Altered cortical functional networks in Wilson's Disease: A resting-state electroencephalogram study

The neuropsychiatric symptoms are common in Wilson's disease (WD) patients. However, it remains unclear about the associated functional brain networks. In this study, source localization-based functional connectivity analysis of close-eye resting-state electroencephalography (EEG) were implemented to assess the characteristics of functional networks in 17 WD patients with neurological involvements and 17 healthy controls (HCs). The weighted phase-lag index (wPLI) was subsequently calculated in source space across five different frequency bands and the resulting connectivity matrix was transformed into a weighted graph whose structure was measured by five graphical analysis indicators, which were finally correlated with clinical scores. Compared to HCs, WD patients revealed disconnected sub-networks in delta, theta and alpha bands. Moreover, WD patients exhibited significantly reduced global clustering coefficients and small-worldness in all five frequency bands. In WD group, the severity of neurological symptoms and structural brain abnormalities were significantly correlated with disrupted functional networks. In conclusion, our study demonstrated that functional network deficits in WD can reflect the severity of their neurological symptoms and structural brain abnormalities. Resting-state EEG may be used as a marker of brain injury in WD.

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Publication Details

Journal
Neurobiology of Disease
Published
2024-10-05
DOI
https://doi.org/10.1016/j.nbd.2024.106692
Citations
3
Primary Topic
Electrochemical Analysis and Applications
Type
article
Field-Weighted Citation Impact
0.52
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article

Altered cortical functional networks in Wilson's Disease: A resting-state electroencephalogram study

Chen Ru-kai, Wuxiang Shi, Wan‐Jin Chen, Naiqing Cai et al.
3 citations
Neurobiology of Disease
Electrochemical Analysis and Applications
0.52
article

Altered cortical functional networks in Wilson's Disease: A resting-state electroencephalogram study

Chen Ru-kai, Wuxiang Shi, Wan‐Jin Chen, Naiqing Cai, Chan Zhang, Jianwei Lin, Yurong Li
article en
3 citations

Abstract

The neuropsychiatric symptoms are common in Wilson's disease (WD) patients. However, it remains unclear about the associated functional brain networks. In this study, source localization-based functional connectivity analysis of close-eye resting-state electroencephalography (EEG) were implemented to assess the characteristics of functional networks in 17 WD patients with neurological involvements and 17 healthy controls (HCs). The weighted phase-lag index (wPLI) was subsequently calculated in source space across five different frequency bands and the resulting connectivity matrix was transformed into a weighted graph whose structure was measured by five graphical analysis indicators, which were finally correlated with clinical scores. Compared to HCs, WD patients revealed disconnected sub-networks in delta, theta and alpha bands. Moreover, WD patients exhibited significantly reduced global clustering coefficients and small-worldness in all five frequency bands. In WD group, the severity of neurological symptoms and structural brain abnormalities were significantly correlated with disrupted functional networks. In conclusion, our study demonstrated that functional network deficits in WD can reflect the severity of their neurological symptoms and structural brain abnormalities. Resting-state EEG may be used as a marker of brain injury in WD.

Neurobiology of DiseaseVol. 202
Fujian Medical University (CN), First Affiliated Hospital of Fujian Medical University (CN), First Affiliated Hospital of Zhengzhou University (CN), Putian University (CN), Fuzhou University (CN), Fujian University of Technology (CN)
Openalex Percentile: Top 43%
Electrochemical Analysis and Applications
0.52
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