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Multimodal neuroimaging of frontal white matter microstructure in early phase schizophrenia: The impact of early adolescent cannabis use

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A disturbance in connectivity between different brain regions, rather than abnormalities within the separate regions themselves, could be responsible for the clinical symptoms and cognitive dysfunctions observed in schizophrenia. White matter, which comprises axons and their myelin sheaths, provides the physical foundation for functional connectivity in the brain. Myelin sheaths are located around the axons and provide insulation through the lipid membranes of oligodendrocytes. Empirical data suggests oligodendroglial dysfunction in schizophrenia, based on findings of abnormal myelin maintenance and repair in regions of deep white matter. The aim of this in vivo neuroimaging project is to assess the impact of early adolescent onset of regular cannabis use on brain white matter tissue integrity, and to differentiate this impact from the white matter abnormalities associated with schizophrenia. The ultimate goal is to determine the liability of early adolescent use of cannabis on brain white matter, in a vulnerable brain.Methods/design: Young adults with schizophrenia at the early stage of the illness (less than 5 years since diagnosis) will be the focus of this project. Four magnetic resonance imaging measurements will be used to assess different cellular aspects of white matter: a) diffusion tensor imaging, b) localized proton magnetic resonance spectroscopy with a focus on the neurochemical N-acetylaspartate, c) the transverse relaxation time constants of regional tissue water, d) and of N-acetylaspartate. These four neuroimaging indices will be assessed within the same brain region of interest, that is, a large white matter fibre bundle located in the frontal region, the left superior longitudinal fasciculus. We will expand our knowledge regarding current theoretical models of schizophrenia with a more comprehensive multimodal neuroimaging approach to studying the underlying cellular abnormalities of white matter, while taking into consideration the important confounding variable of early adolescent onset of regular cannabis use.
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S T U D Y P R O T O C O L Open Access
Multimodal neuroimaging of frontal white matter
microstructure in early phase schizophrenia: the
impact of early adolescent cannabis use
Denise Bernier
1*
, Jacob Cookey
1
, David McAllindon
1
, Robert Bartha
2
, Christopher C Hanstock
3
, Aaron J Newman
1,4
,
Sherry H Stewart
1,4
and Philip G Tibbo
1,4
Abstract
Background: A disturbance in connectivity between different brain regions, rather than abnormalities within the
separate regions themselves, could be responsible for the clinical symptoms and cognitive dysfunctions observed in
schizophrenia. White matter, which comprises axons and their myelin sheaths, provides the physical foundation for
functional connectivity in the brain. Myelin sheaths are located around the axons and provide insulation through
the lipid membranes of oligodendrocytes. Empirical data suggests oligodendroglial dysfunction in schizophrenia,
based on findings of abnormal myelin maintenance and repair in regions of deep white matter. The aim of this
in vivo neuroimaging project is to assess the impact of early adolescent onset of regular cannabis use on brain
white matter tissue integrity, and to differentiate this impact from the white matter abnormalities associated with
schizophrenia. The ultimate goal is to determine the liability of early adolescent use of cannabis on brain white
matter, in a vulnerable brain.
Methods/Design: Young adults with schizophrenia at the early stage of the illness (less than 5 years since
diagnosis) will be the focus of this project. Four magnetic resonance imaging measurements will be used to assess
different cellular aspects of white matter: a) diffusion tensor imaging, b) localized proton magnetic resonance
spectroscopy with a focus on the neurochemical N-acetylaspartate, c) the transverse relaxation time constants of
regional tissue water, d) and of N-acetylaspartate. These four neuroimaging indices will be assessed within the same
brain region of interest, that is, a large white matter fibre bundle located in the frontal region, the left superior
longitudinal fasciculus.
Discussion: We will expand our knowledge regarding current theoretical models of schizophrenia with a more
comprehensive multimodal neuroimaging approach to studying the underlying cellular abnormalities of white
matter, while taking into consideration the important confounding variable of early adolescent onset of regular
cannabis use.
Keywords: Schizophrenia, Cannabis, White matter, N-acetylaspartate, Oligodendrocytes, Transverse relaxation time
constants, Proton magnetic resonance spectroscopy, Diffusion tensor imaging
* Correspondence: dcbernie@dal.ca
1
Department of Psychiatry, Dalhousie University, 5909 VeteransMemorial
Lane, Abbie J. Lane Building, Room 3030, Halifax B3H 2E2, Nova Scotia,
Canada
Full list of author information is available at the end of the article
© 2013 Bernier et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Bernier et al. BMC Psychiatry 2013, 13:264
http://www.biomedcentral.com/1471-244X/13/264
Background
Rationale
One neurodevelopmental model of schizophrenia [1]
postulates a two-hithypothesis. A first hitis said to
disrupt the trajectory of normal neural development,
rendering the brain vulnerable to a second hitwhich
then precipitates the onset of psychosis. Similarly, an-
other model postulates that an underlying neuropatho-
logical vulnerability is necessary but not sufficient for
the development of the illness, and that full disease ex-
pression may require a trigger such as an environmental
or biological stressor [2]. For both models, early age at
onset of regular cannabis use may represent one possible
second hitor biological stressor associated with full dis-
ease expression [3-5].
There is a growing body of evidence suggesting that a
disturbance in connectivity between different brain regions,
rather than abnormalities within the separate regions
themselves, are responsible for the clinical symptoms and
cognitive dysfunctions observed in schizophrenia [6].
White matter, which comprises axons and their myelin
sheaths, provides the physical foundation for functional
connectivity in the brain; it is therefore increasingly be-
coming a focus of research in order to better understand
the underpinnings of schizophrenia. Myelin sheaths are lo-
cated around the axons and provide insulation through the
lipid membranes of oligodendrocytes [7]. Several different
lines of empirical data [8,9] have suggested oligodendroglial
dysfunction in schizophrenia, based on atypical findings
in terms of myelin maintenance and repair in deep
white matter regions. Observed oligodencrocyte abnor-
malities in schizophrenia consist of more dispersed ar-
rangement and lower densities [10,11], reduced absolute
numbers [10,12,13] as well as aberrant morphology, ne-
crosis and apoptosis along with damaged myelin sheaths
[14,15]. This situation is not likely caused by chronic
antipsychotic medications as these drugs have been
reported to alter the numbers of astrocytes, not of oligo-
dendrocytes [16].
The brain region of interest for this study is the left
superior longitudinal fasciculus (SLF), a large bundle of
white matter fibre tract located in the frontal lobe, trav-
elling between the dorsal prefrontal and caudal-inferior
parietal regions of the brain. Frontal regions undergo
substantial myelination during the periods of adoles-
cence and early adulthood [17,18], especially in the
bilateral SLF [19]. Abnormal maturation of the SLF in
adolescence may thus be crucial in the development
of schizophrenia. Several DTI studies have found ab-
normalities in the SLF in schizophrenia as well as in
asymptomatic cannabis users, as reviewed below. We
will investigate the SLF microstructure in early phase
schizophrenia (less than five years since diagnosis)
[20], focusing on the potential role of early adolescent
onset of regular cannabis, and using neuroimaging
modalities that are sensitive to cellular changes.
Neuroimaging modalities and review of the literature
Diffusion tensor imaging (DTI)
Water diffusion can occur equally in all directions (iso-
tropic diffusion), for example in cerebrospinal fluid where
diffusion is not restricted or in brain tissue where water
diffusion is restricted similarly in all directions (e.g., gray
matter tissue which has a complex cellular structure).
