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Neurobiology of Disease 73 (2015) 399–406
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18
FDG-microPET and MR DTI findings in Tor1a+/− heterozygous knock-out mice☆
An Vo a, Wataru Sako a, Stephen L. Dewey a,b,c, David Eidelberg a, Aziz M. Uluğ a,b,d,e,⁎ a
Center for Neurosciences, The Feinstein Institute for Medical Research, NY 11030, USA Department of Molecular Medicine, Hofstra University, NY 11549, USA Department of Psychiatry, New York University, NY 10012, USA d Department of Radiology, Albert Einstein College of Medicine, NY 10461, USA e Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Turkey b c
a r t i c l e
i n f o
Article history: Received 8 July 2014 Revised 23 October 2014 Accepted 29 October 2014 Available online 4 November 2014 Keywords: Tor1a TorsinA Heterozygous knock-out mice Dystonia DTI Glucose metabolism
a b s t r a c t TorsinA is an important protein in brain development, and plays a role in the regulation of neurite outgrowth and synaptic function. Patients with the most common form of genetic dystonia carry a mutation (DYT1) in one copy of the Tor1a gene, a 3-bp deletion, causing removal of a single glutamic acid from torsinA. Previous imaging studies have shown that abnormal cerebellar metabolism and damaged cerebello–thalamo-cortical pathway contribute to the pathophysiology of DYT1 dystonia. However, how a mutation in one copy of the Tor1a gene causes these abnormalities is not known. We studied Tor1a heterozygous knock-out mice in vivo with FDG-PET and ex vivo with diffusion tensor imaging. We found metabolic abnormalities in cerebellum, caudate–putamen, globus pallidus, sensorimotor cortex and subthalamic nucleus. We also found that FA was increased in caudate–putamen, sensorimotor cortex and brainstem. We compared our findings with a previous imaging study of the Tor1a knock-in mice. Our study suggested that having only one normal copy of Tor1a gene may be responsible for the metabolic abnormalities observed; having a copy of mutant Tor1a, on the other hand, may be responsible for white matter pathway damages seen in DYT1 dystonia subjects. © 2014 Elsevier Inc. All rights reserved.
TorsinA is a member of the AAA + superfamily of ATPases. It is thought to function as a molecular chaperone (Tanabe et al., 2009). This protein is primarily localized in the endoplasmic reticulum (ER) and in the nuclear envelope (Hewett et al., 2006). TorsinA plays a key role in the regulation of neurite outgrowth and synaptic function (Ferrari-Toninelli et al., 2004; Granata et al., 2008). The expression of torsinA is more abundant in cerebellar Purkinje cells and in neurons of the dentate nucleus and ventral thalamus (Augood et al., 1999; Konakova et al., 2001). Moreover, its expression is increased during cerebellar maturation (Xiao et al., 2004). Dystonia is a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both (Albanese et al., 2013). DYT1 dystonia, one of the inherited forms of the disease, is caused by 3-bp deletion in the Tor1a gene that removes a single glutamic acid (ΔE) from torsinA (Ozelius et al., 1997). Previous imaging studies have revealed that abnormal cerebellar metabolism and damaged cerebello–thalamo-cortical
☆ The authors declare no competing financial interests. This work is supported in part by a grant from the Bachmann–Strauss Dystonia and Parkinson Foundation. ⁎ Corresponding author at: Center for Neurosciences, The Feinstein Institute for Medical Research, 350 Community Drive, Manhasset, NY 11030, USA. Fax: +1 516 562 1008. E-mail addresses: [email protected], [email protected] (A.M. Uluğ). Available online on ScienceDirect (www.sciencedirect.com).
http://dx.doi.org/10.1016/j.nbd.2014.10.020 0969-9961/© 2014 Elsevier Inc. All rights reserved.
pathway contribute to the pathophysiology of DYT1 dystonia in humans (Argyelan et al., 2009; Vo et al., in press) and Tor1a knock-in mice (Ulug et al., 2011). However, how a mutation in one copy of the Tor1a gene causes these abnormalities is not known. Numerous knock-in, knockout, and transgenic models of DYT1 dystonia have been generated, and studied for behavior and structural abnormalities (Table 2 of ref: LeDoux, 2011). Previous PET studies on DYT1 patients showed increased metabolism in various areas including cerebellum, the basal ganglia, and supplementary motor areas (Trost et al., 2002; Eidelberg et al., 1998; Carbon et al., 2004a; Carbon and Eidelberg, 2009). Studies utilizing diffusion tensor imaging (DTI) revealed structural damage in white matter tracts of DYT1 patients manifesting as decreased FA in a multitude of areas, including superior cerebellar peduncle, supplementary motor area, and specifically cerebello-thalamic pathways (Carbon et al., 2004b, 2008; Argyelan et al., 2009; Vo et al., in press). The observed DTI changes had an important role in both penetrance (Argyelan et al., 2009) and phenotypic manifestations of dystonia (Vo et al., in press). We hypothesized that having one copy of the Tor1a gene influences the microstructure and metabolism of the brain in a manner which is different than the knock-in mouse, where the animal has a mutant copy in addition to one normal copy of the Tor1a gene. By studying mutant mice with a single copy of the Tor1a gene, information about the function of normal torsinA can be discerned; and by comparing the
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results of this study with the results of the previous imaging study of knock-in mice the effect of the mutant torsinA can be better inferred. We imaged Tor1a heterozygous knock-out mice in vivo with 18FDGPET and ex vivo with DTI. We compared our findings with a previous imaging study of Tor1a knock-in mice. Materials and methods We studied twenty-five male Tor1a heterozygous knock-out mice (Tor1a+/−) and twenty male wild-type littermate control animals (Tor1a+/+). Animals were obtained from Jackson Laboratories and described as B6; 129-Tor1atm1Wtd/J, strain 306251. Both mutant and littermate controls were housed together from birth to assure that all animals experienced as identical an environment as possible. At 18 weeks of age, animals were imaged in vivo with a Siemens Inveon microPET using 18FDG. 18
FDG-microPET
Animals received a mean dose of 1.5 mCi of 18FDG administered intra-peritoneally 45 min prior to static image acquisition. After the 45 min of uptake, animals were anesthetized by intra-peritoneal injection of ketamine/xylazine (100 mg/kg of a ketamine/xylazine cocktail of 10% xylazine and 90% ketamine). Animals were then positioned prone on a heated bed and moved into the gantry. A 10 min static acquisition was performed. The resulting images were reconstructed using an iterative algorithm (Nuyts and Fessler, 2003; Mirrione et al., 2007) to a voxel size of 0.3 × 0.3 × 0.8 mm. Following 18FDG microPET imaging all animals underwent transcardiac perfusion with 4% paraformaldehyde (Mori et al., 2001). Brains were then harvested and stored in 4% paraformaldehyde for at least two weeks. Fixed brains of eight Tor1a heterozygous knock-out mice (Tor1a+/−) and eight wild-type littermate control animals (Tor1a+/+) were then imaged using MR DTI. All animal procedures were approved by the Institute for Animal Care and Use Committee (IACUC) at the Feinstein Institute for Medical Research (FIMR). MR DTI Magnetic resonance DTI was performed ex vivo on whole brain samples using the 9.4 Tesla animal MR scanner at Johns Hopkins Medical Center. A RARE sequence was used in 6 diffusion gradient directions and two additional images with a b-value of 210 s/mm2 (Zhang et al., 2005). The maximum b-value in the diffusion weighted images was 2138 s/mm2. Each acquisition included 6 echos with 2 repetitions to improve the signal to noise ratio. The DTI protocol included 128 slices with 62.5 μm thickness. Images were zero-filled before Fourier transformation yielding a nominal DTI image resolution of 62.5 × 62.5 × 62.5 μm3 with a total ex vivo imaging time of approximately 20 h. Data analysis Main effects MicroPET images were registered to a SPMmouse MRI template (Sawiak et al., 2009). The bounding box and the origin of the registered images were set to maintain coherence with the Paxinos and Franklin stereotaxic coordinate space (Franklin and Paxinos, 2007). The analysis steps included: brain extraction, registration and spatial smoothing. Two groups of images were compared voxel-wise over the entire brain volume using SPMMouse software (http://www.wbic.cam.ac.uk/ ~sjs80/spmmouse.html), a toolbox for statistical parametric mapping (SPM) in the mouse (Sawiak et al., 2009). Group differences in regional metabolic activity were considered significant at a voxel-level threshold of p = 0.005 with a correction for multiple comparisons at p b 0.05.
