mapping cortical thickness and gray matter concentration...

Mapping Cortical Thickness and GrayMatter Concentration in First EpisodeSchizophrenia

Katherine L. Narr1, Robert M. Bilder2,3, Arthur W. Toga1,3,

Roger P. Woods4, David E. Rex1, Philip R. Szeszko4, Delbert

Robinson4, Serge Sevy4, Handan Gunduz-Bruce4, Yung-Ping

Wang1, Heather DeLuca1 and Paul M. Thompson1

1Laboratory of Neuro Imaging, Department of Neurology,

Geffen School of Medicine at UCLA, Los Angeles, CA, USA,2Department of Psychiatry and Biobehavioral Sciences,

Geffen School of Medicine at UCLA, Los Angeles, CA, USA,3Ahmanson-Lovelace Brain Mapping Center, Department of

Neurology, Geffen School of Medicine at UCLA,

Los Angeles, CA, USA and 4Department of Psychiatry

Research, The Zucker Hillside Hospital, North-Shore Long

Island Jewish Health Systems, Glen Oaks, NY, USA

We mapped regional changes in cortical thickness and intensity-based cortical gray matter concentration in first episode schizo-phrenia. High-resolution magnetic resonance images were obtainedfrom 72 (51 male, 21 female) first episode patients and 78 (37 male,41 female) healthy subjects similar in age. Cortical pattern match-ing methods allowed comparisons of cortical thickness and graymatter concentration at thousands of homologous cortical locationsbetween subjects in three dimensions. Principal componentsanalyses reduced measures obtained across the cortex to identifyglobal differences in cortical thickness/gray matter concentration.First principal component factor scores showed significant effectsof diagnosis, sex and age for both cortical measures. Diagnosis andage effects remained significant after brain size correction. Corticalthickness and gray matter concentration values were highlycorrelated. Statistical maps showed significant regional graymatter thinning in frontal, temporal and parietal heteromodalassociation cortices bilaterally in first episode patients. Regionalreductions in cortical gray matter concentration were similar butpronounced in the superior temporal lobe. Regional reductions incortical thickness and gray matter concentration are present atdisease onset in brain regions linked with functional disturbancesin schizophrenia. Cortical thickness and gray matter concentrationmapping produce similar results, although the concentration metricmay be influenced by diagnostic differences in extra-corticalcerebrospinal fluid and surface curvature/complexity.

Keywords: brain structure, heteromodal association cortices, imaging,prefrontal cortices, superior temporal gyrus

Introduction

A dialectic of hypotheses focusing on discrete cortical, limbic,

striatal or diencephalic regional or system abnormalities [e.g.

left superior temporal gyrus (Shenton et al., 1992), thalamus

(Andreasen et al., 1994), fronto-striatal (Robbins, 1990), fronto-

limbic (Weinberger et al., 1992; Bilder et al., 1995), cortico-

striatopallidothalamic (Braff et al., 1995), corticostriatothalamo-

cerebellar (Andreasen et al., 1999)], versus hypotheses of

widespread cortical gray matter abnormalities (Pfefferbaum

et al., 1994; Lim et al., 1996a) perhaps maximal in heteromodal

cortex (Pearlson et al., 1996), have been proposed to explain

the underlying neurobiology of schizophrenia. These hypoth-

eses are supported to degree by evidence from in vivo imaging

studies. That is, existing imaging data confirms that multiple

brain regions are affected in schizophrenia (Pearlson, 2000;

Shenton et al., 2001). However, disease effects appear subtle

(Ward et al., 1996; Lawrie and Abukmeil, 1998) and regional

inconsistencies in findings are common. Despite mixed results

that may stem from small effect sizes in the presence of large

inter-individual differences in brain structure, reductions in

tissue volumes have been reported in some cortical and sub-

cortical regions with relative consistency. Notably, gray matter

deficits in lateral and medial temporal cortices, principally the

superior temporal gyrus (and hippocampus subcortically), are

reported in the majority of studies (Lawrie and Abukmeil, 1998;

Wright et al., 1999b, 2000; Shenton et al., 2001). Gray matter

deficits in other neocortical regions, including frontal cortices,

particularly prefrontal and orbitofrontal regions, and parietal

cortices, are also observed, although less frequently replicated

(Shenton et al., 2001).

In humans, the majority of the cerebral cortex consists of

association areas that form functional circuits reciprocally

linking different cortical and subcortical centers to support

higher cognitive functions. During prenatal development, mi-

grating cells from the marginal zone of the telencephalic vesicle

cause the cortex to thicken. The thickness of the cerebral

cortex (ranging between 1.5 to 4.5 mm) thus reflects the

density and arrangement of cells (neurons and neuroglia and

nerve fibers) (Parent and Carpenter, 1995). Disturbances in

neurogenesis, neuronal migration, differentiation and synapto-

genesis and in mechanisms that involve neuronal and synaptic

pruning have been implicated in schizophrenia (Jakob and

Beckmann, 1986; Arnold, 1999). These factors may selectively

affect the lamination of specific cortical regions and may prove

a more sensitive measure by which to identify alterations in

brain structure that form the basis of functional disturbances

characterizing individuals with schizophrenia. However, to

identify regional changes in cortical gray matter, magnetic

resonance imaging (MRI) studies have traditionally compared

volumes from discrete cortical regions of interest. More re-

cently, a number of studies have also used sophisticated

computational image analysis techniques that allow voxel-wise

comparisons of gray matter distributions to be made throughout

the entire brain volume (Wright et al., 1999a; Sigmundsson

et al., 2001; Wilke et al., 2001; Ananth et al., 2002) or across the

cortex exclusively (Thompson et al., 2001b; Sowell et al., 2002;

Narr et al., 2003). Studies using voxel-based morphometry

(VBM) methods (Ashburner and Friston, 2000) and/or using

search regions exclusively at the cortex (Thompson et al.,

2001b) sometimes refer to differences observed in the pro-

portion of gray matter voxels, which are defined based on signal

intensity thresholds, compared with voxels representing other

� Oxford University Press 2004; all rights reserved Cerebral Cortex doi:10.1093/cercor/bhh172

Cerebral Cortex Advance Access published September 15, 2004

tissue types as gray matter density differences. However, to

avoid confusion with the cell packing density measured cyto-

architectonically, in this study we will refer to changes in the

proportion of gray matter voxels with respect to voxels

representing other tissue types, as differences in intensity-based

gray matter concentration. The relationships between intensity-

based gray matter concentration and cortical thickness, which

has been associated with neuronal packing density (Selemon

et al., 1995, 1998), remain to be characterized.

