Cargando…

Homogeneous grey matter patterns in patients with obsessive-compulsive disorder

BACKGROUND: Changes in grey matter volume have frequently been reported in patients with obsessive-compulsive disorder (OCD). Most studies performed whole brain or region-of-interest based analyses whereas grey matter volume based on structural covariance networks has barely been investigated up to...

Descripción completa

Detalles Bibliográficos
Autores principales: Koch, Kathrin, Manrique, Daniela Rodriguez, Rus-Oswald, Oana Georgiana, Gürsel, Deniz A., Berberich, Götz, Kunz, Miriam, Zimmer, Claus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8220095/
https://www.ncbi.nlm.nih.gov/pubmed/34146774
http://dx.doi.org/10.1016/j.nicl.2021.102727
_version_ 1783711073327644672
author Koch, Kathrin
Manrique, Daniela Rodriguez
Rus-Oswald, Oana Georgiana
Gürsel, Deniz A.
Berberich, Götz
Kunz, Miriam
Zimmer, Claus
author_facet Koch, Kathrin
Manrique, Daniela Rodriguez
Rus-Oswald, Oana Georgiana
Gürsel, Deniz A.
Berberich, Götz
Kunz, Miriam
Zimmer, Claus
author_sort Koch, Kathrin
collection PubMed
description BACKGROUND: Changes in grey matter volume have frequently been reported in patients with obsessive-compulsive disorder (OCD). Most studies performed whole brain or region-of-interest based analyses whereas grey matter volume based on structural covariance networks has barely been investigated up to now. Therefore, the present study investigated grey matter volume within structural covariance networks in a sample of 228 participants (n = 117 OCD patients, n = 111 healthy controls). METHODS: First, an independent component analysis (ICA) was performed on all subjects’ preprocessed T1 images to derive covariance-dependent morphometric networks. Then, grey matter volume from each of the ICA-derived morphometric networks was extracted and compared between the groups. In addition, we performed logistic regressions and receiver operating characteristic (ROC) analyses to investigate whether network-related grey matter volume could serve as a characteristic that allows to differentiate patients from healthy volunteers. Moreover, we assessed grey matter pattern organization by correlating grey matter volume in all networks across all participants. Finally, we explored a potential association between grey matter volume or whole-brain grey matter pattern organization and clinical characteristics in terms of symptom severity and duration of illness. RESULTS: There were only subtle group differences in network-related grey matter volume. Network-related grey matter volume had moreover a very poor discrimination performance. We found, however, significant group differences with regard to grey matter pattern organization. When correlating grey matter volume in all networks across all participants, patients showed a significantly higher homogeneity across all networks and a significantly lower heterogeneity, as assessed by the coefficient of variation across all networks as well as in several single networks. There was no association with clinical characteristics. CONCLUSION: The findings of the present study suggest that the pathological mechanisms of OCD reduce interindividual grey matter variability. We assume that common characteristics associated with the disorder may lead to a more uniform, disorder-specific morphometry.
format Online
Article
Text
id pubmed-8220095
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-82200952021-06-28 Homogeneous grey matter patterns in patients with obsessive-compulsive disorder Koch, Kathrin Manrique, Daniela Rodriguez Rus-Oswald, Oana Georgiana Gürsel, Deniz A. Berberich, Götz Kunz, Miriam Zimmer, Claus Neuroimage Clin Regular Article BACKGROUND: Changes in grey matter volume have frequently been reported in patients with obsessive-compulsive disorder (OCD). Most studies performed whole brain or region-of-interest based analyses whereas grey matter volume based on structural covariance networks has barely been investigated up to now. Therefore, the present study investigated grey matter volume within structural covariance networks in a sample of 228 participants (n = 117 OCD patients, n = 111 healthy controls). METHODS: First, an independent component analysis (ICA) was performed on all subjects’ preprocessed T1 images to derive covariance-dependent morphometric networks. Then, grey matter volume from each of the ICA-derived morphometric networks was extracted and compared between the groups. In addition, we performed logistic regressions and receiver operating characteristic (ROC) analyses to investigate whether network-related grey matter volume could serve as a characteristic that allows to differentiate patients from healthy volunteers. Moreover, we assessed grey matter pattern organization by correlating grey matter volume in all networks across all participants. Finally, we explored a potential association between grey matter volume or whole-brain grey matter pattern organization and clinical characteristics in terms of symptom severity and duration of illness. RESULTS: There were only subtle group differences in network-related grey matter volume. Network-related grey matter volume had moreover a very poor discrimination performance. We found, however, significant group differences with regard to grey matter pattern organization. When correlating grey matter volume in all networks across all participants, patients showed a significantly higher homogeneity across all networks and a significantly lower heterogeneity, as assessed by the coefficient of variation across all networks as well as in several single networks. There was no association with clinical characteristics. CONCLUSION: The findings of the present study suggest that the pathological mechanisms of OCD reduce interindividual grey matter variability. We assume that common characteristics associated with the disorder may lead to a more uniform, disorder-specific morphometry. Elsevier 2021-06-13 /pmc/articles/PMC8220095/ /pubmed/34146774 http://dx.doi.org/10.1016/j.nicl.2021.102727 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Koch, Kathrin
Manrique, Daniela Rodriguez
Rus-Oswald, Oana Georgiana
Gürsel, Deniz A.
Berberich, Götz
Kunz, Miriam
Zimmer, Claus
Homogeneous grey matter patterns in patients with obsessive-compulsive disorder
title Homogeneous grey matter patterns in patients with obsessive-compulsive disorder
title_full Homogeneous grey matter patterns in patients with obsessive-compulsive disorder
title_fullStr Homogeneous grey matter patterns in patients with obsessive-compulsive disorder
title_full_unstemmed Homogeneous grey matter patterns in patients with obsessive-compulsive disorder
title_short Homogeneous grey matter patterns in patients with obsessive-compulsive disorder
title_sort homogeneous grey matter patterns in patients with obsessive-compulsive disorder
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8220095/
https://www.ncbi.nlm.nih.gov/pubmed/34146774
http://dx.doi.org/10.1016/j.nicl.2021.102727
work_keys_str_mv AT kochkathrin homogeneousgreymatterpatternsinpatientswithobsessivecompulsivedisorder
AT manriquedanielarodriguez homogeneousgreymatterpatternsinpatientswithobsessivecompulsivedisorder
AT rusoswaldoanageorgiana homogeneousgreymatterpatternsinpatientswithobsessivecompulsivedisorder
AT gurseldeniza homogeneousgreymatterpatternsinpatientswithobsessivecompulsivedisorder
AT berberichgotz homogeneousgreymatterpatternsinpatientswithobsessivecompulsivedisorder
AT kunzmiriam homogeneousgreymatterpatternsinpatientswithobsessivecompulsivedisorder
AT zimmerclaus homogeneousgreymatterpatternsinpatientswithobsessivecompulsivedisorder