After DTI data acquisition, diffusion tensor components for each brain voxel were calculated and fractional anisotropy (FA) maps were determined for all animals. We registered images with a bvalue of 210 s/mm2 to a standard template (Ma et al., 2005) using a 12-parameter affine transformation (Jenkinson et al., 2002); and then applied the resulting transformation to the individual FA maps to register them to standard space using FSL software (http://www. fmrib.ox.ac.uk/fsl/). Once aligned, the FA images were smoothed using a kernel of 312.5 μm (FWHM) for a two group comparison using SPMMouse software. The threshold for significance was p = 0.005 with a correction for multiple comparisons at p b 0.05. The individual data from the resulting clusters of both FA map and 18 FDG image comparisons were measured post-hoc. Post-hoc values for the Tor1a+/− heterozygous knock-out and control groups were displayed graphically using box-and-whisker plots to evaluate overlapping data and potential outlier effects. Each significant cluster within a given hemisphere was transposed to the opposite side and measured for the two groups. Metabolic activity and FA values for each significant cluster, on each hemisphere separately, were compared across groups using Student's t-tests and were considered significant at p b 0.05. Interaction effects To study the interaction effects of heterozygous knock-out and knock-in mice, we used eight Tor1a+/− heterozygous knock-out mice and eight Tor1a+/+ control animals from this study, and eight Tor1aΔE/+ knock-in mice and six Tor1a+/+ control animals from a previous study (Ulug et al., 2011). All animals were 18 weeks of age at the time of imaging in both datasets. We performed SPM voxel-based analyses to identify significant group × genotype (Tor1aΔE/+/ Tor1a+/−) interaction effects on regional metabolism (FDG-PET) as well as FA maps. For each interaction analysis, clusters were considered significant at a voxel-level threshold of p = 0.001 with a correction for multiple comparisons at p b 0.05. To evaluate these effects, clusters corresponding to significant regions were measured posthoc on the individual scans. For each cluster, changes were compared between groups or genotype using a two-factor ANOVA with post-hoc Bonferroni tests. Results were considered significant at p b 0.05. Tractography Tractography was performed to identify the projection pathways associated with significant interaction effects (group × genotype) on FA contrasts from each group using an early registration method (Vo et al., in press) and TrackVis software (http://www.trackvis.org/). Diffusion weighted images from each group were registered using an early registration method and the gradient vectors were reoriented for tensor calculation (Vo et al., in press). Tracking parameters were identical for all groups. The significant clusters identified by the interaction effects of the FA maps were employed as seed volumes for tractography. Tract reconstructions were displayed for each group and compared quantitatively based upon visualized tract count. Group differences in the number of tracts visualized were determined; the standard deviations of the means were estimated using the leave-one-out jackknife method (Efron and Tibshirani, 1998). Fiber counts were obtained for the reconstructed thalamo-striatal (TS), and pontine–cerebellum (PCb) tracts from each group by leaving out one animal at a time from the group set. Group differences in fiber counts were also separately evaluated for each tract using the Mann– Whitney U test. The statistical tests were performed using SPSS software (SPSS Inc., Chicago, IL) and were considered significant at p b 0.05. Results 18
FDG-microPET
To identify metabolic activity changes associated with Tor1a+/− heterozygous knock-out mice, we compared 18FDG microPET scans from
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heterozygous knock-out mice and control by voxel-by-voxel basis. 18 FDG images revealed five brain regions with abnormal glucose utilization in the Tor1a+/− heterozygous knock-out mice (Table 1). A single brain region (Fig. 1A) was localized to the cerebellar vermis (lobule IV/V) (Franklin and Paxinos, 2007) with increased local metabolic activity in heterozygous knock-out relative to control animals (p b 0.001, Student's t-test). Four discrete regions with decreased local metabolic activity in heterozygous knock-out mice relative to control animals (Fig. 1B) were localized to the right caudate–putamen (p b 0.005, Student's t-test), left globus pallidus (p b 0.001, Student's t-test), sensorimotor cortex (p b 0.001, Student's t-test), and the subthalamic nucleus (p b 0.005, Student's t-test) and, of note, the metabolic activity changes in these regions were also significant (p b 0.05) in homologous areas on the opposite side of the brain when measured post-hoc, with the exception of the region in the caudate–putamen (p = 0.08).
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FA interaction effect A whole brain voxel-wise search was also conducted to identify brain regions in which the changes in FA maps with respect to control animals differed for Tor1aΔE/+ and Tor1a+/− animals. This interaction (group × genotype) analysis revealed two regions localized to the caudate–putamen and pons (Fig. 3, Table 2), in which a significant difference was found between the two groups of animals. In the putamen: F(1,26) = 22.3, p b 0.001; in pons: F(1,26) = 18.4, P b 0.001; twoway ANOVA. In these two regions, compared with the control group FA in the Tor1aΔE/+ animals was significantly decreased (p b 0.005 in putamen and p b 0.05, in pons, post-hoc Bonferroni tests). In contrast, the Tor1a+/− group had an increase in FA (p b 0.005 both in putamen and pons, post-hoc Bonferroni tests). Tractography
FA We next determined microstructural changes associated with Tor1a+/− heterozygous knock-out mice (Table 1). Significant increases in FA were present in the Tor1a+/− heterozygous knock-out animals relative to controls (Fig. 2) in three clusters. These clusters were located at the left caudate–putamen, the left sensorimotor cortex (both p b 0.001, Student's t-tests), and brainstem (p b 0.005, Student's t-tests). No significant changes were found in the contralateral hemisphere of these three clusters. We also compared the results of this study with our previous study of Tor1a knock-in mice by doing an interaction analysis.
Using the two clusters found in interaction analysis (Fig. 3, Table 2), we visualized two pathways in both knock-in and heterozygous knockout animals: pontine–cerebellum (PCb) and thalamo-striatal (TS) tracts (Fig. 4). In the heterozygous knock-out experiment, there were no significant differences in tract counts in both pathways (PCb, p = 0.115; and TS, p N 0.99, Mann–Whitney U) between Tor1a+/− heterozygous knock-out and control animals. In the knock-in experiment, the tracts counts were significantly reduced in Tor1aΔE/+ mutants in both pathways when compared with the control animals. In the PCb pathway the tract counts decreased 48% in knock-in animals (Mann–Whitney U, p b 0.05) and in the TS pathway the decrease in knock-in animals was 28% (Mann–Whitney U, p b 0.005) when compared with control animals.
