{"id":4039,"date":"2009-08-07T11:45:45","date_gmt":"2009-08-07T10:45:45","guid":{"rendered":"https:\/\/drugprevent.org.uk\/ppp\/?p=4039"},"modified":"2009-08-08T13:58:11","modified_gmt":"2009-08-08T12:58:11","slug":"regional-brain-abnormalities-associated","status":"publish","type":"post","link":"https:\/\/drugprevent.org.uk\/ppp\/2009\/08\/regional-brain-abnormalities-associated\/","title":{"rendered":"Regional Brain Abnormalities Associated"},"content":{"rendered":"
Context:<\/strong> Cannabis is the most widely used illicit drug
\nin the developed world. Despite this, there is a paucity
\nof research examining its long-term effect on the human
\nbrain.<\/span><\/div>\n
Objective:<\/strong> To determine whether long-term heavy cannabis
\nuse is associated with gross anatomical abnormalities
\nin 2 cannabinoid receptor\u2013rich regions of the brain,
\nthe hippocampus and the amygdala.
\nDesign: Cross-sectional design using high-resolution
\n(3-T) structural magnetic resonance imaging.
\nSetting: Participants were recruited from the general
\ncommunity and underwent imaging at a hospital research
\nfacility.
\nParticipants:<\/strong> Fifteen carefully selected long-term (_10
\nyears) and heavy (_5 joints daily) cannabis-using men
\n(mean age, 39.8 years; mean duration of regular use, 19.7
\nyears) with no history of polydrug abuse or neurologic\/
\nmental disorder and 16 matched nonusing control subjects
\n(mean age, 36.4 years).
\nMain Outcome Measures:<\/strong> Volumetric measures of
\nthe hippocampus and the amygdala combined with measures
\nof cannabis use. Subthreshold psychotic symptoms
\nand verbal learning ability were also measured.
\nResults: Cannabis users had bilaterally reduced hippocampal
\nand amygdala volumes (P=.001), with a relatively
\n(and significantly [P=.02]) greater magnitude of
\nreduction in the former (12.0% vs 7.1%). Left hemisphere
\nhippocampal volume was inversely associated with
\ncumulative exposure to cannabis during the previous 10
\nyears (P=.01) and subthreshold positive psychotic symptoms
\n(P_.001). Positive symptom scores were also associated
\nwith cumulative exposure to cannabis (P=.048).
\nAlthough cannabis users performed significantly worse
\nthan controls on verbal learning (P_.001), this did not
\ncorrelate with regional brain volumes in either group.
\nConclusions: These results provide new evidence of exposure-
\nrelated structural abnormalities in the hippocampus
\nand amygdala in long-term heavy cannabis users and
\ncorroborate similar findings in the animal literature. These
\nfindings indicate that heavy daily cannabis use across protracted
\nperiods exerts harmful effects on brain tissue and
\nmental health.
\nArch Gen Psychiatry. 2008;65(6):694-701<\/span><\/div>\n
THERE IS CONFLICTING
\nevidence regarding the
\nlong-term effects of regular
\ncannabis use. Although
\ngrowing literature suggests
\nthat long-term cannabis use is associated
\nwith a wide range of adverse health
\nconsequences,1-4 many people in the community,
\nas well as cannabis users themselves,
\nbelieve that cannabis is relatively
\nharmless and should be legally available.
\nWith nearly 15 million Americans using
\ncannabis in a given month, 3.4 million
\nusing cannabis daily for 12 months or
\nmore, and 2.1 million commencing use every
\nyear,5 there is a clear need to conduct
\nrobust investigations that elucidate the
\nlong-term sequelae of long-term cannabis
\nuse.
\nThe strongest evidence against the notion
\nthat cannabis is harmless comes from
\nthe animal literature6-9 in which longterm
\ncannabinoid administration has been
\nshown to induce neurotoxic changes in the
\nhippocampus, including decreases in neuronal
\nvolume, neuronal and synaptic density,
\nand dendritic length of CA3 pyramidal
\nneurons. Although such work suggests
\nthat exposure to cannabinoids may be neurotoxic
\nin animals, much less is known
\nabout the neurobiologic consequences of
\nlong-term cannabis exposure in humans.
\nOnly a handful of brain imaging studies
\nhave been conducted in human cannabis
\nusers, with inconsistent findings reported.
