Preserved white matter in unmedicated pediatric bipolar disorder

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ContentslistsavailableatScienceDirect

Neuroscience

Letters

j ou rn a l h om ep a g e :w w w . e l s e v i e r . c o m / l o c a t e / n e u l e t

Preserved

white

matter

in

unmedicated

pediatric

bipolar

disorder

Ana

Maria

A. Teixeira

a,b,c,∗

_,

_Ana

_Kleinman

a

_,

_Marcus

_Zanetti

b,c

_,

_Marcel

_Jackowski

c,d

_,

Fábio

Duran

b,c

_,

_Fabrício

_Pereira

b,c

_,

_Beny

_Lafer

a

_,

_Geraldo

_F.

_Busatto

b,c

_,

Sheila

C. Caetano

a,b,c,d

a_Bipolar_Research_Program,_Department_of_Psychiatry,_University_of_São_Paulo_School_of_Medicine,_São_Paulo,_Brazil

b_Laboratory_of_Psychiatric_{Neuroimaging,}_Department_of_Psychiatry,_University_of_São_Paulo_School_of_Medicine,_São_Paulo,_Brazil c_Center_for_the_Support_of_Research_in_Applied_{Neuroscience,}_University_of_São_Paulo,_São_Paulo,_Brazil

d_Child_and_Adolescent_Psychiatry_Unit_(UPIA),_Department_of_Psychiatry,_Federal_University_of_São_Paulo_(UNIFESP),_São_Paulo,_Brazil

h

i

g

h

l

i

g

h

t

s

•_No_white_matter_{abnormalities}_in_pediatric,_unmedicated_bipolar_disorder. •Nowhitematterabnormalitiesinyoung,healthyoffspring.

•_Disease_ontogeny_and_brain_development_dynamics_may_explain_differences_in_findings.

a

r

t

i

c

l

e

i

n

f

o

Articlehistory: Received14May2014

Receivedinrevisedform17June2014 Accepted29June2014

Availableonline10July2014

Keywords: Bipolardisorder Children DT-MRI Whitematter Offspring

a

b

s

t

r

a

c

t

Whitematter(WM)abnormalitieshavebeenreportedinbipolardisorder(BD)patients,aswellasintheir non-BDrelatives,bothchildrenandadults.Althoughitisconsideredanemergingvulnerabilitymarker forBD,therearenostudiesinvestigatingWMalterationsinpediatricunmedicatedpatientsandyoung healthyoffspring.Inthisstudy,weevaluatedthepresenceofWMalterationsin18pediatric,non medi-catedBDpatients,aswellasin18healthyoffspringofBDtypeIparentsand20healthycontrols.3TDT-MRI datawereacquiredandscanswereprocessedwithtract-basedspatialstatisticstoprovidemeasuresof fractionalanisotropyanddiffusivity.WefoundnosignificantdifferencesinWMmicrostructurebetween BDpatients,healthyoffspringandhealthycontrols.PreviousstudiesthatreportedWMalterations inves-tigatedoldersubjects,eitheronmedication(BDpatients)orwithpsychiatricdiagnosesotherthanBD (unaffectedoffspring).Ourfindingshighlighttheimportanceoftheunderstandingofdiseaseontogeny andbraindevelopmentdynamicsinthesearchforearlyvulnerabilitymarkersforpsychiatricdisorders.

1. Introduction

Bipolardisorder(BD)affectsupto2.5%oftheadultand ado-lescentpopulations[1,2],butitsethyologyandpathophysiology remainelusive.Thereiscompellingevidencethattheearly-onset formofthedisease(priortoage18)displayssignificant differ-encescomparedtothelate-onsetpresentation[3].Consideringthat braindevelopmentisa dynamic,geneticallypredeterminedand environment-dependent process, cross-sectional imaging stud-iesofthesamediseaseindifferentstagesofneurodevelopment

∗ _{Corresponding}_author_at:_Bipolar_Disorder_Research_Program,_Rua_Dr._Ovídio

PiresdeCampos,785,SãoPaulo05403-010,SP,Brazil.Tel.:+551126617928; fax:+551126617928.

E-mailaddress:ana.arist@gmail.com(A.M.A.Teixeira).

