© 2007 The Royal College of Psychiatrists
Grey matter abnormalities in first-episode schizophrenia and affective psychosis
Department of Psychology, University of Westminster, London, UK
MRCPsych, Institute of Psychiatry, Division of Psychological Medicine, King’s College London, London, UK
Sir Charles Gairdner Hospital, Department of Psychiatry, Perth, Australia
University of West Indies, Department of Psychiatry, Trinidad and Tobago
Institute of Psychiatry, Department of Neurology, King’s College London, London, UK
University of Cambridge, Department of Psychiatry, Addenbrooke’s Hospital, Cambridge, UK
Institute of Psychiatry, Department of Neurology, King’s College London
Fulbourn Hospital, Cambridge, UK
Institute of Psychiatry, Division of Psychological Medicine, King’s College London
University of Cambridge, Department of Psychiatry, Addenbrooke’s Hospital, Cambridge
Institute of Psychiatry, Division of Psychological Medicine, King’s College London
Correspondence: Kevin Morgan, Department of Psychology, University of Westminster, 309 Regent Street, London W1B 2UW, UK. Email: k.d.morgan{at}wmin.ac.uk
Declaration of interests None. Funding is detailed in Acknowledgements.
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Background Grey matter and other structural brain abnormalities are consistently reported in first-onset schizophrenia, but less is known about the extent of neuroanatomical changes in first-onset affective psychosis.
Aims To determine which brain abnormalities are specific to (a) schizophrenia and (b) affective psychosis.
Method We obtained dual-echo (proton density/T2-weighted) magnetic resonance images and carried out voxel-based analysis on the images of 73 patients with first-episode psychosis (schizophrenia n=44, affective psychosis n=29) and 58 healthy controls.
Results Both patients with schizophrenia and patients with affective psychosis had enlarged lateral and third ventricle volumes. Regional cortical grey matter reductions (including bilateral anterior cingulate gyrus, left insula and left fusiform gyrus) were evident in affective psychosis but not in schizophrenia, although patients with schizophrenia displayed decreased hippocampal grey matter and increased striatal grey matter at a more liberal statistical threshold.
Conclusions Both schizophrenia and affective psychosis are associated with volumetric abnormalities at the onset of frank psychosis, with some of these evident in common brain areas.
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Neuroimaging studies of first-episode schizophrenia have shown neuroanatomical abnormalities, including ventricular enlargement (Cahn et al, 2002) and subtle grey matter deficits in the whole brain (Fannon et al, 2000a), frontal and temporal lobes (Job et al, 2002). Furthermore, some abnormalities such as basal ganglia enlargement seem to appear early in the illness but only following antipsychotic exposure (Lawrie & Abukmeil, 1998). While abnormalities in the cingulate gyrus (Sassi et al, 2004) and temporal lobe (Kasai et al, 2003a) have been observed in first-onset affective psychosis, it is not clear whether they are as frequent and severe as in schizophrenia. Using high-resolution magnetic resonance imaging (MRI) and voxel-based morphometry methods of image analysis, we set out to examine the brain structure of patients participating in an epidemiological study of first-episode psychosis. We predicted that compared to healthy controls, patients with schizophrenia and affective psychosis would have frontal and temporal lobe grey matter deficits and increased ventricular and striatal volumes, and that those abnormalities would be more severe in schizophrenia.
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Sample
Patients
Participants were inner city South London residents enrolled in an epidemiological study of first-onset psychosis (ÆSOP: Aetiology and Ethnicity in Schizophrenia and Other Psychoses). Details of the ÆSOP study and the overall methodology can be found in Morgan et al, (2006). Inclusion criteria for the MRI study were (a) age 16–65 years; (b) resident in defined area (population 265 950); (c) presenting consecutively for the first time to local psychiatric services (in-patient and out-patient) between 1997 and 2000 with symptoms meeting functional psychosis criteria (ICD–10: F20 Schizophrenia and F30–39 Affective disorders – psychotic codings; World Health Organization, 1992). Exclusion criteria were (a) head trauma history with > 1-hour unconsciousness; (b) central nervous system disease; (c) poor English fluency; (d) transient psychotic symptoms resulting from acute intoxication (ICD–10) following consumption of psychoactive substance.
