Original Article

Structural brain and neuropsychometricchanges associated with pediatric bipolardisorder with psychosis

Pediatric bipolar disorder (PBD) is a severe andpersistent, cyclic mood disorder with an estimatedprevalence of 1% (1). The disorder is thought toarise from dysfunction in neural networks subserv-ing emotional processing and regulation and toinvolve frontolimbic, frontostriatal, and fronto-

temporal circuitries. The pathophysiology of PBDcan in part be elucidated by studying the brainchanges in white matter (WM) and gray matter(GM) and associated cognitive function in anearly-onset sample. The developmental patternof children who go on to develop PBD shows adifferential pattern of cortical GM gain in the lefttemporal cortex and GM loss in the right temporaland subgenual cingulate cortices (2). In PBD,reduced GM density has been found in thedorsolateral prefrontal cortex (DLPFC) (3),

James A, Hough M, James S, Burge L, Winmill L, Nijhawan S,Matthews PM, Zarei M. Structural brain and neuropsychometricchanges associated with pediatric bipolar disorder with psychosis.Bipolar Disord 2011: 13: 16–27. ª 2011 The Authors.Journal compilation ª 2011 John Wiley & Sons A ⁄S.

Objectives: To identify neuropsychological and structural brainchanges using a combination of high-resolution structural and diffusiontensor imaging in pediatric bipolar disorder (PBD) with psychosis(presence of delusions and or hallucinations).

Methods: We recruited 15 patients and 20 euthymic age- and gender-matched healthy controls. All subjects underwent high-resolutionstructural and diffusion tensor imaging. Voxel-based morphometry(VBM), tract-based spatial statistics (TBSS), and probabilistictractography were used to analyse magnetic resonance imaging data.

Results: The PBD subjects had normal overall intelligence with specificimpairments in working memory, executive function, language function,and verbal memory. Reduced gray matter (GM) density was found in theleft orbitofrontal cortex, left pars triangularis, right premotor cortex,occipital cortex, right occipital fusiform gyrus, and right crus of thecerebellum. TBSS analysis showed reduced fractional anisotropy (FA) inthe anterior corpus callosum. Probabilistic tractography from this clustershowed that this region of the corpus callosum is connected with theprefrontal cortices, including those regions whose density is decreased inPBD. In addition, FA change was correlated with verbal memory andworking memory, while more widespread reductions in GM densitycorrelated with working memory, executive function, language function,and verbal memory.

Conclusions: The findings suggest widespread cortical changes as wellas specific involvement of interhemispheric prefrontal tracts in PBD,which may reflect delayed myelination in these tracts.

Anthony Jamesa, Morgan Houghb,Susan Jamesa, Linda Burgea,Louise Winmilla, Sunita Nijhawana,Paul M Matthewsc and MojtabaZareib,c

aHighfield Family and Adolescent Unit, Warneford

Hospital, bOxford Centre for Functional MRI of the

Brain (FMRIB), John Radcliffe Hospital, Oxford,cGSK Clinical Imaging Centre, Imperial College

London, London, UK

doi: 10.1111/j.1399-5618.2011.00891.x

Key words: bipolar disorder – DTI – MRI –

pediatric – VBM

Received 18 May 2010, revised and accepted

for publication 3 December 2010

Corresponding author:

Anthony James

Highfield Family and Adolescent Unit

Warneford Hospital

Oxford, OX3 7JX, UK

Fax: +44 1865 37882

E-mail: anthony.james@psych.ox.ac.uk

The authors of this paper do not have any commercial associations

that might pose a conflict of interest in connection with this manu-

script.