(e.g.,childhood,lateadolescence)mayyieldsignificantlydifferent results.Itmeansthatnotonlytheclinicalandmethodological dif-ferencesamongstudiesshouldbetakenintoaccount,butalsothe ontogeneticaspectsofthedisorderitself.

ItisalsoimportanttoconsiderthatBDisaprogressivedisease

[4],andthatmanystructuralalterationsthathavebeenassociated toitmaybechieflyascarringeffectofrepeatedmoodepisodes

[5] and/or continuedmedicationexposure [6,7]. Hence,it is of paramountimportance toassess unmedicated patientsearlyin the course of the disease. Furthermore, healthy relatives, such ashealthyBDoffspring(HO),canconstituteanimportantmodel byputativelydisplayinganumberofdisease-associatedmarkers withoutthecompletediseasephenotype.

White matter abnormalities detected by Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) have been consistently reportedbothinBDpatients[8,9]and intheirnon-BDrelatives

http://dx.doi.org/10.1016/j.neulet.2014.06.061

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in adulthood [10–12]. Children and adolescents with BD also havebeenfoundtodisplaydecreasedfractionalanisotropy(FA),a measureoffiberscoherenceandorganization,butfindingsdiffer acrossstudies[13–15].Resultsonyoung,unaffectedBDrelatives areevenmoreheterogeneous[16–18].Itisimportanttonoticethat DT-MRIstudieswithunaffectedBD relativesfrequently include subjectswithcurrentorpasthistoryofotherpsychiatricdiagnoses orsubthresholdmoodsymptoms.

Ouraiminthisstudywastoevaluatethepresenceofwhite matteralterationsinhealthychildrenatrisk,aswellasinpediatric, nonmedicatedBDpatients,usingDT-MRI.

2. Method

Thisstudywasundertakeninaccordancewiththeguidanceof theEthicsCommitteeoftheUniversityofSaoPaulo.Informed con-sentwasobtainedfromparentorlegalguardian,andassentwas obtainedfromallsubjects.

2.1. Participants

HealthyoffspringofadultBDpatientswereincludedifthey:(a) werebetween6and17yearsofage;(b)hadatleastoneparentwith BDtypeIdiagnosisaccordingtoDSM-IV-Rcriteria;and(c)hadno lifetimehistoryofDSM-IVaxisIdiagnosis.PediatricBDpatients wererecruitedfromtheoutpatientclinicoftheBipolarDisorder ResearchProgramandincludedifthey:(a)werebetween6and 17yearsofage;(b)fulfilledDSM-IV-RcriteriaforBD;and(c)were nottakingpsychotropicmedicationforatleastfourweekspriorto theexamination.Healthycontrols(HC)withinthesameagerange wererecruitedthroughadvertisementandincludediftheyhadno personalorfamilyhistoryofanyDSM-IVaxisIdiagnosis.Exclusion criteriafortheentiresamplewere:(a)headtraumaresultinginloss ofconsciousness;(b)neurologicalormedicaldisorders;(c)IQ<70; and(c)substanceusedisorders.

2.2. Clinicalassessment

ChildrenandadolescentswereinterviewedusingtheSchedule forAffectiveDisordersandSchizophreniaforSchool-Age Children-PresentandLifetimeVersion(K-SADS-PL)[19].Allinterviewswere ratedbytrainedpsychologistsandchildpsychiatristsandreviewed byboardcertifiedchildpsychiatrists(AKandSCC).Childrenand adolescentswere diagnosed as BD NOSif theypresented clear manic or hypomanic episodes with elation and/or grandiosity butlackedtheduration neededtobeclassifiedasBDIorBDII

[20]. Patients wererated using the ChildrenDepression Rating Scale—Revised(CDRS-R)[21],theYoungManiaRatingScale(YMRS)

[22]andtheClinicalGlobalImpressionScale(CGI)[23].Pubertal statusofallparticipantswasassessedusingthePetersenPubertal Scale[24].ParentaldiagnoseswereobtainedusingtheStructured ClinicalInterviewfortheDSM-IV(SCID-1)[25].Intelligencescores wereassessed usingWechsler Abbreviated Scale of Intelligence

[26].

