Beneficial behavioral, neurochemical and molecular effects of 1-(R)-aminoindan in aged mice

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Beneficial behavioral, neurochemical and molecular effects of 1-(R)-aminoindan in aged mice

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Felix Badinter, Tamar Amit, Orit Bar-Am, Moussa B.H. Youdim, Orly Weinreb* Eve Topf Centers of Excellence for Neurodegenerative Diseases Research, Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel

a r t i c l e i n f o

a b s t r a c t

Article history: Received 1 February 2015 Received in revised form 26 May 2015 Accepted 28 May 2015 Available online xxx

Previous neuroprotective studies demonstrated that 1-(R)-aminoindan (AI), which is the major metabolite of the anti-Parkinsonian drug rasagiline, possesses beneficial pharmacological effects in various cell culture and animal models of neurodegeneration. The present study was aimed at investigating the possible neuroprotective effects of AI on cognitive impairments and neurochemical alterations in aged mice. Our findings provide evidence that following chronic systemic treatment with AI (5 mg/kg; daily; 3 months) of aged mice (24 months old), the compound exerted a significant positive impact on neuropsychiatric functions of cognitive behavior deficits, assessed in a variety of tasks (spatial learning and memory retention, working memory, learning abilities and nest building behavior) and produced an antidepressant-like effect. In addition, chronic AI treatment significantly enhanced expression levels of neurotrophins, including BDNF and nerve growth factor (NGF), tyrosine kinase- B (Trk-B) receptor and synaptic plasticity markers, such as synapsin-1 and growth-associated protein-43 (GAP-43) in the striatum and hippocampus in aged mice. Our results also indicate that AI treatment up-regulated the expression levels of the pro-survival Bcl-2 mRNA, increased the anti-apoptotic index Bcl-2/Bax and enhanced the activity of the antioxidant enzyme catalase in the brain of aged mice. These effects of AI were also confirmed in aged rats (24 months old). Altogether, the present findings indicate that AI can induce neuroprotective effects on age-related alterations in neurobehavioral functions and exerts neurotrophic up-regulatory and anti-apoptotic properties in aged animals. © 2015 Published by Elsevier Ltd.

Keywords: 1-(R)-aminoindan Aging Cognition Depressive-like behavior Neuroprotection Neurotrophic factors Chemical compounds: 1-(R)-aminoindan (PubChem CID: 123445)

1. Introduction Rasagiline (Azilect®) is a second generation, highly potent, selective, irreversible monoamine oxidase (MAO)-B inhibitor, antiParkinsonian drug (Olanow et al., 2008, 2009; Schapira, 2006;

Abbreviations: AI, 1-(R)-aminoindan; 3-MT, 3-methoxytyramine; 5-HIAA, 5hydroxyindoleacetic acid; 5-HT, serotonin; BDNF, brain derived neurotrophic factor; BBB, blood brain barrier; COMT, Catechol-O-methyltransferase; DOPAC, 3,4dihydroxyphenylacetic acid; DA, dopamine; DRD1, dopamine receptor D1; DRD2, dopamine receptor D2; FST, forced swimming test; GAP-43, growth-associated protein-43; GDNF, glial cell line-derived neurotrophic factor; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; 6-OHDA, 6-hydroxydopamine; HPLC, high performance liquid chromatography; HVA, homovanillic acid; MAO, monoamine oxidase; MWM, Morris Water Maze; NE, noradrenaline; NGF, nerve growth factor; OS, oxidative stress; PD, Parkinson's disease; ROS, reactive oxygen species; Trk-B, tyrosine kinase- B; TST, tail suspension test. * Corresponding author. Eve Topf Center, Faculty of Medicine, Technion-Israel Institute of Technology, P.O.B. 9697, 31096 Haifa, Israel. Tel.: þ972 4 8295290; fax: þ972 4 8513145. E-mail address: [email protected] (O. Weinreb).

Weinreb et al., 2010; Youdim et al., 2001). Unlike the first generation MAO-B inhibitor selegiline, which is metabolized to the neurotoxic metabolite methamphetamine, rasagiline is primarily metabolized to its major metabolite 1-(R)-aminoindan (AI), by hepatic cytochrome P-450 isoenzyme 1A2-mediated N-dealkylation, which is devoid of amphetamine-like properties (Chen and Swope, 2005; Chen et al., 2007). AI has been demonstrated to possess a wide range of neuroprotective effects in cell culture and animal models of neurodegeneration (Bar-Am et al., 2010). Thus, AI exerted neuroprotective effects against the Parkinsonian neurotoxin, 6-hydroxydopamine (6-OHDA) in PC-12 cells and hydrogen peroxide (H2O2)-induced oxidative stress in SH-SY5Y cells and rat primary cortical neurons (Bar-Am et al., 2010); prevented cell death in the cytotoxic model of high density SK-N-SH cell cultures (Bar-Am et al., 2007) and decreased ethanol-induced apoptosis in SH-SY5Y cells (Ou et al., 2009, 2010). These studies characterized various molecular mechanisms of action that may be associated with the neuroprotective activity of AI, including upregulation of anti-apoptotic Bcl-2 family proteins, reduction of phosphorylated H2A.X and cleaved levels of caspases 3 and 9 and

http://dx.doi.org/10.1016/j.neuropharm.2015.05.041 0028-3908/© 2015 Published by Elsevier Ltd.