\nEarly cannabis research using
\npneumoencephalography10 reported cerebral
\natrophy in a small sample (N=10)
\nof cannabis users, but further studies using
\ncomputed tomography11-13 did not detect
\nany abnormalities, despite the potential
\nconfounds of polydrug use, comorbid neurologic\/
\npsychiatric diagnoses, and a lack
\nof appropriate comparison groups.<\/span><\/div>\n

More Author Affiliations: ORYGEN
\nResearch Centre (Drs Yu\u00a8 cel,
\nWhittle, and Lubman) and
\nMelbourne Neuropsychiatry
\nCentre, Department of
\nPsychiatry, The University of
\nMelbourne and Melbourne
\nHealth (Drs Yu\u00a8 cel, Whittle,
\nFornito, and Pantelis),
\nMelbourne, Australia; School of
\nPsychology and Illawarra
\nInstitute for Mental Health,
\nUniversity of Wollongong,
\nWollongong, Australia
\n(Dr Solowij and
\nMs Respondek); and
\nSchizophrenia Research
\nInstitute, Sydney, Australia
\n(Dr Solowij).
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recent structural magnetic resonance imaging (MRI) studies
\nhave also reported contradictory findings, ranging from
\nno global or regional changes in brain tissue volume or
\ncomposition14-16 to gray and white matter density changes,
\neither globally17 or in focal regions, most notably in the
\nhippocampal and parahippocampal areas.18,19 However,
\nthese previous studies used imaging techniques with relatively
\ncoarse spatial and anatomical resolution and typically
\nfocused on samples with multiple substance use or
\ncomorbid psychiatric disorders and on only moderate levels
\nof cannabis use (ie, _2 joints per day). Indeed, despite
\nstrong evidence of neurotoxicity in the animal literature,
\n6-9 to our knowledge, no neuroimaging study has
\nexamined the neurobiologic sequelae of long-term heavy
\ncannabis use while controlling for the important confounds
\nof polydrug abuse and co-occurring psychiatric
\ndisorders.
\nIn this study, we used high-resolution 3-T MRI to assess
\nvolumetric changes in 2 cannabinoid-rich regions
\nof the brain (the hippocampus and the amygdala) known
\nto be susceptible to the neurotoxic effects of cannabis exposure
\nin a sample of long-term heavy users carefully
\nscreened for polysubstance abuse and mental disorders.
\nGiven the growing literature regarding an association between
\ncannabis use and the development of psychosis20
\nand cognitive impairment,16,21 we also assessed for subthreshold
\npsychotic symptoms and verbal learning ability
\nin this otherwise psychologically healthy sample.
\nMETHODS
\nPARTICIPANTS
\nMale cannabis users with long histories of regular and heavy
\ncannabis use (n=15) and nonusing healthy male volunteers
\n(n=16) matched on age, estimated premorbid intelligence (National
\nAdult Reading Test),22 years of education, and state and
\ntrait anxiety (Spielberger State-Trait Anxiety Inventory)23 were
\nrecruited from the general community via a variety of advertisements
\n(Table). Cannabis users had lower Global Assessment
\nof Functioning scale scores and greater depressive symptoms
\n(as measured using the Hamilton Depression Rating Scale)24
\nthan the comparison group; however, there were no current
\nor lifetime histories of diagnosable medical, neurologic, or psychiatric
\nconditions as assessed using the Structured Clinical Interview
\nfor DSM-IV Axis I Disorders, Patient Edition.25 All the
\ncontrol subjects also underwent a Structured Clinical Interview
\nfor DSM-IV Axis I Disorders, Non-Patient Edition.25 Subthreshold
\npsychotic symptoms were probed using the Scale for the
\nAssessment of Positive Symptoms26 and the Scale for the Assessment
\nof Negative Symptoms.27 Regarding alcohol use, the
\ngroups did not differ in levels of current consumption, lifetime
\nuse, or history of abuse or dependence; and no participant
\ndrank more than 24 standard alcoholic drinks per week.
\nSignificantly more cannabis users were also tobacco smokers
\n(_2=22.9, P_.001) (Table). For all users, cannabis was the primary
\ndrug of abuse, with only limited experimental use of other
\nillicit drugs (generally _10 lifetime episodes).
\nPROCEDURE
\nParticipants were assessed on 2 occasions, usually 1 week apart.
\nIn the first test session, participants completed demographic,
\nclinical, and substance use history assessments. In the second
\ntest session, they completed the Rey Auditory Verbal Learning
\nTest (RAVLT) and underwent structural MRI.
