] (such as FOSB) [17], and GADD45 family proteins [17].

Recently, Riluzole has been suggested as a candidate drug to treat AIMs/LID. Indeed, several studies on rodent models have provided evidence for the efficacy of Riluzole in the management of AIMs [2, 18, 19]. As for human studies, Riluzole showed anti-dyskinetic effects without affecting the anti-parkinsonian action of L-DOPA in a small pilot study [20], but it was ineffective in another clinical trial [21]. Riluzole essentially has anti-glutamatergic properties—including effects on glutamate release, uptake, and receptor signaling [22, 23, 24, 25], and it protects against glutamate-induced activation of kinases, such as ERK1/2 [26]. More specifically, although Riluzole has properties resembling those of a competitive NMDA receptor antagonist, its effects on reducing glutamatergic neurotransmission are more indirect [27]. Indeed, the anti-glutamatergic effects of Riluzole could result from a reduction of glutamate release from synapses through an inhibition of voltage-gated sodium channels [28], a reduction in the post-synaptic calcium influx mediated by P/Q-type calcium channels [29], a reduction in glutamine import into synapses (with glutamine being a precursor for the releasable glutamate pool) [30], or through interfering with the size of the readily releasable glutamate pool [31]. Further, animal model studies suggest that Riluzole is not selective for glutamate but also reduces the release of acetylcholine, dopamine, and, to a lesser extent, serotonin through mechanisms independent of glutamate receptors [32]. However, a detailed understanding of the molecular mechanism(s) underlying the protective effect of Riluzole on AIMs/LID is essentially lacking.

In this study, we aimed to elucidate the molecular mechanisms underlying the beneficial effect of Riluzole on AIMs. Therefore, we studied the behavior and performed RNA sequencing of the striatum, followed by gene expression analysis and comparison in three groups of rats. All rats received a unilateral lesion with 6-hydroxydopamine (6-OHDA) in their medial forebrain bundle (MFB)—resulting in striatal dopaminergic hypersensitivity—after which they were administered saline, L-DOPA (which constitutes a rat model of AIMs), or L-DOPA combined with Riluzole. We found that Riluzole attenuates L-DOPA-induced AIMs in the rat model. In addition, further analysis indicated that Riluzole is predicted to reduce the activity of the transcription factor CREB1, the key hub in a landscape of interacting proteins that are involved in regulating neuronal apoptosis.

Methods

Animals and Ethical Approvals

Juvenile male Wistar rats (RjHan:WI) were used in this study. Rats were obtained from our provider (Janvier, Le Genest-St Isle, France) at the age of 14 days together with their mothers. In total, 5 juvenile rats and a mother were housed together with free access to food and water, under a 12-h light and dark cycle in temperature- and humidity-controlled rooms. All animals were habituated to their housing conditions for one week. Animal housing and experiments were approved by the appropriate institutional governmental agency (Regierungspräsidium Tübingen, Germany) and performed in an AAALAC (Association for Assessment and Accreditation of Laboratory Animal Care International)-accredited facility, following the European Convention for Animal Care and Use of Laboratory Animals.

Stereotaxic Surgery

After 1 week of habituation at post-natal day (PND) 21 (n = 48), the rats were separated from their mothers and underwent stereotaxic surgery with 6-hydroxydopamine hydrobromide (6-OHDA). Further details are provided in the Supplementary methods.

Animal Treatment

Two weeks after stereotaxic surgery, the rats were randomly allocated to 4 groups (n = 12 animals per group) associated to different pharmacological treatments, at the same conditions: the first group was chronically administered (6 times in 2 weeks, intra-peritoneally (i.p.)) with a solution of L-DOPA methyl ester hydrochloride and benserazide (Sigma-Aldrich Chemie GmbH, Germany) in saline (6/15 mg/kg, i.p.). The second group (control) was administered with saline. The third group was chronically administered (6 times in 2 weeks) with Riluzole (Sigma-Aldrich Chemie GmbH, Germany) dissolved in 1% Tween (6 mg/kg, i.p.) and L-DOPA/benserazide (6/15 mg/kg, i.p.). The fourth (6-OHDA-lesioned) group followed the same procedure as group 1 and was used to verify the presence of the lesion by quantification of dopamine (DA) levels in striatal tissue using high-performance liquid chromatography (HPLC) coupled to electrochemical detection (ECD).

Phenotype Scoring

Four weeks after surgery (PND 49), the rats were administered their treatment and were individually observed for 1 min every 20 min. Abnormal involuntary movements (AIMs) of the limb, mouth, and body axis were assessed according to the widely used AIMs rating scale [33]. Briefly, each type of movement was scored on a scale from 0 to 4 (0 = absent; 1 = occasional; 2 = frequent; 3 = continuous but interrupted by sensory distraction; 4 = continuous, severe, not interrupted by sensory distraction). The sum of the independent scores of each body part per time point gave the total AIMs score.

Animal Sacrifice and Sample Extraction

At PND 53, rats were sacrificed 2 h after the administration of a final treatment. Rats were anesthetized for 60 s in 5% isoflurane and quickly decapitated by guillotine. Following brain removal, lesioned and unlesioned striata were extracted, snapped-frozen in liquid nitrogen, and stored at − 80 °C. A schema of the experimental procedure is outlined in Fig. 1.
Fig. 1

Schematic diagram of the protocol employed including the time course of the experiment and the different assays that were used

Striatal DA Determination Through HPLC

DA levels in 12 6-OHDA-lesioned striata compared to their contralateral controls were quantified using HPLC coupled to ECD. Further details are provided in the Supplementary methods.

Behavioral Testing: Statistical Analysis

Time-course data were analyzed for statistical significance using two-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test. Dopaminergic HPLC quantification in lesioned versus unlesioned striata was analyzed using a Wilcoxon matched-pairs signed-ranked test.