Metabolic activity interaction effect Discussion A whole brain voxel-wise search was conducted to identify brain regions in which the changes of metabolic activity differed for Tor1aΔE/+ and Tor1a+/− animals when compared to the respective controls. However, there were no regions with significant differences in changes of metabolic activity between Tor1aΔE/+ and Tor1a+/− animals.
Table 1 Voxel-based comparison of regional metabolic activity and fractional anisotropy (FA) in Tor1a+/− heterozygous knock-out vs. Tor1a+/+ control animals. Coordinatesa y
z
Cluster sizeb
Zmax
p-Valuec
0.5
−5.8
−1.6
1821
3.37
0.001
Subthalamic nucleus
3.4 −1.5 −2.2 2.4 −4.4 2.4
−0.2 −0.3 −1.4 −2.0 0.1 −2.0
−2.8 −4.2 −0.1 −0.2 −2.1 −4.3
1666 5275 3982 6594 3879 2629
3.41 4.37 3.26 3.84 3.57 3.73
0.001 0.001 0.001 0.001 0.001 0.001
FA Tor1a+/− N Control Caudate–putamen Sensorimotor cortex Brainstem
−1.7 −2.8 −0.1
0.0 1.6 −7.9
−2.9 −1.3 −5.7
394 268 105
3.52 3.39 3.22
0.001 0.001 0.001⁎
Region Metabolism Tor1a+/− N Control Cerebellar vermis (lobule IV/V)d Tor1a+/− b Control Caudate–putamen Globus pallidus Sensorimotor cortex
a
x
Coordinates according to the common space of SPMMouse (Sawiak et al., 2009). Cluster size in voxels (1 voxel = 3.4 × 10−4 mm3). c Clusters are significant at p b 0.05 corrected for cluster extent. Clusters with significant (p b 0.05, Student's t-test) additional changes in the contralateral (“mirror”) hemisphere are presented in bold. d According to the atlas of Franklin and Paxinos (2007). ⁎ Uncorrected, at the voxel level. b
We found a significant increase in metabolic activity in heterozygous knock-out mice in the cerebellum (lobule IV/V), involving areas connected via the thalamus with motor cortex (Coffman et al., 2011). The localization of this abnormality accords with our prior observations in DYT1 knock-in mice (Ulug et al., 2011) and in human gene carriers (Eidelberg et al., 1998; Carbon and Eidelberg, 2009). While the exact cause of increased metabolism in the cerebellar regions cannot be discerned in our study, one can speculate that decreased inhibitory inputs to these cerebellar regions may be the cause of this increased metabolism. Previous studies reported shorter primary dendrites in addition to a decrease in the number of spines on distal dendrites of Purkinje cells, as well as reduced complexity in dendrites in TorsinA Purkinje specific knock-out animals (Zhang et al., 2011). The decreased inhibitory activity of Purkinje cells may be responsible for the increased metabolism. We found four regions of decreased metabolism in the caudate– putamen, globus palladus, subthalamic nuclei, and sensorimotor cortex of heterozygous knock-out mice. Since there is evidence of decreased dendrite branching of neurons in both knock-in and knock-out (Zhang et al., 2011; Song et al., 2013; Song et al., 2014) animals, the decreased metabolism may be the result of overall decreased excitatory input to these areas. While this Tor1a+/− heterozygous knock-out mouse model is not a model of dystonia, previous studies of DYT1 patients also reported abnormal metabolism in the lentiform nucleus (Eidelberg et al., 1998), putamen/GP (Trost et al., 2002), putamen (Carbon et al., 2004a,b; Carbon and Eidelberg, 2009), pre-motor cortex and SMA (Eidelberg et al., 1995), SMA (Trost et al., 2002), pre-SMA (Carbon et al., 2004a,b) and pre-SMA and pre-motor (Carbon and Eidelberg, 2009). Also a recent study of transgenic mice with human mutant torsinA reported decreased glucose utilization in the globus pallidus (Zhao et al., 2011).
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Fig. 2. Regions with abnormal microstructure in Tor1a+/− heterozygous knock-out mice. Significant increases in fractional anisotropy (FA) were present in the following brain areas of the Tor1a+/− heterozygous knock-out animals (Table 1): caudate–putamen, and sensorimotor cortex (both p b 0.001, Student's t-tests); and brainstem (p b 0.005, Student's t-test). The color scale represents voxels thresholded at T = 2.98, p = 0.005.
Our findings of abnormal metabolism in heterozygous knock-out mice in the areas that were previously reported to be abnormal in patients carrying DYT1 mutation are suggestive of the existence of a specific network that depends on normal levels of Tor1A in the brain. In this study, we found three regions with increased FA in heterozygous knock-out mice. One region is in the sensorimotor cortex; the other is in the middle of caudate–putamen; and the third is in the brainstem. The mouse brain, just after birth, has relatively high diffusion anisotropy in both gray and white matter (Mori and Zhang, 2006). Upon development, white matter anisotropy increases upon myelination while gray matter anisotropy decreases rapidly. This phenomenon relates to the dendrite growth in gray matter. Growing dendrites decrease the coherence of water diffusion within gray matter (Mori and Zhang, 2006) leading to a reduction in the observed diffusion anisotropy. If dendrites
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failed to grow and did not decrease the coherence of water diffusion, the diffusion anisotropy would remain elevated. Histological studies of DYT1 knock-in and conditional knock-out mice showed (Zhang et al., 2011) a reduction in the length of primary dendrites as well as a decrease in the number of spines on distal dendrites of Purkinje cells. The reduction of the length of the primary dendrite in knock-out animals was more pronounced (37%) than knock-in animals (20%). Also, the decrease of the distal dentrites was larger in magnitude in knockout (33%) than in knock-in (27%) animals. This would make the FA increases in gray matter more prominent in knock-out animals compared to knock-in animals. Thinner dendrites and less complex dendritic spines in Purkinje cells were also reported in another model of DYT1 knock-in mice (Song et al., 2014). A different study showed that in the striatum of DYT1 mice, there are slightly fewer and thinner dendrites, and there is also a loss of dendritic spines in the medium spiny projection neurons (Song et al., 2013). The previously reported decreases in dendritic development in heterozygous knock-out mice are compatible with our finding of increased FA in these gray matter regions. There is also another study of a mutant mouse model demonstrating an overexpression of torsinA resulting in striatal FA increases (Grundmann et al., 2007), suggesting that abnormal levels of torsinA may interfere with dendritic development, resulting in increased FA in the striatum. Our previous study of DYT1 knock-in mice showed decreased areas of FA in white matter regions (Ulug et al., 2011). Since mutant torsinA interferes with cytoskeletal dynamics (Hewett et al., 2006), decreased FA in white matter bundles could have resulted from the dominant negative effect of mutant torsinA in knock-in mice. In the current study, a single region of increased FA was identified in the brainstem. In our previous study of knock-in mice, we found three separate regions with decreased FA in the pons. Our interaction analysis of heterozygous knock-out and knock-in experiments revealed a large region in the pons. A previous study of DYT1 knock-in mice model reported the ubiquitin- and torsinA-containing aggregates in the neurons of the pontine nuclei (Sashidaran et al., 2004; Dang et al., 2005) suggesting the importance of proper function of torsinA in the pons. In this study, we did not find any evidence of significant (Mann– Whitney U, p N 0.11) white matter tract differences in Tor1a+/− heterozygous knock-out animals compared to controls. In our previous study of Tor1aΔE/+ knock-in animals, there were significant tract differences between Tor1aΔE/+ and control animals, with decreased numbers of tracts in mutant Tor1aΔE/+ animals. This result further suggests that mutant torsinA, through a dominant negative effect, was responsible for the decrease in the number of tracts in knock-in animals. While it is possible that there is a “dose” effect whereby heterozygous knock-out has about 50% of Tor1A, and while DYT1 knock-in mice have much less Tor1A due to a dominant negative effect of the mutation, this dose effect could not explain all of our findings. If dose effect was the only cause of abnormalities found, one would expect that the results of the knock-in experiment would be similar to the heterozygous knock-out experiment but only stronger. Our results show that this is not the case. The decrease in FA was only seen in gray matter regions in the heterozygous knock-out experiment but not in the knock-in experiment. At the same time, the white matter FA reductions were seen only in the knock-in experiment. Together these results suggest two separate affects at work, and DYT1 mutation is responsible for the white matter abnormalities observed.
