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Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder
Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has b...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341112/ https://www.ncbi.nlm.nih.gov/pubmed/30664633 http://dx.doi.org/10.1038/s41398-018-0225-4 |
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author | Schwarz, Emanuel Doan, Nhat Trung Pergola, Giulio Westlye, Lars T Kaufmann, Tobias Wolfers, Thomas Brecheisen, Ralph Quarto, Tiziana Ing, Alex J Di Carlo, Pasquale Gurholt, Tiril P Harms, Robbert L Noirhomme, Quentin Moberget, Torgeir Agartz, Ingrid Andreassen, Ole A Bellani, Marcella Bertolino, Alessandro Blasi, Giuseppe Brambilla, Paolo Buitelaar, Jan K Cervenka, Simon Flyckt, Lena Frangou, Sophia Franke, Barbara Hall, Jeremy Heslenfeld, Dirk J Kirsch, Peter McIntosh, Andrew M Nöthen, Markus M Papassotiropoulos, Andreas de Quervain, Dominique J-F Rietschel, Marcella Schumann, Gunter Tost, Heike Witt, Stephanie H Zink, Mathias Meyer-Lindenberg, Andreas |
author_facet | Schwarz, Emanuel Doan, Nhat Trung Pergola, Giulio Westlye, Lars T Kaufmann, Tobias Wolfers, Thomas Brecheisen, Ralph Quarto, Tiziana Ing, Alex J Di Carlo, Pasquale Gurholt, Tiril P Harms, Robbert L Noirhomme, Quentin Moberget, Torgeir Agartz, Ingrid Andreassen, Ole A Bellani, Marcella Bertolino, Alessandro Blasi, Giuseppe Brambilla, Paolo Buitelaar, Jan K Cervenka, Simon Flyckt, Lena Frangou, Sophia Franke, Barbara Hall, Jeremy Heslenfeld, Dirk J Kirsch, Peter McIntosh, Andrew M Nöthen, Markus M Papassotiropoulos, Andreas de Quervain, Dominique J-F Rietschel, Marcella Schumann, Gunter Tost, Heike Witt, Stephanie H Zink, Mathias Meyer-Lindenberg, Andreas |
author_sort | Schwarz, Emanuel |
collection | PubMed |
description | Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients. |
format | Online Article Text |
id | pubmed-6341112 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63411122019-01-23 Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder Schwarz, Emanuel Doan, Nhat Trung Pergola, Giulio Westlye, Lars T Kaufmann, Tobias Wolfers, Thomas Brecheisen, Ralph Quarto, Tiziana Ing, Alex J Di Carlo, Pasquale Gurholt, Tiril P Harms, Robbert L Noirhomme, Quentin Moberget, Torgeir Agartz, Ingrid Andreassen, Ole A Bellani, Marcella Bertolino, Alessandro Blasi, Giuseppe Brambilla, Paolo Buitelaar, Jan K Cervenka, Simon Flyckt, Lena Frangou, Sophia Franke, Barbara Hall, Jeremy Heslenfeld, Dirk J Kirsch, Peter McIntosh, Andrew M Nöthen, Markus M Papassotiropoulos, Andreas de Quervain, Dominique J-F Rietschel, Marcella Schumann, Gunter Tost, Heike Witt, Stephanie H Zink, Mathias Meyer-Lindenberg, Andreas Transl Psychiatry Article Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients. Nature Publishing Group UK 2019-01-17 /pmc/articles/PMC6341112/ /pubmed/30664633 http://dx.doi.org/10.1038/s41398-018-0225-4 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Schwarz, Emanuel Doan, Nhat Trung Pergola, Giulio Westlye, Lars T Kaufmann, Tobias Wolfers, Thomas Brecheisen, Ralph Quarto, Tiziana Ing, Alex J Di Carlo, Pasquale Gurholt, Tiril P Harms, Robbert L Noirhomme, Quentin Moberget, Torgeir Agartz, Ingrid Andreassen, Ole A Bellani, Marcella Bertolino, Alessandro Blasi, Giuseppe Brambilla, Paolo Buitelaar, Jan K Cervenka, Simon Flyckt, Lena Frangou, Sophia Franke, Barbara Hall, Jeremy Heslenfeld, Dirk J Kirsch, Peter McIntosh, Andrew M Nöthen, Markus M Papassotiropoulos, Andreas de Quervain, Dominique J-F Rietschel, Marcella Schumann, Gunter Tost, Heike Witt, Stephanie H Zink, Mathias Meyer-Lindenberg, Andreas Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder |
title | Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder |
title_full | Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder |
title_fullStr | Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder |
title_full_unstemmed | Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder |
title_short | Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder |
title_sort | reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341112/ https://www.ncbi.nlm.nih.gov/pubmed/30664633 http://dx.doi.org/10.1038/s41398-018-0225-4 |
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