Structural covariance of neostriatal and limbic regions in patients with obsessive–compulsive disorder

Subirà, Marta; Cano, Marta; Wit, Stella J. de; Alonso, Pino; Cardoner, Narcı́s; Hoexter, Marcelo Q.; Kwon, Jun Soo; Nakamae, Takashi; Löchner, Christine; Sato, João Ricardo; Jung, Wi Hoon; Narumoto, Jin; Stein, Dan J.; Pujol, Jesús; Mataix‐Cols, David; Veltman, Dick J.; Busatto, Geraldo F.; Cath, Daniëlle C.; Denys, Damiaan; Fukui, Kenji; Fouche, Jean Paul; Jang, Joon Hwan; Kim, Sung Nyun; Miguel, Euripides C.; Nishida, Seiji; Phillips, Mary L.; Remijnse, Peter L.; Sakai, Yuki; Schweren, Lizanne; Shin, Na Young; Yamada, Kazuo; Menchón, José M.; Heuvel, Odile A. van den; Soriano‐Mas, Carles

doi:10.1503/jpn.150012

Cited by 30 publications

(14 citation statements)

References 61 publications

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“…For example, Pujol et al (2004) found a negative association between relative volume reduction for OCD (compared to healthy controls) in the medial prefrontalinsulo-opercular cortical regions and relative volume enlargement of ventral striatum, suggesting that abnormal brain morphology in OCD might be distributed in coordinated fashion across diverse brain regions. In addition, a recent mega-analysis found higher covariance between volumes of left putamen and left frontal operculum, and higher covariance between volumes of right amygdala and ventromedial prefrontal cortex in OCD compared to healthy controls (Subira et al, 2016). Further, local cortical gyrification (associated with cortical maturation)based structural covariance network demonstrated lower covariance among mainly ventral brain regions in OCD compared to healthy controls (Reess et al, 2018b).…”

Section: Introductionmentioning

confidence: 92%

OUP accepted manuscript

Yun¹,

Boedhoe²,

Vriend³

et al. 2020

Brain

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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 T 1-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.

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Section: Introductionmentioning

confidence: 92%

OUP accepted manuscript

Yun¹,

Boedhoe²,

Vriend³

et al. 2020

Brain

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“…After either procedure, the severity of OCD and depressive symptoms decreased as well as the metabolism in the sgACC, the striatum and the CON (Suetens et al 2014). Finally, a recent voxel-based morphometry study showed a relationship between grey matter density in the vmPFC and amygdala in over 300 OCD patients (Subira et al 2015).…”

Section: Fronto-limbic Networkmentioning

confidence: 95%

Cognitive control networks in OCD: A resting-state connectivity study in unmedicated patients with obsessive-compulsive disorder and their unaffected relatives

Vries

Wit

Heuvel

et al. 2017

The World Journal of Biological Psychiatry

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“…This is based on the theory that interconnected brain regions within a network not only show simultaneous brain activity, but also show correlations in gray-matter volume, perhaps due to joint neuroplastic or neurodegenerative processes (Mechelli et al 2005). In line with this theory, structural covariance networks partially overlap with functional brain networks (He et al 2007), and seed-based SC analyses of striatal and amygdalar sub-regions yield networks that are similar to functional networks (Montembeault et al 2016; Soriano-Mas et al 2013; Subira et al 2016). Our aim was to determine whether there is a difference in SC between PD RBD+ and PD RBD-.…”

Section: Introductionmentioning

confidence: 93%

Smaller subcortical volume in Parkinson patients with rapid eye movement sleep behavior disorder

Kamps

Heuvel

Werf

et al. 2018

Brain Imaging and Behavior

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Parkinson disease (PD) patients with rapid eye movement (REM) sleep behavior disorder (RBD) have worse motor symptoms and non-motor symptoms than patients without RBD. The aim of this study was to examine underlying differences in brain structure from a network perspective. Baseline data were obtained from Parkinson's Progression Markers Initiative (PPMI) participants. We divided PD patients and healthy controls (HC) into RBD positive and RBD negative using a cutoff score of ≥5 on the RBD screening questionnaire. HC with probable RBD were excluded. We first carried out a region-of-interest analysis of structural MRIs using voxel-based morphometry to study volumetric differences for the putamen, thalamus and hippocampus in a cross-sectional design. Additionally, an exploratory whole-brain analysis was performed. To study group differences from a network perspective, we then performed a 'seed-based' analysis of structural covariance, using the bilateral dorsal-caudal putamen, mediodorsal thalamus and anterior hippocampus as seed regions. The volume of the right putamen was smaller in PD patients with RBD. RBD symptom severity correlated negatively with volume of the right putamen, left hippocampus and left thalamus. We did not find any differences in structural covariance between PD patients with and without RBD. Presence of RBD and severity of RBD symptoms in PD are associated with smaller volumes of the putamen, thalamus and hippocampus.

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Structural covariance of neostriatal and limbic regions in patients with obsessive–compulsive disorder

Cited by 30 publications

References 61 publications

OUP accepted manuscript

OUP accepted manuscript

Cognitive control networks in OCD: A resting-state connectivity study in unmedicated patients with obsessive-compulsive disorder and their unaffected relatives

Smaller subcortical volume in Parkinson patients with rapid eye movement sleep behavior disorder

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