Salience Network and Depressive Severities in Parkinson’s Disease with Mild Cognitive Impairment: A Structural Covariance Network Analysis

• Main Authors: Ya-Ting Chang, Cheng-Hsien Lu, Ming-Kung Wu, Shih-Wei Hsu, Chi-Wei Huang, Wen-Neng Chang, Chia-Yi Lien, Jun-Jun Lee, Chiung-Chih Chang
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2018-01-01
• Series: Frontiers in Aging Neuroscience
• Subjects: brain imaging; cognition; depression; mood disorders; neuroimaging
• Online Access: http://journal.frontiersin.org/article/10.3389/fnagi.2017.00417/full

Purpose: In Parkinson’s disease with mild cognitive impairment (PD-MCI), we investigated the clinical significance of salience network (SN) in depression and cognitive performance.Methods: Seventy seven PD-MCI patients that fulfilled multi-domain and non-amnestic subtype were included. Gray matter structural covariance networks were constructed by 3D T1-magnetic resonance imaging and seed based analysis. The patients were divided into two groups by psychiatric interviews and screening of Geriatric Depression Scale (GDS): PD-MCI with depression (PD-MCI-D) or without depression (PD-MCI-ND). The seed or peak cluster volume, or the significant differences in the regression slopes in each seed-peak cluster correlation, were used to evaluate the significance with the neurobehavioral scores.Results: This study is the first to demonstrate that the PD-MCI-ND group presented a larger number of voxels of structural covariance in SN than the PD-MCI-D group. The right fronto-insular seed volumes and the peak cluster of left lingual gyrus showed significant inverse correlation with the Geriatric Depression Scale (GDS; r = -0.231, P = 0.046).Conclusions: This study is the first to validate the clinical significance of the SN in PD-MCI-D. The right insular seed value and the SN correlated with the severity of depression in PD-MCI.