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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
A Longitudinal Study on Attenuated Structural Covariance in Patients With Somatic Symptom Disorder
Hye Youn Park1,2, Ye Eun Jang3, Leonard Sunwoo4,5
1Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea.
Objective:
This study was performed to investigate altered regional gray matter volume (rGMV) and structural covariance related to somatic symptom disorder (SSD) and longitudinal changes after treatment. Additionally, this study examined the relationships of structural alteration with its phenotypic subtypes.
Methods:
Forty-three unmedicated patients with SSD and thirty normal controls completed psychological questionnaires and neurocognitive tests, as well as brain magnetic resonance imaging. Voxel-based morphometry and structural covariances were compared between groups and between subgroups within the SSD group. After 6 months of treatment, SSD patients were followed up for assessments.
Results:
Patients with SSD exhibited attenuated structural covariances in the pallidal-cerebellar circuit (FDR < 0.05-0.1), as well as regions in the default mode and sensorimotor network (FDR < 0.2), compared to normal controls. The cerebellar rGMVs were negatively correlated with the severity of somatic symptoms. In subgroup analyses, patients with somatic pain showed denser structural covariances between the bilateral superior temporal pole and left angular gyrus, the left middle temporal pole and left angular gyrus, and the left amygdala and right inferior orbitofrontal gyrus, while patients with headache and dizziness had greater structural covariance between the right inferior temporal gyrus and right cerebellum (FDR < 0.1-0.2). After 6 months of treatment, patients showed improved symptoms, however there was no significant structural alteration.
Conclusion:
The findings suggest that attenuated structural covariance may link to dysfunctional brain network and vulnerability to SSD; they also suggested that specific brain regions and networks may contribute to different subtypes of SSD.
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