Bipolar Disorders 2011: 13: 16–27 ª 2011 John Wiley and Sons A/S

BIPOLAR DISORDERS

16

temporal lobe (4, 5), cingulate gyrus (5, 6), orbito-frontal cortex (3, 5), and left parietal lobe (4). Allthese areas are thought to be involved in emotionalprocessing, although there are reports of a lack ofa reduction of subgenual volume (7). These GMchanges in PBD need to be understood in the lightof highly dynamic brain development in childhoodand adolescence. A prepubertal increase in GM isfollowed by postpubertal loss (8), leading to aninverted U-shaped trajectory of growth in frontal,parietal, and temporal lobes. This is thought to bedue to a combination of increased synaptic pruningduring adolescence (9) and continued intracorticalmyelination (10). For WM, there is a linearincrease in volume (11), which reflects not onlyprogressive myelination but also an increase inaxon diameter, the latter being sexually dimorphic,with a greater increase in males (12, 13).Loss of WM connectivity, involving prefrontal

and frontal regions and projection, associative, andcommissural fibres, appears to be a central featureof bipolar disorder (BD) (14, 15). According tosome, there is less consistent evidence implicatingthe subcortical and nonfrontal lobes of the brain(15), while others point to the involvement of tractsthat connect prefrontal regions and subcorticalGM structures known to be involved in emotionalprocessing (16). The latter position is confirmedby diffusion tensor imaging studies in PBD whichhave shown widespread reduced fractional aniso-tropy (FA) in the major tracts, such as the superiorfrontal lobes (17, 18), right orbitofrontal lobe (19),anterior corona radiata (20), bilateral superiorlongitudinal fasciculus (18), fornix (21), cingulate(18), left midposterior cingulate gyrus (21), para-cingulate (18), and bilateral parietal and occipitalcorona radiata (21). In the corpus callosum, themajor interhemispheric WM tract, decreased FAhas been reported (18, 21), as well as increasedapparent diffusion coefficient (ADC) and decreasedfibre coherence in the splenium of the corpuscallosum (20).Cognitive deficits are also increasingly recog-

nized as a core feature of BD (22). Meta-analysis ofPBD (23) shows widespread neuropsychologicaldeficits in full-scale IQ (FSIQ) and in the domainsof verbal memory (24), attention, executive func-tioning, working memory, visual memory, visualperceptual skills, verbal fluency (23, 25), socialcognition, and response flexibility (26). Cognitivedeficits, particularly those that involve a memorycomponent, implicate the ventral and dorsolateralprefrontal cortex as loci of pathology in PBD (27).The normal relationship of brain structure tointelligence is complex. An initial increase in thecortical thickness is seen in individuals with supe-

rior intelligence, with peak cortical thicknessreached in frontal regions at 11 years, whereasthere is a decline in cortical thickness in those withaverage intelligence (28). Verbal and performanceabilities are positively related to FA (29), and inindividuals with higher verbal abilities, WM devel-opment is accelerated in late childhood, with asubsequent earlier developmental plateau as com-pared to those with average abilities (29).It is clear that there is a complex interaction

between disease and the normal brain maturationalchanges of adolescence (11). To more clearlyunderstand the disease process, we examined GMand WM changes and associated cognitive func-tion in a sample of adolescents with PBD andpsychosis relative to age-matched controls.Although not typical of all PBD, psychosis pro-vides a marker of severity of PBD and character-izes a defined, potentially homogenous group ofthose with BD.

Methods and subjects

This study was undertaken in accordance with theguidance of the Oxford Psychiatric Research EthicsCommittee. Written consent was obtained from allparticipants and parents if subjects were under theage of 16.

Subjects

All consecutive admissions with BD with psychosisfrom the Oxford regional unit and surroundingunits were approached (Table 1). Subjects werediagnosed according to DSM-IV-TR criteria usingthe Kiddie Schedule for Affective Disorders andSchizophrenia (K-SADS-PL) (30), a semistruc-tured interview which reliably diagnoses affectivepsychotic disorders. In addition, the subjects wereadministered the Positive and Negative SyndromeScale (PANSS) (31); depressive symptoms weremeasured with the Beck Depression Inventory(BDI) (32), a 21-item rating scale; and manicsymptoms were measured with the Young ManiaRating Scale (YMRS) (33), a reliable and validated11-item clinician-administered scale (Table 1). Atotal of 15 subjects with adolescent-onset BD withpsychosis from a defined geographic area and 20healthy adolescent controls were identified. All BDsubjects were euthymic at the time of examination.Subjects were clinically reviewed after the initialdiagnostic screening for a period of at least sixmonths [mean (SD): 10 (1.5) months]; no subjectchanged diagnostic status. The control subjectswere recruited from the community through theirgeneral practitioners and were interviewed using

