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. Author manuscript; available in PMC: 2011 Jun 1.
Published in final edited form as: Int J Neuropsychopharmacol. 2010 May 25;14(5):618–630. doi: 10.1017/S1461145710000520

Lithium ameliorates phenotypic deficits in a mouse model of fragile X syndrome

Zhong-Hua Liu 1, De-Maw Chuang 2, Carolyn Beebe Smith 3
PMCID: PMC3102293  NIHMSID: NIHMS293653  PMID: 20497624

Abstract

As our understanding of the underlying defects in fragile X syndrome (FXS) increases so does the potential for development of treatments aimed at modulating the defects and ameliorating the constellation of symptoms seen in patients. Symptoms of FXS include cognitive disability, hyperactivity, autistic behavior, seizures and learning deficits. Lithium is a drug used clinically to treat bipolar disorder, and it has been used to treat mood dysregulation in individuals with FXS. We examined whether dietary lithium would alter behavioral and morphological abnormalities in fmr1 knockout (KO) mice. We studied wild type (WT) and KO mice untreated (control chow) or treated with lithium (0.3% lithium carbonate containing chow) commenced at weaning and maintained throughout the experiment. Between 8 and 12 weeks of age, mice were subjected to the following behavioral tests: open field, social interaction, elevated plus maze, elevated zero maze and passive avoidance. At 13 weeks, brains were prepared for Golgi staining and analysis of dendritic spine morphology in medial prefrontal cortex. We found that compared with untreated WT, untreated KO mice were hyperactive and had reduced anxiety, impaired social interactions, and deficits on a learning test. Dendritic spines in medial prefrontal cortex were longer and increased in number. Lithium treatment ameliorated the hyperactivity and reversed impaired social interaction and deficits on the learning test. Lithium treatment also partially normalized general anxiety levels and dendritic spine morphology. Our findings and those from other laboratories on the efficacy of lithium treatment in animal models support further studies in patients with FXS.

Keywords: Fragile X syndrome, lithium, behavior, dendritic spines, medial prefrontal cortex

INTRODUCTION

Silencing of the FMR1 gene and the consequent loss of its protein product, the fragile X mental retardation protein (FMRP), results in fragile X syndrome (FXS), the most common inherited form of intellectual disability (Hagerman, 2002). FXS is characterized by physical phenotypes such as distinct facial features and macroorchidism and behavioral features including hyperactivity, cognitive disability, learning deficits, autism, hyperarousal, and seizures (Hagerman, 2002). A distinctive neuroanatomical defect seen in FXS is abnormal dendritic spine morphology that has been identified in autopsy specimens of FXS patients (Hinton et al. 1991).

Lithium is a well known mood stabilizer used clinically to treat bipolar disease. In rodents, lithium treatment alters many behavioral attributes such as aggression (Prasad and Sheard, 1982), depression (Bersudsky et al. 2007), amphetamine-induced hyperlocomotion (Gould et al. 2007) and reserpine-induced hypolocomotion (Borison et al. 1978). Chronic lithium also enhances learning (Nocjar et al. 2007) and spatial memory in rats (Tsaltas et al. 2007; Vasconcellos et al. 2003). Electrophysiologically, chronic lithium increases long-term potentiation (LTP) in hippocampal neurons (Shim et al. 2007) and alleviates stress-induced LTP impairment (Lim et al. 2005). Lithium also exerts neuroprotective effects (Rowe and Chuang, 2004). The effects of lithium are mediated by several known mechanisms such as downregulation of the phospholipase C signaling pathway (Berridge et al. 1989), reduction of NMDA receptor-initiated signaling (Basselin et al. 2006;) and inhibition of glycogen synthase kinase-3 (GSK-3) (Jope and Roh, 2006; Klein and Melton, 1996). The latter is considered by many to be the primary mediator of lithium’s biological effects.

In a Drosophila model of FXS, lithium reverses learning deficits and improves viability (Chang et al. 2008; McBride et al. 2005). In the knockout (KO) mouse model, lithium reduces the incidence of audiogenic seizures and normalizes an elevation in GSK-3β activity (Min et al. 2009). Clinically, lithium alone or in combination with antipsychotic drugs, has been used successfully to stabilize mood dysregulation and bipolar disorder in individuals with FXS (Al-Semaan et al. 1999). A recent pilot add-on trial demonstrated that lithium improves behavior, adaptive skills, and verbal memory in patients with FXS (Berry-Kravis et al. 2008). These findings suggest that lithium may provide some functional benefits in FXS. We have undertaken a study of chronic lithium treatment in KO mice to systematically examine its effects on known fragile X phenotypes. We measured effects on behavior, dendritic spine morphology, and GSK-3β activity.

METHODS

Animals and treatments

Generation of male KO and wild type (WT) mice by FVB/129P-fmr1tm1Cgr/J) breeding pairs (heterozygous females and hemizygous males), genotyping by PCR amplification of tail DNA, and animal housing were described previously (Qin et al. 2002). All procedures were carried out in accordance with the National Institutes of Health Guidelines on the Care and Use of Animals and an animal study protocol approved by the National Institute of Mental Health Animal Care and Use Committee.

Four groups of mice (22–26/group) were studied: 1) WT fed control diet (WT-C); 2) KO fed control diet (KO-C); 3) WT fed lithium-supplemented diet (WT-Li); 4) KO fed lithium-supplemented diet (KO-Li). The lithium-supplemented diet was NIH-31 to which 0.3% (w/w) lithium carbonate had been added (Harlan Teklad, Madison, WI). Feeding commenced at weaning (21 days) and was provided ad libitum for the duration of the study. Mice fed lithium-supplemented chow were given drinking water with 1.5% (w/v) sodium chloride to counteract potential toxicity of lithium.

From 8–11 weeks of age, mice were subjected to a battery of behavioral tests with one-week intervals between tests: open field, social interaction, elevated plus maze and passive avoidance. In a subset of animals, an elevated zero maze was inserted between the elevated plus maze and passive avoidance test; accordingly, the interval for these tests was reduced to 3–4 days. All behavioral tests were performed between 10AM and 3PMin low light (60 lux). At 12–13 weeks of age, brains were processed for either biochemical analysis or Golgi staining; testicles were dissected and weighed. Blood was sampled at the time of decapitation and lithium concentrations were determined (Medtox Laboratories, St. Paul, MN).

Open field test

At 8 weeks of age, mice were subjected to open field testing for evaluation of locomotor activity and general anxiety. Activity was recorded at 5-min intervals for 30 min by means of a computer-operated tracking system (Coulbourn Instruments, Allentown, PA). Total distance moved, distance moved in the margins (within 6.25 cm of walls), and number of entrances into the center (>6.25 cm from walls) were measured

Social interaction test

At 9 weeks of age, mice were tested for social interaction behavior in an automated three-chambered social approach apparatus (Nadler et al. 2004), following the procedure reported previously (Liu and Smith, 2009). Briefly, the test had three consecutive phases. (A) Habituation. With doorways open, the test mouse was placed in the center chamber and allowed to freely explore for 5 min. The amount of time spent in each chamber was recorded. Mice that spent three or more min in any one chamber were eliminated. (B) Social approach. The test mouse was confined to the center chamber with doors closed, and an unfamiliar mouse (stranger-1) was placed inside a wire cup in one of the side chambers. (Chambers-1 and -2 contained inverted wire cups placed in similar locations within each chamber (Fig. 2a).)The doors were opened, and the subject was allowed to explore freely for 5 min. In addition to the amount of time spent in each chamber, time spent sniffing the stranger mouse or the empty cup, and the entries into each chamber were scored. (C) Preference for social novelty. The subject was confined to the center chamber with doors closed. With stranger-1 remaining in its original wire cup, a new unfamiliar mouse (stranger-2) was placed inside a cup in the opposite chamber, which had been empty during the social approach phase. Doors were re-opened and the subject was allowed to explore for 5 min. Measures were taken as described above.

