TY - JOUR
T1 - Brain structural covariance networks in obsessive-compulsive disorder
T2 - A graph analysis from the ENIGMA consortium
AU - ENIGMA OCD Working Group
AU - Yun, Je Yeon
AU - Boedhoe, Premika S.W.
AU - Vriend, Chris
AU - Jahanshad, Neda
AU - Abe, Yoshinari
AU - Ameis, Stephanie H.
AU - Anticevic, Alan
AU - Arnold, Paul D.
AU - Batistuzzo, Marcelo C.
AU - Benedetti, Francesco
AU - Beucke, Jan C.
AU - Bollettini, Irene
AU - Bose, Anushree
AU - Brem, Silvia
AU - Calvo, Anna
AU - Cheng, Yuqi
AU - Cho, Kang Ik K.
AU - Ciullo, Valentina
AU - Dallaspezia, Sara
AU - Denys, Damiaan
AU - Feusner, Jamie D.
AU - Fouche, Jean Paul
AU - Giménez, Mònica
AU - Gruner, Patricia
AU - Hibar, Derrek P.
AU - Hoexter, Marcelo Q.
AU - Hu, Hao
AU - Huyser, Chaim
AU - Ikari, Keisuke
AU - Kathmann, Norbert
AU - Kaufmann, Christian
AU - Koch, Kathrin
AU - Lazaro, Luisa
AU - Lochner, Christine
AU - Marques, Paulo
AU - Marsh, Rachel
AU - Martínez-Zalacaín, Ignacio
AU - Mataix-Cols, David
AU - Menchón, José M.
AU - Minuzzi, Luciano
AU - Morgado, Pedro
AU - Moreira, Pedro
AU - Nakamae, Takashi
AU - Nakao, Tomohiro
AU - Narayanaswamy, Janardhanan C.
AU - Nurmi, Erika L.
AU - O’Neill, Joseph
AU - Piacentini, John
AU - Piras, Fabrizio
AU - Piras, Federica
N1 - Funding Information:
P.D.A (Alberta Innovates Translational Health Chair in Child and Youth Mental Health). D.P.H. is now an employee of Genentech, Inc. working on projects unrelated to this publication. D.M-C. receives royalties for contributing articles to UpToDate, Wolters Kluwer Health and fees from Elsevier for editorial tasks (all unrelated to the submitted work). H.B.S. (Biohaven research support for clinical trial; Royalties from UpToDate, Inc and Cambridge University Press). N.S. (Lundbeck-IIT). P.M.T. has received a research grant from Biogen, Inc. unrelated to the topic of this paper. No further conflict of interest is reported.
Funding Information:
ENIGMA is supported, in part, by an NIH grant (U54 EB020403) for big data analytics.
Funding Information:
This research was funded by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03028464) and the Basic Research Laboratory Program through the National Research Foundation of Korea (NRF) (Grant no. 2018R1A4A1025891).
Publisher Copyright:
© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
PY - 2020
Y1 - 2020
N2 - Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10–0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P 5 0.0001), lower modularity (P 5 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.
AB - Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10–0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P 5 0.0001), lower modularity (P 5 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.
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U2 - 10.1093/brain/awaa001
DO - 10.1093/brain/awaa001
M3 - Article
C2 - 32040561
AN - SCOPUS:85079234329
VL - 143
SP - 684
EP - 700
JO - Brain
JF - Brain
SN - 0006-8950
IS - 2
ER -