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Brain white matter integrity and association with age at onset in pediatric obsessive-compulsive disorder Rosso, Isabelle M; Olson, Elizabeth A; Britton, Jennifer C; Stewart, S E; Papadimitriou, George; Killgore, William D; Makris, Nikos; Wilhelm, Sabine; Jenike, Michael A; Rauch, Scott L Dec 18, 2014

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RESEARCHBrain white matter integrin, MBiology of Mood & Anxiety DisordersRosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13http://www.biolmoodanxietydisord.com/content/4/1/13phenotype [5,6].2Department of Psychiatry, Harvard Medical School, Boston, MA, USAFull list of author information is available at the end of the articleBackgroundObsessive-compulsive disorder (OCD) is a common neuro-psychiatric illness characterized by repetitive thoughtsand behaviors that are unwanted, distressing, and dis-abling (DSM-IV; [1]). Onset occurs in childhood formore than half of OCD patients, with about 40% ofpediatric cases achieving remission and the remainingpersisting into adulthood [2,3]. Epidemiological studiesshow that pediatric OCD has typical onset between 7 and13 years [2] and that it differs from its adult-onset counter-part in a number of ways, including male preponderance,high familial loading, and more frequent comorbidity withdevelopmental disorders [2,4]. Based on these correlates,it has been speculated that pediatric OCD may be a de-velopmental subtype that is discontinuous from adultOCD, or a developmentally moderated expression of etio-logic processes that are shared with the adult clinical* Correspondence: irosso@hms.harvard.edu1Center for Depression, Anxiety and Stress Research, McLean Hospital, 115Mill Street, mailstop 334, Belmont, MA 02478, USAAge at onsetAbstractBackground: Obsessive-compulsive disorder (OCD) is a common and debilitating neuropsychiatric illness thoughtto involve abnormal connectivity of widespread brain networks, including frontal-striatal-thalamic circuits. At leasthalf of OCD cases arise in childhood and their underlying neuropathology may differ at least in part from that ofadult-onset OCD. Yet, only a few studies have examined brain white matter (WM) integrity in childhood-onset OCDusing diffusion tensor imaging (DTI), and none have examined potential associations with age at onset.Results: In this study, 17 youth with OCD and 19 healthy control subjects, ages 10 to 19 years, underwent DTI on a3T Siemens scanner. DSM-IV diagnoses were established with standardized interviews, and OCD symptom severitywas evaluated using the Children ? s Yale-Brown Obsessive-Compulsive Scale (CY-BOCS). Voxel-wise analyses wereconducted on data processed with tract-based spatial statistics (TBSS) to derive measures of fractional anisotropy(FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). OCD patients had significantly lower FAin seven WM clusters, with over 80% of significant voxels in bilateral frontal cortex and corpus callosum (CC). Therewere no regions of significantly higher FA in patients compared with controls. Patients also had significantly higherRD in right frontal cortex and right body of the CC. Earlier age at onset of OCD correlated significantly with lowerFA in the right thalamus and with higher RD in the right CC. FA and RD were not significantly associated withsymptom severity.Conclusions: These findings point to compromised WM integrity and reduced myelination in some brain regionsof children with OCD, particularly the CC and fiber tracts that connect the frontal lobes to widespread cortical andsubcortical targets. They also suggest that age at onset may be a moderator of some of the WM changes inpediatric OCD.Keywords: Obsessive-compulsive disorder, Childhood, Diffusion tensor imaging, Corpus callosum, Thalamus,age at onset in pediatric odisorderIsabelle M Rosso1,2*, Elizabeth A Olson1,2, Jennifer C BrittoWilliam DS Killgore1,2, Nikos Makris5,6,7, Sabine Wilhelm2,8? 2014 Rosso et al.; licensee BioMed Central. ThCommons Attribution License (http://creativecreproduction in any medium, provided the orDedication waiver (http://creativecommons.orunless otherwise stated.Open Accessty and association withbsessive-compulsive3, S Evelyn Stewart4,9, George Papadimitriou5,6,7,ichael A Jenike2,8,10 and Scott L Rauch1,2is is an Open Access article distributed under the terms of the Creativeommons.org/licenses/by/4.0), which permits unrestricted use, distribution, andiginal work is properly credited. The Creative Commons Public Domaing/publicdomain/zero/1.0/) applies to the data made available in this article,Rosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 2 of 10http://www.biolmoodanxietydisord.com/content/4/1/13Neuroimaging research has provided converging evidencethat OCD symptoms arise from alterations in widespreadbrain networks. Abnormalities in frontal-striatal-thalamo-cortical loops are central to prevailing conceptual modelsof the disorder [7,8]. Pathological obsessions and compul-sions are proposed to involve insufficient inhibitory con-trol of striatal and thalamic nuclei by prefrontal corticalregions, particularly the anterior cingulate and lateral orbi-tofrontal cortices [9], and neuroimaging findings of alteredregional brain volumes and function largely support thesemodels (e.g., [10,11]). In addition, there is growing evi-dence implicating brain regions outside of the frontal-subcortical loops, including the posterior parietal andoccipital regions [12]. Similarly, neuropsychological find-ings identify deficits across multiple domains of cognitivefunctioning, including set shifting, response inhibition,memory, and attention [13-17].Most of the imaging literature to date is in adult ratherthan pediatric OCD. This is especially the case for studiesthat have used diffusion tensor imaging (DTI) to identifychanges in brain white matter (WM) [18]. DTI is a mag-netic resonance method that estimates the magnitude anddirection of water diffusion, which is dependent on theunderlying structure of brain tissue. In particular, highlyorganized myelinated axon fibers will constrain and directwater diffusion, such that DTI parameters allow inferencesabout WM organization and integrity. Mean diffusivity(MD) is the DTI parameter that reflects magnitude of dif-fusion at each voxel, which varies with tissue density re-gardless of fiber orientation [19]. Fractional anisotropy(FA) is the DTI parameter reflecting directionality of diffu-sion in each voxel, such that FA is higher along fiber bun-dles that are more coherent or organized [20]. FA can alsobe separated into components reflecting diffusion paralleland perpendicular to the WM tracts, referred to as theaxial diffusivity (AD) and radial diffusivity (RD), respect-ively. FA values decrease when AD decreases and/or RDincreases. Interestingly, RD and AD may be biomarkers ofdifferent cellular developmental or pathological processes.Specifically, changes in