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Cortical white-matter microstructure in schizophrenia

Diffusion imaging study

Published online by Cambridge University Press:  02 January 2018

N. Andreone
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, and Verona–Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, University of Verona
M. Tansella
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, and Verona–Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, University of Verona
R. Cerini
Affiliation:
Department of Morphological and Biomedical Sciences, Section of Radiology GB Rossi Hospital, University of Verona
A. Versace
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, and Verona–Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, University of Verona
G. Rambaldelli
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, and Verona–Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, University of Verona
C. Perlini
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, and Verona–Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, University of Verona
N. Dusi
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, and Verona–Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, University of Verona
L. Pelizza
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, and Verona–Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, University of Verona
M. Balestrieri
Affiliation:
Verona–Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, and Department of Pathology and Experimental and Clinical Medicine, Section of Psychiatry, University of Udine
C. Barbui
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona
M. Nosè
Affiliation:
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona
A. Gasparini
Affiliation:
Department of Morphological and Biomedical Sciences, Section of Radiology, GB Rossi Hospital, University of Verona
P. Brambilla*
Affiliation:
Verona-Udine Brain Imaging and Neuropsychology Programme, Inter-University Centre for Behavioural Neurosciences, and Department of Pathology and Experimental and Clinical Medicine, Section of Psychiatry, University of Udine and Scientific Institute IRCCS E. Medea, Udine, Italy
*
Dr Paolo Brambilla, Dipartimento di Patologia e Medicina Clinica e Sperimentale, Cattedra di Psichiatria, Policlinico Universitario, Via Colugna 50, 33100 Udine, Italy. Tel: +39 0432 55 9494; fax: +39 0432 54 5526; email: paolo.brambilla@uniud.it
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Abstract

Background

Several, although not all, of the previous small diffusion-weighted imaging (DWI) studies have shown cortical white-matter disruption in schizophrenia.

Aims

To investigate cortical white-matter microstructure with DWI in a large community-based sample of people with schizophrenia.

Method

Sixty-eight people with schizophrenia and 64 healthy controls underwent a session of DWI to obtain the apparent diffusion coefficient (ADC) of white-matter water molecules. Regions of interest were placed in cortical lobes.

Results

Compared with controls, the schizophrenia group had significantly greater ADCs in frontal, temporal and occipital white matter (analysis of covariance, P < 0.05).

Conclusions

Our findings confirm the presence of cortical white-matter microstructure disruption in frontal and temporo-occipital lobes in the largest sample of people with schizophrenia thus for studied with this technique. Future brain imaging studies, together with genetic investigations, should further explore white-matter integrity and genes encoding myelin-related protein expression in people with first-episode schizophrenia and those at high risk of developing the disorder.

Type
Papers
Copyright
Copyright © Royal College of Psychiatrists, 2007 

Diffusion-weighted imaging (DWI) is a relatively new technique capable of examining molecular water mobility in brain tissue by providing the apparent diffusion coefficient (ADC) of water molecules (Reference Taylor, Hsu and KrishnanTaylor et al, 2004), particularly in white matter, a highly organised tissue where water diffusion is restricted. The ADC is the critical measure for a detailed investigation of white-matter integrity and inferences can be drawn from it on white-matter micro-structure, organisation and cytoarchitecture, which cannot be visualised using conventional magnetic resonance imaging (Reference Basser and AtlasBasser, 2002). When brain tissue is disrupted, such as in neurological disorders involving white matter (for example multiple sclerosis), the ADC is abnormally increased (Reference Nusbaum, Tang and WeiNusbaum et al, 2000; Reference Rovaris, Bozzali and LannucciRovaris et al, 2002). Recently DWI has been used to explore white matter in schizophrenia, since this tissue has been suggested to have a major role in the pathophysiology of this disorder (Reference KeshavanKeshavan, 1999; Reference Keshavan, Diwadkar and RosenbergKeshavan et al, 2005). Indeed, white-matter changes may alter intra-hemispheric connectivity and functional brain lateralisation in people with schizophrenia (Reference Falkai, Bogerts and SchneiderFalkai et al, 1995; Reference De Lisi, Sakuma and KushnerDeLisi et al, 1997; Reference CrowCrow, 1998; Reference Brambilla, Cerini and GaspariniBrambilla et al, 2005), potentially sustaining cognitive deficits. Several DWI studies conducted in recent years have consistently shown cortical white-matter disruptions (Reference Taylor, Hsu and KrishnanTaylor et al, 2004), although not all investigations have done so (Reference Steel, Bastin and McConnellSteel et al, 2001; Reference Foong, Symms and BarkerFoong et al, 2002; see Table DS1 to the online version of this paper). However, previous diffusion imaging reports were limited by small sample sizes.

We used DWI to investigate cortical white-matter microstructure in a large community-based sample of patients with schizophrenia recruited from the geographically defined catchment area of South Verona in Italy. Our hypothesis, based on previously published findings of disrupted white-matter integrity in schizophrenia, was that people with schizophrenia would have increased ADC values.

METHOD

Sample

Sixty-eight people with a DSM–IV diagnosis of schizophrenia (American Psychiatric Association, 1994) were studied (Table 1). They were recruited from the geographically defined catchment area of South Verona (100 000 inhabitants) and treated by the South Verona community based mental health service and by other clinics reporting to the South Verona Psychiatric Care Register (Reference Amaddeo, Beecham and BonizzatoAmaddeo et al, 1997; Reference Tansella and BurtiTansella & Burti, 2003). Diagnoses of schizophrenia were obtained using the Item Group Checklist of the Schedule for Clinical Assessment in Neuropsychiatry (IGC–SCAN; World Health Organization, 1992) and confirmed with the clinical consensus of two staff psychiatrists. The IGC–SCAN assessments were completed by two trained research clinical psychologists (C.P., L.P.) with extensive experience in using the SCAN instrument. They completed at least ten IGC–SCAN ratings with a senior investigator trained in SCAN assessment, after having conducted several IGC–SCAN assessments. Successively, reliability was checked in a further ten assessments with the senior investigator, masked to the results. Similar diagnoses were obtained for at least eight out of ten IGC– SCAN assessments. Moreover, the psychopathological item groups completed by the two raters were compared in order to discuss any major symptom discrepancies. In addition, we regularly assured reliability of the IGC–SCAN diagnoses by holding consensus meetings with treating psychiatrists and a senior investigator. It is note-worthy that the Italian version of the SCAN was edited by our group (World Health Organization, 1996) and that our investigators attended specific training courses held by an official trainer in order to learn how to administer the IGC–SCAN. Subsequently, diagnoses of schizophrenia were corroborated with the clinical consensus of two staff psychiatrists, according to DSM–IV criteria. Patients with a comorbid psychiatric disorder, alcohol or substance misuse within the 6 months preceding the study, a history of traumatic head injury with loss of consciousness, or epilepsy or other neurological diseases were excluded. All but two patients were receiving antipsychotic medication at the time of imaging. Specifically, 22 patients were taking typical antipsychotic drugs (13 haloperidol, 3 chlorpromazine, 2 fluphenazine, 2 clotiapine, 1 thioridazine, 1 zuclopenthixol) and 44 on atypical antipsychotic medication (25 on olanzapine, 9 on clozapine, 8 on risperidone, 2 on quetiapine). Patients’ clinical information was retrieved from psychiatric interviews, the attending psychiatrist and medical charts. Clinical symptoms were characterised using the 24-item Brief Psychiatric Rating Scale (BPRS; Reference Ventura, Nuechterlein and SubotnikVentura et al, 2000), which was administered by two trained research clinical psychologists (C.P., L.P.). The reliability of the BPRS ratings was established and monitored using similar procedures to those used for the IGC–SCAN.

