The structure of the corpus callosum in obsessive compulsive disorder

European Psychiatry 28 (2013) 499–506

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Original article

The structure of the corpus callosum in obsessive compulsive disorder M. Di Paola a,*,b, E. Luders c, I.A. Rubino d, A. Siracusano d, G. Manfredi e, P. Girardi e, G. Martinotti f, P.M. Thompson c, Y.-Y. Chou c, A.W. Toga c, C. Caltagirone a,d, G. Spalletta a a

IRCCS Santa Lucia Foundation, Laboratory of Clinical and Behavioural Neurology, Via Ardeatina 306, 00179 Rome, Italy Department of Internal Medicine and Public Health, University of L’Aquila, Piazzale Salvatore Tommasi 1, 67010 L’Aquila-Coppito, Italy c Laboratory of Neuroimaging, Department of Neurology, UCLA School of Medicine, 635 Charles Young Drive South, Los Angles, CA 90095, USA d Neuroscience Department, University of Rome ‘‘Tor Vergata’’, Via Montpellier, 1, 00133 Rome, Italy e NESMOS Department, Faculty of Medicine and Psychology, University of Rome ‘‘Sapienza’’, Rome, Italy f Institute of Psychiatry, Catholic University of Sacred Heart, Rome, Italy b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 9 September 2011 Accepted 30 January 2012 Available online 15 October 2012

Abnormal brain connectivity has recently been reported in obsessive compulsive disorder (OCD). However, structural differences in the corpus callosum (CC), the primary structure connecting the two hemispheres, have not been extensively studied. In this case-control study, we recruited 30 patients with OCD and 30 healthy control subjects carefully matched for age, sex and handedness. Combining surfacebased mesh-modeling and voxel-based morphometry (VBM), we compared callosal thickness and white matter (WM) density in patients and controls. We investigated associations between callosal structure and cortical gray matter (GM) density, and we related CC measures to neuropsychological performance in OCD. OCD patients showed small anterior and posterior callosal regions compared to healthy control subjects. In the OCD group, anterior callosal thickness was positively correlated with GM density of the right mid-dorso-lateral prefrontal (BA 9/46) area, while posterior callosal thickness was positively correlated with GM density in the left supramarginal gyrus (BA 40). Moreover, posterior callosal WM density was positively correlated with verbal memory, visuo-spatial memory, verbal fluency, and visuospatial reasoning performances. Callosal attributes were related to GM density in cortical areas innervated by the CC, and were also related to performance in cognitive domains impaired in the disorder. The CC may therefore be integrally involved in OCD. ß 2012 Elsevier Masson SAS. All rights reserved.

Keywords: Corpus callosum Region of interest Voxel-based morphometry Diffusion tensor imaging Cortical gray matter Neuropsychological tests

1. Introduction Obsessive compulsive disorder (OCD) has been traditionally linked to dysfunctions of the orbito-frontal circuitry [43]. More recently, some investigators [11,29,36,48,53] proposed (additional) dysfunction of the dorso-lateral prefrontal circuitry. However, neither the interhemispheric integration of orbital nor of dorsolateral regions has been sufficiently examined in anatomical studies. The corpus callosum (CC) is the largest fiber bundle interconnecting the two hemispheres [1] and plays a primary role in the interhemispheric integration of many brain functions. For example, the CC modulates attention [27] and regulates the inhibiting of cortical activity [8], and both of these processes may be dysfunctional in OCD [47]. Thus, the CC is likely to be a key brain structure in the OCD. In light of the aforementioned old and new theories on the neuroanatomical substrate of OCD, we hypothesized that various subregions of the CC are affected in OCD patients,

* Corresponding author. Tel.: +39 06 51501215; fax: +39 06 51501213. E-mail address: [email protected] (M. Di Paola). 0924-9338/$ – see front matter ß 2012 Elsevier Masson SAS. All rights reserved. http://dx.doi.org/10.1016/j.eurpsy.2012.07.001

such as the callosal rostrum and genu (which interconnect orbital and dorsal frontal cortices), as well as the callosal isthmus and splenium (which interconnect posterior temporal, parietal, and occipital areas). Abnormalities of the CC have received only minimal attention in the context of OCD. Two structural MRI studies [9,28] from the early 1990s and one more recent investigation [39] examined macrostructural differences in the CC by applying a region of interest (ROI) analysis. While one group reported comparable length and area measures in six OCD patients compared to eight matched controls [9], the second study reported comparable callosal areas but longer callosal lengths in ten OCD patients compared to ten controls [28]. The latest work [39] described a reduced callosal thickness in OCD patients in posterior callosal regions (i.e., within the splenium). In addition, studies addressing callosal microstructure using diffusion tensor imaging (DTI) revealed a lower fractional anisotropy (FA) in the splenium as well as an altered fiber directionality in the genu, body and splenium of the CC in OCD [23]. Furthermore, DTI studies reported FA reductions in OCD in the rostrum [44] as well as FA increases in posterior callosal sections [53]. Moreover, increases in FA and in