Fig. 1. Metabolic abnormalities in the Tor1a+/− heterozygous knock-out mice. A. An abnormal increase in regional metabolic activity (p b 0.001, Student's t-test) was detected in the cerebellar vermis (lobule IV/V) of the Tor1a+/− heterozygous knock-out mice (Table 1). Individual values for this cluster in the Tor1a+/− heterozygous knock-out and control animals are represented by box-and-whisker plots. The color scale represents voxels thresholded at T = 2.70, p = 0.005. B. Significant reductions in regional metabolic activity were present in the following brain areas of the Tor1a+/− heterozygous knock-out animals: right caudate–putamen (p b 0.005, Student's t-test); left globus pallidus (p b 0.001, Student's t-test); sensorimotor cortex (p b 0.001, Student's t-test), and subthalamic nucleus (p b 0.005, Student's t-test). Metabolic activity values were normalized (z-scored) with respect to measurements from the control group.
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Fig. 3. Interaction effect of Tor1aΔE/+ knock-in and Tor1a+/− heterozygous knock-out animals in fractional anisotropy (FA). The interaction analysis (group × genotype) revealed two regions localized to the caudate–putamen and the pons (Table 2) in which a significant difference in changes of FA maps was found between the Tor1aΔE/+ and Tor1a+/− animals. In putamen: F(1,26) = 22.3, p b 0.001; in pons: F(1,26) = 18.4, p b 0.001; two-way ANOVA. In these two regions, compared with the control group, FA in the Tor1aΔE/+ animals significantly decreased (p b 0.005 in putamen and p b 0.05, in pons, post-hoc Bonferroni tests). In contrast, the Tor1a+/− group had an increase in FA (p b 0.005, both in putamen and pons, posthoc Bonferroni tests). FA values were normalized (z-scored) with respect to measurements from the corresponding control group. The color scale represents voxels thresholded at T = 2.78, p = 0.005.
If one considers what happens to a subject with DYT1 mutation in the terms of loss or gain of function: there is loss of function because there is only one normal allele that remains; at the same time there is a gain of function because of the effects of the mutant protein.
Cluster sizeb
Zmax
p-Valuec
found in gray matter regions are the evidence of decreased neurite extensions in the gray matter. The metabolic abnormalities found suggest that these neurite extension decreases result in decreased synaptic connections, and therefore cause decreased inhibitory or excitatory inputs to the affected regions. Comparison of our results with the previous imaging study of knock-in animals shows that the white matter abnormalities found in knock-in animals may be mainly due to the mutant torsinA interfering with cytoskeletal dynamics in the development of the white matter bundles with a dominant negative effect. Our results may suggest that the imaging findings reported in DYT1 dystonia subjects can be explained. The lack of normal levels of torsinA due to having only one copy of the normal Tor1a gene may be responsible for the abnormal metabolic changes seen in the DYT1 dystonia patients; having mutant torsinA, on the other hand, may be responsible for the white matter tract damages observed in these patients.
225 975
4.31 4.25
b0.001 b0.001
Acknowledgments
Conclusions Our imaging findings show that having one copy of the Tor1a gene has structural and functional consequences. Increased FA clusters Table 2 Voxel-based fractional anisotropy interaction effect of Tor1aΔE/+ knock-in and Tor1a+/− heterozygous knock-out animals. Coordinatesa Region
x ΔE/+
y
z +/−
Control — Tor1a N Control — Tor1a Caudate–putamen −2.3 −0.2 Pons 0.4 −5.6 a b c
−2.3 −5.0
Coordinates according to the common space of SPMMouse (Sawiak et al., 2009). Cluster size in voxels (1 voxel = 3.4 × 10−4 mm3). Clusters are significant at p b 0.05 corrected for cluster extent.
This work is supported in part by a grant from the Bachmann– Strauss Dystonia and Parkinson Foundation.
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Fig. 4. Pontine–cerebellum and thalamo-striatal tracts. The two regions (caudate–putamen and the pons) determined in interaction analysis were used in visualizing white matter tracts in both knock-in (left) and heterozygous knock-out animals (right) and their respective controls. Pontine–cerebellum (PCb) tracts and thalamo-striatal (TS) tracts are displayed in white. The red region is in the caudate–putamen (Table 2, region 1), and the green region is in the pons (Table 2, region 2). Thalamus is shown in blue.