Table 1 Socio-demographic and clinical variables of the sample

Control group (n=64) Schizophrenia group (n=68)
Age, years: mean (s.d.) 40.70 (11.16) 41.39 (11.68)
Males/females, n 34/30 39/29
Right-handed 60 64
Ethnicity, %
    White 100 100
Education, n
    Primary or secondary school 22 51***
    High school 15 15
    First degree or professional school 27 2
Clinical variables: mean (s.d.)
    Age at onset, years 27.46 (9.48)
    Length of illness, years 14.40 (11.12)
    Number of hospitalisations 3.79 (6.09)
    Lifetime antipsychotic treatment, years 12.83 (10.76)
    BPRS score
        Total 45.38 (16.96)
        Negative symptom score 9.08 (3.13)
        Positive symptom score 11.74 (6.68)

Sixty-four people were recruited to constitute a healthy control group (Table 1). They had no DSM–IV Axis I disorder, as determined by an interview modified from the Structured Clinical Interview – DSM–IV Axis I Disorders, non-patient version (Reference Spitzer and WilliamsSpitzer & Williams, 1988), no history of psychiatric disorder in a first-degree relative, no history of alcohol or substance misuse and no current major medical illness. Members of the control group were hospital or university staff volunteers or patients undergoing magnetic resonance imaging (MRI) for dizziness without evidence of central nervous system abnormalities on the scan, as reviewed by the neuroradiologist (R.C.); their dizziness was due to benign paroxysmal positional vertigo or to nontoxic labyrinthitis. Control group participants were scanned only after a full medical history and general neurological, otoscopic and physical examinations, and after they had completely recovered from their dizziness. None was taking any medication at the time of participation, including drugs for nausea or vertigo.

This research study was approved by the biomedical ethics committee of the Azienda Ospedaliera of Verona. All individuals provided signed informed consent, after having understood all issues involved in study participation.

Imaging procedure

The MRI scans were acquired with a 1.5 T Siemens Magnetom Symphony Maestro Class, Syngo MR 2002B (http://www.medical.siemens.com). A standard head coil was used for radiofrequency transmission and reception of the MR signal and restraining foam pads were used to minimise head motion. First, T 1-weighted images were obtained to verify the participant's head position and the image quality: repetition time (TR) 450 ms, time to echo (TE) 14 ms, flip angle 90°, field of view (FOV) 230 mm × 230 mm, 18 slices, slice thickness=5 mm, matrix size 384 mm × 512 mm. Proton density T 2–weighted images were then acquired (TR=2500 ms, TE=24/121 ms, flip angle 180°, FOV 230 mm × 230 mm, 20 slices, slice thickness 5 mm, matrix size 410 × 512), according to an axial plane parallel to the anterior– posterior commissures (AC–PC), for clinical neurodiagnostic evaluations (exclusion of focal lesions). Subsequently, diffusion-weighted echoplanar images were acquired in the axial plane parallel to the AC–PC line (TR=3200 ms, TE=94 ms, FOV 230 mm × 230 mm, 20 slices, slice thickness 5 mm with 1.5 mm gap, matrix size 128 mm × 128 mm; these parameters were the same for b=0, b=1000 and the ADC maps) and in the coronal plane from the frontal to the occipital lobes (TR=5000 ms, TE=94 ms, FOV 230 mm × 230 mm, 30 slices, slice thickness 4 mm with 0.4 mm gap, matrix size 128 × 128; these parameters were the same for b=0, b=1000 and the ADC maps). Specifically, diffusion-weighted MRI was performed in three orthogonal directions during all sequences.

Image analyses

The apparent diffusion coefficients of water molecules for cortical white matter were detected by using software developed in-house written in MatLab version 7 (The Mathworks, Natick, Massachusetts, USA). The ADCs were obtained by placing, bilaterally, circular regions of interest in the frontal, temporal, parietal and occipital cortex on the non-diffusion-weighted (b=0) echoplanar images in reference to standard brain atlases (Reference Jackson and DuncanJackson & Duncan, 1996; Reference Patel and FriedmanPatel & Friedman, 1997) and according to previous studies (Reference Sun, Wang and CuiSun et al, 2003; Reference Wolkin, Choi and SzilagyiWolkin et al, 2003; Reference Kumra, Ashtari and McMenimanKumra et al, 2004; Reference Kitamura, Matsuzawa and ShioiriKitamura et al, 2005; Fig. 1). The regions of interest were then automatically transferred to the corresponding maps to obtain the ADCs. The ADC maps were obtained from the diffusion images with b=1000, according to the equation b ADC=ln[A(b)/A(0)], where A(b) is the measured echo magnitude, b is the measure of diffusion weighting and A(0) is the echo magnitude without diffusion gradient applied (Reference Basser and AtlasBasser, 2002). The resulting ADC was expressed in units of 10–5 mm2/s. A trained rater (N.A.), masked to group assignment and patient identity, measured all scans. The intraclass correlation coefficients, which were calculated by having two independent raters (N.A. and A.V.) trace ten training scans were higher than 0.90.

