Levodopa and Pramipexole induce different striatal expression profiles in an animal model of parkinsonism

CELIA LARRAMENDY; GERMÁN GONZÁLEZ; FLOOR SPAANS; MARIANO D SABORIDO; IRENE R. E. TARAVINI; M. GUSTAVO MURER; OSCAR S. GERSHANIK

Buenos Aires, Argentina

Congreso; 14th International Congress of Parkinson´s Disease and Movement Disorders; 2010

The Movement Disorder Society

Objective: To compare the gene expression profiles induced by L-dopa or pramipexole (PRA) in the lesioned striatum of rats with a moderate lesion of the nigrostriatal pathway. Background: Both L-dopa and PRA are widely used Parkinson´s disease (PD) clinics. Initially L-dopa works sufficiently against the symptoms of PD; however, when taken for long periods of time, L-dopa has been known to induce dyskinesias. Lower risks of dyskinesias are observed when D2 dopamine receptor agonists, like PRA, are used. PRA has been successfully used to treat the symptoms of PD at its early stages. However, their therapeutic benefit tends to be less when compared to L-dopa. Although there have been several studies published on the gene expression profile induced by the nigrostriatal dennervation and by L-dopa therapy in patients, and in animal models, only a few have dealt with the gene expression profile induced by dopamine agonists. Methods: Rats with readily identifiable motor deficiencies were randomly assigned to receive during 3 weeks water (LW), L-dopa 170 mg/kg (LL), or PRA 3.5 mg/kg (LP). Normal rats were treated with water as a control group (NW). Drugs were dissolved in the animal’s drinking water. The doses employed were chosen to be capable of causing comparable improvement of contralateral forepaw akinesia in the cylinder test during the third week of treatment. Messenger RNA was isolated from the lesioned striata and pooled to interrogate Affymetrix Rat Gene 1.0 ST covering all known rat genomic transcripts. The probes sets were summarized and normalized by the Robust Multichip Average algorithm. Differentially expressed genes between conditions and controls were determined using the empirical Bayes moderated t-test in the Bioconductor package Linear Models for Microarray Data. All analyses were performed using the open-source R programming environment (version 2.10.0) in conjunction with the open-source Bioconductor software (version 2.6.0). Results: Microarray profiling identified several genes that were differentially expressed between the LL and the LP groups. Sets of co-regulated genes are visualized in a heatmap. Between these genes we have identified some dopamine related genes and genes related to mitochondrion, ribosomal and proteosome function. Conclusions: We hope to further identify key transcripts and metabolic pathways related to the therapeutic effects, as well as those possibly related to neuroprotection, plasticity and dyskinesias.