RD appear to be associated withcell membrane alterations (myelination), whereasvariations in AD may be more related to axonal injuries(volume and organization) [21].In DTI studies of adult OCD, FA has been the mostcommonly studied diffusion parameter. FA alterations havebeen observed most consistently in the corpus callosum(CC), cingulum bundle, internal capsule, and anterior thal-amic radiation, as well as the parietal cortex (e.g., [22-25]).However, the directionality of FA alterations has varied,with reports of lower [23,24,26,27], higher [25,28], or com-parable FA values when comparing adult OCD patientswith healthy control (HC) subjects [22,29,30]. These seem-ingly disparate findings likely reflect true regional brainvariability in hypo- and hyper-connectivity across fibertracts implicated in OCD, as well as methodological differ-ences across studies. For instance, although all studieshave reported on FA, fewer have incorporated other diffu-sivity measures that can help contextualize FA findings.In addition, findings may relate to certain patient vari-ables, such as psychiatric comorbidity, illness duration,and medication use. Notably, investigation of childhoodOCD can help reduce some of these confounding influ-ences including those related to illness chronicity [6] andcan also isolate neurobehavioral features that relate to anearly age at onset. Most adult OCD studies have combinedpatients with childhood and adult onset, which may intro-duce neurobiological variability. For instance, whereasmeta-analyses of functional imaging findings indicate acentral role of the caudate nucleus in adult OCD, neuro-imaging studies of pediatric OCD point to more promin-ent involvement of other basal ganglia structures and thethalamus [5]. Thus, age at onset may be associated withneurobiological variability in OCD and could help parsedisease heterogeneity.As in the adult literature, studies of pediatric OCD haveprovided evidence of diffusion abnormalities in multipleWM tracts, although the nature and directionality ofdiffusion changes have varied, as have their associationswith clinical features of illness. Two pediatric OCD DTIstudies have reported FA as the main measure of diffusion[16,31]. Zarei et al. [31] found increased FA across a num-ber of WM tracts in adolescent OCD patients, changesmore widespread than those found in many adult OCDstudies. Moreover, OCD symptom severity was positivelycorrelated with FA in several of these tracts. Similarly,Gruner and colleagues [16] found that children with OCDhad FA increases, though these were localized to fourWM tracts, namely the left dorsal cingulum bundle, sple-nium of the CC, right corticospinal tract, and left inferiorfronto-occipital fasciculus. Interestingly, increased FA inthe cingulum bundle predicted better executive function-ing within the OCD group, suggesting that it may reflect acompensatory process. Another two pediatric OCD stud-ies found no group differences in FA, but examination ofAD and RD revealed significant diffusivity differences[32,33]. Specifically, Silk et al. [33] found lower AD in thegenu and splenium of the CC of children with OCD com-pared with controls, and lower AD correlated with greaterseverity of symptoms. In contrast, Jayarajan et al. [32]found significantly higher AD and RD, and neither wassignificantly correlated with symptom severity, medicationdosage, or treatment duration. No pediatric OCD studyhas yet reported on whether diffusion changes are signifi-cantly associated with age at onset.In this study, we used DTI to compare brain WMmicro-structure in youth with OCD compared with healthymatched controls, examining four diffusion parameters(MD, FA, AD, and RD). We hypothesized that pediatricRosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 3 of 10http://www.biolmoodanxietydisord.com/content/4/1/13OCD would be associated with altered FA, without an ?priori prediction concerning the directionality of alteration(i.e., increased or decreased) due to scant published datain pediatric samples and inconsistent adult OCD DTIfindings. Based on theoretical and empirical indicationsthat age at onset may be relevant to the variability ofDTI findings in OCD, we also tested the hypothesis thatdiffusion differences would be associated with age at onsetof OCD.MethodsSubjectsThirty-six youth were enrolled in this neuroimaging experi-ment as paid volunteers. OCD subjects were treatment-seeking children presenting to an OCD clinic, and controlsubjects were recruited in the surrounding Boston metro-politan community via advertisements. The subjects wereselected to be between 10 and 19 years old, similar to theage range in prior imaging studies of pediatric OCD. Par-ticipants were excluded if they reported current medicalor neurological illness, or a history of head injury withloss of consciousness. Prior to enrollment, written in-formed consent was obtained from a parent/legal guardianand written informed assent was obtained from the child/adolescent participant. All study procedures were per-formed in accordance with the Human ResearchCommittees at McLean Hospital and Partners Health-care System.The Kiddie Schedule for Affective Disorders andSchizophrenia (KSADS) was administered to all partici-pants and their parents by doctoral-level psychologists[34]. Individuals included in the OCD group met DSM-IVcriteria for this disorder based on the KSADS [1]. Inaddition, OCD symptom severity scores were determinedusing the Children? s Yale-Brown Obsessive-CompulsiveScale (CY-BOCS) [35]. To recruit a representative andgeneralizable OCD sample, the inclusion criteria for theOCD group allowed for comorbid psychiatric disorders,with the exception of psychotic disorders, bipolar disorder,mental retardation, substance use disorders, and pervasivedevelopmental disorders. Neuroleptic and anti-hypertensivemedications were exclusionary. All individuals included inthe HC group were free from any current Axis I psychiatricdisorder and psychotropic medications. All subjects com-pleted the Child Depression Inventory (CDI) [36], and theYale Global Tic Severity Scale (YGTSS) was used to ruleout subjects with Tourette? s syndrome and other tic-relateddisorders [37].The participants consisted of 17 children with OCD and19 HC youth. This sample was obtained after excludingdata from participants for excessive head movement (1OCD) and poor head coverage (1 HC). The patient groupendorsed the following types of OCD symptoms acrosspreviously identified clusters [38]: contamination/washing(N= 4); symmetry/arranging/counting/repeating (N = 10);and aggression, sexual, religious, and/or somatic obsessions/checking (N = 14). No hoarding symptoms were reported.Nine (9) of the patients had no comorbid Axis I diag-nosis. The following comorbidities were present in theremaining eight OCD patients, based on KSADS inter-views: generalized anxiety disorder (N = 1), specific phobia(N = 2), agoraphobia (N = 1), major depressive disorder(N = 2), depression not otherwise specified (N = 2), op-positional defiant disorder (N = 1), and attention-deficithyperactivity disorder (N = 2). Three (3) of the OCD pa-tients were not taking any psychotropic medication. Pri-mary medications taken by the remaining 14 OCDsubjects were antidepressants: selective serotonin re-uptake inhibitors (N = 13) and tricyclic agents (N = 1). Inaddition, some patients were taking secondary medica-tions, namely stimulants (N = 4), mood stabilizers (N = 3),and benzodiazepines (N = 1).Diffusion tensor imagingImage acquisitionDTI scans were acquired using a Siemens Tim Trio 3Tscanner at the McLean Hospital Imaging Center. Diffusionweighted imaging data were obtained in 60 directions withthe following parameters: echo time = 98 ms, bandwidth =1,396 Hz/pixel, matrix = 128 mm ? 