Water diffusion is called anisotropic (preferentially diffus-
ing in one direction) where the brain tissue microstructure
contains fibres that are aligned (e.g., white matter fibre
tracts); in that case, water diffusion will preferentially
occur along the axis of the fibre tracts. An ellipsoid model
of anisotropic water diffusion tensor (describing linear as-
sociations between vectors) can be calculated for each
anatomical voxel (the smallest volumetric unit of brain
images).
DTI is thus an in vivo brain imaging tool that provides
an index of the micro-structural integrity of white mat-
ter tissue [21]. Mean diffusivity (MD) provides a general
measure of water diffusion without differentiating the
direction of diffusivity. Another measure called fractional
anisotropy (FA), when found to be high, will indicate a pre-
ferred direction of water diffusion in the region of interest
[22,23]; when found to be reduced relative to normative
data, it broadly suggests reduced white matter integrity
[24]. Ultrastructural studies directly comparing DTI pa-
rameters with tissue pathology have associated changes in
DTI water diffusivity measures with dysmyelination of
white matter tracts; other tissue alterations that influence
water diffusivity are axonal pathology and changes in cell
densities [24].
There have been over 60 studies using DTI to evaluate
white matter integrity in schizophrenia [25]. The major-
ity of these studies have focussed on chronic schizo-
phrenia and have reported evidence of multiple areas of
white matter disruption most notably in the corpus
callosum, prefrontal white matter, SLF, and cingulum
bundle [26,27]. There have been fewer DTI studies of
early phase schizophrenia. This cohort is however ex-
tremely important, as it allows for the investigation of
pathology core to the illness, with minimal impact of
confounders such as medication, age, and length of time
with illness.
DTI in early phase schizophrenia DTI studies of early
phase schizophrenia have yielded inconsistent findings.
In a review of this literature (2010), it was observed that
for each white matter fibre tract that was found abnor-
mal in the clinical sample relative to the normative sam-
ple, there was at least one other, negative research report
[27]. In more recent studies (20102013), the pattern of
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mixed findings remains, however with fewer reports of
negative findings [28,29] than positive findings [30-38].
Altogether, several different white matter tracts have
been reported as disrupted in schizophrenia at different
stages of the illness, supporting the hypothesis that white
matter deficits could possibly be widespread throughout
the whole brain [29]. In early phase schizophrenia more
specifically, the three white matter tracts most often
implicated are the SLF [31,34,37,39-42], the splenium
of the corpus callosum [31,33,34,39,40,43-45], and the
fronto-occipital fasciculus [25,31,34,37,39,41-43,46].
DTI in cannabis users without schizophrenia Differ-
ent lines of evidence support the assumption that early
cannabis use in a developing (adolescent) brain could be
markedly more damaging than in a more mature brain
(with early usersdefined as those below age 17 years;
[4,47]). In healthy volunteers, a greater detrimental im-
pact of early initiation of regular cannabis use (relative
to a later initiation) has been reported for visual reaction
times [48], cognitive performance [49], and volumetric
brain tissue abnormalities [50].
DTI studies have reported that early adolescent regular
cannabis use in otherwise healthy young adults is associ-
ated with reduced FA values in white matter tracts
involving fronto-temporal connections [51], and with in-
creased mean diffusivity (MD) in the prefrontal section
of the corpus callosum [52]. MD quantifies water diffu-
sion in each voxel and is increased when there is re-
duced white matter integrity. It is thus possible that
early onset cannabis use in adolescence might decrease
white matter structural integrity in otherwise healthy
individuals. The white matter fibre tracts most often
reported as abnormal in cannabis users include the SLF
[51,53-56], the corpus callosum [52,53,57,58], and more
broadly defined temporal [51,53,56,58] and frontal re-
gions [53,54,57].
DTI in cannabis users with schizophrenia A recent re-
view of epidemiological evidence found that onset of
cannabis use in early adolescence is associated with a
particularly increased risk of developing schizophrenia
[47], while the lifetime rate of cannabis use use in adults
with schizophrenia is associated with earlier onset of the
illness [59].
In early adolescent onset of schizophrenia, cannabis-
positive patients showed reduced FA values relative to
cannabis-negative patients in several white matter tracts
including the SLF [34]. In people with first episode psych-
osis, cannabis-naive patients had reduced FA in the corpus
callosum, relative to patients with early onset of cannabis
use and healthy controls [33]. On the other hand, patients
with recent onset schizophrenia and early adolescent can-
nabis use had increased FA values in temporal and frontal
regions, relative to healthy controls; no differences were
found between controls and patients without early adoles-
cent cannabis use [60].
Although some findings go in opposite direction (de-
creased and increased FA values), altogether the empir-
ical DTI data supports the assumption of a greater
detrimental effects of cannabis on an immature brain in
both healthy volunteers and patients with recent onset
schizophrenia. In addition to being a potential second
hitfor psychosis in a vulnerable brain, failure to control
for this confounding variable could underlie the incon-
sistent findings in previous DTI studies of early phase
schizophrenia and would demand for this variable to be
factored into future studies of white matter abnormal-
ities in psychosis.
Proton magnetic resonance spectroscopy (
1
H-MRS)
Another neuroimaging technique that will be used in
this study is
1
H-MRS, which will be acquired from the
same targeted brain region (the left SLF). The neuro-
chemical of interest is N-acetylaspartate (NAA), a free
amino acid that produces the most prominent resonance
in
1
H-MRS of the human brain: a peak located at 2.02
ppm on the spectral profile [61].
In vivo concentration levels of NAA are slightly higher
in white matter relative to gray matter tissue [62]. Post-
mortem studies have demonstrated that NAA is synthe-
sized in neurons, transported into white matter and then
catabolized into aspartate and acetate in oligodendrocytes
via aspartoacylase [63]. NAA catabolism is therefore
closely linked to myelin lipid metabolism, as it provides a
very important source of acetate which is crucial for mye-
lin lipid production and maintenance [64,65].
The assumption of abnormal myelin biosynthesis in
schizophrenia, strongly supported by several different
lines of evidence [8,9,66], can thus be examined by
1
H-
MRS studies as long as the targeted brain region in-
volves a single tissue type (white matter) that allows a
meaningful interpretation of findings in terms of the
catabolic cycle of NAA.
Noteworthy for this study, the cannabinoid receptors
CB1 are present on astrocytes and oligodendrocytes and
may thus be implicated in the detrimental impact of
early adolescent cannabis use by affecting the trajectory
of white matter development in the critical period of
adolescence [4,53].
1
H-MRS: technical limitation Due to the low concen-
tration (mM) of the neurochemicals detected by
1
H-
MRS, localized spectroscopy studies generally sample a
relatively large brain volume and require averaging several
acquisitions to build up a reasonable signal-to noise ratio
from the brain volume of interest. As such, most previous
1
H-MRS clinical studies have reported on NAA signals
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originating from both gray and white matter tissues taken
together as a whole; unfortunately, this approach has
prevented the interpretation of findings in regards to the
specific anabolic and catabolic activities of NAA.
In this proposed study, we will sample a large brain
volume comprised of 95% white matter. Our previous
1
H-MRS data acquired in the same brain region has
demonstrated that across more than 150 brain scans ac-
quired with these anatomical landmarks, the mean (SD)
fractional content of white matter was 95(2.8)% (unpub-
lished). These
1
H-MRS data will thus provide insight
about the specific catabolic cycle of NAA in early phase
schizophrenia and consequently, about the regional avail-
ability of acetate which is required for biosynthesis of
myelin. In this context, regional levels of NAA can be con-
sidered a marker of myelin integrity.