Fig. 2.

Fig. 2

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Behavior of WT-C (n = 21), KO-C (n = 22), WT-Li (n = 25), and KO-Li (n = 23) mice on a test of social interaction. Bars (mean ± SEM) represent the time spent in each chamber (c–d), the time spent sniffing the wire cage in each chamber (e–f), or the number of chamber entries (g–h). Results were analyzed by RM ANOVA with genotype (WT, KO), treatment (untreated, lithium-treated), condition (social approach, social novelty), and chamber (chamber-1, chamber-2) as factors and repeated measures on condition and chamber. For the time spent in a chamber the chamber × condition × genotype × treatment interaction was not statistically significant (F(1,87) =1.78, NS), but the chamber × condition × treatment (F(1, 87) = 12.02, P ≤ 0.001) and chamber × condition × genotype (F(1, 87) = 5.63, P ≤ 0.05) interactions were both statistically significant. The genotype × treatment interaction (F(1, 87) = 3.12, P = 0.08) approached statistical significance and there were statistically significant main effects of both genotype (F(1, 87) = 6.76, P ≤ 0.05) and treatment (F(1, 87) = 9.20, P ≤ 0.01). For the time spent sniffing, the chamber × condition × genotype × treatment interaction (F(1,87) = 2.47, NS) did not reach statistical significance, but chamber × condition × treatment (F(1, 87) = 32.41, P ≤ 0.001) and chamber × condition × and genotype (F(1, 87) = 10.92, P ≤ 0.001) interactions were both statistically significant. The genotype × treatment interaction (F(1, 87) = 6.25, P ≤ 0.05) was also statistically significant. For the number of chamber entries, the chamber × condition × genotype × treatment interaction was not statistically significant (F(1,87) = 0.37, NS). The only statistically significant interaction was the condition × chamber (F(1, 87) = 24.94, P ≤ 0.001). The main effect of treatment (P<0.001) was statistically significant. Regardless of genotype or treatment the number of entries into both chambers (chamber-1, P<0.05; chamber-2, P<0.001) was higher in social novelty v. social approach, and in social approach entries into chamber-1 were higher than entries into chamber-2 (P<0.001).

Elevated plus maze

At 10 weeks of age, mice were tested for general anxiety in an elevated plus maze(EPM) as described previously (Liu and Smith, 2009). Briefly, the mouse was placed in the center of the apparatus facing an open arm. The time spent in the closed and open arms and the numbers of entrances into closed and open arms were recorded for 5 min. We defined an arm entry as the mouse having his head and forepaws in the arm.

Elevated zero maze

We tested 48 mice for general anxiety in the elevated zero maze (MED Associates Inc, St. Albans, VE)as described previously (Liu and Smith, 2009). Briefly, mice were placed in the center of a closed quadrant and allowed to explore freely for 5 min; behavior was recorded by video camera. Time spent and number of head dips in and number of entrances into each quadrant were evaluated. Mice that fell off the maze were not included.

Passive avoidance

At 11 weeks of age mice were subjected to the passive avoidance test as previously described (Qin et al. 2002). Briefly, mice underwent one-trial training and one test session 24 h later. On training day the mouse was placed in the lighted chamber of a two-chambered apparatus (Coulbourn Instruments, Whitehall, PA). After 10 sec the door to the dark chamber was raised. Once the mouse entered the dark chamber, the door automatically closed and an electric shock (0.3 mA for 1 sec) was administered. The mouse was removed from the apparatus after 10 sec, returned to its home cage, and 24 h later latency to enter the dark compartment of the apparatus was recorded up to 300 sec.

Golgi staining and morphological analysis of dendritic spines

At 12 weeks, 24 mice (6/group) were perfused with saline and brains were subjected to Golgi-staining (Rapid GolgiStain™ Kit, FD NeuroTechnologies, Ellicott City, MD). Coronal sections 100-μm in thickness were prepared. Pyramidal neurons (7 each for apical and basal dendrites) in Layer III of medial prefrontal cortex (MPC) (infralimbic and prelimbic) were selected for quantification. Dendritic branches directly originating from cell soma were classified as primary dendrites, and those originating from primary dendrites were classified as secondary dendrites. In this study, primary basal and secondary apical dendrites originating from the apical trunk located 25–50 μm from the soma were selected for analysis. Spine length and density were analyzed in 50 μm segments starting 25 μm from the origin of a branch. Only one segment from each neuron was analyzed.

Western blotting

At 12 weeks, 24 mice (6/group) were decapitated, brains were removed quickly and homogenized in 3% (w/v) ice-cold T-PER tissue protein extraction reagent with 1% Halt protease inhibitor cocktail (Thermo Scientific, Waltham, MA) and 1% phosphatase inhibitor cocktails (Sigma-Aldrich, St Louis, MO). Homogenates were centrifuged (12,000 × g, 4 °C, 15 min) and supernatant fractions were used for Western blot analyses. Protein concentrations were determined by BCA protein assay kit. Two equivalent protein samples (20μg) were subjected to electrophoresis on 10% NuPAGE Bis-Tris gels. Proteins were transferred electrophoretically to nitrocellulose membranes, and membranes were incubated with either GSK-3β rabbit monoclonal antibody (1:20,000, Cell Signaling Technology, Danvers, MA) or phosphorylated GSK-3β (ser9) rabbit monoclonal antibody (1:2,000, Cell Signaling Technology). β-Actin rabbit polyclonal antibody (1:2,000, Cell Signaling Technology) was used as a loading control. Specific reactions were detected by the WesternBreeze Chemiluminescent kit (Invitrogen, Carlsbad, CA).

Statistical analyses

Data were expressed as mean ± SEM. Open field and social interaction results were analyzed by repeated measures (RM) ANOVA. All other results were analyzed by two-way ANOVA with genotype and treatment as factors. Statistically significant interactions were further probed with post-hoc Bonferroni t-tests. Spine length distributions were compared by two-way Kruskal-Wallis followed by Kolmogorov-Smirnov tests. The criterion for statistical significance was P<0.05.

RESULTS

Body weight

We compared body weights in a subset of animals at 11 weeks of age (Suppl., Fig. 1-S). The genotype × treatment interaction, was not statistically significant, but main effects of both genotype (F(1,29)=14.79, P<0.001) and treatment (F(1,29)=6.88, P<0.05) were. Body weights of KO mice were 9% higher than WT, and weights of lithium-treated mice were about 6% higher than control mice. The concentrations of lithium in whole blood from WT and KO mice were 0.38 ± 0.03 (n=4) and 0.38 ± 0.02 mEq/L (n=4), respectively. No toxicity of the lithium treatment was observed.