128 mm, FOV =256 mm ? 256 mm, NEX = 1, voxel size = 2.0 mm 3 ?2.0 mm3 ? 2.0 mm 3, 10 T2 low b (b = 0 s/mm2), and 60DWI (diffusion sensitivity b = 700 s/mm2), and 60 axialslices with 2-mm thickness.Image processing and analysisThe analysis of DTI data was done using the FMRIB Dif-fusion Toolbox from the FSL processing software pack-age (http://www.fmrib.ox.ac.uk/fsl) [39,40]. The first stepwas motion and eddy current distortion correction, ap-plied using FSL? s eddy_correct tool, which ran with its de-fault options. The raw data were skull-stripped usingFSL? s Brain Extraction Tool (BET) [41]. A diffusion tensormodel was fit at each voxel using a least squares fit tothe diffusion signal with FSL? s dtifit tool; this generatedmaps for each of the diffusivity measures (FA, MD, AD,and RD). At this point, a mathematical correction forsystematic vibration artifact was applied [42]. Voxel-wiseprocessing of diffusivity measures was carried out usingtract-based spatial statistics (TBSS) [43], which is part ofFSL [44]. Images from all subjects were aligned to eachother using nonlinear registration in order to determinethe most representative individual (i.e., the closest to themean of the group) to be defined as the target image. Thistarget image was then aligned, using affine registration, toMNI152 standard space. Each individual subject was thenregistered into the Montreal Neurological Institute (MNI)space by combining the nonlinear transform (generatedvia FSL? s FNIRT) from the subject to the target image withthe affine transform from the target image into the MNIspace. A mean FA image was created by averaging allaligned FA maps and was thresholded with an FA ≥ 0.2 togenerate a mean FA skeleton, which represents the centersof all fiber tracts common to all subjects. Each subject? saligned FA image was projected onto the mean FA skel-eton and served as the input to the TBSS. Group statisticalanalysis was then conducted only on voxels within thewhite matter skeleton mask, therefore restricting thevoxel-wise analysis only to voxels with high confidence oflying within equivalent major white matter pathways inRosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 4 of 10http://www.biolmoodanxietydisord.com/content/4/1/13each individual. After completing the above proceduresfor FA, the nonlinear warps and skeleton projection wereapplied to MD, RD, and AD using tbss_non_FA. Differ-ences in FA, MD, and axial and radial diffusivity betweenthe OCD and control groups were assessed using voxel-wise independent two-sample t-tests by randomization,the nonparametric analysis tool in FSL. The Threshold-FreeCluster Enhancement (TFCE [45]) option was employedat family-wise error-corrected p < 0.05 to obtain clusterinferences.Statistical analysesGroup differences in demographic characteristics were ex-amined using χ2 tests for categorical variables and inde-pendent t-tests for continuous variables. DTI parameters(FA, RD, MD, and AD) were analyzed using permutationtesting and TFCE in FSL by applying an independentt-test to the data for between-group comparisons. The sig-nificance level was p < 0.05, family-wise error-corrected.Within significant clusters, the mean values were com-puted. Correlations of DTI variables with demographicand clinical variables were performed in SPSS version 20.ResultsDemographic and clinical data are summarized inTable 1. CY-BOCS total scores ranged from 8 to 32,spanning the mild to extreme severity range of obsessiveTable 1 Demographic and clinical characteristics of thesample (mean ? SD or N (%))Variable OCD (n = 17) Controls (n = 19) pFemale 6 (35%) 6 (32%) 0.8Age (years) 14.06 ? 2.56 13.58 ? 2.12 0.54Education (years) 8.65 ? 2.40 8.37 ? 1.95 0.70CDI (total) 8.94 ? 7.16 3.47 ? 3.79 <0.01CY-BOCS (total) 17.06 ? 8.17 -Obsessions 8.12 ? 4.47 -Compulsions 8.94 ? 4.19 -Age at onset (years) 8.82 ? 3.36 -Duration of illness (years) 5.24 ? 2.97 -and compulsive symptoms. In addition, OCD patientsendorsed significantly higher levels of depression thanHC subjects on the CDI (p ? s < 0.01).Between-group differences in diffusionOCD youth had significantly lower FA than HC subjectsin widespread areas across seven separate clusters, num-bered 1 ? 7 in Table 2 and Figures 1 and 2. Nearly 98% ofthe significant voxels localized to clusters 1 and 2. Cluster1 was a bilateral cluster (9,022 voxels) encompassing areasof the frontal lobes and CC (genu, body, and splenium).Cluster 2 (1,454 voxels) encompassed areas of the anteriorcingulate cortex and extended into several subcortical re-gions including the putamen, amygdala, and thalamus.Cluster 3 (132 voxels) localized to the right angular andlateral occipital gyri. Cluster 4 (50 voxels) was in the rightinferior frontal cortex, more specifically the subcallosalcortex. Cluster 5 was also a right inferior frontal clusterbut more anteriorly, corresponding to the orbitofrontalcortex. Cluster 6 corresponded to 14 voxels in the rightthalamus, and cluster 7 comprised 6 voxels in the rightcaudate and anterior internal capsule. There were no sig-nificant clusters where FA was higher in OCD patientsthan in HC subjects. Compared with HC subjects, OCDpatients also had significantly increased RD in areas of theright frontal cortex and body of the CC, across threeclusters that overlapped with the first FA cluster (Table 3;Figure 3). There were no significant clusters where RDwas lower in OCD patients than in HC subjects. Therewere no statistically significant group differences in MDor AD.Post hoc analyses showed that the mean FA and RD ofclusters that differed between the diagnostic groups didnot differ significantly between OCD patients with andwithout current comorbid disorders.Clinical correlates of diffusion changesAge at onsetTo examine relationships with age at onset, the mean FAand mean RD were extracted from the seven FA clustersand the three RD clusters characterized above. Lower ageat onset was associated with significantly decreased FA inFA cluster 6 (right thalamus: Figure 2), r(15) = 0.691, p =0.002, and with significantly increased RD in RD cluster 2(right body of the CC), r(15) = ? 