Brain structural abnormalities in Doberman pinschers with canine compulsive disorder

PNP-08366; No of Pages 6 Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2013) xxx–xxx

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Progress in Neuro-Psychopharmacology & Biological Psychiatry journal homepage: www.elsevier.com/locate/pnp

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Niwako Ogata a,⁎, Timothy E. Gillis b, Xiaoxu Liu b, Suzanne M. Cunningham a, Steven B. Lowen b, Bonnie L. Adams b, James Sutherland-Smith a, Dionyssios Mintzopoulos b, Amy C. Janes b, Nicholas H. Dodman a, 1, Marc J. Kaufman b, 1

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Brain structural abnormalities in Doberman pinschers with canine compulsive disorder

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Department of Clinical Sciences, Cummings School of Veterinary Medicine, Tufts University, 200 Westboro Road, North Grafton, MA 01536, United States McLean Imaging Center, McLean Hospital, Harvard Medical School, 115 Mill St., Belmont, MA 02478, United States

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Article history: Received 15 November 2012 Received in revised form 3 April 2013 Accepted 3 April 2013 Available online xxxx

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Obsessive compulsive disorder (OCD) is a debilitating condition, the etiology of which is poorly understood, in part because it often remains undiagnosed/untreated for a decade or more. Characterizing the etiology of compulsive disorders in animal models may facilitate earlier diagnosis and intervention. Doberman pinschers have a high prevalence of an analogous behavioral disorder termed canine compulsive disorder (CCD), which in many cases responds to treatments used for OCD. Thus, studies of CCD may help elucidate the etiology of compulsive disorders. We compared brain structure in Dobermans with CCD (N = 8) and unaffected controls (N = 8) to determine whether CCD is associated with structural abnormalities comparable to those reported in humans with OCD. We obtained 3 Tesla magnetic resonance structural and diffusion images from anesthetized Dobermans and subjected images to segmentation, voxel based morphometry, and diffusion tensor analyses. CCD dogs exhibited higher total brain and gray matter volumes and lower dorsal anterior cingulate cortex and right anterior insula gray matter densities. CCD dogs also had higher fractional anisotropy in the splenium of the corpus callosum, the degree of which correlated with the severity of the behavioral phenotype. Together, these findings suggest that CCD is associated with structural abnormalities paralleling those identified in humans with OCD. Accordingly, the CCD model, which has a number of advantages over other animal models of OCD, may assist in establishing the neuroanatomical basis for and etiology of compulsive disorders, which could lead to earlier diagnosis of and new treatments for humans and animals with these disorders. © 2013 Published by Elsevier Inc.

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Keywords: Blanket and flank sucking Compulsive disorder Diffusion tensor imaging Doberman pinschers Voxel-based morphometry

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1. Introduction

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Obsessive compulsive disorder (OCD) is a debilitating condition with a lifetime prevalence of about 2% of the population (Ruscio et al., 2010). According to the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 2000), OCD symptoms include obsessions, intrusive recurrent and persistent thoughts, impulses, or images that cause marked anxiety or stress, which are time consuming or

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Abbreviations: OCD, obsessive compulsive disorder; CCD, canine compulsive disorder; SSRI, selective serotonin reuptake inhibitors; TCA, tricyclic anti-depressants; PET, positron emission tomography; NMDA, N-Methyl-D-aspartate; OFC, orbitofrontal cortex; ACC, anterior cingulate cortex; ROI, region of interest; FA, fractional anisotropy; CDH2, cadherin 2 gene; BS, blanket sucking behavior; FS, flank sucking behavior; VWD, Von Willebrand's disease; DTI, diffusion tensor imaging; VBM, voxel based morphometry; CSF, cerebrospinal fluid; ADC, apparent diffusion coefficient. ⁎ Corresponding author at: Dept. of Veterinary Clinical Sciences, College of Veterinary Medicine, Purdue University, 625 Harrison St., West Lafayette, IN 47907-2026, United States. Tel.: +1 765 494 8775; fax: +1 765 496 1108. E-mail address: [email protected] (N. Ogata). 1 Contributed equally to this work.