A few studies have assessed cortical thickness in schizo-

phrenia using postmortem data. These studies, focusing mainly

on frontal regions, have shown that neuronal density is increased

and that neuronal somal sizes are smaller in patients with

schizophrenia compared with control groups (Selemon et al.,

1995, 1998, 2003; Rajkowska, 1997). Importantly, increased

neuronal packing density and smaller somal sizes appear to

correspond with small reductions in cortical thickness. In-

creased neuronal density has also been observed in the anterior

cingulate (Bouras et al., 2001) and in occipital regions (Selemon

et al., 1995), while increases in the density of microglia has

been reported in both frontal and temporal cortical regions

(Radewicz et al., 2000). Post-mortem studies, however, are

limited by the labor intensiveness of measurement methods,

rendering it impractical to measure cellular density and thick-

ness in all cortical regions. Furthermore, post-mortem speci-

mens are less commonly available and sample sizes have been

comparatively small in these investigations. Thus, at present,

post-mortem studies may not be able to adequately address the

regional specificity of cortical thickness changes in schizo-

phrenia. In contrast, in vivo imaging data togetherwith improve-

ments in computational image analysis methods may allow

differences in cortical thickness across the cortex to be esti-

mated at high resolution using automated or semi-automated

procedures.

To our knowledge, only three prior studies have examined

cortical thickness in schizophrenia using imaging data. Of these,

only one has assessed cortical thinning across the entire cortex

at relatively high spatial resolution (Kuperberg et al., 2003).

Results showed significant thinning in distributed areas of the

cortex, but most prominently in frontal and temporal regions, in

chronic schizophrenia patients relative to demographically

similar healthy comparison subjects. A second study examined

sulcal and gyral cortical thickness separately collapsed over

each lobar region in patients with childhood and adolescent

onset schizophrenia compared with age equivalent healthy

controls (White et al., 2003). Significant thinning was observed

in the cortex underlying the sulci in frontal, temporal and

parietal regions in schizophrenia patients. Significant cortical

thinning beneath the gyri was observed in the temporal lobe

only. Another study examining exclusively prefrontal regions in

first episode schizophrenia (Wiegand et al., 2004), however, did

not detect cortical thinning averaged across the entire pre-

frontal lobe. Notwithstanding, patients showed significant

reductions in prefrontal gray matter volume and cortical

thickness and volume were significantly correlated. Interest-

ingly, both age and age at first medication were negatively

correlated with prefrontal cortical thickness in first episode

patients but not in healthy control subjects, or in patients with

first episode affective psychosis.

Despite mixed findings, prior evidence suggests that the

pathophysiological mechanisms underlying schizophrenia

affect cortical regions linked by functional circuitry and may

manifest as abnormalities in cortical thickness and/or lamina-

tion. Advanced image analysis methods and large sample sizes,

however, may be necessary to isolate small and regionally

specific differences in cortical thickness, given that effect sizes

for global and regional gray matter abnormalities in volumetric

studies are reported as small (Ward et al., 1996; Lawrie and

Abukmeil, 1998). In this investigation, we therefore set out to

examine cortical thickness at sub-voxel resolution across the

entire cortex in a large sample of first episode patients, who had

received little or no prior medication exposure, compared with

demographically similar healthy subjects. To increase the likeli-

hood of isolating regional changes cortical thickness, we used

cortical pattern matching methods that control for individual

differences in anatomy by matching homologous cortical

regions between subjects (Thompson et al., 2000, 2001a). We

hypothesized that cortical thinning would occur predominantly

in association cortices (prefrontal, temporal and parietal

regions), as implicated in earlier investigations of cortical thick-

ness in schizophrenia (Selemon et al., 1998; Kuperberg et al.,

2003; White et al., 2003). The modulating influences of sex and

age were also examined, given that these variables have not

been assessed in association with cortical thickness in schizo-

phrenia. As a secondary goal, we aimed to determine whether

intensity-based cortical gray matter concentration (the distri-

bution of voxels segmenting as gray matter), as measured in

VBM (Wright et al., 1999a; Sigmundsson et al., 2001; Wilke et al.,

2001; Ananth et al., 2002) and earlier cortical pattern matching

studies (Thompson et al., 2001b; Narr et al., 2003), indexes

similar disease-related processes in schizophrenia. Principal

components analyses were used to reduce cortical thickness

and gray matter concentration values obtained at thousands

of homologous cortical locations to examine overall effects of

diagnosis and hemisphere. To identify the regional specificity of

cortical thinning and/or reduced intensity-based gray matter

concentration, statistical comparisons were performed at each

cortical location. Relationships between cortical thickness and

intensity-based gray matter concentration were compared at

both the global and regional levels.

Materials and Methods

SubjectsSubjects included 72 (51 male, 21 female) patients experiencing their

first episode of schizophrenia and 78 (37 male, 41 female) healthy

comparison subjects, similar in age (patients: mean ± SD = 25.1 ± 4.7

years; controls: 27.3 ± 6.6 years). A structured diagnostic interview, the

Schedule for Affective Disorders and Schizophrenia (Endicott and

Spitzer, 1978) and the Structured Clinical Interview for Axis I DSM-IV

Disorders (First et al., 1997) were performed to determine diagnostic

status of patients. Patients were assessed longitudinally to confirm

diagnoses made at the initial episode. Psychopathology was assessed

using the Schedule for Affective Disorders and Schizophrenia Change

Version with Psychosis and Disorganization Items rating scale and the

Scale for the Assessment of Negative Symptoms (Andreasen, 1984).

Thirty-nine patients (54%) were drug-naive at the time of the scan. The

median number of days of antipsychotic medication received by the

remaining first episode patients prior to scanning was 8 days (range =1--187 days).