0.552, p = 0.022. The cor-relation between age at onset and FA in the thalamusremained significant after partialing out age, r(14) = 0.636,p = 0.008, though the correlation between age at onset andRD in the right body of the CC was reduced to a trendlevel after partialing out age, r(14) = ? 0.435, p = 0.093.After partialing out duration of illness, the correlations be-tween both DTI variables and age at onset remained sig-nificant: for the FA cluster, r(14) = 0.556 and p = 0.022; forthe RD cluster, r(14) = ? 0.520 and p = 0.039.Table 2 White matter clusters with reduced fractional anisotropy (FA) in pediatric OCD patients versus healthy controlsCluster label and anatomical localization Voxels MNI coordinates FAx y z OCD HC p1. Bilateral frontal (ATR, UF, IFOF, forceps minor, anterior corona radiata)and corpus callosum (genu, body, splenium)9,022 20 37 6 0.533 ? 0.191 0.573 ? 0.188 0.0262. Right cingulate and basal ganglia: anterior cingulate cortex (UF), anteriorlimb of IC (ATR), putamen (UF), amygdala (ILF), cerebral peduncle (CST),1,454 23 0 −9 0.419 ? 0.157 0.460 ? 0.158 0.035nfeRosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 5 of 10http://www.biolmoodanxietydisord.com/content/4/1/13Symptom severityThe mean FA and mean RD from the identified clusterswere also examined in relation to symptom severity. Therewere no significant correlations with CY-BOCS totalscores, CY-BOCS compulsive symptom scores, or CY-BOCS obsessive symptom scores. CY-BOCS total scoreswere not significantly correlated with age, age at onset, orduration of illness.DiscussionThese findings add to emerging evidence of abnormalintegrity of brain WM tracts in pediatric OCD. This isthe first DTI study to report that children with OCDcompared with healthy youth show regional brain reduc-tions in FA. Over 84% of the significant voxels localizedto a single cluster that encompassed a large expanse ofbilateral frontal cortex and extended into the CC.Smaller clusters of FA reduction were seen in the rightposterior parietal and occipital cortices and the subcallo-sal and orbitofrontal cortices, as well as the thalamusthalamus, and posterior limb of IC (ATR)3. Right posterior cerebral cortex: lateral occipital and angular gyri (SLF)4. Right inferior frontal lobe (subcallosal cortex)5. Right inferior frontal: orbitofrontal cortex6. Right thalamus7. Right caudate, anterior IC (ATR)ATR anterior thalamic radiation, CST corticospinal tract, IC internal capsule, IFOF ilongitudinal fasciculus, UF uncinate fasciculus.and putamen. Youth with OCD also had significantly in-creased RD in areas that overlapped with the largestcluster of FA reduction, including the right anterior cin-gulate cortex and right body of the CC, suggesting defi-cient myelination in these areas. Finally, an earlier onsetof OCD was associated with more pronounced FA re-ductions in the right thalamus and greater RD increasesin the right body of the CC. Overall, our results are inFigure 1 Clusters of significantly lower fractional anisotropy in youthcontrols (skeleton: yellow; cluster 1: light blue; cluster 2: red; cluster 3magenta; cluster 7: light green).line with increasing evidence that brain WM alterationsare present in pediatric OCD and support a possiblemoderating role of age at onset on some aspects of OCDpathophysiology.We found prominent alterations of frontal WM insubjects with OCD, affecting fiber tracts that connectthe frontal lobe to both cortical and subcortical regions.Thus, OCD youth exhibited lower FA in a large clusterof bilateral frontal cortex, including anterior cingulate cor-tex (BA 32) and orbital-frontal cortex (BA 11), areas thatare considered central to OCD pathophysiology [4,7]. Thiscluster overlapped with multiple WM tracts, includingprojection and association fibers that extend to the thal-amus, anterior temporal-limbic regions, and parietaland occipital cortices. Consistent with frontal-subcorticalmodels of OCD, FA reductions were also seen in the puta-men, caudate, and thalamus of OCD youth. In adult DTIstudies, both increased and decreased frontal FA havebeen found in OCD (e.g., [22,24]) and this may relate inpart to illness heterogeneity. One source of variance in132 36 −56 33 0.423 ? 0.100 0.500 ? 0.098 0.04850 8 21 −19 0.296 ? 0.067 0.370 ? 0.107 0.04936 8 37 −22 0.267 ? 0.067 0.323 ? 0.073 0.05014 18 −5 11 0.639 ? 0.041 0.668 ? 0.038 0.0506 22 −4 24 0.430 ? 0.056 0.493 ? 0.081 0.050rior fronto-occipital fasciculus, ILF inferior longitudinal fasciculus, SLF superiorDTI studies of adult OCD appears to be the relative pre-dominance of genetic versus environmental etiologic fac-tors [29]. In their adult sample of monozygotic twinsconcordant and discordant for OCD, den Braber et al.[29] found that some WM tracts (including frontal tracts)show FA alterations that are in the opposite direction insubjects at high genetic risk compared with subjects athigh environmental risk for OCD. Although neither thewith obsessive-compulsive disorder compared with healthy: dark blue; cluster 4: bright green; cluster 5: copper; cluster 6:Rosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 6 of 10http://www.biolmoodanxietydisord.com/content/4/1/13current nor prior DTI studies of pediatric OCD formallyassessed family history, it is possible that our sample wasrelatively high on genetic loading given its particularlyearly age at onset (averaging several years earlier than inprior studies [31,32]) and that this would explain findingsof reduced FA in our sample but not prior pediatric OCDstudies. Future DTI studies could be designed to parse theinfluences of genetic and environmental influences onWM in pediatric OCD.Consistent with a growing body of neurobehavioral evi-dence that posterior association cortices are implicated inFigure 2 Association of age at onset with fractional anisotropy (FA) inTable 3 White matter clusters with increased radial diffusivityCluster label and anatomical localization Voxels MNx1. Right frontal (anterior corona radiata, forceps minor,ATR; overlaps FA cluster 1)406 192. Right body of the corpus callosum (overlaps FA cluster 1) 81 123. Right body of the corpus callosum (close to midline;overlaps FA cluster 1)49 3ATR anterior thalamic radiation.OCD, we found reduced WM integrity in the angular andlateral occipital gyri. A number of functional imagingstudies have found abnormalities of glucose metabolism,cerebral blood flow, and brain activation in the posteriorcortices of adult OCD patients [12]. Neuropsychologicalstudies have shown that adults with OCD are impaired onvisuospatial and decision-making functions that rely onthe integrity of the parietal lobe [46-48]. In addition, amagnetic resonance spectroscopy study found increasedcholine in the parietal lobe WM of OCD, indicative of in-creased phospholipid turnover of myelinated axons in thisyouth with OCD in cluster 6.(RD) in pediatric OCD patients versus healthy controlsI coordinates RDy z OCD HC p32 12 0.000655 ? 0.000085 0.000594 ? 