Previous relevant
1
H-MRS studies In adolescent chronic
cannabis users, reductions in NAA concentration levels
were reported, relative to non-user controls, in the an-
terior cingulate region encompassing mainly gray matter
[67]. Levels of NAA might also be altered in schizophre-
nia but findings are inconsistent across studies, thus
inconclusive. Indeed, if we compile previous
1
H-MRS
studies of schizophrenia while selecting studies with the
best contemporary methods (those that referenced neuro-
chemical levels to internal water and that used a sample
size of 20 subjects or more in each group in order to de-
crease probabilities of noise discoveries) [68,69], no con-
sensus can be reached in the current literature [70].
In the frontal/prefrontal regions of the brain, the focus
of this study, some
1
H-MRS studies have reported that
concentrations were reduced in established schizophrenia
relative to healthy controls for levels of NAA [71-74], and
age-adjusted NAA [75]. On the other hand, several other
studies have reported normal levels of NAA in the same
frontal/prefrontal regions in never treated first episode
psychosis [76], medicated first episode psychosis [77,78],
and established schizophrenia [79-86]. These studies,
for the most part, sampled a brain volume of interest
encompassing both gray matter and white matter tissue
types, consequently precluding any specific interpret-
ation of findings in terms of the precise anabolic or
catabolic cycle of NAA. Obviously there is a need to
search for confounding variables that might impact on
the current mixed
1
H-MRS findings reported across
population samples and laboratories. Early adolescent
onset of regular cannabis use certainly has the potential
to be one such factor [3,5].
Transverse (T
2
) relaxation time constants
Another neuroimaging modality involved in this study tar-
gets the same white matter brain region, while maintaining
the focus at the cellular level. The transverse relaxation
time constants of regional tissue water (involving both
intracellular and extracellular tissue water) and of NAA
(intracellular) provide an index of the integrity of the
microcellular environment of the brain region studied.
In fact, T
2
relaxation time constants are dependent on
the morphological parameters of cell size and cell pack-
ing density in the brain region studied; they also reflect
intracellular molecular mobility as they are dependent
on the frequency of molecule-microenvironment inter-
actions [87]. As such, prolonged T
2
time constants are
associated with reduced cell densities.
Transverse time constants of NAA in the context of
~95% white matter tissue will provide an index of intracel-
lular density of cells in this brain region, oligodencrodytes
being an important target among these cells [65]. Trans-
verse time constants of water will provide an index of
intracellular plus extracellular cell packing densities with-
out differentiation of which type of cells are present in the
specific region of interest.
Previous studies Different from DTI and
1
H-MRS stud-
ies of schizophrenia, the studies assessing T
2
relaxation
time constants in this illness have, to this date, reported
consistent findings. The T
2
time constants of water were
found to be prolonged relative to healthy controls in pre-
frontal white matter [75,88] and anterior corpus callosum
[89], in adults with established schizophrenia [75,88,89]
and first episode psychosis [89]. No differences were ob-
served between adults with first episode psychosis and
those with established schizophrenia [89]. These findings
altogether support the assumption of abnormal axonal mi-
lieu and myelin structures in schizophrenia.
Transverse relaxation time constants of NAA, on the
other hand, were found to be shortened relative to
healthy controls in prefrontal white matter of adults
with established schizophrenia [75,88] and first episode
psychosis [89], thus supporting the assumption of in-
creased intracellular (oligodendrocytes) cell density. In
gray matter (anterior cingulate cortex), T
2
time con-
stants of NAA were also shortened in adults with
schizophrenia relative to healthy controls but the group
difference did not reach statistical significance [90].
Because of the consistency of reported findings with
these particularly sensitive neuroimaging indices of cell
packing densities, T
2
relaxation time constants acquired
in this proposed study will be used as an anchor point
against which DTI and
1
H-MRS measures will be
interpreted. The aim is to generate, from these in vivo
data, a plausible interpretation of the specific cellular
abnormalities associated with schizophrenia, which
might differ from those associated with early adolescent
onset of regular cannabis use.
Noteworthy for this project, the T
2
relaxation time
constants of NAA and tissue water have never been used
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to help differentiate the detrimental impact of cannabis
use from the white matter cellular abnormalities associ-
ated with schizophrenia. We expect that these sensitive
measures of intracellular and extracellular cell packing
densities will be related to DTI (FA) values, as water dif-
fusivity is also influenced by cell densities [24].
Aims
We propose a multimodal neuroimaging study of frontal
white matter microstructure in patients in the early
phase of schizophrenia, while taking into account the
detrimental impact of early adolescent onset of regular
cannabis use. The brain region of interest is the left SLF
from which FA values, NAA levels as well as T
2
relax-
ation time constants of tissue water and of NAA will be
measured, providing novel insight into the specific cellu-
lar pathology associated with early phase schizophrenia,
and into the potential confounding impact of early ado-
lescent onset of regular cannabis use.
Methods/Design
Sample size and groups/subgroups
This study will involve 240 participants overall. The two
main conditions are a) young adults in their early phase
of schizophrenia (n = 120) and b) healthy controls (n =
120). Each condition will be further subdivided into
three subgroups (n = 40 each) based on age at initiation
of regular cannabis use: a) prior to age 17, b) after age
17, or c) with no lifetime exposure or very minimal ex-
perimentation with cannabis.
A priori premises
1. How are we going to interpret the findings?
The particular neuroimaging indices that will show
anomalies relative to normative data (non-user
healthy controls) in regards to each of the four
potential situations outlined below will permit a
meaningful micro-structural interpretation of the
specific and potentially different cellular
abnormalities existing in each group and subgroup
of participants.
a) Given the specific online selection of white matter
tissue, reduction in regional levels of NAA will lead
to the assumption of insufficient availability of
acetate, which is the main building blocknecessary
for myelin repair and maintenance. Thus, we would
assume reduced integrity of myelin sheaths.
b) In the case of reduction in FA values, we would
assume reduced integrity of axonal fibres in this
same brain region (more disorganized axonal fibres).
Integrity of myelin sheaths has less impact on FA
values than integrity of axonal fibres.
c) In the case of prolonged T
2
relaxation time
constants of regional tissue water, we would assume
reductions in intracellular and extracellular cell
packing density of axonal fibres (myelin water is not
included in this measure; see next section).
d) T
2
time constants of NAA are sensitive to
intracellular density; as such, shorter T
2
time
constants would yield the assumption of greater
intracellular density of regional white matter cells,
oligodendrocytes being involved.
2. Specific hypotheses:
a) In terms of T
2
relaxation time constants of NAA
and of regional tissue water:
In the clinical group (n = 120), T
2
time constants
of NAA will be reduced relative to healthy
controls (n = 120), while T
2
time constants of
tissue water will be prolonged (replication data)
[75,88,89]. In addition, the clinical subgroup of
early cannabis users (n = 40) will display a greater
level of deviation from normative data (non-user
healthy controls; n = 40) compared with the two
other clinical subgroups (novel data).
In the healthy control group, similar findings (as
above) will be observed in early cannabis users
(n = 40) relative to non-users (n = 40), but not in
late cannabis users (n = 40) relative to non-users
(novel data).
b) In terms of FA values and NAA levels: We expect
these two measures to correlate with each other [82].
In the clinical group (n = 120), reduced FA values
and NAA levels might or might not be observed
relative to healthy controls (n = 120), as previous
findings are mixed and inconclusive; however, the
clinical subgroup of early cannabis users will
display reduced FA values and NAA levels
relative to normative data and relative to the two
other clinical subgroups (novel data).
In healthy controls, reduced FA values and NAA
levels will be found in early cannabis users
relative to non-users (replication data) [51,53-56],
but not in late cannabis users relative to non-
users (novel data).