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the K-SADS-PL to rule out any history of emo-tional, behavioural, or medical problems. Hand-edness was assessed with the EdinburghHandedness Questionnaire (34). All participantsattended normal schools. Exclusion criteria, as permedical and general practitioner notes, interview,and psychometric evaluation, included moderatemental impairment (IQ < 70), a history of perva-sive developmental disorder, significant headinjury, neurological disorder, major medical disor-der, or a history of illegal drug use (use of anypsychoactive substance at any time, apart frompossible one-time experimentation) (Table 1).

Image acquisition

All 35 participants underwent the same imagingprotocol with whole-brain T1-weighted and diffu-sion-weighted scanning using a 1.5 T Sonatamagnetic resonance imager (Siemens, Erlangen,Germany) with a standard quadrature head coiland maximum 40 mT ⁄m gradient capability. The3D T1-weighted FLASH sequence was performedwith the following parameters: coronal orientation,matrix = 256 · 256, 208 slices, 1 · 1 mm2 in-planeresolution, slice thickness = 1 mm, echo time(TE) ⁄ repetition time (TR) = 5.6 ⁄12 msec, flipangle a = 19�.

Diffusion-weighted images were obtained usingecho-planar imaging (SE-EPI) (TE ⁄TR = 89 ⁄8500 msec, 60 axial slices, bandwidth = 1860Hz ⁄vx, voxel size = 2.5 · 2.5 · 2.5 mm3), with 60isotropically distributed orientations for the diffu-sion-sensitising gradients at a b-value of 1000sec ⁄mm2 and five b = 0 images. To increasesignal-to-noise ratio, scanning was repeated threetimes; the first two scans were registered into thethird scan, and the average of three was usedfor analysis.

Cognitive assessment

A comprehensive neuropsychological assessmentbattery was completed with the study subjects by atrained clinical neuropsychologist or a supervisedassistant. On average, the assessment took between1.5 and 2 hours to complete; when necessary, theevaluation was completed over more than onesession. To reduce the problems of multiple com-parisons, neuropsychological test variables weregrouped into six cognitive domains. In some cases,two age-appropriate versions of the same measurehad been utilised dependent on the participant�sage, and consequently, equivalent standard scoreswere used instead of raw scores. This was the casefor the psychomotor speed ⁄dexterity, working

Table 1. Demographic data of adolescent-onset pediatric bipolar disorder (PBD) with psychosis versus controls

PBD (n = 15) Controls (n = 20) Statistics (Control > PBD) p-value

Gender, M ⁄ F 8 ⁄ 7 8 ⁄ 12 v2, 0.79 0.64Age 15.0 (2.0) 15.3 (1.0) t33, 0.56 0.57Handedness, R ⁄ L 13 ⁄ 2 19 ⁄ 1 v2, 1.51 0.56Age at onset of symptoms, years 14.0 (2.0)Disease duration, years 0.9 (0.5)PANSS: positive scores 19.3 (3.9)PANSS: negative scores 10.1 (2.7)Chlorpromazine equivalents 236.6 (127.5)Full Scale IQ 96.3 (16.0) 107.5 (14.1) t33, 2.24 0.03Performance IQ 98.2 (14.7) 109.1 (11.3) t33, 2.03 0.05Verbal IQ 94.8 (17.0) 105.0 (16.7) t33, 1.80 0.08Beck Depression Inventory 6.6 (1.4)Young Mania Rating Scale 1.4 (0.8)Cerebrospinal fluid, mm3 28,328 (11,943) 23,539 (10,287) t33, 1.20 0.21Total gray matter, mm3 888,827 (66,071) 880,521 (41,151) t33, 0.46 0.65Total white matter, mm3 805,868 (60,409) 804,636 (75,729) t33, 0.05 0.96Total brain volume, mm3 1,694,696 (59,637) 1,681,673 (55,430) t33, 0.67 0.51Comorbidity (ADHD), n (%) 5 ⁄ 15 (33)Medication, n

Olanzapine 7Quetiapine 3Risperidone 1Fluoxetine 1Sodium valproate 2Lithium 3

Values are mean (SD) unless otherwise noted. PANSS = Positive and Negative Syndrome Scale; ADHD = attention-deficit hyperactivitydisorder.