0.000089 0.0424 28 0.000421 ? 0.000085 0.000358 ? 0.000083 0.0494 23 0.000474 ? 0.000084 0.000399 ? 0.000077 0.049it.Rosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 7 of 10http://www.biolmoodanxietydisord.com/content/4/1/13region [49]. Although prior childhood OCD DTI studiesfound evidence of CC alterations suggestive of posteriorassociation cortex involvement, the current study is thefirst to identify a cluster of altered FA in parietal cortex ofpediatric patients. In DTI studies of adult OCD, reducedFA in parietal WM also has been found to distinguish pa-tients from healthy control subjects (e.g., [12,24]). Thus,our results extend those of adult DTI studies by indicatingthat reduced parietal WM integrity is present in pediatricpatients. This finding converges with a report of reducedparietal WM volume in adolescents with OCD comparedwith healthy youth [50]. Neurodevelopmental studieshave shown that increases in FA and other maturationalchanges occur in parietal-occipital WM structure fromthe earliest years of childhood [51], such that disruption ofthis process could relate to early-onset pathophysiology[52]. In adult studies, visuospatial deficits and intrusivevisual imagery are prominent features of OCD and havebeen documented premorbidly in adults prior to their on-set of OCD symptoms [53]. Altogether, this suggests thatabnormal parietal-occipital lobe structure and its behav-ioral manifestations are present in childhood OCD andearly in the course of adult OCD.Findings of diffusion alterations in the CC add togrowing evidence of interhemispheric abnormalities inOCD, evident in both the pediatric and adult literaturesFigure 3 Clusters of significantly higher radial diffusivity in youth w(skeleton: yellow; cluster 1: magenta; cluster 2: red; cluster 3: blue)[18,54]. In this study, OCD compared with healthy youthhad reduced FA in portions of the genu, body, and sple-nium, which implicates fibers that connect bilateral frontal,parietal, and temporal-occipital association cortices [55,56].There was a prominent cluster of FA reduction in themiddle to posterior body of the CC, which connectsbilateral somatosensory cortices and posterior parietal re-gions [57]. We also found decreased FA in the anteriorportion of the genu, where small axons connect bilateralprefrontal cortex and ventral prefrontal cortex to the stri-atum. In an earlier study of pediatric OCD, Zarei et al.[31] had found increased FA in somewhat different CCareas corresponding to the posterior genu and anter-ior body of the CC, where larger axons connect primarymotor cortices. Thus, it is possible that directional coherenceof fiber tracts is differentially altered across different sec-tions of the genu and body of the CC in childhood OCD,indicating variable pathology across topographically dis-tinct association cortices.Our finding of decreased splenium FA conflicts withtwo prior reports on youth with OCD [16,31]. Both in-vestigations found higher splenium FA, which correlatedwith significantly greater OCD symptom severity [16,31].Both of these prior studies had a lower proportion of med-icated OCD patients (61%, 52%) than the current study(82%). Moreover, significantly elevated splenium FA wasseen only among the subgroup of unmedicated patients inone of those studies [16]. Thus, it may be that our findingof lower splenium FA reflects the effects of medicationtreatment. Our study design does not allow us to test thisquestion, but there is some prior evidence that treatment-na?ve OCD patients, including pediatric patients, havehigher FA, greater WM density, and larger size of the CC[57]. Moreover, in a longitudinal study of adults withOCD, Yoo et al. [25] found that drug-na?ve patients hadmultiple areas of increased FA (including in the posteriorCC) and that these normalized after a course of clinicallyeffective citalopram treatment. Another possible sourceof conflicting findings across DTI studies is heterogeneityof OCD clinical features (e.g., our sample included a mi-nority of ? washers? relative to ? checkers? ). The adult OCDh obsessive-compulsive disorder compared with healthy controlsliterature has begun to explore neural correlates of symp-tom dimensions in OCD [58]. Similar studies could be de-signed in pediatric OCD by selecting more homogeneouspatient samples.Alterations in diffusion anisotropy (FA) can result fromchanges in either RD (perpendicular) and/or AD (parallel),and these subcomponents are differentially modulated bymyelin and axonal degeneration mechanisms, respectively[59]. In this study, we found concomitant decreases in FAand increases in RD in the right frontal cortex and rightbody of the CC, a pattern thought to reflect deficient mye-lination [59-62]. Abnormal myelination also has beenimplicated in OCD by other lines of research, includingmagnetic resonance spectroscopy findings of increasedlevels of cell membrane breakdown products in OCDRosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 8 of 10http://www.biolmoodanxietydisord.com/content/4/1/13youth [63,64], and genetic evidence of an association be-tween OCD and a gene (OLIG2) involved in the develop-ment of oligodendrocytes [65]. Similar to our study,Jayarajan and colleagues [32] also had found significantlyincreased RD in a DTI in children with OCD comparedwith controls, although FA did not differ significantly be-tween groups. Because increased RD was accompanied byincreased AD in their patient sample, Jayarajan et al. [32]interpreted this as indicative of hyperconnected yet in-sufficiently myelinated WM tracts in affected regions.In contrast, Gruner et al. [16] found decreased RD inthe context of significantly increased FA in four WMregions of pediatric OCD compared with control subjects,pointing to excessive myelination of certain axon fibers.Finally, Silk et al. [33] found significantly decreased AD inthe genu and splenium of the CC of OCD youth, whichcould indicate less coherently organized callosal axons; FAwas not significantly different between the groups in theCC or any other WM tract of that study. Thus, in the rela-tively small literature to date, there are different patternsof FA/RD/AD findings across pediatric OCD DTI studies.This could indicate involvement of multiple possible com-binations of WM microstructure alterations in pediatricOCD wherein both myelin and axonal changes may bepresent in the context of either reduced or increased co-herence of fiber tracts. The pattern of abnormalities mayvary across brain regions, due to age-related maturationalprocesses [16,31] and/or as a function of clinical phenom-enology. These questions will need to be disentangled byconducting additional studies in this relatively young areaof study.Our findings suggest that age at onset may be an influ-ential moderating factor on some of the WM changes inpediatric OCD. On average, our patients had an earlieronset of illness (average 8 years) than those in the twoearlier pediatric OCD studies