Healthy comparison subjects were recruited through local newspa-

per advertisements and community word of mouth. Healthy controls

had no history of psychiatric illness as determined by clinical interview

using the Structured Clinical Interview, nonpatient edition. Exclusion

criteria for all subjects included serious neurological or endocrine

disorders, any medical condition or treatment known to affect the

brain, or meeting DSM-IV criteria for mental retardation. The North

of 12 Cortical Thickness in First Episode Schizophrenia d Narr et al.

Shore--Long Island Jewish Health System Institute Review Board (IRB)

approved all procedures and informed written consent was obtained

from all subjects. Additional approval for image processing and analysis

was received from the UCLA IRB.

Image Acquisition and PreprocessingHigh-resolution 3-D SPGR MR images were obtained on a GE 1.5 T

scanner (General Electric, Milwaukee, WI) as a series of 124 contiguous

1.5 mm coronal brain slices (256 3 256 matrix, 0.86 mm 3 0.86 mm in-

plane resolution). Each image volume was corrected for magnetic field

inhomogeneities (Zijdenbos and Dawant, 1994; Sled and Pike, 1998) and

non-brain tissue, including the scalp, bone and meninges, was manually

removed from each brain slice (inter-rater reliability for scalp editing

procedures, rI = 0.99). Image volumes were resampled into 1 mm

isotropic voxels and corrected for head tilt and alignment using a three-

translation and three-rotation rigid-body transformation with no scaling.

For rigid body transformation, 10 standard anatomical landmarks were

identified in all three planes, and matched with a set of corresponding

point locations predefined on the ICBM-305 average brain as previously

detailed (Sowell et al., 1999; Narr et al., 2002). Each brain volume was

thus reoriented into the standard co-ordinate system of the ICBM-305

average brain (Mazziotta et al., 1995) using a trilinear interpolation and

a six parameter Procrustes fit. Scalp-edited MRI volumes were then used

to estimate brain volume and for tissue segmentation where voxels were

automatically classified as most representative of gray matter, white

matter and cerebrospinal fluid (CSF) as based on signal intensity

thresholds using a partial volume correction method (Shattuck et al.,

2001).

Cortical Pattern MatchingCortical pattern matching methods were used to spatially relate

homologous regions of cortex between subjects. These matching

algorithms are employed to ensure that gray matter measures (cortical

thickness and intensity-based gray matter concentration) are obtained

from equivalent cortical locations in each individual (Narr et al., 2001;

Thompson et al., 2001b; Sowell et al., 2002). For cortical pattern

matching, a cortical surface extractor is first used to obtain parametric

models of the cortex from each MR volume (MacDonald et al., 1994).

The cortical surface parameter space coordinates are made up of 65 536

surface points, but do not yet index the same anatomy across all

subjects. In order to match equivalent cortical regions between

subjects, the cortical surface models from each individual were used

to outline 38 primary cortical sulci and fissures employing previously

validated anatomic delineation protocols (www.loni.ucla.edu/~esowell/

new_sulcvar.html). The manually derived sulcal landmarks were then

used as anchors to drive the surrounding cortical surface anatomy of

each individual into correspondence. That is, during the surface-

warping procedures, the algorithm computes a 3-D vector deformation

field that records the amount of x, y and z coordinate shift (or

deformation), associating the same cortical surface locations in each

subject with reference to the average anatomical pattern of the entire

study group (Thompson et al., 2000, 2001a,b). In this study, the cortical

pattern matching algorithms were used only to associate the same

parameter space coordinates across subjects without actually warping

each cortical surface model to the average. Cortical models thus remain

in native space but are reparameterized such that the same anatomy

bears the same coordinate locations in each subject. Reliability for the

manual outlining of sulcal landmarks was established on six test brains,

where the 3-D root mean square distance was <2 mm for all landmarks

within and between raters as previously described (Narr et al., 2003).

Intensity-based Gray Matter ConcentrationThe 3-D deformation vector fields obtained from the cortical pattern

matching methods allow a local measurement of gray matter to be made

at spatially homologous 3-D cortical surface locations in each subject,

referencing corresponding point locations in spatially registered tissue

classified scalp-edited brain volumes. Tissue classified brain volumes

were obtained using the partial volume correction method described

above (Shattuck et al., 2001). To quantify cortical gray matter, we

measured the proportion (or concentration) of voxels segmenting as

gray matter based on signal intensity information, relative to all other

tissue types, within a sphere with a fixed radius of 15 mm at homologous

cortical surface locations in each individual. For each point on the

cortical surface, gray matter concentration ratios (ranging between 0.00

and 1.00) can be compared statistically to provide maps indexing very

local differences in tissue proportions across the entire cortex within or

across groups (Thompson et al., 2001b; Sowell et al., 2002; Narr et al.,

2003).

Cortical ThicknessTo quantify cortical gray matter thickness, the 3-D deformation fields

obtained from the cortical pattern matching algorithms were again used

to equate homologous cortical locations between individuals. Cortical

thickness was defined as the 3-D distance measured from the cortical

white--gray matter boundary in the tissue classified brain volumes

(Shattuck et al., 2001) to the cortical surface (gray--CSF boundary) in

each subject using the 3-D Eikonal equation (Sapiro, 2001). Tissue

classified brain volumes were resampled at 0.33 mm cubic voxels to

obtain distance measures indexing gray matter thickness at sub-voxel

spatial resolution. Gray matter thickness was then measured at

thousands of homologous cortical locations in each subject. Impor-

tantly, while the gray matter concentration measure estimates the ratio

of gray matter within the cortical mantle relative to other tissue types,

gray matter thickness quantifies only the distance of the cortical ribbon

across the entire cortex in millimeters. Gray matter thickness measures

may again be averaged and compared at each cortical surface location

providing spatially detailed maps of local thickness differences within or

between groups.