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human ΔGAG torsinA in a transgenic mouse model causes phenotypic abnormalities. Neurobiol. Dis. 27, 190–206. Hewett, J.W., Zeng, J., Niland, B.P., Bragh, D.C., Breakefield, X.O., 2006. Dystonia-causing mutant torsinA inhibits cell adhesion and neurite extension through interference with cytoskeletal dynamics. Neurobiol. Dis. 22, 98–111. Jenkinson, M., Bannister, P., Brady, M., Smith, S., 2002. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17, 825–841. Konakova, M., Huynh, D.P., Yong, M., Polst, S.M., 2001. Cellular distribution of torsin A and torsin B in normal human brain. Arch. Neurol. 58, 921–927. LeDoux, M.S., 2011. Animal models of dystonia: lessons from a mutant rat. Neurobiol. Dis. 42, 152–161. Ma, Y., Hof, P.R., Grant, S.C., Blackband, S.J., Bennett, R., Slatest, L., McGuigan, M.D., Benveniste, H., 2005. A three-dimensional digital atlas database of the adult C57BL/ 6J mouse brain by magnetic resonance microscopy. Neuroscience 135 (4), 1203–1215. Mirrione, M.M., Schiffer, W.K., Fowler, J.S., Alexoff, D.L., Dewey, S.L., Tsirka, S.E., 2007. A novel approach for imaging brain–behavior relationships in mice reveals unexpected metabolic patterns during seizures in the absence of tissue plasminogen activator. Neuroimage 38 (1), 34–42. Mori, S., Zhang, J., 2006. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51, 527–539. Mori, S., Itoh, R., Zhang, J., Kaufmann, W.E., van Zijl, P.C., Solaiyappan, M., Yarowsky, P., 2001. Diffusion tensor imaging of the developing mouse brain. Magn. Reson. Med. 46 (1), 18–23. Nuyts, J., Fessler, J.A., 2003. A penalized-likelihood image reconstruction method for emission tomography, compared to postsmoothed maximum-likelihood with matched spatial resolution. IEEE Trans. Med. Imaging 22 (9), 1042–1052. Ozelius, L.J., Hewett, J.W., Page, C.E., Bressman, S.B., Kramer, P.L., Shalish, C., de Leon, D., Brin, M.F., Raymond, D., Corey, D.P., Fahn, S., Risch, N.J., Buckler, A.J., Gusella, J.F., Breakefield, X.O., 1997. The early-onset torsion dystonia gene (DYT1) encodes an ATP-binding protein. Nat. Genet. 17, 40–48. Sashidaran, P., Sandu, D., Potla, U., Armata, I.A., Walker, I.A., McNaught, K.S., Weisz, D., Sreenath, T., Brin, M.F., Olanaw, C.W., 2004. Transgenic mouse model of early-onset DYT1 dystonia. Hum. Mol. Genet. 14 (1), 125–133. Sawiak, S.J., Wood, N.I., Williams, G.B., Morton, A.J., Carpenter, T.A., 2009. Voxelbased morphometry in the R6/2 transgenic mouse reveals differences between genotypes not seen with manual 2D morphometry. Neurobiol. Dis. 33 (1), 20–27. Song, C.H., Bernhard, D., Bolarinwa, C., Hess, E.J., Smith, Y., Jinnah, H.A., 2013. Subtle microstructural changes of the striatum in a DYT1 knock-in mouse model of dystonia. Neurobiol. Dis. 54, 362–371. Song, C.H., Bernhard, D., Hess, E.J., Jinnah, H.A., 2014. Subtle microstructural changes of the cerebellum in a knock-in mouse model of DYT1 dystonia. Neurobiol. Dis. 62, 372–380. Tanabe, L.M., Kim, C.E., Alagem, N., Dauer, W.T., 2009. Primary dystonia: molecules and mechanisms. Nat. Rev. Neurol. 5, 598–609.
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18
FDG-microPET and MR DTI findings in Tor1a+/− heterozygous knock-out mice☆
An Vo a, Wataru Sako a, Stephen L. Dewey a,b,c, David Eidelberg a, Aziz M. Uluğ a,b,d,e,⁎ a
Center for Neurosciences, The Feinstein Institute for Medical Research, NY 11030, USA Department of Molecular Medicine, Hofstra University, NY 11549, USA Department of Psychiatry, New York University, NY 10012, USA d Department of Radiology, Albert Einstein College of Medicine, NY 10461, USA e Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Turkey b c
a r t i c l e
i n f o
Article history: Received 8 July 2014 Revised 23 October 2014 Accepted 29 October 2014 Available online 4 November 2014 Keywords: Tor1a TorsinA Heterozygous knock-out mice Dystonia DTI Glucose metabolism
a b s t r a c t TorsinA is an important protein in brain development, and plays a role in the regulation of neurite outgrowth and synaptic function. Patients with the most common form of genetic dystonia carry a mutation (DYT1) in one copy of the Tor1a gene, a 3-bp deletion, causing removal of a single glutamic acid from torsinA. Previous imaging studies have shown that abnormal cerebellar metabolism and damaged cerebello–thalamo-cortical pathway contribute to the pathophysiology of DYT1 dystonia. However, how a mutation in one copy of the Tor1a gene causes these abnormalities is not known. We studied Tor1a heterozygous knock-out mice in vivo with FDG-PET and ex vivo with diffusion tensor imaging. We found metabolic abnormalities in cerebellum, caudate–putamen, globus pallidus, sensorimotor cortex and subthalamic nucleus. We also found that FA was increased in caudate–putamen, sensorimotor cortex and brainstem. We compared our findings with a previous imaging study of the Tor1a knock-in mice. Our study suggested that having only one normal copy of Tor1a gene may be responsible for the metabolic abnormalities observed; having a copy of mutant Tor1a, on the other hand, may be responsible for white matter pathway damages seen in DYT1 dystonia subjects. © 2014 Elsevier Inc. All rights reserved.
TorsinA is a member of the AAA + superfamily of ATPases. It is thought to function as a molecular chaperone (Tanabe et al., 2009). This protein is primarily localized in the endoplasmic reticulum (ER) and in the nuclear envelope (Hewett et al., 2006). TorsinA plays a key role in the regulation of neurite outgrowth and synaptic function (Ferrari-Toninelli et al., 2004; Granata et al., 2008). The expression of torsinA is more abundant in cerebellar Purkinje cells and in neurons of the dentate nucleus and ventral thalamus (Augood et al., 1999; Konakova et al., 2001). Moreover, its expression is increased during cerebellar maturation (Xiao et al., 2004). Dystonia is a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both (Albanese et al., 2013). DYT1 dystonia, one of the inherited forms of the disease, is caused by 3-bp deletion in the Tor1a gene that removes a single glutamic acid (ΔE) from torsinA (Ozelius et al., 1997). Previous imaging studies have revealed that abnormal cerebellar metabolism and damaged cerebello–thalamo-cortical
☆ The authors declare no competing financial interests. This work is supported in part by a grant from the Bachmann–Strauss Dystonia and Parkinson Foundation. ⁎ Corresponding author at: Center for Neurosciences, The Feinstein Institute for Medical Research, 350 Community Drive, Manhasset, NY 11030, USA. Fax: +1 516 562 1008. E-mail addresses: [email protected], [email protected] (A.M. Uluğ). Available online on ScienceDirect (www.sciencedirect.com).
http://dx.doi.org/10.1016/j.nbd.2014.10.020 0969-9961/© 2014 Elsevier Inc. All rights reserved.