Testes weight

Testes were dissected from 12–13 week old mice and weighed. The genotype × treatment interaction was not statistically significant. The testes weight of KO mice was significantly higher than WT (F(1,90)=186.1, P<0.001), but the effect of lithium treatment (F(1,90)=3.87, P=0.052) was small (<5% decrease)(Suppl., Fig. 2-S).

Open field activity

In all four groups the total distance traveled per epoch gradually decreased during the 30min session (Fig. 1a). Data were analyzed by RM ANOVA with genotype, treatment and epoch as factors and RM on epoch. The three-way interaction was not statistically significant, and neither were the epoch × treatment and genotype × treatment interactions, but the epoch × genotype interaction (F(4,351)=2.67, P<0.05)and the main effects of all three factors were statistically significant. Overall, the time × distance curves of KO mice were higher than those of WT (P<0.01 at all epochs) indicating hyperactivity of KO mice. Regardless of genotype and epoch, lithium treatment decreased locomotor activity of mice (P<0.05). The curve of KO-Li mice was below the curve of KO-C mice, suggesting partial reversal of hyperactivity in KO mice by lithium treatment.

Fig. 1.

Fig. 1

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Open-field activity in WT-C (n = 23), KO-C (n = 22), WT-Li (n = 26), and KO-Li (n = 22). Each point represents the mean ± SEM for each five min epoch. Data were analyzed by means of RM ANOVA with genotype (WT, KO), treatment (untreated, lithium-treated) and epoch as factors and repeated measures on epoch. (a) Total distance moved in the horizontal plane. The epoch × genotype × treatment (F(4, 351) = 1.52, NS) and epoch × treatment (F(4, 351) = 0.30, NS) interactions were not statistically significant, but epoch × genotype interaction (F(4, 351) = 2.67, P ≤ 0.05) was statistically significant. The genotype × treatment interaction (F(1,89) = 0.81, NS) was not statistically significant, but main effects of both genotype (F(1,89) = 25.60, P ≤ 0.001) and treatment (F(1,89) = 5.17, P < 0.05) were. (b) Percent distance moved in the margins of the field. The epoch × genotype × treatment (F(4, 383) = 0.171, NS), epoch × treatment (F(4, 383) = 1.56, NS), epoch × genotype (F(4, 383) = 1.19, NS), and genotype × treatment (F(1, 89) = 0.67, NS) interactions were not statistically significant, but main effects of both genotype (F(1, 89) = 21.55, P ≤ 0.001) and treatment (F(1, 89) = 7.87, P ≤ 0.01) were statistically significant. (c). Number of entries into the center of the field. The epoch × genotype × treatment (F(5, 433) = 0.373, NS) and epoch × genotype (F(5, 433) = 1.90, NS) interactions were not statistically significant, but epoch × treatment interaction (F(5, 433) = 2.68, P ≤ 0.05) was statistically significant. The genotype × treatment interaction, (F(1,89) = 4.23, P ≤ 0.05) was also statistically significant.

As an indicator of the level of general anxiety, we analyzed the distance traveled in the margins of the field as a percent of the total distance moved (Fig. 1b). There were no statistically significant interactions, but we did find statistically significant main effects of treatment (F(1,89)=7.81, P<0.01), genotype (F(1,89)=21.5, P<0.001) and epoch (F(5,445)=7.29, P<0.001). KO mice traveled less in the margins than WT regardless of treatment, suggesting that KO mice have less anxiety than WT. Regardless of genotype, mice with lithium treatment moved more in the margins than control mice, implying that lithium treatment increased anxiety levels.

Another indicator of the level of general anxiety is the number of entrances into the center of the field (Fig. 1c). The three-way interaction was not statistically significant, and neither was the epoch × genotype interaction, but the epoch × treatment interaction (F(5,433)=2.68, P<0.05) was, indicating that the shape of the curve was influenced by lithium treatment but not by genotype. There was also a statistically significant genotype × treatment interaction (F(1,89)=4.23, P<0.05). Post-hoc tests revealed that the total number of center entries was higher in KO-C than WT-C mice (P<0.001), suggesting less anxiety in KO mice. Compared with KO-C, KO-Li mice entered the center less (P<0.01) and behaved more like WT mice, implying alleviation of this behavioral deficit.

Social interaction

During the habituation phase, two WT-C and one WT-Li mice remained in one side chamber for more than 3 min and were eliminated from further study.

The social approach phase began with the introduction of a novel mouse (stranger-1) under the cup in chamber-1 (Fig. 2a). The social novelty phase began with the introduction of a second novel mouse (stranger-2) under the cup in chamber-2 with stranger-1 remaining in its original wire cup (Fig. 2b). The times spent in the two chambers (Fig. 2c, d) were analyzed by RM ANOVA with chamber, condition, genotype and treatment as factors with RM on chamber and condition. Although there was no statistically significant four-way interaction, chamber × condition × treatment (F(1,87)=12.02, P0.001) and chamber × condition × genotype (F(1,87)=5.63, P<0.05) interactions were both statistically significant. Post hoc analyses indicated that during the social approach phase, mice of all groups spent more time in chamber-1 than chamber-2 (empty chamber) (P<0.001), and the preference for chamber-1 was enhanced by lithium treatment in both genotypes (P<0.001). During the social novelty phase all mice showed a switch in preference for chamber-2 (P<0.01). Compared with WT, KO mice spent significantly less time in chamber-2 (P<0.01), and KO-C mice spent about the same amount of time in chamber-2 as in chamber-1. Analysis of the between-subjects effects indicates that the genotype × treatment interaction approached statistical significance (F(1,87)=3.12, P=0.081). Main effects of both genotype (F(1,87)=6.75, P<0.05) and treatment (F(1,87)=9.2, P<0.01) were statistically significant. These results show clear effects of both genotype and treatment, and a tendency for the effect of treatment with lithium to be greater in KO mice.

The measure of time spent sniffing the wire cups in chambers-1 and -2 (Fig. 2e, f) is considered to be an index of more direct social interest (Nadler et al. 2004). There was no statistically significant four-way interaction, but chamber × condition × treatment (F(1, 87)=32.4, P<0.001) and chamber × condition × genotype (F(1, 87)=10.9, P<0.001) interactions were both statistically significant. Further analysis revealed that during the social approach phase, mice of all groups spent more time sniffing stranger-1 than the empty cup in chamber-2(P<0.001). KO mice spent significantly less time sniffing stranger-1 than WT (P<0.01), and, in both genotypes, lithium treatment increased the time spent sniffing stranger-1 (P<0.001). During the social novelty phase, all animals showed a clear switch in preference for sniffing stranger-2 (P<0.001). Compared with WT, KO mice spent significantly less time sniffing stranger-2 (P<0.001), while there was no difference between these two genotypes for time sniffing stranger-1. In KO mice, lithium treatment appeared to normalize sniffing behavior. The treatment × genotype interaction was statistically significant (F(1,87)=6.25, P<0.05). Post hoc tests revealed a statistically significant difference in sniffing time between WT-C and KO-C mice regardless of chamber (P<0.001). Further, sniffing time in both WT and KO mice was increased by lithium treatment (P<0.01).