Please cite this article in press as: Badinter, F., et al., Beneficial behavioral, neurochemical and molecular effects of 1-(R)-aminoindan in aged mice, Neuropharmacology (2015), http://dx.doi.org/10.1016/j.neuropharm.2015.05.041

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induction of phosphorylated protein kinase C (Bar-Am et al., 2007). In vivo studies demonstrated that chronic administration of AI reversed motor behavioral asymmetry and restored striatal catecholamine levels in rat models of Parkinson's diseases (PD), the 6-OHDA- and lactacystin-induced nigrostriatal degeneration (Weinreb et al., 2011). In addition, AI significantly antagonized amethyl-p-tyrosin-induced hypokensia and improved cognition and memory deficits in hypoxic rats (Speiser et al., 1998). The present study was aimed to address the effects of AI on agerelated behavioral impairments, including spatial learning and memory function and depressive-like behavior in aged mice. In accordance, we have also determined the effect of AI on the levels of biogenic amines and expression of neurotrophic, synaptic factors and Bcl-2 family members involved in age-related cognitive decline. 2. Material and methods 2.1. Materials The MD-TM Mobile Phase, for analysis of monoamines and metabolites in high performance liquid chromatography (HPLC) system, was purchased from Thermo Fisher Scientific Inc. (Waltham, MA, USA). Bradford reagent and the monoamines: dopamine (DA), homovanilic acid (HVA), 3,4-dihydroxyphenylacetic acid (DOPAC), 3-methoxytyramine (3-MT), serotonin (5-HT), 5-hydroxyindoleacetic acid (5-HIAA) and noradrenaline (NE) were purchased from Sigma Chemical Co. (St Louis, MO, USA). Catalase from bovine liver was purchased from Calbiochem® (Merck KGaA, Darmstadt, Germany). For the MAO activity assay, phenylethylamine HCl, trans-2phenylcyclopropylamine HCl (TCP), clorgyline HCl and deprenyl HCl were purchased from Sigma Chemical Co. (St Louis, MO, USA). The [14C]Phenylethylamine HCl (specific activity 43.8 mCi/mmol) and [14C]5-HT binoxalate (specific activity 56.5 mCi/mmol) were purchased from Perkin Elmer (Boston, MA, USA). Other chemicals and reagents were of the highest analytical grade and were purchased from local commercial sources. Primers for real-time RT-PCR were purchased from QIAGEN Ltd (Germany). Rabbit monoclonal antibody against brain derived neurotrophic factor (BDNF) was purchased from Epitomics Inc. (Burlingame, CA, USA). An antibody against b-tubulin was purchased from Sigma Chemical Co. (St Louis, MO, USA). AI (PubChem CID 123445) was kindly supplied by Teva Pharmaceuticals Industries Ltd (Netanya, Israel).

trial. To assess memory consolidation, a probe trial was performed after platform training trials. In this trial, the platform was removed from the tank, and mice were allowed to swim freely. For these tests, time spent in the target quadrant within 60 s was recorded. All trials were monitored by a video camera positioned above the pool and the behavior of each mouse is acquired by a computerized video-tracking system (Smart JUNIOR, Panlab, Spain). 2.3.2. Object recognition test Mice were trained and tested in the novel object recognition task, as previously described (de Lima et al., 2005; de Lima et al., 2008). The object recognition test required that the mice recalled which of the two objects they had been previously familiarized with. 24 h after arena exploration, training was conducted by placing individual mouse into the field, in which two identical objects (objects A1 and A2) were positioned in two adjacent corners. Mice were left to explore the objects until they had accumulated 30 s of total object exploration time or for a maximum of 20 min. In a short-term memory test, given 1.5 h after training, the animal explored the open field for 5 min in the presence of one familiar (A) and one novel (B) object. In the long-term memory test, given 24 h after training, the same animal explored the field for 5 min in the presence of a familiar object (A) and a novel object (C). All objects presented similar textures, colors, and sizes, but distinctive shapes. A recognition index was calculated for each animal and expressed by the ratio TB/(TA þ TB). A discrimination index was calculated as the difference between the time spent exploring new (TB) and old (TA) object divided by the total time spent exploring the objects (TB  TA)/ (TB þ TA) (Wiescholleck et al., 2014). 2.3.3. Depressive-like behavior test the tail suspension test (TST) in mice was performed according to the method described previously (Cryan et al., 2005). The mice were individually suspended in the hook of the tail suspension test box, 40 cm above the surface of table with an adhesive tape placed three quarters of the distance from the base of the tail. After 2 min acclimatization, immobility duration was recorded for 4 min. 2.3.4. Nest building test to evaluate the quality of nest construction, mice were individually housed overnight, with food, water and sawdust bedding. On the first day of testing, two pieces of cotton (5  5 cm, Nestlets; Ancare, Bellmore, NY), from which the mice could make nests, were placed in each cage. The presence and quality of nesting were rated on the following day by using a 5-point scale ranging from 1 to 5, as follows: 0, no nest; 1, flat nest; 2, nestlet partially torn up; 3, mostly shredded but often no identifiable nets site; 4, an identifiable but flat nest and 5, perfect nest (Deacon et al., 2002).

