ContentslistsavailableatScienceDirect
Developmental
Cognitive
Neuroscience
jou rn a l h om ep ag e : h t t p : / / w w w . e l s e v i e r . c o m / l o c a t e / d c n
Longitudinal
changes
in
white
matter
microstructure
after
heavy
cannabis
use
Mary
P.
Becker
a,b,∗,
Paul
F.
Collins
a,b,
Kelvin
O.
Lim
c,
R.L.
Muetzel
a,
M.
Luciana
a,baDepartmentofPsychology,UniversityofMinnesota,75EastRiverRoad,Minneapolis,MN55455,UnitedStates
bCenterforNeurobehavioralDevelopment,UniversityofMinnesota,717DelawareStreetSE,Ste.333,Minneapolis,MN55414,UnitedStates cDepartmentofPsychiatry,UniversityofMinnesota,2450RiversideAvenueSouth,Minneapolis,MN55454,UnitedStates
a
r
t
i
c
l
e
i
n
f
o
Articlehistory:
Received21May2015
Receivedinrevisedform3October2015 Accepted6October2015
Availableonline9October2015
Keywords: DTI Cannabis Longitudinal Youngadult Whitematter
a
b
s
t
r
a
c
t
Diffusion tensorimaging (DTI) studiesof cannabis users report alterations in brain whitematter microstructure,primarilybasedoncross-sectionalresearch,andetiologyofthealterationsremains unclear.WereportfindingsfromlongitudinalvoxelwiseanalysesofDTIdatacollectedatbaselineand ata2-yearfollow-upon23youngadult(18–20yearsoldatbaseline)regularcannabisusersand23 age-,sex-,andIQ-matchednon-usingcontrolswithlimitedsubstanceusehistories.Onsetofcannabis usewaspriortoage17.Cannabisusersdisplayedreducedlongitudinalgrowthinfractionalanisotropy inthecentralandparietalregionsoftherightandleftsuperiorlongitudinalfasciculus,inwhitematter adjacenttotheleftsuperiorfrontalgyrus,intheleftcorticospinaltract,andintherightanterior thala-micradiationlateraltothegenuofthecorpuscallosum,alongwithlesslongitudinalreductionofradial diffusionintherightcentral/posteriorsuperiorlongitudinalfasciculus,corticospinaltract,andposterior cingulum.GreateramountsofcannabisusewerecorrelatedwithreducedlongitudinalgrowthinFAas wasrelativelyimpairedperformanceonameasureofverballearning.Thesefindingssuggestthat contin-uedheavycannabisuseduringadolescenceandyoungadulthoodaltersongoingdevelopmentofwhite mattermicrostructure,contributingtofunctionalimpairment.
©2015TheAuthors.PublishedbyElsevierLtd.ThisisanopenaccessarticleundertheCCBY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Cannabisis experiencing itsmoment in thespotlight inthe UnitedStates. Currently,23 states andtheDistrict of Columbia havelegalizedcannabisformedicaluse,and4stateshave legal-izeditforbothmedicalandrecreationaluse.Inthecontextofits changinglegalstatus,cannabishasbeenthemostcommonlyused “illicit”substanceintheUnitedStates(SubstanceAbuseandMental
HealthServicesAdministration,2014),with14%of11thand12th
gradestudentsreportinglifetimeuse(Falcketal.,2012),and6.5% of12thgradestudentsreportingdailyuse(Johnstonetal.,2013). Adolescentusemaybeproblematic.
Adolescenceis a criticalperiod ofneuralmaturation, during whichthereisreorganizationofcorticalconnections,anincrease in the fidelity of corticolimbic interactions, and neurochemical changesthatpromoteadaptivebehavioralregulation(Colbyetal.,
2011;Giedd,2004; O’Hareand Sowell,2008; Wahlstrometal.,
2010).Graymatterdevelopsalonganonlineartrajectorythatvaries byregion,withpeakproliferationpriortopuberty,followedbya
∗ Correspondingauthorat:DepartmentofPsychology,UniversityofMinnesota, 75EastRiverRoad,Minneapolis,MN55455,UnitedStates.
E-mailaddress:petr0308@umn.edu(M.P.Becker).
gradualdeclineandpruningduringadolescenceandyoung adult-hood, extendinginto the30s (Giedd,2004; Giedd etal., 1999;
Gogtayetal.,2004;Pfefferbaumetal.,1994;Sowelletal.,2001,
2003).Incontrast,whitemattervolumeincreaseslinearlyinaless regionally-variantmannerfromchildhoodtoadolescence(Giedd
etal., 1999;Paus etal.,2001), following aposterior–inferior to
anterior–superior developmental trajectory (Colby et al., 2011;
Sowelletal.,1999).Whitemattervolumedoesnotreachitspeak
untiladulthood,betweenthemid-30sand40s(Bartzokisetal.,
2001;Sowelletal.,2003;Westlyeetal.,2010).White matteris
criticalforefficiencyofsignalconductionbetweenbrainregions, anditsdevelopmentisassociatedwithimprovedcognitivecontrol andexecutivefunctioningduringadolescence(Petersetal.,2014;
Treitetal.,2013).
Diffusion tensor imaging (DTI) is a sensitive neuroimag-ing technique that characterizes parameters of white matter microstructure,yieldingmeasuresofitsdirectionalorganization (fractionalanisotropy:FA),averagedwaterdiffusioninall direc-tions(meandiffusivity: MD),and waterdiffusionperpendicular totheprimaryfiberorientation(radialdiffusivity:RD).Although severaleigenvaluesofthediffusiontensorcontributetothe cal-culationofFAandareaveragedtoyieldMD,thereductioninRD http://dx.doi.org/10.1016/j.dcn.2015.10.004
hasbeenspecificallyassociatedwithincreasedmyelination and axonalpackinginanimalmodels(Buddeetal.,2007;Songetal.,
2003,2005),andage-relatedchangesinFAinhumansareoften
attributedtodecreasedRD(Giorgioetal.,2008;LebelandBeaulieu,
2011;Lebeletal.,2008).Ingeneral,increasesinFAanddecreases
inMDaswellasRDareobservedinmajorwhitematterfibertracts throughoutadolescenceandextendingintoadulthood.The biolog-icalmechanismsthatdriveMDchangesarelesscleargiventhat MDisanimprecisemeasure.
Estimatesofpeakdevelopmentofwhitemattermicrostructure varybetweenages20and42(Kochunovetal.,2012;Lebeletal.,
2012;SchmithorstandYuan,2010;Westlyeetal.,2010).Unlike
studiesofwhitemattervolume,thereisconsiderableregional vari-abilityinthematurationaltimingofwhitemattermicrostructure, withearliermaturationincommissuralandprojectionwhite mat-tertracts,andlaterdevelopmentduringadolescenceandyoung adulthoodintheassociationtracts(Ashtarietal.,2007;Kochunov
etal.,2012;LebelandBeaulieu,2011;Lebeletal.,2008).
Asisthecasewithotheractiveperiodsofbraindevelopment
(Fride, 2008; Huizink,2014; Linnet etal., 2003), substanceuse
duringadolescenceandyoungadulthoodmayinterferewith nor-mativedevelopment,alteringthestructuralintegrityandfunction oftheadultbrain.Agrowingliteraturesuggestsneurocognitive deficitsand neuroanatomical alterations among adolescent and youngadultcannabis users (CUs) relative tonon-users. Behav-iorally,cannabisuseinadolescenceandyoungadulthoodismost commonlyassociatedwithrelativedeficitsinverballearningand memory,decision-making,abstractreasoning,andcomplexspatial workingmemory(Beckeretal.,2014;Bollaetal.,2002;Dougherty
etal.,2013;Fontesetal.,2011;Gruberetal.,2012;Hansonetal.,
2010;LisdahlandPrice,2012;Medinaetal.,2007)withdeficits
inverballearningandmemoryrepresentingthemostreplicated finding.