RNA Sequencing and Data Analysis

Total RNA was extracted from striatum tissue from 8 animals from each group using the QiagenAllPrep Kit (Qiagen, Hamburg, Germany), according to the manufacturer’s instructions. RNA was further quantified using the NanoDrop 1000 Spectrophotometer and Bioanalyzer 2100 (Agilent). Samples with RIN value above 8.0 were used for transcriptome analysis. The sequencing library preparation was done using 200 ng of total RNA input with the TrueSeq RNA Sample Prep Kit v3-Set B (RS-122-2002, Illumina Inc., San Diego, CA) producing a 275 bp fragment including adapters in average size. In the final step before sequencing, 12 individual libraries were normalized and pooled together using the adapter indices supplied by the manufacturer. Pooled libraries were clustered on the cBot Instrument from Illumina using the TruSeq SR Cluster Kit v3—cBot—HS (GD-401-3001, Illumina Inc., San Diego, CA), and sequencing was then performed as 78 bp, single reads and 7 bases index read on an Illumina HiSeq3000 instrument using the TruSeq SBS Kit HS—v3 (50-cycle) (FC-401-3002, Illumina Inc., San Diego, CA). Reads were aligned to the rat genome using the STAR Aligner v2.5.2a [34] with corresponding Ensembl 84 reference genome (http://www.ensembl.org). Sequenced read quality was checked with FastQC v0.11.2 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/), and alignment quality metrics were calculated using RNASeQC v1.18 [35]. Following read alignment, duplication rates of the RNA sequencing samples were computed with bamUtil v1.0.11 to mark duplicate reads and the dupRadar v1.4 Bioconductor R package for assessment [36]. Gene expression profiles were quantified using Cufflinks software version 2.2.1 [37] and the feature counts software package [38]. Transcripts with at least 10 reads in 8 samples were retained and further used to identify differentially expressed genes between the following three experimental groups: saline, L-DOPA, and L-DOPA + Riluzole. Statistical analyses were performed using R (www.r-project.org) and the Bioconductor package ([39], www.bioconductor.org) limma-voom [40]. The Benjamini-Hochberg’s method was used to correct for multiple testing, and only protein-coding genes with adjusted p value < 0.01, independent of magnitude of change, were considered as differentially expressed and used in the subsequent analyses. The Venn diagram of the final sets of significantly differentially expressed genes for the two comparisons was built with Venny [41]. To assess the effect of Riluzole on L-DOPA-regulated genes, we also looked at the overlap between the genes regulated by L-DOPA (L-DOPA vs. saline, comparison 1) and the genes regulated by Riluzole in the L-DOPA model (L-DOPA + Riluzole vs. L-DOPA, comparison 2). To quantify this overlap, we used the hypergeometric distribution test [42]:
$$ p\left(x|\ n,M,N\right)=\frac{\left(\genfrac{}{}{0pt}{}{M}{x}\right)\left(\genfrac{}{}{0pt}{}{N-M}{n-x}\right)}{\left(\genfrac{}{}{0pt}{}{N}{n}\right)} $$

This test calculates the chance of observing exactly x overlapping genes from a total of n differentially expressed genes by Riluzole in the L-DOPA model, with a total of M genes that were differentially expressed by L-DOPA and a total of N genes detected with RNAseq. The total number of unique genes detected with RNAseq (N) consists of genes detected in both comparisons, irrespective of their FC or expression p value. For all comparisons, only protein-coding genes were considered. To determine the correlation between the fold changes for the overlapping genes in the two comparisons, we created a scatter plot and calculated the Spearman’s correlation coefficient using the ggscatter function in R package ggpubr.

Upstream Regulator and Gene Enrichment Analyses

Using Ingenuity Pathway Analysis (IPA; Qiagen Inc.), we performed upstream regulator and gene enrichment analyses. Based on the differentially expressed genes, IPA generates a list of “upstream regulators,” i.e., proteins or compounds that are able to explain observed gene expression changes in the input dataset. For each upstream regulator, IPA calculates a p value of overlap (measuring the statistical significance of the overlap between the dataset genes and all genes that are regulated by the upstream regulator) and a z score (reflecting the inhibition or activation of the upstream regulator-dependent effects on target gene expression). We selected the major upstream regulator with the best z score and p value of overlap for the two comparisons—i.e., L-DOPA vs. saline and L-DOPA + Riluzole vs. L-DOPA—and used the target genes of this upstream regulator for further analyses. In the gene enrichment analysis, IPA assigns genes and their corresponding mRNAs/proteins to functional (sub)-categories, i.e., “canonical pathways” and “biofunctions,” with the latter including “diseases and disorders” and “molecular and cellular functions.”

Molecular Landscape Building

Following the upstream regulator and enrichment analyses, we searched the literature for the functions and interactions of all proteins encoded by the target genes of the major upstream regulator and expressed in the opposite direction in the two comparisons, i.e., L-DOPA vs. saline and L-DOPA + Riluzole vs. L-DOPA. First, we used the UniProt Knowledge Base ([43], http://www.uniprot.org) to gather basic information on the functions of all target genes and their encoded proteins. Subsequently and starting with the interactions reported by IPA, we used PubMed (http://www.ncbi.nlm.nih.gov/pubmed) to search for all functional, experimental evidence-based interactions between the proteins. Based on all gathered information, we generated a protein interaction landscape. The figure depicting this landscape was made using the drawing program Serif DrawPlus version 4.0 (www.serif.com).

qPCR Validation of Selected CREB1 Targets

To provide an additional validation of the RNA sequencing data, we performed qPCR to assess and compare the mRNA expression levels of 10 randomly chosen CREB1 targets in each of the samples of the groups investigated in this study (saline, L-DOPA, L-DOPA + Riluzole). RNA from the same samples used for the RNA sequencing was reverse-transcribed to cDNA using the RT2 First-Strand Kit (Qiagen, Cat. number 330404) according to the manufacturer’s instructions. Three-step qPCR (95 °C for 10 min, followed by 40 two-step cycles at 95 °C for 15 s and 60 °C for 30 s, and the generation of melting curves from 70 to 95 °C; Rotor-Gene Q 1000, Qiagen) was performed using RT2 SYBR Green ROX™ qPCR Mastermix (Qiagen, Cat. number 330521) and RT2 qPCR primer Assays provided by Qiagen. The housekeeping genes Bcap29 and Cdkn1b were used as reference for normalization of gene expression, and a Student’s t test was used to assess statistical significance. The full list of primers is specified in Supplementary Table 1.

Results

Assessment of Striatal DA Depletion by Assaying Its Content

To confirm the degree of dopaminergic denervation in the unilateral 6-OHDA-lesioned rats, total (intracellular and extracellular) dopamine (DA) tissue content in the ipsilateral (lesioned) and contralateral (control) striatum relative to the lesion was assayed by HPLC coupled to ECD. 6-OHDA lesion induced a marked decrease (76%) in DA concentration in the ipsilateral striatum compared with the contralateral side (Supplementary Fig. 1).