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memory ⁄ cognitive shifting, verbal learning ⁄mem-ory, and intellectual ability domains. The batterycomprised the following tests:

Intellectual ability. The Wechsler AbbreviatedScale of Intelligence (WASI) (35) was used toassess intellectual ability. The scale includesVocabulary and Similarities in the verbal quotientand Block Design and Matrix Reasoning in theperformance quotient. This measure also producesa four-subtest FSIQ.

New learning ⁄memory. For verbal skills, the WordLists subtest from the Children�s Memory Scale(CMS) (36) was included. Individuals over the ageof 16 were administered the Word Lists task fromthe Wechsler Memory Scale-III (WMS-III) (37).The Rey Complex Figure Test and RecognitionTrial (RCFT) (38) was used to assess nonver-bal ⁄visual memory.

Working memory. Working memory was evalu-ated with the Digit Span subtest from the WechslerIntelligence Scale for Children-III UK (WISC-III)(39). Individuals over the age of 16 were adminis-tered the Digit Span task from the Wechsler AdultIntelligence Scale-Revised (WAIS-R) (40).

Language. This domain included tests of expres-sive language. Verbal fluency (Letter and Categoryfluency) was included from the Delis-KaplanExecutive Function System (DKEFS) (41). Thisdomain also included the Vocabulary subtest fromthe WASI.

Visuospatial skills. The Copy portion from theRCFT was included to assess visuospatial skills.The Block Design subtest from the WASI was alsoincluded.

Psychomotor speed ⁄dexterity. This domain includedthe coding subtest from the WISC-III. Individualsover the age of 16 were administered the DigitSymbol task from the WAIS-R and the GroovedPegboard dominant hand score (42).

Executive function. This domain included VerbalFluency from the DKEFS, specifically with theLetter Fluency and Category Switching conditionsof the task. Also included were the Learning scorefrom the Word Lists task (CMS or WMS-III) andthe Digits Backward score from Digit Span(WISC-III or WAIS-R). Finally, the score fromthe Copy condition on the RCFT was included.These tests are weighted to verbal components ofexecutive functioning; measures of inhibitory con-

trol such as the Stroop Test, Trail Making Test–part B, and the Wisconsin Card Sorting Test werenot used.

Image analysis

To assess global changes in brain volume we usedSIENAX [part of the FMRIB Software Library(FSL) (http://www.fmrib.ox.ac.uk/fsl)] (43). Thisinvolves stripping nonbrain tissue and then usingthe brain and skull images to estimate the scalingbetween the subject�s image and standard space.SIENAX then runs tissue segmentation to estimatethe volume of brain tissue and multiplies this bythe estimated scaling factor to reduce head-size-related variability between subjects (44).

Gray matter. Structural data was analysed withFSL-VBM, a voxel-based morphometry (VBM)analysis (45) which is part of the FSL (44). First,structural images were brain-extracted using theBrain Extraction Tool (BET) (43). Next, tissue-type segmentation was carried out using FAST4(46). The resulting GM partial volume images werethen aligned to MNI152 standard space using theaffine registration tool FMRIB�s Linear ImageRegistration Tool (FLIRT) (47, 48), followedoptionally by nonlinear registration usingFMRIB�s Non-linear Registration Tool (FNIRT)(49), which uses a B-spline representation of theregistration warp field (50). The resulting imageswere averaged to create a study-specific template,to which the native GM images were then nonlin-early reregistered. The registered partial volumeimages were then modulated (to correct for localexpansion or contraction) by dividing by theJacobian of the warp field. The modulated seg-mented images were then smoothed with anisotropic Gaussian kernel with a sigma of 3 mm.