Fig. 1 Circular regions of interest were placed in cortical white matter on the b=0 echoplanar images, and then automatically transferred to apparent diffusion coefficient (ADC) maps (A, frontal lobes; B, temporal lobes; C, parietal lobes; D, occipital lobes).

Anatomical landmarks

Frontal cortex

Regions of interest were positioned in the axial slice at the level of the genu of corpus callosum (standardised at 43.5 mm2), then in the inferior slice (standardised at 43.5 mm2) and in the two superior slices (standardised at 84.4 mm2), posteriorly and medially to the frontal horns of the lateral ventricles.

Parietal cortex

Regions of interest (standardised at 84.4 mm2) were placed in the axial slice when the lateral ventricles first disappeared and in the superior slice, posteriorly to the postcentral sulcus.

Temporal cortex

Regions of interest (standardised at 43.5 mm2) were positioned in the axial slice at the level of the lateral fissure and in the inferior slice, posteriorly and laterally to the lateral fissure.

Occipital cortex

Regions of interest (standardised at 43.5 mm2) were placed in the two inferior axial slices where the occipital horns of the lateral ventricles become visible, posteriorly to the occipital horns.

Statistical analyses

All analyses were conducted using the Statistical Package for the Social Sciences version 11.0 for Windows and the two-tailed statistical significance level was set at P < 0.05. Analysis of covariance (ANCOVA) with age and gender as covariates was performed to compare white-matter ADCs between the schizophrenia group and the control group. Pearson's correlation and partial correlation analyses controlled for age were used to examine possible association between age and clinical variables respectively, and ADC measures.

RESULTS

Compared with the control group, the participants with schizophrenia had significantly greater apparent diffusion coefficients for frontal, temporal and occipital white matter (Table 2), even when taking educational level into consideration (right and left frontal ADCs, P=0.09, P=0.12; right and left temporal ADCs, P=0.006, P=0.009; right and left occipital ADCs, P = 0.006, P = 0.002, respectively; ANCOVA, age, gender and educational level as covariates). Similar results were found when the schizophrenia group was compared separately with control participants recruited from hospital and university staff (n=33) (left frontal ADCs, P=0.14; temporal ADCs: P < 0.001, occipital ADCs, P < 0.003) and with control participants who had been treated for dizziness (n=31) (right frontal ADCs, P=0.07; temporal ADCs, P=0.01; occipital ADCs, P ≤ 0.01) (ANCOVA; age and gender as covariates). Also, no significant difference for any ADC measure was found between the two control subgroups (ANCOVA; age and gender as covariates, P>0.05).

Table 2 Apparent diffusion coefficient measures for cortical white matter.

ADC, 10-5 mm2/s: mean (s.d.)
Control group (n=64) Schizophrenia group (n=68) F P
Right frontal cortex 75.31 (3.43) 76.48 (4.34) 2.98 0.08
Left frontal cortex 72.17 (3.86) 73.59 (4.89) 4.10 0.04
Right temporal cortex 75.20 (4.37) 78.71 (5.66) 15.91 <0.001
Left temporal cortex 75.23 (4.67) 78.88 (5.63) 16.83 <0.001
Right parietal cortex 71.04 (4.52) 70.63 (3.80) 0.22 0.64
Left parietal cortex 72.86 (3.95) 73.27 (3.27) 0.60 0.44
Right occipital cortex 77.47 (4.43) 80.94 (6.37) 12.98 <0.001
Left occipital cortex 75.91 (3.70) 79.26 (5.14) 17.71 <0.001

The ADC measures were still greater in the schizophrenia group than in the combined control group when both groups were stratified by gender, both in men (left frontal ADCs, P=0.04; temporal ADCs, P<0.001, occipital ADCs, P<0.002) and women (right temporal ADCs, P=0.12; left temporal ADCs, P=0.03; right occipital ADCs, P=0.06; left occipital ADCs, P=0.01) (Mann–Whitney U-test).

Age was significantly and directly correlated with left temporal ADC measures in the control group (r=0.28, P=0.02) but not in the schizophrenia group (r=0.16, P = 0.18). No significant association was shown between age and other ADC values (Pearson's correlation, P>0.05) or between clinical variables (age at onset, length of illness, number of hospitalisations, BPRS scores, antipsychotic lifetime treatment) and white matter ADCs (partial correlation controlled for age, P>0.05). Furthermore, no significant difference for any ADC value was observed between patients treated with typical antipsychotic drugs (n=22) and those treated with atypical antipsychotics (n=44) (Mann–Whitney U-test, P>0.05). Also, patients with severe illness (BPRS>41; n=37) did not differ significantly on any ADC measure compared with patients with mild-to-moderate illness (BPRS ≤ 41; n=31) (Mann–Whitney U-test, P>0.05). A BPRS total score of 41 was chosen as the cut-off level for mild or moderate illness, indicated by Leucht et al (Reference Leucht, Kane and Kissling2005).