\nParticipants were asked to abstain from using substances for
\nat least 12 hours before each test session, and cannabis users
\nreported abstaining from cannabis for a mean of 21.3 hours before
\nthe first test session (median, 14 hours; range, 10-72 hours)
\nand a mean of 19.8 hours before the second test session (median,
\n17 hours; range, 12-48 hours). Urine samples were obtained
\nfrom users on 4 occasions and from controls on 2 occasions
\nto corroborate self-reported abstinence. Specifically, for
\ncannabis users, samples were obtained on the evening before
\neach test session and on the day of testing. For controls, samples
\nwere collected only on the day of testing. Examination of these
\nsamples demonstrated that all but 1 cannabis user had cannabinoid
\nmetabolites (11-nor-_9-tetrahydrocannabinol-9-
\ncarboxylic acid creatinine normalized) detected in urine samples
\nfrom the first test session, and levels were generally high
\n(evening: median, 467 ng\/mg [range, 0-2320 ng\/mg]; day of
\ntesting: median, 447 ng\/mg [range, 0-11 293 ng\/mg]). From the
\nsecond test session, 2 users returned a 0 reading; otherwise,
\ncannabinoid metabolite levels were again high (evening: median,
\n456 ng\/mg [range, 0-3511 ng\/mg]; day of testing: median,
\n389 ng\/mg [range, 0-4470 ng\/mg]). The levels of urinary
\ncannabinoid metabolites generally corroborate the selfreported
\npatterns of heavy cannabis use in the sample. All but
\n2 control subjects returned a 0 reading for cannabinoid metabolites
\nacross both test sessions. The 2 controls with positive
\nurine samples reported only minimal and very occasional
\nexposure to cannabis. The median level of cannabinoid metabolites
\nin controls at the first test session was 0 ng\/mg (range,
\n0-184 ng\/mg) and at the second test session was 0 ng\/mg (range,
\n0-180 ng\/mg).
\nSTRUCTURAL MRI
\nThe MRI data were obtained using a 3-T scanner (Intera; Phillips
\nMedical Systems NA, Bothell, Washington) at the Symbion
\nClinical Research Imaging Centre, Prince of Wales Medical
\nResearch Institute, Sydney. A 3-dimensional volumetric
\nspoiled gradient\u2013recalled echo sequence generated 180 contiguous
\ncoronal slices. The imaging parameters were as follows:
\necho time, 2.9 milliseconds; repetition time, 6.4 milliseconds;
\nflip angle, 8\u00b0; matrix size, 256_256; and 1-mm3 voxels.
\nHippocampal, amygdala, whole brain, and intracranial volumes
\nwere measured using established reliable protocols28-31
\nand were delineated by a trained rater (S.W.) masked to group
\ninformation. Specifically, the hippocampal boundaries were as
\nfollows: posterior, the slice with the greatest length of continuous
\nfornix; medial, the open end of the hippocampal fissure
\nposteriorly, the uncal fissure in the hippocampal body, and the
\nmedial aspect of the ambient gyrus anteriorly; lateral, the temporal
\nhorn of the lateral ventricle; inferior, the white matter inferior
\nto the hippocampus; superior, the superior border of the
\nhippocampus; and anterior, the alveus was used to differentiate
\nthe hippocampal head from the amygdala. The anterior border
\nwas the most difficult to identify consistently and was aided
\nby moving between slices before and after the index slice. The
\namygdala boundaries were as follows: posterior, the appearance
\nof amygdala gray matter above the temporal horn; superolateral,
\nthe thin strip of white matter that separates the amygdala
\nfrom the claustrum and the tail of the caudate; medial, the
\nangular bundle, which separates the amygdala from the entorhinal
\ncortex; superomedial, the semilunar gyrus; inferior, the
\nhippocampus; inferolateral, the temporal lobe white matter and
\nthe extension of the temporal horn; and anterior, the slice anterior
\nto the appearance of the optic chiasm. Whole brain volumes
\nwere estimated using the Brain Extraction Tool method32
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\nto separate brain from nonbrain tissue. After brain\/nonbrain
\nsegmentation, each voxel was classified into gray matter, white
\nmatter, or cerebrospinal fluid using FAST Model statistical software.
\n33 Only gray and white matter were used in the estimate
\nof whole brain volumes. The intracranial cavity was delineated
\nfrom a sagittal reformat of the original 3-dimensional data
\nset. The major anatomical boundary was the dura mater below
\nthe inner table, which was generally visible as a white line.
\nWhere the dura mater was not visible, the cerebral contour was
\noutlined. Other landmarks included the undersurfaces of the
\nfrontal lobes, the dorsum sellae, the clivus, and the posterior
\narch of the craniovertebral junction.