Statistical AnalysesTo circumvent the need to correct for statistical comparisons made at

each cortical surface location (surface points) and to examine global

effects of cortical gray matter, Principal Component Analysis (PCA) was

first used to reduce (i) intensity-based gray matter concentration

and (ii) cortical thickness values, measured at the 65 536 spatially

homologous cortical surface locations in each individual, into principal

components. PCA was performed for each hemisphere separately to

allow the examination of hemispheric asymmetries and potential

interactions between Hemisphere and Diagnosis in statistical analyses.

The scree plots in Figure 1 show that the first components for gray

matter concentration explained 28 and 29% of the total variance for the

left and right hemispheres respectively. For cortical thickness, 33% of

the total variance was explained by the first PCA component for both

hemispheres. Only components falling above the elbow (or bend) of the

scree plots were examined statistically. Figure 1 shows that approxi-

mately four components fall above the elbow of the scree plots for all

measures. Figure 1 also shows the variance accounted for by additional

principal components where no factor beyond the fourth component

accounts for >4% of the total variance.

Factor scores from the first four PCA components were thus included

as dependent variables in statistical analyses using the General Linear

Model (GLM). Factor scores from the left and right hemisphere were

included as repeated measures. Diagnostic group (Schizophrenia

patients; Normal controls) was included as a categorical predictor

variable. Sex was included as a covariate, given that different ratios of

males and females were present within each diagnostic group. Inter-

actions between Diagnosis and the covariate, Sex, were also examined.

Age was included as a second covariate. All interactions with the within

subjects variable, Hemisphere, were included in the model. To confirm

that total brain size did not contribute to any observed schizophrenia

effects, statistical analyses were performed both with and without

covarying for total brain volume. A similar statistical model was used to

examine group differences in total brain volume and total gray matter,

white matter and CSF volumes, although Hemisphere was not included

as a variable.

To follow up significant omnibus results from analyses of PCA factor

scores, statistical comparisons were performed at each cortical surface

location in 3-D to reveal the regional specificity of intensity-based gray

matter concentration and cortical thickness abnormalities in first

episode schizophrenia. Main effects of Diagnosis were again examined

after covarying for Sex. Interactions between Diagnostic group and the

covariate, Sex, were also examined. Regional effects of Age were not

examined given that diagnostic groups were similar in age and showed

Cerebral Cortex of 12

similar aging effects for the PCA factor scores as shown in Figure 2.

Finally, Diagnostic group differences were examined within male and

female groups separately to confirm that sex-related differences in

global brain size did not influence any observed disease-related effects.

The results of these tests, performed at 65 536 cortical locations in 3-D,

were mapped onto the group-averaged cortical surface model where

statistically significant results are indexed in color. For all analyses,

a two-tailed alpha level of 0.05 (uncorrected) was used as the threshold

for statistical significance.

Finally, Pearson’s correlation coefficients were used to examine

relationships between cortical intensity-based gray matter concentra-

tion and cortical thickness for the same PCA components. Correlations

between gray matter concentration and cortical thickness measures

were also performed at each cortical location in 3-D to show the extent

of statistical relationships at the regional level. The average and

variability distributions of cortical thickness and gray matter concen-

tration were examined within each group.

Results

Total Brain and Brain Tissue Volumes

Main effects of Diagnosis were absent for total brain volume

although the effect of the covariate, Sex, was highly significant

[F(1,145) = 48.13, P < 0.00001]. For total gray matter volume,

significant main effects of Diagnosis [F(1,145) = 4.81, P < 0.02],

Sex [F(1,145) = 35.20, P < 0.00001] and Age [F(1,145) = 9.14,

P < 0.002] were detected. After correcting for total brain

volume, effects of Diagnosis [F(1,144) = 14.06, P < 0.0002] and

Age [F(1,144) = 42.54, P < 0.00001] remained significant. White

matter volumes showed only main effects of Sex [F(1,145) =32.90, P < 0.00001] and Age [F(1,145) = 4.01, P < 0.05]. After

covarying for total brain volume, only main effects of Age

remained significant [F(1,144) = 12.23, P < 0.0006]. CSF volumes

showed main effects of Diagnosis [F(1,145) = 3.93, P < 0.049],

Sex [F(1,145) = 14.77, P < 0.0002] and Age [F(1,145) = 7.64,

P < 0.006]. After brain size correction, main effects of Diagnosis

[F(1,144) = 6.58, P < 0.01] and Age [F(1,144) = 10.10,

P < 0.00001] were significant. Means and standard deviations

for total brain and brain tissue volumes are provided in Table 1

in groups defined by Sex and Diagnosis. To show relative group

differences after correcting for total brain volume, tissue

volumes were residualized for brain volume and residuals were

added to the means obtained from the entire sample for each

tissue compartment.

Intensity-based Gray Matter Concentration PCA Scores

Factor scores from the first principal component, accounting

for ~28% of the variance, showed significant main effects of

Diagnosis [F(1,145) = 15.79, P < 0.0001], Sex [F(1,145) = 4.23,

P < 0.01] and Age [F(1,145) = 6.11, P < 0.01] for gray matter

concentration. No effects of Hemisphere or interactions

between the predictor variable and any of the covariates were

observed. Effects of Diagnosis [F(1,144) = 16.35, P < 0.0001] andAge [F(1,144) = 6.15, P < 0.01] remained significant after

covarying for total brain volume. Figure 2 (top panel) shows

factor scores from the first PCA component plotted by age in

groups defined by Sex and Diagnosis. Factor scores from the

second principal component (~8% of the total variance)

showed main effects of Age [F(1,145) = 4.01, P < 0.04] and

Hemisphere [F (1,145) = 11.39, P < 0.001] and a significant

interaction between Age and Hemisphere [F(1,145) = 11.94,

P < 0.001]. These results were similar after covarying total

for brain volume, showing significant Age [F(1,144) = 7.46,

P < 0.02] and Hemisphere [F(1,144) = 9.88, P < 0.002] effects, aswell as a significant Age by Hemisphere interaction [F(1,144) =12.18, P < 0.0006]. Factor scores from the third principal

component (~6% of the variance), only showed a main effect

of Sex both before [F(1,145) = 7.83, P < 0.006] and after brain

size correction [F(1,144) = 5.60, P < 0.02]. Finally, factor scores

from the fourth principal component (~4% of the variance)

Figure 1. Scree plots showing the total variance from principal components obtained from cortical gray matter concentration (top) and cortical thickness (bottom) measures foreach hemisphere.


revealed main effects of Sex [F(1,145) = 3.87, P < 0.05] and Age

[F(1,145) = 6.90, P < 0.01] that remained significant after brain

size correction; Sex: F(1,144) = 6.99, P < 0.01; Age: F(1,144) =7.03, P < 0.009.