Only patients meeting criteria for a narrow definition of schizophrenia (ICD–10 F20) were included in the ‘schizophrenia’ group. Patients diagnosed with bipolar disorder or depressive psychosis were allocated to the ‘affective psychosis’ group (ICD–10 F30–39). To ensure the diagnostic homogeneity of the two groups, patients with schizoaffective disorder were excluded from either group.
There were 153 patients diagnosed with either schizophrenia or affective
psychosis enrolled in the ÆSOP study; 97 of those patients consented to
MRI scanning; 9 of these did not complete the full scanning procedure and
therefore were not included in the analysis. Fifteen further scans were
excluded due to (a) subject motion n=13; (b) congenital hydrocephalus
n=1; (c) sub-arachnoid cyst n=1. Therefore, 73 patients were
included in the analysis, 44 of whom were diagnosed with schizophrenia, 12
with psychotic depression and 17 with bipolar disorder. These 73 patients were
younger (mean age 27.1 years (s.d.=7.6) v. 30.1 years (s.d.=9.1),
t=2.8, P=0.007) and comprised proportionately more White
British patients (27 (37%) v. 12 (16%), 
2=8.4,
P=0.004) than the 80 patients not included in the MRI analysis. There
were no significant differences between the patients included and those not
included in the analysis in terms of the proportion of male patients
(2=1.2, P=0.27) and the number of patients with
schizophrenia (2=2.3, P=0.13).
Controls
There were 58 controls recruited from the same community as the patients.
Exclusion criteria were the same as those as for the patients. Evidence of
past or present psychosis, screened with the Psychosis Screening Questionnaire
(Bebbington & Nayani,
1995), was an additional exclusion criterion. We excluded 8 MRI
scans (subject motion n=7; suspected hydrocephalus n=1). For
the MRI analysis, controls were separately compared to the patients with (a)
schizophrenia and (b) affective psychosis. The controls were paired with the
patients in the schizophrenia and affective psychosis groups on the basis of
age (± 5 years) and gender. Thus, 44 paired controls were included in
the analysis of the schizophrenia patients and 29 paired controls in the
analysis of the patients with affective psychosis. In addition to the patient
versus control subject analyses, an analysis directly comparing patients with
schizophrenia with those with affective psychosis was conducted.
Ethical approval was granted by the South London and Maudsley Trust Research Ethical Committee. All participants gave written, informed consent.
Clinical assessments
Patients were interviewed using the WHO Schedules for Clinical Assessment
in Neuropsychiatry (WHO–SCAN) (World
Health Organization, 1994). ICD–10 diagnoses were made in
consensus meetings with senior clinicians (R.M. or J.L.), using WHO–SCAN
information and clinical notes. Using the WHO–SCAN data we encoded (in
weeks): duration of illness as the onset date of psychotic symptoms to MRI
date; and lifetime duration of antipsychotic exposure (to MRI date). Total
symptomology was scored by summing the individual item scores on the
WHO–SCAN using the algorithm of Wing & Sturt
(1978).
Structural magnetic resonance image acquisition
Scans were acquired with a GE Signa 1.5–T system, at the Maudsley
Hospital, London. Contiguous, interleaved proton-density- and T2-weighted 3 mm
thick coronal plane dual-echo images were acquired, providing whole brain
coverage. A repetition time of 4000 ms and effective echo times of 20 ms and
85 ms were used with 8-echo train length. Matrix size was 256 x 192,
collected from a rectangular field-of-view of 22 cm x 16.5 cm, giving an
in-plane resolution of 0.859 mm. Total acquisition time was 10 min, 12 s.
Structural magnetic resonance image processing
The methods used for segmentation and registration of each fast spin echo
data-set are described in detail elsewhere
(Suckling et al,
1996; Bullmore et al,
1999). Briefly, subject masks were generated to identify neural
tissue. Extracerebral tissues were removed first, using an automated
algorithm. Manually editing the skull-stripped images was necessary only to
remove brainstem and cerebellum from the cerebral hemispheres and
diencephalon. The probability of each intracerebral voxel belonging to each of
four possible tissue classes (grey matter, white matter, cerebrospinal fluid,
or dura/vasculature) was estimated with a modified fuzzy clustering algorithm
(Suckling et al,
1996). This type of segmentation assigns for each voxel a value in
the range 0–1 indicating the fraction of the voxel comprised by each
tissue type (e.g. a grey matter value of 0.7 means 70% of tissue represented
by that voxel is grey matter; therefore the value indicates the proportion of
the voxel occupied by grey matter). Total grey tissue volume was calculated at
this stage of the analysis.