Neuroimagingstudiesfindalterations inbrain structure and functionassociatedwithuse.Reducedhippocampal(Ashtarietal.,
2011;Demirakcaetal.,2011;Lorenzettietal.,2015;Schachtetal.,
2012;Yüceletal.,2008),parahippocampalgyrus(Battistellaetal.,
2014;Matochiketal.,2005),orbitalfrontal(Battistellaetal.,2014;
Churchwelletal.,2010;Filbeyetal.,2014),andincreased
cere-bellum(Battistellaetal.,2014;Cousijnetal.,2012;Medinaetal., 2010)graymattervolumesareamongthemoreconsistent find-ingswithinCUs.Alterationsinamygdalagraymatterarereported, butthe directionofalterations varies betweenreports (Gilman
etal., 2014; Lorenzetti et al.,2015; Schachtet al., 2012;Yücel
etal.,2008).Thedegreetowhichgroupsarematchedonpotential confoundsofsex,age,andothersubstanceusevariesbetween stud-ies.Onenotablerecentstudyfoundnogroupdifferencesbetween CUsandcontrols,whowerematchedonalcoholuse,onmeasures ofgraymattermorphologyinthenucleusaccumbens,amygdala, hippocampus, and cerebellum, suggesting alcohol use or other confoundsmaysignificantlycontributetoreportedgroup differ-ences(Weilandetal.,2015).Further,findingsacrossstudiessuggest cannabisuselikelyexertsonlyamodesteffectongraymatter vol-ume,indicatingthatlargesamplesizesmaybeneededtodetecta trueeffect(Weilandetal.,2015).
Amongmagneticresonanceimaging(MRI)andpositron emis-siontomography(PET)studiesoffunctionalrelationshipsamong brainregions,CUsdemonstratealteredpatternsofbrainactivity whencomparedtonon-usingcontrols,particularlywithinthe pre-frontalcortex(Batallaetal.,2013),orbitofrontalnetwork(Filbey etal.,2014),prefrontalandoccipitoparietalcortex(Hardingetal., 2012), and frontal-subcortical network (Filbey and Yezhuvath, 2013).Apotentialmechanismdrivingthesedifferencesmaybe dis-ruptionofwhitematterfibertractsthatsupportsignalingbetween neuronswithinandacrossneuralnodes.Thedirectionof alter-ationsinwhitemattervolumeinavarietyofcorticalandsubcortical
regionshasbeeninconsistentlyreportedinCUs,withonegroup findingincreaseddensityofwhitematterassociatedwiththeleft parahippocampalandfusiformgyriandlowerdensityinleft pari-etallobewhitematter(Matochiketal.,2005),andasecondgroup notingcerebellarwhitemattervolumereductioninCUs(Solowij
etal.,2011b).However,otherstudiesfindnoassociationbetween
cannabisuseandwhitematterextentorvolume(Blocketal.,2000;
Cousijnetal.,2012;Jageretal.,2007),makingitdifficulttodraw
generalconclusionsfromtheexistingstudies.Itappearsthat mea-suresofwhitemattervolumeorextentderivedfromT1weighted structuralMRI scansmaynot besufficientlysensitivetosubtle alterationsinwhitemattermicrostructurethatimpactinformation processing.
DTIhasthepotentialtoaddressthislimitationgiventhatwhite matterorganizationcanbeexaminedatthemicrostructurallevel. DTIstudiesindicatethatCUsdemonstratealteredwhitematter organization,althoughagainthereareinconsistenciesacross stud-iesinthedirectionofMRI-measuredchanges.Moststudiesindicate thatFAislowerinvariouswhitematterregionsinCUs.SomeDTI reportsincludefindingsofincreasedCURDandMD,also indica-tiveofreducedwhitematterorganizationinCUs.DTIfindingsfor CUshaveinvolvedwidelyscatteredbrainregions,includingthe superiorlongitudinalfasciculus(Ashtarietal.,2009;Bavaetal.,
2009;Thatcheretal.,2010;Yüceletal.,2010),arcuatefasciculus
(Ashtarietal.,2009),frontalwhitematteradjacenttotheanterior
cingulatecortex(Gruberetal.,2011)andhippocampus(Zalesky etal.,2012),internalcapsule(Gruberetal.,2014),and the
ros-trum(Arnoneetal.,2008),genu(Gruberetal.,2014),andsplenium
(Zaleskyet al.,2012)ofthecorpuscallosum.Cannabisusemay
disruptthedevelopmentaltrajectoryofwhitematterorganization sincelowerFAlevelshavebeenassociatedwithanearlierageof cannabisuseonset(Gruberetal.,2011,2014).
NotallDTIstudieshave foundevidencefor lowerFAand/or greaterRDandMDinCUs.GreaterFAandlowerRDhavebeen reportedintheforcepsminorofthecorpuscallosum,atractthat connectstheorbitofrontalcortices(Filbeyetal.,2014),although yearsofusewithintheCUgroupshowedacurvilinear(quadratic) associationwithdecliningFAlevelsandrisingRDlevels.Oneearly studyfoundincreasedFAinCUsinwhitematterassociatedwith medialfrontal,cingulate,precentral,andparietalcortex,aswellas decreasedMDincingulateandmedialfrontalwhitematter(Delisi
etal.,2006).
Though findings are compelling,this literature is comprised ofcross-sectionaldesigns,limitinginterpretationofgroup-based differences.Longitudinalresearchmayclarifysomeinterpretative complexities, by assessing neural changes over time in rela-tiontoongoingsubstanceuse.Recentlongitudinalstudieshave exploredwhitematterdevelopmentassociatedwithalcohol ini-tiation (Luciana et al., 2013), binge alcohol use withcomorbid cannabisuse(Jacobusetal.,2013a),andpolysubstanceuse(Bava etal.,2013).Nolongitudinalstudytodatehasexploredwhite mat-termicrostructurespecificallyrelated tosustainedcannabis use duringyoungadulthood.
Thisstudyexamineschangeinmeasuresofaxonalfiber orga-nizationacrosstimeasa functionofcannabisuse.Young adult, regularCUsandcontrol participantswereassessedattwo time points,withatwo-yeartimeintervalbetweenassessments.Itwas predictedthatongoingdevelopmentofaxonalfiberorganization, asmeasuredbyincreasingFAanddecreasingRD,wouldbe rela-tivelydiminishedamongCUsaftermultipleyearsofchronicuse. GiventhebroadlydistributedDTIfindingstodate,weexpected alterationsoffiberorganizationinfrontalwhitematteraswellas fibertractsconnectingfrontalandposteriorregions;hippocampal whitematter;thecorpuscallosum;andcortical–subcortical pro-jectionfibers suchasthecorticospinaltract.We predictedthat thesealterationsinfiberorganizationwouldbecorrelated with
amountofcannabisuseinthefollow-upintervalintheCUgroup. TofacilitateinterpretationoftheDTIfindingsintermsof behav-ioralfunctioning,weincludeacorrelationalanalysisofscoresona testofauditoryverballearningandmemory.CUshaveconsistently shownimpairmentsinthisdomain(e.g.,Beckeretal.,2014)andwe predictedthattestperformancewouldcorrelatepositivelywithFA changesintask-relevantbrainregions.
1. Methods 1.1. Sample
Thirty-sevenCUswere initiallyrecruited intothis longitudi-nalstudythroughuniversityadvertisements.CUswererecruited if they reported using cannabis at least 5 times per week for at least 1 year. Cannabis useonset was required to be before age17 sothatlengthofuseacrossstudyparticipantswouldbe relativelyuniformandtoindexadolescentuseonset.CUswere excludedif theyweredaily cigarette smokersor if alcohol use exceeded4 drinksfor females and 5drinks for malesonmore than2occasionsperweek.Participantswereinitiallytested on a comprehensivebehavioral andimaging battery (Beckeretal.,
2014;Muetzelet al.,2013).Ofthose whoinitially participated,
27CUsreturnedforfollow-upassessmentafteratwo-year inter-val. Of these, 2 CUs were excluded from the current analysis becausetheyreportedcannabisusepatternsmarkedlylowerthan themajorityoftheCUsample(≤5timesinpast12 months)at follow-up.Twenty-threeoftheremaining25subjects(16males, 7 females), aged 18–20 years (M=19.45, SD=0.66) generated artifact-free scanning data. Twenty-three controls(16 males, 7 females),aged15–23yearsold(M=19.19,SD=2.31),wereselected fromalargerlongitudinalstudyofadolescentbraindevelopment (describedinmoredetailinLucianaetal.,2013;Uroˇsevi ´cetal., 2012)tomatchtheCUs onageand sexand scanning parame-ters.