White matter. Voxelwise statistical analysis of theFA data was carried out using Tract-BasedSpatial Statistics (TBSS) (51), part of FSL (44).First, FA images were created by fitting a tensormodel to the raw diffusion data using FMRIB�sDiffusion Toolbox and then brain-extracted usingBET (43). All subjects� FA data were then alignedinto a common space using the nonlinear regis-tration tool FNIRT (49, 52). Next, the mean FAimage was created and thinned to create a meanFA skeleton which represents the centres of alltracts common to the group. Each subject�saligned FA data were thresholded at 0.2 andthen projected onto this skeleton. The resultingdata were then fed into voxelwise cross-subjectstatistics.

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Statistical analyses

Statistical analyses of demographic and neuropsy-chological data were performed using SPSS(16.0.0) (53). Group comparison of categoricaldifferences and normally distributed scalar datawere examined using chi-square and Student�st-test, respectively. All data were examined fornormality of data and homogeneity of varianceusing Levene�s test. Analysis of covariance(ANCOVA) was used to compare differences incognition with diagnosis (PBD, Control) as fixedfactor and FSIQ as covariate.To achieve accurate statistical inference from

imaging data, we first applied permutation testing(5,000 times) on the data using Randomise (54). Wethen applied the generalized linear model (GLM)comparing groups (Control > PBD), taking FSIQas a nuisance covariant to remove the potential effectof intelligence on brain structure. We also assessedthe associationof neuropsychologicalmeasureswithimaging markers using regression analysis, takingGMdensity or FA as the regressor and age and gen-der as naissance covariates. To correct for the effectof multiple comparison, we applied the false discov-ery rate (FDR) on the final result of our analysis.

Results

The PBD subjects (n = 15) and controls (n = 20)were matched for age, gender, and handedness(Table 1). The age range of the subjects was from11 to 16.5 years and for controls from 13.5 to17.8 years; pubertal status was not ascertained. Athird of the PBD subjects (5 ⁄15) had attention-deficit hyperactivity disorder (ADHD) clinicallydiagnosed before the onset of BD but had no othercomorbid diagnoses. The average length of psy-chosis was 0.9 years, and in most cases this was thefirst presentation of the bipolar illness.

Neuropsychometry

The PBD subjects had no significant differencewhen compared to control subjects on FSIQ,

although their FSIQ and performance IQ wererelatively lower than controls. PBD subjects weresignificantly impaired in the domains of attention,executive functioning, and working memory(Table 2); however, when FSIQ was entered as acovariate in a GLM analysis, only executivefunction, working memory, language function,and verbal memory remained significantly reducedin PBD subjects (Table 2). There was a significantnegative correlation of negative PANSS with FSIQ(r = 0.72, p = 0.002), but no such relationshipexisted for positive PANSS.

White matter differences

The PBD subjects had reduced FA in the anteriorhalf of the corpus callosum relative to age- andgender-matched healthy controls (Fig. 1A). Wecarried out probabilistic tractography from thesesignificant voxels in the anterior callosal cluster toassess the connectivity profile of these voxels. Theresult of this tractography was thresholded by 10%of maximum connectivity value to get rid ofspurious low-connectivity values. A populationmap of the resulting tracts was created representinga minimum of 75% of the population (Fig. 1B).This showed that voxels within the anterior callosalcluster were connected to the prefrontal cortex,particularly the orbitofrontal cortex, premotorcortex, pars triangularis, and frontal poles.

Gray matter differences

The PBD subjects had the following distinctclusters of reduced GM density (Fig. 1B): leftoccipital cortex, right occipital fusiform gyrus,right crus of the cerebellum, paracingulate, leftinferior frontal gyrus ⁄operculum, left frontal orbi-tal cortex, and left angular gyrus (Fig. 2).