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significantly interfere with normal routine; symptoms also include compulsions, such as repetitive behaviors or mental acts that the patient feels driven to perform to neutralize the obsession. Cortico-striatal circuitry has been implicated as playing a key role in OCD, but additional brain elements now are thought to contribute to the disorder, including anterior cingulate and orbitofrontal cortices, as well as amygdalo-cortical circuitry (Milad and Rauch, 2012). OCD typically is not diagnosed until nearly a decade after symptom onset (Stengler et al., in press), making it difficult to characterize the etiology of the disorder in humans. Accordingly, several rodent models have been developed to study compulsive disorders. These include transgenic and in-bred mouse lines that exhibit several of the hallmarks of OCD such as compulsive behaviors, some of which are ameliorated by serotonergic agents typically used to treat OCD in humans (Greene-Schloesser et al., 2011; Shmelkov et al., 2010; Welch et al., 2007). Canine models offer several advantages over rodent models in that canine central nervous system genetics (Ostrander and Wayne, 2005) and neuroanatomy are more similar to humans than mice, and the dog brain is many times the size of the mouse brain. Dogs and humans live together and dogs have adapted to human social environments. Moreover, more than 200 canine disorders have close similarities to

0278-5846/$ – see front matter © 2013 Published by Elsevier Inc. http://dx.doi.org/10.1016/j.pnpbp.2013.04.002

Please cite this article as: Ogata N, et al, Brain structural abnormalities in Doberman pinschers with canine compulsive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2013), http://dx.doi.org/10.1016/j.pnpbp.2013.04.002

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2.2. Anesthesia

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After fasting for 8 h and withdrawal of water for 2 h, all dogs were premedicated by intravenous injection of acepromazine (0.025 mg/kg) and butorphanol (0.05 mg/kg) and then had anesthesia induced with intravenous propofol (3 mg/kg). Anesthesia was maintained using 2% isoflurane/oxygen mixture delivered via a semi-closed circle absorber anesthetic circuit. Respiratory rates were monitored and pulse oximetry was used to monitor heart rates and oxygen saturations constantly throughout MRI imaging.

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This study was conducted according to national and international guidelines for canine research. Informed consent was obtained from all owners. The study was reviewed and approved by the Clinical Studies Review Committee (CSRC# 090-09) of Tufts Cummings School of Veterinary Medicine. The MRI study components were reviewed and approved by the McLean Hospital Institutional Animal Care and Use Committee (IACUC# 09-8/2-27).

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Doberman pinscher dogs included in this study were recruited at local dog shows and via advertisement through the Pilgrim Doberman Pinscher Club and the website of the Animal Behavior Clinic in Tufts Cummings School of Veterinary Medicine (TCSVM). We recruited dogs aged 1.5 to 6 years old, to avoid effects related to brain development or brain aging. Nineteen dogs were recruited, 16 of which (8 dogs with CCD (6 males) and 8 controls (2 males)) were clinically cleared for imaging. Because of the relatively small sample sizes available, it was not possible to match control and CCD groups with respect to sex. Owners of these dogs were required to complete the same detailed behavior assessment questionnaire employed in a prior phenotypic survey of CCD-affected and control Doberman pinschers (Moon-Fanelli et al., 2007) and in a prior study linking a genetic polymorphism in the cadherin 2 (CDH2) gene to CCD (Dodman et al., 2010). In addition, owners were interviewed by veterinary behaviorists affiliated with the Animal Behavior Clinic at TCSVM. When necessary, owners were asked to send videos of their dog's behavior to aid in behavioral phenotyping. Eight dogs were diagnosed as exhibiting either compulsive blanket sucking behavior (BS) or flank sucking behavior (FS). Two out of 8 affected dogs were positive on a DNA test for Von Willebrand's disease (VWD), which causes a deficiency of a platelet clotting factor that can result in increased bleeding. Dobermans are predisposed to develop VWD, the most commonly inherited bleeding disorder of dogs. One affected dog had a history of episodic head tremor, but did not exhibit head tremor at the time of the MRI. CCD dogs were ranked for the severity of their behavior by determining the numbers of hours the dogs engaged in BS/FS behavior during a typical 24-hour period. When ties emerged, we used the presence of an additional compulsive behavior, such as acral lick dermatitis or pica, as well as disorder duration (the numbers of years dogs exhibited BS/FS before the study), to further inform the rankings. None of the dogs had received any medications or behavior modification treatments designed to modify behavior. A separate group of 8 Dobermans not exhibiting any CCD behaviors or other behavior problems was enrolled as a control group. Since the dogs enrolled in the study were to be anesthetized for the MRI procedure, a complete physical examination, including echocardiogram examination as well as blood work, including CBC, chemistry profile, total thyroxine (T4), N-terminal pro B-type natriuretic peptide (NT-proBNP; Cardiopet™ proBNP test, IDEXX Laboratories, Inc., Westbrook, ME, USA), were performed on all 16 dogs. Echocardiography, including standard M-mode, 2-dimensional, color-flow, spectral Doppler and tissue Doppler imaging was performed by a board-certified veterinary cardiologist in all dogs (GE Vivid 7™, GE Medical systems, USA). Continuous ECG monitoring was implemented during the echocardiographic examination. No dogs showed any clinical signs of heart disease. Dogs cleared of medical complications that might impact the dog's well being under anesthesia were brought to the McLean Imaging Center at McLean Hospital, Belmont MA for MRI imaging. The MRI images were examined by a board certified veterinary radiologist at TCSVM to identify any gross structural abnormalities that might affect behavior.