DISCUSSION

This study found widespread regional white-matter disruption in schizophrenia, as shown by higher ADCs in frontal, temporal and occipital lobes. To our knowledge, this is the largest study to show disrupted white-matter cytoarchitecture in schizophrenia (Reference Kanaan, Kim and KaufmannKanaan et al, 2005). Consistently, impairments of cortical white-matter integrity have been found in people with schizophrenia by a number of prior small diffusion imaging studies (Reference Kubicki, McCarley and WestinKubicki et al, 2007, see online Table DS1). Specifically, abnormally increased water diffusion coefficients or abnormally decreased fractional anisotropy have been found in at least ten prior investigations of frontal lobes (Reference Buchsbaum, Tang and PeledBuchsbaum et al, 1998; Reference Ardekani, Nierenberg and HoptmanArdekani et al, 2003; Reference Minami, Nobuhara and OkugawaMinami et al, 2003; Reference Kumra, Ashtari and McMenimanKumra et al, 2004; Reference Wang, Sun and CuiWang et al, 2004; Reference Kitamura, Matsuzawa and ShioiriKitamura et al, 2005; Reference Kubicki, Park and WestinKubicki et al, 2005a ; Reference Szeszko, Ardekani and AshtariSzeszko et al, 2005; Reference Hao, Liu and JiangHao et al, 2006; Reference Shin, Kwon and HaShin et al, 2006) and in temporo-occipital lobes (Reference Lim, Hedehus and MoseleyLim et al, 1999; Reference Agartz, Andersson and SkareAgartz et al, 2001; Ardekani et al, Reference Ardekani, Nierenberg and Hoptman2003, Reference Ardekani, Bappal and D'Angelo2005; Minami et al, Reference Minami, Nobuhara and Okugawa2003; Reference Minami, Nobuhara and Okugawa2003; Reference Kumra, Ashtari and McMenimanKumra et al, 2004; Reference Kubicki, Park and WestinKubicki et al, 2005a ; Reference Szeszko, Ardekani and AshtariSzeszko et al, 2005; Reference Hao, Liu and JiangHao et al, 2006; Reference Shin, Kwon and HaShin et al, 2006). However, some studies report preserved integrity of white matter in schizophrenia (Reference Steel, Bastin and McConnellSteel et al, 2001; Reference Foong, Symms and BarkerFoong et al, 2002; Reference Kubicki, Westin and MaierKubicki et al, 2002). Both ADC and fractional anisotropy are considered as complementary indices of white-matter microstructure organisation, providing evidence of disruption when increased and decreased respectively (Reference Taylor, Hsu and KrishnanTaylor et al, 2004). In our study, we did not report fractional ansotropy because the diffusion tensor sequence was not collected. Specifically, the ADC image provides a relative presentation of the diffusion coefficient in each pixel within the image, where low and high intensity values indicate respectively low and high diffusion (Reference Basser and AtlasBasser, 2002). Abnormalities in cortical white matter may lead to impaired connection, which may ultimately alter the speed, quantity and/or quality of intrahemispheric communication, relevant to cognitive disturbances reported in schizophrenia (Reference Krabbendam, Arts and van OsKrabbendam et al, 2005). This may be a result of reduced axonal density or myelination. Indeed, oligodendrocytes, which have the potential to influence myelination and synaptic transmission, have been found to be functionally abnormal in schizophrenia (Reference Hof, Haroutunian and CoplandHof et al, 2002; Reference Davis, Stewart and FriedmanDavis et al, 2003; Reference Bartzokis and AltshulerBartzokis & Altshuler, 2005). None the less, several factors may contribute to explain increased water white-matter diffusion, such as less dense packing of fibres, disruption of internal axonal integrity (reduced intra-axonal microtubular density), reduced degree of myelination or variation in membrane permeability to water. However, since white-matter is mostly composed of myelinated axons, the density of axonal membranes and myelin seem to play the major part (Reference Beaulieu and AllenBeaulieu & Allen, 1994; Reference GieddGiedd, 2004).

Several earlier diffusion imaging studies reported frontal, temporal and occipital white-matter alterations within regions of interest identified by visual inspection of the individual anatomy, as in our method (Reference Steel, Bastin and McConnellSteel et al, 2001; Reference Hoptman, Volavka and JohnsonHoptman et al, 2002; Reference Minami, Nobuhara and OkugawaMinami et al, 2003; Reference Wolkin, Choi and SzilagyiWolkin et al, 2003; Reference Kumra, Ashtari and McMenimanKumra et al, 2004; Reference Kitamura, Matsuzawa and ShioiriKitamura et al, 2005). In particular, we examined the middle and inferior frontal white-matter regions, which have been shown to be functionally altered in schizophrenia (Reference Shenton, Dickey and FruminShenton et al, 2001), potentially sustaining executive function deficits (Reference Macdonald, Carter and KernsMacDonald et al, 2005; Reference Brambilla, Macdonald and SassiBrambilla et al, 2007). Moreover, temporal regions of interest were positioned in the medial temporal white matter regions, which are involved in modulating language domain in humans and are likely to have a key role in language abnormalities in schizophrenia (Reference Seidman, Pantelis and KeshavanSeidman et al, 2003; Reference Antonova, Sharma and MorrisAntonova et al, 2004). Finally, the occipital regions of interest were placed in medial occipital areas, which have been shown to be altered in schizophrenia by other diffusion imaging studies (Reference Lim, Hedehus and MoseleyLim et al, 1999; Reference Agartz, Andersson and SkareAgartz et al, 2001; Ardekani et al, Reference Ardekani, Nierenberg and Hoptman2003, Reference Ardekani, Bappal and D'Angelo2005; Reference Minami, Nobuhara and OkugawaMinami et al, 2003; Reference Kumra, Ashtari and McMenimanKumra et al, 2004). Furthermore, abnormalities in early-stage visual processing in schizophrenia have recently been shown, possibly contributing to higher-level cognitive deficits (Reference Butler, Zemon and SchechterButler et al, 2005; Reference Schechter, Butler and ZemonSchechter et al, 2005). Therefore, our findings suggest that frontal and temporo-occipital white-matter disruption may in part support cognitive and language deficits in schizophrenia.

Taken together, these brain imaging findings indicate that cortical white-matter microstructure is disrupted in schizophrenia. Moreover, these results may be supported by post-mortem studies showing a quantitative reduction in white matter cells (Reference Akbarian, Kim and PotkinAk-barian et al, 1996; Reference Uranova, Vostrikov and OrlovskayaUranova et al, 2004). In particular, reduced expression of myelin and oligodendrocyte-related genes and proteins has been shown in schizophrenia, suggesting oligodendrocyte dysfunction (Reference Flynn, Lang and MackayFlynn et al, 2003; Reference Hof, Haroutunian and FriedrichHof et al, 2003; Reference Tkachev, Mimmack and RyanTkachev et al, 2003; Reference Chambers and Perrone-BizzozeroChambers & Perrone-Bizzozero, 2004). Specifically, neuregulin 1 (NRG1), a candidate gene for schizophrenia (Reference Stefansson, Sigurdsson and SteinthorsdottirStefansson et al, 2002; Reference Tosato, Dazzan and CollierTosato et al, 2005; Reference Williams, O'Donovan and OwenWilliams et al, 2005), has been shown to have a key role in oligodendrocyte development and proliferation (Reference Marchionni, Goodearl and ChenMarchionni et al, 1993; Reference Vartanian, Fischbach and MillerVartanian et al, 1999; Reference Liu, Ford and MannLiu et al, 2001). Therefore, altered expression of NRG1 or other myelination-related genes may potentially result in abnormal oligodendrocyte function or myelination in schizophrenia (Reference Hakak, Walker and LiHakak et al, 2001; Reference O'Donovan, Williams and OwenO'Donovan et al, 2003). However, it remains to be elucidated whether cortical white-matter impairment mostly reflects brain mal-development or neurodegeneration. In particular, it would be of great interest to understand how and when the white-matter disruption in schizophrenia relates to the physiological processes of white-matter maturation (Reference BartzokisBartzokis, 2002; Reference HafnerHafner, 2004; Reference HarrisonHarrison, 2004; Reference Bresnahan, Schaefer and BrownBresnahan et al, 2005). Indeed, recent reports suggest that intracortical myelination increases during adulthood, reaching its peak during the fifth decade of life, particularly in the frontal and temporal lobes (Reference Bartzokis, Nuechterlein and LuBartzokis et al, 2003), in a constant state of well-regulated structural and functional change. Affected myelination in schizophrenia, which may itself be due to multiple genetic and environmental factors, may contribute to alter this temporally expanded view of brain white-matter development from adolescence until middle age. As proposed by Bartzokis, this would ultimately result in dysregulation of the temporal synchronous development of widely distributed neural networks in schizophrenia, being manifested in the heterogeneity of symptoms and cognitive impairments (Reference BartzokisBartzokis, 2002). Interestingly, white-matter alterations (particularly of corpus callosum) and abnormal down-regulation of oligodendrocyte and myelination genes have been demonstrated in bipolar affective disorder as well as in schizophrenia (Brambilla et al, Reference Brambilla, Nicoletti and Sassi2003, Reference Brambilla, Nicoletti and Sassi2004; Reference Tkachev, Mimmack and RyanTkachev et al, 2003). This sustains the notion that the two disorders may have similar white-matter pathophysiological pathways. Future brain imaging studies together with genetic investigations should further explore white-matter integrity and genes encoding myelin-related protein expression in people with first-episode schizophrenia and possibly bipolar affective disorder, and in the populations at high risk of developing these disorders.