\nInterrater and intrarater reliabilities were assessed by means
\nof the intraclass correlation coefficient (ICC) (absolute agreement)
\nusing 15 brain images from a separate MRI database established
\nspecifically for this purpose and that has previously
\nbeen delineated by another expert rater. For the hippocampus,
\ninterrater ICC reliabilities were 0.92 (right) and 0.91 (left)
\nand intrarater ICC reliabilities were 0.98 (right) and 0.95 (left).
\nFor the amygdala, interrater ICC reliabilities were 0.85 (right)
\nand 0.88 (left) and intrarater ICC reliabilities were 0.93 (right)
\nand 0.97 (left). Once reliability was established, the rater (S.W.)
\ndelineated the regions of interest for the images acquired from
\nthe present study.
\nSTATISTICAL ANALYSES
\nWhole brain volume, age, educational level, and estimated IQ
\nwere not significantly different between the 2 groups and were,
\ntherefore, not used as covariates (Table). Regional gray matter
\nvolumes for the hippocampus and amygdala were corrected for
\nthe effect of the intracranial cavity using a previously described
\nformula34 and were analyzed using analyses of variance,
\nwith hemisphere (left or right) and region (hippocampus
\nand amygdala) as within-subject factors and group as the
\nbetween-subject factor. Main effects and interactions were evalu-
\nTable. Demographic, Clinical, Drug Use, and MRI Volumetric Measures
\nMeasure
\nLong-term Cannabis Users
\n(n=15)
\nNonusing Control Subjects
\n(n=16) P Valuea
\nAge, mean (SD), y 39.8 (8.9) 36.4 (9.8) .31
\nIQ, mean (SD) 109.2 (6.3) 113.9 (8.1) .09
\nRAVLT score, mean (SD)
\nSum of 5 learning trials 43.8 (8.8) 57.4 (10.1) _.001
\n20-min delay 8.9 (4.1) 12.3 (3.7) .009b
\nEducational level, mean (SD), y 13.4 (3.2) 14.8 (3.7) .28
\nGAF scale score, mean (SD) 72.0 (11.2) 80.8 (9.4) .02
\nHAM-D score, mean (SD) 5.87 (3.2) 2.56 (1.9) _.001b
\nSTAI, mean (SD)
\nState anxiety 34.3 (9.8) 32.9 (9.4) .67
\nTrait anxiety 39.3 (9.7) 39.0 (8.2) .92
\nSAPS score, mean (SD) 8.1 (7.9) 0.6 (1.2) _.001b
\nSANS score, mean (SD) 11.7 (8.5) 1.4 (1.4) _.001b
\nCannabis use
\nDuration of regular use, mean (SD) [range], yc 19.7 (7.3) [10-32] NA NA
\nAge started regular use, mean (SD) [range], yc 20.1 (6.9) [12-34] NA NA
\nCurrent use, mean (SD), d\/mod 28 (4.6) NA NA
\nCurrent use, mean (SD), cones\/mod,e 636 (565) NA NA
\nCumulative exposure, past 10 y, mean (SD)f 77 816 (66 542) NA NA
\nCumulative exposure, lifetime, mean (SD)f 186 184 (210 022) 12.7 (12.2) _.001
\nEstimated episodes of use, median (range) 62 000 (4600-288 000) 11 (0-30) _.001
\nAlcohol use, mean (SD), standard drinks\/wk 9.6 (6.1) 6.8 (5.0) .19
\nTobacco use, mean (SD), cigarettes\/d 16.5 (8.9) 7.5 (9.2) .20
\nBrain volumes, mean (SD), mm3
\nIntracranial cavity 1 546 237 (94 018) 1 607 590 (136 386) .14
\nWhole brain 1 310 780 (90 778) 1 374 123 (105 673) .09
\nHippocampus .002g
\nLeft hemisphere 2849 (270) 3240 (423)
\nRight hemisphere 2949 (244) 3348 (400)
\nAmygdala .01g
\nLeft hemisphere 1766 (98) 1878 (190)
\nRight hemisphere 1601 (143) 1744 (158)
\nAbbreviations: GAF, Global Assessment of Functioning; HAM-D, Hamilton Depression Rating Scale; MRI, magnetic resonance imaging; NA, not applicable;
\nRAVLT, Rey Auditory Verbal Learning Test; SAPS, Scale for the Assessment of Positive Symptoms; SANS, Scale for the Assessment of Negative Symptoms;
\nSTAI, State-Trait Anxiety Inventory.