The number of entries into each chamber (Fig. 2 g, h) can be a measure of activity as well as social interest. There were no statistically significant four-way or three-way interactions, but the chamber × condition (F(1, 87)=24.94, P<0.001) interaction was statistically significant. Post hoc tests indicated that both genotypes regardless of treatment made more entries into chamber-1 v. chamber-2 during social approach (P<0.001) and into both chamber-1 (P<0.05) and chamber-2 (P<0.001)during social novelty v social approach. There was also a statistically significant main effect of treatment (F(1,87)=24.1, P<0.001) indicating that overall numbers of entries into both chambers decreased with lithium treatment.

Overall our results indicate that KO-C mice exhibit deficits in social interaction which are corrected by lithium treatment. Lithium also appeared to influence some aspects of behavior in WT mice.

Elevated plus maze

To evaluate general anxiety, times spent in open and closed arms were analyzed by RM ANOVA with genotype, treatment, and arm as factors and RM on arm (Fig. 3). We found a statistically significant arm × genotype × treatment interaction (F(1, 90)=4.72, P<0.05). Differences among groups in time spent in the open arms were not statistically significant by post-hoc tests but time spent in the closed arm was statistically significantly lower in KO-C mice than WT-C (P<0.001), indicating lower anxiety in KO mice. This difference was ameliorated by lithium treatment (P<0.01). The lack of effect on time spent in the open arms may be a function of the ambiguity of the open center which was not counted as part of the open arm but was nevertheless open.

Fig. 3.

Fig. 3

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Behavior of WT-C (n = 23), KO-C (n = 22), WT-Li (n = 26), and KO-Li (n = 23) mice on the elevated plus maze. Bars are the means ± SEMs. Time spent in open or closed arms in the elevated plus maze were analyzed by RM ANOVA with genotype (WT, KO), treatment (untreated, lithium-treated), and arm (open, closed) as factors and RM on arm. The arm × genotype × treatment interaction (F(1, 90) = 4.72, P ≤ 0.05) was statistically significant. Post hoc Bonferroni t-tests were used to compare WT and KO as indicated on the figure.

Elevated zero maze

In a subset of mice we also measured general anxiety by the EZM (Fig. 4). One WT-Li mouse was eliminated from further analysis after it fell off the platform. Time spent (Fig. 4a) and head dips (Fig. 4b) in the open quadrants were analyzed by two-way ANOVA. For time spent in the open quadrants the genotype × treatment interaction was not statistically significant, but main effects of genotype (F(1,46)=6.93, P<0.05) and treatment (F(1,46)=9.17, P<0.01) were both statistically significant. KO mice spent more time in the open quadrants than WT, indicating reduced anxiety in KO mice and lithium treatment decreased the time spent in open quadrants suggesting a normalizing effect of lithium on anxiety. For the number of head dips (Fig. 4b) neither the interaction nor the main effects achieved statistical significance. We also recorded the number of entrances into the open and closed quadrants of the zero maze (Fig. 4c). These data were analyzed with RM ANOVA with genotype, treatment and quadrant as factors and RM on quadrant. The genotype × treatment × quadrant and quadrant × genotype interactions were not statistically significant, but the quadrant × treatment (F(1,46)=7.61, P<0.01) and genotype × treatment (F(1,46)=7.68, P<0.01) interactions were. Post-hoc tests showed that regardless of quadrant, the total number of entrances was higher in KO-C mice than WT-C (P<0.001), reflecting the hyperactivity of KO mice. Lithium treatment significantly decreased the activity of KO mice (P<0.001).

Fig. 4.

Fig. 4

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Behavior of WT-C (n = 14), KO-C (n = 11), WT-Li (n = 13), and KO-Li (n = 12) mice on the elevated zero maze. Bars are the means ± SEMs. Results of time spent in open quadrants and number of head dips were analyzed by means of two-way ANOVA with genotype (WT, KO) and treatment (untreated, lithium-treated) as factors. The numbers of entrances into open and closed quadrants were analyzed by means of RM ANOVA with genotype, treatment, and quadrant (open, closed) as factors with repeated measures on quadrant. (a) Time spent in the open quadrants. The genotype × treatment (F(1, 46) = 2.80, P = 0.101) interaction approached statistical significance, and main effects of both genotype (F(1, 46) = 6.93, P ≤ 0.05) and treatment (F(1, 46) = 9.14, P ≤ 0.01) were statistically significant. (b) Number of head dips. Neither the genotype × treatment interaction (F(1,46) = 0.32, NS) nor the main effect of genotype (F(1, 46) = 0.59, NS) and treatment (F(1, 46) = 1.44, NS) were statistically significant. (c) Number of entrances into open and closed quadrants. Both genotype × treatment × quadrant (F(1, 46) = 2.38, P=0.130) and genotype × quadrant (F(1, 46) = 2.60, P = 0.114) interactions approached statistical significance, and the treatment × quadrant interaction (F(1, 46) = 3.70, P ≤ 0.01)was statistically significant.

Passive avoidance

In the results of the passive avoidance test the genotype × treatment interaction did not reach statistical significance, but main effects of both genotype (F(1,60)=5.29, P<0.05) and treatment (F(1,60)=4.76, P<0.05) were statistically significant. The latency to enter the dark compartment was lower in KO mice, and latency was increased by lithium treatment (Fig. 5).

Fig. 5.

Fig. 5

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Behavior of WT-C (n = 23), KO-C (n = 22), WT-Li (n = 26), and KO-Li (n = 23) mice on the passive avoidance test. Bars represent the mean ± SEM latency to enter the dark chamber 24 h after a single training session in which mice received a foot-shock (0.3 mA for 1 s) upon entering the dark chamber. Results were analyzed by a two-way ANOVA with genotype (WT, KO) and treatment (untreated, lithium-treated) as factors. The genotype × treatment interaction was not quite statistically significant (F(1,90) = 2.38, P = 0.126), but main effects of both genotype (F(1,90) = 5.11, P 0.05) and treatment (F(1,90) = 4.96, P ≤ 0.05) were statistically significant.

Dendritic spine morphology

Dendritic spines on apical and basal (Fig. 6a) dendrites of Layer III pyramidal neurons in MPC were analyzed. Cumulative frequency distributions of spine length show that spines on both apical (Fig. 6b) and basal (Fig. 6c) dendrites were longer in KO-C than WT-C mice, and lithium treatment normalized the length of spines in KO mice. Two-way Kruskal-Wallis tests showed statistically significant treatment × genotype interactions for both apical (H=10.6, P<0.01) and basal(H=18.6, P<0.001) dendrites. Pairs of cumulative frequencies were further probed by Kolmogorov-Smirnov Tests; results indicate that for apical dendrites there were statistically significant differences between WT-C and KO-C (P<0.001), WT-C and WT-Li (P<0.05), and KO-C and KO-Li (P<0.001). For basal dendrites there were statistically significant differences between WT-C and KO-C (P<0.001) and KO-C and KO-Li (P<0.001), but differences between WT-C and WT-Li were not statistically significant.

Fig. 6.