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axial diffusivity in the genu and body of CC have been found [30], suggesting an impaired axonal integrity. Decreased FA and increased radial diffusivity in the body of the CC have also been reported [6] and hypothesized to indicate abnormal myelination in OCD. Finally, it has been observed [36] decreased FA in callosal fibers interconnecting both orbito-frontal and dorso-lateral circuitries. Altogether, studies on callosal changes in OCD patients have revealed inconsistent results, where the failure to replicate findings may be due to rather small samples and/or effect size, the callosal measurement methods adopted, as well as the different imaging modalities. The main goal of the present study was to investigate the structure of the CC in a relatively large group of OCD patients using two structural MRI techniques: one is based on manually CC tracing and surface-based mesh-modeling techniques to explore callosal thickness; the other one is an automatic procedure based on statistical parametric mapping to indicate callosal white matter (WM) density on a voxel level. As a secondary aim we set out to investigate how callosal features are related to cortical gray matter (GM) density and to neuropsychological performance. 2. Materials and methods 2.1. Subjects Thirty patients diagnosed with OCD, who were consecutively seen in three outpatient clinics in central Italy, were recruited for the study. OCD was diagnosed according to the DSM-IV-TR [2]. Three clinical psychiatrists who were treating the patients and knew their clinical history, made a preliminary diagnosis of OCD. The clinicians were blind to the aims of the study. All diagnoses were then confirmed (or not) on the day of image acquisition by another clinical psychiatrist (G.S.) using the structured clinical interview for DSM-IV-TR patient edition (SCID-P) [19]. This latter psychiatrist also screened the patients to see whether they fulfilled the exclusion criteria of the study. If the clinicians disagreed, additional information was requested to resolve differences, and the diagnostic process was continued to yield a final consensus. If the diagnosticians still disagreed, the patient was removed from the sample. The inter-rater reliability of the psychiatrists was more than 0.80 for diagnosing OCD. Exclusion criteria were: present or past substance dependence or abuse; history of traumatic head injury with loss of consciousness; any past or present major medical or neurological illness; any other current or past DSM-IV-TR Axis I disorder as assessed by the SCID-P (of note, all patients suffered from pure OCD without any additional axis I disorder in comorbidity);  any brain pathology identified on T1-, T2- and FLAIR-scans;  mental retardation.    

Clinical history information was obtained from the patients, their relatives, physicians and psychiatrists and their clinical charts. We measured OCD symptom severity with the Yale-Brown Obsessive Compulsive Severity Scale (Y-BOCS) [25]. Mean total YBOCS severity scale score was 28 (SD 7.3). All OCD patients (17 males, 13 females) were between 19 and 55 years of age. All were right-handed and had completed at least 5 years of education (Table 1). Twenty-one patients (out of 30) were under stable pharmacological treatment for at least 3 months. Nine patients were drug-free (Table 2). However, all patients were in a period of clinical stability of at least 3 months. The thirty healthy control (HC) subjects, who volunteered to participate in this study, were recruited from the same geographic area. All were carefully screened for a current or past axis I or II disorder diagnosis using the SCID-I non-patient edition and the SCIDII [18,20]. Any mental disorder diagnosis in parents and siblings was also an exclusion criterion, as well as the other above-mentioned exclusion criteria for patients. They also underwent a neuropsychological assessment. The thirty HC subjects were matched with the OCD patients for age, gender and handedness [37] (Table 1). Consent was obtained according to the Declaration of Helsinki and the study was approved by the Santa Lucia Foundation Research Ethics Committee. All participants (and/or their proxies when needed) provided written informed consent. 2.2. Cognitive examination Two trained neuropsychologists, blind to the aims of the study, conducted the cognitive assessment of all OCD patients and HC subjects within seven days of the MRI. Acceptable inter-rater reliability was defined as k > 0.80. The cognitive profiles of both groups of OCD and HC were assessed via administering a neuropsychological battery. More specifically, to examine verbal and visuo-spatial episodic memory we administered the Rey’s 15word Immediate Recall (RWIR) test and Delayed Recall (RWDR) test [42], as well as the Rey-Osterrieth Complex Figure delayed recall (ROCFDR) test [38]. To examine visuo-spatial short-term memory, language and executive functions, we administered the Immediate Visual Memory (IVM) test [10], the Phonological Verbal Fluency (PVF) test [7] and the Modified Wisconsin Card Sorting Test (MWCST) [35]. To examine visuo-spatial functions, we administered the simple praxis Copy of Drawing (CD) and Copy of Drawings with Landmarks (CDL) tests [22]. Finally, we examined visuo-spatial logical reasoning abilities via administering the Raven’s Progressive Matrices’ 47 (PM47) [41]. 2.3. MRI data acquisition All MRI data were acquired on a 3 T Allegra MR system (Siemens, Erlangen, Germany) using a birdcage head coil. Scans for clinical and research purposes were collected in a single session, with the following pulse sequences:

Table 1 Sociodemographic and clinical characteristics of OCD patients and HC subjects. Characteristics

OCD (n = 30)

HC (n = 30)

Fischer’s Exact and T test

Males n (%)

17 (56.7)

15 (50)

0.796

1

n.s.

Age (in years) mean  SD (range)

37  10.4 (19–55)

37  10.5 (19–57)

0.000

58

n.s.

Educational level (in years) mean  SD

13  3.3

15  2.7

58

0.026

Handness (The Edinburgh Inventory) [37]

All right hand

All right hand

MMSE (mean  SD)

28.5  2.1

29.3  1.1

Illness duration (in years) (mean  SD)

17.2  13.03

2.279 1.000 1.682

df

P

1

n.s.

58

n.s.

OCD: obsessive compulsive disorder; HC: healthy controls; SD: standard deviation; df: degrees of freedom; MMSE: mini mental state examination; n.s.: non significant.

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Table 2 Pharmacological treatment and illness duration of individual obsessive compulsive disorder (OCD) patients. OCD (n)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Drugs

Dosages (mg/day equivalent values)

Antipsychotic (olanzapine)

Antidepressant (citalopram)

Antipsychotic (olanzapine)

Antidepressant (citalopram)

Yes No No Yes Yes No No No No No No Yes Yes No Yes No No No No No Yes Yes Yes No No Yes No Yes No Yes

Yes No Yes No No Yes Yes No No Yes Yes Yes Yes Yes Yes No No Yes No No Yes Yes Yes Yes No Yes Yes Yes No Yes

2 0 0 15 20 0 0 0 0 0 0 20 10 0 10 0 0 0 0 0 33 10 2 0 0 5 0 5 0 15

40 0 30 0 0 70 45 0 0 70 60 10 20 50 100 0 0 20 0 0 100 80 10 20 0 80 20 60 0 60

 PD and T2-weighted double turbo spin-echo (SE) acquired in transverse planes (TR: 4500 ms, TE: 12 ms, TE: 112 ms, FOV 230  172 mm, matrix 320  240, slice thickness: 5 mm, number of slices: 24);  fluid-attenuated inversion-recovery (FLAIR) in the same planes as the SE sequence (TR/TE: 8500/109 ms, TI: 2000 ms, FOV: 230  168 mm, matrix 256  256, slice thickness: 5 mm, number of slices: 24);  high-resolution T1-weighted 3D images, with partitions acquired in the sagittal plane, using a modified driven equilibrium Fourier transformation (MDEFT) [14] sequence (TE/TR = 2.4/ 7.92 ms, flip angle 15, TI: 910, isotropic voxels: 1  1  1 mm3). 2.4. Group differences in point-wise callosal thickness Radiofrequency bias-field corrections were applied to all images to reduce intensity variations due to magnetic field inhomogeneities [46]. Images were linearly registered to the Montreal Neurological Institute (MNI) 305-template using nineparameter transformations to adjust for brain orientation and size. Using the bias-corrected, scaled images, regional callosal thickness was estimated in a three-step approach as detailed elsewhere [31,32]. Briefly, one trained rater manually outlined upper and lower callosal boundaries in the midsagittal section of each brain (Step I). The intra-rater reliability for manually tracing the midsagittal callosal boundaries was Cohen k = 0.90. The spatial average from 100 equidistant surface points representing the upper and lower boundaries was then calculated, and a new midline segment (also consisting of 100 equidistant points) was created (Step II). Distances between 100 corresponding surface points from this new midline to upper/lower boundaries were quantified (Step III). Using the callosal distance values, we applied independent sample t-tests between OCD patients and HC. As statistical tests were made at hundreds of callosal surface points