Behavioral Effects: Induction of AIMs by L-DOPA in 6-OHDA-Lesioned Rats and Their Mitigation by Riluzole

Intra-MFB 6-OHDA lesion plus 2 weeks of chronic L-DOPA exposure induced strong abnormal involuntary movements (p < 0.001), while 6-OHDA-lesioned rats given saline showed no abnormal motor phenotype. Chronic treatment with Riluzole together with L-DOPA was associated with fewer AIMs than L-DOPA alone (p < 0.001), as shown in Fig. 2.
Fig. 2

Induction of AIMs by L-DOPA in 6-OHDA-lesioned rats and their mitigation by Riluzole. Data shown as mean ± S.E.M. AIMs scores. Significant differences between the saline and L-DOPA-treated groups are indicated as **p < 0.01 and ****p < 0.001 and between the L-DOPA and L-DOPA + Riluzole-treated groups as ####p < 0.001

RNA Sequencing Data Analysis and Upstream Regulator/Gene Enrichment Analyses

Transcriptomic analysis was performed on the mRNA from the RNA samples isolated from the (lesioned) striatum of saline-, L-DOPA-, and L-DOPA + Riluzole-treated rats 2 h after the administration of a final injection. This allowed examination of the striatal mRNA gene expression profiles (and assessment of the counteracting effect of Riluzole) at the peak of L-DOPA effectiveness. The statistically significant differences in gene expression levels in striatum of L-DOPA- vs. saline-treated rats (comparison 1) and in L-DOPA + Riluzole- vs. L-DOPA-treated rats (comparison 2) are shown in Supplementary Data file 1.

Among the differentially expressed genes, 667 were differentially expressed only in comparison 1 and 1200 genes were differentially expressed only in comparison 2. Further, 465 genes were overlapping in that they were differentially expressed in both comparisons (Supplementary Fig. 2), and all of these genes were differentially expressed in the opposite direction in the two comparisons (i.e., genes that were upregulated by chronic L-DOPA treatment were downregulated by Riluzole co-administration and vice versa). The significance of the overlap in differentially expressed genes was calculated by using the hypergeometric distribution test, which showed that the overlap is much greater than would be expected based on random gene selection (p value = 1.01E−142).

As indicated in Supplementary Table 2, cAMP-responsive element binding protein 1 (CREB1) is the top upstream regulator of both the genes that were differentially expressed in comparison 1 and comparison 2, and in these comparisons, CREB1 is predicted to be activated and inhibited, respectively. In addition, CREB1 is the top upstream regulator of the 465 overlapping differentially expressed genes (see previous texts) and there is a highly significant, negative correlation (r = − 0.91, p value = 2.2E−16) between the fold changes for these genes—including the 58 direct CREB1 target genes—in the two comparisons (Supplementary Fig. 3).

Furthermore, gene enrichment analysis (Supplementary Table 3) revealed that the three sets of differentially expressed genes are significantly enriched for a number of “diseases and disorders” categories, including “epileptic seizure” (enriched in all three gene sets), as well as “disorder of basal ganglia” and “neuromuscular disease” (enriched in the genes from comparison 1). In addition, the gene sets are enriched for multiple “molecular and cellular functions” categories, such as “cell death/apoptosis” and “expression/transcription of RNA” (enriched in all three gene sets) as well as “development of neurons” (enriched in the genes from comparison 2).

Molecular Landscape of CREB1 Targets

Subsequently, we further investigated the CREB1-mediated molecular mechanisms implicated in the counteractive effect of Riluzole on L-DOPA-induced changes in gene expression. Therefore, the set of 58 CREB1 target genes that were regulated in the opposite direction by L-DOPA and Riluzole (Table 1) was studied in more detail, and enrichment analysis of these 58 overlapping genes showed that “epileptic seizure” and “apoptosis” are the most significantly enriched “diseases and disorders” and “molecular and cellular functions” categories, respectively (Supplementary Table 4).
Table 1

CREB1 target genes that were significantly differentially expressed in comparisons L-DOPA vs. saline and L-DOPA + Riluzole vs. L-DOPA with the corresponding fold changes (FDR-corrected p value < 0.01). The genes in bold encode proteins that are included in our molecular landscape (Fig. 3)