2.2. Animal treatment procedures All procedures were carried out in accordance with the National Institutes of Health Guide for care and Use of Laboratory Animals, and were approved by the Animal Ethics Committee of the Technion, Haifa, Israel. Animals were kept 3e4 per cage on a 12 h light/dark cycle with food and water available ad libitum. The dose of AI was chosen on the basis of previous studies (Weinreb et al., 2011). Control young (6 months-old) and aged (24 months-old) male C57Bl/6J mice were obtained from Harlan Laboratories, Inc. (Israel). AI (5 mg/kg) or vehicle (water) were p.o. daily administered to aged mice (7e10 mice per each experimental group) for 3 months. Aged (24 months-old) male Sprague Dawley rats were obtained from Harlan Laboratories, Inc (Israel). AI (5 mg/kg) or vehicle (saline) were s.c daily administered to aged rats (6e7 rats per each experimental group) for 3 months. In all experimental protocols, animals were weighted once a week, and no significant change in body weight was observed during treatment period. At the end of the experiment, the animals were killed by decapitation and brains were dissected and stored at 80  C for further biochemical analyses. 2.3. Behavioral tests With the aim of assessing the effects of the drug on cognition and depression, behavioral studies were performed 2e3 weeks before the end of drug treatment, as followed: 2.3.1. Morris water maze test Spatial learning and memory were assessed in mice, using the Morris Water Maze (MWM) test, as previously described (Morris, 1984). Briefly, we used a circular tank (120 cm diameter  50 cm height) filled to a depth of 25 cm with tepid water and a white escape platform (10 cm diameter). The surface area of the tank was divided into four equal quadrants. The water was made opaque by addition of milk powder, and its temperature was adjusted to 23e26  C. Mice were gently released into the water, always facing the tank wall, and given 60 s to find the platform. On reaching the platform, the mice were allowed to remain on it for 20 s. The training schedule consisted of 7 consecutive days of testing. During the 2 first days of testing, the mice were training with visible platform for three 60 s trials per day. During the 4 following days of testing, the mice were trained with hidden platform for three 60 s trials per day. Each subsequent trial was starting at a different direction for each

2.4. Analysis of amine levels The content of striatal DA and its metabolites, DOPAC, HVA and 3-MT; NE; 5-HT and its metabolite, 5-HIAA was determined by HPLC system (ESA, Inc. USA), as previously reported (Gal et al., 2005). The levels were calculated by comparison to monoamine standards in known concentrations and normalized relative to tissue weight. 2.5. MAO activity assay The cerebellum was homogenized using a glass Teflon homogenizer in icecold sucrose buffer (10 mM TriseHCl) buffer, pH 7.4, containing 0.32 M sucrose, followed by the addition of sucrose buffer to a final concentration of 1 mL homogenate. The homogenates were centrifuged at 300  g for 2 min at 4  C. The supernatant fraction was removed and used to determine MAO activity. MAO-A and -B activities were measured according to Tipton et al. (Tipton et al., 1982). Protein homogenate was added to a suitable dilution of the enzyme preparation and incubated with [C14]serotonin (5-HT) for 30 min (final concentration 100 mM) as a substrate for MAO-A, or with [C14]phenylethylamine (PEA) for 20 min (final concentration 100 mM) as a substrate for MAO-B. The reaction was stopped with ice-cold citric acid (2 M) and radioactivity was determined by liquid scintillation counter. 2.6. Quantitative real-time RT-PCR Isolation of striatal and hippocampal RNA was performed using PurfectPure RNA Cultured Cell Kit (50 PRIME Inc., MD, USA), as recommended by the manufacturer, and reverse transcribed by using PrimeScript RT reagent kit (Takara Bio Inc. Korea). Real-Time PCR was performed with specific primers, for the genes in search (including, dopamine receptor D1 (DRD1), dopamine receptor D2 (DRD2), brain derived neurotrophic factor (BDNF), nerve growth factor (NGF), tyrosine kinase- B (Trk-B) receptor, synapsin-1, growth-associated protein-43 (GAP-43), Bcl-2, Bax, and Glial cell line-derived neurotrophic factor (GDNF) purchased from QIAGEN Ltd Germany) on the provided program of 7500 Real time PCR system and SYBR premix Ex Taq ll (Hot Start; Takara Bio Inc.) The relative expression level of a given mRNA was assessed by normalizing to the housekeeping genes b-actin and g-tubulin, compared with control values.