Illness duration (in years)

5 9 10 19 3 38 8 1 15 18 4 5 3 4 26 27 36 30 1 22 33 24 19 20 37 5 7 22 49 16

and adjacent data points are highly correlated, statistical results were corrected for multiple comparisons using the False Discovery Rate (FDR) method, with a 5% maximum allowable FDR [5]. Both uncorrected and corrected maps were displayed. 2.5. Group differences in voxel-wise callosal white matter density Images were processed and analyzed using VBM [3,24] in the statistical parametric mapping framework (SPM5, Wellcome Department of Imaging Neuroscience, University College London, UK). To improve image registration, images were first manually reoriented to approximate the orientation to that of the ICBM-152 default SPM5 template. Each volume was segmented into WM and GM partitions. Then, the Diffeomorphic Anatomical Registration Through Exponential Lie Algebra (DARTEL) toolbox was applied to the WM and GM partitions separately. Template creation is incorporated into the algorithm and a new template based on the entire sample is recreated at the end of each iteration. This technique improves the realignment of small inner structures [52]. Then, we used a script to transform the DARTEL template and images to MNI space (D. MacLaren, personal communication). Finally, WM and GM partitions (unmodulated data) were smoothed using a Gaussian kernel of 8 mm full width at half maximum (FWHM) and entered into subsequent statistical analyses. We applied independent sample t-tests at each voxel to compare OCD patients to HC subjects with respect to WM density. Statistical maps were corrected for multiple comparisons using the family wise error (FWE) at P < 0.05. Significant findings were mapped onto the ICBM-152 default SPM5 template. The presentation of significant clusters was restricted to findings located on the CC using a three-dimensional volume of interest (VOI). This VOI was manually created using the averaged and normalized WM partitions of all patients and controls (accounting for the shape variability of the CC in our group) and smoothed using a Gaussian kernel of 8 mm FWHM.

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Fig. 1. Callosal differences between obsessive compulsive disorder (OCD) patients and healthy control (HC) subjects. The upper panel displays the outcomes of the callosal thickness analysis. The color bar encodes the uncorrected significance (P). The smaller callosal map indicates where significant group differences survived false discovery rate (FDR)-corrections (in red). The lower panel displays the outcomes of the voxel-based morphometry (VBM) analysis. The color bar encodes the family wise error (FWE)corrected significance (T). The left panel illustrates decreased callosal features in OCD patients compared to HC subjects; the right panel demonstrates the lack of decreased callosal features in HC subjects compared to OCD patients.

2.6. Correlations between callosal thickness/callosal white matter density and whole-brain gray matter density within obsessive compulsive disorder subjects As shown in Fig. 1, callosal thickness analysis revealed group differences with greatest effect sizes in anterior and posterior callosal sections, while the VBM analysis revealed group effects only in posterior callosal regions. To calculate the average anterior callosal thickness in OCD subjects, we extracted and averaged the callosal distance values from point 26 to 36 (corresponding to the anterior callosal subregion, where we found a significant difference between the OCD and the HC groups; Fig. 1, upper panel). Similarly, to calculate the average posterior callosal thickness in OCD subjects, we extracted and averaged the callosal distance values from point 66 to 85 (corresponding to the posterior callosal subregion, where we found a significant difference between the OCD and the HC groups; Fig. 1 upper panel). This resulted in two averaged values (i.e., one for the anterior and one for the posterior callosal section) for each OCD subject. We then calculated the anterior and the posterior callosal mean thickness. To calculate the average posterior callosal WM density in OCD subjects, we extracted and averaged the intensity values of the posterior CC region (corresponding to the cluster where we found a difference between the OCD and the HC groups; Fig. 1 lower panel). This resulted in one averaged value for each OCD subject. We then calculated the posterior callosal mean WM density in OCD subjects. Finally, we entered the whole-brain GM density maps and the anterior and posterior callosal mean thickness values, as well as the posterior callosal WM density mean values (calculated as described above) in the design matrix followed by running a multiple regression analysis in SPM5. Given the lack of previous data in the literature linking callosal and cortical GM features in OCD, results were considered statistically significant at both uncorrected as well as corrected levels using FWE correction for multiple comparisons at P < 0.05 cluster-level. To reduce the risk of false-positives, we applied an additional extent threshold of 707 voxels [21,50,51]. 2.7. Correlations between callosal thickness/callosal white matter density and cognitive scores within obsessive compulsive disorder subjects We also investigated whether anterior and posterior callosal thickness as well as posterior callosal WM density were linked to