CREB1 target gene

Description

L-DOPA vs. saline

L-DOPA + Riluzole vs. L-DOPA

Arc

Activity regulated cytoskeleton-associated protein

6.41

− 2.99

Atf3

Activating transcription factor 3

10.98

− 6.06

Bag3

BCL2-associated athanogene 3

1.80

− 1.73

Ccnd3

Cyclin D3

1.22

− 1.31

Cdc37

Cell division cycle 37

1.27

− 1.28

Cdk19

Cyclin-dependent kinase 19

− 1.22

1.18

Cdkn1a

Cyclin-dependent kinase inhibitor 1A

4.09

− 2.57

Crem

cAMP-responsive element modulator

1.73

− 1.52

Crh

Corticotropin-releasing hormone

6.32

− 4.62

Csrnp1

Cysteine- and serine-rich nuclear protein 1

3.06

− 1.88

Dusp14

Dual specificity phosphatase 14

4.15

− 2.44

Egr4

Early growth response 4

10.01

− 4.16

Ehd4

EH domain containing 4

1.30

− 1.30

Fgf13

Fibroblast growth factor 13

− 1.29

1.26

Fos

Fos proto-oncogene, AP-1 transcription factor subunit

12.99

− 4.94

Fosb

FosB proto-oncogene, AP-1 transcription factor subunit

17.17

− 4.96

Frmd6

FERM domain containing 6

2.16

− 1.59

Gaa

Glucosidase alpha, acid

1.46

− 1.34

Gadd45b

Growth arrest and DNA damage-inducible beta

3.43

− 1.76

Gadd45g

Growth arrest and DNA damage-inducible gamma

4.59

− 2.92

Gpr3

G protein-coupled receptor 3

8.19

− 3.95

Hspa5

Heat-shock protein family A (Hsp70) member 5

1.64

− 1.41

Id1

Inhibitor of DNA binding 1, HLH protein

1.44

− 1.57

Igsf9b

Immunoglobulin superfamily member 9B

1.93

− 1.63

Inhba

Inhibin beta A subunit

5.76

− 3.41

Irs2

Insulin receptor substrate 2

6.01

− 3.00

Jun

Jun proto-oncogene, AP-1 transcription factor subunit

2.45

− 1.70

Junb

JunB proto-oncogene, AP-1 transcription factor subunit

7.83

− 3.28

Klf4

Kruppel like factor 4

2.00

− 1.60

Lmo1

LIM domain only 1

1.25

− 1.23

Midn

Midnolin

2.52

− 2.34

Ndufv1

NADH:ubiquinone oxidoreductase core subunit V1

1.19

− 1.21

Nfil3

Nuclear factor, interleukin 3 regulated

2.08

− 1.51

Npas4

Neuronal PAS domain protein 4

5.50

− 5.07

Nptx2

Neuronal pentraxin 2

4.96

− 2.70

Npy

Neuropeptide Y

1.72

− 2.23

Nr4a1

Nuclear receptor subfamily 4 group A member 1

4.27

− 2.15

Nr4a3

Nuclear receptor subfamily 4 group A member 3

10.26

− 4.16

Nrgn

Neurogranin

1.56

− 1.36

Pdxk

Pyridoxal kinase

1.93

− 1.69

Pdyn

Prodynorphin

2.50

− 1.75

Per1

Period circadian clock 1

2.18

− 1.87

Pim3

Pim-3 proto-oncogene, serine/threonine kinase

1.41

− 1.39

Plat

Plasminogen activator, tissue type

1.47

− 1.48

Ptgs2

Prostaglandin-endoperoxide synthase 2

5.15

− 3.08

Pvr

Poliovirus receptor

2.84

− 2.34

Rem2

RRAD- and GEM-like GTPase 2

5.42

− 2.82

Rheb

Ras homolog enriched in brain

1.49

− 1.18

Scg2

Secretogranin II

2.90

− 1.69

Sema7a

Semaphorin 7A (John Milton Hagen blood group)

1.30

− 1.27

Sertad1

SERTA domain containing 1

2.83

− 1.74

Sh3kbp1

SH3 domain containing kinase binding protein 1

− 1.15

1.13

Sik1

Salt-inducible kinase 1

3.10

− 2.08

Slc32a1

Solute carrier family 32 member 1

1.79

− 1.52

Srxn1

Sulfiredoxin 1

6.08

− 3.28

Stat3

Signal transducer and activator of transcription 3

1.13

− 1.13

Tac1

Tachykinin precursor 1

2.82

− 1.92

Vegfa

Vascular endothelial growth factor A

1.33

− 1.30

The proteins encoded by 43 of the 58 CREB1 target genes could be placed into a molecular landscape (Fig. 3). In the supplementary materials (Supplementary materials), all the protein interactions in this landscape are described in great detail. That being said, we here give a succinct description of the main processes and signaling cascades in the landscape. Importantly, as the main signaling “hub” in the landscape, CREB1 is a transcription factor that regulates the expression of many target genes involved in neuronal processes, such as neuronal survival, differentiation, and development. Further, there are three main landscape cascades in the nucleus. First, the AP-1 transcription factor complex—consisting of JUN, FOS, JUNB, and FOSB—binds and interacts with CREB1 and is regulated by and regulates the expression of a number of other landscape proteins, e.g., ATF3 and CREM. In addition, a complex of two functionally related transcription factors—NR4A1 and NR4A3, which regulate neuronal survival downstream of CREB1—interacts with the AP-1 complex and is regulated by extracellular molecules that are involved in (dopaminergic) apoptosis, such as CRH, TAC1, and VEGFA. The third important signaling cascade in the nucleus centers around the transcription factors of the GADD45 family that regulate the neuronal stress response and apoptosis and interact with other transcription factors like CCND3 and CDKN1A. Further, most other landscape proteins interact with two proteins/protein complexes that regulate neuronal apoptosis and can be found both in the nucleus and cytoplasm, i.e., ERK1/2 and the adaptor protein STAT3. The signaling cascades dependent on ERK1/2 and STAT3 are in turn modulated by a number of extracellular proteins—e.g., FGF13, PLAT, and SCG2—and cytoplasmic regulators—e.g., DUSP14, HSPA5, and IRS2—with prominent roles in neuronal function and survival.
Fig. 3

The molecular landscape is located in a neuron and shows the functional interactions between proteins encoded by 43 of the 58 CREB1 target genes regulated in the opposite direction by L-DOPA and after Riluzole co-administration in our AIMs model

qPCR Validation of Selected CREB1 Targets

To provide an additional validation of the RNA sequencing data, we performed qPCR to assess and compare the mRNA expression levels of 10 selected CREB1 targets. In Supplementary Fig. 4, the expression differences are shown for both comparisons (L-DOPA vs. saline and L-DOPA + Riluzole vs. L-DOPA). As we were able to validate 8 of the 10 tested mRNA expression differences and the two other differences were not statistically significant but still in the right direction, we submit that the RNA sequencing data, in general, and the expression data for the CREB1 targets, in particular, indeed reflect true expression changes.

Discussion

In the current study, we ascertained that 6-OHDA-lesioned rats treated with L-DOPA demonstrate clear AIMs and this is counteracted by chronic exposure to Riluzole, a drug that has already been shown to have some effect on attenuating AIMs in previous studies. Our experiments revealed that Riluzole induces mRNA expression changes in the rat striatum that are tightly linked to the occurrence of L-DOPA-induced AIMs.

Our findings point towards the regulation of apoptosis as a key molecular mechanism underlying both the effect of chronic L-DOPA administration—with the accompanying AIMs—and the “rebalancing” effect of Riluzole, leading to a reduction of AIMs. In general terms, the landscape that we built based on the CREB1 targets that were expressed in the opposite direction in the AIMs model and after Riluzole administration suggests that chronic administration of L-DOPA tilts the neuronal survival/apoptosis balance towards increased survival (and, hence, less apoptosis). Conversely, Riluzole administration leads to a reversal of this balance towards less survival and more apoptosis. Indeed, most of the landscape genes encode proteins that have anti-apoptotic properties, and these genes are upregulated after chronic L-DOPA administration, an effect that is counteracted by Riluzole. Mechanistically, as derived from the upstream regulator analysis, the effect of Riluzole is mediated through decreasing the activation of CREB1, i.e., CREB1 (and, hence, the regulation of its downstream targets) is predicted to be activated upon exposure to L-DOPA and inhibited after adding Riluzole. CREB1 acts as a functional “go-between” between cytoplasmic kinase/enzyme signaling cascades and nuclear regulation of gene expression. More specifically, CREB1 is known to be activated through phosphorylation by kinases, such as ERK1/2 [44] and protein kinase C (PKC) [45] (see subsequent texts), which in turn leads to reduced neuronal apoptosis through the upregulation of anti-apoptotic gene expression by activated CREB1 [46]. In addition, L-DOPA administration to 6-OHDA-lesioned rats was found to markedly increase CREB1 phosphorylation in striatal neurons [47, 48], and, interestingly, a very recent study showed that Riluzole reduces neuronal CREB1 phosphorylation [49].

