Citation

Li L, Liang Z, Li G, Xu H, Yang X, Liu X, Zhang X, Wang J, Zhang Z, Zhou Y. CNS Neurosci. Ther. 2024; 30(5): e14684.

Copyright

(Copyright © 2024, John Wiley and Sons)

DOI

10.1111/cns.14684

PMID

38739217

PMCID

PMC11090151

Abstract

AIMS: Limited understanding exists regarding the neurobiological mechanisms underlying non-suicidal self-injury (NSSI) and suicide attempts (SA) in depressed adolescents. The maturation of brain network is crucial during adolescence, yet the abnormal alternations in depressed adolescents with NSSI or NSSI+SA remain poorly understood.

METHODS: Resting-state functional magnetic resonance imaging data were collected from 114 depressed adolescents, classified into three groups: clinical control (non-self-harm), NSSI only, and NSSI+SA based on self-harm history. The alternations of resting-state functional connectivity (RSFC) were identified through support vector machine-based classification.

RESULTS: Convergent alterations in NSSI and NSSI+SA predominantly centered on the inter-network RSFC between the Limbic network and the three core neurocognitive networks (SalVAttn, Control, and Default networks). Divergent alterations in the NSSI+SA group primarily focused on the Visual, Limbic, and Subcortical networks. Additionally, the severity of depressive symptoms only showed a significant correlation with altered RSFCs between Limbic and DorsAttn or Visual networks, strengthening the fact that increased depression severity alone does not fully explain observed FC alternations in the NSSI+SA group.

CONCLUSION: Convergent alterations suggest a shared neurobiological mechanism along the self-destructiveness continuum. Divergent alterations may indicate biomarkers differentiating risk for SA, informing neurobiologically guided interventions.

Language: en

Keywords

*Brain/diagnostic imaging/physiopathology; *Magnetic Resonance Imaging; *Self-Injurious Behavior/psychology; *Suicide, Attempted/psychology; adolescence; Adolescent; Child; depression; Depression/psychology/physiopathology/diagnostic imaging; Female; Humans; machine learning; Male; Nerve Net/diagnostic imaging/physiopathology; Neural Pathways/physiopathology/diagnostic imaging; non‐suicidal self‐injury; resting‐state functional connectivity; suicidal attempt