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F. Badinter et al. / Neuropharmacology xxx (2015) 1e9 2.7. Western blotting analysis Samples were homogenized with homogenization buffer pH ¼ 7.4 (containing a mixture of protease inhibitors, Roche, Inc. and phosphatase inhibitors), separated by SDS-PAGE (4e12% Bis-Tris gels) and blotted on Protran nitrocellulose membrane (Schleicher & Schuell, Dassel, Germany), as previously described cultures (Bar-Am et al., 2007). Protein content was determined using the Bradford method. Detection was achieved using Western blotting detection reagent, ECL system (Amersham Pharmacia, Little Chalfont, Buckinghamshire, UK). Quantitation of the labeled bands in the autoradiograms was accomplished by measuring the optical density, using the computerized imaging program Bio-1D (Vilber Lourmat Biotechnology, Marne de Vallee, France). 2.8. Catalase enzyme activity assay Catalase activity was measured according to the assay previously described (BarAm et al., 2009). The measurement of catalase activity is based on monitoring of H2O2 breakdown using spectrophotometer at 240 nm. The reaction mixture contained 0.033 M H2O2 in 0.05 M phosphate buffer pH 7.0. One unit of enzyme was defined as 1 mM of H2O2 cleaved per min at 25  C and defined as relative activities (% of controls). 2.9. AI levels in aged rat brain and liver Determination of AI levels in cerebellum, brain stem and liver of aged rats, following chronic s.c. administration (1 and 5 mg/kg, daily for 3 months), was performed in the Bioanalytical Laboratory, Teva Pharmaceutical Works P. Ltd. Co. (Hungary), using liquid chromatography/mass spectrometry (LC/MS) analysis, as described in AZILECT; Product Monograph, control no: 13427, 2010 (Teva Pharmaceutical Industries Ltd. Netanya, Israel). 2.10. Statistical analyses All values are expressed as means ± SEM. For analyses, either one-way or twoway analysis of variance (ANOVA) with Dannet's for one-way and Bonferroni for two-way post-hoc tests were used. Normal distribution and homogeneity of variance were found for all analyzed categories. P-Values less than 0.05 were considered as statistically significant. Statistical analyses were done by using GraphPad Prism program (version V, La Jolla, California, USA).

3. Results 3.1. AI attenuates cognitive deficits and depressive-like behavior in aged mice The possible beneficial effect of AI (5 mg/kg) on spatial learningmemory deficits in aged mice was initially examined in the MWM test, one of the most accepted behavioral tests of the hippocampal cognitive functions (Morris, 1984). Spatial learning was assessed by the time required to find the hidden platform (escape latency). When comparing aged vs. young mice, the results showed impaired acquisition of spatial learning in vehicle-treated aged, compared with vehicle-treated young mice, as indicated by longer duration to locate the hidden platform across consecutive trials. On the 4th day, the escape latency of aged mice was longer than that of the young mice (Fig. 1A). Chronic AI (5 mg/kg) treatment ameliorated the performance deficits in aged mice during the testing period with the hidden platform (Fig. 1A). As shown in Fig. 1B, there was no significant difference on swimming velocity among AI-and vehicletreated aged mice across the 4 training days. Probe trials, in which the platform was removed to assess spatial bias, are shown in Fig. 1C. The time spent in the target quadrant was markedly decreased in vehicle-treated aged, as compared to vehicle-treated young mice. Chronic AI treatment significantly attenuated the decrease in acquisition phase of place learning and improved memory retention during the probe trial (Fig. 1C). In addition to the effect of AI on spatial learning and memory measured by the MWM test, the effect of AI on non-spatial learning and memory was assessed by the novel object recognition test. In the novel object recognition test, vehicle-treated aged mice showed significantly lower preference towards the novel object, compared with vehicle-treated young mice, as indicated in discrimination and recognition indexes, in short- and long-term memory retention