that reported on age at onset(11 years [31] and 13 years [32] on average). Moreover,within our patient sample, earlier onset was associatedwith significantly lower FA in the right thalamus and sig-nificantly higher RD in the right CC. The former associ-ation remained significant even after controlling for age,suggesting that earlier onset of OCD disease-related pro-cesses is associated with reduced integrity of WM in thethalamus. Involvement of the thalamus in early-onsetOCD is consistent with the conclusions of a literature re-view that prominent thalamic abnormalities may be acomponent of a slightly different neuropathological sub-strate of childhood-onset versus adult-onset OCD [54].Studying pediatric patients near the onset of their ill-ness helps identify neurobiological changes that may bemore primary than those arising later on in the courseof illness, although developmental and disease effectsmay still be influential. Brain alterations noted duringchildhood and adolescence may change in their naturedue to ongoing maturation of both gray matter and WM,which may contribute to variable findings across studies.In addition, compulsively engaging in a particular type ofbehavior or cognitive process can change brain structure[4,66,67]. Thus, even in pediatric OCD, anatomical braindifferences may reflect a consequence rather than a pre-cursor of the disorder. In the only study of neuropsycho-logical correlates of DTI measures in pediatric OCD, thepattern of results found by Gruner et al. [16] suggestedthat certain FA increases might reflect compensatory in-creases in WM coherence to mitigate neuropsychologicaldeficits. This highlights the usefulness of studying patientswith OCD as close to symptom onset as possible, whensuch epiphenomenal changes may be less prominent.Our findings should be interpreted in the context of thestudy? s limitations. This was a cross-sectional investiga-tion, and our results are therefore correlational in nature.We cannot rule out that these findings were affected bycomorbidity within our OCD sample, particularly depres-sion and other anxiety disorders present in a third of thepatients. However, in post hoc analyses, severity of depres-sion and anxiety symptoms was not associated with FA orRD in any of the significant clusters. Moreover, only asmall percentage of the sample had any particular comor-bid condition, making it implausible that the group find-ings were driven by a particular comorbidity. Similarly, wecannot exclude the possibility of medication effects, sincemost of our patients were medicated; although noneof the previous pediatric OCD studies found any indi-cation that DTI parameters were affected by medicationuse [16,31,32], it is possible that this reflected limited powerto detect such effects. Finally, this and other pediatric OCDstudies to date have not had sufficient power to examinethe relationship of DTI WM measures with OCD symptomprofile, which have been found to differentially relate toregional brain abnormalities in adult OCD [68].ConclusionsOur findings of significantly lower FA and higher RD inchildhood OCD are consistent with compromised WMintegrity and reduced myelination, particularly involvingthe CC and fiber tracts that connect the frontal lobes towidespread cortical and subcortical targets. Our findingsalso suggest that age at onset may be a moderator ofsome of the WM changes in children with OCD. DTIresearch in childhood OCD is still in its infancy, and fu-ture studies should incorporate examination of how gen-etic and environmental risk factors, as well as aspects ofillness phenomenology, may help parse divergent find-ings across studies.AbbreviationsAD: Axial diffusivity; CC: Corpus callosum; CDI: Child Depression Inventory;CY-BOCS: Children ? s Yale-Brown Obsessive-Compulsive Scale; DTI: Diffusiontensor imaging; FA: Fractional anisotropy; HC: Healthy control; KSADS: KiddieRosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 9 of 10http://www.biolmoodanxietydisord.com/content/4/1/13Schedule for Affective Disorders and Schizophrenia; MD: Mean diffusivity;RD: Radial diffusivity; OCD: Obsessive-compulsive disorder; TBSS: Tract-basedspatial statistics; TFCE: Threshold-Free Cluster Enhancement; WM: Whitematter; YGTSS: Yale Global Tic Severity Scale.Competing interestsThe authors declare that they have no competing interests.Authors ? contributionsIMR was involved in data collection and analysis and wrote the first draft ofthe manuscript. EAO analyzed the imaging data and contributed to writingof the methods and results. JCB, SES, and SLR designed the study and wereinvolved in subject recruitment and data interpretation. GP and NM contributedto the processing, analysis, and interpretation of the imaging data. WDSK wasinvolved in data collection. SW and MAJ assisted with subject recruitment.All authors contributed to and have approved the final manuscript.AcknowledgementsThis research was supported by an anonymous donor. We would like toacknowledge the contributions of Jennifer Ragan, Anne Chosak, AdrianeAlpern, Elizabeth Flamm, Sarah Glaser, and Elizabeth Sadock for theirassistance in conducting assessments and the McLean Hospital ImagingCenter MRI technologists for their assistance with scanning.Author details1Center for Depression, Anxiety and Stress Research, McLean Hospital, 115Mill Street, mailstop 334, Belmont, MA 02478, USA. 2Department ofPsychiatry, Harvard Medical School, Boston, MA, USA. 3Department ofPsychology, University of Miami, 5665 Ponce de Leon Blvd, Flipse Building,Coral Gables, Miami, FL 33146, USA. 4British Columbia Mental Health andAddictions Research Institute, University of British Columbia, Vancouver, BC,Canada. 5Center for Morphometric Analysis, Massachusetts General Hospital,Bldg 149, 13th Street, Charlestown, MA 02129, USA. 6Department ofNeurology, Harvard Medical School, Boston, MA, USA. 7Department ofRadiology, Harvard Medical School, Boston, MA, USA. 8Department ofPsychiatry, Massachusetts General Hospital, Simches Research Building, 185Cambridge Street, Suite 2282, Boston, MA 02114, USA. 9UBC PsychiatryA3-118, 938 West 28th Ave, Vancouver, BC V5Z 4H4, Canada. 10Departmentof Psychiatry, University of Arizona, Tucson, AZ, USA.Received: 2 July 2014 Accepted: 14 November 2014References1. American Psychiatric Association: Diagnostic and Statistical Manual of MentalDisorders, Fourth Edition (DSM-IV). Washington, D.C.: American PsychiatricAssociation; 1994.2. Geller DA: Obsessive-compulsive and spectrum disorders in children andadolescents. Psychiatr Clin North Am 2006, 29:353 ? 370.3. Stewart SE, Geller DA, Jenike M, Pauls D, Shaw D, Mullin B, Faraone SV:Long-term outcome of pediatric obsessive-compulsive disorder:a meta-analysis and qualitative review of the literature. Acta PsychiatrScand 2004, 110:4? 13.4. Maia TV, Cooney RE, Peterson BS: The neural bases of obsessive-compulsivedisorder in children and adults. Dev Psychopathol 2008, 20:1251? 