Generalinclusioncriteriaforallparticipantsincludedbeinga nativeEnglishspeaker,right-handed,andwith normal/corrected-to-normal vision and hearing. Exclusion criteria included any contraindicationstoMRIscanning, areportedhistory of neuro-logicalproblemsorsignificantheadinjury,intellectualdisability, or current pregnancy. Controlsubjects were excludedat study enrollmentforevidenceofAxisIDSM-IVpsychopathology.Adult participantsandparentsofminorsprovidedinformedconsent,and minors(thoseunderage18)assentedtoparticipateinthestudy. TheUniversityofMinnesota’sInstitutionalReviewBoardapproved the protocol. Inclusion criteria were verified during an initial visit bya demographic and healthinterview questionnaire,the EdinburghHandednessInventory(Oldfield,1971), theWechsler AbbreviatedScaleofIntelligence(WASI:Wechsler,1999),andby structureddiagnosticinterviews(theKiddieScheduleforAffective DisordersandSchizophrenia;Kaufmanetal.,1997)administeredto theparticipantaswellas(forthoseunderage18)aparent. Partici-pantswhometinclusioncriteriareturnedforasecondassessment, whichincludedMRIscansaswellasabatteryofneuropsychological tasks.Cannabisuserswereaskedtorefrainfromdruguseforatleast 24hbeforetestingsoasnottobeacutelyhighduringthe assess-ment.Longerperiodsofabstinencewerenotrequired,becausewe didnotwishtostudyindividualsinthemidstofdrugwithdrawal andbecauseagoalofthestudywastocapturefunctional capaci-tiesinthecontextofactiveuse(Beckeretal.,2014;Muetzeletal.,
2013).
Participants completed MRI scanning and the neuropsycho-logicalbattery atstudyenrollment(Time 1)and ata follow-up assessment(Time2),approximately2yearsafterstudyenrollment (M=2.23years,SD=0.52).
1.2. Verballearningandmemory
We selected the Rey Auditory Verbal Learning Test (RAVLT;
Lezaketal.,2004;Rey,1993)toassessverballearningand
mem-oryperformance amongthesample. ThistaskdistinguishedCU fromcontrolsinapriorcomprehensiveassessmentof neuropsy-chological performance atbaseline (Beckeret al., 2014).It is a robustmeasureofeffortfulperformance,andrepresentsacognitive domainthatiscommonlyreportedtobediminishedamongCUs
(Bollaetal.,2002;Gonzalezetal.,2012;Grantetal.,2003;Hanson
andLuciana,2010;Harveyetal.,2007;Solowijetal.,2011a).The
RAVLTmeasuresacquisition,storage,andretrievalofverbal infor-mation.Duringthelearningphase,participantsarefirstreadand askedtorecallalistof15words.Thisprocedureisrepeatedfour additionaltimestoyieldthenumberofitemscorrectlyrecalled. Thisfive-triallearningphaseassessestheparticipant’simmediate learningandtemporarystorageofverbalinformation.Following thelearningtrials,participantsarethenreadandaskedtorecall anewlistof15words(interference trial).Theinterferencetrial assessesimmediatelearningofnewinformation,andispresented onlyonce.Followingtheinterferencetrial,participantsarethen askedtofreelyrecallasmanywordsastheycanfromthefirstlist (immediaterecall)andagainfollowinga30-mindelay(delayed recall).Statisticalanalyseswereconductedusingthetotal num-berofwordsrecalledduringthelearningtrials,interferencetrial, immediaterecall,anddelayedrecalltrials.
1.3. Substanceuseassessment
Substanceusefrequencyandamountwereassessedwiththe K-SADSinterview,andsubstanceusefrequencywasfurtherassessed withtheself-reportedPersonalExperienceInventory(PEI;Henley
and Winters, 1989). Within the PEI, participants reported the
numberoftimestheyusedsubstances(alcohol,cannabis,and non-cannabisillicitsubstances)withinthelast12monthsona5-point scale(never,1–5times,6–20times,21–49times,50–99times,100+ times).TheadolescentversionofthePEIwasusedwithparticipants undertheageof18,andtheadultversionofthePEIwasusedwith participants18yearsandolder.Scoringwasharmonizedtocreate comparable metricsacrossthetwo versions.Anin-house inter-viewquestionnaire,basedonguidelinesprovidedbytheNational InstituteonAlcoholAbuseandAlcoholism,wasalsoimplemented toassessalcoholandcannabisusecharacteristicsinthesample. Participantsreportedtheirtypicalusepatterns,asindexedby fre-quencyandquantityofuse,aswellasheavierusepatterns,defined asthenumberofoccasionsCUsusedtheirself-definedmaximum numberofcannabishits.
The Achenbach’s Adult Self-Report (ASR; Achenbach and
Rescorla,2003)questionnaireassessedself-reporteddailytobacco
use during the previous 6 months for subjects who endorsed tobaccouse.
1.4. MRIdataacquisitionandprocessing
MRI data were collected on a Siemens 3T Tim Trio scan-ner (Siemens Medical Systems, Erlangen, Germany) using a 12-channelarrayheadcoil attheUniversity ofMinnesota Cen-ter for Magnetic Resonance Research. Diffusion weighted data were acquired in the axial plane using a dual spin echo, single-shot,pulsed-gradient,echo-planarimaging(EPI)sequence (TR=8500ms,TE=90ms,64slices,nogap,FOV=256mm,voxel size=2.0mm×2.0mm×2.0mm, b value=1000s/mm2, GRAPPA iPAT=2).Theacquisitionboxwaspositionedtocoverthe cere-brumandasmuchofthecerebellumaspossible.Thirty-sixvolumes wereacquiredinthediffusionscan:6non-diffusion-weighted vol-umes(b=0)and30diffusion-weightedvolumes(b=1000s/mm2),
using gradient vectors distributed uniformly in 3-dimensional spaceaccordingtoanelectrostatic repulsionalgorithm (i.e.,the “Jones30”;Joneset al.,1999).For off-lineEPIgeometric distor-tioncorrection,b0fieldmapswereconstructedfromgradient-echo images acquired using different echo times (TE=4.62ms and 7.08ms; TR=700ms, flip angle=90◦, 64 slices, no gap, voxel size=2.0mm×2.0mm×2.0mm,FOV=256mm).
DiffusionMRIdatawereprocessedusingtheFDTandTBSS pack-agesinFSL(FMRIBSoftwareLibraryv4.0.1,http://www.fmrib.ox.
ac.uk/fsl,Smithetal.,2004).Eachdiffusion-weightedvolumewas
correctedforheadmotionandeddycurrentdistortionsusingan affineregistrationtothefirstb0referencevolume.Thediffusion series was corrected for geometric distortion caused by mag-neticfieldinhomogeneityusingPRELUDE(PhaseRegionExpanding LabelerforUnwrappingDiscreteEstimates)andFUGUE(FMRIB’s UtilityforGeometricallyUnwarpingEPIs)inconjunctionwiththe b0fieldmaps.BraintissuewasextractedusingBET(Brain Extrac-tionTool).Thediffusiontensorwasfitateachvoxelbysubmitting thepreprocesseddatafromtheb0referencevolumeandthe30 diffusion-weightedvolumestoFSL’sDTIFIT.Diagonalizationyields theeigenvectors(V1,V2,V3)andcorrespondingeigenvalues(L1, L2,L3)ofthediffusiontensor,whichdescribethedirectionsand apparentmagnitudesofwaterdiffusionwithineachvoxel.Two scalarvariableswerecomputedfromthesetensor components: radialdiffusivity(RD),whichistheaverageofL2andL3andreflects themagnitudeofdiffusionperpendiculartowhitemattertracts; andfractionalanisotropy(FA),avariancemeasurethatreflectshow stronglywaterdiffusionisrestrictedtotheprincipleeigenvector andrangesfrom0(equivalentdiffusionalongV1,V2,andV3)to 1(nodiffusionalongV2andV3).Givenourfocusonthe devel-opmentoffiberorganization,wedidnotanalyzemeandiffusivity, whichislessinterpretablethanRDinregionswithcomplexfiber orientations(Vosetal.,2012),oraxialdiffusivity,whichismore informativeinthecontextofaxonalinjuryanddegeneration(e.g.,
Buddeetal.,2009).