Cortical Thickness PCA Scores

Factor scores from the first principal component for cortical

gray matter thickness, accounting for 33% of the total variance,

showed main effects of Diagnosis [F(1,145) = 6.37, P < 0.01],

Sex [F(1,145) = 10.24, P < 0.001] and Age [F(1,145) = 6.97,

P < 0.009]. Effects of Diagnosis [F(1,144) = 7.22, P < 0.008] and

Age [F(1,144) = 7.27, P < 0.008] remained significant after

covarying for total brain volume. No interactions between the

predictor variable, Diagnosis, and any of the covariates were

observed. Figure 2 (bottom panel) shows factor scores from the

first PCA component plotted by age in groups defined by sex

and diagnosis. Factor scores from the second principal compon-

ent (~9% of the variance) showed main effects of Age only

[F(1,145) = 7.35, P < 0.008] that were also significant after brain

size correction [F(1,144) = 8.51, P < 0.004]. Third component

factor scores (~4% of the variance) showed a main effect of

Hemisphere [F(1,145) = 5.78, P < 0.02] that was no longer

significant after taking brain volume into account. Factor scores

from the fourth principal component (also ~4% of the variance)

showed main effects of Sex [F(1,145) = 9.49, P < 0.002] and Age

[F(1,145) = 4.09, P < 0.05], and a significant Hemisphere by

Diagnostic group interaction [F(1,145) = 4.37, P < 0.04]. The

Figure 2. Factor scores from the first principal components for gray matter concentration (top) and cortical thickness (bottom) plotted by age in groups defined by sex anddiagnosis.


same effects were significant after covarying for total brain

volume; Sex: F(1,144) = 6.06, P < 0.01; Age: F(1,144) = 4.10,

P < 0.04; Hemisphere by Diagnostic group, F(1,144) = 4.37,

P < 0.04.

Regional Effects of Intensity-based Gray MatterConcentration

To isolate regional differences in intensity-based gray matter

concentration across the cortex, we compared gray matter

concentration ratios at all cortical surface locations in 3-D.

Probability values, indexed in color, were mapped back onto an

averaged cortical surface model from the entire group at each

3-D point location. Probability values showing positive and

negative effects were mapped separately to determine

whether group differences reflect increased or decreased gray

matter concentration. Figure 3 shows statistical mapping

results for (i) comparisons between schizophrenia patients

and healthy subjects after covarying for sex (top row); (ii)

between groups defined by sex (second row); (iii) interactions

between sex and diagnosis (third row); and (ii) effects of

diagnosis mapped within male and female groups separately

(last row).

The top row of Figure 3 shows that first episode patients

possess significant decreases in intensity-based gray matter

concentration in dorsolateral prefrontal cortex, most promi-

nently in the middle frontal gyrus, and in the temporal lobe,

particularly the superior temporal gyrus bilaterally. Further

decreases are visible in inferior parietal regions, and in occipital

regions in the left hemisphere. No significant increases in

intensity-based gray matter concentration were observed in

schizophrenia patients compared with controls. The second

row shows regional increases in gray matter concentration in

superior parietal regions in females compared with males

(right). Males fail to show any significant regional increases in

gray matter concentration compared with females (left). Statis-

tical maps in the third row show that sex by diagnosis

interactions were absent for local gray matter concentration

measures as consistent with the PCA factor score comparisons.

Finally, in the last row, effects of diagnosis compared separately

within male (right) and female (left) groups show that de-

creases in intensity-based gray matter concentration are more

pronounced in the pre- and post-central gyrus in males,

although the spatial profiles possess many similarities between

males and females overall.

Regional Effects of Cortical Thickness

Statistical maps in Figure 4 show the same statistical compari-

sons described above, but include cortical thickness values

obtained at homologous cortical locations in 3-D as the de-

pendent measure. The top row of Figure 4 shows schizophrenia

effects after covarying for biological sex. Cortical thinning is

evident in dorsolateral prefrontal and lateral temporal cortices,

consistent with the pattern of results observed for gray matter

concentration (Fig. 3). Cortical thinning, however, appears

more spatially diffuse in the left hemisphere in temporal and

inferior parietal regions when compared with the regional gray

matter concentration results. No significant regional increases

in cortical thickness were observed in first episode patients (top

left). Overall, females possessed thicker cortices in parietal

regions (second row) even without brain size correction. Males,

however, exhibited thicker cortex in frontal regions proximal

to the interhemispheric fissure. The statistical maps in the third

row show interactions between sex and diagnosis: they suggest

that left anterior temporal and medial frontal regions are more

affected in female schizophrenia patients. In the last row, gray

matter thinning appears most prominent in temporal and

dorsolateral prefrontal regions in female patients compared

with female comparison subjects. Male patients, however,

appear to exhibit regional decreases in gray matter thickness

most prominently in the vicinity of the pre and postcentral

sulcus bilaterally, although some gray matter thinning is also

evident in temporal and frontal regions.

Associations between Intensity-based Gray MatterConcentration and Cortical Thickness

Pearson’s correlation coefficients showing relationships be-

tween factor scores from the first four principal components

for intensity-based cortical gray matter concentration and

thickness are presented in Table 2. Factor scores were highly

correlated for the same components in each hemisphere with

all probability values of <0.001. Figure 5 shows average cortical

gray matter thickness (top) and gray matter concentration

(middle) distributions across all subjects. Average cortical

thickness ranged between 2 and 4.5 mm, and intensity-based

gray matter concentration ratios ranged between 0.25 and 0.65

across the cortex. Average and variability profiles for both

measures were similar within each group (figures not shown).

