Brain dynamics as outcome predictors of non-suicidal self-injury during SSRI treatment in adolescent depression: a 14-month longitudinal study

Non-suicidal self-injury (NSSI) represents a major health concern among adolescents with depression, yet no pharmacotherapies are specifically approved for NSSI. Selective serotonin reuptake inhibitors (SSRIs), commonly prescribed for adolescent depression, show inconsistent efficacy for NSSI, highlighting the need for neural signatures to predict NSSI outcomes. This study conducted a large-scale analysis of dynamic functional connectivity in 452 adolescents (332 drug-naïve patients with first-episode depression, including 178 with and 154 without NSSI, and 120 healthy controls) from an open-label SSRI trial (ChiCTR2000039503), examining how brain dynamics relate to the frequency and treatment outcomes of NSSI.

Clinical and neuroimaging data were collected at baseline, with follow-up clinical assessments at 8 weeks and 14 months during SSRI treatment. Dynamic brain states and variability in graph-theoretical metrics were derived from imaging data, and the reproducibility of temporal dynamic patterns was validated in an independent dataset (N = 112). Adolescents with depression and NSSI exhibited prolonged engagement in a biologically reproducible, relatively low-modularized, and moderately connected brain state, as well as elevated variability in small-world network metrics.

This state was characterized by altered connectivity in the default mode and frontoparietal networks. Notably, baseline fractional windows of this state predicted both short-term reduction in NSSI frequency at 8 weeks and NSSI cessation at 14 months following SSRI treatment. These findings were consistently replicated across multiple validation analyses.

Our results identify dynamic brain network patterns linked to NSSI outcomes during SSRI treatment, suggesting that characterizing such dynamic properties may help identify individuals at risk of poor NSSI outcomes and inform early intervention in adolescent depression. The authors thank all participants and their families for their participation in this study. This research was supported by the National Natural Science Foundation of China (82171534, 82471557), the National Major Science and Technology Project of China (2021ZD0200600, 2021ZD0200701), the Shanxi Provincial Clinical Medical Research Center for Mental and Psychological Disorders (Depression) (20240410501002), and the Postgraduate Education Innovation Program of Shanxi Province (2023SJ132).

Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China Dan Qiao, Yujiao Wen, Wentao Zhao, Hong Li, Qianru Guo, Peiyun Zhai, Ting Zhao, Gaizhi Li, Penghong Liu & Zhifen Liu Shanxi Provincial Clinical Medical Research Center for Mental and Psychological Disorders (Depression), Taiyuan, China Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology and Emory University, Georgia State University, Atlanta, GA, USA School of Systems Biology, George Mason University, Manassas, VA, USA The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

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