pathway contribute to the pathophysiology of DYT1 dystonia in humans (Argyelan et al., 2009; Vo et al., in press) and Tor1a knock-in mice (Ulug et al., 2011). However, how a mutation in one copy of the Tor1a gene causes these abnormalities is not known. Numerous knock-in, knockout, and transgenic models of DYT1 dystonia have been generated, and studied for behavior and structural abnormalities (Table 2 of ref: LeDoux, 2011). Previous PET studies on DYT1 patients showed increased metabolism in various areas including cerebellum, the basal ganglia, and supplementary motor areas (Trost et al., 2002; Eidelberg et al., 1998; Carbon et al., 2004a; Carbon and Eidelberg, 2009). Studies utilizing diffusion tensor imaging (DTI) revealed structural damage in white matter tracts of DYT1 patients manifesting as decreased FA in a multitude of areas, including superior cerebellar peduncle, supplementary motor area, and specifically cerebello-thalamic pathways (Carbon et al., 2004b, 2008; Argyelan et al., 2009; Vo et al., in press). The observed DTI changes had an important role in both penetrance (Argyelan et al., 2009) and phenotypic manifestations of dystonia (Vo et al., in press). We hypothesized that having one copy of the Tor1a gene influences the microstructure and metabolism of the brain in a manner which is different than the knock-in mouse, where the animal has a mutant copy in addition to one normal copy of the Tor1a gene. By studying mutant mice with a single copy of the Tor1a gene, information about the function of normal torsinA can be discerned; and by comparing the
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results of this study with the results of the previous imaging study of knock-in mice the effect of the mutant torsinA can be better inferred. We imaged Tor1a heterozygous knock-out mice in vivo with 18FDGPET and ex vivo with DTI. We compared our findings with a previous imaging study of Tor1a knock-in mice. Materials and methods We studied twenty-five male Tor1a heterozygous knock-out mice (Tor1a+/−) and twenty male wild-type littermate control animals (Tor1a+/+). Animals were obtained from Jackson Laboratories and described as B6; 129-Tor1atm1Wtd/J, strain 306251. Both mutant and littermate controls were housed together from birth to assure that all animals experienced as identical an environment as possible. At 18 weeks of age, animals were imaged in vivo with a Siemens Inveon microPET using 18FDG. 18
FDG-microPET
Animals received a mean dose of 1.5 mCi of 18FDG administered intra-peritoneally 45 min prior to static image acquisition. After the 45 min of uptake, animals were anesthetized by intra-peritoneal injection of ketamine/xylazine (100 mg/kg of a ketamine/xylazine cocktail of 10% xylazine and 90% ketamine). Animals were then positioned prone on a heated bed and moved into the gantry. A 10 min static acquisition was performed. The resulting images were reconstructed using an iterative algorithm (Nuyts and Fessler, 2003; Mirrione et al., 2007) to a voxel size of 0.3 × 0.3 × 0.8 mm. Following 18FDG microPET imaging all animals underwent transcardiac perfusion with 4% paraformaldehyde (Mori et al., 2001). Brains were then harvested and stored in 4% paraformaldehyde for at least two weeks. Fixed brains of eight Tor1a heterozygous knock-out mice (Tor1a+/−) and eight wild-type littermate control animals (Tor1a+/+) were then imaged using MR DTI. All animal procedures were approved by the Institute for Animal Care and Use Committee (IACUC) at the Feinstein Institute for Medical Research (FIMR). MR DTI Magnetic resonance DTI was performed ex vivo on whole brain samples using the 9.4 Tesla animal MR scanner at Johns Hopkins Medical Center. A RARE sequence was used in 6 diffusion gradient directions and two additional images with a b-value of 210 s/mm2 (Zhang et al., 2005). The maximum b-value in the diffusion weighted images was 2138 s/mm2. Each acquisition included 6 echos with 2 repetitions to improve the signal to noise ratio. The DTI protocol included 128 slices with 62.5 μm thickness. Images were zero-filled before Fourier transformation yielding a nominal DTI image resolution of 62.5 × 62.5 × 62.5 μm3 with a total ex vivo imaging time of approximately 20 h. Data analysis Main effects MicroPET images were registered to a SPMmouse MRI template (Sawiak et al., 2009). The bounding box and the origin of the registered images were set to maintain coherence with the Paxinos and Franklin stereotaxic coordinate space (Franklin and Paxinos, 2007). The analysis steps included: brain extraction, registration and spatial smoothing. Two groups of images were compared voxel-wise over the entire brain volume using SPMMouse software (http://www.wbic.cam.ac.uk/ ~sjs80/spmmouse.html), a toolbox for statistical parametric mapping (SPM) in the mouse (Sawiak et al., 2009). Group differences in regional metabolic activity were considered significant at a voxel-level threshold of p = 0.005 with a correction for multiple comparisons at p b 0.05.
After DTI data acquisition, diffusion tensor components for each brain voxel were calculated and fractional anisotropy (FA) maps were determined for all animals. We registered images with a bvalue of 210 s/mm2 to a standard template (Ma et al., 2005) using a 12-parameter affine transformation (Jenkinson et al., 2002); and then applied the resulting transformation to the individual FA maps to register them to standard space using FSL software (http://www. fmrib.ox.ac.uk/fsl/). Once aligned, the FA images were smoothed using a kernel of 312.5 μm (FWHM) for a two group comparison using SPMMouse software. The threshold for significance was p = 0.005 with a correction for multiple comparisons at p b 0.05. The individual data from the resulting clusters of both FA map and 18 FDG image comparisons were measured post-hoc. Post-hoc values for the Tor1a+/− heterozygous knock-out and control groups were displayed graphically using box-and-whisker plots to evaluate overlapping data and potential outlier effects. Each significant cluster within a given hemisphere was transposed to the opposite side and measured for the two groups. Metabolic activity and FA values for each significant cluster, on each hemisphere separately, were compared across groups using Student's t-tests and were considered significant at p b 0.05. Interaction effects To study the interaction effects of heterozygous knock-out and knock-in mice, we used eight Tor1a+/− heterozygous knock-out mice and eight Tor1a+/+ control animals from this study, and eight Tor1aΔE/+ knock-in mice and six Tor1a+/+ control animals from a previous study (Ulug et al., 2011). All animals were 18 weeks of age at the time of imaging in both datasets. We performed SPM voxel-based analyses to identify significant group × genotype (Tor1aΔE/+/ Tor1a+/−) interaction effects on regional metabolism (FDG-PET) as well as FA maps. For each interaction analysis, clusters were considered significant at a voxel-level threshold of p = 0.001 with a correction for multiple comparisons at p b 0.05. To evaluate these effects, clusters corresponding to significant regions were measured posthoc on the individual scans. For each cluster, changes were compared between groups or genotype using a two-factor ANOVA with post-hoc Bonferroni tests. Results were considered significant at p b 0.05. Tractography Tractography was performed to identify the projection pathways associated with significant interaction effects (group × genotype) on FA contrasts from each group using an early registration method (Vo et al., in press) and TrackVis software (http://www.trackvis.org/). Diffusion weighted images from each group were registered using an early registration method and the gradient vectors were reoriented for tensor calculation (Vo et al., in press). Tracking parameters were identical for all groups. The significant clusters identified by the interaction effects of the FA maps were employed as seed volumes for tractography. Tract reconstructions were displayed for each group and compared quantitatively based upon visualized tract count. Group differences in the number of tracts visualized were determined; the standard deviations of the means were estimated using the leave-one-out jackknife method (Efron and Tibshirani, 1998). Fiber counts were obtained for the reconstructed thalamo-striatal (TS), and pontine–cerebellum (PCb) tracts from each group by leaving out one animal at a time from the group set. Group differences in fiber counts were also separately evaluated for each tract using the Mann– Whitney U test. The statistical tests were performed using SPSS software (SPSS Inc., Chicago, IL) and were considered significant at p b 0.05. Results 18
FDG-microPET
To identify metabolic activity changes associated with Tor1a+/− heterozygous knock-out mice, we compared 18FDG microPET scans from
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heterozygous knock-out mice and control by voxel-by-voxel basis. 18 FDG images revealed five brain regions with abnormal glucose utilization in the Tor1a+/− heterozygous knock-out mice (Table 1). A single brain region (Fig. 1A) was localized to the cerebellar vermis (lobule IV/V) (Franklin and Paxinos, 2007) with increased local metabolic activity in heterozygous knock-out relative to control animals (p b 0.001, Student's t-test). Four discrete regions with decreased local metabolic activity in heterozygous knock-out mice relative to control animals (Fig. 1B) were localized to the right caudate–putamen (p b 0.005, Student's t-test), left globus pallidus (p b 0.001, Student's t-test), sensorimotor cortex (p b 0.001, Student's t-test), and the subthalamic nucleus (p b 0.005, Student's t-test) and, of note, the metabolic activity changes in these regions were also significant (p b 0.05) in homologous areas on the opposite side of the brain when measured post-hoc, with the exception of the region in the caudate–putamen (p = 0.08).