3. Associations between neuroimaging indices:
We expect that correlations between abnormalities
in neuroimaging indices will be stronger in early
cannabis users with schizophrenia relative to non-
users with schizophrenia and relative to early
cannabis users without symptoms of schizophrenia.
4. Associations with symptom/function measures:
We expect that in the clinical group, abnormalities
in neuroimaging indices will correlate with more
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pronounced clinical/functional abnormalities
according to symptom/function measures (see
section Questionnaires and interviews, below).
There are few studies investigating the relationship
between different aspects of white matter cellular
integrity and symptom/function measures in early
phase schizophrenia. These analyses will be
exploratory and will be used for the generation of
hypotheses for future studies.
Statistical power analyses
To our knowledge, this study is the first one to compare
and contrast four cellular neuroimaging indices acquired
from the exact same brain region, while targeting a sin-
gle tissue type. As such, these data will help establish
statistical power calculations for future studies. We com-
puted power estimations using data from studies with
contemporary neuroimaging methods and relatively
good sample sizes, while selecting those studies that
were very close to our own research question. Our pur-
pose was to ensure that our planned sample size was
reasonable even in this context of a pioneer study.
From previous data reporting T
2
relaxation time con-
stants of NAA in patients with schizophrenia relative to
healthy controls [75], we estimated that a sample size of
35 participants in each group would provide adequate
power to detect differences between independent
groups, with a two-tailed test at an alpha level of .05 and
power of .8.
From previous data reporting T
2
relaxation time con-
stants of water in patients with schizophrenia relative to
healthy controls [88], we estimated that a sample size of
23 participants in each group will provide adequate power
to detect differences between independent groups.
From frontal DTI FA values previously reported in
patients with schizophrenia who started cannabis use
prior to age 17 versus healthy non-users controls [60],
sample size calculations revealed that 23 participants in
each group will yield adequate power to detect group
differences.
With the reduced levels of NAA in anterior cingulate
previously reported in adolescent marijuana users versus
non-user controls [67], computations yielded a sample
size of 24 participants in each group in order to have ad-
equate power.
Our planned sample size of 40 participants per sub-
group will thus yield adequate power for all planned
analyses.
Operational definitions
Early phase schizophrenia: less than 5 years since
diagnosis of psychosis with initiation of appropriate
medical treatment [20].
Regular cannabis use: usage occurring on 3 or more
days per week, maintained for a period of 6 months
or more [34].
Early adolescent onset of cannabis use: start of regular
cannabis use prior to age 17 years old [33,60].
Minimal or non-cannabis users: people who are
cannabis-naive or who had minimal experimentation
with cannabis (less than 10 experimentations over
lifetime) [57].
Recruitment and diagnosis
Recruitment of patients will be conducted at the Nova
Scotia Early Psychosis Program (NSEPP). Currently
NSEPP has about 220 individuals who are active in the
clinic and within 5 years of illness onset (meeting our
criteria); approximately 60-70% of these patients have a
history of cannabis use, as assessed at time of referral.
Approximately 50 new incoming patients are accepted
at the clinic every year, adding to the current pool of pa-
tients. Recruitment of healthy controls will be conducted
through advertisements. Diagnosis of patients (using
DSM-IV) will be confirmed by consensus between the
treating psychiatrist and one of the authors (PT).
Inclusion and exclusion criteria
Healthy controls will be 1935 years of age; with no life-
time diagnosis of psychiatric disorder; healthy; and tak-
ing no prescribed medications. They will have no first
degree relatives (sibling, mother, or father) with a life-
time diagnosis of psychosis or bipolar disorder. They will
be matched with patients in regards to age, gender and
history of cannabis use. Patients will be 1935 years of
age and within five years of diagnosis of schizophrenia.
They will be taking appropriate antipsychotic medica-
tions (these will be recorded and tested as potential
confounding variables). Participants will be excluded if
they have a lifetime history of a) more than minimal
experimentation with illicit drugs other than cannabis
(e.g., cocaine, ecstasy) or b) more than low risk alcohol
consumption as behaviourally defined by the Canadas
Low-Risk Alcohol Drinking Guidelines [90]; we esti-
mated that approximately 10% of patients in our clinic
will be excluded based on this lifetime history.
Ethics approval and financial support
Full ethics approval to conduct this study was received
from the Capital Heath Research Ethics Board. Capital
Health is a public provider of health care services in
Halifax, Nova Scotia, Canada. Ethics approval was also
obtained from the IWK Research Ethics Board, as the
scanner is located in this hospital. The IWK Health
Centre is a public provider of health care in Halifax.
Each participant will be fully informed of the study prior
to signing the consent form. Seed funding for this study
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was obtained from the Department of Psychiatry Re-
search Fund at Dalhousie University, Halifax. This study
is also financially supported by the Dr. Paul Janssen
Chair in Psychotic Disorders (P. Tibbo).
Questionnaires and interviews
The Structured Clinical Interview for the Diagnostic
and Statistical Manual of Mental Disorders Axis 1
(SCID-1) [91] is a semi-structured interview used
for diagnosis.
The Structured Clinical Interview for the Positive and
Negative Syndrome Scale (SCI-PANSS) [92] assesses
30 different symptoms associated with schizophrenia
[93], grouped into three subscales: The Positive,
Negative and General Symptoms subscales.
The Personal and Social Performance scale (PSP)
was developed to measure social functioning in
schizophrenia, separate from psychological
symptoms [94].
Severity of anxiety and mood symptoms is assessed
with the Beck Anxiety Inventory (BAI) [95] and the
Calgary Depression Rating Scale for Schizophrenia
[96].
Detailed information about past and current use of
all types of illicit drugs, alcohol, and cigarette
smoking is collected using a custom Drug
Questionnaire, which includes all the questions
provided in the SCID but organized in a much more
detailed way. Cumulative usage of cannabis will be
estimated (in grams) for two time periods: before
age 17 (when applicable) and cumulative lifetime.
Neuroimaging
MR online acquisitions
Neuroimaging data will be acquired with a GE 1.5 Tesla
MRI and a multi-channel head coil. MR acquisition pa-
rameters are outlined in Table 1. A 6.5 cm volume of
interest (VOI) is prescribed in the left dorsal frontal white
matter, immediately anterior to the rostral part of the
inferior parietal lobe. VOI dimensions are 45 mm (A/P)
by 13 mm (S/I) and 11 mm (R/L) (Figure 1). Relaxometry
acquisitions for NAA start at a TE of 80 ms, in order to
minimize the contribution from macromolecules into the
estimation of neurochemicals (which would present at
shorter TE times). Relaxometry acquisitions for the water
files start at a TE of 50 ms, in order to minimize the con-
tribution from the myelin water signal into the estimations
of tissue water relaxation times[87].
MR offline analyses
1
H-MRS data Offline analysis of the neurochemical
spectra are performed with the program fitMAN [97].
The following signals will be quantified: N-acetylaspartate
plus N-acetylaspartylglutamate (NAA), choline-containing
compounds (Cho), and creatine plus phosphocreatine
(tCr). We will compile all the data acquired, even when
not part of the main research question. At 1.5 Tesla how-
ever, it is impossible to biologically meaningfully interpret
findings from the Cho signal, as its anabolic component
(phosphocholine; PC) cannot be resolved separately from
its catabolic component (glycerophosphocholine; GPC).
Neurochemical concentration levels will be adjusted to
account for the fractional content of tissue types within
each VOI, according to their known variation in this re-
spect [62], and they will be referenced to the estimation
of internal water signal extrapolated to TE = 0 ms. For
each individual participant, neurochemical levels will be
corrected for T
2
induced signal losses.