Interestingly, we found a significant direct correlation between age and left temporal ADC values in the control group which was not present in the schizophrenia group. This is consistent with a recent investigation showing in controls, but not in patients, a significant negative effect of age on the integrity of the left superior longitudinal fasciculus, which connects the frontal and temporal cortex (Reference Jones, Catani and PierpaoliJones et al, 2006). Also, age-related decline of cerebral white-matter coherence in humans, which may represent subtle structural white-matter changes with normal ageing, has been demonstrated by diffusion imaging studies (Reference Engelter, Provenzale and PetrellaEngelter et al, 2000; Reference Pfefferbaum, Sullivan and HedehusPfefferbaum et al, 2000; Reference O'Sullivan, Jones and SummersO'Sullivan et al, 2001; Reference Sullivan, Adalsteinsson and HedehusSullivan et al, 2001). Thus, as a speculative interpretation, it is possible that the effects of physiological ageing on white matter cannot be seen in schizophrenia owing to the presence, since early adolescence, of abnormal neurodevelopment and cytoarchitectural organisation of cortical white matter, particularly in the temporal region (Reference Pantelis, Yucel and WoodPantelis et al, 2005).

No significant association between ADC values and any clinical variable was found in our study, consistent with several prior reports exploring correlations between diffusion measures and clinical features in schizophrenia (Reference Steel, Bastin and McConnellSteel et al, 2001; Kumra et al, Reference Kumra, Ashtari and McMeniman2004, Reference Kumra, Ashtari and Cervellione2005; Reference Jones, Catani and PierpaoliJones et al, 2005; Reference Kubicki, Park and WestinKubicki et al, 2005a ; Reference Kitamura, Matsuzawa and ShioiriKitamura et al, 2005; Reference Szeszko, Ardekani and AshtariSzeszko et al, 2005). This suggests that cortical white-matter disruption in schizophrenia is not a secondary effect of chronicity, medication or psychopathology but is potentially related to the core pathophysiology of the disease. However, it should be mentioned that two small studies have found increased white-matter alterations in people with schizophrenia with more severe negative symptoms in the right insula (Reference Shin, Kwon and HaShin et al, 2006) and the inferior frontal region (Reference Wolkin, Choi and SzilagyiWolkin et al, 2003). However, the latter group also showed a relationship between impulsivity/aggression and altered white-matter microstructure in the right inferior frontal region and insula in men with schizophrenia (Hoptman et al, Reference Hoptman, Volavka and Johnson2002, Reference Hoptman, Ardekani and Butler2004). Therefore, the correlation between white-matter cytoarchitecture and clinical symptoms in schizophrenia is still controversial and needs further investigation in large samples.

It should be noted that our schizophrenia sample mostly comprised treated patients with chronic illness, thus it is not clear whether white-matter disruption preceded the onset of the illness or appeared subsequently as a result of illness course or psychotropic treatment. However, length of illness or antipsychotic lifetime administration did not significantly affect ADC values, suggesting that cortical white-matter abnormalities may not be related to illness or medication. Also, we recruited a relatively larger number of participants than prior diffusion imaging studies, with a good match between those in the schizophrenia and control groups, providing adequate power. Part of our control group was selected from individuals undergoing MRI scanning for dizziness, which may represent a methodological limitation. However, these participants were fully recovered at the time of scanning and had no evidence of central nervous system abnormalities on the scan. Finally, no particular white-matter tracts could be detected with our approach, such as the uncinate or the arcuate fasciculi which form specific temporo- and parieto-frontal connections (Reference Burns, Job and BastinBurns et al, 2003; Reference Kubicki, Westin and McCarleyKubicki et al, 2005b ; Reference Jones, Catani and PierpaoliJones et al, 2006).

In conclusion, altered cortical white-matter microstructure in schizophrenia has been replicated in this large study, particularly in frontal and temporo-occipital lobes. Hypothetically, abnormal myelination due to oligodendrocyte dysfunction might account for these findings. This might potentially affect intrahemispheric communication and ultimately lead to the cognitive disturbances seen in people with schizophrenia.

Acknowledgements

We thank Dr Sarah Tosato, MD, for helpful comments on the earlier version of this manuscript. This work was partly supported by grants from the American Psychiatric Institute for Research and Education (APIRE/AstraZeneca Young Minds in Psychiatry Award) and from the Italian Ministry for Education, University and Research (PRIN 2005068874) to P.B.

Footnotes

Declaration of interest

None.