1283.5. Huyser C, Veltman DJ, de Haan E, Boer F: Paediatric obsessive-compulsivedisorder, a neurodevelopmental disorder? Evidence from neuroimaging.Neurosci Biobehav Rev 2009, 33:818? 830.6. Rosenberg DR, Keshavan MS: A.E. Bennett Research Award. Toward aneurodevelopmental model of obsessive ? compulsive disorder.Biol Psychiatry 1998, 43:623 ? 640.7. Graybiel AM, Rauch SL: Toward a neurobiology of obsessive-compulsivedisorder. Neuron 2000, 28:343? 347.8. Saxena S, Brody AL, Schwartz JM, Baxter LR: Neuroimaging andfrontal-subcortical circuitry in obsessive-compulsive disorder.Br J Psychiatry Suppl 1998, 35:26 ? 37.9. Fineberg NA, Potenza MN, Chamberlain SR, Berlin HA, Menzies L, Bechara A,Sahakian BJ, Robbins TW, Bullmore ET, Hollander E: Probing compulsiveand impulsive behaviors, from animal models to endophenotypes:a narrative review. Neuropsychopharmacology 2010, 35:591 ? 604.10. Radua J, van den Heuvel OA, Surguladze S, Mataix-Cols D: Meta-analyticalcomparison of voxel-based morphometry studies in obsessive-compulsivedisorder vs other anxiety disorders. Arch Gen Psychiatry 2010, 67:701 ? 711.11. Rotge JY, Guehl D, Dilharreguy B, Tignol J, Bioulac B, Allard M, Burbaud P,Aouizerate B: Meta-analysis of brain volume changes in obsessive-compulsivedisorder. Biol Psychiatry 2009, 65:75? 83.12. Menzies L, Chamberlain SR, Laird AR, Thelen SM, Sahakian BJ, Bullmore ET:Integrating evidence from neuroimaging and neuropsychologicalstudies of obsessive-compulsive disorder: the orbitofronto-striatal modelrevisited. Neurosci Biobehav Rev 2008, 32:525 ? 549.13. Abramovitch A, Dar R, Schweiger A, Hermesh H: Neuropsychologicalimpairments and their association with obsessive-compulsive symptomseverity in obsessive-compulsive disorder. Arch Clin Neuropsychol 2011,26:364? 376.14. Bannon S, Gonsalvez CJ, Croft RJ, Boyce PM: Response inhibition deficits inobsessive-compulsive disorder. Psychiatry Res 2002, 110:165 ? 174.15. Chamberlain SR, Blackwell AD, Fineberg NA, Robbins TW, Sahakian BJ:The neuropsychology of obsessive compulsive disorder: the importanceof failures in cognitive and behavioural inhibition as candidateendophenotypic markers. Neurosci Biobehav Rev 2005, 29:399? 419.16. Gruner P, Vo A, Ikuta T, Mahon K, Peters BD, Malhotra AK, Ulug AM, Szeszko PR:White matter abnormalities in pediatric obsessive-compulsive disorder.Neuropsychopharmacology 2012, 37:2730? 2739.17. Penades R, Catalan R, Rubia K, Andres S, Salamero M, Gasto C: Impairedresponse inhibition in obsessive compulsive disorder. Eur Psychiatry 2007,22:404? 410.18. Fontenelle LF, Harrison BJ, Yucel M, Pujol J, Fujiwara H, Pantelis C: Is thereevidence of brain white-matter abnormalities in obsessive-compulsivedisorder?: A narrative review. Top Magn Reson Imaging 2009, 20:291? 298.19. Olson EA, Collins PF, Hooper CJ, Muetzel R, Lim KO, Luciana M:White matterintegrity predicts delay discounting behavior in 9- to 23-year-olds: a diffusiontensor imaging study. J Cogn Neurosci 2009, 21:1406? 1421.20. Beaulieu C: The basis of anisotropic water diffusion in the nervoussystem - a technical review. NMR Biomed 2002, 15:435 ? 455.21. Harsan LA, Poulet P, Guignard B, Steibel J, Parizel N, de Sousa PL, Boehm N,Grucker D, Ghandour MS: Brain dysmyelination and recovery assessmentby noninvasive in vivo diffusion tensor magnetic resonance imaging.J Neurosci Res 2006, 83:392 ? 402.22. Cannistraro PA, Makris N, Howard JD, Wedig MM, Hodge SM, Wilhelm S,Kennedy DN, Rauch SL: A diffusion tensor imaging study of white matterin obsessive-compulsive disorder. Depress Anxiety 2007, 24:440? 446.23. Garibotto V, Scifo P, Gorini A, Alonso CR, Brambati S, Bellodi L, Perani D:Disorganization of anatomical connectivity in obsessive compulsivedisorder: a multi-parameter diffusion tensor imaging study in asubpopulation of patients. Neurobiol Dis 2010, 37:468? 476.24. Szeszko PR, Ardekani BA, Ashtari M, Malhotra AK, Robinson DG, Bilder RM,Lim KO: White matter abnormalities in obsessive-compulsive disorder:a diffusion tensor imaging study. Arch Gen Psychiatry 2005, 62:782 ? 790.25. Yoo SY, Jang JH, Shin YW, Kim DJ, Park HJ, Moon WJ, Chung EC, Lee JM,Kim IY, Kim SI, Kwon JS: White matter abnormalities in drug-naivepatients with obsessive-compulsive disorder: a diffusion tensor studybefore and after citalopram treatment. Acta Psychiatr Scand 2007,116:211 ? 219.26. Nakamae T, Narumoto J, Sakai Y, Nishida S, Yamada K, Nishimura T,Fukui K: Diffusion tensor imaging and tract-based spatial statistics inobsessive-compulsive disorder. J Psychiatr Res 2011, 45:687 ? 690.27. Saito Y, Nobuhara K, Okugawa G, Takase K, Sugimoto T, Horiuchi M, Ueno C,Maehara M, Omura N, Kurokawa H, Ikeda K, Tanigawa N, Sawada S,Kinoshita T: Corpus callosum in patients with obsessive-compulsivedisorder: diffusion-tensor imaging study. Radiology 2008, 246:536 ? 542.28. Li F, Huang X, Yang Y, Li B, Wu Q, Zhang T, Lui S, Kemp GJ, Gong Q:Microstructural brain abnormalities in patients with obsessive-compulsivedisorder: diffusion-tensor MR imaging study at 3.0 T. Radiology 2011,260:216? 223.29. den Braber A, van ? t D, Boomsma DI, Cath DC, Veltman DJ, Thompson PM,de Geus EJ: White matter differences in monozygotic twins discordant orconcordant for obsessive-compulsive symptoms: a combined diffusiontensor imaging/voxel-based morphometry study. Biol Psychiatry 2011,70:969? 977.30. Menzies L, Williams GB, Chamberlain SR, Ooi C, Fineberg N, Suckling J,Sahakian BJ, Robbins TW, Bullmore ET: White matter abnormalities in52. Barnea-Goraly N, Menon V, Eckert M, Tamm L, Bammer R, Karchemskiy A,Dant CC, Reiss AL: White matter development during childhood andadolescence: a cross-sectional diffusion tensor imaging study.Rosso et al. Biology of Mood & Anxiety Disorders 2014, 4:13 Page 10 of 10http://www.biolmoodanxietydisord.com/content/4/1/13patients with obsessive-compulsive disorder and their first-degreerelatives. Am J Psychiatry 2008, 165:1308 ? 1315.31. Zarei M, Mataix-Cols D, Heyman I, Hough M, Doherty J, Burge L, Winmill L,Nijhawan S, Matthews PM, James A: Changes in gray matter volume andwhite matter microstructure in adolescents with obsessive-compulsivedisorder. Biol Psychiatry 2011, 70:1083? 1090.32. Jayarajan RN, Venkatasubramanian G, Viswanath B, Janardhan Reddy YC,Srinath S, Vasudev MK, Chandrashekar CR: White matter abnormalities inchildren and adolescents with obsessive-compulsive disorder: a diffusiontensor imaging study. Depress Anxiety 2012, 29:780? 788.33. Silk T, Chen J, Seal M, Vance A: White matter abnormalities in pediatricobsessive-compulsive disorder. Psychiatry Res 2013, 213:154 ? 160.34. Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, Williamson D,Ryan N: Schedule for affective disorders and schizophrenia for school-Agechildren-present and lifetime version (K-SADS-PL): initial reliability andvalidity data. J Am Acad Child Adolesc Psychiatry 1997, 36:980? 