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2. Methods

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human disorders (Parker et al., 2010; Tsai et al., 2007), including the canine analog of OCD, canine compulsive disorder (CCD). CCD derives from normal species-typical behavior, including grooming (acral lick dermatitis), predatory behavior (tail chasing), eating/suckling (pica and flank/blanket sucking) and locomotion (pacing/circling) (Luescher, 2003; Overall and Dunham, 2002; Rapoport et al., 1992; Shuster and Dodman, 1998). CCD is highly prevalent among Dobermans, with an estimated incidence of about 28% in a database including over 2300 dogs (personal communication, Andrew Borgman, Statistical Analyst, Van Andel Research Institute, Grand Rapids, MI). Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine or tricyclic anti-depressants (TCAs) such as clomipramine used to treat human OCD (and as noted above are effective in rodent compulsive disorder models), also are commonly employed to treat CCD (Goldberger and Rapoport, 1991; Hewson et al., 1998; Irimajiri et al., 2009; Moon-Fanelli and Dodman, 1998; Overall, 1994; Stein et al., 1998; Wynchank and Berk, 1998). Further, it has been shown that humans with OCD (Aboujaoude et al., 2009; Feusner et al., 2009; Stewart et al., 2010) and dogs with CCD respond to treatment with the glutamatergic NMDA receptor antagonist memantine (Schneider et al., 2009). In addition, positron emission tomography (PET) imaging detected serotonergic and dopaminergic abnormalities in dogs with CCD, paralleling some reports in humans with OCD (Vermeire et al., 2012). Thus, dogs with CCD respond to treatments that improve OCD symptoms and exhibit behavioral and neurochemical phenotypes similar to those found in OCD, suggesting that the CCD model may be useful for studying the etiology of compulsive disorders. However, to date, no studies have reported on whether brain structural abnormalities exist in dogs with CCD. Brain regions most consistently found to be abnormal in humans with OCD include the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), insula, thalamus, corpus callosum, and striatum (Song et al., 2011; Zarei et al., 2011). ACC abnormalities include reduced gray matter volumes and densities (Carmona et al., 2007; Gilbert et al., 2008; Matsumoto et al., 2010b; Rotge et al., 2010; Valente et al., 2005; Yoo et al., 2008). Fractional anisotropy abnormalities have been found in the corpus callosum (den Braber et al., 2011; Garibotto et al., 2010; Nakamae et al., 2011; Yoo et al., 2007; Zarei et al., 2011). Together, these findings support the idea that structural abnormalities in multiple brain areas contribute to OCD (Milad and Rauch, 2012). Accordingly, we sought to determine whether Dobermans diagnosed with CCD exhibit brain abnormalities comparable to those found in humans with OCD. We acquired 3 Tesla structural and diffusion weighted images from anesthetized Dobermans diagnosed with CCD and from a matched sample of behaviorally normal dogs. We analyzed structural images using a whole-brain approach including tissue segmentation and voxel based morphometry. Because our diffusion images were of lower spatial resolution and because they had lower signal to noise ratios than our structural images, we conducted a region of interest (ROI) analysis limited to 3 selected ROIs (genu and splenium of corpus callosum and cingulum bundle). We hypothesized that we would observe higher fractional anisotropy (FA) in these ROIs, which would reflect greater anisotropy of water diffusion between white matter fibers and possibly greater ordering of fiber bundles. Higher FA values in these areas have been reported in humans with OCD (Cannistraro et al., 2007; Yoo et al., 2007; Zarei et al., 2011).