The construction of the sample’s template image is described elsewhere (Dazzan et al, 2004). In summary, a template image was constructed using the AFNI (Analysis of Functional Neuroimages) programme from 6 proton-density images acquired from 6 healthy controls and then averaging these images. Tissue distribution maps were registered onto the template by first registering each subject’s proton density image using a 9-parameter affine registration, minimising between image grey-level difference. This registration aligns all the images together, and scales them to the same gross dimensions. The derived mapping was then applied to the corresponding tissue maps.
Ventricular volume
Additional masks were generated per subject by tracing around the lateral
and third ventricles in native space, in every slice in which they were
visible. Ventricles were traced by one rater (S.-J.P.), masked to age, gender,
ethnicity and patient/control status. Within the masked area, cerebrospinal
fluid volume was calculated using the data generated from the previously
described modified fuzzy clustering algorithm.
Statistical analysis
Between-group regional differences in grey matter volume were estimated by
fitting an analysis of covariance (ANCOVA) model at each intracerebral voxel
in standard space covarying for age and total grey matter volume. Permutation
testing was used to assess statistical significance, and regional
relationships were tested at voxel cluster level
(Bullmore et al, 1999,
Sigmundsson et al,
2001). Given that structural brain changes are likely to extend
over a number of contiguous voxels, test statistics incorporating spatial
information, such as 3-D cluster mass (the sum of suprathreshold voxel
statistics), are generally more powerful than other possible test statistics
informed only by single voxel data. We set the statistical threshold for
cluster significance in all analyses so that the expected number of
false-positive clusters (P-value times number of tests) was <1
false-positive. We examined the association between grey matter cluster size
and measures for duration of illness, duration of antipsychotic exposure and
total symptoms using Pearson correlation coefficients. Student’s
t-test calculations were used to analyse between-group differences in
ventricle to brain volume ratio and total grey matter and cerebrospinal fluid
volume.
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Forty-four patients received an ICD–10 schizophrenia diagnosis and 29 patients a diagnosis of bipolar disorder (n=17) or psychotic depression (n=12). T-tests and
2 analyses
showed there were no significant differences between the schizophrenia and
affective psychosis groups in terms of duration of illness, duration of
antipsychotic exposure, total symptom scores
(Table 1) and number of
compulsory admissions. The percentage of patients who were prescribed atypical
antipsychotics was higher among patients with schizophrenia than in those with
affective psychosis (22 (50%) v. 2 (7%), 2=16.7,
P<0.001). More patients with affective psychosis were prescribed
typical antipsychotics (n=14, 48%) than patients with schizophrenia
(n=13, 30%). This difference did not reach statistical
significance. |
View this table: [in a new window] | Table 1 Clinical characteristics of the patient sample |
Schizophrenia v. controls
Patients with schizophrenia had, on average, 2 fewer years of education
(mean 12.4 years (s.d. 2.0) v. 14.1 years (s.d. 2.6), t=3.5,
d.f.=86, P=0.001) and scored significantly lower on the National
Adult Reading Test (NART), an estimated measure of premorbid IQ
(Nelson & Willison, 1991)
than the control group (93.3 (s.d. 16.0) v. 106.5 (s.d. 11.9),
t=4.1, d.f.=75, P<0.001). Analyses using t-tests
and 2 showed there were no significant differences between the
schizophrenia patients and controls in terms of age, gender, handedness,
parental socio-economic status and ethnicity
(Table 2).
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View this table: [in a new window] | Table 2 Characteristics of sample: patients and controls |
Total tissue and ventricular volumes
There were no between-group differences in total grey matter or
cerebrospinal fluid volume. However, patients with schizophrenia had
significantly larger lateral ventricle to brain ratio (+17.7% volume:
t=2.33, d.f.=86, P<0.03) and larger third ventricle to
brain ratio (+63.2% volume: t=3.08, d.f.=86, P<0.01) than
healthy controls (Table 3).
