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Shared white-matter dysconnectivity in schizophrenia and bipolar disorder with psychosis

Published online by Cambridge University Press:  04 August 2014

J. Kumar
Affiliation:
Translational Neuroimaging, Division of Psychiatry, Institute of Mental Health, University of Nottingham, Nottingham, UK
S. Iwabuchi
Affiliation:
Translational Neuroimaging, Division of Psychiatry, Institute of Mental Health, University of Nottingham, Nottingham, UK
S. Oowise
Affiliation:
The Forensic Hospital, Justice and Forensic Mental Health Network, Sydney, Australia
V. Balain
Affiliation:
Nottinghamshire Healthcare NHS Trust, Nottingham, UK
L. Palaniyappan*
Affiliation:
Translational Neuroimaging, Division of Psychiatry, Institute of Mental Health, University of Nottingham, Nottingham, UK Nottinghamshire Healthcare NHS Trust, Nottingham, UK
P. F. Liddle
Affiliation:
Translational Neuroimaging, Division of Psychiatry, Institute of Mental Health, University of Nottingham, Nottingham, UK
*
*Address for correspondence: Dr L. Palaniyappan, Room-09, C Floor, Institute of Mental Health Building, Triumph Road, Nottingham NG7 2TU, England, UK. (Email: Lena.Palaniyappan@nottingham.ac.uk)

Abstract

Background

There is an appreciable overlap in the clinical presentation, epidemiology and treatment response of the two major psychotic disorders – schizophrenia and bipolar disorder. Nevertheless, the shared neurobiological correlates of these two disorders are still elusive. Using diffusion tensor imaging (DTI), we sought to identify brain regions which share altered white-matter connectivity across a clinical spectrum of psychotic disorders.

Method

A sample of 41 healthy controls, 62 patients in a clinically stable state of an established psychotic disorder (40 with schizophrenia, 22 with bipolar disorder) were studied using DTI. Tract-based spatial statistics (TBSS) was used in order to study group differences between patients with psychosis and healthy controls using fractional anisotropy (FA). Probabilistic tractography was used in order to visualize the clusters that showed significant differences between these two groups.

Results

The TBSS analysis revealed five clusters (callosal, posterior thalamic/optic, paralimbic, fronto-occipital) with reduced FA in psychosis. This reduction in FA was associated with an increase in radial diffusivity and a decrease in mode of anisotropy. Factor analysis revealed a single white-matter integrity factor that predicted social and occupational functioning scores in patients irrespective of the diagnostic categorization.

Conclusions

Our results show that a shared white-matter dysconnectivity links the two major psychotic disorders. These microstructural abnormalities predict functional outcome better than symptom-based diagnostic boundaries during a clinically stable phase of illness, highlighting the importance of seeking shared neurobiological factors that underlie the clinical spectrum of psychosis.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2014 

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