Resting-state functional connectivity predicting clinical improvement following treatment in female adolescents with non-suicidal self-injury

Abstract

BackgroundNon-suicidal self-injury (NSSI) is highly prevalent among adolescents and predicts future psychopathology including suicide. To improve therapeutic decisions and clinical outcome of patients engaging in NSSI, it seems beneficial to determine neurobiological markers associated with treatment response. The present study investigated whether resting-state functional brain connectivity (RSFC) served to predict clinical improvements following treatment in adolescents engaging in NSSI. MethodsN = 27 female adolescents with NSSI took part in a baseline MRI exam and clinical outcome was assessed at follow-ups one, two and three years after baseline. During the follow-up period, patients received in- and/or outpatient treatment. Mixed-effects linear regression models were calculated to examine whether RSFC was associated with clinical improvement. ResultsPatients' clinical outcome improved across time. Lower baseline RSFC between left paracentral gyrus and right anterior cingulate gyrus was associated with clinical improvement from baseline to one-year and from two-year to three-year follow-up. Lower and higher baseline RSFC in several inter- and intrahemispheric cortico-cortical and cortico-subcortical connections of interest were associated with clinical symptomatology and its severity, independent from time. LimitationsA relatively small sample size constrains the generalizability of our findings. Further, no control group not receiving treatment was recruited, therefore clinical changes across time cannot solely be attributed to treatment. ConclusionsWhile there was some evidence that RSFC was associated with clinical improvement following treatment, our findings suggest that functional connectivity is more predictive of severity of psychopathology and global functioning independent of time and treatment. We thereby add to the limited research on neurobiological markers as predictors of clinical outcome after treatment.