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trials (Fig. 2A and B, respectively). However, AI (5 mg/kg)-treated animals exhibited a higher preference in exploring the novel object, than vehicle-treated aged mice, as their discrimination and recognition indexes were significantly higher than those of the vehicletreated aged group, during the short-term memory retention (Fig. 2A) and long-term memory retention (Fig. 2B) trials. Taken together, these data, obtained from MWM and novel object recognition tests, indicate that AI chronic treatment significantly improved spatial and non-spatial learning and memory deficits in aged mice, compared with vehicle-treated aged mice. The possible antidepressant action of AI in aged mice was analyzed by the TST, one of the most widely used models for assessing pharmacological antidepressant-like effects (Cryan et al., 2005). Results for the TST demonstrated a significant elevation of time spent in immobility in the vehicle-treated aged mice, compared to vehicle-treated young mice (Fig. 3A). Chronic treatment with AI significantly reversed the effect of aging on the duration immobility time in TST (Fig. 3A). Nesting behavioral is an ethnological assay of normal behavior of mice and may evaluate step-by-step planning and organization (multistep problem solving) and reflect initiative, curiosity or apathy (Deacon et al., 2002; Chung and Cummings, 2000). The results for nesting behavioral test followed by analysis of nesting scores revealed that nesting was impaired in vehicle-treated aged mice, in comparison with vehicle-treated young mice (Fig. 3B). A significantly improved nesting behavior has been observed in aged mice treated with AI, compared with vehicle-treated aged mice (Fig. 3B). 3.2. Regulatory effects of AI on striatal amines and metabolites and expression levels of DRD1 and DRD2 in aged mice The effect of chronic AI administration on the levels of amines and metabolites (DA, DOPAC, HVA, 3-MT, 5-HT, 5-HIAA and NE) was further examined in the striatum of aged mice. As shown in Fig. 4A, treatment with AI (5 mg/kg) significantly elevated striatal levels of DA and the extraneuronal metabolite 3-MT, compared to vehicletreated aged mice; the ratio DOPAC/DA (MAO-associated oxidative pathway) was significantly decreased by AI, thus indicating a decreased intraneuronal DA metabolism in the striatum; AI treatment also significantly increased 3-MT/DOPAC ratio (a DA reuptake index). In addition, AI treatment significantly increased 5-HT levels and reduced 5-HT turnover, as assessed by the 5-HIAA/5-HT ratio, compared to vehicle-treated aged mice (Fig. 4B). No significant effect on striatal NE levels was detected following AI administration, compared with vehicle-treated aged mice (Fig. 4C). Furthermore, it was observed that AI (5 mg/kg) administrated to aged mice had no significant inhibitory effect on brain MAO-A and MAO-B activities: 0.5 ± 0.2% and 7.6 ± 2.8%, respectively, compared to vehicle-treated aged mice. As it was reported that the dopaminergic system could regulate the expression of DA receptors (Jaber et al., 1996), we analyzed the effect of AI on mRNA expression of DRD1 and DRD2 in the striatum of aged mice. The administration of AI (5 mg/kg) significantly upregulated the striatal DRD1 expression levels (1.52 ± 0.12 folds; p < 0.05) vs. vehicle-aged mice; no changes in striatal DRD2 expression levels was found following the treatment with AI, compared to vehicle aged animals (1.06 ± 0.09 folds). 3.3. Effect of AI on mRNA expression levels of neurotrophic/synaptic factors and Bcl-2 family members, and catalase activity in aged mice Real-time RT-PCR revealed that AI (5 mg/kg) significantly upregulated mRNA expression levels of Trk-B receptor and synapsin-1 in the striatum of aged mice, compared to vehicle-

Please cite this article in press as: Badinter, F., et al., Beneficial behavioral, neurochemical and molecular effects of 1-(R)-aminoindan in aged mice, Neuropharmacology (2015), http://dx.doi.org/10.1016/j.neuropharm.2015.05.041

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Fig. 1. Effect of AI on spatial learning and memory of aged mice in MWM test. The analyses of MWM were consisted of: A. Platform latencies in visible- and hidden-platform versions; B. Swim velocity and C. Time percentage spending in the target quadrant in the probe trial. Values represent mean ± SEM of 4 trials (n ¼ 7e10). Treatment effect (F(2,22) ¼ 8.07, p ¼ 0.0024); Day effect (F(3,66) ¼ 4.29, p ¼ 0.008). #p < 0.05 vs. vehicle-treated young mice; *p < 0.05 vs. vehicle-treated aged mice.