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Please cite this article as: Ogata N, et al, Brain structural abnormalities in Doberman pinschers with canine compulsive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2013), http://dx.doi.org/10.1016/j.pnpbp.2013.04.002

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Imaging data were processed using FSL 4.1 (http://www.fmrib.ox. ac.uk/fsl/index.html) automated by in-house scripts. The overall VBM method was based on FSL's voxel based morphometry (VBM) procedure (http://www.fmrib.ox.ac.uk/fsl/fslvbm/index.html), adapted for different-shaped brains. Brains were preprocessed using the following semi-automated procedure. A bounding box was defined for each brain by visual inspection. Next, an upper threshold was selected by trial and error; any voxels above that threshold were set to zero. These two steps enabled determination of brain vs. non-brain regions using the FSL brain extraction tool (BET, see below). Voxel dimensions were stored for later use; brains were scaled by factors of (2,2,4) in the (x,y,z) dimensions, respectively, to more closely resemble human brains, for which BET was designed. BET then was run, using robust brain center estimation and a fractional intensity threshold of 0.4. Brains then were scaled up by a factor of 2 times in all dimensions when compared to original brain sizes. This facilitated registration (using the FSL nonlinear image registration tool, FNIRT). Because the BET algorithm was designed for use with human brains and because canine brain shapes are different, this procedure yielded registered brains with some small missing regions as a consequence of the mismatch between human and canine brain shapes and the threshold operation performed earlier. These voids were filled by creating a mask of each brain, inverting it (exchanging foreground for background values), performing a cluster analysis on the inverted mask, selecting the largest cluster, inverting that cluster back to yield an improved mask, and finally applying that mask to the scaled brain. Preprocessed brains were examined to ensure that boundaries were accurate, and that underlying image quality was satisfactory. A high-quality (non-annotated) brain atlas was generated from all 16 brains using the following automated procedure. First, each brain was resampled to 2 mm isotropic resolution (equivalent to 1 mm in native space). Brains were assembled into a stack, with each brain comprising a volume in that stack. The stack was cropped to the smallest 3D box that contained all non-zero voxels. Next, each brain was normalized to have the same intensity averaged over all voxels in the box. The stack was averaged over volumes to yield a first iteration of the atlas. Each brain was aligned to this atlas iteration using FNIRT and the T1_2_MNI152_2mm configuration file. The aligned brains were then averaged into a second iteration of the atlas. This alignment and averaging process was iterated two more times to yield the final atlas, since further iterations did not improve the atlas. Alignment was assessed for all brains, as was definition in the averaged atlas. Next, a study-specific gray matter template was created by running the FSL automated segmentation tool (FAST) on each brain in the stack, aligning the brains using FNIRT, and then averaging this gray-matter stack. Again, alignment was assessed for all brains, as was definition in the averaged atlas. Smoothing was not performed, as it reduced statistical power. The volume of each brain

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All scans were acquired on a Siemens Tim Trio 3 T whole-body scanner using an extremity (knee) coil. Structural images were obtained with an MPRAGE scan using the following parameters: repetition time (TR) = 1940 ms; echo time (TE) = 2.39 ms; inversion time (TI) = 850 ms; acquisition matrix = 192 × 192; slices = 128; with nominal voxel dimensions of 0.7 mm × 0.7 mm × 0.7 mm (scan time = 8 min). Diffusion Tensor Imaging (DTI) scans were acquired using the vendor-provided spin-echo (SE) EPI diffusion sequence. Eight b0 volumes and 72 DTI gradient directions were acquired with the following parameters: TR = 4000 ms; TE = 91 ms; acquisition matrix = 96 × 96; slices = 26; with nominal voxel dimensions of 1.333 mm × 1.333 mm × 1.900 mm.