Tract-BasedSpatialStatistics(TBSS;Smithetal.,2006)wasused toaligntheDTIscalarvolumessothatvoxelwisestatisticalanalysis couldbeperformedacrossparticipantsandbetweentimepoints. AllFAvolumeswerealignedtoacommonspacetemplateusing thenonlinearregistrationIRTK(Rueckertetal.,1999;www.doc.ic.
ac.uk/∼dr/software).ThetemplatewasanaverageFAvolume
con-structedfrom72participantsdrawnfromourfullresearchsample, alignedto2mmisotropicMNIvoxelspace(Lucianaetal.,2013;
Olsonetal.,2009).RDvolumeswerealignedtocommonspaceby
applyingthetransformationmatricespreviouslycomputedduring theFAvolumealignments.FAvolumesweremaskedata thresh-oldof FA≥0.15 toreduce partialvolumeeffects, and thesame voxelmaskswereappliedtoRDvolumes.Toassesschangesover timewhilecontrollingforbaselinedifferences,commonspaceDTI scalarvolumesatfollow-upwereregressedonbaselinevolumes, yielding follow-up vs. baseline regression residuals for FA and RD.Theseresidualizedvolumesweresmoothedat4mmFWHM priortostatisticalanalysis.Inlongitudinaldataanalysisusingthis regressorvariablemethod(Allison,1990),thevarianceintime2 performance,residualizedforpredictionbasedontime1variables, reflectschangeovertimethatwasnotpredictedbybaseline
lev-els(seeCohenandCohen,1983,pp.402–422;CronbachandFurby,
1970;Metalskyetal.,1987).Baselinedatawereseparately
exam-ined.
1.5. Statisticalapproach
Distributionsofvariableswereexamined,andvariablesthatdid notmeettheassumptionsforparametricanalysisweresquareroot transformed,includingcannabisusevariablesoftotalnumberof hitsforthepast12monthsandmaximumcannabishitsfrequency
inthelast12months.Demographicdataaswellasbehavioral char-acteristicsrelatedtosubstanceusewerecomparedbetweengroups usinganalysesofcovariance,Chi-squareanalysisofindependence, andtheMann–WhitneyUtestatbaselineandfollow-up(computed inSPSS,version22).
SPM8(www.fil.ion.ucl.ac.uk/spm/software/spm8)wasusedto
performvoxelwisemultipleregressionanalysisoftheFAandRD follow-upvs.baselineresiduals.Predictorsintheregression equa-tionsincludedgroup,sex,ageatbaseline,timeintervalbetween baselineandfollow-upassessments,andaveragealcoholuse(the meanofbaselineandfollow-upPEIratingsforuseinthepast12 months).Preliminaryanalyseswereconductedusingbothbaseline andfollow-upPEIratingsforalcoholuseinthepast12months,but nosupra-thresholdclusterswereproducedforthealcohol predic-tors.Accordingly,thefinalregressionmodelsweresimplifiedto includeasinglealcoholcovariaterepresentingaverageduselevels acrossbaselineandfollow-up.Toassessgroupdifferencesat base-line,multipleregressionswereperformedonbaselineFAandRD volumeswithgroup,sex,ageatbaseline,andalcoholuseat base-line(past12months)aspredictorsinthemodel.Theseanalyses yieldtherelationshipbetweenapredictorvariableandcriterion variablewhileregressingoutthevarianceaccountedforbyother predictorsinthemodel(i.e.,ageatbaseline,sex,intervalbetween assessments,averagealcoholuse).
Allregression analyseswere evaluatedaccording to cluster-levelstatisticalsignificanceafterfamily-wiseerrorcorrectionfor multiplecomparisonsbasedonrandomfieldtheory(Worsleyetal., 1992),usinganinputvoxelwiseheightthresholdofp<0.01.
MeanvalueswerecomputedwithinclustersfromtheFA-change regressionanalysesandthencorrelatedwithcannabisusevariables withintheCUgroup,whilecontrollingforvariablesofno inter-est.Specifically,follow-upcannabisusemeasureswereregressed onbaselinecannabisusemeasures,along withsex,ageat base-line,timeinterval betweenbaselineandfollow-upassessments, andaverage12-monthalcoholuse.Residualsfromthese regres-sionswereusedastheoutcomeusevariables.Measuresofcannabis useexaminedincluded:ageofregularcannabisuse,totalnumber ofhitsforthepast12months,andmaximumcannabishits fre-quencyinthepast12months.Forcomparison,correlationswere performedonfollow-upmeasuresofalcoholuse(i.e.,total num-berofdrinks,binge-drinkingoccasionsinthelast12months,and maximumdrinksfrequencyinthepast12months,controllingfor intervaltimeandsexasdescribedabove)andtobaccouse, con-trollingforsex,timeintervalbetweenbaselineandfollow-up,and average12-monthalcoholuse.
Additionally,partialcorrelationswerecomputedovertheentire sample(bothCUsandcontrols)betweenclustermeanvaluesand totalscoresontheRAVLT,controllingforsex,ageatbaseline,time intervalbetweenbaselineandfollow-upassessments,average 12-monthalcoholuse,andWASIIQscores.Thiscorrelationalanalysis wasconductedtoclarifythedirectionoffunctionalassociationsfor thelongitudinalFA-changeclusters,i.e.,todetermineforeach clus-terwhetherincreasingordecreasingFAoverthefollow-upperiod wasassociatedwithbettercognitiveperformance.Arepeated mea-suresanalysisofcovariance(ANCOVA)wasperformedtoassessthe temporalstabilityofRAVLTscoresoverthefollow-upintervalas wellasgroupdifferencesinperformanceatbothtimepoints.More comprehensiveassessmentoftheneuropsychologicalfunctioning ofthisCUsampleatbaselinecanbefoundinBeckeretal.(2014). 2. Results
2.1. Demographicandsubstanceusecharacteristics
Groups were matchedon sexdistribution, ethnic and racial background,yearsofeducation,andestimatedIQ(seeTable1).The studyparticipantswerelargelyCaucasianandhadaboveaverage
Table1
Demographicandsubstanceusecharacteristicsofcannabisusers(CUs)andhealthycontrols.Valuesrepresentmeansandstandarddeviationunits,unlessotherwisespecified. GroupcomparisonswereconductedusingChi-square,Mann–WhitneyU,andone-wayanalysisofvariance.
Variable Control CU F,U,2 p
n 23 23
Time1:Baselinecharacteristics
Age 19.19(2.31) 19.45(0.66) 0.27 0.61
#Male/#Female 16/7 16/7 2=0.00 1.00
#Caucasian/#OtherEthnicity 21/2 19/4 2=0.77 0.38
Yearsofeducation 13.09(2.07) 13.26(0.92) 0.14 0.71
EstimatedFullScaleIQ 115.65(9.46) 115.17(11.02) 0.03 0.88
VocabularyT-Score 62.09(5.43) 61.83(8.34) 0.02 0.90
MatrixreasoningT-Score 55.65(7.06) 55.35(5.58) 0.03 0.87 Alcoholuse,past12months(MedianPEIrating) 1 4 U=54.00 <0.00
0:Never(n) 9 1 – – 1:1–5times(n) 7 0 – – 2:6–20times(n) 3 3 – – 3:21–49times(n) 3 6 – – 4:50–99times(n) 1 8 – – 5:100+times(n) 0 5 – –
Cannabisuse,past12months 0 5 U=0.00 <0.00
0:Never(n) 21 0 – – 1:1–5times(n) 2 0 – – 2:6–20times(n) 0 0 – – 3:21–49times(n) 0 0 – – 4:50–99times(n) 0 0 – – 5:100+times(n) 0 23 – –
Ageofregularcannabisuseonset – 15.35(1.16) – –
Total#hits,past12months – 3032.55(2395.31) – –
Maximumcannabishitsfrequency,past12months – 11.21(13.77) Time2:Follow-upcharacteristics
Yearsbetweenassessments 2.12(0.66) 2.34(0.31) 2.18 0.15
Ageatfollow-up 21.31(2.43) 21.79(0.82) 0.82 0.37
Agerangeatfollow-up 17.2–26.0 20.6–23.3 – –
Alcoholuse,past12months(MedianPEIrating) 3 4 U=84.5 <0.00
0:Never(n) 2 1 – – 1:1–5times(n) 3 0 – – 2:6–20times(n) 6 1 – – 3:21–49times(n) 8 2 – – 4:50–99times(n) 3 11 – – 5:100+times(n) 1 8 – –
Cannabisuse,past12months 0 5 U=0.00 <0.00
0:Never(n) 14 0 – – 1:1–5times(n) 7 0 – – 2:6–20times(n) 2 0 – – 3:21–49times(n) 0 1 – – 4:50–99times(n) 0 6 – – 5:100+times(n) 0 16 – –
Total#hits,past12months – 2637.92(2203.77) – –
Maximumcannabishitsfrequency,past12months – 16.20(28.66) – –
IQestimates.Groupswerematchedintermsofmeanage,though alargeragerangecharacterizedthecontrolsampletobalancethe sexdistributionacrossbothgroups.Timetofollow-upassessment wasmatchedbetweengroups,withanoverallaverageof2.23years (SD=0.52).