treated aged mice (Fig. 5A). In addition, mRNA expression levels of the neurotrophins, BDNF and NGF, Trk-B receptor, synapsin-1 and GAP-43 in the hippocampus of aged mice were significantly increased following AI treatment, as compared to vehicle-treated aged mice (Fig. 5B). AI also down-regulated mRNA expression levels of striatal pro-apoptotic Bax (Fig. 6A) and up-regulated hippocampal mRNA expression levels of the anti-apoptotic Bcl-2 (Fig. 6B) in aged mice, as compared to vehicle-treated aged mice. The ratio of Bcl-2 to Bax, which correlates with cellular apoptosis, was significantly increased in the striatum and hippocampus of AItreated vs. vehicle-treated aged mice (Fig. 6). Additionally, chronic AI administration (5 mg/kg) significantly enhanced the enzyme activity of catalase in the frontal cortex of AItreated aged mice, compared to vehicle-treated aged mice (Fig. 7). 3.4. Neurochemical and molecular effects of AI in aged rats Regulatory effects of AI (5 mg/kg) on the levels of amines and metabolites in the striatum of aged rats are demonstrated in Supplementary Table 1. No significant inhibition of brain MAO-A and MAO-B activities was found following AI (5 mg/kg) treatment (3.15 ± 0.72% and 4.57 ± 1.46%, respectively) in aged rats, compared to vehicle-treated aged rats. Effects of AI (5 mg/kg) on mRNA expression levels of DRD1 and DRD2, neurotrophic factors and Bcl2 family members in the striatum and hippocampus of aged rats are shown in Supplementary Table 2. AI administration significantly up-regulated the striatal mRNA expression of DRD1 and DRD2 in

aged rats. In addition, AI treatment significantly up-regulated mRNA expression levels of striatal and hippocampal BDNF and synapsin-1, striatal GDNF and Trk-B receptor and striatal and hippocampal Bcl-2 (Supplementary Table 2). The ratio of striatal Bcl-2/ Bax (1.66 ± 0.18 folds; p < 0.05) was increased in AI-treated, as compared to vehicle-treated aged rats. Supplementary Fig.1 also demonstrates that hippocampal BDNF protein levels were increased following AI (5 mg/kg) treatment in aged rats, compared to vehicle-treated aged rats. To assess the brain penetration ability of AI following systemic administration of AI (1 and 5 mg/kg, s.c) for 3 months, we have measured the levels of AI in the cerebellum and brain stem in aged rats. AI could be delivered to the brain after chronic systemic drug administration, indicating that the compound exhibits penetration across the blood brain barrier (BBB) (Supplementary Table 3). The levels of AI in the cerebellum and brain stem were proportional to the drug dosing, with no significant differences at both brain regions; similar AI levels were found in the liver (Supplementary Table 3). In addition, AI administration (5 mg/kg) significantly increased the enzyme activity of catalase in the frontal cortex (3.31 ± 0.52 folds; p < 0.05) vs. vehicle-aged rats. 4. Discussion Previous neuroprotective studies demonstrated that the major metabolite of the anti-Parkinsonian drug rasagiline(Azilect®), AI possesses beneficial pharmacological effects in various cell culture

Please cite this article in press as: Badinter, F., et al., Beneficial behavioral, neurochemical and molecular effects of 1-(R)-aminoindan in aged mice, Neuropharmacology (2015), http://dx.doi.org/10.1016/j.neuropharm.2015.05.041

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Fig. 2. Effect of AI on memory acquisition of aged mice in novel object recognition test. The novel object recognition test was performed in: A. short (1.5 h after training) and B. longterm retention (24 h after training). The discrimination and recognition indexes were calculated as described in Material and Methods section. Each bar represents the mean ± SEM of 4 trials (n ¼ 7e10). #p < 0.05 vs. vehicle-treated young mice; *p < 0.05 vs. vehicle-treated aged mice.

and animal models of PD, including the 6-OHDA- and lactacystininduced dopaminergic neurodegeneration models (Abu-Raya et al., 2002; Bar-Am et al., 2004, 2007; Speiser et al., 1998; Weinreb et al., 2011). Also, it was reported that AI decreased ethanol-

induced cell death (Ou et al., 2009) and could prevent dexamethasone-induced neuronal apoptosis (Tazik et al., 2009). The present study was undertaken to investigate, for the first time, the possible neuroprotective effects of AI in aging mice. Our

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Fig. 3. Behavioral effects of AI in the TST and nesting behavior in aged mice. A. The immobility time (s) in TST and B. presence and quality of nesting, rated on a 5-point scale. Each bar represents the mean ± SEM of 3 trials (n ¼ 7e10). #p < 0.05 vs. vehicle-treated young mice; *p < 0.05 vs. vehicle-treated aged mice.