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segmentation type (cerebrospinal fluid (CSF), gray matter, white matter) was recorded for later processing. Differences among brains were assessed using a randomize, non-parametric program for testing significance using permutation. Cluster-based thresholding was used to establish significance, with T test scores thresholded at a value of 2.5. Since this threshold readily detects large regions with moderate T scores but can fail when small regions of especially large T scores exist, the process was repeated with a threshold doubled to 5.0, in an exploratory manner. Differences between control and affected dogs were assessed in one test. In addition, we tested whether VBM differences correlated with CCD phenotype severity (in the 8 CCD dogs only). Diffusion data were processed using the TrackVis suite (www. TrackVis.org; Wang and Wedeen, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). Because diffusion data had lower signal to noise ratios than the MPRAGE data, we elected to perform a region of interest (ROI) analysis by selecting 3 ROIs for study rather than subjecting the data to a whole brain analysis. Scans were blinded with regard to subject diagnosis, and then a trained rater placed two 4-pixel (13.5 mm 3) ROIs in the corpus callosum splenium and genu on the midsagittal image, and one 9-pixel (30.4 mm 3) ROI in the posterior-medial cingulum on a coronal image. The locations of these ROIs are illustrated in Fig. 1 (bottom). The average fractional anisotropies (FA) and apparent diffusion coefficients (ADC) were computed for these ROIs using the fslstats command in FSL (www.fmrib.ox.ac.uk/fsl/). For ROIs yielding a group difference, we followed up by testing within the CCD group whether diffusion differences correlated with CCD phenotype severity.

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2.5. Statistical analyses

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In addition to the image analyses described above performed by FSL, Prism statistical software (version 4.0c, GraphPad Software, Inc.) was used to conduct additional tests. We conducted one-sided t-tests to compare diffusion imaging findings in pre-selected regions of interest to test our a priori hypothesis that we would find higher FA in these ROIs in subjects with CCD. We conducted two-sided t-tests to compare continuous demographic variables, χ2 contingency tests to compare categorical demographic variables, and a Pearson Product Moment Correlation analysis to compare CCD severity to diffusion imaging ROI data. The threshold for statistical significance was set to P b 0.05.

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The two groups were matched for age but the CCD group included more males than the control group (Table 1). In affected dogs, CCD symptom onset age averaged (SD) 2.25 (±1.54) months and the symptom duration at the time of scanning averaged (SD) 4.52 (±1.85) years. None of the dogs had been exposed to psychotropic medications (by owner report). Structural brain images in all dogs were normal except for one minor structural brain abnormality detected in a control dog, a congenital Rathke's cleft cyst. This dog did not show any clinical signs. Segmentation of T1-weighted (MPRAGE) images revealed that CCD dogs exhibited slightly higher total gray matter volume and gray matter fraction of total brain volume (TBV), slightly lower CSF volume and fraction of TBV, and slightly lower white matter fraction of TBV (Table 1). A whole brain analysis of MPRAGE images comparing CCD to control dogs using a threshold T > 2.5 revealed a significant cluster of lower gray matter density (p = 0.0238, 537 voxels, 537 mm3 in the original brain space, Fig. 1) covering a large part of the dorsal anterior cingulate cortex (dACC). Using the more stringent T > 5 threshold, we found a smaller cluster of lower gray matter density (p = 0.0176, 16 voxels, 16 mm3 in the original brain space) in the right anterior insula (Fig. 1). We found no associations between CCD phenotype severities in either of these clusters.

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Please cite this article as: Ogata N, et al, Brain structural abnormalities in Doberman pinschers with canine compulsive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2013), http://dx.doi.org/10.1016/j.pnpbp.2013.04.002

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VBM T = 2.5

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In Dobermans with CCD, we detected higher total brain and gray matter volumes, lower gray matter densities in the dACC and right anterior insula, and higher fractional anisotropy in the splenium of the corpus callosum than in controls, findings consistent with those reported in OCD. CCD dogs exhibited 3.7% higher gray matter volumes versus 7% higher gray matter volumes in adult OCD (Jenike et al., 1996) and 3.7% higher gray matter volumes in pediatric OCD (Zarei et al., 2011). CCD dogs also exhibited 2.2% lower white matter volumes versus 15% lower white matter volumes in adult OCD (Jenike et al., 1996). Our finding of lower dACC gray matter densities in CCD is consistent with reports of dACC structural abnormalities and N-acetylaspartate reductions in OCD (Carmona et al., 2007; Matsumoto et al., 2010b; Yoo et al., 2008; Yücel et al., 2007). The dACC gray matter abnormality was localized in motor regions adjacent to the cingulate sulcus, an area involved in preparation for or execution of highly practiced remembered movement sequences (Picard and Strick, 1997). Abnormalities in this

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Table 2 Diffusion data.

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Table 1 Subject demographics.