Noteworthy, the fitMAN program can be used to ana-
lyse spectra in the time domain, therefore allowing the
elimination of the tail of the free induction decay curve
(where mainly noise remains) from the fitting, which
strategy strikingly increases the signal-to-noise ratio
(SNR) of the spectra in the frequency domain. The
model function used is Equation 1 in Bartha et al. (1999)
[97], with parameters for both zero- and first-order phase.
As a result, there is no need to perform zero- or first
order-phasing of the data prior to quantification in the
time domain; these parameters are estimated as part of
Table 1 Neuroimaging acquisition sequences
Type Parameters Min
Localizer and calibration 2
3D SPGR T
1
-weighted, for online placement of VOI and
its offline tissue segmentation
256 x 256 matrix; 170 sagittal slices; 1 mm isotropic resolution, no inter-slice gap;
TR = 11.3 s; TE = 4.2 ms; flip angle = 20 deg.
7
1
H-MRS volume of interest (VOI) Online VOI placement; shimming (values are carried over to each subsequent
1
H-MRS acquisition)
6
NAA concentration levels and T
2
time constants of NAA PRESS; TR = 3 s; TEs = 80, 120, 180, 350, 600 ms; NEX = 64 25
T
2
time constants of water TR = 10 s; TEs = 50, 60, 80, 120, 180, 350, 600, 800, 1000 ms; NEX = 4 20
Diffusion-weighted images TR = 8.5 s; TE 8090 ms; flip angle = 90 deg; 54 non-collinear diffusion weighting
directions, b-factor of 1000 s/mm
2
; 6 acquisitions, b-factor of ~ 0 s/mm
2
; 256 x
256 matrix; 260 FOV; 1.02 x 1.02 x 3 mm
3
voxels; NEX = 1; acquisition of field maps.
25
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the fitting process. When fitting in the time domain, we
simply specify the time interval over which to perform the
minimization; therefore, eliminating data points at the be-
ginning or end of the FID becomes straightforward. For
spectral fitting, we include data points that range from 1
to 512.
Prior knowledge basis set spectra are not required as the
three main singlets of the spectral profiles are quite ro-
bust. The quality criteria for
1
H-MRS data to be retained
for statistical analyses are the following: signal-to-noise ra-
tio (SNR) of 15 or greater, computed from the amplitude
of NAA divided by the standard deviation (SD) of the
noise; linewidth (FWHM) of 8 Hz or less; and uncertainty
in the estimation of the fit (Cramer Rao bounds) smaller
than 10 %SD. Our preliminary data shows that SNR for
NAA typically ranges from 20 to 55, depending on the
specific TE used for acquisition; FWHM is 6 Hz or less;
and % SD is consistently 5 (Figure 2).
T
2
measurements Area under the water signal is calcu-
lated from the frequency domain at each TE, using a
MATLAB script ([98]. From the decrease in water signal
amplitude as a function of TE, the corresponding T
2
re-
laxation time constants are estimated as a curve fit of a
two-component exponential decay using the Curve Fit-
ting Tool in MATLAB. The decay curve of water could
potentially involve three components: CSF (long T
2
), tis-
sue water (intermediate T
2
), and myelin water (very short
T
2
) [87]. With this study design however, signals from
myelin water mostly decayed at the echo times sampled;
the very short myelin component is therefore not identi-
fied by the fitting algorithm. As for NAA levels, signal loss
(as a function of TE) has a better fit with a mono-
exponential decay curve [99] (Figures 3 and 4).
DTI data
The scanner 3D coordinates used at time of
1
H-MRS
online acquisition will be used to precisely define a DTI
region of interest encompassing the exact same brain
volume that was prescribed for estimation of
1
H-MRS
neurochemical levels and T
2
relaxation time constants.
This strategy will permit the offline estimation of all
Figure 1 Online placement of the
1
H-MRS volume of interest. Note. The volume is parallel to the AC-PC line. Its posterior border is aligned
3 mm posterior to the point of posterior commissure using the sagittal view. Its inferior border is placed axially on the first slice where the corpus
callosum meets from the two hemispheres. In the right/left direction, it is centered on the white matter fibre tract using the inferior axial slice.
Bernier et al. BMC Psychiatry 2013, 13:264 Page 8 of 13
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neuroimaging indices (DTI,
1
H-MRS and T
2
time con-
stants) from the exact same brain region, as precisely de-
fined by online coordinates of
1
H-MRS VOI placement.
Fractional anisotropy (FA) images are calculated using
Bayesian estimation of diffusion parameters at each
voxel. Images are spatially normalized using nonlinear
registration to the MNI152 brain template. A mean FA
image is created and thinned to generate a mean FA
skeleton representing the maximum FA values of all
tracts common to all participants. A threshold of 0.2 is
applied to the skeleton to control for cross-subject
variability.
The VOI described above is used to mask the FA skel-
eton image; tracts passing through this VOI are statistically
analysed using nonparametric tract-based spatial statistics
[100] using 10000 permutations. Threshold-free cluster
Figure 2 Spectral profiles acquired at different times of echo (TE). Note. Yellow: raw data; blue: residuals; red: fitted data. No data filtering
has been applied. In the time domain, the number of data points included in the fits ranged from 1 to 512.
Figure 3 NAA signal decay curve. Note. NAA signal areas are fitted to a single exponential decay model using MATLAB.
Bernier et al. BMC Psychiatry 2013, 13:264 Page 9 of 13
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enhancement [101] is used to correct for multiple compar-
isons. Statistical significance is determined at p < .05,
corrected. Tracts are identified using the MRI Atlas of Hu-
man White Matter and the JHU DTI-based white matter
atlases included with the FSL software: the ICBM-DTI-81
white matter labels atlas and the JHU white matter
tractography atlas [102,103].
Statistical analyses
All statistical analyses will be two-tailed and computed
with SPSS version 17; alpha will be set at p < .05 unless
otherwise specified.
Testing hypotheses 1 and 2:
A multivariate analysis of variance (MANOVA) will be
computed. Two between-group factors will be entered in
the model: Group with two levels (clinical and controls),
and Subgroup with three levels (Early, Late, and Min-
imal cannabis users). The four dependent variables will
be T
2
time constants of water and of NAA, FA values,
and NAA levels. Analyses of variance (ANOVAs) and
then t tests will be used to follow-up on significant main
effects and interaction effects.
Testing hypothesis 3:
Potential significant interaction effects between the
two factors entered in the MANOVA will be used as a
basis to determine whether or not hypothesis 3 is sup-
ported. Further follow-up analyses of these significant
interactions will involve Pearsons correlations with rele-
vant neuroimaging indices.
Testing hypothesis 4:
Exploratory analyses will involve Pearsons correlations
between neuroimaging variables and clinical variables; e.g.,
cumulative lifetime use of cannabis, gender, current age,
age at onset of psychosis, duration of untreated psychosis,
current stage of illness, severity of symptoms, medication
type, and length of time taking antipsychotic medications.
A p value of .01 or smaller will be necessary for an associ-
ation to be considered for discussion.
Discussion
We hereby propose to differentiate the detrimental im-
pact of early adolescent cannabis use from the cellular
changes associated with schizophrenia, in order to refine
the current understanding of the specific cellular mecha-
nisms involved in white matter abnormalities in the early
phase of schizophrenia [64]. This comparison will also
highlight the protective factors by which resiliency to
cannabis use occurs; that is, not all cannabis users de-
velop psychosis.
