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Insular volume abnormalities associated with different transition probabilities to psychosis
R Smieskova1, P Fusar-Poli, J Aston
1Department of Psychiatry, University of Basel, Switzerland.
Psychological Medicine
|December 1, 2011
Summary
Individuals at risk for psychosis show brain volume differences, particularly in the insula. These structural changes correlate with symptom severity and global functioning, indicating varying transition probabilities.
Area of Science:
- Neuroscience
- Psychiatry
- Neuroimaging
Background:
- Individuals vulnerable to psychosis exhibit brain volumetric abnormalities.
- Structural alterations linked to varying transition probabilities remain unclear.
- Voxel-based morphometry (VBM) is employed to investigate these differences.
Purpose of the Study:
- To investigate grey matter volume (GMV) abnormalities in individuals at risk for psychosis.
- To compare GMV in different at-risk mental state (ARMS) groups and first-episode psychosis (FEP) patients.
- To correlate structural alterations with clinical symptoms and functioning.
Main Methods:
- Compared neuroleptic-free groups: FEP (n=16), ARMS (n=31) divided into short-term (ARMS-ST, n=18) and long-term (ARMS-LT, n=13) follow-up, and healthy controls (HC, n=19).
- Utilized three-dimensional (3D) magnetic resonance imaging (MRI) for voxel-based morphometry (VBM) analysis.
- Assessed GMV differences and their correlation with global functioning and symptomatology.
Main Results:
- ARMS-ST group showed reduced GMV in the right and left insula compared to ARMS-LT and FEP groups, respectively.
- GMV differences positively correlated with global functioning in the ARMS group.
- Insular alterations were linked to negative symptoms and hallucinations; antipsychotic use affected GMV in FEP.
Conclusions:
- GMV abnormalities in individuals at high risk for psychosis are associated with symptom severity and global functioning.
- Alterations in the right insula may indicate a higher risk for transition to psychosis.
- These findings suggest distinct transition probabilities are related to specific structural changes.
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