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FA interaction effect A whole brain voxel-wise search was also conducted to identify brain regions in which the changes in FA maps with respect to control animals differed for Tor1aΔE/+ and Tor1a+/− animals. This interaction (group × genotype) analysis revealed two regions localized to the caudate–putamen and pons (Fig. 3, Table 2), in which a significant difference was found between the two groups of animals. In the putamen: F(1,26) = 22.3, p b 0.001; in pons: F(1,26) = 18.4, P b 0.001; twoway ANOVA. In these two regions, compared with the control group FA in the Tor1aΔE/+ animals was significantly decreased (p b 0.005 in putamen and p b 0.05, in pons, post-hoc Bonferroni tests). In contrast, the Tor1a+/− group had an increase in FA (p b 0.005 both in putamen and pons, post-hoc Bonferroni tests). Tractography
FA We next determined microstructural changes associated with Tor1a+/− heterozygous knock-out mice (Table 1). Significant increases in FA were present in the Tor1a+/− heterozygous knock-out animals relative to controls (Fig. 2) in three clusters. These clusters were located at the left caudate–putamen, the left sensorimotor cortex (both p b 0.001, Student's t-tests), and brainstem (p b 0.005, Student's t-tests). No significant changes were found in the contralateral hemisphere of these three clusters. We also compared the results of this study with our previous study of Tor1a knock-in mice by doing an interaction analysis.
Using the two clusters found in interaction analysis (Fig. 3, Table 2), we visualized two pathways in both knock-in and heterozygous knockout animals: pontine–cerebellum (PCb) and thalamo-striatal (TS) tracts (Fig. 4). In the heterozygous knock-out experiment, there were no significant differences in tract counts in both pathways (PCb, p = 0.115; and TS, p N 0.99, Mann–Whitney U) between Tor1a+/− heterozygous knock-out and control animals. In the knock-in experiment, the tracts counts were significantly reduced in Tor1aΔE/+ mutants in both pathways when compared with the control animals. In the PCb pathway the tract counts decreased 48% in knock-in animals (Mann–Whitney U, p b 0.05) and in the TS pathway the decrease in knock-in animals was 28% (Mann–Whitney U, p b 0.005) when compared with control animals.
Metabolic activity interaction effect Discussion A whole brain voxel-wise search was conducted to identify brain regions in which the changes of metabolic activity differed for Tor1aΔE/+ and Tor1a+/− animals when compared to the respective controls. However, there were no regions with significant differences in changes of metabolic activity between Tor1aΔE/+ and Tor1a+/− animals.
Table 1 Voxel-based comparison of regional metabolic activity and fractional anisotropy (FA) in Tor1a+/− heterozygous knock-out vs. Tor1a+/+ control animals. Coordinatesa y
z
Cluster sizeb
Zmax
p-Valuec
0.5
−5.8
−1.6
1821
3.37
0.001
Subthalamic nucleus
3.4 −1.5 −2.2 2.4 −4.4 2.4
−0.2 −0.3 −1.4 −2.0 0.1 −2.0
−2.8 −4.2 −0.1 −0.2 −2.1 −4.3
1666 5275 3982 6594 3879 2629
3.41 4.37 3.26 3.84 3.57 3.73
0.001 0.001 0.001 0.001 0.001 0.001
FA Tor1a+/− N Control Caudate–putamen Sensorimotor cortex Brainstem
−1.7 −2.8 −0.1
0.0 1.6 −7.9
−2.9 −1.3 −5.7
394 268 105
3.52 3.39 3.22
0.001 0.001 0.001⁎
Region Metabolism Tor1a+/− N Control Cerebellar vermis (lobule IV/V)d Tor1a+/− b Control Caudate–putamen Globus pallidus Sensorimotor cortex
a
x
Coordinates according to the common space of SPMMouse (Sawiak et al., 2009). Cluster size in voxels (1 voxel = 3.4 × 10−4 mm3). c Clusters are significant at p b 0.05 corrected for cluster extent. Clusters with significant (p b 0.05, Student's t-test) additional changes in the contralateral (“mirror”) hemisphere are presented in bold. d According to the atlas of Franklin and Paxinos (2007). ⁎ Uncorrected, at the voxel level. b
We found a significant increase in metabolic activity in heterozygous knock-out mice in the cerebellum (lobule IV/V), involving areas connected via the thalamus with motor cortex (Coffman et al., 2011). The localization of this abnormality accords with our prior observations in DYT1 knock-in mice (Ulug et al., 2011) and in human gene carriers (Eidelberg et al., 1998; Carbon and Eidelberg, 2009). While the exact cause of increased metabolism in the cerebellar regions cannot be discerned in our study, one can speculate that decreased inhibitory inputs to these cerebellar regions may be the cause of this increased metabolism. Previous studies reported shorter primary dendrites in addition to a decrease in the number of spines on distal dendrites of Purkinje cells, as well as reduced complexity in dendrites in TorsinA Purkinje specific knock-out animals (Zhang et al., 2011). The decreased inhibitory activity of Purkinje cells may be responsible for the increased metabolism. We found four regions of decreased metabolism in the caudate– putamen, globus palladus, subthalamic nuclei, and sensorimotor cortex of heterozygous knock-out mice. Since there is evidence of decreased dendrite branching of neurons in both knock-in and knock-out (Zhang et al., 2011; Song et al., 2013; Song et al., 2014) animals, the decreased metabolism may be the result of overall decreased excitatory input to these areas. While this Tor1a+/− heterozygous knock-out mouse model is not a model of dystonia, previous studies of DYT1 patients also reported abnormal metabolism in the lentiform nucleus (Eidelberg et al., 1998), putamen/GP (Trost et al., 2002), putamen (Carbon et al., 2004a,b; Carbon and Eidelberg, 2009), pre-motor cortex and SMA (Eidelberg et al., 1995), SMA (Trost et al., 2002), pre-SMA (Carbon et al., 2004a,b) and pre-SMA and pre-motor (Carbon and Eidelberg, 2009). Also a recent study of transgenic mice with human mutant torsinA reported decreased glucose utilization in the globus pallidus (Zhao et al., 2011).
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Fig. 2. Regions with abnormal microstructure in Tor1a+/− heterozygous knock-out mice. Significant increases in fractional anisotropy (FA) were present in the following brain areas of the Tor1a+/− heterozygous knock-out animals (Table 1): caudate–putamen, and sensorimotor cortex (both p b 0.001, Student's t-tests); and brainstem (p b 0.005, Student's t-test). The color scale represents voxels thresholded at T = 2.98, p = 0.005.