The bottom panel of Figure 5 shows the statistical relationships

between gray matter concentration and cortical thickness at

Table 1Means and standard deviations for global tissue volumes (cm3) before and after brain size correction in groups defined by sex and diagnosis

Men Women

Patients with schizophrenia(n 5 51)

Comparison subjects(n 5 37)

Patients withschizophrenia (n 5 21)

Comparison subjects(n 5 41)

Brain volumea 1255.6 ± 122.9 1245.6 ± 93.43 1107.8 ± 133.9 1137.1 ± 77.1CSF volumea,b,c 159.67 ± 27.58 150.07 ± 29.17 140.08 ± 28.87 135.64 ± 24.08Corrected CSFb,c 152.62 ± 23.80 144.30 ± 25.84 151.78 ± 22.23 143.63 ± 20.64Gray matter volumea,b,c 644.23 ± 68.48 649.06 ± 73.92 571.29 ± 60.98 601.49 ± 45.86Corrected grayb,c 617.78 ± 31.96 627.42 ± 32.06 615.17 ± 25.95 631.39 ± 20.64White matter volumea,c 451.78 ± 58.89 446.47 ± 65.10 396.49 ± 64.05 400.06 ± 40.76Corrected whitec 429.69 ± 33.67 428.38 ± 32.77 433.15 ± 24.15 425.08 ± 28.07

Corrected 5 residualized for brain volume and added to the mean volume for each tissue compartment.aSignificant effects of sex.bSignificant effects of diagnosis.cSignificant effects of age.


each cortical location in 3-D. Cortical gray matter indices were

significantly (positively) correlated across all cortical locations

with the exception of the temporal poles.

Discussion

Total Brain and Brain Tissue Volumes

Patients experiencing their first episode of schizophrenia failed

to show significant differences in brain volume compared with

healthy comparison subjects. On average male patients pos-

sessed slightly larger mean brain volumes than male controls

(Table 1). These mean increases, however, were attributable to

the significantly larger CSF volumes observed across both male

and female schizophrenia patients. Importantly, patients ex-

hibited significant reductions in global gray matter, with respect

to comparison subjects, that were more pronounced after

taking total brain volume into account. No diagnostic differ-

ences were observed for white matter tissue volumes and no

interactions between diagnostic group and sex or age were

detected for any brain tissue compartment. The presence of

global CSF increases and gray matter decreases match many

previous observations in schizophrenia (Lawrie and Abukmeil,

1998; Harrison, 1999; Wright et al., 2000; Shenton et al., 2001).

Moreover, these abnormalities have been identified in first

episode patients (Lim et al., 1996b; Zipursky et al., 1998). Many

previous studies, however, have failed to detect significant

global differences in gray matter in schizophrenia (Ward et al.,

1996; Lawrie and Abukmeil, 1998). Our findings thus illustrate

the importance of using large sample sizes to detect small

differences in brain tissue volumes as appear present in indi-

viduals with schizophrenia. Although some evidence suggests

that gray matter loss in schizophrenia is progressive, at least in

the early stages of the illness and may influenced by anti-

psychotic medication exposure (Cahn et al., 2002), our data

supports the idea that gray matter abnormalities are present

near disease onset in patients with little or no prior medication

treatment.

PCA Analyses of Cortical Gray Matter Changes

PCA analyses of intensity-based gray matter concentration and

cortical thickness values obtained from homologous cortical

regions, confirm the presence of cortical (as opposed to whole

brain) gray matter changes in first episode schizophrenia. The

first principal components, accounting for 27--33% of the total

variance for both cortical gray matter indices (concentration

and thickness) sampled at high resolution across the entire

cortex, showed significant disease-related effects. Although

cortical thickness values represent the distance between the

cortical white--gray matter boundary and the external gray

matter--CSF boundary, and gray matter concentration measures

reflect the proportion of gray matter within the cortical mantle

with respect to other tissue types, results showed that these

measures are highly correlated. That is, intensity-based gray

matter concentration and cortical thickness values appear to

index the same or similar disease-related processes both at the

global (i.e. when measures are reduced using PCA) and at the

Figure 3. Statistical maps showing significant regional differences in cortical gray matter concentration (i) in patients with first episode schizophrenia (sz) compared with healthysubjects (nc) after covarying for sex (top row); (ii) between male and female subjects across diagnostic groups (second row); (iii) for interactions between sex and diagnosis (thirdrow); and (iv) between diagnostic groups with in males (right) and females (left). Probability values, indexed in color, show positive and negative effects.


regional level (Table 2, Fig. 5). Differences in cortical gray

matter concentration reduced using PCA, however, were not

detected previously in chronic schizophrenia even in the

presence of significant extra-cortical (sulcal and subarachnoid)

CSF increases (Narr et al., 2003). The sample size of the prior

investigation, however, was only one-third of the current

sample size. Thus, in the presence of small effect sizes, global

intensity-based gray matter concentration findings may have

remained undetected.

Regional Effects of Intensity-Based Gray MatterConcentration

Some cortical regions, such as lateral and medial temporal

cortices and, to a lesser extent, frontal and parietal cortices,

appear most implicated in the structural neuropathology of

schizophrenia (Lawrie and Abukmeil, 1998; Shenton et al.,

2001). Results from volumetric studies (Goldstein et al., 1999;

Gur et al., 2000; Sanfilipo et al., 2000) and investigations of gray

matter concentration throughout the brain using VBM (Wright

et al., 1999a; Sigmundsson et al., 2001; Wilke et al., 2001; Ananth

et al., 2002), however, frequently disagree concerning the

spatial localization of cortical gray matter changes. In our

investigation, cortical gray matter concentration and thickness

measures showed similar regional effects when comparisons

were performed at thousands of homologous cortical locations

in 3-D. Regional changes in intensity-based gray matter concen-

tration showed that patients exhibit decreased cortical gray

matter proportions in heteromodal association areas, particu-

larly in superior temporal and lateral prefrontal cortices (Fig. 3).