Neural correlates of cognitive impairments in PBD

Regressional analysis showed that only verbalmemory and working memory correlated withFA in PBD subjects (Fig. 3). This figure shows

Table 2. Group comparison of z-scores of cognitive domains (Control > PBD)

Domain Controls PBD Statistics p-value F statistics covariate FSIQ p-value

Verbal learning ⁄ memory 1.38 )0.55 t33, 3.50 < 0.001 F1,34 6.9 0.013Nonverbal learning ⁄ memory 0.80 0.06 t33, 1.30 0.20 F1,34 1.5 0.23Language 1.30 )1.00 t33, 3.22 0.003 F1,34 5.7 0.023Visuospatial skills 1.03 )0.30 t33, 2.62 0.01 F1,34 2.4 0.07Working memory ⁄ cognitive shifting 1.70 )0.89 t33, 3.60 0.001 F1,34 8.8 0.006Executive functioning 2.20 )1.50 t33, 3.80 0.001 F1,34 8.6 0.006

PBD = pediatric bipolar disorder; FSIQ = full-scale IQ.

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that working memory correlated extensively withforceps minor and anterior thalamic radiation. FAin posterior frontal part of the right hemispherewithin the corona radiata also predicted verbalmemory.GM density was associated with all four cogni-

tive domains: executive functioning, language,verbal memory, and working memory (Fig. 2).GM density in the right frontal pole and the rightcerebellar cortex predicted language, executivefunction, and verbal memory. In addition, thefusiform cortex correlated with executive functionand verbal memory. The anterior temporal polecorrelated negatively with verbal memory andlanguage. Working memory correlated negativelywith the density of GM in the left temporal pole,midbrain, left striatum, and lateral occipital cortex.There were no significant correlations between

FA values or GM density and depression severity,

mania severity, duration of illness, or medicationdosage (chlorpromazine equivalents).

Discussion

This study examined neuropsychological and brainstructural changes in a population of patients withPBD and psychosis compared with age- andgender-matched controls.

Neuropsychometry

The general intelligence (FSIQ) of patientsincluded in this study was within the normal range.All the cognitive domains were impaired in PBDsubjects. However, only executive function, work-ing memory, language function, and verbal mem-ory remained significantly impaired whencovarying for FSIQ, suggesting that these deficits

Fig. 1. A. Spatial map of group comparison of fractional anisotropy (FA) maps contrasting controls > patients overlaid on thetarget FA map using tract-based spatial statistics analysis. The result is corrected for multiple comparison using false discovery rate(FDR) at p < 0.01. B. Spatial map of group comparison of gray matter density using voxel-based morphometry overlaid on theMNI-152 standard brain. The result (red-yellow) is corrected for multiple comparison using FDR thresholded at p < 0.01. Greencolour represents group map (thresholded at 25%) of the tracts (obtained from probabilistic tractography on diffusion tensorimaging dataset) that pass through the voxels in the corpus callosum which showed significantly reduced FA in pediatric bipolardisorder.

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are more disease-specific. Preserved general intel-ligence alongside deficits in executive functioningand working memory has been reported in PBD(25) and in adults with BD and psychosis (55).These neuropsychological findings indicate dys-function in the prefrontal and executive corticalareas (27). In our study, reduced GM density in thelateral prefrontal cortex as well as reduced FAvalue in the transcallosal prefrontal connectionsare consistent with these neuropsychological defi-cits. FA was correlated with verbal memory andworking memory, while widespread reductions inGM density correlated with working memory,executive function, language function, and verbalmemory. In particular, working memory correlatedextensively with forceps minor and anteriorthalamic radiation. Reduced functional fronto-temporal connectivity is implicated in the deficitsin working memory in PBD as shown by resting

state functional connectivity (RSFC), where reducedconnectivity between the left DLPFC and the rightsuperior temporal gyrus has been found (56).The relationship of cognition to WM changes

can be illustrated by comparison with schizophre-nia. In first-episode psychosis, moderate to severeimpairments in executive and motor functioningare linked to structural deficits in WM at very earlystages of the illness (57). Furthermore, by compar-ing those with and without cognitive deficits, itappears that it is the cognitive impairment itself,and not the illness per se, which is the factor relatedto abnormalities in WM structure (57). A similarstudy in PBD would help clarify the role of WMchanges to any cognitive impairment.The cognitive impairment in BDwith psychosis is

greater than in BD without psychosis, but the effectis modest (58). Adolescent patients with psychosisperform significantly worse than controls in all

Fig. 2. Spatial map of regressional analysis of the significant cognitive domains with gray matter density. Red = positive correlationwith gray matter density; blue = negative correlation with gray matter density.