Fig. 6

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Dendritic spines on apical and basal dendrites of layer III pyramidal neurons in medial prefrontal cortex. (a) Golgi-stained sections of spines on basal dendrites. Scalebar represents 5μm. Cumulative frequency distributions of dendritic spine lengths on apical (b) and basal (c) dendrites. Statistical analysis of all four cumulative frequency distributions of spine length on both apical and basal dendrites indicate statistically significant differences for both apical and basal dendrites (2-way Kruskal-Wallis test; apical: H = 10.6, P ≤ 0.01; basal:H = 18.6, P ≤ 0.001). Pairs of cumulative frequencies were further probed by means of Kolmogorov-Smirnov Tests; results indicate that for apical dendrites there were statistically significant differences between WT-C and KO-C (P ≤ 0.001), WT-C and WT-Li (P ≤ 0.05), and KO-C and KO-Li (P ≤ 0.001). For basal dendrites there were statistically significant differences between WT-C and KO-C (P ≤ 0.001) and KO-C and KO-Li (P ≤ 0.001). The density of spines along both apical (d) and basal (e) dendrites were analyzed by means of two-way ANOVA with genotype (WT, KO) and treatment (untreated, lithium-treated) as factors. Values are the means ± SEM of 42 dendrites per group. For apical dendrites, the genotype × treatment interaction (F(1, 164) = 1.33, NS) was not statistically significant, but main effects of genotype (F(1, 164) = 5.64, P ≤ 0.05) and treatment (F(1, 164) = 7.69, P ≤ 0.01) were both statistically significant. In basal dendrites the genotype × treatment interaction (F(1, 164) = 2.73, P = 0.10) was not quite statistically significant. The main effect of treatment (F(1, 164) = 0.01, NS) was not statistically significant, but the main effect of genotype was (F(1, 164) = 14.94, P ≤ 0.001).

We also analyzed the density of spines along both apical and basal dendrites. For apical dendrites (Fig. 6d), there was no statistically significant interaction, but main effects of genotype (F(1,164)=5.64, P<0.05) and treatment (F(1,164)=7.69, P<0.01) were both statistically significant. Overall, the density of apical spines was higher in KO mice and was reduced by lithium treatment. In basal dendrites (Fig. 6e), however, only the main effect of genotype was statistically significant (F(1,164)=14.9, P<0.001). Spine density on basal dendrites was higher in KO mice, but this effect was not significantly influenced by lithium.

Activity of GSK-3β

The levels of total and Ser9-phosphorylated- GSK-3β in whole brain were studied (Fig. 7a) and results were expressed as percent of WT-C. For phosphorylated GSK-3β (Fig. 7b) a statistically significant genotype × treatment interaction (F(1,20)=5.83, P<0.05) was found. Post-hoc tests revealed that the level of phosphorylated GSK-3β of KO mice was markedly increased following lithium treatment (P<0.01), suggesting that the upregulated GSK-3β activity is reduced by lithium. The levels of total GSK-3β were similar in all four groups (Fig. 7c).

Fig 7.

Fig 7

Open in a new tab

Western blot analysis of phosphorylated-GSK-3β (ser9)andtotal GSK-3β levels in extracts prepared from whole mouse brain. Representative Western blots (a) and summary data from six mice per group for p-GSK-3β (b) and total GSK-3β (c). Optical densities were normalized to β-actin and values were expressed as percent of WT-C. The genotype × treatment interaction (F(1, 20) = 5.83, P ≤ 0.05) was statistically significant for p-GSK-3β levels, and results of post-hoc Bonferroni t-tests are shown on the figure. For total GSK-3β levels the genotype × treatment interaction (F(1, 20) = 0.42, NS) was not statistically significant and neither were the main effects of genotype (F(1, 20) = 0.24, NS) nor treatment (F(1, 20) = 0.39, NS).

DISCUSSION

The ameliorative effects of chronic lithium treatment on neuropathology and a wide range of behavioral measures in the fmr1 KO mouse indicate that lithium is a promising candidate drug for treatment of FXS. Lithium treatment initiated at the time of weaning reversed behavioral phenotypes of KO mice including hyperactivity, reduced anxiety, reduced social interaction, and a deficit in a test of learning/memory. Lithium treatment also mitigated abnormal spine length and density in MPC. One of the novel findings of our study is the wide range of effects of lithium treatment suggesting that lithium treatment may affect underlying chemical pathology.

For most of the measures studied, effects of lithium treatment were selective for KO mice, but in some cases lithium effects were seen in both genotypes. With respect to effects on body and testes weights and spine density on apical dendrites in MPC there were clear effects of lithium treatment in both WT and KO mice. In the cases of open field behavior (horizontal distance and % distance moved in the margins) effects appeared to be greater in the KO mice v WT, but the three-way interactions were not statistically significant.

Animals in our study were male, closely matched for age, group-housed 3–4 to a cage, and studied at about the same time of day. We controlled for genetic drift by using a breeding scheme that produces WT and KO littermates. FVB/129P-fmr1tm1Cgr/J mice are prone to retinal degeneration which occurs at about 21 days of age, so it is probable that at the time of study our mice had reduced visual acuity. It’s unlikely that poor visual acuity would have affected the results of this study because both WT and KO mice were similarly affected. Moreover, non-visual sensory cues such as olfaction and somatosensory input are likely more important in mice.

We used robust behavioral phenotypes to assess the effects of lithium. Hyperactivity in the open field has been observed in KO mice on several different genetic backgrounds (Bakker et al. 1994; de Diego-Otero et al. 2009; Nielsen et al. 2002; Peier et al. 2000; Qin et al. 2002, 2005b; Spencer et al. 2005). In the present study chronic lithium treatment partially normalized hyperactivity in KO mice. Activity was also assessed in the social interaction and EZM tests as the number of chamber and quadrant entries, respectively. By design these two tests produce increased arousal and are less neutral than the open field test. In the EZM, KO-C mice made more entries into both open and closed quadrants than WT-C mice and this “hyperactivity” appeared to be normalized with lithium treatment. In the social interaction test both WT and KO mice regardless of treatment made more entries into both chambers during social novelty v social approach. The latter demonstrates the highly activating nature of the social novelty condition. Because the effect was seen in all four groups it is unlikely to be a reflection of some attribute of the KO mice.

Reduced anxiety is another generally agreed upon phenotype (Bakker et al. 1994; de Diego-Otero et al. 2009; Liu and Smith, 2009; Peier et al. 2000; Qin et al. 2002, 2005b; Qin and Smith, 2008; Yuskaitis et al. 2010). We evaluated generalized anxiety by means of three different tests: 1) behavior in the open field, 2) EPM, and 3) EZM. The EZM is a modification of the EPM; it removes any ambiguity in interpretation of time spent in the central square, and it allows uninterrupted exploration. By the criteria of all three tests, KO mice appeared to be less anxious than WT. In open field (center entries) and EPM the generalized anxiety levels were normalized in KO mice by lithium treatment. Results of the EZM were not quite as clear cut probably due to the smaller number of mice studied. Hyperactivity of KO-C mice also may have been a factor. However, despite a higher number of open and closed quadrant entrances, KO-C mice spent on average 38% of the time in the open quadrants while WT-C spent 26%. Hyperactivity of KO mice was quelled by lithium treatment and open quadrant time was reduced to an average of 25% v 22% in WT-Li. The effect of lithium treatment on general anxiety in WT mice was small compared with its effect in KOs.