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View this table: [in a new window] | Table 3 Mean total tissue, total cerebrospinal fluid and ventricular volumes (ml) in patients and normal controls1 |
Regional proportional grey tissue volume differences
There were no regional differences in grey matter volume between patients
and controls (Table 4).
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View this table: [in a new window] | Table 4 Regional differences in grey matter: patients v. normal controls and schizophrenia v. affective psychosis, and correlation of clinical factors with grey matter volume and ventricle to whole brain ratios |
However, a secondary analysis of the grey matter map using a lowered statistical threshold for cluster significance (P-value set at 0.01), detected 3 excess grey matter areas and 1 grey matter deficit area in the patients. The excess clusters were located in the left and right lenticular nucleus and the right pre-central gyrus. The deficit cluster was located at the right parahippocampal gyrus.
Symptomology, duration of illness and duration of antipsychotic exposure
These clinical factors were not associated with lateral or third ventricle
volume (Table 4).
Affective psychosis v. controls
Analyses using t-tests and 2 showed there were no
significant differences between the patients with affective psychosis and
controls in terms of age, gender, years of education, NART, handedness,
parental socio-economic status and ethnicity
(Table 2).
Total tissue and ventricular volumes
There were no between-group differences in total grey matter or CSF volume.
Patients with affective psychosis had larger third ventricle to brain ratio
than controls (+70% volume: t=2.72, d.f.=56, P<0.01), but
there was no significant between-group difference in lateral ventricle volume
(Table 3).
Regional proportional tissue volume differences
Four regional clusters of grey matter deficit were identified in patients
with affective psychosis compared to the controls. These were located: (a)
bilaterally within the anterior cingulate gyrus (centred Brodmann’s Area
(BA) 24), and extending anteriorly to BA31 and posteriorly to BA23; (b) within
the left insula; (c) at the right postcentral gyrus (BA1 and BA2); (d) at the
left fusiform gyrus (BA37) and extending laterally into the lingual gyrus. The
patients had a single grey matter excess cluster located in the left
lenticular nucleus (Table 4;
see Fig. DS1 in data supplement of online version of this paper).
Symptomology, duration of illness and duration of antipsychotic exposure
Longer duration of antipsychotic exposure correlated with increased third
ventricle volume (r=0.49, P=0.007) and increased lateral
ventricle volume (r=0.54, P=0.003). Increased third
ventricle volume correlated with higher total symptom scores (r=0.41,
P=0.03). The amount of grey matter in the regional deficit and excess
tissue clusters identified did not correlate with symptomology scores,
duration of illness or duration of antipsychotic exposure
(Table 4).
Schizophrenia v. affective psychosis
The proportion of males in the schizophrenia group was significantly higher
(n=31 (70.4%) v. n=11 (38.0%) 2=7.60,
d.f.=1, P=0.006). Patients with schizophrenia had on average 1.1 less
years of education (mean 12.4 years (s.d. 2.0) v. 13.5 years
(s.d.=2.5), t=1.96, d.f.=71, P=0.056) and scored
significantly lower on NART (93.3 (s.d.=16.0), v. 102.8 (s.d.=14.0),
t=2.5, d.f.=63, P=0.016). Patients with schizophrenia were
on average 3.2 years younger than patients with affective psychosis (25.8
years (s.d.= 7.1) v. 29.0 years (s.d.=7.9)). This difference in age
bordered on statistical significance (t=1.78, d.f.=71,
P=0.079). Analyses using t-tests and 2
showed there were no significant differences between the two patient groups in
terms of handedness, parental socio-economic status and ethnicity
(Table 2).
Total tissue and ventricular volumes
An ANCOVA (controlling for age and gender) was used compare total tissue
and ventricular volumes. There were no between-group differences in total grey
matter, cerebrospinal fluid volume or ventricular volumes.
Regional proportional grey tissue volume differences
In addition to age and total grey matter volume, gender was added as a
covariate in the analysis of regional grey matter differences. One regional
cluster of grey matter deficit was identified in the affective psychosis
group. This was located bilaterally within the anterior cingulate gyrus,
centred on Brodmann’s Area (BA) 24, and extending anteriorly to BA31 and
BA32 and posteriorly to BA23 (Table
4). As there were significant differences in the type of
antipsychotic taken, an additional analysis adding type of antipsychotic as a
covariate (typicals, atypicals or none) was performed. When type of
antipsychotic was added as a covariate, there were no differences between
groups in regional grey matter.