References

Agartz, I., Andersson, J. L. & Skare, S. (2001) Abnormal brain white matter in schizophrenia: a diffusion tensor imaging study. NeuroReport, 12, 22512254.Google Scholar
Akbarian, S., Kim, J. J., Potkin, S. G., et al (1996) Maldistribution of interstitial neurons in prefrontal white matter of the brains of schizophrenic patients. Archives of General Psychiatry, 53, 425436.CrossRefGoogle ScholarPubMed
Amaddeo, F., Beecham, J., Bonizzato, P., et al (1997) The use of a case register to evaluate the costs of psychiatric care. Acta Psychiatrica Scandinavica, 95, 189198.CrossRefGoogle ScholarPubMed
American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders (4th edn) (DSM-IV). APA.Google Scholar
Antonova, E., Sharma, T., Morris, R., et al (2004) The relationship between brain structure and neurocognition in schizophrenia: a selective review. Schizophrenia Research, 70, 117145.Google Scholar
Ardekani, B. A., Nierenberg, J., Hoptman, M. J., et al (2003) MRI study of white matter diffusion anisotropy in schizophrenia. NeuroReport, 14, 20252029.Google Scholar
Ardekani, B. A., Bappal, A., D'Angelo, D., et al (2005) Brain morphometry using diffusion-weighted magnetic resonance imaging: application to schizophrenia. NeuroReport, 16, 14551459.CrossRefGoogle ScholarPubMed
Bartzokis, G. (2002) Schizophrenia: breakdown in the well-regulated lifelong process of brain development and maturation. Neuropsychopharmacology, 27, 672683.CrossRefGoogle ScholarPubMed
Bartzokis, G. & Altshuler, L. (2005) Reduced intracortical myelination in schizophrenia. American Journal of Psychiatry, 162, 12291230.Google Scholar
Bartzokis, G., Nuechterlein, K. H., Lu, P. H., et al (2003) Dysregulated brain development in adult men with schizophrenia: a magnetic resonance imaging study. Biological Psychiatry, 53, 412421.Google Scholar
Basser, P. J. (2002) Diffusion and diffusion tensor MR imaging. In Magnetic Resonance Imaging of the Brain and Spine. (3rd edn) (ed. Atlas, S. W.), pp. 197214. Lippincott Williams & Wilkins.Google Scholar
Beaulieu, C. & Allen, P. S. (1994) Determinants of anisotropic water diffusion in nerves. Magnetic Resonance Medicine, 31, 394400.Google Scholar
Brambilla, P., Nicoletti, M. A., Sassi, R. B., et al (2003) Magnetic resonance imaging study of corpus callosum abnormalities in patients with bipolar disorder. Biological Psychiatry, 54, 12941297.CrossRefGoogle ScholarPubMed
Brambilla, P., Nicoletti, M., Sassi, R. B., et al (2004) Corpus callosum signal intensity in patients with bipolar and unipolar disorder. Journal of Neurology, Neurosurgery and Psychiatry, 75, 221225.Google Scholar
Brambilla, P., Cerini, R., Gasparini, A., et al (2005) Investigation of corpus callosum in schizophrenia with diffusion imaging. Schizophrenia Research, 79, 201210.Google Scholar
Brambilla, P., Macdonald, A. W., Sassi, R. B., et al (2007) Context processing performance in bipolar disorder patients. Bipolar Disorders, 9, 230237.Google Scholar
Bresnahan, M., Schaefer, C. A., Brown, A. S., et al (2005) Prenatal determinants of schizophrenia: what we have learned thus far? Epidemiologia e Psichiatria Sociale, 14, 194197.Google Scholar
Buchsbaum, M. S., Tang, C. Y., Peled, S., et al (1998) MRI white matter diffusion anisotropy and PET metabolic rate in schizophrenia. NeuroReport, 9, 425430.Google Scholar
Burns, J., Job, D., Bastin, M. E., et al (2003) Structural disconnectivity in schizophrenia: a diffusion tensor magnetic resonance imaging study. British Journal of Psychiatry, 182, 439443.Google Scholar
Butler, P. D., Zemon, V., Schechter, I., et al (2005) Early-stage visual processing and cortical amplification deficits in schizophrenia. Archives of General Psychiatry, 62, 495504.Google Scholar
Chambers, J. S. & Perrone-Bizzozero, N. I. (2004) Altered myelination of the hippocampal formation in subjects with schizophrenia and bipolar disorder. Neurochemical Research, 29, 22932302.Google Scholar
Crow, T. J. (1998) Schizophrenia as a transcallosal misconnection syndrome. Schizophrenia Research, 30, 111114.Google Scholar
Davis, K. L., Stewart, D. G., Friedman, J. I., et al (2003) White matter changes in schizophrenia: evidence for myelin-related dysfunction. Archives of General Psychiatry, 60, 443456.CrossRefGoogle ScholarPubMed
De Lisi, L. E., Sakuma, M., Kushner, M., et al (1997) Anomalous cerebral asymmetry and language processing in schizophrenia. Schizophrenia Bulletin, 23, 255271.CrossRefGoogle ScholarPubMed
Engelter, S. T., Provenzale, J. M., Petrella, J. R., et al (2000) The effect of aging on the apparent diffusion coefficient of normal-appearing white matter. American Journal of Roentgenology, 175, 425430.Google Scholar
Falkai, P., Bogerts, B., Schneider, T., et al (1995) Disturbed planum temporale asymmetry in schizophrenia. A quantitative post-mortem study. Schizophrenia Research, 14, 161176.Google Scholar
Flynn, S. W., Lang, D. J., Mackay, A. L., et al (2003) Abnormalities of myelination in schizophrenia detected in vivo with MRI, and post-mortem with analysis of oligodendrocyte proteins. Molecular Psychiatry, 8, 811820.Google Scholar
Foong, J., Symms, M. R., Barker, G. J., et al (2002) Investigating regional white matter in schizophrenia using diffusion tensor imaging. NeuroReport, 13, 333336.Google Scholar
Giedd, J. N. (2004) Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Sciences, 1021, 7785.Google Scholar
Hafner, H. (2004) Schizophrenia: still Kraepelin's dementia praecox? Epidemiologia e Psichiatria Sociale, 13, 99112.CrossRefGoogle ScholarPubMed
Hakak, Y., Walker, J. R., Li, C., et al (2001) Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia. Proceedings of the National Academy of Sciences of the USA, 98, 47464751.Google Scholar
Hao, Y., Liu, Z., Jiang, T., et al (2006) White matter integrity of the whole brain is disrupted in first-episode schizophrenia. NeuroReport, 17, 2326.Google Scholar