neuropsychological scores. For this purpose, within OCD patients, we correlated the averaged callosal thickness and callosal WM density values (calculated as described above), with those of nine neuropsychological scores where OCD patients performed significantly worse than HC subjects (Table 2), applying a non-parametric correlation test, the Spearman rank-order correlation. The significance level was adjusted for the nine independent statistical comparisons (Bonferroni correction, P < 0.05/9 < 0.005). 3. Results 3.1. Cognitive measures As some test scores were not normally distributed (Kolmogorov-Smirnov test), we applied a non-parametric test (MannWhitney) to compare OCD patients and HC subjects. Compared to HC, OCD patients showed poorer verbal memory (RWIR U = 186.5, and RWDR U = 190.0) and poorer visuo-spatial episodic and short-term memory (IVM U = 278.0; ROCFDR U = 209.5) performances. OCD patients also showed poorer verbal fluency (PVF U = 182.0) and increased difficulties in executive functions, both with respect to shifting and mental flexibility (MWCST U = 375.0, perseverative errors U = 314.0, non perseverative errors U = 275.0). OCD patients also showed deficits in visuospatial logical reasoning (PM47 U = 218.0) (Table 3). 3.2. Callosal thickness analysis As shown in Fig. 1 (upper panel), we observed significantly thinner callosal regions in OCD patients compared to HC subjects across posterior portions (i.e., anterior splenium, isthmus, and posterior midbody) and anterior portions (i.e., rostral body and rostrum). When applying FDR-corrections, group effects remained significant across large portions of the callosal surface, including anterior splenium, isthmus, and rostral body (q = 0.0145). Callosal thickness was not smaller in HC subjects compared to OCD patients in any region. 3.3. Callosal white matter density analysis As further shown in Fig. 1 (lower panel), callosal WM density was reduced in OCD patients compared to HC subjects within the anterior splenium and isthmus (P = 0.02, FWE-corrected). Callosal

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Table 3 Cognitive scores of OCD patients and HC subjects (neuropsychological battery). Mental deterioration battery

OCD (n = 30)

HC (n = 30)

OCD vs. HC

Mean ( SD)

Range

Mean ( SD)

Range

P

Memory tasks RWIR RWDR ROCFDR IVM

39.4 7.9 14.8 19.7

(13.7) (4.0) (7.4) (2.6)

20–71 0–15 2.5–30 9–22

52.6 12.5 21.7 21.1

(8.7) (2.5) (5.2) (0.9)

36–67 7–15 10.5–33 19–22

0.000 0.000 0.000 0.009

Executive tasks PVF MWCST cat MWCST persev err MWCST non persev err

28.5 5.8 0.9 1.5

(11.1) (0.5) (2.1) (1.6)

9–61 4–6 0–4 0–5

41.0 6.0 0.1 0.5

(11.5) (0.0) (0.4) (0.8)

19–66 6–6 0–2 0–2

0.000 0.021 0.008 0.006

Visuo-spatial tasks CD CDL PM47

10.9 (1.6) 63.4 (10.3) 28.0 (6.7)

6–12 32–70 9–36

9–16 54–70 26–36

n.s. n.s. 0.001

11.5 (1.1) 67.8 (3.1) 33.0 (2.6)

OCD: obsessive compulsive disorder; HC: healthy controls; SD: standard deviation; RWIR: Rey’s 15-word immediate recall; RWDR: Rey’s 15-word delayed recall; ROCFDR: Rey-Osterrieth complex figure delayed recall; IVM: immediate visual memory; PVF: phonological verbal fluency; MWCST cat: modified Wisconsin card sorting test achieved categories; MWCST persev err: modified Wisconsin card sorting test perseverative errors; MWCST non persev err: modified Wisconsin card sorting test non perseverative errors; CD: copy of drawing; CDL: copying drawings with landmarks; PM47: Raven’s progressive matrices’47; n.s.: non significant.

