Altered dynamic functional connectivity characteristics in adolescent depression with childhood trauma: a pilot resting-state EEG study.
This exploratory small sample study aimed to investigate dynamic functional connectivity (dFC) abnormalities in adolescent depression associated with childhood trauma through resting-state electroencephalography (EEG), focusing on identifying atypical patterns in key brain networks and their correlation with clinical symptoms.
Resting-state EEG data were recorded from adolescents diagnosed with depression, encompassing two subtypes: individuals with a history of childhood trauma (CTD) and those without such a history (NCTD). Additionally, data were collected from a matched group of healthy controls (HCs). Childhood trauma was assessed using the Childhood Trauma Questionnaire-Short Form (CTQ-SF). Depression severity was evaluated using the 17-item Hamilton Depression Rating Scale (HAMD-17). dFC was analyzed using the sliding window method and weighted phase-lag index, followed by K-means clustering to identify key connectivity states across frequency bands. Spearman correlation analysis was performed to explore the relationship between dFC matrix characteristics and clinical features in the CTD group.
The final sample comprised 25 individuals in the CTD group, 27 in the NCTD group, and 32 HCs. The CTD group exhibited an earlier onset and more severe depression compared to the NCTD group, with significant differences (p < 0.001). In the CTQ-SF assessment, the CTD group scored significantly higher on emotional abuse, emotional neglect, and somatic neglect compared to both the HC and NCTD groups (p < 0.001). dFC analysis and K-means clustering revealed three distinct brain states (S1, S2, S3). These brain states correlated with CTQ-SF scores in the CTD group.
Resting EEG with dFC analysis and K-means clustering could be biomarkers for identifying adolescent depression linked to childhood trauma, aiding personalized trauma-focused interventions and monitoring treatment efficacy.
Resting-state EEG data were recorded from adolescents diagnosed with depression, encompassing two subtypes: individuals with a history of childhood trauma (CTD) and those without such a history (NCTD). Additionally, data were collected from a matched group of healthy controls (HCs). Childhood trauma was assessed using the Childhood Trauma Questionnaire-Short Form (CTQ-SF). Depression severity was evaluated using the 17-item Hamilton Depression Rating Scale (HAMD-17). dFC was analyzed using the sliding window method and weighted phase-lag index, followed by K-means clustering to identify key connectivity states across frequency bands. Spearman correlation analysis was performed to explore the relationship between dFC matrix characteristics and clinical features in the CTD group.
The final sample comprised 25 individuals in the CTD group, 27 in the NCTD group, and 32 HCs. The CTD group exhibited an earlier onset and more severe depression compared to the NCTD group, with significant differences (p < 0.001). In the CTQ-SF assessment, the CTD group scored significantly higher on emotional abuse, emotional neglect, and somatic neglect compared to both the HC and NCTD groups (p < 0.001). dFC analysis and K-means clustering revealed three distinct brain states (S1, S2, S3). These brain states correlated with CTQ-SF scores in the CTD group.
Resting EEG with dFC analysis and K-means clustering could be biomarkers for identifying adolescent depression linked to childhood trauma, aiding personalized trauma-focused interventions and monitoring treatment efficacy.
Authors
Zhang Zhang, Wang Wang, Song Song, Long Long, Li Li, Hu Hu, Zhang Zhang, Jin Jin, Li Li, Liu Liu
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