As for how Riluzole would decrease CREB1 activity, there are some clues from the literature. Taken together with our results, these literature findings have led us to propose a putative molecular mechanism—shown in Fig. 4—through which Riluzole could decrease CREB1 activity, modulate apoptosis, and ultimately reduce AIMs. First, and as pointed out previously, Riluzole mainly exerts anti-glutamatergic effects which, through a number of mechanisms [27, 28, 29, 30, 31], lead to reduced glutamatergic neurotransmission. When activated by glutamate, post-synaptic NMDA receptors activate ERK1/2, kinases with an important role in our landscape that subsequently phosphorylate—and, hence, activate—CREB1 [44]. These data imply that through its anti-glutamatergic effects, Riluzole would decrease CREB1 activity by reducing NMDA receptor-induced ERK1/2 signaling. Second, Riluzole is a potent intracellular inhibitor of PKC [50], a kinase that positively regulates NMDA receptor function [51] and phosphorylates/activates CREB1, either directly or through activating ERK1/2 [45]. Although not shown in Fig. 4, a recent paper reported that Riluzole also reduces presynaptic glutamatergic vesicle recycling and, hence, the size of the readily releaseable glutamate pool through inhibiting PKC [31]. Further, it is interesting that glutamate-induced activation of CREB1 is (partially) blocked by inhibiting ERK1/2 with U0126 [52], a compound that, as opposed to CREB1, is predicted to be inhibited after exposure to L-DOPA and activated by adding Riluzole (see Supplementary Table 2).
Fig. 4

Putative mechanisms of how Riluzole could counteract CREB1-mediated gene expression by decreasing the activity of CREB1. Firstly, through a number of mechanisms, Riluzole reduces glutamatergic neurotransmission, which includes less glutamate binding to post-synaptic NMDA glutamate receptors. As a result, NMDA-mediated ERK1/2 signaling and the subsequent activation of CREB1 are also reduced. Secondly, Riluzole could inhibit PKC, a kinase that positively regulates NMDA receptors and activates CREB1 (directly or through activating ERK1/2), leading to a reduced CREB1 activity. The key players in this mechanism—L-DOPA, NMDA glutamate receptors, the kinases ERK1/2 and PKC, and CREB1 itself—are shown

Although our study yielded interesting findings, it has some limitations. First, while chronic L-DOPA administration is thought to be the main contributor to the AIMs phenotype through its effect on striatal projection neurons—i.e., through promoting dopamine receptor hypersensitivity in these neurons—lesioning with 6-OHDA affects dopaminergic as well as noradrenergic neurons. As such, a contribution of 6-OHDA-induced noradrenergic denervation to the AIMs phenotype cannot be excluded. In addition, although our results indicate that the effect of Riluzole on reducing AIMs is mediated through lowering CREB1 activity, further studies are needed to confirm that Riluzole (in)directly decreases CREB1 activity through reducing its phosphorylation. In this respect, it is interesting to note that the literature provides some corroborating evidence that phosphorylation-dependent CREB1 activation is indeed an important contributing factor to the development of AIMs. For example, psychostimulants, such as amphetamines and cocaine, and other drugs, such as the anti-psychotic aripiprazole—that are all known to induce AIMs [53, 54, 55]—promote phosphorylation-dependent CREB1 activation in (striatal) neurons [56, 57, 58]. Therefore, in addition to confirming the effect of Riluzole, future studies could test other (novel or existing) drugs for their positive effect on AIMs (and LID) through decreasing CREB1 activity.

In conclusion, we have demonstrated that Riluzole attenuates AIMs in 6-OHDA-lesioned rats that were chronically treated with L-DOPA. In addition, RNA sequencing analysis revealed that Riluzole reverses the expression direction of genes regulating mainly pro-apoptotic processes, downstream of activated CREB1. This molecular mechanism underlying the beneficial effect of Riluzole needs to be confirmed in future studies and can be leveraged to design AIMs/LID treatment studies using novel and/or existing compounds.

Notes

Acknowledgements

LP, EN, and JW were supported by the European Union Seventh Framework People Program (TS-EUROTRAIN (FP7-PEOPLE-2012-ITN), no 316978). CB was supported by the Merit-prize fellowship of Semmelweis University, the Bolyai János research fellowship of the Hungarian Academy of Sciences BO/00987/16/5, the ÚNKP-18-4 of the new National Excellence Program of the Ministry of Human Capacities and the Baron Munchausen Program of the Institute of Medical Chemistry, Molecular Biology and Pathobiochemistry, Semmelweis University. In addition, we thank Katrin Fundel-Clemens (Boehringer Ingelheim Pharma GmbH & Co., Germany) for her contribution to the analysis of the RNA sequencing data.

Author Contributions

LP, JW, EN, CB, BH, and GP conceived and designed the experiments. LP, JW, EN, and TH performed the experiments. LP, JW, EN, TH, and GP analyzed the data. LP, JW, EN, JG, BH, and GP wrote the paper. All the authors reviewed and approved the final version of the manuscript.