Our findings of abnormal metabolism in heterozygous knock-out mice in the areas that were previously reported to be abnormal in patients carrying DYT1 mutation are suggestive of the existence of a specific network that depends on normal levels of Tor1A in the brain. In this study, we found three regions with increased FA in heterozygous knock-out mice. One region is in the sensorimotor cortex; the other is in the middle of caudate–putamen; and the third is in the brainstem. The mouse brain, just after birth, has relatively high diffusion anisotropy in both gray and white matter (Mori and Zhang, 2006). Upon development, white matter anisotropy increases upon myelination while gray matter anisotropy decreases rapidly. This phenomenon relates to the dendrite growth in gray matter. Growing dendrites decrease the coherence of water diffusion within gray matter (Mori and Zhang, 2006) leading to a reduction in the observed diffusion anisotropy. If dendrites
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failed to grow and did not decrease the coherence of water diffusion, the diffusion anisotropy would remain elevated. Histological studies of DYT1 knock-in and conditional knock-out mice showed (Zhang et al., 2011) a reduction in the length of primary dendrites as well as a decrease in the number of spines on distal dendrites of Purkinje cells. The reduction of the length of the primary dendrite in knock-out animals was more pronounced (37%) than knock-in animals (20%). Also, the decrease of the distal dentrites was larger in magnitude in knockout (33%) than in knock-in (27%) animals. This would make the FA increases in gray matter more prominent in knock-out animals compared to knock-in animals. Thinner dendrites and less complex dendritic spines in Purkinje cells were also reported in another model of DYT1 knock-in mice (Song et al., 2014). A different study showed that in the striatum of DYT1 mice, there are slightly fewer and thinner dendrites, and there is also a loss of dendritic spines in the medium spiny projection neurons (Song et al., 2013). The previously reported decreases in dendritic development in heterozygous knock-out mice are compatible with our finding of increased FA in these gray matter regions. There is also another study of a mutant mouse model demonstrating an overexpression of torsinA resulting in striatal FA increases (Grundmann et al., 2007), suggesting that abnormal levels of torsinA may interfere with dendritic development, resulting in increased FA in the striatum. Our previous study of DYT1 knock-in mice showed decreased areas of FA in white matter regions (Ulug et al., 2011). Since mutant torsinA interferes with cytoskeletal dynamics (Hewett et al., 2006), decreased FA in white matter bundles could have resulted from the dominant negative effect of mutant torsinA in knock-in mice. In the current study, a single region of increased FA was identified in the brainstem. In our previous study of knock-in mice, we found three separate regions with decreased FA in the pons. Our interaction analysis of heterozygous knock-out and knock-in experiments revealed a large region in the pons. A previous study of DYT1 knock-in mice model reported the ubiquitin- and torsinA-containing aggregates in the neurons of the pontine nuclei (Sashidaran et al., 2004; Dang et al., 2005) suggesting the importance of proper function of torsinA in the pons. In this study, we did not find any evidence of significant (Mann– Whitney U, p N 0.11) white matter tract differences in Tor1a+/− heterozygous knock-out animals compared to controls. In our previous study of Tor1aΔE/+ knock-in animals, there were significant tract differences between Tor1aΔE/+ and control animals, with decreased numbers of tracts in mutant Tor1aΔE/+ animals. This result further suggests that mutant torsinA, through a dominant negative effect, was responsible for the decrease in the number of tracts in knock-in animals. While it is possible that there is a “dose” effect whereby heterozygous knock-out has about 50% of Tor1A, and while DYT1 knock-in mice have much less Tor1A due to a dominant negative effect of the mutation, this dose effect could not explain all of our findings. If dose effect was the only cause of abnormalities found, one would expect that the results of the knock-in experiment would be similar to the heterozygous knock-out experiment but only stronger. Our results show that this is not the case. The decrease in FA was only seen in gray matter regions in the heterozygous knock-out experiment but not in the knock-in experiment. At the same time, the white matter FA reductions were seen only in the knock-in experiment. Together these results suggest two separate affects at work, and DYT1 mutation is responsible for the white matter abnormalities observed.
Fig. 1. Metabolic abnormalities in the Tor1a+/− heterozygous knock-out mice. A. An abnormal increase in regional metabolic activity (p b 0.001, Student's t-test) was detected in the cerebellar vermis (lobule IV/V) of the Tor1a+/− heterozygous knock-out mice (Table 1). Individual values for this cluster in the Tor1a+/− heterozygous knock-out and control animals are represented by box-and-whisker plots. The color scale represents voxels thresholded at T = 2.70, p = 0.005. B. Significant reductions in regional metabolic activity were present in the following brain areas of the Tor1a+/− heterozygous knock-out animals: right caudate–putamen (p b 0.005, Student's t-test); left globus pallidus (p b 0.001, Student's t-test); sensorimotor cortex (p b 0.001, Student's t-test), and subthalamic nucleus (p b 0.005, Student's t-test). Metabolic activity values were normalized (z-scored) with respect to measurements from the control group.
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Fig. 3. Interaction effect of Tor1aΔE/+ knock-in and Tor1a+/− heterozygous knock-out animals in fractional anisotropy (FA). The interaction analysis (group × genotype) revealed two regions localized to the caudate–putamen and the pons (Table 2) in which a significant difference in changes of FA maps was found between the Tor1aΔE/+ and Tor1a+/− animals. In putamen: F(1,26) = 22.3, p b 0.001; in pons: F(1,26) = 18.4, p b 0.001; two-way ANOVA. In these two regions, compared with the control group, FA in the Tor1aΔE/+ animals significantly decreased (p b 0.005 in putamen and p b 0.05, in pons, post-hoc Bonferroni tests). In contrast, the Tor1a+/− group had an increase in FA (p b 0.005, both in putamen and pons, posthoc Bonferroni tests). FA values were normalized (z-scored) with respect to measurements from the corresponding control group. The color scale represents voxels thresholded at T = 2.78, p = 0.005.
If one considers what happens to a subject with DYT1 mutation in the terms of loss or gain of function: there is loss of function because there is only one normal allele that remains; at the same time there is a gain of function because of the effects of the mutant protein.
Cluster sizeb
Zmax
p-Valuec
found in gray matter regions are the evidence of decreased neurite extensions in the gray matter. The metabolic abnormalities found suggest that these neurite extension decreases result in decreased synaptic connections, and therefore cause decreased inhibitory or excitatory inputs to the affected regions. Comparison of our results with the previous imaging study of knock-in animals shows that the white matter abnormalities found in knock-in animals may be mainly due to the mutant torsinA interfering with cytoskeletal dynamics in the development of the white matter bundles with a dominant negative effect. Our results may suggest that the imaging findings reported in DYT1 dystonia subjects can be explained. The lack of normal levels of torsinA due to having only one copy of the normal Tor1a gene may be responsible for the abnormal metabolic changes seen in the DYT1 dystonia patients; having mutant torsinA, on the other hand, may be responsible for the white matter tract damages observed in these patients.
225 975
4.31 4.25
b0.001 b0.001
Acknowledgments
Conclusions Our imaging findings show that having one copy of the Tor1a gene has structural and functional consequences. Increased FA clusters Table 2 Voxel-based fractional anisotropy interaction effect of Tor1aΔE/+ knock-in and Tor1a+/− heterozygous knock-out animals. Coordinatesa Region
x ΔE/+
y
z +/−
Control — Tor1a N Control — Tor1a Caudate–putamen −2.3 −0.2 Pons 0.4 −5.6 a b c
−2.3 −5.0
Coordinates according to the common space of SPMMouse (Sawiak et al., 2009). Cluster size in voxels (1 voxel = 3.4 × 10−4 mm3). Clusters are significant at p b 0.05 corrected for cluster extent.
This work is supported in part by a grant from the Bachmann– Strauss Dystonia and Parkinson Foundation.
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Fig. 4. Pontine–cerebellum and thalamo-striatal tracts. The two regions (caudate–putamen and the pons) determined in interaction analysis were used in visualizing white matter tracts in both knock-in (left) and heterozygous knock-out animals (right) and their respective controls. Pontine–cerebellum (PCb) tracts and thalamo-striatal (TS) tracts are displayed in white. The red region is in the caudate–putamen (Table 2, region 1), and the green region is in the pons (Table 2, region 2). Thalamus is shown in blue.
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