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Fig. 4. Chronic effect of AI on striatal levels of amines and their metabolites in aged mice. Aged mice were treated with either vehicle or AI (5 mg/kg; p.o. daily) for 3 months. A. The levels of striatal of DA and its metabolites, DOPAC, HVA and 3-MT were determined by using HPLC analysis. DA metabolism was expressed as the following ratios of: DOPAC/DA, HVA/DA and 3-MT/DA and inhibition of DA reuptake was expressed as the ratio of 3-MT/DOPAC. B. The levels of striatal 5-HT and its major metabolite 5-HIAA were determined by using HPLC analysis. 5-HT metabolism was expressed as the ration of 5-HIAA/5-HT. Results represent mean ± SEM (n ¼ 7e10). #p < 0.05, vs. vehicle-treated young mice; *p < 0.05, vs. vehicle-treated aged mice.

findings provide evidence that following chronic systemic treatment of aged mice with AI (5 mg/kg), the drug exerted a significant positive impact on neuropsychiatric functions of cognitive behavior deficits, assessed in a variety of tasks (spatial learning and memory retention, working memory, learning abilities and nesting behavior) and produced an antidepressant-like effect, analyzed by the TST. Further biochemical and pharmacological determination of the potential neuroprotective-associated targets, regulated by AI in the brain of aged mice provided the following observations: 1. Chronic AI treatment significantly enhanced the expression levels of neurotrophins (BDNF and NGF), Trk-B receptor and synaptic plasticity markers (synapsin-1 and GAP-43) in the striatum and hippocampus. 2. AI up-regulated the expression levels of the pro-survival Bcl-2, which is in keeping with previous studies demonstrating that AI increased mRNA expression of Bcl2 and Bcl-xL, while reduced those of the death-related genes Bad and Bax in primary cortical cells (Bar-Am et al., 2010). It was indicated that the protein kinase C (PKC) signaling cascade is essential for AI-induced neuronal protective effect (Bar-Am et al., 2007). 3. We observed a significant increase in the activity of the antioxidant enzyme catalase in the brain of AI-treated, compared with vehicle-treated aged mice. This is consisted with previous in vitro findings demonstrating that AI significantly increased catalase enzymatic activity and protected neurons from H2O2induced oxidative stress (Weinreb et al., 2011). Additionally, It

was shown that AI induced mRNA expression levels of catalase, peroxiredoxin 1 and NAD(P)H quinone oxidoreductase 1 in neuronal cell cultures (Weinreb et al., 2011). These effects of AI were also confirmed in aged rats. The neuroprotective effects of AI may be resulted, at least in part, from the presence of the compound in the brain, as our LC/MS results showed considerable AI levels in the cerebellum and brain stem homogenates, following systemic administration of AI. Previous studies have indicated that the mechanisms responsible for learning and memory deficits in aging are multifactorial and complex. Neurotrophic factors (such as BDNF and NGF) play a key role in the survival, differentiation and synaptic transmission and plasticity of various populations of neurons in the central nervous system (CNS) and regulate the cognition, formation and storage of memories (Frade and Barde, 1998; Halbach, 2010; Sofroniew et al., 2001). In addition, it was indicated that dysregulation of the apoptotic cascade may be involved in some aging processes and contribute to the incidence of age-related neurodegenerative diseases (Deng et al., 1999; Toman and Fiskum, 2011). For example, the anti-apoptotic Bcl-2 has been shown to have an important role in maintenance of mitochondrial function (inhibiting mitochondrial depolarization and reactive oxygen species production), and regulation of intrinsic apoptotic pathway in the brain of aged animals (Deng et al., 1999; Toman and Fiskum, 2011). Thus, it can be suggested that the beneficial responses of AI treatment on cognitive-age-related impairments might be attributable,

Please cite this article in press as: Badinter, F., et al., Beneficial behavioral, neurochemical and molecular effects of 1-(R)-aminoindan in aged mice, Neuropharmacology (2015), http://dx.doi.org/10.1016/j.neuropharm.2015.05.041

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Fig. 5. Effect of AI on mRNA expression levels of neurotrophic and synaptic factors in the striatum and hippocampus of aged mice. BDNF, NGF, Trk-B receptor, synapsin-1, and GAP43 mRNA expression levels were measured in: A. striatum and B. hippocampus of vehicle- and AI-treated aged mice by quantitative real time RT-PCR. The amount of each product was normalized to the housekeeping genes, b-actin and g-tubulin. Data are expressed as relative gene expression vs. the respective control (folds) and represent mean ± SEM (n ¼ 7e10); *p < 0.05 vs. vehicle-treated aged mice.