Compliance with Ethical Standards

Competing Interests

Boehringer Ingelheim Pharma GmbH & Co. provided support in the form of salary for authors BH and TH, but it did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Supplementary material

12035_2018_1433_MOESM1_ESM.docx (478 kb)
ESM 1 (DOCX 478 kb)
12035_2018_1433_MOESM2_ESM.xlsx (430 kb)
ESM 2 (XLSX 429 kb)

References

  1. 1.
    Maas R, Wassenberg T, Lin JP, van de Warrenburg BPC, Willemsen M (2017) L-Dopa in dystonia: a modern perspective. Neurology 88(19):1865–1871.  https://doi.org/10.1212/wnl.0000000000003897 CrossRefPubMedGoogle Scholar
  2. 2.
    Dekundy A, Lundblad M, Danysz W, Cenci MA (2007) Modulation of L-DOPA-induced abnormal involuntary movements by clinically tested compounds: further validation of the rat dyskinesia model. Behav Brain Res 179(1):76–89.  https://doi.org/10.1016/j.bbr.2007.01.013 CrossRefPubMedGoogle Scholar
  3. 3.
    Ahlskog JE, Muenter MD (2001) Frequency of levodopa-related dyskinesias and motor fluctuations as estimated from the cumulative literature. Mov Disord 16(3):448–458CrossRefGoogle Scholar
  4. 4.
    Huot P, Johnston TH, Koprich JB, Fox SH, Brotchie JM (2013) The pharmacology of L-DOPA-induced dyskinesia in Parkinson's disease. Pharmacol Rev 65(1):171–222.  https://doi.org/10.1124/pr.111.005678 CrossRefPubMedGoogle Scholar
  5. 5.
    Ahmed I, Bose SK, Pavese N, Ramlackhansingh A, Turkheimer F, Hotton G, Hammers A, Brooks DJ (2011) Glutamate NMDA receptor dysregulation in Parkinson's disease with dyskinesias. Brain 134(Pt 4):979–986.  https://doi.org/10.1093/brain/awr028 CrossRefPubMedGoogle Scholar
  6. 6.
    Chase TN, Oh JD (2000) Striatal mechanisms and pathogenesis of parkinsonian signs and motor complications. Ann Neurol 47(4 Suppl 1):S122–S129 discussion S129–130PubMedGoogle Scholar
  7. 7.
    Bordet R, Ridray S, Schwartz JC, Sokoloff P (2000) Involvement of the direct striatonigral pathway in levodopa-induced sensitization in 6-hydroxydopamine-lesioned rats. Eur J Neurosci 12(6):2117–2123CrossRefGoogle Scholar
  8. 8.
    Solis O, Garcia-Montes JR, Gonzalez-Granillo A, Xu M, Moratalla R (2017) Dopamine D3 receptor modulates L-DOPA-induced dyskinesia by targeting D1 receptor-mediated striatal signaling. Cereb Cortex 27(1):435–446.  https://doi.org/10.1093/cercor/bhv231 CrossRefPubMedGoogle Scholar
  9. 9.
    Charbonnier-Beaupel F, Malerbi M, Alcacer C, Tahiri K, Carpentier W, Wang C, During M, Xu D et al (2015) Gene expression analyses identify Narp contribution in the development of L-DOPA-induced dyskinesia. J Neurosci 35(1):96–111.  https://doi.org/10.1523/jneurosci.5231-13.2015 CrossRefPubMedGoogle Scholar
  10. 10.
    Santini E, Feyder M, Gangarossa G, Bateup HS, Greengard P, Fisone G (2012) Dopamine- and cAMP-regulated phosphoprotein of 32-kDa (DARPP-32)-dependent activation of extracellular signal-regulated kinase (ERK) and mammalian target of rapamycin complex 1 (mTORC1) signaling in experimental parkinsonism. J Biol Chem 287(33):27806–27812.  https://doi.org/10.1074/jbc.M112.388413 CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Song L, Zhang Z, Hu R, Cheng J, Li L, Fan Q, Wu N, Gan J et al (2016) Targeting the D1-N-methyl-D-aspartate receptor complex reduces L-dopa-induced dyskinesia in 6-hydroxydopamine-lesioned Parkinson's rats. Drug Des Devel Ther 10:547–555.  https://doi.org/10.2147/dddt.s93487 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Pavon N, Martin AB, Mendialdua A, Moratalla R (2006) ERK phosphorylation and FosB expression are associated with L-DOPA-induced dyskinesia in hemiparkinsonian mice. Biol Psychiatry 59(1):64–74.  https://doi.org/10.1016/j.biopsych.2005.05.044 CrossRefPubMedGoogle Scholar
  13. 13.
    Cerovic M, Bagetta V, Pendolino V, Ghiglieri V, Fasano S, Morella I, Hardingham N, Heuer A et al (2015) Derangement of Ras-guanine nucleotide-releasing factor 1 (Ras-GRF1) and extracellular signal-regulated kinase (ERK) dependent striatal plasticity in L-DOPA-induced dyskinesia. Biol Psychiatry 77(2):106–115.  https://doi.org/10.1016/j.biopsych.2014.04.002 CrossRefPubMedGoogle Scholar
  14. 14.
    Gerfen CR, Miyachi S, Paletzki R, Brown P (2002) D1 dopamine receptor supersensitivity in the dopamine-depleted striatum results from a switch in the regulation of ERK1/2/MAP kinase. J Neurosci 22(12):5042–5054CrossRefGoogle Scholar
  15. 15.
    Westin JE, Vercammen L, Strome EM, Konradi C, Cenci MA (2007) Spatiotemporal pattern of striatal ERK1/2 phosphorylation in a rat model of L-DOPA-induced dyskinesia and the role of dopamine D1 receptors. Biol Psychiatry 62(7):800–810.  https://doi.org/10.1016/j.biopsych.2006.11.032 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Heiman M, Heilbut A, Francardo V, Kulicke R, Fenster RJ, Kolaczyk ED, Mesirov JP, Surmeier DJ et al (2014) Molecular adaptations of striatal spiny projection neurons during levodopa-induced dyskinesia. Proc Natl Acad Sci U S A 111(12):4578–4583.  https://doi.org/10.1073/pnas.1401819111 CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Figge DA, Eskow Jaunarajs KL, Standaert DG (2016) Dynamic DNA methylation regulates levodopa-induced dyskinesia. J Neurosci 36(24):6514–6524.  https://doi.org/10.1523/jneurosci.0683-16.2016 CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Lundblad M, Usiello A, Carta M, Hakansson K, Fisone G, Cenci MA (2005) Pharmacological validation of a mouse model of L-DOPA-induced dyskinesia. Exp Neurol 194(1):66–75.  https://doi.org/10.1016/j.expneurol.2005.02.002 CrossRefPubMedGoogle Scholar