Abbreviations
Cho: Choline-containing compounds; MD: Mean diffusivity; DTI: Diffusion tensor
imaging; NAA: N-acetylaspartate; FA: Fractional anisotropy; SLF: Superior
longitudinal fasciculus; FWHM: Full width at half maximum of peak; tCr: Creatine
plus phosphocreatine;
1
H-MRS: Proton magnetic resonance spectroscopy;
TE: Time of echo; MANOVA: Multivariate analysis of variance; TR: Time of repetition.
Competing interests
The authors declare that they have no competing interests.
Authorscontributions
DB made a substantial contribution to the conception and design of the
proposal. DB and JC made a substantial contribution to the initial writing of
the draft proposal. JC is recruiting and screening participants. JC and DB are
acquiring data and performing MR offline analyses. DM made a substantial
contribution to all MR technical aspects of this proposal namely, pre-testing
of MR data quality; computing of the decay curves and T
2
relaxation time
constants; and all aspects of compilation of MR data. RB provided his
program for
1
H-MRS offline analyses (fitMAN) and also provided technical
support for the program in the context of 3-peak fits at 1.5T, along with
extensive teaching about offline analyses. CH has designed the relaxometry
Figure 4 Water signal decay curve. Note. Water signal areas are fitted to a two-component decay model using MATLAB.
Bernier et al. BMC Psychiatry 2013, 13:264 Page 10 of 13
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parameters for acquisition and offline analyses; he also provided a custom-
made program to assess the decay curves. RB and CH made a substantial
intellectual contribution to the writing of the
1
H-MRS technical part of the
proposal. AN has designed the DTI section of the proposal in terms of data
acquisition parameters and offline analyses as well as writing of this
technical section. SS brought expertise about the addiction part of this
study. PT provided help with recruitment and diagnosis of patients, and he
supported the research as the Director of the NSEPP and as the Dr. Paul
Janssen Chair in Psychotic Disorders. All authors have made intellectual
contributions to the writing and editing of the full study proposal. All
authors read and approved the final manuscript.
Acknowledgements
We are thankful to Gregory MacLean, Matthew Rogers and Sarah Sullivan
who are meticulously acquiring MR data at the IWK scanner site, Halifax,
Nova Scotia, Canada. We are grateful to all participants for their contributions
to this study. We also thank anonymous reviewers who provided helpful
comments and suggestions to this study proposal.
Author details
1
Department of Psychiatry, Dalhousie University, 5909 VeteransMemorial
Lane, Abbie J. Lane Building, Room 3030, Halifax B3H 2E2, Nova Scotia,
Canada.
2
Robarts Research Institute, Western University, 100 Perth Drive,
London N6A 5K8, Ontario, Canada.
3
Department of Biomedical Engineering,
University of Alberta, 8308-114 Street, Edmonton T6G 2V2, Alberta, Canada.
4
Department of Psychology and Neuroscience, Dalhousie University, Box
15000, Life Sciences Centre, B3H 4R2 Halifax, Nova Scotia, Canada.
Received: 20 May 2013 Accepted: 14 October 2013
Published: 17 October 2013
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doi:10.1186/1471-244X-13-264
Cite this article as: Bernier et al.:Multimodal neuroimaging of frontal
white matter microstructure in early phase schizophrenia: the impact of
early adolescent cannabis use. BMC Psychiatry 2013 13:264.
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... In samples of antipsychotic-naïve schizophrenia patients, we and others have reported FA reductions in the superior longitudinal fasciculus, inferior longitudinal fasciculus, cingulum, inferior fronto-occipital fasciculus, thalamic radiation, corpus callosum and the corticospinal tract (Alvarado-Alanis et al. 2015;Ebdrup et al. 2016;Filippi et al. 2014;Liu et al. 2013;Li et al. 2018;Sun et al. 2015;Zeng et al. 2016). Likewise, a detrimental impact of substance use on WM microstructure has been reported (Bernier et al. 2013;Cookey et al. 2014). Recreational cannabis use has been associated with greater reductions of FA in both healthy volunteers and patients with recent onset schizophrenia (Bernier et al. 2013;Cookey et al. 2014). ...
... Likewise, a detrimental impact of substance use on WM microstructure has been reported (Bernier et al. 2013;Cookey et al. 2014). Recreational cannabis use has been associated with greater reductions of FA in both healthy volunteers and patients with recent onset schizophrenia (Bernier et al. 2013;Cookey et al. 2014). The prevalence of cannabis use in schizophrenia patients is higher than in the general population (up to 43%), suggesting that this may be a confounding issue in schizophrenia WM studies (Bersani et al. 2002). ...
... We speculate that these inconsistencies may be attributable to the confounding effect of substance use within the patient population. This is in agreement with most studies that have shown the combined impact (i.e. an interaction) of substance use and the illness on WM microstructure in patients to be greater than each one of them separately (Bernier et al. 2013;Cookey et al. 2014;Filbey et al. 2014;James et al. 2011). In an independent cohort of antipsychotic-naïve schizophrenia patients, we previously reported differential effects on subcortical gray matter regions in patients with and without lifetime substance abuse (Ebdrup et al. 2010). ...
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Cerebral white matter (WM) aberrations in schizophrenia have been linked to multiple neurobiological substrates but the underlying mechanisms remain unknown. Moreover, antipsychotic treatment and substance use constitute potential confounders. Multimodal studies using diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI) may provide deeper insight into the whole brain WM pathophysiology in schizophrenia. We combined DTI and MTI to investigate WM integrity in 51 antipsychotic-naïve, first-episode schizophrenia patients and 55 matched healthy controls, using 3 T magnetic resonance imaging (MRI). Psychopathology was assessed with the positive and negative syndrome scale (PANSS). A whole brain partial least squares correlation (PLSC) method was used to conjointly analyze DTI-derived measures (fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), mode of anisotropy (MO)) and the magnetization transfer ratio (MTR) to identify group differences, and associations with psychopathology. In secondary analyses, we excluded recreational substance users from both groups resulting in 34 patients and 51 healthy controls. The primary PLSC group difference analysis identified a significant pattern of lower FA, AD, MO and higher RD in patients (p = 0.04). This pattern suggests disorganized WM microstructure in patients. The secondary PLSC group difference analysis without recreational substance users revealed a significant pattern of lower FA and higher AD, RD, MO, MTR in patients (p = 0.04). This pattern in the substance free patients is consistent with higher extracellular free-water concentrations, which may reflect neuroinflammation. No significant associations with psychopathology were observed. Recreational substance use appears to be a confounding issue, which calls for attention in future WM studies.
... 9,36,37,50,54 Additionally, it was observed that that for patients with psychosis associated with marijuana usage, such usage started in adolescence and they developed the symptoms subsequently. Some studies have found that marijuana users with episodes of psychosis have a reduction in brain volume when compared to patients with schizophrenia who did not try the drug, in addition to the brain abnormalities 33,38,42 , changes in cognitive functioning and development of depressive symptoms. 29 The effect of marijuana on the body can affect the structures of the frontal, temporal and median lobe. ...
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Background: Studies have pointed out the increased risk of developing psychosis in adulthood related to cannabis use during adolescence. Aim: To conduct a systematic review of the literature on the use of cannabis in adolescence and risk of psychosis. Method: We conducted a systematic review in accordance with PRISMA guidelines. We searched by PubMed, PsycINFO, and SciELO database between 2010 and 2019. Results: After an accurate analysis, of the 8.673 records screened articles, we selected and included 32 original studies in this systematic review. The sample in the original papers totaled 81.049 participants, indicating an association between early use of cannabis and the onset of psychosis in 97.3% of the studies, with a robust variety of instruments used. It has been shown that early cannabis use, associated to genetic vulnerability, gender, duration of use, environmental and social factors, or the use of other drugs may lead to late development of schizophrenia whether compared with non-users. Conclusion: There is evidence that marijuana use is associated with the occurrence of psychosis in adolescence and later in life. However, other variables, such as social and biological aspects, should be considered. This shows the importance of educational programs of public policies on risks of cannabis and clear information to the population about several combination factors that might lead to trigger psychotic disorders, such as schizophrenia.
