Abstract
BackgroundDisturbance of networks was recently proposed to be associated with the occurrence of depression in Parkinson’s disease (PD). However, the neurobiological mechanism of depression underlying PD remains unclear.ObjectiveThis study was conducted to investigate whether intra-network and inter-network brain connectivity is differently changed in PD patients with and without depression (PDD and PDND patients, respectively).MethodsForty-one PDD patients, 64 PDND patients, and 55 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI). The default mode network (DMN), executive control network (ECN), salience network (SN), precuneus network (PCUN), and sensorimotor network (SMN) were extracted using independent component analysis (ICA), and then the functional connectivity (FC) values within and between these networks were measured.ResultsPDD patients exhibited abnormal FC values within the DMN, ECN, SN, PCUN, and SMN. In addition, PDD patients demonstrated decreased connectivity between anterior SN (aSN) and bilateral ECN, between posterior SN (pSN) and dorsal DMN (dDMN), and between PCUN and dDMN/SMN/bilateral ECN. Connectivity within the left hippocampus of dDMN and the right medial superior frontal gyrus of aSN was a significant predictor of depression level in PD patients.ConclusionsAberrant intra- and inter-network FC is involved in several important hubs in the large-scale networks, which can be a biomarker for distinguishing PDD from PDND.
Highlights
Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease (Mason et al, 2014); it is characterized by a combination of cardinal motor features and nonmotor symptoms (NMS), including different prominent psychiatric disturbances (McLaughlin et al, 2014)
Connectivity within the left hippocampus of dorsal DMN (dDMN) and the right medial superior frontal gyrus of anterior SN (aSN) was a significant predictor of depression level in PD patients
Aberrant intra- and inter-network functional connectivity (FC) is involved in several important hubs in the large-scale networks, which can be a biomarker for distinguishing PD with depression (PDD) from PDND
Summary
Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease (Mason et al, 2014); it is characterized by a combination of cardinal motor features and nonmotor symptoms (NMS), including different prominent psychiatric disturbances (McLaughlin et al, 2014). The triple-network model includes the default mode network (DMN), executive control network (ECN), and salience network (SN) (Menon, 2011). They are the three most important intrinsic networks of the human brain activation. Abnormalities in the triple-network model have been observed across several psychiatric disorders including PDD (Manoliu et al, 2014; Wang et al, 2014; Fan et al, 2017; Weng et al, 2019). These network abnormalities were found in PD patients from a small cohort. The neurobiological mechanism of depression underlying PD remains unclear
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