AllCUsreportedconsistentcannabisusepriortoboththeTime 1andTime2assessments(seeTable1).Giventhehighprevalence ofcannabisuseinthegeneralpopulation,controlswhohad min-imallyexperimentedwithcannabisuse(thatis,usethatdidnot exceed5timesinthepastyear)wereincluded.Minimal experi-mentationwithcannabisusewasreportedby2healthycontrolsat theTime1assessment(bothreportedusingcannabis1–5timesin thepast12months);atTime2,n=7reportedusing1–5timesinthe past12months,n=2reportedhavingtransitionedintousing6–20 timesinthepast12 months.Additionally, CUsreportedgreater alcoholuse(Time1&Time2CUMdnuse=50–99timesinpast12 months)thanhealthycontrols(Time1Mdnuse=neverinthepast 12months;Time2Mdnuse=21–49timesinpast12months). Min-imalnon-cannabisdrugusewasreportedamongCUs(usefewer than20times),andcontrols(Time1:noreporteduse;Time2:fewer than5times,seeTable1).Asindicatedinourpriorpublications
(Beckeretal.,2014;Muetzeletal.,2013),CUslargelymetcriteriafor
DSM-IV cannabis dependence at baseline without evidence of comorbidpsychopathology.
2.2. FAdevelopment
Significant differences in two-year FA change between CUs andnon-usingcontrolswereidentifiedinfivevoxelclusters(see
Table2)withtrend-leveldifferencesin two additionalclusters.
Infiveofthesesevenclusters,theControlshadmorepositiveFA changethanCUsoverthetwo-yearfollow-upinterval(Fig.1),while theconverseheldintheremainingtwoclusters(Fig.2).Thelargest Controls>CU FA-change cluster(3864mm3)was locatedin the righthemisphereprimarilyalongthesuperiorlongitudinal fascicu-lus(SLF)adjacenttotheprecentralandpostcentralgyri.Itextended anteriorlyintothejunctionbetweentheSLFandthecorticospinal tract(CST).ThenextlargestFAcluster(1632mm3)haditspeak adjacenttotheparietaloperculuminthelefthemisphere.The clus-terfollowed theSLFadjacenttothesupramarginaland angular gyri,extendingintotheforcepsmajorofthecorpuscallosum(CC) neartheanteriorportionofthelateraloccipitalcortex;abovethe forcepsmajor,itoverlappedacaudodorsalportionoftheinferior longitudinalfasciculus(ILF).TheposteriorportionofthethirdFA
Table2
Analysisofgroupdifferencesin2-yearchangeinfractionalanisotropy(FA)andradialdiffusivity(RD).ResultsfromvoxelwisemultipleregressionanalysisofFAandRD2-year changevalues(i.e.,residualsfromregressionofeachparticipant’sfollow-upFAorRDvolumeonthecorrespondingbaselineFAorRDvolume).Multipleregressioncovariates weregroup,sex,ageatbaseline,timeintervalbetweenbaselineandfollow-upassessments,andaveragealcoholuse(meanofbaselineandfollow-upPEIratingsforusein past12months).Allregressionanalyseswereevaluatedaccordingtocluster-levelstatisticalsignificanceafterfamily-wiseerror(FWE)correctionformultiplecomparisons basedonrandomfieldtheory,usinganinputvoxelwiseheightthresholdofp<0.01;trend-levelresults(FWEp≤0.10)areincludedaswell.Abbreviations:ATR=anterior thalamicradiation;CC=corpuscallosum;CST=corticospinaltract;CWP=cluster-wiseFWE-correctedp-value;FOF=fronto-occipitalfasciculus;SLF=superiorlongitudinal fasciculus.
Measure Contrast PeakZ-stat Peak partialr
Clustersize (mm3)
CWP X Y Z Hemisphere Anatomical region
Fractionalanisotropy Controls>CU 5.80 0.76 3864 0.001 32 −32 40 Right SLF,extendingtojunction withCST
Fractionalanisotropy Controls>CU 4.12 0.59 1632 0.017 −38 −44 24 Left SLF,extendingtoCC forcepsmajor
Fractionalanisotropy Controls>CU 3.88 0.56 1464 0.030 −18 16 42 Left Whitematteradjacentto superiorfrontalgyrus Fractionalanisotropy Controls>CU 4.46 0.63 1232 0.065 −16 −28 50 Left CST,adjacenttopre-and
postcentralgyri Fractionalanisotropy Controls>CU 4.25 0.61 1208 0.071 26 16 12 Right ATR;superiorFOF;
adjacenttofrontal operculum Fractionalanisotropy Controls<CU 4.49 0.63 1808 0.010 −14 16 26 Left AnteriorCC
Fractionalanisotropy Controls<CU 3.75 0.55 1696 0.014 −10 −24 −6 Left Whitematteradjacentto posteriorthalamus Radialdiffusivity Controls<CU 4.54 0.64 6848 0.001 16 −36 38 Right CST;SLF;posterior
cingulum Radialdiffusivity Controls>CU 3.97 0.57 2368 0.006 −24 −18 4 Left CST
cluster(1464mm3)waslocatedinthewhitematterofthemiddle regionofthesuperiorfrontalgyrusinthelefthemisphere,while theanteriorportionextendedintothelateralanteriorcingulumand anteriorthalamicradiation(ATR)adjacenttotheanteriorsuperior frontalgyrus.MostofthefourthFAcluster(1232mm3;trendlevel atclusterwiseFWEp=0.065)waslocatedwithintheCSTadjacent totheprecentralandpostcentralgyriinthelefthemisphere,with thelateralaspectoftheclusterextendingintotheSLF.Thefifth
Controls>CUFA-change cluster(1208mm3;trend levelat clus-terwiseFWEp=0.071)wasadjacenttotheinferiorfrontalgyrus (specifically,thefrontaloperculum)intherighthemisphere,with themedialaspectoftheclusteroverlappingtheanteriorthalamic radiationandthelateralaspectextendingintothesuperior por-tionoftheFOF.Aswillbediscussed,thesetrendlevelfindingsare mentionedbecausetheyreplicatefindingsreportedintheextant literature.
Fig.1.Voxelwiseanalysisofgroupdifferencesin2-yearchangeinfractionalanisotropyandradialdiffusivity.MultipleregressionanalysisasdescribedforTable2.Color codingindicatescontrastsformultipleregressioneffects:red=fractionalanisotropy,Controls>cannabisusers;green=radialdiffusivity,Controls<cannabisusers.(For interpretationofthereferencestocolorinthisfigurelegend,thereaderisreferredtothewebversionofthisarticle.)
Fig.2. Voxelwiseanalysisofgroupdifferencesin2-yearchangeinfractionalanisotropyandradialdiffusivity.MultipleregressionanalysisasdescribedforTable2.Colorcoding indicatescontrastsformultipleregressioneffects:red=fractionalanisotropy,Controls<cannabisusers;green=radialdiffusivity,Controls>cannabisusers;blue=baseline fractionalanisotropy,Controls<cannabisusers;yellow=baselineradialdiffusivity,Controls>cannabisusers.(Forinterpretationofthereferencestocolorinthisfigure legend,thereaderisreferredtothewebversionofthisarticle.)
Morepositivetwo-yearFAchangewasobservedforCUsthan Controls within two clusters in the left hemisphere.One clus-ter(1808mm3)waslocatedprimarilyinanteriorcorpuscallosum (posteriorgenu,rostralbody),withasmalloverlapintothecaudal anteriorcingulum.Theothercluster(1696mm3)waslocatedin posteriorthalamuswhitematter.Themedialaspectofthiscluster overlappedtheCSTandtheATR,whilethelateralaspectextended intotheacousticandopticradiations.