Social anxiety is a major component of autism and a frequent symptom found in FXS (Hagerman, 2002). We used a three-chambered apparatus designed specifically to assess social behavior in mice (Nadler et al. 2004). Quantification of social interaction is in terms of time spent with a novel mouse and preference for a novel v. familiar mouse. We confirm here our previously reported finding that social approach and response to social novelty are both diminished in KO mice (Liu and Smith, 2009). Reduced levels of social approach are in accord with some studies (Mineur et al. 2006), but differ from others reporting normal or increased interest of KO mice in an unfamiliar partner (McNaughton et al. 2008; Spencer et al. 2005). Differences in age of the animals tested, characteristics of stranger mice used(see Suppl.), time of day of tests, and housing conditions likely explain the disparate results. We found that reduced social interaction is a robust phenotype in KO mice, and is reversed by chronic lithium treatment. Results of time sniffing were stronger than results of time in chamber, probably due to the fact that sniffing is a more direct index of social interest in mice. Mice are primarily olfactory animals and as such use olfaction to learn about objects and other animals in their environment. Thus, it is possible that the increased exploration of the novel social object may be involved in an effort to learn. The present novel finding suggests that lithium treatment, in addition to ameliorating hyperactivity and normalizing general anxiety levels, may also address autistic features of FXS.

Cognitive impairment and low intelligence quotients are characteristic of patients with FXS, but measures of these phenotypes have been difficult to demonstrate in the mouse model (Bernardet and Crusio, 2006). Tests of spatial learning and memory such as the Morris water maze have not shown remarkable effects in KO mice (Bakker et al. 1994; Peier et al. 2000; Yan et al. 2004). We and others have found that the passive avoidance test may be a good marker of learning/memory impairment, albeit nonspatial learning, in KO mice (Qin et al. 2002, 2005b; Yuskaitis et al. 2010). This is an aversively motivated task that likely involves the dorsal striatum (White and McDonald, 2002). In some aspects the passive avoidance test is similar to the leverpress escape/avoidance task which is also impaired in KO mice (Brennan et al. 2006). In the present study, performance of both genotypes improved with lithium treatment but on average the improvement was much greater in KO mice(78% v 8% increase in latency in KO and WT, respectively). Whereas the genotype × treatment interaction did not reach statistical significance the magnitude of the difference in improvement suggests that chronic lithium treatment improves performance. These results may represent an improvement in learning/memory. Another possible interpretation is that the shorter latency in KO-C mice is a reflection of their hyperactivity and impulsivity (Moon et al. 2006), and that improvement with lithium treatment is due to reduced activity and improved inhibitory control. These findings are of particular interest in light of the reversal by lithium treatment of abnormal dendritic spines in MPC in KO mice because of the role of MPCin behavioral control (Birrell and Brown, 2000; Muir et al. 1996).

Complementing our findings of the effects of lithium treatment on behavioral phenotypes in KO mice are our findings on changes in neuronal morphology imposed by lithium treatment. Abnormality of dendritic spine morphology in neocortical pyramidal cells is the most prominent neuropathological finding in FXS (Hinton et al. 1991). Spines are higher in density and have long, thin and tortuous shapes reminiscent of immature spines on developing neurons. Similar morphological changes have been reported in KO mice (Comery et al. 1997). In the present study we show that spine pathology also occurs in MPC and that it is normalized by chronic lithium treatment. MPC plays an important role in social cognition (Nachev, 2006). Thus, it is plausible that abnormal dendritic spine morphology in this region may be linked to the autistic-like behavior. A recent study found that the dendritic spine densities on cortical projection neurons were increased in autism spectrum disorders (Hutsler and Zhang, 2010). MPC is also critically involved in executive function and management of impulsive and compulsive responses. Attentional dysfunction, impulsivity and resistance to change are all features of FXS and have also been found in the fmr1 KO mouse (Moon et al. 2006). The ability of lithium treatment to decrease hyperactivity and to improve performance on the passive avoidance and social interaction tests may be linked to its ameliorative effects on spine morphology in MPC.

Efficacy of lithium treatment has been demonstrated in two animal models of FXS. In the dfmr1 mutant (McBride et al. 2005), treatment with lithium reversed deficient courtship behavior and mushroom body defects and restored memory deficits in an experience-dependent behavior modification task. In another study in which the sensitivity of the dfmr1 mutant to excess glutamate in food was used as a drug screen, lithium rescued lethal effects of elevated glutamate (Chang et al. 2008). The effects of lithium treatment have also been studied in the fmr1 KO mouse. Both acute and chronic treatment with lithium reduced the susceptibility to audiogenic seizures (Min et al. 2009). It is noteworthy that a two-month pilot open-label treatment trial of lithium in 15 subjects with FXS indicated a trend toward behavioral improvement (Berry-Kravis et al. 2008).

In the present study, we measured the lithium concentration in whole blood. This concentration is equivalent to a plasma lithium level that is at the low end of the therapeutic range of plasma lithium for treatment of bipolar disorder in human subjects (0.4–1.2 mEq/L) (Aydemir et al. 2007; Shimizu et al. 1979). Importantly, in our study lithium activity was well below the toxic range, and we saw no evidence of lithium toxicity in treated mice. The therapeutic range in the mouse likely depends on the therapeutic target, and one target of lithium is GSK-3β (Jope and Roh, 2006; Klein and Melton, 1996). The decreased level of Ser9-phosphorylated GSK-3β suggests an upregulation of GSK-3β activity in untreated KO mice that was reversed by lithium treatment. These findings are in agreement with those of Min et al. (2009) and Yuskaitis et al. (2010). Evidence that GSK-3 is the therapeutic target of lithium in the KO mouse is supported by the finding that lithium, as well as selective inhibitors of GSK-3, reduced susceptibility to audiogenic seizures and modified open field behavior (Min et al. 2009). GSK-3 is a highly regulated enzyme with a regulatory role in a large number of processes (Grimes and Jope, 2001) including transcription factors that control gene expression, such as AP-1, β-catenin, CREB, NF-κB; cell signaling cascades such as cAMP-dependent protein kinase, eIF2B, glycogen synthase; and cell architecture through phosphorylation of structural proteins such as MAP1B, MAP2, and Tau. Lithium increases cell survival by inducing neurotrophins, such as BDNF which in turn stimulates activity in the phosphatidylinositol 3-kinase (PI3K)/Akt and the mitogen-activated protein kinase (MAPK) pathways (Chuang and Priller, 2006).

The protein lacking in patients with FXS, FMRP, is a negative regulator of translation. In fmr1KO mice, the lack of FMRP results in elevated in vivo regional rates of cerebral protein synthesis (Qin et al. 2005a) which may underlie the range of phenotypes in this disorder. We posit that chronic lithium treatment acting through a decrease in GSK-3β activity, modulates this excessive translation and, in doing so, ameliorates many of the symptoms of FXS. A study of the effect of lithium treatment on cerebral protein synthesis rates is currently underway in our laboratory. Our results in the mouse model coupled with the results from other laboratories studying the mouse model (Min et al. 2009), the Drosophila model (McBride et al. 2005), and human subjects (Berry-Kravis et al. 2008) make a strong case for instituting a placebo-controlled trial of lithium in subjects with FXS.

Supplementary Material

Fig S-1
Fig S-2
Supl Text

Acknowledgments

We thank Zengyan Xia for overseeing the breeding colony and determining genotypes. We also thank Mei Qin for helpful discussions and Guangping Liu for assistance with Western blotting. The research was supported by the Intramural Research Program of the National Institute of Mental Health, National Institutes of Health.

Footnotes

Statement of Interest: None.