2.3. Neuroimagingdataacquisition

GradientechoplanarMRimageswereacquiredusinga 3.0T PhilipsAchievaMR system(PhilipsHealthcare,USA)fittedwith 40mT/m highspeed gradients. Foam padding and a forehead strap were used to limit head motion, and a quadrature bird-cagehead coil was used for radio frequency transmission and reception. Data acquisition parameters for the DTI scan were repetition time (TR)=6106ms, echo time (TE)=65ms, field of view(FOV)=224×224mm,slicethickness=2mm,nogap,number

of slices=70, acquisition matrix=112×112, number of

diffu-sion gradient directions=32, b=0 and 1000s/mm2_, _number _of

averages=3, and the total scan time=24min. The MRI proto-col also included a tridimensional (3-D) T1-weighted imaging usingafastspoiledgradient-echosequence(TR=7ms,TE=3.2ms, FOV=240×240×180, slice thickness=1mm, no gap, number

of averages=1, acquisition matrix=240×240). All scans were

reviewedbyaradiologisttoensurethatnogrossbrain abnormali-tieswereevident.

2.4. Statisticalanalysis

2.4.1. Clinicaldata

Statistical analyseswereperformed withthe SPSSsoftware, version 14 (SPSS, Inc., Chicago, IL). We adopted a 2-tailed sig-nificancelevelof0.05.Wetestedthedatadistributionusingthe Kolmogorov–SmirnovZtest.Tocomparedemographicand clini-calcharacteristicsamongthethree groups,weusedanalysesof variance(ANOVA)andchi-squaretests.

2.4.2. DT-MRIdata

Diffusion-weightedimageswerefirstalignedtotheB0imageby Fourierinterpolation[27].Headmotionandeddycurrent-induced distortion correction were performedusing the “eddy current” script,and brainsegmentation wascarriedout bythesoftware “bet”,bothimplementedintheFSLtoolbox[28].Subsequently,the software“dtifit”,whichisimplementedinFSL,wasusedto com-putetheimagetensorusingtheadjusteddiffusion-weighedandB0 imagesandasimpleleastsquaresfit.Groupcomparisonswere car-riedoutusingthetract-basedspatialstatistics(TBSS)approachon theFSLsoftware[29].Voxelwiseanalysesofdatawereperformed usingpermutation-basedinferenceasimplementedinRandomise

[30]inFSLusingthreshold-freeclusterenhancement(TFCE)[31]. LineareffectsofdiagnosticgrouponFA,MD,RDandADweretested usinggenerallinearmodelswithageascovariate.Fivethousand permutationswereperformedforeachcontrast.Statisticalmaps werethresholdedatP<0.05,fullycorrectedformultiple compar-isons(family-wiseerror).Regionofinterest(ROI)analyseswere performedusingprobabilisticWMROIsincludedinFSLcomprising 11 tracts, two of which were considereda priori regions: cor-puscallosumandcingulum.Themeanvoxelintensityvaluewas obtainedforeachskeletonizedROIforthethreegroups,andgroup meanswerecomparedwithanalysesofcovariance(ANCOVA),with ageascovariate.

3. Results

Sociodemographicvariablesaredisplayedin Table1.Groups didnotdifferinage,gender,IQ,pubertydegreeorsocioeconomic status.

3.1. Clinicalcharacteristics

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Table1

Samplesociodemographiccharacteristicsbydiagnosticgroupandstatistics.

Variable BD(n=18) HO(n=18) HC(n=20) For2 P

Age(years),mean(SD) 12.3(2.8) 12.7(3.1) 12.7(2.6) 0.13* _0.88

Gender,%female 6(33.3) 10(50.0) 6(33.3) 1.50** _0.47

Ethnicity 2.90** _0.82

White,n(%) 10(55.5) 12(66.6) 11(55.0)

Black,n(%) 1(5.5) 1(5.5) 2(10.0)

Mixed,n(%) 6(33.3) 5(27.8) 7(35.0)

Asian,n(%) 1(5.5) 0 0

IQ,mean(SD) 94.4(15.5) 92.1(7.9) 97.1(14.1) 0.65* _0.53

Socioeconomicclass(scorea₎ _0.18** _0.92

A(≥89),n(%) 2(6.3) 0 1(6.7)