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Control subjects (N = 8)

Statistic

P value

6a/2b 4.46 ± 1.91 2.25 ± 1.54e 4.52 ± 1.85e 35.74 ± 0.45

2c/6d 3.78 ± 2.18 – – 37.11 ± 0.37

X2 = 4.00 t14 = 0.67

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Demographic

CCD subjects (N = 8)

Sex (males/females) Age (years) CCD age onset (months) CCD duration (years) Cerebrospinal fluid (CSF, cm3) Total gray matter (cm3) Total white matter (cm3) Total brain volume (cm3) CSF fraction (%) Gray fraction (%) White fraction (%)

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A region of interest (ROI) analysis of diffusion tensor imaging data revealed higher fractional anisotropy (FA) and a lower diffusion coefficient (ADC) in the splenium of the corpus callosum in the CCD group (one-sided t-test t = 2.539, df = 14, P = 0.012, Table 2, Fig. 2 (Top)). The FA finding survived a Bonferroni multiple comparisons correction for the 3 ROIs tested. We also found a positive association between splenium FA and CCD behavioral phenotype severity rating (Pearson Product Moment R > 0.73, P b 0.04, Fig. 2 (Bottom)).

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Fig. 1. Top row: Voxel Based Morphometry (VBM) whole brain analysis (T = 2.5) showing areas of lower dorsal anterior cingulate cortex gray matter density in CCD dogs mapped onto the composite dog brain image obtained from 16 dogs and warped to a common space. Middle row: whole brain analysis (T = 5.0) showing area of lower right insula gray matter in CCD dogs. Bottom row: illustrations of locations of 3 regions of interest (ROIs) applied to diffusion imaging data to extract fractional anisotropy and apparent diffusion coefficient data. A = anterior; P = posterior; R = right; L = left; S = superior; I = inferior. Shown are coronal (left column), sagittal (middle column), and axial (right column) images.

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CCD = canine compulsive disorder; All other data are shown as means ± SDs. CSF = Cerebrospinal Fluid. T-statistics pertain to 2-sided t-tests with df = 14. a 4 neutered males. b 2 spayed females. c 1 neutered male. d 4 spayed females. e Two CCD dogs exhibiting CCD behavior at the time of adoption (6 months and two years) were excluded from these statistics because current owners did not know ages at CCD onset (N = 6).

Diffusion measure

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Controls (N = 8)

One-sided T-test t (df = 14)

Uncorrected P

0.318 ± 0.037 0.363 ± 0.038 0.179 ± 0.013

2.539 0.188 1.729

0.012⁎ 0.427 0.053

Apparent diffusion coefficient ∗ 1000 (ADC) Splenium 0.885 ± 0.034 1.139 ± 0.133 Genu 1.015 ± 0.106 1.019 ± 0.087 Cingulum 0.898 ± 0.045 0.968 ± 0.039

1.850 0.027 1.175

0.043 0.489 0.130

Fractional anisotropy (FA) Splenium 0.486 ± 0.055 Genu 0.351 ± 0.046 Cingulum 0.225 ± 0.024

CCD = canine compulsive disorder. ⁎ Survives Bonferroni multiple comparisons correction.

Please cite this article as: Ogata N, et al, Brain structural abnormalities in Doberman pinschers with canine compulsive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2013), http://dx.doi.org/10.1016/j.pnpbp.2013.04.002

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Splenium Fractional Anisotropy

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organization or order that could enhance information flow. The splenium is a main hub of the orienting attention network (Niogi et al., 2010). In healthy humans, orienting attention performance is positively correlated with splenium FA (Niogi et al., 2010). It has been reported that people with OCD exhibit increased attention orienting to novel stimuli (Ischebeck et al., 2011), which could enhance distractibility and cognitive interference reported in OCD. Those with OCD also exhibit increased posterior brain fMRI reactivity during cognitive interference tasks (van den Heuvel et al., 2005). Increased splenium FA could enhance the influence of posterior brain activities, including sensory and cognitive functions, on other aspects of brain function. Indeed, it has been reported that OCD subjects exhibit abnormal posterior brain activity during an implicit learning task, which was hypothesized to reflect compensation by posterior networks for a dysfunctional cortico-striatal network (Rauch et al., 1997). Although the CCD abnormalities we detected are analogous to those in OCD, we failed to detect abnormalities in striatum and orbitofrontal cortex, regions thought to play key roles in OCD (Menzies et al., 2008; Milad and Rauch, 2012; Radua et al., 2010). This negative finding could have resulted from our small sample sizes but could reflect neuroanatomical differences between CCD and OCD. Further, our most robust finding (lower anterior cingulate gray matter densities in CCD dogs) has been reported in human anxiety disorders including OCD, but it is not specific to OCD (Radua et al., 2010).