Contributor Information

Zhong-Hua Liu, Section on Neuroadaptation and Protein Metabolism, National Institute of Mental Health.

De-Maw Chuang, Molecular Neurobiology Section, National Institute of Mental Health.

Carolyn Beebe Smith, Section on Neuroadaptation and Protein Metabolism, National Institute of Mental Health.

References

  1. Al-Semaan Y, Malla AK, Lazosky A. Schizoaffective disorder in a fragile-X carrier. Australian and New Zealand Journal of Psychiatry. 1999;33:436–440. doi: 10.1046/j.1440-1614.1999.00564.x. [DOI] [PubMed] [Google Scholar]
  2. Aydemir B, Kiziler A, Akyolcu M. Determination of optimal lithium concentration in fractions of blood in atomic absorption spectrophotometer. Trace Elements and Electrolytes. 2007;24:87–91. [Google Scholar]
  3. Bakker CE Dutch-Belgian Consortium. Fmr1 knockout mice: a model to study fragile X mental retardation. Cell. 1994;78:23–33. [PubMed] [Google Scholar]
  4. Basselin M, Chang L, Bell JM, Rapoport SI. Chronic lithium chloride administration attenuates brain NMDA receptor-initiated signaling via arachidonic acid in unanesthetized rats. Neuropsychopharmacology. 2006;31:1659–1674. doi: 10.1038/sj.npp.1300920. [DOI] [PubMed] [Google Scholar]
  5. Bernardet M, Crusio WE. Fmr1 KO mice as a possible model of autistic features. ScientificWorldJournal. 2006;6:1164–1176. doi: 10.1100/tsw.2006.220. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Berridge MJ, Downes CP, Hanley MR. Neural and developmental actions of lithium: a unifying hypothesis. Cell. 1989;59:411–419. doi: 10.1016/0092-8674(89)90026-3. [DOI] [PubMed] [Google Scholar]
  7. Berry-Kravis E, Sumis A, Hervey C, Nelson M, et al. Open-label treatment trial of lithium to target the underlying defect in fragile X syndrome. Journal of Developmental and Behavioral Pediatrics. 2008;29:293–302. doi: 10.1097/DBP.0b013e31817dc447. [DOI] [PubMed] [Google Scholar]
  8. Bersudsky Y, Shaldubina A, Belmaker RH. Lithium’s effect in forced-swim test is blood level dependent but not dependent on weight loss. Behavioural Pharmacology. 2007;18:77–80. doi: 10.1097/FBP.0b013e32801416ed. [DOI] [PubMed] [Google Scholar]
  9. Birrell JM, Brown VJ. Medial frontal cortex mediates perceptual attentional set shifting in the rat. Journal of Neuroscience. 2000;20:4320–4324. doi: 10.1523/JNEUROSCI.20-11-04320.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Borison R, Sabelli H, Maple P, Havdala H, et al. Lithium prevention of amphetamine-induced ‘manic’ excitement and of reserpine-induced ‘depression’ in mice: possible role of 2-phenylethylamine. Psychopharmacology (Berl) 1978;59:259–262. doi: 10.1007/BF00426631. [DOI] [PubMed] [Google Scholar]
  11. Brennan FX, Albeck DS, Paylor R. Fmr1 knockout mice are impaired in a leverpress escape/avoidance task. Genes, Brain, and Behavior. 2006;5:467–471. doi: 10.1111/j.1601-183X.2005.00183.x. [DOI] [PubMed] [Google Scholar]
  12. Chang S, Bray SM, Li Z, Zarnescu DC, et al. Identification of small molecules rescuing fragile X syndrome phenotypes in Drosophila. Nature Chemical Biology. 2008;4:256–263. doi: 10.1038/nchembio.78. [DOI] [PubMed] [Google Scholar]
  13. Comery TA, Harris JB, Willems PJ, Oostra BA, et al. Abnormal dendritic spines in fragile X knockout mice: maturation and pruning deficits. Proceedings of the National Academy of Sciences of the United States of America. 1997;94:5401–5404. doi: 10.1073/pnas.94.10.5401. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. de Diego-Otero Y, Romero-Zerbo Y, el Bekay R, Decara J, et al. Alpha-tocopherol protects against oxidative stress in the fragile X knockout mouse: an experimental therapeutic approach for the Fmr1 deficiency. Neuropsychopharmacology. 2009;34:1011–1026. doi: 10.1038/npp.2008.152. [DOI] [PubMed] [Google Scholar]
  15. Gould TD, Einat H, O’Donnell KC, Picchini AM, et al. Beta-catenin overexpression in the mouse brain phenocopies lithium-sensitive behaviors. Neuropsychopharmacology. 2007;32:2173–2183. doi: 10.1038/sj.npp.1301338. [DOI] [PubMed] [Google Scholar]
  16. Grimes CA, Jope RS. The multifaceted roles of glycogen synthase kinase 3beta in cellular signaling. Progress in Neurobiology. 2001;65:391–426. doi: 10.1016/s0301-0082(01)00011-9. [DOI] [PubMed] [Google Scholar]
  17. Hagerman RJ. The physical and behavioral phenotype. In: Hagerman RJ, Hagerman PJ, editors. Fragile X syndrome: Diagnosis, treatment, and research. Baltimore: Johns Hopkins University Press; 2002. pp. 3–109. [Google Scholar]
  18. Hinton VJ, Brown WT, Wisniewski K, Rudelli RD. Analysis of neocortex in three males with the fragile X syndrome. American Journal of Medical Genetics. 1991;41:289–294. doi: 10.1002/ajmg.1320410306. [DOI] [PubMed] [Google Scholar]
  19. Hutsler J, Zhang H. Increased dendritic spine densities on cortical projection neurons in autism spectrum disorders. Brain Research. 2010;1309:83–94. doi: 10.1016/j.brainres.2009.09.120. [DOI] [PubMed] [Google Scholar]
  20. Jope RS, Roh MS. Glycogen synthase kinase-3 (GSK3) in psychiatric diseases and therapeutic interventions. Current Drug Targets. 2006;7:1421–1434. doi: 10.2174/1389450110607011421. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Klein PS, Melton DA. A molecular mechanism for the effect of lithium on development. Proceedings of the National Academy of Sciences of the United States of America. 1996;93:8455–8459. doi: 10.1073/pnas.93.16.8455. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Lim KY, Yang JJ, Lee DS, Noh JS, et al. Lithium attenuates stress-induced impairment of long-term potentiation induction. Neuroreport. 2005;16:1605–1608. doi: 10.1097/01.wnr.0000179078.54906.52. [DOI] [PubMed] [Google Scholar]
  23. Liu ZH, Smith CB. Dissociation of social and nonsocial anxiety in a mouse model of fragile X syndrome. Neuroscience Letter. 2009;454:62–66. doi: 10.1016/j.neulet.2009.02.066. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. McBride SM, Choi CH, Wang Y, Liebelt D, et al. Pharmacological rescue of synaptic plasticity, courtship behavior, and mushroom body defects in a Drosophila model of fragile X syndrome. Neuron. 2005;45:753–764. doi: 10.1016/j.neuron.2005.01.038. [DOI] [PubMed] [Google Scholar]