Baselinedifferencesbetweengroupsdidnotfullyaccountfor thesefindings.AnalysisofFAgroupdifferencesatbaselineyielded onesignificantvoxelcluster(2584mm3),inwhichFAlevelswere greaterforCUsthanControls(Table3).Thisclustercoveredthe rightsideofthegenuoftheCC,crossingovertheCCmidlineto extendinto theinferiorpartof the leftgenu. In terms of fiber tracts,theclusteroverlappedthecaudalforcepsminor,withamuch greaterextensionintotherighthemispherethantheleft.
2.3. RDdevelopment
InadditiontotheFAresults,significantdifferencesintwo-year DTIchangebetweenCUsandControlswereidentifiedinthe anal-ysisofRDdata.ItwasgenerallyexpectedthatRDwoulddecrease overtime.RDchangewasmorepositiveforCUsthanControlsina verylargevoxelcluster(6848mm3)thatextendedoverthe poste-riortwo-thirdsoftherighthemisphere,inwhitematteradjacentto precentral,postcentral,supramarginal,inferiorparietal,precuneus, and posterior cingulatecortex (Table 2). The cluster peak was locatedinthemedialaspectofthecluster,whichoverlappedthe posteriorcingulum.Themiddlesectionoftheclusteroverlapped theCST,whilethelateralaspectoverlappedtheSLF.Bothofthese
clustersegmentshadsubstantialoverlapwithasimilarlylocated Controls>CUFA-change cluster(notethat increasedFAoftenis accompaniedbydecreasedRD;seeFig.1).RDchangewasmore positiveforControlsthanCUsinalefthemispherevoxelcluster (2368mm3)locatedalongtheCST,withapeakin theposterior limboftheinternalcapsule.
AnalysisofRDgroupdifferencesatbaselineyieldedone trend-level voxel cluster (1640mm3; trend level at clusterwise FWE p=0.10;Table3),inwhichRDlevelsweregreaterforControlsthan CUs.TheControls>CUsbaselineRDclusterwaslocatedinthesame CCregionastheControls<CUsbaselineFAcluster,butwassmaller insize(seeFig.2).
2.4. Brain–behaviorassociations
Cannabisusecharacteristics.WithinCUs,extentofcannabisuse wasnegatively associated withcluster meanFA-change values, forthreeControls>CUFA-changeclusters(seeTable4)suchthat higherlevelsofreportedusewereassociatedwithlower magni-tudesofchangeovertime. Specifically,thetotal numberofhits duringthepast12monthswassignificantlynegativelyassociated withclustermeanFA-changeintheleftCST(r=−0.259,p<0.05) andleft SLF/CCforcepsmajorjunction(r=−0.525,p<0.01).The maximumcannabishitsfrequencyduringthepastyearwas sig-nificantlynegatively associatedwithclustermeanFA-changein therightSLF/CST junction(r=−0.514,p<0.05).Age ofcannabis useonsetwasnotsignificantlycorrelatedwithclustermean FA-changevalues.Analogouscorrelationswereexaminedinrelation tomeasuresofalcoholandtobaccouseatfollow-upbutwere non-significant.
Table3
Baselinegroupdifferencesinfractionalanisotropy(FA)andradialdiffusivity(RD).ResultsfromvoxelwisemultipleregressionanalysisofFAandRDatbaseline.Multiple regressioncovariatesincludedgroup,sex,ageatbaseline,andalcoholuse.Allregressionanalyseswereevaluatedaccordingtocluster-levelstatisticalsignificanceafter family-wiseerror(FWE)correctionformultiplecomparisonsbasedonrandomfieldtheory,usinganinputvoxelwiseheightthresholdofp<0.01;trend-levelresult(FWE
p≤0.10)isincludedaswell.Abbreviations:CC=corpuscallosum;CWP=cluster-wiseFWE-correctedp-value.
Measure Contrast PeakZ-stat Peak partialr
Clustersize (mm3)
CWP X Y Z Hemisphere Anatomicalregion
Fractionalanisotropy Controls<CU 4.18 0.60 2584 0.012 4 26 4 Right Genu,forcepsminorofCC Radialdiffusivity Controls>CU 3.86 0.56 1640 0.102 2 26 6 Right Genu,forcepsminorofCC
Table4
Partialcorrelationsofclustermeanfractionalanisotropy(FA)changevalueswithcannabisuse.Partialcorrelationsbetweenclustermeanvaluesandmeasuresofcannabisuse overthepast12months,controllingforinterval,sex,ageatbaseline,andaveragealcoholuse(n=23).Abbreviations:ATR=anteriorthalamicradiation;CC=corpuscallosum; CST=corticospinaltract;FOF=fronto-occipitalfasciculus;SFG=superiorfrontalgyrus;SLF=superiorlongitudinalfasciculus;CU=cannabisuser;L=lefthemisphere;R=right hemisphere.
FAcluster Total#hitsa Maximumcannabishitsfrequencya Ageofregularcannabisuse CU>Controls
LanteriorCC(−14,16,26) 0.209 −0.325 −0.313 Lthalamicwhitematter(−10,−24,−6) −0.004 0.335 −0.087
Controls>CU RSLF/CST(32,−32,40) 0.115 −0.514* 0.281 LCST(−16,−28,50) −0.259* 0.354 −0.016 RATR(26,16,12) −0.152 0.321 −0.010 LSLF/CCforcepsmajor(−38,−44,24) −0.525* 0.345 0.074 LSFGwhitematter(−18,16,42) −0.230 −0.061 0.065
aSquareroottransformed. * p≤0.05.
Table5
Partialcorrelationsofclustermeanfractionalanisotropy(FA)changevalueswith RAVLTscores.Partialcorrelationsbetweenclustermeanvaluesandtotalscoreson theReyAuditoryVerbalLearningTest(RAVLT),controllingforsex,ageat base-line,timeintervalbetweenbaselineandfollow-upassessments,average12-month alcoholuse,andIQ.Abbreviations:ATR=anteriorthalamicradiation;CC=corpus callosum;CST=corticospinaltract;FOF=fronto-occipitalfasciculus;SFG=superior frontalgyrus;SLF=superior longitudinalfasciculus;CU=cannabis user;L=left hemisphere;R=righthemisphere.
FAcluster RAVLT:Baseline RAVLT:Follow-up CU>Controls
LanteriorCC(−14,16,26) −0.226 −0.504**
Lthalamicwhitematter (−10,−24,−6) −0.407** −0.342* Controls>CU RSLF/CST(32,−32,40) 0.350* 0.364* LCST(−16,−28,50) 0.360* 0.334* RATR(26,16,12) 0.288 0.210 LSLF/CCforcepsmajor (−38,−44,24) 0.319* 0.317* LSFGwhitematter (−18,16,42) 0.315* 0.357* * p≤0.05. ** p≤0.01.
Verballearningandmemory.Partialcorrelationsofclustermean FA-changevaluesandtotalRAVLTscores,computedovertheentire sampleofcontrolsandCUs,arelistedinTable5.Forboth base-lineandfollow-upRAVLTtotalscores,whenexaminedseparately, negativepartialcorrelations were obtainedforclusters derived fromtheCUs>Controlscontrastinthevoxelwiseanalysis,while positivepartialcorrelations wereobtainedforclustersfromthe Controls>CUs contrast.No significantpartial correlations were observedbetweenclustermeanFA-changevaluesandRAVLT dif-ferencescores (follow-up scoreminusbaseline score),as RAVLT scoresshowedlittlechangeduringthelongitudinaltestinginterval (F=0.972inarepeatedmeasuresANCOVAthatcontrolledforthe samenuisancevariablesasinthepartialcorrelations).Itshouldbe notedthatCUsperformedsignificantlymorepoorlythanControls atbothtimepoints(F=8.18,p=0.007,partialetasquared=0.173 forthemaineffectofgroupintherepeatedmeasuresANCOVA).
3. Discussion
Thisstudyassessedchangesinaxonalfiberorganizationovera 2-yearperiodofcontinuedheavycannabisuseinyoungadultswho initiateduseduringadolescence.Whitemattermicrostructureis knowntoshowcontinueddevelopmentalchangesduringthisage period(Lebeletal.,2012).Aspredicted,FAchangewasgenerally lowerandRDchangewasgenerallyhigherforCUsascomparedto controls.Specifically,CUsshowedlessFAchangeinthecentraland parietalregionsoftherightandleftSLF(extendingintothe tempo-ral/parietal/occipitalwhitematterjunctionregionontheleft),in whitematteradjacenttotheleftsuperiorfrontalgyrus,intheleft CSTjustmedialtotheSLF,andintherightanteriorthalamic radi-ationlateraltothegenuofthecorpuscallosum.Acorresponding findingofmoreRDchangeforCUsoverlappedtheFAclusterinthe rightSLF,butencompassedamuchlargerwhitematterregionthat includedadjacentmedialstructuressuchastheCSTandposterior cingulum.