regulating cerebral Bcl-2/Bax ratio, a crucial factor in determining the cell apoptosis status (Raghupathi, 2004). Another potential neuroprotective target of AI may be related to an anti-oxidative effect via up-regulation of the activity of the

at least partly, to its up-regulatory effects on mRNA expression levels of neuronal neurotrophins/synaptic markers and antiapoptotic Bcl-2 (Jonas et al., 2014). Indeed, AI may enhance neuronal anti-apoptotic capacity, as shown by its effects on upA. Striatum

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Fig. 6. Effect of AI on mRNA expression levels of Bcl-2 and Bax in the striatum and hippocampus of aged mice. Bcl-2 and Bax mRNA expression levels and Bcl-2/Bax apoptotic ratio were determined in: A. striatum and B. hippocampus of vehicle- and AI-treated aged mice by quantitative real time RT-PCR. The amount of each product was normalized to the housekeeping genes, b-actin and g-tubulin. Data are expressed as relative gene expression vs. the respective control (folds) and represent mean ± SEM (n ¼ 7e10); *p < 0.05 vs. vehicle-treated aged mice.

Please cite this article in press as: Badinter, F., et al., Beneficial behavioral, neurochemical and molecular effects of 1-(R)-aminoindan in aged mice, Neuropharmacology (2015), http://dx.doi.org/10.1016/j.neuropharm.2015.05.041

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In conclusion, our data demonstrated that AI possesses beneficial effects on cognitive functions, regulates striatal amines and exerts neurotrophic up-regulatory and anti-apoptotic properties in aged mice. Further studies need to be conducted to fully identify the exact neurochemical mechanisms underlying the beneficial effects of AI on cognitive decline and depressive-like behavior in aging. 5. Conflict of interest

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MBH Youdim developed with Teva pharmaceutical company (Israel) the anti-Parkinson's drug rasagiline and received royalty.

0 Vehicle Aged+AI Vehicle AI Aged (5(5mg/kg) mg/kg) Aged Fig. 7. Effect of AI on catalase enzyme activity in the brain of aged mice. Catalase enzyme activity was measured in the frontal cortex in mice, and expressed as relative activities (% of control, vehicle-treated aged animals). The values represent mean ± SEM (n ¼ 6e10); *p < 0.05 vs. vehicle-treated aged mice.

antioxidant enzyme catalase, thus preventing neurotoxic oxidative damage. In this context, accumulating evidence indicates that the CNS exerts an enhanced vulnerability to oxidative stress, since it is deficient in free radicals protection and this vulnerability may even increase in aging (Kumar et al., 2012). Indeed, it has been shown that increased cognitive decline with aging may be partially due to an increased oxidative stress and decreased antioxidants in the aging brain, indicating that age-related behavioral/neuronal dysfunctions could be retarded by increasing antioxidant defense mechanisms (Butterfield et al., 2006). Age-related impairments of cognitive functions are often associated with DA system dysfunction, including loss of substantia nigra (SN) pars compacta neurons; decline in striatal DA levels and DRD1 and DRD2 subtypes (Harada et al., 2002; Suzuki et al., 2001); reduced DA uptake and DA receptor binding (Jonec and Finch, 1975; Ricci et al., 1996), and a marked increase in the response of aged SN dopaminergic neurons to neurotoxins (Collier et al., 2005). Regarding the effect of AI on the levels of amines and metabolites in the striatum in aged mice, the current study demonstrated that although AI did not affect MAO activity, chronic administration of the drug increased DA levels, while significantly reduced DOPAC/ DA ration, thus indicating decreased intraneuronal DA metabolism in the striatum of aged mice (Konieczny et al., 2014). Previous data, using kinetic and crystallographic analyses, suggested that AI is a weak reversible MAO inhibitor at pharmacological and clinical doses (Binda et al., 2005).In addition, AI elevated the levels of the extraneuronal metabolite, 3-MT and the ratio 3-MT/DOPAC, which is a DA reuptake index (Karoum et al., 1994; Najib, 2001) and significantly up-regulated striatal DRD1 expression levels. Our results showed that AI increased 5-HT striatal levels and decreased the turnover 5-HIAA/5-HT, suggesting a reduction in 5-HT metabolism. A previous study (Brotchie et al., 2007) also demonstrated that AI increased striatal extracellular DA and 5-HT levels by ~60% and ~50%, respectively, but not in the frontal cortex in freely moving rats, using in vivo microdialysis. Furthermore it was reported that AI enhanced striatal DA transmission in haloperidoltreated rat model of cognition and motor dysfunction (Brotchie et al., 2007). Since, AI did not bind to DA receptors, 5-HT receptors and/or transporters, or various enzymes known to modulate DA or 5-HT transmission, it was suggested that AI may interact with novel sites controlling/regulating monoamine release or uptake (Brotchie et al., 2007).

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