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In contrast with other first-onset MRI investigations, we found relatively few structural abnormalities in schizophrenia but identified several regional grey matter deficits in the affective psychoses. Furthermore, in patients with affective disorders, but not with schizophrenia, we found increased ventricular volumes to be associated with higher total symptom ratings and longer lifetime use of antipsychotics.
Schizophrenia
Our finding of increased ventricular volume is consistent with other
first-episode schizophrenia studies
(Fannon et al,
2000b; Cahn et
al, 2002). Evidence of ventricular enlargement in patients
with first-episodes either never treated or minimally treated with
antipsychotics (Fannon et al,
2000b) suggests that this abnormality either predates or
closely follows psychosis onset and it is perhaps of note that in our sample,
ventricular abnormalities in schizophrenia were not associated with
symptomology, duration of illness or duration of antipsychotic exposure.
Contrary to our prediction that patients with schizophrenia would show frontal
and temporal grey matter reductions and increased striatal grey matter, no
grey matter abnormalities were found. To explore the possibility that this
could have been due to a lack of statistical power, we re-ran the grey matter
comparison using a lower statistical threshold. This analysis identified grey
matter differences in two of the predicted locations: lenticular nuclei
increases (left and right) and reductions in the right parahippocampal gyrus
(part of the temporal lobe). Although in this post-hoc analysis the
possibility of false-positive type 1 errors is increased, the findings may
nevertheless indicate the presence of a pattern of structural abnormalities
similar but less pronounced than that reported elsewhere
(Lawrie & Abukmeil, 1998;
Fannon et al,
2000a; Job et
al, 2002).
Affective psychosis
We found enlargement of third ventricle in the affective psychoses, but in
contrast to the schizophrenia group, this was correlated with higher total
symptom scores and longer duration of antipsychotic exposure. The latter may
indicate that this brain abnormality is less likely to reflect
neurodevelopmental pathology than in schizophrenia
The grey matter deficits we found are in line with other studies of affective disorders. Anterior cingulate gyrus deficits have been found in bipolar disorder (Sassi et al, 2004) and major depression (Bremner et al, 2002) and in people with a genetic risk for bipolar disorder, but not for schizophrenia (McDonald et al, 2004). Findings such as these suggest a role for the anterior cingulate gyrus in the regulation of emotions. Combined ratings for affective symptoms (depression and mania) in the affective psychosis group were as one might expect higher than in the schizophrenia group (t=2.8, P=0.008), but a post-hoc analysis showed no correlation between severity of affective symptoms and the amount of grey matter in the anterior cingulate gyrus cluster.
Recent findings have shown left fusiform grey matter deficits in patients with mixed psychotic disorders, scanned 1 year after psychosis onset (Pantelis et al, 2003). The possible role of the fusiform gyrus in the psychopathology of psychosis remains unclear but it has been suggested that it is implicated in the appraisal and encoding of faces in disorders such as schizophrenia (Onitsuka et al, 2003). In our sample we found no correlation between fusiform grey matter volume and symptoms scores, duration of illness and duration of antipsychotic exposure. Similarly, no association was found between those variables and grey matter volume in the two other deficit regions identified in our patients with affective psychosis: the post central gyrus and the left insula. Although a recent ventricle to brain ratio study (Job et al, 2002) observed reduced postcentral gyrus grey matter in schizophrenia, there have been few reports elsewhere in the psychosis literature of structural abnormalities in this region. On the other hand, left insula grey matter deficits have previously been reported in ventricle to brain ratio studies of affective psychosis (Kubicki et al, 2002), as well as in first-onset schizophrenia (Kasai et al, 2003b) and schizophrenia of mixed chronicity (Kubicki et al, 2002).