\naTwo-tailed t test unless otherwise indicated.
\nbMann-Whitney test.
\ncRegular use was defined as at least twice a month.
\ndCannabis users had used at this level for most of their drug-using history.
\neA cone is the small funnel into which cannabis is packed to consume through a water pipe in a single inhalation. Without the loss of sidestream smoke, the
\nquantity of tetrahydrocannabinol delivered by this method is estimated as equating 3 cones to 1 cigarette-sized joint. Thus, the cannabis users in this study
\nsmoked the equivalent of 212 joints per month, or approximately 7 joints per day.
\nfExpressed as cones for users and as episodes for controls. Estimates of lifetime exposure beyond 10 years in these very long-term users became skewed and
\nunreliable; hence, the 10-year estimate was used in correlational analyses.
\ngRegion_group analysis of variance.
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\nated using Greenhouse-Geisser\u2013corrected degrees of freedom,
\nwith _=.05. Effect sizes, expressed as Cohen d, are also reported
\nfor pairwise contrasts. Only effects involving group (cannabis
\nusers vs nonusers) and associations with cannabis use
\nparameters are reported because this was the primary focus of
\nthe present study. Group comparisons of performance on the
\nRAVLT and measures of subthreshold psychotic symptoms
\n(using the Scale for the Assessment of Positive Symptoms and
\nthe Scale for the Assessment of Negative Symptoms) were conducted
\nusing independent-samples t tests or Mann-Whitney tests
\nfor nonnormally distributed data. Pearson product moment correlational
\nanalyses were conducted to examine the behavioral
\n(ie, symptom and cognitive) relevance of any identified group
\ndifferences in regional brain volumes and the association
\nbetween these brain changes and parameters of cannabis use.
\nThese analyses were necessarily exploratory given the limited
\nsample size.
\nRESULTS
\nGROUP CONTRASTS
\nIn the analysis of regional gray matter volumes, there
\nwas a significant main effect of group (F1,29=12.98,
\nP=.001) and a region_group interaction (F1,29=6.25,
\nP=.02). This result and the post hoc pairwise analyses
\ndemonstrated reduced hippocampal volumes in cannabis
\nusers (F1,29=11.14, P=.002 corrected; a reduction of
\n12.1% in the left and 11.9% in the right hippocampus
\nrelative to controls), with a very large effect size (Cohen
\nd: left hippocampus, 1.17; and right hippocampus,
\n1.27) (Figure 1). Cannabis users also had smaller
\namygdala volumes (F1,29=7.31, P=.01 corrected; a
\nreduction of 6.0% in the left amygdala and 8.2% in the
\nright amygdala relative to controls), with large effect
\nsizes (Cohen d: left amygdala, 0.80; and right amygdala,
\n0.99). The region _ group interaction reflects that the
\noverall reduction in hippocampal volume was relatively
\n(and significantly) greater than the reduction in amygdala
\nvolume (12.0% in the hippocampus vs 7.1% in the
\namygdala). In the analysis of subthreshold psychotic
\nsymptoms, cannabis users reported significantly higher
\npositive symptoms (Scale for the Assessment of Positive
\nSymptoms; z=\u22123.57, P_.001) and negative symptoms
\n(Scale for the Assessment of Negative Symptoms;
\nz=\u22123.66, P_.001) than nonusing controls. Regarding
\nverbal learning, cannabis users displayed significantly
\npoorer performance than controls on the RAVLT measures
\n(sum of words recalled across the 5 learning trials:
\nz=\u22123.97, P_.001; and free recall after a 20-minute
\ndelay: z=\u22122.61, P=.009).
\nCORRELATIONAL ANALYSES
\nThere was a significant inverse association between left
\nhippocampal volume and cumulative cannabis exposure
\nduring the previous 10 years (r=\u22120.62, P=.01; accounting
\nfor 38% of the variance in left hippocampal volume)
\n(Figure 2A). When 1 participant with relatively
\nhigher cumulative cannabis exposure and small hippocampal
\nvolume was excluded, 22% of the variance was
\nstill accounted for despite falling short of significance in
\nthe reduced sample (r=\u22120.47, P=.09). There was also an
\nassociation between left hippocampal volume and positive
\nsymptoms (r=\u22120.77, P_.001) (Figure 2B) and between
\npositive symptoms and cumulative cannabis exposure
\n(r=0.52, P=.048) (Figure 2C). The associations
\nbetween left hippocampal volume and cumulative cannabis
\nexposure and between left hippocampal volume and
\npositive symptoms remained after controlling for the effects
\nof global functioning (Global Assessment of Functioning
\nscale) and depressive symptoms (Hamilton Depression
\nRating Scale). No other associations were found
\nbetween other brain volumetric measures, cannabis use,
\nand psychotic symptoms, and they did not vary as a function
\nof alcohol or tobacco use. Measures of RAVLT performance
\ndid not correlate with hippocampal or amygdala
\nvolumes in either controls or cannabis users.
