Progress in Neuro-Psychopharmacology and Biological Psychiatry
White matter reduction in patients with schizophrenia as revealed by voxel-based morphometry: An activation likelihood estimation meta-analysis
Introduction
Schizophrenia has long been considered a disconnection between different cortical areas (Friston and Frith, 1995, Stephan et al., 2006). For example, distinct gray matter networks have been identified to be abnormal in patients with schizophrenia in comparison with healthy controls (Glahn et al., 2008). Given that white matter constitutes the anatomical infrastructure for neural connectivity, it is reasonable to hypothesize the existence of white matter abnormalities in patients with schizophrenia.
Using magnetic resonance imaging (MRI), several studies have shown white matter abnormalities in patients with schizophrenia relative to healthy controls. The whole brain white matter volume was found to be decreased by 1% in schizophrenia patients (Wright et al., 2000). Using region of interest (ROI) analysis, some studies have reported decreases in the white matter volume of the frontal lobes (Buchanan et al., 1998, Hulshoff Pol et al., 2002), but the data on the frontal lobe deficit has not been conclusive. Recently, voxel-based morphometry (VBM) analysis (Ashburner and Friston, 2000) has been used extensively to estimate focal white matter abnormalities in the whole brain volume (e.g. Sigmundsson et al., 2001, Sowell et al., 2000, Paillère-Martinot et al., 2001). However, most VBM studies have not reported consistent white matter deficits in patients with schizophrenia (Hulshoff Pol et al., 2004). Diffusion tensor imaging (DTI) for evaluating the organization and coherence of white matte fiber tracts has also been used extensively to estimate white matter abnormalities in schizophrenia patients. However, the findings were inconclusive (Kanaan et al., 2005), until subjected to meta-analysis (Ellison-Wright and Bullmore, 2008).
VBM analysis is a statistical method extensively used to compare the structural differences of MRI images between two groups of individuals. It registers individual brain volume on a standard template and voxel-wise statistics are used to find voxels across the whole brain volume where there are significant differences between two groups. This kind of mass-univariate statistics has a problem of multiple comparisons. Although several methods for the correction of such comparisons have been used in VBM studies, clusters of false positives cannot be fully excluded, which could explain the inconsistent findings. In addition, several other limitations of the VBM approach such as poor spatial registration (Bookstein, 2001) and sample selection differences can also lead to inconsistencies. Hence, analysis across studies is needed to estimate consistent white matter abnormalities in patients with schizophrenia.
Activation likelihood estimation (ALE, Turkeltaub et al., 2002) is a relatively new method to compensate for the limitations of VBM. It treats a foci reported by a single study as an activation likelihood, and estimates consistent activation clusters among different studies. Although several ALE meta-analyses have investigated structural abnormalities in brain gray matter (Ellison-Wright et al., 2008a, Fornito et al., 2009, Glahn et al., 2008) and diffusion tensor abnormalities in white matter (Ellison-Wright and Bullmore, 2008) of patients with schizophrenia, white matter morphometry abnormalities have not been addressed.
In the present study, we systematically reviewed VBM studies of white matter change in patients with schizophrenia. Although these studies varied from patient samples and VBM processing protocols, we used a quantitative ALE meta-analysis to verify whether there is a consistent focal white matter deficit among schizophrenia patients in the published VBM studies.
Section snippets
Paper selection
We used the key words “voxel based morphometry,” “schizophrenia” and “white matter” to search for appropriate studies in the MEDLINE and PubMed databases. Studies were selected according to the following inclusion criteria: 1) they had to be research articles published in international journals; 2) they had to use VBM analysis to investigate white matter density change in the MRI dataset; 3) they had include a control group and a direct comparison of patients with schizophrenia and healthy
Results
Four clusters were identified in the ALE analysis under FDR p < 0.01 and k > 100. As illustrated in Fig. 1 and Table 2, several regions, including the frontal white matter regions and the bilateral internal capsule, show consistent white matter deficit in patients with schizophrenia compared to healthy controls.
Two clusters were activated in the frontal white matter regions (peak Talairach coordinates at 20, 46, 26 and − 8, 48, − 2). Four out of the seventeen studies reported white matter reduction
Discussion
Using the quantitative ALE method, we evaluated the consistent focal white matter deficit of patients with schizophrenia in VBM studies. Multiple white matter fasciculi reductions were found in patients with schizophrenia, including in the frontal white matter regions and the bilateral internal capsule. The current ALE results were consistent with evidence from other techniques. Frontal lobe white matter reductions in patients with schizophrenia have been widely reported in region-of-interest
Acknowledgements
This study was partially supported by the Project-Oriented Hundred Talents Programme (O7CX031003) of the Institute of Psychology, the Knowledge Innovation Project of the Chinese Academy of Sciences (KSCX2-YW-R-131), a grant from the National Natural Science Foundation of China (30770723), and two grants from the National Basic Research Programme (973 Programme No. 2007CB512302 and 2007CB512305). These funding agents had no further role in the study design, the collection, analysis and
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