... Across primary studies using duration-based definitions to select patients, nearly half did not specify the disease onset definition used (71/147; 48%). 32,36, The remaining 52% (n = 76) of studies used a variety of definitions for disease onset, including five studies that used multiple onset definitions: 29 studies referred to time since symptom onset; 14 studies referred to time since first episode or acute phase; 33,34,[136][137][138][139][140][141][142][143][144][145][146][147] 17 studies referred to time since first presentation to mental health services, hospitalisation or admission; 138,[148][149][150][151][152][153][154][155][156][157][158][159][160][161][162][163] 17 studies referred to time since schizophrenia diagnosis; 37,108,137,[164][165][166][167][168][169][170][171][172][173][174][175][176][177] and 5 studies referred to time since treatment had first been initiated. 35,108,109,149,178 In total, 142 of these studies selected patients with disease duration of less than a particular period of time to define early schizophrenia. ...
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Schizophrenia is a debilitating psychiatric disorder and patients experience significant comorbidity, especially cognitive and psychosocial deficits, already at the onset of disease. Previous research suggests that treatment during the earlier stages of disease reduces disease burden, and that a longer time of untreated psychosis has a negative impact on treatment outcomes. A targeted literature review was conducted to gain insight into the definitions currently used to describe patients with a recent diagnosis of schizophrenia in the early course of disease (‘early’ schizophrenia). A total of 483 relevant English-language publications of clinical guidelines and studies were identified for inclusion after searches of MEDLINE, MEDLINE In-Process, relevant clinical trial databases and Google for records published between January 2005 and October 2015. The extracted data revealed a wide variety of terminology and definitions used to describe patients with ‘early’ or ‘recent-onset’ schizophrenia, with no apparent consensus. The most commonly used criteria to define patients with early schizophrenia included experience of their first episode of schizophrenia or disease duration of less than 1, 2 or 5 years. These varied definitions likely result in substantial disparities of patient populations between studies and variable population heterogeneity. Better agreement on the definition of early schizophrenia could aid interpretation and comparison of studies in this patient population and consensus on definitions should allow for better identification and management of schizophrenia patients in the early course of their disease.
... Although not systematically evaluated, other studies with smaller samples have failed to detect abnormalities in dorsal regions. 7,35,[57][58][59] Also, several studies suggest that glutamatergic increases may be more robust in ventral brain regions 23,24,[33][34][35][60][61][62] with effect sizes larger than here reported. We are currently implementing a whole-brain 1 H-MRSI sequence. ...
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Glutamine plus glutamate (Glx), as well as N-acetylaspartate compounds (NAAc, N-acetylaspartate plus N-acetyl-aspartyl-glutamate), a marker of neuronal viability, can be quantified with proton magnetic resonance spectroscopy ((1)H-MRS). We used (1)H-MRS imaging to assess Glx and NAAc, as well as total-choline (glycerophospho-choline plus phospho-choline), myo-inositol and total-creatine (creatine plus phosphocreatine) from an axial supraventricular slab of gray matter (GM, medial-frontal and medial-parietal) and white matter (WM, bilateral-frontal and bilateral-parietal) voxels. Schizophrenia subjects (N = 104) and healthy controls (N = 97) with a broad age range (16 to 65) were studied. In schizophrenia, Glx was increased in GM (P < .001) and WM (P = .01), regardless of age. However, with greater age, NAAc increased in GM (P < .001) but decreased in WM (P < .001) in schizophrenia. In patients, total creatine decreased with age in WM (P < .001). Finally, overall cognitive score correlated positively with WM neurometabolites in controls but negatively in the schizophrenia group (NAAc, P < .001; and creatine [only younger], P < .001). We speculate the results support an ongoing process of increased glutamate metabolism in schizophrenia. Later in the illness, disease progression is suggested by increased cortical compaction without neuronal loss (elevated NAAc) and reduced axonal integrity (lower NAAc). Furthermore, this process is associated with fundamentally altered relationships between neurometabolite concentrations and cognitive function in schizophrenia.
... But despite of this limitation the application to studies is broad, because alterations in brain biochemistry of lesion free areas had been detected nearby tumors [35][36][37], in patients with multiple sclerosis [38], Table 3 with Table 4). This legitimates the missing calculations with all 54 pairs for the protocols not enlisted in Table 4 "ref" indicates that the amplitude of a metabolite is referenced to Cre3, which is the calculation of relative concentrations i.e. evaluatedas amp ref (met) = amp(met)/amp(Cre3) "±% of mean" for each metabolite (five last lines) is the maximal percentage deviation from the mean value for a pair of amplitudes drug abuse [39][40][41], AIDS [42,43] or psychiatric disorders [44]. ...
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Post processing for brain spectra has a great influence on the fit quality of individual spectra, as well as on the reproducibility of results from comparable spectra. This investigation used pairs of spectra, identical in system parameters, position and time assumed to differ only in noise. The metabolite amplitudes of fitted time domain spectroscopic data were tested on reproducibility for the main brain metabolites. Proton spectra of white matter brain tissue were acquired with a short spin echo time of 30 ms and a moderate repetition time of 1500 ms at 1.5 T. The pairs were investigated with one time domain post-processing algorithm using different parameters. The number of metabolites, the use of prior knowledge, base line parameters and common or individual damping were varied to evaluate the best reproducibility. The protocols with most reproducible amplitudes for N-acetylaspartate, creatine, choline, myo-inositol and the combined Glx line of glutamate and glutamine in lesion free white matter have the following common features: common damping of the main metabolites, a baseline using only the points of the first 10 ms, no additional lipid/macromolecule lines and Glx is taken as the sum of separately fitted glutamate and glutamine. This parameter set is different to the one delivering the best individual fit results. All spectra were acquired in “lesion free” (no lesion signs found in MR imaging) white matter. Spectra of brain lesions, for example tumors, can be drastically different. Thus the results are limited to lesion free brain tissue. Nevertheless the application to studies is broad, because small alterations in brain biochemistry of lesion free areas had been detected nearby tumors, in patients with multiple sclerosis, drug abuse or psychiatric disorders. Main metabolite amplitudes inside healthy brain can be quantified with a normalized root mean square deviation around 5 % using CH 3 of creatine as reference. Only the reproducibility of myo-inositol is roughly twice as bad. The reproducibility should be similar using other references like internal or external water for an absolute concentration evaluation and are not influenced by relaxation corrections with literature values.
... Longitudinal designs would also be very helpful in clarifying the timing and relationship between the emergence of WM abnormalities and the onset of psychotic illness and cannabis use. Finally, acquiring several imaging modalities assessing the microstructure of WM integrity would bring a more precise interpretation of WM abnormalities (Bernier et al., 2013). ...