\nCOMMENT
\nTo our knowledge, this is the first human study of longterm
\nheavy cannabis users to demonstrate marked
\nexposure-related hippocampal volume reductions.
\nThese findings corroborate previous animal research,6-9
\nsuggesting that long-term heavy cannabis use is associated
\nwith significant and localized hippocampal volume
\nreductions that relate to increasing cumulative cannabis
\nexposure. In addition, the present findings are consis-
\ntent with the view that cannabis use increases the risk
\nof psychotic symptoms and informs the debate concerning
\nthe potential long-term hazardous effects of cannabis
\nin this regard. The bilateral reduction in amygdala
\nvolume is a novel but not unexpected finding given the
\ndense concentration of cannabinoid receptors in this
\nregion.35
\nAlthough these findings are consistent with those of
\na previous study,18 it is difficult to directly compare these
\nresults with those of other human studies given that past
\nwork used MRI with lower magnetic field strength and
\nspatial resolution and did not conduct region-of-interest\u2013
\nbased analyses (eg, performed whole-brain voxel-based
\nanalyses18). Tzilos et al14 conducted the only other study,
\nto our knowledge, that investigated cannabis users with
\na relatively long history of use (specifically, an average
\nduration of use of 22.6 years, or 18.9 years of daily use)
\nand their study is, therefore, most comparable with the
\npresent study. Although they found no effects of longterm
\ncannabis use on hippocampal volume, the authors
\nacquired their images at a lower field strength and with
\na coarser spatial resolution (1.5 T with 3-mm-thick slices
\nvs 3 T with 1-mm-thick slices in the present study), an
\nimportant consideration given the size of the brain structures
\ninvestigated. Moreover, their region of interest was
\nless specific to the hippocampus relative to the present
\nmeasure because they also included the parahippocampal
\ngyrus. Furthermore, there was a relatively large age
\ndiscrepancy between their users and controls (38.1 vs 29.5
\nyears), and the minimum duration of exposure to cannabis
\nwas considerably lower in their sample (as little as
\n1 year of cannabis exposure), but, overall, their sample
\nreported an average of 20 100 lifetime episodes of use.
\nIn contrast, the minimum duration of exposure to cannabis
\nin the present sample was 10 years, with an average
\nof 62 000 episodes of use. Thus, despite a similar mean
\nduration of use, the present sample used more than 3 times
\nas much cannabis, which may explain the finding of a
\ndose-response relationship between hippocampal volume
\nand cumulative cannabis use. Further highresolution
\nMRI work is necessary to characterize precisely
\nthe dosage of cannabis required for significant brain
\nchanges to occur.
\nThe pattern of use in the present sample is consistent
\nwith heavy cannabis use patterns that have previously
\nbeen reported in other Australian studies. For example,
\nCopeland and colleagues36 reported median daily intake
\nof 8 cones (the small funnel into which cannabis is packed
\nto consume through a water pipe in a single inhalation)
\nin an Australian sample of cannabis users seeking treatment
\nfor cannabis dependence, ranging up to 125 cones
\nper day in the heaviest user, with 11% reporting cannabis
\nsmoking throughout the day. The heaviest user herein
\nreported smoking 80 cones per day (approximately 25
\njoints smoked throughout the day). This pattern of cannabis
\nuse is not dissimilar to the heaviest cannabis users
\nfrom other studies of non\u2013treatment-seeking samples of
\nAustralian cannabis users.37,38
\nDespite the large magnitude of effects observed, it remains
\nunclear whether these volumetric reductions
\nreflect neuronal or glial loss, a change in cell size, or a
\nreduction in synaptic density (eg, dendritic arborization),
\nall of which have been reported in rodent studies.
\n6-9 For example, Scallet and colleagues9 found striking
\ntetrahydrocannabinol-induced residual decreases in
\nthe mean volume of hippocampal neurons and their nuclei
\nand a 44% reduction in the number of synapses up
\nto 7 months after the last exposure to tetrahydrocannabinol.
