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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 2017-12, Vol.270, p.8-21 |
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| container_title | Psychiatry research. Neuroimaging |
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| creator | Vitolo, Enrico Tatu, Mona Karina Pignolo, Claudia Cauda, Franco Costa, Tommaso Ando’, Agata Zennaro, Alessandro |
| description | 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. |
| doi_str_mv | 10.1016/j.pscychresns.2017.09.014 |
| format | article |
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•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.</description><identifier>ISSN: 0925-4927</identifier><identifier>EISSN: 1872-7506</identifier><identifier>DOI: 10.1016/j.pscychresns.2017.09.014</identifier><identifier>PMID: 28988022</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Adult ; Diffusion Tensor Imaging ; Female ; Humans ; Likelihood Functions ; Male ; Meta-analysis ; Middle Aged ; Schizophrenia ; Schizophrenia - diagnostic imaging ; Schizophrenia - pathology ; Schizophrenia - physiopathology ; Voxel-based morphometry ; White matter ; White Matter - diagnostic imaging ; White Matter - pathology ; Young Adult</subject><ispartof>Psychiatry research. Neuroimaging, 2017-12, Vol.270, p.8-21</ispartof><rights>2017 Elsevier B.V.</rights><rights>Copyright © 2017 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c494t-9ac5888d915699d10d87cab3a97c94141080db99580da8e59c998a066b3a6de33</citedby><cites>FETCH-LOGICAL-c494t-9ac5888d915699d10d87cab3a97c94141080db99580da8e59c998a066b3a6de33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,786,790,27957,27958</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28988022$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Vitolo, Enrico</creatorcontrib><creatorcontrib>Tatu, Mona Karina</creatorcontrib><creatorcontrib>Pignolo, Claudia</creatorcontrib><creatorcontrib>Cauda, Franco</creatorcontrib><creatorcontrib>Costa, Tommaso</creatorcontrib><creatorcontrib>Ando’, Agata</creatorcontrib><creatorcontrib>Zennaro, Alessandro</creatorcontrib><title>White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies</title><title>Psychiatry research. Neuroimaging</title><addtitle>Psychiatry Res Neuroimaging</addtitle><description>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.</description><subject>Adult</subject><subject>Diffusion Tensor Imaging</subject><subject>Female</subject><subject>Humans</subject><subject>Likelihood Functions</subject><subject>Male</subject><subject>Meta-analysis</subject><subject>Middle Aged</subject><subject>Schizophrenia</subject><subject>Schizophrenia - diagnostic imaging</subject><subject>Schizophrenia - pathology</subject><subject>Schizophrenia - physiopathology</subject><subject>Voxel-based morphometry</subject><subject>White matter</subject><subject>White Matter - diagnostic imaging</subject><subject>White Matter - pathology</subject><subject>Young Adult</subject><issn>0925-4927</issn><issn>1872-7506</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqNkE1v1DAQhi0EotvCX0DmxiXBzqeHW7UCilSpF6oeLa896XqV2MGTVCy_HpctiGNPc3ned2Yext5LUUohu4-HciZ7tPuEFKishOxLAaWQzQu2kaqvir4V3Uu2EVC1RQNVf8bOiQ5CVLXq6tfsrFKglKiqDYt3e78gn8yyYOImOE5273_FOZcHbz7xSz7hYgoTzHgkTzwO_CH-xLHYGULHp5jmfcxIOv5JOz8MK_kY-IKBYuJ-Mvc-3HNaVueR3rBXgxkJ3z7NC3b75fP37VVxffP12_byurANNEsBxrZKKQey7QCcFE711uxqA72FRjZSKOF2AG0eRmELFkAZ0XUZ6RzW9QX7cOqdU_yxIi168mRxHE3AuJKW0IBQtRRdRuGE2hSJEg56TvnqdNRS6Eff-qD_860ffWsBOvvO2XdPa9bdhO5f8q_gDGxPAOZnHzwmTdZjsOh8QrtoF_0z1vwGAGaZuw</recordid><startdate>20171230</startdate><enddate>20171230</enddate><creator>Vitolo, Enrico</creator><creator>Tatu, Mona Karina</creator><creator>Pignolo, Claudia</creator><creator>Cauda, Franco</creator><creator>Costa, Tommaso</creator><creator>Ando’, Agata</creator><creator>Zennaro, Alessandro</creator><general>Elsevier B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20171230</creationdate><title>White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies</title><author>Vitolo, Enrico ; Tatu, Mona Karina ; Pignolo, Claudia ; Cauda, Franco ; Costa, Tommaso ; Ando’, Agata ; Zennaro, Alessandro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c494t-9ac5888d915699d10d87cab3a97c94141080db99580da8e59c998a066b3a6de33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adult</topic><topic>Diffusion Tensor Imaging</topic><topic>Female</topic><topic>Humans</topic><topic>Likelihood Functions</topic><topic>Male</topic><topic>Meta-analysis</topic><topic>Middle Aged</topic><topic>Schizophrenia</topic><topic>Schizophrenia - diagnostic imaging</topic><topic>Schizophrenia - pathology</topic><topic>Schizophrenia - physiopathology</topic><topic>Voxel-based morphometry</topic><topic>White matter</topic><topic>White Matter - diagnostic imaging</topic><topic>White Matter - pathology</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vitolo, Enrico</creatorcontrib><creatorcontrib>Tatu, Mona Karina</creatorcontrib><creatorcontrib>Pignolo, Claudia</creatorcontrib><creatorcontrib>Cauda, Franco</creatorcontrib><creatorcontrib>Costa, Tommaso</creatorcontrib><creatorcontrib>Ando’, Agata</creatorcontrib><creatorcontrib>Zennaro, Alessandro</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Psychiatry research. Neuroimaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vitolo, Enrico</au><au>Tatu, Mona Karina</au><au>Pignolo, Claudia</au><au>Cauda, Franco</au><au>Costa, Tommaso</au><au>Ando’, Agata</au><au>Zennaro, Alessandro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies</atitle><jtitle>Psychiatry research. Neuroimaging</jtitle><addtitle>Psychiatry Res Neuroimaging</addtitle><date>2017-12-30</date><risdate>2017</risdate><volume>270</volume><spage>8</spage><epage>21</epage><pages>8-21</pages><issn>0925-4927</issn><eissn>1872-7506</eissn><notes>ObjectType-Article-2</notes><notes>SourceType-Scholarly Journals-1</notes><notes>ObjectType-Feature-1</notes><notes>content type line 23</notes><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.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>28988022</pmid><doi>10.1016/j.pscychresns.2017.09.014</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Adult Diffusion Tensor Imaging Female Humans Likelihood Functions Male Meta-analysis Middle Aged Schizophrenia Schizophrenia - diagnostic imaging Schizophrenia - pathology Schizophrenia - physiopathology Voxel-based morphometry White matter White Matter - diagnostic imaging White Matter - pathology Young Adult |
| title | White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies |
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