Reduced gray matter proportions were also apparent in the

inferior parietal lobules bilaterally and in left hemisphere

occipital regions. These spatial patterns appeared similar when

comparing female diagnostic groups separately. However, com-

parisons of men with schizophrenia to healthy male controls

also showed reductions of gray matter concentration in and

around the pre and postcentral gyri. In spite of some differences

in the spatial profiles of gray matter reductions within male and

female groups, significant interactions between sex and diag-

nosis were not observed at the regional (or global) level. Thus,

we do not believe the independent interpretation of these gray

matter maps among men alone merits separate interpretation,

but could serve as a focus for a replication study to determine

the generality of this finding.

Uncorrected statistical maps of regional intensity-based

gray matter concentration showed similar regional effects

in our earlier study of chronic schizophrenia patients and

Figure 4. Statistical maps showing significant regional differences in cortical thickness (i) in patients with first episode schizophrenia (sz) compared with healthy subjects (nc) aftercovarying for sex (top row); (ii) between male and female subjects across diagnostic groups (second row); (iii) for interactions between sex and diagnosis (third row); and (iv)between diagnostic groups with in males (right) and females (left). Probability values, indexed in color, show positive and negative effects.

Table 2Correlations between PCA factor scores from gray matter concentration and thickness measures

Gray matter concentration factor scores

PCA 1 PCA 2 PCA 3 PCA 4

Cortical thickness factor scores Left Right Left Right Left Right Left Right

Left 0.83 0.81 0.71 0.73 0.62 0.57 0.40 0.37Right 0.81 0.84 0.72 0.75 0.63 0.64 0.26 0.46

Probability values associated with the correlation coefficients above range between P\ 0.00001

and P\ 0.001.


demographically similar healthy comparison subjects, even

though cortical gray matter concentration values reduced using

PCA were not significant (Narr et al., 2003). Specifically, re-

gional reductions in gray matter concentration were distributed

through heteromodal association areas and within the pre- and

post-central gyrus, although they were less notable in the super-

ior temporal cortex. Extra-cortical CSF increases, however,

were pronounced surrounding temporal regions. Reciprocal

relationships between gray matter decreases and extra-cortical

CSF increases have been shown to occur during normal aging

(Jernigan et al., 1991; Coffey et al., 1998; Courchesne et al.,

2000). Thus, it is possible that regional increases in extra-

cortical CSF may serve to predict more subtle regional reduc-

tions in cortical gray matter. Our findings are also compatible

with at least two VBM studies of first episode schizophrenia (Job

et al., 2002; Kubicki et al., 2002). Specifically, Kubicki et al.

(2002) showed differences in intensity-based gray matter con-

centrations within the superior temporal gyrus and parietal

lobe. Job et al. (2002) similarly observed gray matter concen-

tration reductions in the left middle temporal and postcentral

gyri in first episode patients compared with controls.

Regional Effects of Gray Matter Thickness

Our statistical maps of cortical thickness showed similar spatial

profiles as those for intensity-based cortical gray matter con-

centration. Patients with first episode schizophrenia exhibited

cortical thinning in heteromodal lateral prefrontal and temporal

cortices, as well as in parietal and occipital regions (Fig. 4).

Comparisons between exclusively female diagnostic groups

showed similar regional effects. Males, however, showed thin-

ning within the pre and postcentral gyrus regions that were

largely above the threshold of statistical significance in female

patients, while regional effects appeared more pronounced in

temporal regions in female patients. Interactions between sex

and diagnostic group showed that female patients also possess

some cortical thinning in anterior temporal regions and adja-

cent to the interhemispheric fissure (medial frontal) that did

not appear present in male patients. Sex by diagnosis inter-

actions were not observed for cortical gray matter concentration.

Our cortical thickness findings are in line with results from an

earlier imaging study of cortical thickness in chronic schizo-

phrenia (Kuperberg et al., 2003). Using a similar methodo-

logical approach, Kuperberg et al. (2003) measured cortical

thickness in twelve cortical regions in 33 schizophrenia

patients compared with 32 demographically similar healthy

subjects. Cortical thickness was also approximated across

cerebral cortex after smoothing with a kernel of radius 60 mm.

Results showed that cortical thinning was most prominent in

prefrontal and temporal cortices. However, cortical thinning

was also observed in orbitofrontal and inferior frontal regions,

local effects that were marginal or absent in our study. Cortical

thinning was also identified in right medial frontal cortices,

a region that was not examined in our investigation. Another

study examined prefrontal cortical thickness in first episode

schizophrenia (Wiegand et al., 2004), where cortical thickness

was defined as the shortest distance from the white-gray matter

boundary to voxels on the 3-D cortical surface. Significant

reductions in prefrontal gray matter volume were observed in

first episode patients (n = 17) compared with healthy subjects

(n = 17), but reductions in cortical thickness averaged across

the region were not detected, even though thickness and

volume measures were positively correlated. These results

may suggest cortical thinning was below the threshold of

significance for the entire prefrontal lobe, and that more

regional effects may have remained undetected.

A third study used a slightly different approach to examine

differences in cortical thickness between early and adolescent

onset schizophrenia patients compared with healthy compari-

son subjects (White et al., 2003). Cortical thickness was

estimated by creating an iso-surface from the midpoint of

voxels segmenting ‘purely’ as gray matter within the cortical

ribbon. Cortical thickness was then defined as the minimum

distance from the iso-surface to voxels segmenting 50% as gray

matter and 50% as white matter and these distances were

doubled to approximate actual thickness. Cortical thickness

was then compared for gyral and sulcal regions separately

collapsed across the four lobes. Results showed that the

thickness of the cortex was reduced in sulcal regions in the

frontal, parietal and temporal lobes and reduced in gyral regions

only in the temporal lobes in patients compared with controls.

These findings are partially compatible with our results, al-

though our statistical maps did not reveal pronounced effects in

the sulcal folds.