These deviations in the development of white matter microstructurewereobservedprimarilyinwidelydistributed cor-tical association fibers, which is consistent with findings from functional MRI and behavioral studies of cannabis users. Cog-nitive studies consistently find diminished CU performance on tasksthatrequiremoreeffortfulperformance,suchasexecutive functioning,verbalfreerecallofpreviouslylearnedinformation, decision-making,abstractreasoning, andcomplexspatial work-ing memory(Beckeret al., 2014; Bolla et al.,2002; Dougherty
et al., 2013; Fontes et al., 2011; Gruber et al., 2012; Hanson
et al., 2010; Lisdahl and Price, 2012; Medina et al., 2007).
In functional MRI studies, CUs tend to show a broader pat-ternofcorticalactivationandrecruitalternativebrainnetworks during task performance, as compared to non-using controls
(Block et al., 2002; Chang et al., 2006; Harding et al., 2012;
Jacobsenetal.,2004;Kanayamaetal.,2004;Padulaetal.,2007;
Schweinsburgetal.,2010;Tapertetal.,2007).Increasedactivation
andrecruitmentofalternativeinformation processingpathways byCUs mayreflect imperfectfunctional compensationfor sub-tledegradationsinstructuralconnectivity,suchasthosereported here.
SomeofthechangesinCUswhitemattermicrostructurewere dose-dependent, i.e., correlated with self-reported quantity of typicalandheaviercannabisusepatterns,againinaccordwith pre-diction.Thetotalnumberofcannabishitsinthepast12months, asassessedatfollow-up,demonstrated strongnegative correla-tionswithmeanFAchangeintheleftSLF(−38,−44,24)andCST (−16,−28,50)clusters,asdidthemaximumcannabishitsfrequency withtherightSLF(32,−32,40)cluster.Similarmeasuresofalcohol useandameasureoftobaccousedidnotcorrelatewithFAchange. Thus,althoughtheCUgroupusedmorealcoholandtobaccothan controls,onlytheircannabisusewasassociatedinacontinuous quantitativemannerwithFAchange,therebystrengtheningthe inferencethatcannabisuseitselfwasaprimaryfactorunderlying theobservedgroupdifferences.Thisfindingcontradictsexisting longitudinalDTIstudiesthathavenotdocumentedchangesover time attributabletoamountofcannabis use. Bavaet al.(2013)
reporteda largenumber of DTIvoxel clustersdifferentiating a groupofalcohol-plus-cannabisusersfromnon-usersbutfoundthat resultsweredrivenbyalcoholuseoverthe18-monthfollow-up periodratherthancannabisuse.Similarly,Jacobusetal.(2013a)
foundthatovera3-yearinterval,agroupofbingealcoholusers andagroupofcombinedbingealcoholandcannabisusersdiffered fromnon-usingcontrolsin15voxelclusters,but withonlyone exception,theclustersdidnotdifferentiatethetwousergroups. However,a smallerlongitudinalDTIstudy(n=16)onthe initia-tion(ratherthancontinuation)ofheavyalcoholandcannabisuse reported20clustersdistributedthroughoutthebrainthat differ-entiatedparticipantswhoinitiatedcombinedalcoholandcannabis usevs.alcoholusealone,withdecreasedFAshownalmost exclu-sivelybythecombinedalcoholandcannabisusersoverthe3-year follow-upperiod(Jacobusetal.,2013b).Ourresultsareconsistent
withJacobusetal.(2013b)insuggestingthatbrainwhitematter
changesdrivenbyheavycannabisuseduringlateadolescenceand earlyadulthoodcanbedetectedbyDTIdespitethepresenceof concurrentalcoholuse.Thisisanimportantempirical demonstra-tion,giventhatwhitematterdevelopmentextendsintothethird decadeoflife(e.g.,Lebeletal.,2012)andthatcannabisuseduring adolescenceandearlyadulthoodhasbeenfoundtohavelong-term impactsoncognitivefunctioningandbrainstructureand organi-zation,bothinanimalmodels(e.g.,Bambicoetal.,2010;Gleason
etal.,2012;Pistisetal.,2004;Raveretal.,2013;Rubinoetal.,2009;
SchneiderandKoch,2003,2007;Schneideretal.,2008;Stopponi
etal.,2014)andinhumans(e.g.,Battistietal.,2010;Ehrenreich
etal.,1999;Fontesetal.,2011;Lisdahletal.,2013;Meieretal.,
2012;Popeetal.,2003;Solowijetal.,2012;Wagneretal.,2010).
Contrarytoourpredictions,severalfindingsfortheCUgroup involved DTIchanges generally associated with what mightbe interpretedasbetterwhitematterorganization,i.e.,increasedFA anddecreasedRD.Inthelefthemisphere,morepositiveFAchange was observed for CUs in the anterior CC (posterior genu, ros-tralbody)andposteriorthalamicwhitematter.Acorresponding decreased-RDclusteroverlappedtheposteriorthalamicareaand alsoextendedmediallyintotheCST.Inanalysesofbaselinedata, themedial CCgenuregion(caudalforcepsminortract)showed higherFAvalues,andtherewasatrendeffectoflowerRDvaluesin theCUgroup.Filbeyetal.(2014)alsoreportedhigherFAandlower RDforCUsintheforcepsminoroftheCC,andmoregenerallyan earlystudyreportedasimilarpatterninseveralregionsincluding themedialfrontalwhitematter(Delisietal.,2006).
Differencesobservedatbaselinemayreflectareasofrelative strengthintheCUgroup,consistentwithourpreviousbehavioral reportthatdescribedincreasedprocessingspeedinCUsinthe con-textofnumerousrelativecognitivedeficits(Beckeretal.,2014). InterpretationofFAincreasesandRDdecreasesintheCUgroup overthe2-yearfollow-upperiodismorecomplex,asthefunctional implicationsdependonmorenuancedaspectsofthedevelopment
ofaxonalfiberorganizationthatcandriveDTImetricsin oppos-ingdirections.For example,FAincreasesmaybeobservedover timewhenaxonalconnectionsalignmorecohesivelyinasingle fiberpopulation, i.e.,duringdevelopmentwithinaparallel bun-dled tract,while theconverse (FA decreases)may beobserved when neuraldevelopmentoccurswithin multiplefiber popula-tionsinthesameregion,i.e.,areaswherefiberscrossorfanout intograymatter(e.g.,Douaudetal.,2011).Thus,althoughboth groupcontrasts,Controls>CUsandCUs>Controls,generated sig-nificantclustersinthevoxelwiseanalysis,itdoesnotnecessarily followthattheCUs>Controlscontrastclustersrepresentregions ofenhancedwhitematterdevelopmentinCUs.Such determina-tionsultimatelydependoncorrelationswithbehavioralmeasures. AlthoughmappingtheDTIresultstolongitudinalchangesin per-formanceonourfullneuropsychologicalbattery,whichincludes nearlyahundredvariables,wasbeyondthescopeofthisreport, aninformativecorrelationalpatternemergedwhenweanalyzed thedirectionofassociationsbetweenthemeanFA-change clus-tervaluesandperformanceonademandingtestoflearningand memory,theRAVLT.TotalRAVLTscorescorrelatedpositivelywith FAchangewithinfiveofthesevenclusters,namelythose gener-atedbytheControls>CUscontrast.Conversely,totalRAVLTscores correlated negativelywithFAchangewithintheremainingtwo clustersgeneratedbytheCUs>Controlscontrast,i.e.,better per-formancewasassociatedwithmorenegative,ratherthanpositive, FAchangeduringthefollow-upperiodwithinthethalamic/CSTand anteriorCCregions.Thus,itispossiblethatallofourlongitudinal DTIresultsreflectdeleteriouseffectsofcontinuedheavycannabis use,asexpressedinwhitemattermicrostructureinbrainregions spanningdifferentformsoffibertractdevelopment,andin contin-uingfunctionaldecrementsinlearningandmemory.Interpretation islimited,though,bythefactthatCUsdemonstratedconsistently poorperformancerelativetocontrolsintheirverballearningand memoryperformanceanddidnotshowaperformancedeclineover time.