  19. 19.
    Marin C, Jimenez A, Bonastre M, Chase TN, Tolosa E (2000) Non-NMDA receptor-mediated mechanisms are involved in levodopa-induced motor response alterations in parkinsonian rats. Synapse 36(4):267–274.  https://doi.org/10.1002/(sici)1098-2396(20000615)36:4<267::aid-syn3>3.0.co;2-y CrossRefPubMedGoogle Scholar
  20. 20.
    Merims D, Ziv I, Djaldetti R, Melamed E (1999) Riluzole for levodopa-induced dyskinesias in advanced Parkinson's disease. Lancet 353(9166):1764–1765.  https://doi.org/10.1016/s0140-6736(99)00120-8 CrossRefPubMedGoogle Scholar
  21. 21.
    Bara-Jimenez W, Dimitrova TD, Sherzai A, Aksu M, Chase TN (2006) Glutamate release inhibition ineffective in levodopa-induced motor complications. Mov Disord 21(9):1380–1383.  https://doi.org/10.1002/mds.20976 CrossRefPubMedGoogle Scholar
  22. 22.
    Albo F, Pieri M, Zona C (2004) Modulation of AMPA receptors in spinal motor neurons by the neuroprotective agent riluzole. J Neurosci Res 78(2):200–207.  https://doi.org/10.1002/jnr.20244 CrossRefPubMedGoogle Scholar
  23. 23.
    De Sarro G, Siniscalchi A, Ferreri G, Gallelli L, De Sarro A (2000) NMDA and AMPA/kainate receptors are involved in the anticonvulsant activity of riluzole in DBA/2 mice. Eur J Pharmacol 408(1):25–34CrossRefGoogle Scholar
  24. 24.
    Fumagalli E, Funicello M, Rauen T, Gobbi M, Mennini T (2008) Riluzole enhances the activity of glutamate transporters GLAST, GLT1 and EAAC1. Eur J Pharmacol 578(2–3):171–176.  https://doi.org/10.1016/j.ejphar.2007.10.023 CrossRefPubMedGoogle Scholar
  25. 25.
    Wang SJ, Wang KY, Wang WC (2004) Mechanisms underlying the riluzole inhibition of glutamate release from rat cerebral cortex nerve terminals (synaptosomes). Neuroscience 125(1):191–201.  https://doi.org/10.1016/j.neuroscience.2004.01.019 CrossRefPubMedGoogle Scholar
  26. 26.
    Stevenson A, Yates DM, Manser C, De Vos KJ, Vagnoni A, Leigh PN, McLoughlin DM, Miller CC (2009) Riluzole protects against glutamate-induced slowing of neurofilament axonal transport. Neurosci Lett 454(2):161–164.  https://doi.org/10.1016/j.neulet.2009.02.061 CrossRefPubMedGoogle Scholar
  27. 27.
    Kretschmer BD, Kratzer U, Schmidt WJ (1998) Riluzole, a glutamate release inhibitor, and motor behavior. Naunyn Schmiedeberg's Arch Pharmacol 358(2):181–190CrossRefGoogle Scholar
  28. 28.
    Urbani A, Belluzzi O (2000) Riluzole inhibits the persistent sodium current in mammalian CNS neurons. Eur J Neurosci 12(10):3567–3574CrossRefGoogle Scholar
  29. 29.
    Kim JE, Kim DS, Kwak SE, Choi HC, Song HK, Choi SY, Kwon OS, Kim YI et al (2007) Anti-glutamatergic effect of riluzole: comparison with valproic acid. Neuroscience 147(1):136–145.  https://doi.org/10.1016/j.neuroscience.2007.04.018 CrossRefPubMedGoogle Scholar
  30. 30.
    Erickson JD (2017) Functional identification of activity-regulated, high-affinity glutamine transport in hippocampal neurons inhibited by riluzole. J Neurochem 142(1):29–40.  https://doi.org/10.1111/jnc.14046 CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Lazarevic V, Yang Y, Ivanova D, Fejtova A, Svenningsson P (2018) Riluzole attenuates the efficacy of glutamatergic transmission by interfering with the size of the readily releasable neurotransmitter pool. Neuropharmacology 143:38–48.  https://doi.org/10.1016/j.neuropharm.2018.09.021 CrossRefPubMedGoogle Scholar
  32. 32.
    Jehle T, Bauer J, Blauth E, Hummel A, Darstein M, Freiman TM, Feuerstein TJ (2000) Effects of riluzole on electrically evoked neurotransmitter release. Br J Pharmacol 130(6):1227–1234.  https://doi.org/10.1038/sj.bjp.0703424 CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Winkler C, Kirik D, Bjorklund A, Cenci MA (2002) L-DOPA-induced dyskinesia in the intrastriatal 6-hydroxydopamine model of parkinson's disease: relation to motor and cellular parameters of nigrostriatal function. Neurobiol Dis 10(2):165–186CrossRefGoogle Scholar
  34. 34.
    Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15–21.  https://doi.org/10.1093/bioinformatics/bts635 CrossRefPubMedGoogle Scholar
  35. 35.
    DeLuca DS, Levin JZ, Sivachenko A, Fennell T, Nazaire MD, Williams C, Reich M, Winckler W et al (2012) RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinformatics 28(11):1530–1532.  https://doi.org/10.1093/bioinformatics/bts196 CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Sayols S, Scherzinger D, Klein H (2016) dupRadar: a bioconductor package for the assessment of PCR artifacts in RNA-Seq data. BMC Bioinformatics 17(1):428.  https://doi.org/10.1186/s12859-016-1276-2 CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L (2013) Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotechnol 31(1):46–53.  https://doi.org/10.1038/nbt.2450 CrossRefPubMedGoogle Scholar
  38. 38.
    Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30(7):923–930.  https://doi.org/10.1093/bioinformatics/btt656 CrossRefPubMedGoogle Scholar
  39. 39.
    Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S et al (2015) Orchestrating high-throughput genomic analysis with Bioconductor. Nat Methods 12:115–121.  https://doi.org/10.1038/nmeth.3252 CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Law CW, Chen Y, Shi W, Smyth GK (2014) voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15(2):R29.  https://doi.org/10.1186/gb-2014-15-2-r29 CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Oliveros J VENNY. An interactive tool for comparing lists with Venn diagrams. BioinfoGP, CNB-CSIC. citeulike-article-id:6994833Google Scholar