WM density in HC subjects was not significantly reduced when compared to OCD patients. 3.4. Correlations between callosal measures and whole-brain gray matter density within obsessive compulsive disorder subjects At an uncorrected threshold, we found positive correlations between anterior callosal thickness and cortical GM density in the right mid-dorso-lateral prefrontal region (BA 9/46) and in the medial frontal gyri bilaterally (left BA8 and right BA9) in OCD patients. We also detected positive correlations between posterior callosal thickness and cortical GM density in the supramarginal gyrus bilaterally (BA 40) and in the left superior parietal lobe (BA19). Moreover, we observed positive correlations between posterior callosal WM density and GM density within the left hippocampus (tail), left supramarginal gyrus (BA 40) and left occipital lobe (BA 17/18). When we corrected for multiple comparisons, using FWE at the P < 0.05 cluster-level, with a minimum cluster size of 707 voxels, survived significant positive correlations between anterior callosal thickness and cortical GM

density in the right mid-dorso-lateral prefrontal region (BA 9/46) (Z = 3.86, cluster-corrected P = 0.030), and between posterior callosal thickness and cortical GM density in the left supramarginal gyrus (BA 40) (Z = 3.85, cluster-corrected p = 0.011) in OCD patients (Fig. 2). 3.5. Correlations between callosal measures and cognitive scores within obsessive compulsive disorder subjects We found significant positive correlations between the anterior callosal thickness and RWDR score. Significant correlations for posterior callosal thickness were not detectable. We also detected significant positive correlations between the posterior callosal WM density and RWIR and RWDR scores, ROCFDR score, PVF score, and PM47 score (Table 4). 3.6. Supplementary analysis I As shown in Table 3, the OCD group contained patients with lower levels of visuo-spatial logical reasoning (as measured by

Fig. 2. Correlations between callosal measures and whole-brain gray matter (GM) density within obsessive compulsive disorder (OCD) patients. Illustrated are significant positive correlations between anterior callosal thickness and GM density (Panel A) and between posterior callosal thickness and GM density (Panel B). Results are shown at cluster-level (P < 0.05, family wise error [FWE]-corrected) using a minimum cluster size of 707 voxels.

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Table 4 Correlations between corpus callosum measures and neuropsychological scores.

Anterior callosal thickness

RWIR

RWDR

ROCFDR

IVM

PVF

MWCST cat

MWCST persev err

MWCST non persev err

PM47

n.s.

r = 0.358

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

P = 0.003 Posterior callosal thickness

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

Posterior callosal WM density

r = 0.508 P = 0.000

r = 0.581

r = 0.428

n.s.

r = 0.399

n.s.

n.s.

n.s.

r = 0.355

P = 0.000

P = 0.000

P = 0.001

P = 0.003

n.s.: non significant (after applying Bonferroni corrections considering the nine independent statistical comparisons, P < 0.05/9 < 0.005); RWIR: Rey’s 15-word immediate recall; RWDR: Rey’s 15-word delayed recall; IVM: immediate visual memory; ROCFDR: Rey-Osterrieth complex figure delayed recall; PVF: phonological verbal fluency; MWCST cat: modified Wisconsin card sorting test achieving categories; MWCST persev err: modified Wisconsin card sorting test perseverative errors; MWCST non persev err: modified Wisconsin card sorting test non perseverative errors; PM47: Raven’s progressive matrices’47.

PM47) compared to HC subjects. More specifically, the PM47 scores of OCD patients ranged from 9 to 36, while subjects in the HC group scored between 26 and 36. Since the intellectual heterogeneity in the OCD group may affect the main findings of the study, we repeated the main analyses (i.e., the group comparisons with respect to callosal thickness and callosal WM density) after excluding the OCD patients with PM47 scores lower than 26. As shown in Supplementary Fig. 1, within OCD patients with high levels of visuo-spatial logical reasoning, the callosal thickness analysis as well as the callosal WM density analysis revealed outcomes similar to those when including the whole OCD sample, and group differences were only slightly less pronounced, thus confirming results obtained in the main analyses. 3.7. Supplementary analysis II As described above (Table 2), the OCD patients were under pharmacological treatment. To address possible confounding effects of medication, we repeated the main analyses (i.e., the HC vs. OCD comparisons with respect to callosal thickness and callosal WM density) within two subgroups of patients:  those who did not take antipsychotic drugs (n = 18);  those who did not take antidepressant drugs (n = 11). As shown in Supplementary Fig. 1, when conducting these analyses within the antipsychotic drug-free OCD group, the callosal thickness analysis as well as the callosal WM density analysis revealed the most pronounced effects within the isthmus. In contrast, when conducting these analyses within the antidepressant drug-free OCD group, OCD callosal thickness was reduced within the tip of the splenium, while OCD callosal WM density was reduced within the isthmus. 4. Discussion OCD patients present pronounced macrostructural callosal aberrations in anterior and posterior callosal subregions. The reduction in the posterior callosal subregions remains evident even when taking into consideration the reduced visuo-spatial logical reasoning level of OCD patients and/or the influence of antipsychotic and antidepressant drugs treatments. 4.1. Anterior versus posterior alterations Our data suggests that OCD patients have macrostructural abnormalities in the CC rostral body and rostrum, with accompanying abnormalities in orbito-frontal regions connected through these callosal fiber tracts [26,45]. The orbito-frontal cortex is involved in mediating emotional response and behavioral regulation [17], and abnormalities in the orbito-frontal circuit can