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cognitive domains, but evidence suggests that thedegree of impairment is not diagnosis-specific (59).When considering the neuropsychology of PBD,

comorbidity is an important issue to consider. Inparticular, ADHD comorbidity appears to be asignificant confounding factor when measuringneuropsychological performance in PBD (23),and is likely to affect the results here, as a thirdof the subjects had a history of ADHD.

Gray matter changes

This study reports a series of GM and WMchanges mainly related (but not limited) to theprefrontal cortex. VBM analysis of the GMshowed reduced GM density in the left orbitofron-tal cortex, left pars triangularis, right anteriorcingulate, right premotor cortex, occipital cortex,and right fusiform cortex. The more anterior right-sided changes have recently been shown to confer agenetic risk for BD (60).

Left medial frontal GM volume deficits havebeen reported in first-episode psychosis patientswith BD (61)—an overlapping, but less extensivearea of involvement than is reported here, and alsoless extensive than that in patients with BD withoutpsychosis. It is difficult to disentangle GM changesthat are specific to bipolar illness without psycho-sis; however, a recent study found no significantdifferences in GM and WM density between BDpatients who had experienced psychotic symptomsat some point during their illness and those withoutpsychotic symptoms (60).The fusiform, cingulate, and orbitofrontal GM

density abnormalities are consistent with the find-ing of disturbed affective neurocircuitry withreduced connectivity between the left amygdalaand the right posterior cingulate ⁄precuneus andright fusiform gyrus ⁄parahippocampal gyrus (62).Although we have also highlighted a dorsal patternof loss of GM density, in PBD the major loss ofGM density is in the frontal areas, and a recentmeta-analysis has shown the GM density lossin BD is more confined to the paralimbicregions—anterior cingulate and insula—implicatedin emotional processing (63).The loss of GM density in the cerebellum has not

been previously reported in this age group. Inadults with multiple episodic BD, midline vermalchanges have been found (64), while vermalvolumes are not significantly reduced in adoles-cents (65). A progressive loss of cerebellar GMdensity in BD has been reported (66); cohortselection and age covariation in our study mayaccount for identification of changes here despiteprevious lack of evidence in PBD patients.Our observation that total brain volume was

not altered significantly in size relative to healthycontrols is consistent with an intermediary stagebetween childhood- and adult-onset BD. How-ever, it is unclear at what stage impairment ofneurodevelopment has occurred and whether thisprocess will alter later in life. The effects ofmedication also cannot be totally dismissed,although the lack of correlation between medica-tion dosage and GM ⁄FA suggests that they arenot significant. Indeed, only three patients wereon lithium, which has been shown to affect GM(67).

White matter changes

We found that reduced FA was restricted to theanterior callosal area. This is consistent withprevious reports of FA changes in the corpuscallosum (18, 21), although others report widerWM changes (17, 18, 20, 21). This difference may

Fig. 3. Spatial map of regressional analysis of the significantcognitive domains with fractional anisotropy.

