Case Control Study
Copyright ©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatr. Sep 22, 2016; 6(3): 311-321
Published online Sep 22, 2016. doi: 10.5498/wjp.v6.i3.311
Voxel-based magnetic resonance imaging investigation of poor and preserved clinical insight in people with schizophrenia
Adegboyega Sapara, Dominic H Ffytche, Michael A Cooke, Steven CR Williams, Veena Kumari
Adegboyega Sapara, Michael A Cooke, Veena Kumari, Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
Dominic H Ffytche, Department of Old Age Psychiatry and Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
Steven CR Williams, Department of Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
Veena Kumari, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London SE5 8AF, United Kingdom
Author contributions: Sapara A, Ffytche DH and Kumari V designed the study; Cooke MA carried out the neuropsychological assessments; Williams SCR assisted with neuroimaging data acquisition; Sapara A performed all analyses and wrote the manuscript under Ffytche DH and Kumari V’s joint supervision.
Supported by The Wellcome Trust, United Kingdom and was carried out as part of the first author’s PhD research under Professor Veena Kumari and Dr Dominic ffytche’s supervision, Nos. 067427 and 072298; Professor Kumari is part funded by the Biomedical Research Centre for Mental Health at the Institute of Psychiatry, Psychology and Neuroscience King’s College London, and the South London and Maudsley NHS Foundation Trust, United Kingdom (to Kumari V).
Institutional review board statement: The study procedures had the approval (reference number 209/02) of the ethics committee of the Institute of Psychiatry and South London and Maudsley Foundation NHS Trust, London.
Informed consent statement: All participants provided written informed consent.
Conflict-of-interest statement: None of the authors declare any conflict of interest in this study.
Data sharing statement: The anonymised dataset is available from the first author and the corresponding author.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Veena Kumari, PhD, Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, London SE5 8AF, United Kingdom. veena.kumari@kcl.ac.uk
Telephone: +44-207-8480233
Received: March 2, 2016
Peer-review started: March 2, 2016
First decision: April 15, 2016
Revised: June 23, 2016
Accepted: July 11, 2016
Article in press: July 13, 2016
Published online: September 22, 2016
Abstract
AIM

To define regional grey-matter abnormalities in schizophrenia patients with poor insight (Insight-), relative to patients with preserved clinical insight (Insight+), and healthy controls.

METHODS

Forty stable schizophrenia outpatients (20 Insight- and 20 Insight+) and 20 healthy controls underwent whole brain magnetic resonance imaging (MRI). Insight in all patients was assessed using the Birchwood Insight Scale (BIS; a self-report measure). The two patient groups were pre-selected to match on most clinical and demographic parameters but, by design, they had markedly distinct BIS scores. Voxel-based morphometry employed in SPM8 was used to examine group differences in grey matter volumes across the whole brain.

RESULTS

The three participant groups were comparable in age [F(2,57) = 0.34, P = 0.71] and the patient groups did not differ in age at illness onset [t(38) = 0.87, P = 0.39]. Insight- and Insight+ patient groups also did not differ in symptoms on the Positive and Negative Syndromes scale (PANSS): Positive symptoms [t(38) = 0.58, P = 0.57], negative symptoms [t(38) = 0.61, P = 0.55], general psychopathology [t(38) = 1.30, P = 0.20] and total PANSS scores [t(38) = 0.21, P = 0.84]. The two patient groups, as expected, varied significantly in the level of BIS-assessed insight [t(38) = 12.11, P < 0.001]. MRI results revealed lower fronto-temporal, parahippocampal, occipital and cerebellar grey matter volumes in Insight- patients, relative to Insight+ patients and healthy controls (for all clusters, family-wise error corrected P < 0.05). Insight+ patient and healthy controls did not differ significantly (P > 0.20) from each other.

CONCLUSION

Our findings demonstrate a clear association between poor clinical insight and smaller fronto-temporal, occipital and cerebellar grey matter volumes in stable long-term schizophrenia patients.

Keywords: Psychosis, Insight, Grey matter volumes, Fronto-temporal, Neural networks, Birchwood insight scale

Core tip: Poor clinical insight is the most prevalent symptom in patients with schizophrenia and is of growing importance due to its direct association with poor clinical outcomes, such as frequent relapses and hospital admissions. This study identified significantly reduced fronto-temporal, parahippocampal, occipital and cerebellar grey matter volumes in Insight- patients relative to both Insight+ patients and healthy controls. The involvement of multiple brain areas and corresponding neural networks supports the theory that clinical insight, as a neurological function, is not confined to specific neuroanatomical regions but probably a function of a complex neurocognitive interplay with contributions from multiple neural networks.