Harrison, G. (2004) Trajectories of psychosis: towards a newsocial biology of schizophrenia. Epidemiologia e Psichiatria Sociale, 13, 152157.Google Scholar
Hof, P. R., Haroutunian, V., Copland, C., et al (2002) Molecular and cellular evidence for an oligodendrocyte abnormality in schizophrenia. Neurochemical Research, 27, 11931200.Google Scholar
Hof, P. R., Haroutunian, V., Friedrich, V. L., et al (2003) Loss and altered spatial distribution of oligodendrocytes in the superior frontal gyrus in schizophrenia. Biological Psychiatry, 53, 10751085.Google Scholar
Hoptman, M. J., Volavka, J., Johnson, G., et al (2002) Frontal white matter microstructure, aggression, and impulsivity in men with schizophrenia: a preliminary study. Biological Psychiatry, 52, 914.Google Scholar
Hoptman, M. J., Ardekani, B. A., Butler, P. D., et al (2004) DTI and impulsivity in schizophrenia: a first voxelwise correlational analysis. NeuroReport, 15, 24672470.Google Scholar
Jackson, G. D. & Duncan, J. S. (1996) MRI Anatomy: A New Angle on the Brain. Churchill Livingstone.Google Scholar
Jones, D. K., Catani, M., Pierpaoli, C., et al (2005) A diffusion tensor magnetic resonance imaging study of frontal cortex connections in very-late-onset schizophrenia-like psychosis. American Journal of Geriatric Psychiatry, 13, 10921099.Google Scholar
Jones, D. K., Catani, M., Pierpaoli, C., et al (2006) Age effects on diffusion tensor magnetic resonance imaging tractography measures of frontal cortex connections in schizophrenia. Human Brain Mapping, 27, 230238.Google Scholar
Kanaan, R. A., Kim, J. S., Kaufmann, W. E., et al (2005) Diffusion tensor imaging in schizophrenia. Biological Psychiatry, 58, 921929.CrossRefGoogle ScholarPubMed
Keshavan, M. S. (1999) Development, disease and degeneration in schizophrenia: a unitary pathophysiological model. Journal of Psychiatric Research, 33, 513521.CrossRefGoogle ScholarPubMed
Keshavan, M. S., Diwadkar, V. A. & Rosenberg, D. R. (2005) Developmental biomarkers in schizophrenia and other psychiatric disorders: common origins, different trajectories? Epidemiologia e Psichiatria Sociale, 14, 188193.Google Scholar
Kitamura, H., Matsuzawa, H., Shioiri, T., et al (2005) Diffusion tensor analysis in chronic schizophrenia. A preliminary study on a high-field (3.0T) system. European Archives of Psychiatry and Clinical Neuroscience, 255, 313318.Google Scholar
Krabbendam, L., Arts, B., van Os, J., et al (2005) Cognitive functioning in patients with schizophrenia and bipolar disorder: A quantitative review. Schizophrenia Research, 80, 137149.Google Scholar
Kubicki, M., Westin, C. F., Maier, S. E., et al (2002) Uncinate fasciculus findings in schizophrenia: a magnetic resonance diffusion tensor imaging study. American Journal of Psychiatry, 159, 813820.CrossRefGoogle ScholarPubMed
Kubicki, M., Westin, C. F., Nestor, P. G., et al (2003) Cingulate fasciculus integrity disruption in schizophrenia: a magnetic resonance diffusion tensor imaging study. Biological Psychiatry, 54, 11711180.Google Scholar
Kubicki, M., Park, H., Westin, C. F., et al (2005a) DTI and MTR abnormalities in schizophrenia: analysis of white matter integrity. NeuroImage, 26, 11091118.Google Scholar
Kubicki, M., Westin, C. F., McCarley, R. W., et al (2005b) The application of DTI to investigate white matter abnormalities in schizophrenia. Annals of the New York Academy of Science, 1064, 134148.CrossRefGoogle ScholarPubMed
Kubicki, M., McCarley, R., Westin, C. F., et al (2007) A review of diffusion tensor imaging studies in schizophrenia. Journal of Psychiatric Research, 41, 1530.Google Scholar
Kumra, S., Ashtari, M., McMeniman, M., et al (2004) Reduced frontal white matter integrity in early-onset schizophrenia: a preliminary study. Biological Psychiatry, 55, 11381145.Google Scholar
Kumra, S., Ashtari, M., Cervellione, K. L., et al (2005) White matter abnormalities in early-onset schizophrenia: a voxel-based diffusion tensor imaging study. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 934941.Google Scholar
Leucht, S., Kane, J. M., Kissling, W., et al (2005) Clinical implications of Brief Psychiatric Rating Scale scores. British Journal of Psychiatry, 187, 366371.CrossRefGoogle ScholarPubMed
Lim, K. O., Hedehus, M., Moseley, M., et al (1999) Compromised white matter tract integrity in schizophrenia inferred from diffusion tensor imaging. Archives of General Psychiatry, 56, 367374.Google Scholar
Liu, Y., Ford, B., Mann, M. A., et al (2001) Neuregulins increase alpha 7 nicotinic acetylcholine receptors and enhance excitatory synaptic transmission in GABA ergic interneurons of the hippocampus. Journal of Neuroscience, 21, 56605669.Google Scholar
Macdonald, A. W., Carter, C. S., Kerns, J. G., et al (2005) Specificity of prefrontal dysfunction and context processing deficits to schizophrenia in never-medicated patients with first-episode psychosis. American Journal of Psychiatry, 162, 475484.Google Scholar
Marchionni, M. A., Goodearl, A. D., Chen, M. S., et al (1993) Glial growth factors are alternatively spliced erbB2 ligands expressed in the nervous system. Nature, 362, 312318.Google Scholar
Minami, T., Nobuhara, K., Okugawa, G., et al (2003) Diffusion tensor magnetic resonance imaging of disruption of regional white matter in schizophrenia. Neuropsychobiology, 47, 141145.Google Scholar
Nusbaum, A. O., Tang, C. Y., Wei, T., et al (2000) Whole-brain diffusion MR histograms differ between MS subtypes. Neurology, 54, 14211427.Google Scholar
O'Donovan, M. C., Williams, N. M. & Owen, M. J. (2003) Recent advances in the genetics of schizophrenia. Human Molecular Genetics, 12, R125R133.Google Scholar
O'Sullivan, M., Jones, D. K., Summers, P. E., et al (2001) Evidence for ‘cortical’ disconnection as a mechanism of age-related cognitive decline. Neurology, 57, 632638.Google Scholar