\nMoreover, Landfield and colleagues7 administered
\ntetrahydrocannabinol 5 times a week for 8 months
\n(approximately 30% of the rat lifespan, and comparable
\nin frequency and duration to the present sample) and
\nfound significant tetrahydrocannabinol-induced decreases
\nin neuronal density in the hippocampus. Such
\nfindings may help explain the mechanisms underlying
\ngross hippocampal and amygdala volume loss seen in this
\nsample of long-term heavy cannabis users.
\nLeft Hippocampal Volume, mm3
\nIn the present study, hippocampal volume in the cannabis-
\nusing group was inversely correlated with cumulative
\nexposure to the drug in the left, but not right, hemisphere.
\nPrevious functional imaging studies16,39 have found
\nreduced left hippocampal activation during cognitive performance
\nin cannabis users, and there is evidence to suggest
\nthat hippocampal abnormalities in psychiatric disorders
\nsuch as schizophrenia are more prominent in the
\nleft hemisphere.40 These findings converge to suggest that
\nthe left hippocampus may be particularly vulnerable to
\nthe effects of cannabis exposure and may be more closely
\nrelated to the emergence of psychotic symptoms. In this
\ncontext, it is interesting that we found a significant inverse
\ncorrelation between left hippocampal volume and
\npositive symptoms. Cannabis use was also positively correlated
\nwith positive symptoms, suggesting that there are
\ncomplex associations among exposure to cannabis, hippocampal
\nvolume reductions, and psychotic symptoms.
\nGiven these relationships, it is possible that the exposurerelated
\nhippocampal reduction may reflect heavy cannabis
\nuse in response to preexisting or developing psychotic
\nsymptoms. However, there is limited empirical
\nsupport for long-term self-medication of subthreshold psychotic
\nsymptoms with cannabis and stronger support for
\nthe induction of psychotic symptoms subsequent to cannabis
\nexposure.20 As such, it seems more likely that prolonged
\nheavy use of cannabis induced subthreshold psychotic
\nsymptoms and that both of these factors are
\nassociated with hippocampal volume loss. These symptoms
\nwere subthreshold because these cannabis-using participants
\nwere carefully screened for current and past history
\nof mental disorders. Furthermore, the fact that the
\nmean age of the present cannabis-using sample was nearly
\n40 years suggests that these symptoms are unlikely to reflect
\na prodrome. One speculation is that the present participants
\nwere less genetically vulnerable to developing
\na psychotic disorder subsequent to cannabis use,41,42 allowing
\nthem to smoke heavily for many years. Future longitudinal
\nwork assessing the emergence of hippocampal
\nreductions and psychotic symptoms with continued exposure
\nto cannabis, and how these are related to polymorphic
\nvariations in susceptibility genes for psychotic
\ndisorders, will prove useful in better characterizing these
\nrelationships.
\nGiven that cannabis users had significantly greater depressive
\nsymptom scores than controls and that there is
\nan association between depression and hippocampal volume
\nreduction,43 it could also be argued that depressive
\nsymptoms may be another mediating factor in the relationship
\nbetween cannabis use and hippocampal volume
\nreduction. However, there are a variety of important
\nconsiderations that make this unlikely. First, there
\nwas no significant association between hippocampal volumes
\nand depressive symptom scores. Second, the relationship
\nbetween left hippocampal volume and quantity
\nof cannabis used was maintained after statistically
\ncontrolling for depressive symptoms. Finally, the overwhelming
\nevidence suggests that hippocampal reductions
\nin major depressive disorder tend to occur in the
\nmore persistent forms of the disorder (eg, multiple episodes,
\nrepeated relapses, or long illness duration).43,44 This
\nwas not the case in the present sample of cannabis users,
\nwho scored less than 6.0 on the Hamilton Depression
\nRating Scale, had never been diagnosed as having
\nmajor depression, and did not seek treatment for any depressive
\ndisorder.
\nCannabis users showed poorer performance on measures
\nof verbal learning, consistent with previous findings.
\nAlthough some functional imaging studies have
\nfound reduced left hippocampal blood flow and activation
\nduring verbal (and visual) learning tasks in cannabis
\nusers, we found no correlation between RAVLT
\nperformance measures and hippocampal volume in either
\ncontrols or cannabis users. It is likely that anatomical volume
\nis a less sensitive measure than brain activation for
\nidentifying correlations with behavioral performance. This
\nis a particularly pertinent consideration given that the
\nperformance measures on the RAVLT are likely to reflect
\nthe operation of numerous cognitive processes not
\nnecessarily related to hippocampal function. Future work
\nusing experimental tasks designed to more specifically
\nprobe memory functions mediated by the hippocampus
\nmay be useful in this regard.