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be due to methodological differences (e.g., imagingprotocols, approaches to image analysis) andcomposition of the cohort (e.g., the age of subjects,mental state, medication use), as well as thecontroversy around the diagnosis of BD in thevery young (68).Despite the evidence that abnormalities of the

corpus callosum, the major interhemispheric WMtract, are a central feature of BD (15, 69), thefindings in PBD are mixed, with reports ofdecreased FA (18, 21), increased ADC, anddecreased fibre coherence in the splenium of thecorpus callosum (20).A consistent finding in adult studies has been

a reduction in corpus callosum size (70), withabnormal axonal orientation or structure,although interestingly, affective psychotic disordersdo not show the callosal reductions seen in first-episode schizophrenia spectrum disorders (71). InPBD, there are conflicting reports of a smallercorpus callosum in the middle and posteriorregions, with reduced typical age-related increasesin size (72), shape changes with reduced circularityof the splenium (73), and unchanged size inadolescence (74). Overall, however, the evidencepoints to active changes in the corpus callosum(75), with axonal abnormalities and abnormalindices of myelination (76).The anatomical location of the cluster that

showed reduced FA in our patients correspondswith the region of the corpus callosum thatmostly contains interhemispheric prefrontal con-nection (77). This is further supported by trac-tography from this cluster in each individualconsistently showing that prefrontal interhemi-spheric tracts pass through this region. Observa-tion of reduced FA in the anterior corpuscallosum in PBD and the demonstration ofinterhemispheric prefrontal tracts passing throughthis region suggest that these tracts may bepathologically involved in this condition. Theinterhemispheric prefrontal tracts consist ofsmall-diameter, slow-conducting fibres whosemyelination is not completed until the early 20s(78). Reduced FA in the corpus callosum of PBDmay represent a delayed myelination and matu-ration of interhemispheric prefrontal tracts. Thisindicates an interaction between pathologicalprocess and neural development in these patients.Clearly, changes in the corpus callosum in PBDcannot explain all cortical changes, but may berelevant to the loss of GM density in the parstriangularis, orbitofrontal cortex, and premotorcortex.The genetic risk for developing BD is related to

reduced WM density in the superior longitudinal

fasciculus (60). The superior longitudinal fasciculus,which has been reported to be affected in PBD andsuggested as a possible endophenotype (18), was,however, not shown to be affected in this study.

Comparison with early-onset schizophrenia

It is of interest to compare the phenotypic expres-sions of the two major psychotic disorders: BDwith psychosis and schizophrenia during the neu-rodevelopmental phase of adolescence. Indeed,PBD appears to differ from early-onset schizo-phrenia in a number of ways. Unlike early-onsetschizophrenia (79), PBD with psychosis is associ-ated with a normal IQ; however, the deficits inexecutive functioning and working memory arecommon to both disorders. The pattern of loss ofGM density in PBD in this study differs to a degreefrom the more fronto-temporal loss seen in early-onset schizophrenia (80), and the WM changes areconsiderably more diffuse in early-onset schizo-phrenia (80), suggesting that the pathophysiologyis different. The findings are, however, limited bythe sample size of this study. There is considerablecontroversy in the genetic literature and elsewhereas to whether these represent separate disorders(81). Thus, comparative studies in this age rangemay add to this important discussion.

Limitations

A limitation of this study is the relatively smallnumber of subjects with PBD and psychosis.Although not an epidemiological study, it wasrepresentative of consecutive admissions with PBDand psychosis within a defined catchment area. Thestudy was confined to those with psychosis, andthus the findings cannot be generalised to PBD as awhole. Indeed, psychosis occurs in 16% of PBDand is a marker of severity and a poorer prognosis(82). However, unlike some previous studies, sub-jects were restricted to euthymic mood. Moodchanges, including depression, are reported to beassociated with acute microstructural WMchanges, which remit with clinical state (83). Astrength of the study was the longitudinal diag-nostic procedure, which adds to the reliability ofthe diagnosis (84). The use of imaging analysis withproven sensitivity and reproducibility (51) along-side quality control of the scanning procedures andimage acquisition enhance the strength of thefindings. As in a previous study from this group(80), the anatomical relation of WM to GMchanges in the frontal lobes, analysed with differingtechniques, adds biological plausibility to thesefindings.

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Acknowledgements

Funding for this study was provided by the Medical ResearchCouncil (MRC) and the Oxford Hospital Services ResearchCommittee (OHSCR). We would like to thank the patients,their families, and the Donnington Health Centre, Oxford.

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