  25. McNaughton CH, Moon J, Strawderman MS, Maclean KN, et al. Evidence for social anxiety and impaired social cognition in a mouse model of fragile X syndrome. Behavioral Neuroscience. 2008;122:293–300. doi: 10.1037/0735-7044.122.2.293. [DOI] [PubMed] [Google Scholar]
  26. Min WW, Yuskaitis CJ, Yan Q, Sikorski C, et al. Elevated glycogen synthase kinase-3 activity in Fragile X mice: key metabolic regulator with evidence for treatment potential. Neuropharmacology. 2009;56:463–472. doi: 10.1016/j.neuropharm.2008.09.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Mineur YS, Huynh LX, Crusio WE. Social behavior deficits in the Fmr1 mutant mouse. Behavioural Brain Research. 2006;168:172–175. doi: 10.1016/j.bbr.2005.11.004. [DOI] [PubMed] [Google Scholar]
  28. Muir JL, Everitt BJ, Robbins TW. The cerebral cortex of the rat and visual attentional function: dissociable effects of mediofrontal, cingulate, anterior dorsolateral, and parietal cortex lesions on a five-choice serial reaction time task. Cerebral Cortex. 1996;6:470–481. doi: 10.1093/cercor/6.3.470. [DOI] [PubMed] [Google Scholar]
  29. Nachev P. Cognition and medial frontal cortex in health and disease. Current Opinion in Neurology. 2006;19:586–592. doi: 10.1097/01.wco.0000247609.36482.ae. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Nadler JJ, Moy SS, Dold G, Trang D, et al. Automated apparatus for quantitation of social approach behaviors in mice. Genes, Brain, and Behavior. 2004;3:303–314. doi: 10.1111/j.1601-183X.2004.00071.x. [DOI] [PubMed] [Google Scholar]
  31. Nielsen DM, Derber WJ, McClellan DA, Crnic LS. Alterations in the auditory startle response in Fmr1 targeted mutant mouse models of fragile X syndrome. Brain Research. 2002;927:8–17. doi: 10.1016/s0006-8993(01)03309-1. [DOI] [PubMed] [Google Scholar]
  32. Nocjar C, Hammonds MD, Shim SS. Chronic lithium treatment magnifies learning in rats. Neuroscience. 2007;150:774–788. doi: 10.1016/j.neuroscience.2007.09.063. [DOI] [PubMed] [Google Scholar]
  33. Moon J, Beaudin AE, Verosky S, Driscoll LL, et al. Attentional dysfunction, impulsivity, and resistance to change in a mouse model of fragile X syndrome. Behavioral Neuroscience. 2006;120:1367–1379. doi: 10.1037/0735-7044.120.6.1367. [DOI] [PubMed] [Google Scholar]
  34. Peier AM, McIlwain KL, Kenneson A, Warren ST, et al. (Over)correction of FMR1 deficiency with YAC transgenics: behavioral and physical features. Human Molecular Genetics. 2000;9:1145–1159. doi: 10.1093/hmg/9.8.1145. [DOI] [PubMed] [Google Scholar]
  35. Prasad V, Sheard M. Effect of lithium upon desipramine enhanced shock-elicited fighting in rats. Pharmacology, Biochemistry, and Behavior. 1982;17:377–378. doi: 10.1016/0091-3057(82)90097-1. [DOI] [PubMed] [Google Scholar]
  36. Qin M, Kang J, Burlin TV, Jiang C, et al. Postadolescent changes in regional cerebral protein synthesis: an in vivo study in the FMR1 null mouse. Journal of Neuroscience. 2005a;25:5087–5095. doi: 10.1523/JNEUROSCI.0093-05.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Qin M, Kang J, Smith CB. A null mutation for Fmr1 in female mice: effects on regional cerebral metabolic rate for glucose and relationship to behavior. Neuroscience. 2005b;135:999–1009. doi: 10.1016/j.neuroscience.2005.06.081. [DOI] [PubMed] [Google Scholar]
  38. Qin M, Kang J, Smith CB. Increased rates of cerebral glucose metabolism in a mouse model of fragile X mental retardation. Proceedings of the National Academy of Sciences of the United States of America. 2002;99:15758–15763. doi: 10.1073/pnas.242377399. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Rowe MK, Chuang DM. Lithium neuroprotection: molecular mechanisms and clinical implications. Expert Reviews in Molecular Medicine. 2004;6:1–18. doi: 10.1017/S1462399404008385. [DOI] [PubMed] [Google Scholar]
  40. Shepherd JK, Grewal SS, Fletcher A, Bill DJ, et al. Behavioural and pharmacological characterisation of the elevated “zero-maze” as an animal model of anxiety. Psychopharmacology (Berl) 1994;116:56–64. doi: 10.1007/BF02244871. [DOI] [PubMed] [Google Scholar]
  41. Shim SS, Hammonds MD, Ganocy SJ, Calabrese JR. Effects of sub-chronic lithium treatment on synaptic plasticity in the dentate gyrus of rat hippocampal slices. Progress in Neuro-psychopharmacology & Biological Psychiatry. 2007;31:343–347. doi: 10.1016/j.pnpbp.2006.09.008. [DOI] [PubMed] [Google Scholar]
  42. Shimizu M, Sakaue N, Kaito T, Ikeda R. Studies on the use of blood lithium concentrations in lithium therapy in Japan. International Pharmacopsychiatry. 1979;14:170–175. doi: 10.1159/000468375. [DOI] [PubMed] [Google Scholar]
  43. Spencer CM, Alekseyenko O, Serysheva E, Yuva-Paylor LA, et al. Altered anxiety-related and social behaviors in the Fmr1 knockout mouse model of fragile X syndrome. Genes, Brain, and Behavior. 2005;4:420–430. doi: 10.1111/j.1601-183X.2005.00123.x. [DOI] [PubMed] [Google Scholar]
  44. Tsaltas E, Kontis D, Boulougouris V, Papakosta VM, et al. Enhancing effects of chronic lithium on memory in the rat. Behavioural Brain Research. 2007;177:51–60. doi: 10.1016/j.bbr.2006.11.003. [DOI] [PubMed] [Google Scholar]
  45. Vasconcellos AP, Tabajara AS, Ferrari C, Rocha E, et al. Effect of chronic stress on spatial memory in rats is attenuated by lithium treatment. Physiology & Behavior. 2003;79:143–149. doi: 10.1016/s0031-9384(03)00113-6. [DOI] [PubMed] [Google Scholar]
  46. White NM, McDonald RJ. Multiple parallel memory systems in the brain of the rat. Neurobiology of Learning and Memory. 2002;77:125–184. doi: 10.1006/nlme.2001.4008. [DOI] [PubMed] [Google Scholar]
  47. Yan QJ, Asafo-Adjei PK, Arnold HM, Brown RE, et al. A phenotypic and molecular characterization of the fmr1-tm1Cgr fragile X mouse. Genes, Brain, and Behavior. 2004;3:337–359. doi: 10.1111/j.1601-183X.2004.00087.x. [DOI] [PubMed] [Google Scholar]
  48. Yuskaitis CJ, Mines MA, King MK, Sweatt D, et al. Lithium ameliorates altered glycogen synthase kinase-3 and behavior in a mouse model of fragile X syndrome. Biochemical Pharmacology. 2010;79:632–646. doi: 10.1016/j.bcp.2009.09.023. [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

Fig S-1
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Fig S-2
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Supl Text
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