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area could reflect impaired structural or functional connectivity with frontal executive control areas that could result in reduced top down cognitive control over motor behavior characteristic of CCD, including excessive and repetitive BS/FS, licking, and pica. In OCD, abnormal functional connectivity between dorsolateral prefrontal cortex (dlPFC) and dACC has been reported along with a negative association between OCD symptom severity and functional connectivity between the left dlPFC and dACC (Schlösser et al., 2010). Further, in OCD, dACC hyperactivation has been documented during conflict trials on the multisource interference (MSIT) and Stroop tasks, which could reflect dysfunction of this area (Schlösser et al., 2010; Yücel et al., 2007). The insula cortex abnormality we found in CCD dogs is consistent with insula structural, functional, and neurochemical abnormalities reported in OCD (Cocchi et al., 2012; Matsumoto et al., 2010a; Nishida et al., 2011; Pujol et al., 2004; Song et al., 2011; Zarei et al., 2011). A recent fMRI study reported increased functional connectivity between the anterior insula and dACC during MSIT task performance and generally increased and decreased anterior insula and dACC functional connectivity, respectively, in OCD (Cocchi et al., 2012). Coordinated activity within the dACC and anterior insula during task performance in OCD could reflect compensation for reduced connectivity between frontal cognitive control areas and the dACC (Schlösser et al., 2010). Alternatively, as suggested by Cocchi et al. (2012), it is known that the anterior insula is a key element of a brain network that processes autonomic arousal and interoceptive stimuli (Craig, 2009), and in OCD, coordinated activity of the anterior insula and dACC may reflect the degree of arousal induced during task performance, which may be greater in OCD. We also observed higher splenium FA in CCD dogs, consistent with reports in OCD studies (den Braber et al., 2011; Yoo et al., 2007; Zarei et al., 2011). Higher FA could reflect increased white matter fiber

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Fig. 2. Top: scatterplot comparing fractional anisotropy (FA) measurements in the splenium of the corpus callosum from control dogs to those from CCD dogs. The difference is statistically significant (one-sided t-test t = 2.539, df = 14, P = 0.012). This effect survives Bonferroni multiple comparisons correction. Bottom: correlation plot in CCD dogs (N = 8) showing an association between splenium of corpus callosum FA and CCD behavioral phenotype severity ranking (Pearson Product Moment R > 0.73, P b 0.04).

The main limitation of this study is our small sample sizes. In addition, our CCD group had more males than our control group and we cannot rule out a sex effect on gray matter abnormalities. However, we do believe that the higher splenium FA in CCD dogs is not attributable to cohort sex differences, since diffusion studies in healthy adults (dog studies are lacking) report higher splenium FA in women (Kanaan et al., 2012), the opposite of what we would have expected had sex influenced FA. Notwithstanding these limitations, our data suggest that neuroanatomically, CCD has parallels with human anxiety disorders including OCD. Our data are the first brain structural findings supporting construct validity of the Doberman pinscher CCD model as being relevant to human OCD. Because Doberman CCD can have a very early onset (Table 1), the condition may be particularly useful for studying early onset forms of these disorders. CCD in other canine breeds also occurs with early onset (Tiira et al., 2012), suggesting that a number of dog breeds could be useful for studying early onset events associated with these disorders. Such work could be important since early onset OCD persists untreated for long periods (Stengler et al., in press) and tends to be associated with greater symptom severity and poorer outcomes (Skoog and Skoog, 1999). As the building homology between CCD and OCD is intriguing, conducting parallel research in both disorders could accelerate research into and treatment development for humans and companion animals with these conditions.

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We conclude that CCD is associated with structural abnormalities paralleling some of those identified in humans with anxiety disorders including OCD. Accordingly, we believe that the CCD model, which has a number of advantages over other animal models of compulsive disorders, may be useful for studying the etiology of and for developing new treatments for these disorders.

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We are grateful to all the owners of dog participants in this study. 434 We also thank Andrew Borgman and colleagues at the Van Andel Re- 435 search Institute (Grand Rapids, MI). 436

Please cite this article as: Ogata N, et al, Brain structural abnormalities in Doberman pinschers with canine compulsive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2013), http://dx.doi.org/10.1016/j.pnpbp.2013.04.002

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