determine changes in personality, including emotional lability and behavioral disinhibition [47]. Thinning in these callosal subregions might be linked to dysfunctions in inhibition, response suppression, and response selection – typical behavioural changes in OCD patients – which are historically assigned to dysfunctions of the orbito-frontal circuit. The observed differences in posterior callosal subregions are in line with those recently reported in the context of OCD [39]. They also found a posterior callosal involvement. This novel datum stresses the potential abnormal interhemispheric connectivity of the parieto-temporal and occipital cortices – cerebral areas connected through the affected posterior callosal subregions [26,45]. This result invokes the role of the dorso-lateral prefrontal circuit in OCD pathology. Indeed, the dorso-lateral prefrontal circuit is an ‘‘open loop’’ receiving afferent input and providing efferent connections from and to no-circuit sources. Specifically, the dorso-lateral prefrontal circuit projects and receives input, at the cortical level, from the posterior temporal, the parietal, and the occipital association areas [13]. The possible involvement of the dorso-lateral prefrontal circuit in OCD patients seems to be supported by the outcomes of the correlations analysis: anterior callosal measures were positively correlated with GM density values of the right mid-dorso-lateral prefrontal regions (BA 9/46), while posterior callosal measures were positively correlated with GM density values of the left supramarginal gyrus (BA 40) – a temporo-parietal association area. Furthermore, a possible impairment of the dorso-lateral prefrontal circuit corresponds well with impaired cognitive performance in OCD, as proposed previously [12,13,47], and also observed here. Indeed, our OCD patients showed reduced performance in verbal and visuo-spatial memory, in executive functions, in visuo-spatial construction, and in visuo-spatial reasoning. Moreover, we detected a link between callosal measures and neuropsychological scores (verbal memory, visuo-spatial memory, verbal fluency, and visuo-spatial reasoning) specifically located in posterior callosal subregions (including isthmus and splenium) connecting parietal, temporal and occipital lobes which are known to support ‘‘posterior’’ cognitive functions, such as memory and visuo-spatial abilities [34,49]. Altogether, these results are congruent with those described in recent articles [11,29,36,48,53], which link OCD to comprehensive impairments of the anatomical system, including both the orbito-frontal circuit (according to the traditional model) and the dorso-lateral prefrontal circuit (postulated more recently). 4.2. Macrostructure versus microstructure A fundamental aspect to consider when studying the CC of OCD patients is WM fiber density, diameter, and myelinization. That is, anterior CC subregions contain a lower density of smaller diameter and lightly myelinized fibres [1]. In contrast, the isthmus contains

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the highest density of larger diameter and heavily myelinized fibres [1]. Callosal thickness (albeit somewhat dependent on fiber number and diameter) measures mainly a rather macroscopic feature; differently, callosal WM density – indicative of the amount of WM concentration in the tissue – seems to be more directly linked to microscopic features. Changes in callosal thickness as well as WM density may also be ascribed to regional variations in extracellular and/or intracellular water content (which, again, might vary depending on the density of regional fibers and/or damages to individual axons or myelin sheaths). Neither callosal thickness nor WM density measures, however, allow capturing the precise underlying microstructural anatomical substrate. Thus, future studies might benefit from obtaining DTI-based measures. DTI is a non-invasive MR technique, which uses the local water diffusion in the brain tissues to study microstructural aspects of WM anatomy [40]. There is a general agreement that the diffusivity of water depends primarily on the presence of microscopic structural barriers (membranes of cell bodies, axons and myelin sheaths), which impedes the water to move randomly in the brain tissue [4]. When these structural barriers are damaged, the water is free to move in different directions. The computation of different DTI parameters such as fractional anisotropy, axial and radial diffusivity, together with macrostructural assessments has already been proven to be extremely helpful in understanding pathophysiological mechanisms (e.g., axonal damage versus demyelinization) that underlie the callosal WM changes [15]. Thus, further studies should analyze OCD callosal changes using also DTI parameters of axial and radial diffusivity. 4.3. Discrepancies in findings The slightly different findings resulting from the surface-based approach (examining callosal thickness) and from VBM (examining callosal WM density) underline the importance of applying a multiple-measurement approach. Different techniques examine different features and thus provide a more comprehensive picture of affected brain structures and systems in OCD (and in neurological and psychiatric disorders, in general). Technical differences between the two MRI approaches also account for some discrepancies in findings. The well-validated surface-based approach examines callosal morphology with high regional specificity but, due to the manual tracing procedure, is somewhat observer-dependent. Moreover, it is rather time-consuming and does not survey the whole-brain. In contrast, VBM is largely operator-independent and relatively quick, albeit restricted to analyzing brain tissue (rather than the shape of specific brain structures). Altogether, previous reports [16] suggested that ROI-based and VBM analyses generally reveal congruent results. The correspondence between surfacebased (ROI-based analysis) and voxel-based findings in posterior callosal section supports this common observation. The additional effect in the anterior callosal section was detected using the surfacebased approach and suggests that the ROI-based technique can offer advantages when studying a specific brain region. While discrepancies between current outcomes and some previous results may indeed reflect differences across methods, they may also stem from differences with respect to clinical features of the OCD population studied. Symptoms of OCD can be extremely heterogeneous [33], with sometimes non-overlapping symptom patterns across patients. Unfortunately, pure subtypes of OCD patients are rare and the recruitment of sufficient sample sizes of each subtype is difficult. In fact, the majority of studies (and our study is no exception) grouped together patients with mixed OCD phenomenology, which may obscure (and bias) study outcomes [33]. Thus, further studies should focus on investigation of more homogeneous OCD subtypes and associated CC specific abnormalities. On a related note, the analysis of imaging data obtained from patients who are