The finding of more grey matter deficits in affective psychosis than in schizophrenia was contrary to our predictions and is at variance with other studies of psychosis. It is unlikely the findings can be accounted for by anomalies in image acquisition or processing as such effects would not occur systematically in one group only. One possible confounder is between-patient group differences in prescribed antipsychotics; this could provide some explanation for these findings as recent research suggests different effects of typical and atypical antipsychotics on brain structure (Garver et al, 2005; Lieberman et al, 2005). Indeed, in an earlier analysis of our sample (Dazzan et al, 2005) we found that, in comparison to drug-free patients, patients taking typicals, but not those taking atypicals, had smaller volumes in the lobulus paracentralis; anterior cingulate gyrus; superior and medial frontal gyri; superior and middle temporal gyri; insula; and precuneus. It is conceivable that such an effect might explain the greater deficits in the affective psychosis group rather than the schizophrenia group as more patients with affective psychosis were taking typical antipsychotics (48%) than patients with schizophrenia (30%) and significantly more patients with schizophrenia were taking atypicals (50% v. 7%). A role for differences in pharmacological treatment was confirmed by our additional analysis showing that when these differences are taken into account, there are no regional differences in brain structure between patient groups.
Treatment with typical antipsychotics may also be relevant to the increased left lenticular nucleus grey matter as these drugs have a strong affinity to subcortical D2 dopamine receptors and receptor block-ade may induce cellular growth and increase blood flow (Corson et al, 2002). Striatal enlargement appears less likely in patients treated only with atypical antipsychotics (Corson et al, 1999), which have weaker D2 receptor affinity. Indeed, in a previous analysis on this first-onset sample, we showed that patients treated with atypicals have similar striatal volumes to drug-free patients, while subjects taking typicals had significantly larger basal ganglia volumes than drug-free patients (Dazzan et al, 2005).
Schizophrenia and affective psychosis
A direct comparison of the two patients groups (controlling for
between-group differences in age, gender and total grey matter volume)
revealed grey matter of the anterior cingulate gyrus in the patients with
affective psychosis, but no other neuroanatomical differences. This was
consistent with the findings of the patient–control comparisons. The
patients with affective psychosis were prescribed more typical antipsychotics
and significantly less atypical antipsychotics than the patients with
schizophrenia. When the analysis was repeated, controlling for type of
antipsychotic, no between-group differences were found. This suggests that
grey matter changes may be associated with variations in the type of
antipsychotic taken and is consistent with our previous finding of typicals
being associated with grey matter reductions in the anterior cingulate gyrus
(Dazzan et al,
2005).
The finding of regional deficits in the patients with affective psychosis was of interest and indicates that some morphological changes take place in those patients close to illness onset or at prodromal or even premorbid stage. We found significant, but fewer neuroanatomical abnormalities in schizophrenia. The absence of more widespread differences in these patients might be accounted for by the epidemiological basis of our study, in which both patients and controls were recruited from the same catchment area. Using an epidemiologically based sample avoids the potential bias of recruiting subjects according to factors such as illness severity and family history. Many reports on patients with first-episode schizophrenia come from university clinics, referral centres and in-patient samples, which attract subjects not necessarily representative of first-episode schizophrenia in general (Job et al, 2002, Pantelis et al, 2003) and it is possible that our findings do not reflect the findings reported in patients with more severe illnesses. The use of an epidemiological sample may also explain in part the findings in the affective psychosis sample. The recruitment of those patients was not based on referrals from bipolar and other affective clinics and may have resulted in a more psychotic affective sample than that seen in earlier MRI studies of affective disorders.
Limitations
This study is not without limitations. First, the finding of grey matter
abnormalities in the schizophrenia patients at a lower statistical threshold
suggests that more grey matter changes in this group might have been
identified in a larger sample. Second, because there may be longitudinal MRI
changes following the first episode, a different pattern of group differences
may be evident when patients are studied later in the illness. And third, our
appraisal of the relationship between antipsychotic medication, grey matter
change and diagnosis was limited by the fact that patients were not selected
into the study on the basis of drug prescription status. This would have
allowed for a more systematic analysis of the potential effects of exposure to
different types of antipsychotic and that of drug-free status.
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We thank Mandy Sharpley and the other ÆSOP researchers who helped with data collection.
The AESOP study was funded by the Medical Research Council (UK) and the Stanley Medical Research Institute. P.D. research is supported by a NARSAD Young Investigator Award.
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