White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies
Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia a...
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| Published in | Psychiatry research. Neuroimaging Vol. 270; pp. 8 - 21 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier B.V
30.12.2017
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| Abstract | Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions.
•White matter reductions in schizophrenia involve specific cerebral circuits.•Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) detect some shared WM bundles.•Meta-regression analyses found significant effects of age, duration of illness, and gender on several WM bundles.•The bundles detected by both methodologies may be the “core tracts” of the WM impairments in schizophrenia.•Schizophrenia seems to be characterized by several dysfunctionalities and disconnections of a widespread cerebral network. |
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| AbstractList | Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions. Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions.Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions. Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions. •White matter reductions in schizophrenia involve specific cerebral circuits.•Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) detect some shared WM bundles.•Meta-regression analyses found significant effects of age, duration of illness, and gender on several WM bundles.•The bundles detected by both methodologies may be the “core tracts” of the WM impairments in schizophrenia.•Schizophrenia seems to be characterized by several dysfunctionalities and disconnections of a widespread cerebral network. |
| Author | Pignolo, Claudia Costa, Tommaso Ando’, Agata Zennaro, Alessandro Tatu, Mona Karina Vitolo, Enrico Cauda, Franco |
| Author_xml | – sequence: 1 givenname: Enrico surname: Vitolo fullname: Vitolo, Enrico email: enrico.vitolo88@gmail.com organization: Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy – sequence: 2 givenname: Mona Karina surname: Tatu fullname: Tatu, Mona Karina email: monakarina.tatu@unito.it organization: Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy – sequence: 3 givenname: Claudia surname: Pignolo fullname: Pignolo, Claudia email: claudia.pignolo@unito.it organization: Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy – sequence: 4 givenname: Franco surname: Cauda fullname: Cauda, Franco email: franco.cauda@unito.it organization: Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy – sequence: 5 givenname: Tommaso surname: Costa fullname: Costa, Tommaso email: tommaso.costa@unito.it organization: Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy – sequence: 6 givenname: Agata surname: Ando’ fullname: Ando’, Agata email: agatamariaclaudia.ando@unito.it organization: Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy – sequence: 7 givenname: Alessandro surname: Zennaro fullname: Zennaro, Alessandro email: alessandro.zennaro@unito.it organization: Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28988022$$D View this record in MEDLINE/PubMed |
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| Title | White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies |
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