988.35. Goodman WK, Price LH, Rasmussen SA, Mazure C, Fleischmann RL, Hill CL,Heninger GR, Charney DS: The Yale-Brown Obsessive Compulsive Scale. I.Development, use, and reliability. Arch Gen Psychiatry 1989, 46:1006 ? 1011.36. Kovacs M: Children ? s Depression Inventory Manual. North Tonawanda:Multi-Health Systems; 1992.37. Leckman JF, Riddle MA, Hardin MT, Ort SI, Swartz KL, Stevenson J, Cohen DJ:The Yale Global Tic Severity Scale: initial testing of a clinician-rated scaleof tic severity. J Am Acad Child Adolesc Psychiatry 1989, 28:566 ? 573.38. Stewart SE, Rosario MC, Baer L, Carter AS, Brown TA, Scharf JM, Illmann C,Leckman JF, Sukhodolsky D, Katsovich L, Rasmussen S, Goodman W,Delorme R, Leboyer M, Chabane N, Jenike MA, Geller DA, Pauls DL:Four-factor structure of obsessive-compulsive disorder symptoms inchildren, adolescents, and adults. J Am Acad Child Adolesc Psychiatry2008, 47:763 ? 772.39. Andersson JLR, Jenkinson M, Smith S: Non-linear optimisation. [www.fmrib.ox.ac.uk/analysis/techrep]40. Andersson JLR, Jenkinson M, Smith S: Non-linear registration, aka spatialnormalisation. [www.fmrib.ox.ac.uk/analysis/techrep]41. Smith SM: Fast robust automated brain extraction. Hum Brain Mapp 2002,17:143? 155.42. Gallichan D, Scholz J, Bartsch A, Behrens TE, Robson MD, Miller KL:Addressing a systematic vibration artifact in diffusion-weighted MRI.Hum Brain Mapp 2010, 31:193? 202.43. Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE,Watkins KE, Ciccarelli O, Cader MZ, Matthews PM, Behrens TE: Tract-basedspatial statistics: voxelwise analysis of multi-subject diffusion data.Neuroimage 2006, 31:1487? 1505.44. Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE,Johansen-Berg H, Bannister PR, De Luca M, Drobnjak I, Flitney DE, Niazy RK,Saunders J, Vickers J, Zhang Y, De Stefano N, Brady JM, Matthews PM:Advances in functional and structural MR image analysis and implementationas FSL. Neuroimage 2004, 23(Suppl 1):S208 ? S219.45. Nichols TE, Holmes AP: Nonparametric permutation tests for functionalneuroimaging: a primer with examples. Hum Brain Mapp 2002, 15:1? 25.46. Chamberlain SR, Fineberg NA, Blackwell AD, Clark L, Robbins TW, Sahakian BJ:A neuropsychological comparison of obsessive-compulsive disorder andtrichotillomania. Neuropsychologia 2007, 45:654? 662.47. Menzies L, Achard S, Chamberlain SR, Fineberg N, Chen CH, del Campo N,Sahakian BJ, Robbins TW, Bullmore E: Neurocognitive endophenotypes ofobsessive-compulsive disorder. Brain 2007, 130:3223? 3236.48. Okasha A, Rafaat M, Mahallawy N, El Nahas G, El Dawla AS, Sayed M, El Kholi S:Cognitive dysfunction in obsessive-compulsive disorder. Acta PsychiatrScand 2000, 101:281? 285.49. Kitamura H, Shioiri T, Kimura T, Ohkubo M, Nakada T, Someya T: Parietalwhite matter abnormalities in obsessive-compulsive disorder: a magneticresonance spectroscopy study at 3-Tesla. Acta Psychiatr Scand 2006,114:101? 108.50. Lazaro L, Bargallo N, Castro-Fornieles J, Falcon C, Andres S, Calvo R, Junque C:Brain changes in children and adolescents with obsessive-compulsivedisorder before and after treatment: a voxel-based morphometric MRIstudy. Psychiatry Res 2009, 172:140? 146.51. Giedd JN, Blumenthal J, Jeffries NO, Castellanos FX, Liu H, Zijdenbos A,Paus T, Evans AC, Rapoport JL: Brain development during childhood andadolescence: a longitudinal MRI study. Nat Neurosci 1999, 2:861 ? 863.Cereb Cortex 2005, 15:1848 ? 1854.53. Grisham JR, Anderson TM, Poulton R, Moffitt TE, Andrews G: Childhoodneuropsychological deficits associated with adult obsessive-compulsivedisorder. Br J Psychiatry 2009, 195:138 ? 141.54. MacMaster FP, O ?Neill J, Rosenberg DR: Brain imaging in pediatricobsessive-compulsive disorder. J Am Acad Child Adolesc Psychiatry 2008,47:1262? 1272.55. Giedd JN, Rumsey JM, Castellanos FX, Rajapakse JC, Kaysen D, Vaituzis AC,Vauss YC, Hamburger SD, Rapoport JL: A quantitative MRI study of thecorpus callosum in children and adolescents. Brain Res Dev Brain Res1996, 91:274 ? 280.56. Mac Master FP, Keshavan MS, Dick EL, Rosenberg DR: Corpus callosal signalintensity in treatment-naive pediatric obsessive compulsive disorders.Prog Neuropsychopharmacol Biol Psychiatry 1999, 23:601 ? 612.57. Rosenberg DR, Keshavan MS, Dick EL, Bagwell WW, MacMaster FP, Birmaher B:Corpus callosal morphology in treatment-naive pediatric obsessivecompulsive disorder. Prog Neuropsychopharmacol Biol Psychiatry 1997,21:1269? 1283.58. Mataix-Cols D, Cullen S, Lange K, Zelaya F, Andrew C, Amaro E, Brammer MJ,Williams SC, Speckens A, Phillips ML: Neural correlates of anxiety associatedwith obsessive-compulsive symptom dimensions in normal volunteers.Biol Psychiatry 2003, 53:482? 493.59. Song SK, Sun SW, Ramsbottom MJ, Chang C, Russell J, Cross AH:Dysmyelination revealed through MRI as increased radial (butunchanged axial) diffusion of water. Neuroimage 2002, 17:1429 ? 1436.60. Basser PJ: Inferring microstructural features and the physiological state oftissues from diffusion-weighted images. NMR Biomed 1995, 8:333 ? 344.61. Song SK, Sun SW, Ju WK, Lin SJ, Cross AH, Neufeld AH: Diffusion tensorimaging detects and differentiates axon and myelin degeneration inmouse optic nerve after retinal ischemia. Neuroimage 2003, 20:1714 ? 1722.62. Song SK, Yoshino J, Le TQ, Lin SJ, Sun SW, Cross AH, Armstrong RC:Demyelination increases radial diffusivity in corpus callosum of mousebrain. Neuroimage 2005, 26:132 ? 140.63. Rosenberg DR, MacMillan SN, Moore GJ: Brain anatomy and chemistrymay predict treatment response in paediatric obsessive ? compulsivedisorder. Int J Neuropsychopharmacol 2001, 4:179 ? 190.64. Smith EA, Russell A, Lorch E, Banerjee SP, Rose M, Ivey J, Bhandari R, MooreGJ, Rosenberg DR: Increased medial thalamic choline found in pediatricpatients with obsessive-compulsive disorder versus major depression orhealthy control subjects: a magnetic resonance spectroscopy study.Biol Psychiatry 2003, 54:1399 ? 1405.65. Stewart SE, Platko J, Fagerness J, Birns J, Jenike E, Smoller JW, Perlis R,Leboyer M, Delorme R, Chabane N, Rauch SL, Jenike MA, Pauls DL: Agenetic family-based association study of OLIG2 in obsessive-compulsivedisorder. Arch Gen Psychiatry 2007, 64:209? 214.66. Lazar SW, Kerr CE, Wasserman RH, Gray JR, Greve DN, Treadway MT,McGarvey M, Quinn BT, Dusek JA, Benson H, Rauch SL, Moore CI, Fischl B:Meditation experience is associated with increased cortical thickness.Neuroreport 2005, 16:1893 ? 1897.67. Schlaug G: The brain of musicians. A model for functional and structuraladaptation. Ann N Y Acad Sci 2001, 930:281 ? 299.68. van den Heuvel OA, Remijnse PL, Mataix-Cols D, Vrenken H, Groenewegen HJ,Uylings HB, van Balkom AJ, Veltman DJ: The major symptom dimensions ofobsessive-compulsive disorder are mediated by partially distinct neuralsystems. Brain 2009, 132:853? 868.doi:10.1186/s13587-014-0013-6Cite this article as: Rosso et al.: Brain white matter integrity andassociation with age at onset in pediatric obsessive-compulsive disorder.Biology of Mood & Anxiety Disorders 2014 4:13.

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