Salience network and depressive severities in Parkinson's disease with mild cognitive impairment: A structural covariance network analysis

Y.-T. Chang, C.-H. Lu, M.-K. Wu, S.-W. Hsu, C.-W. Huang, W.-N. Chang, C.-Y. Lien, J.-J. Lee, Chia-Chen Chang

Research output: Contribution to journalJournal Article peer-review

21 Scopus citations

Abstract

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.
Original languageAmerican English
JournalFrontiers in Aging Neuroscience
Volume9
Issue numberJAN
DOIs
StatePublished - 2018

Keywords

  • Brain imaging
  • Brain imaging
  • Cognition
  • Cognition
  • Depression
  • Depression
  • Mood disorders
  • Mood disorders
  • Neuroimaging
  • Neuroimaging

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