B(59–88),n(%) 7(37.5) 6(33.3) 9(40.0)

C(35–58),n(%) 8(50.0) 8(46.7) 9(53.3)

D(20–34),n(%) 1(6.3) 0 0

Education(years),mean(SD) 6.8(2.6) 7.5(2.8) 8.1(2.6) 0.92** _0.40

Pubertaldevelopment 2.8** _0.95

Prepubertal,n(%) 2(11.1) 3(16.6) 5(25.0)

Earlypubertal,n(%) 3(16.6) 4(22.2) 3(15.0)

Midpubertal,n(%) 6(33.3) 3(16.6) 4(20.0)

Latepubertal,n(%) 5(27.8) 5(27.8) 5(25.0)

Postpubertal,n(%) 2(11.1) 3(16.6) 3(15.0)

*_F. **2_.

a_Brazilian_Association_of_Market_Research_Institutes_Demographic_and_{Socioeconomic}_Class_Scale_[48].

patientshadmood congruentpsychoticsymptoms.BD patients wereeithermedication-naïve(n=10)orwereoffmedicationfor atleast4weeks(n=8).

3.2. Neuroimagingresults

TBSSresultsshowednosignificantdifferencesinFA,MD, RD orADindicesbetweenBD,HO,andHC,bothinthewhole-brain pairwisecomparisons(Fig.1)andROIanalyses.ROIindicesforall whitemattertractsanalyzedareshowninTable2.

4. Discussion

Inthisyoung,unmedicatedsample,wedidnotfindany sig-nificantwhite matter differences acrossdiagnostic groups. The mostreplicated white matterfinding in pediatric BD seemsto bedecreasedFAinanteriorcorpuscallosum[14,32,33],followed by decreased FA in the anterior cingulate and cingulate gyrus

[15,16,33], and in thecorona radiata [33,34]. In most previous

Fig.1.TBSSstatisticalmapsshowingnoclustersofhigherFAincontrolscompared toBD(P<0.05),bothintheTCFE-corrected(left)anduncorrected(right)maps.A: anterior;P:posterior.

studies,though, participantswere onmedication, and subjects’ meanagewasusually2–3yearsoldercomparedtothepresent study. Only Luet al. [35] evaluated unmedicated pediatric BD, andfoundlowerFAintheanteriorlimboftheinternalcapsule. However,theirdatahadlowspatialresolution,andtheydidnot haveanyfindingsinlargerwhitemattertracts,neitherinchildren norinadults,suggestingresultscouldbeapartialvolumeartifact. We used an ROI approach to investigate specific WM tracts, includingthelargestandmostfrequentlyimplicatedinpediatric BD(corpuscallosumandcingulumbundles),butfailedtofindany differencesacrossgroups.

Ourchoiceforscanningpreferentiallydrug-naïvesubjectsled toaparticularlyyoungsampleofBDpatients.Despitetheongoing controversyofBDdiagnosisinprepubertalchildren,weconsider thatoursamplemayprovideimportantinformationregardingthe underlyingneurobiologyofBD.First,halfofoursample,though young,wasclassifiedasBDtypeI,fulfillingdiagnosticcriteriafor classicmaniapresentation.Childrendiagnosed asBDnot other-wise specified (NOS)had topresent clear manic orhypomanic symptoms,includingelatedmood.Noneofoursubjectspresented withirritablemoodonly.AllBDpatientsinthissamplehavebeen followedupinourservices,andthere havebeennochangesin diagnoses.

Weevaluatedchildrenacrossawideagerange,butthemajority (63%)wasagedbetween8and12.SincelongitudinalMRIstudies inBDsuggestlossofgraymatterwithdiseaseprogression, partic-ularlyintheprefrontal,anteriorcingulateandsubgenualcortices

[36],andconsideringthesearelate-maturingbrainregions[37,38], partofoursubjectsareexpectedtobeundergoingdramatic struc-turalchanges—whileothersmaynotevenhavestartedtomature atthestudiedagerange.ConsideringBDcausesalterationsinbrain structurethatarerelativelymild[5]andthatevenpatientswith late-onsetBDusuallyhavehadsymptomssincechildhood[39],we couldhypothesizetheseyoungpatientsarelesslikelytoexhibit scarringeffectsofprolongeddiseaseand,therefore,thesinglemost importantfactoraccountingforthebetween-subjectsvariability couldbepubertaldevelopment.

