Brain volumes in psychotic youth with schizophrenia and mood disorders.
BACKGROUND: We sought to test the hypothesis that deficits in grey matter volume are characteristic of psychotic youth with early-onset schizophrenia-spectrum disorders (EOSS) but not of psychotic youth with early-onset mood disorders (EOMD). METHODS: We used magnetic resonance imaging to examine brain volume in 24 psychotic youth (13 male, 11 female) with EOSS (n = 12) or EOMD (n = 12) and 17 healthy controls (10 male, 7 female). We measured the volume of grey and white matter using an automated segmentation program. RESULTS: After adjustment for age and intracranial volume, whole brain volume was lower in the EOSS patients than in the healthy controls (p = 0.001) and EOMD patients (p = 0.002). The EOSS patients had a deficit in grey matter volume (p = 0.005), especially in the frontal (p = 0.003) and parietal (p = 0.006) lobes, with no significant differences in white matter volume. LIMITATIONS: The main limitations of our study were its small sample size and the inclusion of patients with depression and mania in the affective group. CONCLUSION: Adolescents with EOSS have grey matter deficits compared with healthy controls and psychotic adolescents with EOMD. Our results suggest that grey matter deficits are not generally associated with psychosis but may be specifically associated with schizophrenia. Larger studies with consistent methods are needed to reconcile the contradictory findings among imaging studies involving psychotic youth.
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Related Subject Headings
- Young Adult
- Schizophrenia
- Psychotic Disorders
- Psychiatry
- Psychiatric Status Rating Scales
- Parietal Lobe
- Mood Disorders
- Male
- Magnetic Resonance Imaging
- Image Interpretation, Computer-Assisted
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Young Adult
- Schizophrenia
- Psychotic Disorders
- Psychiatry
- Psychiatric Status Rating Scales
- Parietal Lobe
- Mood Disorders
- Male
- Magnetic Resonance Imaging
- Image Interpretation, Computer-Assisted