Sex Effects

Males exhibited larger total brain volumes and individual brain

tissue volumes compared with females, as universally documen-

ted in the normative literature. Factor scores from PCA analyses

also showed main effects of sex for both cortical gray matter

indices. Sex effects, however, were no longer significant after

covarying for total brain volume, with the exception of com-

parisons between factor scores from the third and fourth

Figure 5. Maps showing average cortical thickness (top) and average gray matterconcentration distributions across all subjects (middle) as indexed by the colorbar.Relationships between cortical thickness and gray matter concentration are shown inthe bottom row, where correlation coefficients are indexed in color.


principal component for intensity-based gray matter concen-

tration values. These results suggest that there are some sex

differences in cortical gray matter that are independent of brain

size. Importantly, the removal of brain size differences may also

serve to obscure potential sex effects since sex and brain size

are strongly associated. Statistical maps of regional effects of sex

showed similar patterns as reported by other groups (Nopoulos

et al., 2000; Good et al., 2001). That is, although males possess

larger brain tissue volumes than females, females show some

focal increases in gray matter concentration compared with

males in absolute terms. These differences, measured across

both diagnostic groups, were present in posterior parietal

regions (Nopoulos et al., 2000; Good et al., 2001). Statistical

maps showing sex differences in cortical thickness were similar

to those observed for gray matter concentration values. How-

ever, small increases in cortical thickness were shown in

anterior medial frontal regions and towards the temporal poles

in male compared with female subjects whereas male subjects

showed no local increases in gray matter concentration.

Age and Hemispheric Effects

Significant effects of age were also observed for the three major

tissue compartments. Subtle gray matter decreases and white

matter and CSF increases occurred with age, as consistent with

previous findings in this age range (Coffey et al., 1998; Magnotta

et al., 1999; Symonds et al., 1999; Good et al., 2001). Diagnostic

groups showed similar age effects for all brain tissue compart-

ments and for PCA factor scores from the first principal

components of both cortical gray matter indices, irrespective

of brain size corrections. These results demonstrate that age is

a strong predictor of cortical gray matter differences between

individuals even in early adulthood. Previously, whole brain gray

matter volumes and regional changes in intensity-based gray

matter concentration were shown to occur prematurely in male

patients with chronic schizophrenia (Narr et al., 2003). That is,

male patients showed early gray matter reductions that re-

mained relatively static from disease onset into the fifth decade,

while demographically similar healthy comparison subjects and

female patients showed a gradual decline in gray matter volume

over the same time period. These results do not contradict our

current findings given that our study groups were of a relatively

narrow age range and on average a decade younger that the

chronic schizophrenia patients previously examined. Further-

more, differences in aging effects between groups were only

examined cross-sectionally in the chronic schizophrenia study,

and remain to be confirmed longitudinally. Hemispheric differ-

ences between diagnostic groups were only detected in factor

scores from the fourth PCA component cortical thickness

values. Statistical maps, however, show some small hemispheric

differences when comparisons of cortical thickness and con-

centration are made locally.

Methodological Limitations

Although intensity-based gray matter concentration and thick-

ness measures are strongly associated over the majority of the

cortex, these measures were not significantly correlated in the

temporal poles and in medial frontal regions (Fig. 5). These

small discrepancies in results illustrate some important meth-

odological differences between the two measures. Specifically,

gray matter concentration measures may be more susceptible

to artifacts stemming from differences in the curvature of the

cortical surface where increased curvature may cause less gray

matter to be sampled within the kernel of a fixed radius.

Interestingly, the temporal poles and interhemispheric folds

are among the most curved regions of the cortex perhaps

accounting for the lack of significant correlations in these

regions only. Intensity-based concentration measures may in

part also reflect differences in the surrounding tissue. For

example, prior data suggest that disease effects are larger when

CSF to whole brain ratios are examined compared with when

brain tissue volumes are examined alone (Gur et al., 1991;

Woods et al., 1996; Cannon et al., 1998). This may also apply at

the regional level. The gray matter concentration ratio may also

be influenced by sulcal widening as has been previously

documented in schizophrenia (Shenton et al., 2001). Import-

antly, none of these potential confounds are associated with

the cortical thickness measure. However, both measures may

be susceptible to partial volume effects given that gray matter

thickness and concentration are estimated from tissue seg-

mented brain volumes.

Conclusion

Cortical thickness and intensity-based gray matter concentra-

tion ratios produce similar results suggesting they index the

same pathophysiological processes in schizophrenia. Local

reductions in cortical thickness and gray matter concentration

appear to be present at disease onset implying the involvement

of disturbed neurodevelopmental mechanisms. Cortical thin-

ning and reduced intensity-based gray matter concentration are

most notable in frontal, temporal and parietal association

cortices that have been linked with functional disturbances in

schizophrenia. That is, widespread deficits, affecting the thick-

ness of the cortical mantle over broad areas of heteromodal

association cortex, may underlie complex deficits in attentional

regulation, executive deficits and deficits in learning/memory

functions that appear most prominent in schizophrenia (e.g.

Seidman et al., 1994; Baare et al., 1999; Harrison, 1999; Bilder

et al., 2000; Pearlson, 2000. Interestingly, motor deficits have

also been identified in first episode schizophrenia that appear at

least partially independent of medication treatments, perhaps

associated with gray matter thinning in primary motor areas

particularly in male patients (Bilder et al., 2000). The direct

relationships between neuropsychological measures and cor-

tical thickness in schizophrenia, however, remain to be assessed

empirically. Earlier post-mortem studies show small reductions

in cortical thickness in patients in the presence of increased

neuronal packing density and smaller neuronal somal sizes

(Selemon et al., 1995, 1998; Rajkowska, 1997). Neuropil reduc-

tions and smaller cell sizes, rather than neuronal loss, may thus

be the basis for cortical thinning in schizophrenia and account

for disturbances in neurotransmission.

Notes

This work was generously supported by research grants from the

National Center for Research Resources (2 P41 RR13642, 2 M01

RR00865 and R21 RR19771), the National Institute of Mental Health

(RO1-MH-60374) the National Library of Medicine (5 R01 LM05639),

the National Institute for Biomedical Imaging and Bioengineering (EB

001561), a NIMH NRSA Training Grant (MH14584) and a NARSAD

Young Investigator Award for which K.L.N. is the 2003 Daniel X.

Freedman recipient.

Address correspondence to Dr Arthur W. Toga, Laboratory of Neuro

Imaging, Department of Neurology, Division of Brain Mapping, UCLA


School of Medicine, 710 Westwood Plaza, Los Angeles, CA 90095-1769,

USA. Email: [email protected].

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