Assubjects becomeolder,agedifferences maybecome pro-gressivelylessimportantinDT-MRIstudies,butatthisagerange, intensepruningandmyelinationprocessesaretakingplace[40]

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Table2

MeanROIFAindicesforthethreediagnosticgroups.

Tract Hemisphere BDmean(SD) HOmean(SD) HCmean(SD) F P

CC – 0.318(0.056) 0.344(0.017) 0.348(0.100) 1.163 0.322

Cingulum Left 0.275(0.049) 0.310(0.034) 0.298(0.095) 1.517 0.231

Right 0.209(0.049) 0.255(0.035) 0.244(0.101) 2.439 0.099

ATR Left 0.296(0.054) 0.313(0.015) 0.328(0.095) 1.150 0.326

Right 0.323(0.052) 0.323(0.016) 0.341(0.099) 0.481 0.622

CST Left 0.368(0.056) 0.394(0.021) 0.400(0.097) 1.276 0.289

Right 0.403(0.042) 0.412(0.021) 0.430(0.088) 0.960 0.391

SLF Left 0.295(0.047) 0.323(0.024) 0.331(0.088) 0.763 0.472

Right 0.296(0.046) 0.312(0.028) 0.317(0.098) 0.554 0.578

UF Left 0.265(0.048) 0.277(0.017) 0.297(0.090) 1.325 0.276

Right 0.307(0.049) 0.323(0.024) 0.305(0.088) 1.328 0.275

Abbreviations:CC,corpuscallosum;ATR,anteriorthalamicradiation;CST,corticospinaltract;SLF,superiorlongitudinalfasciculus;UF,uncinatefasciculus.

BDandschizophreniameanageofonset–lateadolescence–is associatedwithaderegulationoflatermaturationalprocessesin thebrain,suchasabnormalmyelinationoralteredexpressionof neurotransmittersandtheirreceptors[41,42].Consequently,brain alterationswouldbecomevisibleasthepatientsbecomeolderand theirbraindevelopmenttrajectoriesbegintovisiblydeviatefrom thetypicalcourse.

Itisalsoimportanttoconsiderthis wasanunmedicated BD sample,half of which wasdrug-naïve. Youth withBD are pre-scribedantipsychoticmedicationmoreoftenthanadults[43]and, thoughantipsychoticsmayacutelyincreasefrontallobe intracor-tical myelinvolume, chronicusemayexert theopposite effect

[44,45]. Moreover, a recent longitudinal study withdrug-naïve

patientswithschizophreniashoweddifferencesinFAindicesonly aftermedication:after6weeksofantipsychotictreatmentpatients showeddecreasedFAwhencomparedtohealthycontrolsandto baseline[46].

Themostrelevantlimitationtoourstudyistherelatively mod-estsizeofthesample.However,itshouldbenotedthatoursample isofcomparable[17,35]orlarger[32,47]sizethanthoseincluded inmostDT-MRIstudiesthathavereportedwhitematter abnormal-itiesinBDgroupsofolderageand/orwithahistoryofcontinuous medicationexposure.

Inconclusion,thereisagrowingbodyofevidenceassociating BDtograyandwhitematterabnormalities.Nevertheless, hetero-geneityamongstudiesishighandshouldbeproperlyaddressed. Ourstudyoffersanotherevidenceforthehypothesisof neuropro-gressioninBD,suggestingthatunmedicatedpediatricpatientsdo notcarryobservablewhitematteralterations,despitedisplaying thecomplete diseasephenotype. Similarly,whitematter abnor-malitiesarealsoabsentinhealthy,youngoffspringofBDparents. Futurelongitudinalstudiesarewarrantedtoevaluatethe progres-sionofstructuralalterationsinBDpediatricpatientsandtofurther investigatepossiblevulnerabilitymarkersinoffspringathigh-risk forBD.

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