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La marihuana es la droga ilícita más consumida en el mundo y de inicio más frecuente, poderosa inductora del consumo de otras sustancias lícitas e ilícitas. La legalización de la marihuana no la individualiza ni la separa del mercado; tampoco la libera del submundo de las drogas ilícitas, en el cual coexisten el alcohol y el tabaco, entre otras drogas. Cabe anotar que la legalización del alcohol y el tabaco no disminuyó la producción y consumo de estas sustancias; por el contrario, se incrementaron al punto que actualmente son las drogas de mayor consumo en la sociedad global. Los promotores de la legalización de la marihuana mienten cuando afirman que la legalización de esta droga disminuirá su consumo. Los adictos compran la marihuana de mayor potencia y les es indiferente si quien se las vende es el Estado o su proveedor (dealer). Los productores de marihuana ilegal se van a esmerar en producir marihuana de más alta potencia; mientras que el Estado no puede competir en este aspecto. Su consumo agudo y crónico lesiona estructuras cerebrales y trastorna los circuitos neuronales, produciendo deterioro de la personalidad con abandono de los roles personales, familiares y sociales, por lo que cabe preguntarnos si es ético que el Estado legalice la marihuana.
Chapter
There is ongoing debate around the effects of cannabis on the developing adolescent brain and, in particular, on its role in the development of psychosis in those at risk. Epidemiological evidence reports that consumption of cannabis in adolescence increases the risk of developing psychosis. However, there is very little scientific evidence to show the mechanism by which cannabis and the developing adolescent brain interact. Much of the evidence that does exist is from in vitro experiments or preclinical work in mice. This work suggests a possible role of oligodendrocytes in the mechanism of psychosis development. Neuroimaging provides an effective tool for examining changes in oligodendrocytes noninvasively in the living human brain. This chapter is focused on examining what we know from neuroimaging by two techniques, diffusion tensor imaging and proton magnetic resonance spectroscopy, in cannabis use in adolescence and early phase psychosis.
Chapter
Evidence that long-term cannabis use may be hazardous to white matter in the developing brain has been accumulating, with early onset use in particular thought to impair structural morphology and integrity, during the critical neurodevelopment occurring in adolescence. We found specific localized axonal connectivity disturbances in adult long-term heavy cannabis users, with 84–88% reductions in streamlines in the fimbria of the hippocampus, and commissural fibers extending to the precuneus. White matter integrity within these fiber bundles was associated with the age of onset of cannabis use. The endocannabinoid system is critically involved in axonal growth in the developing brain; mechanisms underlying axonal morphological alterations following exposure to cannabis in utero have been identified. Mechanisms that may be specifically perturbed by cannabis use impacting the neurodevelopment and brain maturational processes that occur during adolescence require further research. Dysfunctional connectivity may underlie a wide range of cognitive disturbances and psychological symptoms, including vulnerability to psychosis, depression, and anxiety disorders, all of which are significant public health concerns.
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Objective: Young adults with early phase schizophrenia often report a past or current pattern of illicit substance use and/or alcohol misuse. Still, little is known about the cumulative and separate effects of each stressor on white matter tissue, at this vulnerable period of brain development. Methods: Participants involved 24 healthy controls with a past or current history of sustained illicit drug use and/or alcohol misuse (users), 23 healthy controls without such history (normative data), and 27 users with early phase schizophrenia. (1)H-MRS data were acquired from a large frontal volume encompassing 95% of white matter, using a 4Tesla scanner (LASER sequence, TR/TE 3200/46ms). Results: Reduced levels of choline-containing compounds (Cho) were specific to the effect of illness (Cohen's d=0.68), with 22% of the variance in Cho levels accounted for by duration of illness. Reduced levels of myoInositol (d=1.10) and creatine plus phosphocreatine (d=1.07) were specific to the effects of illness plus substance use. Effect of substance use on its own was revealed by reductions in levels of glutamate plus glutamine (d=0.83) in control users relative to normative data. Conclusions: The specific effect of illness on white matter might indicate a decreased synthesis of membrane phospholipids or alternatively, reduced membrane cellular density. In terms of limitations, this study did not include patients without a lifetime history of substance use (non-users), and the specific effect of each substance used could not be studied separately.
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Rationale and objective: The present study tested the hypothesis that chronic interference by cannabis with endogenous cannabinoid systems during peripubertal development causes specific and persistent brain alterations in humans. As an index of cannabinoid action, visual scanning, along with other attentional functions, was chosen. Visual scanning undergoes a major maturation process around age 12–15 years and, in addition, the visual system is known to react specifically and sensitively to cannabinoids. Methods: From 250 individuals consuming cannabis regularly, 99 healthy pure cannabis users were selected. They were free of any other past or present drug abuse, or history of neuropsychiatric disease. After an interview, physical examination, analysis of routine laboratory parameters, plasma/urine analyses for drugs, and MMPI testing, users and respective controls were subjected to a computer-assisted attention test battery comprising visual scanning, alertness, divided attention, flexibility, and working memory. Results: Of the potential predictors of test performance within the user group, including present age, age of onset of cannabis use, degree of acute intoxication (THC+THCOH plasma levels), and cumulative toxicity (estimated total life dose), an early age of onset turned out to be the only predictor, predicting impaired reaction times exclusively in visual scanning. Early-onset users (onset before age 16; n = 48) showed a significant impairment in reaction times in this function, whereas late-onset users (onset after age 16; n = 51) did not differ from controls (n = 49). Conclusions: These data suggest that beginning cannabis use during early adolescence may lead to enduring effects on specific attentional functions in adulthood. Apparently, vulnerable periods during brain development exist that are subject to persistent alterations by interfering exogenous cannabinoids.
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Morosini P-L, Magliano L, Brambilla L, Ugolini S, Pioli R. Development, reliability and acceptability of a new version of the DSM-IV Social and Occupational Functioning Assessment Scale (SOFAS) to assess routine social funtioning. Acta Psychiatr Scand 2000: 101:323–329. © Munksgaard 2000. Objective: Development of a scale to assess patients' social functioning, the Personal and Social Performance scale (PSP). Method: PSP has been developed through focus groups and reliability studies on the basis of the social functioning component of the DSM-TV Social and Occupational Functioning Assessment Scale (SOFAS). The last reliability study was carried out by 39 workers with different professional roles on a sample of 61 psychiatric patients admitted to the rehabilitation unit. Each patient was rated independently on the scale by the two workers who knew them best. Results: The PSP is a 100–point single-item rating scale, subdivided into 10 equal intervals. The ratings are based mainly on the assessment of patient's functioning in four main areas: 1) socially useful activities; 2) personal and social relationships; 3) self-care; and 4) disturbing and aggressive behaviours. Operational criteria to rate the levels of disabilities have been defined for the above-mentioned areas. Excellent inter-rater reliability was also obtained in less educated workers. Conclusion: Compared to SOFAS, PSP has better face validity and psychometric properties. It was found to be an acceptable, quick and valid measure of patients' personal and social functioning.
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Using a 4.1 T whole body system, we have acquired 1H spectroscopic imaging (SI) data of N-acetyl (NA) compounds, creatine (CR), and choline (CH) with nominal voxel sizes of 0.5 cc (1.15 cc after filtering). We have used the SI data to estimate differences in cerebral metabolites of human gray and white matter. To evaluate the origin of an increased CWNA and CWNA ratios in gray matter relative to white matter, we measured the T1 and T2 of CR, NA, and CH in gray and white matter using moderate resolution SI imaging. In white matter the T2s of NA, CR, and CH were 233 ± 27,141 ± 18, and 167 ± 20 ms, respectively, and 227 ± 27,140 ± 16, and 189 ± 25 ms in gray matter. The T, values for NA, CR, and CH were 1267 ±141, 1487 ± 146, and 1111 ± 136 ms in gray matter and 1260 ± 154, 1429 & 233, and 1074 ± 146 ms in white matter. After correcting for T1 and T2 losses, creatine content was significantly lower in white matter than gray (P < e 0.01, t-test), with a white/gray content ratio of 0.8, in agreement with biopsy and in vivo measurements at 1.5 and 2.0T.