Notably,ourfindingsarealsoinformativeregardingthetiming ofuse-relatedimpactsonbrainstructure.Neurocognitivedeficits
(Fontesetal.,2011;Gruberetal.,2012)aswellasfunctional
alter-ationsobservedintask-basedfMRIparadigms(Tapertetal.,2007) incannabisusershavebeenattributedtoearlyonsetofuse,most typicallyoperationalizedasapatternofregularusebeginningprior totheageof16–17years.Becauseearlyonsetusersarelikelyto useinlargequantitiesandwithhigherfrequenciesthanlateronset users(Sagaretal.,2015),itisunclearwhetherageofonset, fre-quency,andmagnitudeofuseshowindependenteffectsonbrain structureandfunction.Indeed,earlyonsetuse,incombinationwith thehighfrequencyofuseanduseinlargeamountsthattendsto co-occur,mayrepresentadditivevulnerabilitiesassuggestedbySagar
etal.(2015).Heavychronicusehasbeenassociatedwithstructural
braindeviations(Battistellaetal.,2014;Filbey etal.,2014)and neurocognitivechanges(Bollaetal.,2002).Ourfindingssuggest thatimpactsofheavycannabisuseonwhitematter microstruc-turedonotnecessarilydependonageofonset.Furthermore,such impactsmaynotbereliablydetectableuntilafteratleast3–4years ofheavyusebeginningin theadolescentperiodgiven thatfew differencesatourbaselineassessment(after1–2yearsofheavy use)wereobserved.Thispatterningisconsistentwiththeideathat enduringchangesinbrainstructure,particularlynon-lesion-based alterationsthatcanbedetectedwithMRI,emergegraduallydueto theimpactsofexogenouscannabinoidexposureonneurochemical substratesthatultimatelyimpactaxonalintegrity.Largerstudies areneededtodisentangleindividualdifferencesintheeffectsof earlyexposureandlevelsofuseonlaterneuraland behavioral disruptions.
Unlike previouscross-sectional studies,we didnot find DTI differencesbetweenCUsandnon-usingcontrolsinwhitematter
tracts associated with core limbic structures such as the hip-pocampus(e.g.,fimbria;Zaleskyet al.,2012; Yücelet al.,2010) andamygdala(e.g.,uncinate fasciculus;Jacobuset al.,2013a,b;
Shollenbargeretal.,2015),eitheratbaselineorfollow-up.These
limbic structures are rich in endocannabinoid receptors, and cannabisexposurehasbeenlinkedwithhippocampaldamagein animalmodels(Rubinoetal.,2009).Otherstudiesmayhavehad greatersensitivitytodetecteffectsinthesesmallertortuouswhite mattertractsduetotheuseoffibertractography(Shollenbarger
etal.,2015;Zaleskyetal.,2012)andincorporationofsubstantially
lowercluster-sizethresholdsinvoxel-basedanalysis(Jacobusetal.,
2013a,b).
Limitationsofourstudymustbenoted.Thesamplewas rela-tivelysmallandcomprisedmostlyofCaucasianparticipants.While theDTIresultsweresimilartothosereportedinothersamples, additionalresearchisneededamongmoreraciallyandethnically diversesamplestoimprovegeneralizabilityofthefindings. Sim-ilarly,oursampleischaracterizedbyhighaverageIQestimates, which againlimits thegeneralizability of findings and perhaps skewsoverallFAlevelstowardhighervalues(Navas-Sánchezetal., 2014).Thatsaid,thesefindingsaresoberingregardingpotential impactsofchroniccannabisuseacrosslateadolescent develop-mentin anotherwiselow-risk sample.Anadditionallimitation withoursampleisthegreaterrangeofagesinthecontrolgroup relativetoCUs.Groupswerematchedonmeanage,andwetookthe additionalstepofcontrollingforageatbaselineinstatistical analy-sestomitigatepotentialconfoundingbyagevariance.Baselineage didnotproducesupra-thresholdclustersinanalysesofFAandRD changeoverthetwo-yearfollow-upperiod,whichindicatedthat thegroup-wiseDTIfindingswerenotconfoundedsignificantlyby theagerangedifferencebetweengroups.
Perhapsmoreimportantly,CUsandcontrolsdiffered substan-tiallyinalcohol use, whichis commonlyobservedin studiesof adolescent and young adultcannabis users (e.g.,Arnone et al.,
2008;Bavaetal.,2009,2013;Gruberetal.,2014;Jacobusetal.,
2013a,b;Shollenbargeretal.,2015;Thatcheretal.,2010).Toassess
thissamplingconfound,past12-monthalcoholuseatboth base-lineand follow-upwereincludedin preliminaryanalysesofFA andRDchange,whichproducednosupra-thresholdclustersfor thetwo alcohol usevariables. To providestatistical control for sub-thresholddifferences,weincludedtheaverageofthe base-lineandfollow-upalcoholusevariablesinthefinalDTIanalyses. Thedose-dependentfindingsalsoindicatedthatcannabisusewas theprimaryfactorinourDTIclusterresults,asmeanvaluesfrom severaloftheFAchangeclusterscorrelatedwithpast12-month usevariablesforcannabisbutnotalcohol.Nevertheless,the opti-maldesigntodetectandisolatelongitudinalcannabiseffectswould employcontrastinggroupsthatusedalcoholatequivalentlevels.
While we requested that participants be free of substance use for at least 24h prior to scanning, we did not assess for recencyofcannabis,alcohol,orotherdruguseanddidnotemploy drugtestingtoverifyreportedlevelsofcannabisandother sub-stance use among CUs or abstinence in both groups. CU and controlparticipantscompletedmultipleself-reportandinterview measuresofsubstanceuse,andresponsesacrossmeasureswere comparedforreliabilityofinformation.While itispossiblethat participantsendorsedfalseuselevels,thisappearsunlikelygiven consistencyof reports across measureswithin time points and across the follow-up interval. Further, CUs’ self-reported level ofcannabisusewassupportedbyevidenceofDSM-IV cannabis dependenceinthesampleaswellastheneurocognitive impair-mentsnotedatbaselinefortheseparticipants(seeBeckeretal.,
2014).
Finally, while reports have described alterations in cerebel-lar white matter in CUs, our field-of-view placement did not allowforequivalentexaminationofthisregionacrossparticipants.
Therefore, the current study could not address the impact of cannabisuseoncerebellarwhitematterdevelopment.
4. Conclusions
Ourfindingsareconsistentwithcross-sectional DTIresearch indicating that heavy cannabis use is associated with deleteri-ousalterationsinwhitemattermicrostructurewithinmajorfiber tracts,suchasthesuperiorlongitudinalfasciculus,corticospinal tract,andcorpuscallosum.Ourlongitudinalstudydesignextends theexistingliteraturebyassessingwhitemattermicrostructural changeinthecontextofcontinuingregularcannabisuseby high-functioning,non-treatment-seekingyoungadultswhowerefree ofcomorbiditiesotherthanalcoholuse.Thisdesignallowedusto distinguisha smallnumberofbaseline DTIdifferences between CUsandnon-usingcontrolsfromalargernumberofgroup differ-encesinFAandRDchangeovertime.Thesedifferencessuggest aberrantpatternsofneurodevelopmentasaconsequenceofheavy cannabisusegiventhatseveralDTIindicatorsofdisruptedwhite matterdevelopmentwerecorrelatedinadose-dependentpattern withthequantityandfrequencyofcannabisuse.Thesedistributed alterationsinwhitematterfiberdevelopmentmayunderliethe inefficient functional MRI activation patterns shown by heavy cannabisusers,aswellastheirdeficitsincomplexcognitionand effortfulprocessing.
Conflictofinterest
Theauthorsreportnoconflictsofinterest. Acknowledgements
Thiswork wassupported bythe NationalInstitute onDrug AbuseunderGrantR01DA017843awardedtoM.Luciana,bythe NationalInstituteonAlcoholAbuseandAlcoholismunderGrant R01AA020033awardedtoM.Luciana,andbyBTRCP41EB015894 andP30NS076408grantsawardedtotheUniversityofMinnesota’s CenterforMagneticResonanceResearch.Supportfromthe Univer-sityofMinnesota’sCenterforNeurobehavioralDevelopmentand theMinnesotaSupercomputingInstituteisalsogratefully acknowl-edged.
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