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undergoing drug treatment is problematic in general. On the one hand, there is a high inter-individual variability in drug selection, drug dosage and administration and start and length of treatment. On the other hand, even within subjects, treatment responses and dosages are likely to change during the course of the disorder. Thus, although we have accounted for some medication effects in our study, the high inter-individual variability with respect to treatment history, procedures, and responses should be considered as a general limitation in this kind of research. 5. Conclusion Compared to HC subjects, OCD patients show structural differences in anterior and posterior callosal regions. The posterior differences may exist independently from any other potentially confounding influence, such as lower intellectual levels or drug treatment. The callosal differences may be linked to cortical aberrations as well as cognitive differences in OCD. These data suggest that the CC should be considered as a structure integrally involved in OCD. Disclosure of interest The authors declare that they have no conflicts of interest concerning this article. Acknowledgements This work was supported by the Italian Ministry of Health (RC07-08-09 and RF 07-08) grants. This study was also supported by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 RR021813 entitled Center for Computational Biology (CCB). Additional support was provided by grants P41 RR013642 and M01 RR000865 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). Algorithm development for this study was also funded by the NIBIB (R01 EB007813, R01 EB008281, R01 EB008432), NICHHD (R01 HD050735), and NIA (R01 AG020098). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.eurpsy. 2012.07.001. References [1] Aboitiz F, Scheibel AB, Fisher RS, Zaidel E. Fiber composition of the human corpus callosum. Brain Res 1992;598:143–53. [2] APA. Diagnostic and statistical manual of mental disorders. (IV-TR), 4th ed. text revised, Washington: American Psychiatric Press; 2000. [3] Ashburner J, Friston KJ. Voxel-based morphometry: the methods. Neuroimage 2000;11:805–21. [4] Beaulieu C. The basis of anisotropic water diffusion in the nervous system: a technical review. NMR Biomed 2002;15:435–55. [5] Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc 1995;57:289–300. [6] Bora E, Harrison BJ, Fornito A, Cocchi L, Pujol J, Fontenelle LF, et al. White matter microstructure in patients with obsessive compulsive disorder. J Psychiatry Neurosci 2011;36:42–6. [7] Borkowsky JG, Benton AL, Spreen O. Word fluency and brain damage. Neuropsychologia 1967;5:135–40. [8] Boroojerdi B, Topper R, Foltys H, Meincke U. Transcallosal inhibition and motor conduction studies in patients with schizophrenia using transcranial magnetic stimulation. Br J Psychiatry 1999;175:375–9. [9] Breiter HC, Filipek PA, Kennedy DN, Baer L, Pitcher DA, Olivares MJ, et al. Retrocallosal white matter abnormalities in patients with obsessive compulsive disorder. Arch Gen Psychiatry 1994;51:663–4. [10] Caltagirone C, Gainotti G, Masullo C, Miceli G. Validity of some neuropsychological tests in the assessment of mental deterioration. Acta Psychiatr Scand 1979;60:50–6.

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