Pantelis, C., Yucel, M., Wood, S. J., et al (2005) Structural brain imaging evidence for multiple pathological processes at different stages of brain development in schizophrenia. Schizophrenia Bulletin, 31, 672696.Google Scholar
Park, H. J., Westin, C. F., Kubicki, M., et al (2004) White matter hemisphere asymmetries in healthy subjects and in schizophrenia: a diffusion tensor MRI study. NeuroImage, 23, 213223.Google Scholar
Patel, V. H. & Friedman, L. (1997) MRI of the Brain: Normal Anatomy and Normal Variants. Saunders.Google Scholar
Pfefferbaum, A., Sullivan, E. V., Hedehus, M., et al (2000) Age-related decline in brain white matter anisotropy measured with spatially corrected echoplanar diffusion tensor imaging. Magnetic Resonance Medicine, 44, 259268.Google Scholar
Rovaris, M., Bozzali, M., Lannucci, G., et al (2002) Assessment of normal-appearing white and gray matter in patients with primary progressive multiple sclerosis: a diffusion-tensor magnetic resonance imaging study. Archives of Neurology, 59, 14061412.Google Scholar
Schechter, I., Butler, P. D., Zemon, V. M., et al (2005) Impairments in generation of early-stage transient visual evoked potentials to magno- and parvocellular-selective stimuli in schizophrenia. Clinical Neurophysiology, 116, 22042215.Google Scholar
Seidman, L. J., Pantelis, C., Keshavan, M. S., et al (2003) A review and new report of medial temporal lobe dysfunction as a vulnerability indicator for schizophrenia: a magnetic resonance imaging morphometric family study of the parahippocampal gyrus. Schizophrenia Bulletin, 29, 803830.Google Scholar
Shenton, M. E., Dickey, C. C., Frumin, M., et al (2001) A review of MRI findings in schizophrenia. Schizophrenia Research, 49, 152.CrossRefGoogle ScholarPubMed
Shin, Y. W., Kwon, J. S., Ha, T. H., et al (2006) Increased water diffusivity in the frontal and temporal cortices of schizophrenic patients. NeuroImage, 30, 12851291.Google Scholar
Spitzer, R. L. & Williams, D. (1988) Structured Clinical Interview for Diagnoses – Nonpatient Version. New York State Psychiatric Institute.Google Scholar
Steel, R. M., Bastin, M. E., McConnell, S., et al (2001) Diffusion tensor imaging (DTI) and proton magnetic resonance spectroscopy (IH MRS) in schizophrenic subjects and normal controls. Psychiatry Research, 106, 161170.Google Scholar
Stefansson, H., Sigurdsson, E., Steinthorsdottir, V., et al (2002) Neuregulin I and susceptibility to schizophrenia. American Journal of Human Genetics, 71, 877892.Google Scholar
Sullivan, E. V., Adalsteinsson, E., Hedehus, M., et al (2001) Equivalent disruption of regional white matter microstructure in ageing healthy men and women. NeuroReport, 12, 99104.Google Scholar
Sun, Z., Wang, F., Cui, L., et al (2003) Abnormal anterior cingulum in patients with schizophrenia: a diffusion tensor imaging study. NeuroReport, 14, 18331836.Google Scholar
Szeszko, P. R., Ardekani, B. A., Ashtari, M., et al (2005) White matter abnormalities in first-episode schizophrenia or schizoaffective disorder: a diffusion tensor imaging study. American Journal of Psychiatry, 162, 602605.Google Scholar
Tansella, M. & Burti, L. (2003) Integrating evaluative research and community-based mental heath care in Verona, Italy. British Journal of Psychiatry, 183, 167169.Google Scholar
Taylor, W. D., Hsu, E., Krishnan, K. R., et al (2004) Diffusion tensor imaging: background, potential, and utility in psychiatric research. Biological Psychiatry, 55, 201207.Google Scholar
Tkachev, D., Mimmack, M. L., Ryan, M. M., et al (2003) Oligodendrocyte dysfunction in schizophrenia and bipolar disorder. Lancet, 362, 798805.CrossRefGoogle ScholarPubMed
Tosato, S., Dazzan, P. & Collier, D. (2005) Association between the neuregulin I gene and schizophrenia: a systematic review. Schizophrenia Bulletin, 31, 613617.Google Scholar
Uranova, N. A., Vostrikov, V. M., Orlovskaya, D. D., et al (2004) Oligodendroglial density in the prefrontal cortex in schizophrenia and mood disorders: a study from the Stanley Neuropathology Consortium. Schizophrenia Research, 67, 269275.Google Scholar
Vartanian, T., Fischbach, G. & Miller, R. (1999) Failure of spina cord oligodendrocyte development in mice lacking neuregulin. Proceedings of the National Academy of Sciences of the USA, 96, 731735.Google Scholar
Ventura, J., Nuechterlein, K. H., Subotnik, K. L., et al (2000) Symptom dimensions in recent-onset schizophrenia and mania: a principal components analysis of the 24-item Brief Psychiatric Rating Scale. Psychiatry Research, 97, 129135.Google Scholar
Wang, F., Sun, Z., Cui, L., et al (2004) Anterior cingulum abnormalities in male patients with schizophrenia determined through diffusion tensor imaging. American Journal of Psychiatry, 161, 573575.Google Scholar
Williams, N. M., O'Donovan, M. C. & Owen, M. J. (2005) Is the dysbindin gene (DTNBPI) a susceptibility gene for schizophrenia? Schizophrenia Bulletin, 31, 800805.Google Scholar
Wolkin, A., Choi, S. J., Szilagyi, S., et al (2003) Inferior frontal white matter anisotropy and negative symptoms of schizophrenia: a diffusion tensor imaging study. American Journal of Psychiatry, 160, 572574.Google Scholar
World Health Organization (1992) Schedules for Clinical Assessment in Neuropsychiatry. WHO.Google Scholar
World Health Organization (1996) Schede di Valutazione Clinica in Neuropsichiatria. SCAN 2.1. 11 Pensiero Scientifico Editore.Google Scholar
Figure 0

Table 1 Socio-demographic and clinical variables of the sample

Figure 1

Fig. 1 Circular regions of interest were placed in cortical white matter on the b=0 echoplanar images, and then automatically transferred to apparent diffusion coefficient (ADC) maps (A, frontal lobes; B, temporal lobes; C, parietal lobes; D, occipital lobes).

Figure 2

Table 2 Apparent diffusion coefficient measures for cortical white matter.

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