\nThe bilateral reduction in amygdala volume is a novel
\nbut not unexpected finding given the dense concentration
\nof cannabinoid receptors in this region.35 There were
\nno cognitive, psychotic, or depressive symptom associations
\nwith reduced volume in the amygdala. However,
\nthis region has been significantly implicated in cannabinoid-
\nassociated emotional and reward-related learning
\nand memory processes.47,48 Given that these aspects of
\nlearning have not been examined in human cannabis users,
\nthey would seem to serve as a potentially informative
\navenue forward to help elucidate the functional relevance
\nof such volumetric reduction in the amygdala.
\nThe relationship between long-term cannabis use and
\nbrain abnormalities is complex. Although a limitation of
\nthis study may be the residual effects of cannabis in light
\nof the fact that the cannabis users in this study were required
\nto be cannabis free for only 12 to 24 hours before
\nMRI, such issues are likely to be more pertinent for studies
\nexamining more dynamic aspects of brain functioning
\n(eg, activations and cognition).49 The present structural
\nfindings are unlikely to relate to the recent effects
\nof cannabis use because we are unaware of any evidence
\nthat suggests that the hippocampus and amygdala can
\nchange in volume by 6% to 12% in short periods. However,
\nalthough we maintain that the present results reflect
\nbrain changes associated with long-term heavy cannabis
\nuse rather than the consequences of recent exposure,
\nfurther longitudinal work is required to assess whether
\nsuch changes are reversible across more protracted periods
\nof abstinence.
\nAnother limitation of this study is the relatively small
\nsample size, although the sample was exceptionally unique
\nin that participants were very long-term and heavy cannabis
\nusers (mean of 5-7 joints per day for _10 years)
\nwithout polydrug use or co-occurring neurologic or diagnosable
\nmental disorders. As such, we conducted the
\nfirst, to our knowledge, \u201cpure\u201d examination of the effects
\nof heavy and protracted exposure to cannabis in humans.
\nThe large effect sizes of the main findings suggest
\nthat these results are robust and reproducible. These findings
\nare further strengthened by the observed dose-
\nresponse relationships between hippocampal volume reductions
\nand cumulative cannabis use.
\nThere is ongoing controversy concerning the longterm
\neffects of cannabis on the brain.\u00a0 These findings
\nchallenge the widespread perception of cannabis as having
\nlimited or no neuroanatomical sequelae. Although
\nmodest use may not lead to significant neurotoxic effects,
\nthese results suggest that heavy daily use might indeed
\nbe toxic to human brain tissue. Further prospective,
\nlongitudinal research is required to determine the
\ndegree and mechanisms of long-term cannabis-related
\nharm and the time course of neuronal recovery after abstinence.
\nCorrespondence: MuratYu\u00a8 cel, PhD,MAPS,ORYGENResearch
\nCentre, 35 Poplar Rd (Locked Bag 10), Melbourne,<\/p>\n

Murat Yu\u00a8 cel, PhD, MAPS; Nadia Solowij, PhD; Colleen Respondek, BSc; Sarah Whittle, PhD; Alex Fornito, PhD;
\nChristos Pantelis, MD, MRCPsych, FRANZCP; Dan I. Lubman, MB ChB, PhD, FRANZCP
\nSource: Arch.Gen.Psychiatry.\u00a0 Vol.65\u00a0 June 2008<\/em><\/span><\/div>\n
\u00a0<\/span><\/div>\n

\u00a0<\/p>\n

<\/span><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Context: Cannabis is the most widely used illicit drug in the developed world. Despite this, there is a paucity of research examining its long-term effect on the human brain. Objective: To determine whether long-term heavy cannabis use is associated with gross anatomical abnormalities in 2 cannabinoid receptor\u2013rich regions of the brain, the hippocampus and the […]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[22],"tags":[],"class_list":["post-4039","post","type-post","status-publish","format-standard","hentry","category-effects-of-drugs-papers"],"_links":{"self":[{"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/posts\/4039","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/comments?post=4039"}],"version-history":[{"count":0,"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/posts\/4039\/revisions"}],"wp:attachment":[{"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/media?parent=4039"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/categories?post=4039"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/drugprevent.org.uk\/ppp\/wp-json\/wp\/v2\/tags?post=4039"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}