  42. 42.
    Wu WS, Li WH (2008) Systematic identification of yeast cell cycle transcription factors using multiple data sources. BMC Bioinformatics 9:522.  https://doi.org/10.1186/1471-2105-9-522 CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    The UniProt Consortium (2017) UniProt: the universal protein knowledgebase. Nucleic Acids Res 45(D1):D158–D169.  https://doi.org/10.1093/nar/gkw1099 CrossRefGoogle Scholar
  44. 44.
    Marini AM, Jiang H, Pan H, Wu X, Lipsky RH (2008) Hormesis: a promising strategy to sustain endogenous neuronal survival pathways against neurodegenerative disorders. Ageing Res Rev 7(1):21–33.  https://doi.org/10.1016/j.arr.2007.07.003 CrossRefPubMedGoogle Scholar
  45. 45.
    Mao LM, Tang Q, Wang JQ (2007) Protein kinase C-regulated cAMP response element-binding protein phosphorylation in cultured rat striatal neurons. Brain Res Bull 72(4–6):302–308.  https://doi.org/10.1016/j.brainresbull.2007.01.009 CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Mantamadiotis T, Lemberger T, Bleckmann SC, Kern H, Kretz O, Martin Villalba A, Tronche F, Kellendonk C et al (2002) Disruption of CREB function in brain leads to neurodegeneration. Nat Genet 31(1):47–54.  https://doi.org/10.1038/ng882 CrossRefPubMedGoogle Scholar
  47. 47.
    Cole DG, Kobierski LA, Konradi C, Hyman SE (1994) 6-Hydroxydopamine lesions of rat substantia nigra up-regulate dopamine-induced phosphorylation of the cAMP-response element-binding protein in striatal neurons. Proc Natl Acad Sci U S A 91(20):9631–9635CrossRefGoogle Scholar
  48. 48.
    Oh JD, Chartisathian K, Ahmed SM, Chase TN (2003) Cyclic AMP responsive element binding protein phosphorylation and persistent expression of levodopa-induced response alterations in unilateral nigrostriatal 6-OHDA lesioned rats. J Neurosci Res 72(6):768–780.  https://doi.org/10.1002/jnr.10629 CrossRefPubMedGoogle Scholar
  49. 49.
    Akagi K, Yamada M, Saitoh A, Oka JI, Yamada M (2018) Post-reexposure administration of riluzole attenuates the reconsolidation of conditioned fear memory in rats. Neuropharmacology 131:1–10.  https://doi.org/10.1016/j.neuropharm.2017.12.009 CrossRefPubMedGoogle Scholar
  50. 50.
    Noh KM, Hwang JY, Shin HC, Koh JY (2000) A novel neuroprotective mechanism of riluzole: direct inhibition of protein kinase C. Neurobiol Dis 7(4):375–383.  https://doi.org/10.1006/nbdi.2000.0297 CrossRefPubMedGoogle Scholar
  51. 51.
    Lamanauskas N, Nistri A (2008) Riluzole blocks persistent Na+ and Ca2+ currents and modulates release of glutamate via presynaptic NMDA receptors on neonatal rat hypoglossal motoneurons in vitro. Eur J Neurosci 27(10):2501–2514.  https://doi.org/10.1111/j.1460-9568.2008.06211.x CrossRefPubMedGoogle Scholar
  52. 52.
    Perkinton MS, Ip JK, Wood GL, Crossthwaite AJ, Williams RJ (2002) Phosphatidylinositol 3-kinase is a central mediator of NMDA receptor signalling to MAP kinase (Erk1/2), Akt/PKB and CREB in striatal neurones. J Neurochem 80(2):239–254CrossRefGoogle Scholar
  53. 53.
    Lane EL, Brundin P, Cenci MA (2009) Amphetamine-induced abnormal movements occur independently of both transplant- and host-derived serotonin innervation following neural grafting in a rat model of Parkinson's disease. Neurobiol Dis 35(1):42–51.  https://doi.org/10.1016/j.nbd.2009.03.014 CrossRefPubMedGoogle Scholar
  54. 54.
    Jesic MP, Jesic A, Filipovic JB, Zivanovic O (2012) Extrapyramidal syndromes caused by antipsychotics. Med Pregl 65(11–12):521–526CrossRefGoogle Scholar
  55. 55.
    Maat A, Fouwels A, de Haan L (2008) Cocaine is a major risk factor for antipsychotic induced akathisia, parkinsonism and dyskinesia. Psychopharmacol Bull 41(3):5–10PubMedGoogle Scholar
  56. 56.
    Kreibich AS, Briand L, Cleck JN, Ecke L, Rice KC, Blendy JA (2009) Stress-induced potentiation of cocaine reward: a role for CRF R1 and CREB. Neuropsychopharmacology 34(12):2609–2617.  https://doi.org/10.1038/npp.2009.91 CrossRefPubMedPubMedCentralGoogle Scholar
  57. 57.
    Madsen HB, Navaratnarajah S, Farrugia J, Djouma E, Ehrlich M, Mantamadiotis T, Van Deursen J, Lawrence AJ (2012) CREB1 and CREB-binding protein in striatal medium spiny neurons regulate behavioural responses to psychostimulants. Psychopharmacology 219(3):699–713.  https://doi.org/10.1007/s00213-011-2406-1 CrossRefPubMedGoogle Scholar
  58. 58.
    Pan B, Huang XF, Deng C (2016) Chronic administration of aripiprazole activates GSK3beta-dependent signalling pathways, and up-regulates GABAA receptor expression and CREB1 activity in rats. Sci Rep 6:30040.  https://doi.org/10.1038/srep30040 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Luca Pagliaroli
    • 1
  • Joanna Widomska
    • 2
  • Ester Nespoli
    • 3
    • 4
  • Tobias Hildebrandt
    • 5
  • Csaba Barta
    • 1
  • Jeffrey Glennon
    • 2
  • Bastian Hengerer
    • 3
  • Geert Poelmans
    • 6
    Email author
  1. 1.Institute of Medical Chemistry, Molecular Biology and PathobiochemistrySemmelweis UniversityBudapestHungary
  2. 2.Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CenterNijmegenThe Netherlands
  3. 3.CNS DepartmentBoehringer Ingelheim Pharma GmbH & Co. KGBiberach an der RissGermany
  4. 4.Department of Child and Adolescent Psychiatry/PsychotherapyUniversity of UlmUlmGermany
  5. 5.Target DiscoveryBoehringer Ingelheim Pharma GmbH & Co. KGBiberach an der RissGermany
  6. 6.Department of Human GeneticsRadboud University Medical CenterNijmegenThe Netherlands

Personalised recommendations