Resting-state functional connectivity of the default mode network as a predictor for escitalopram response in adolescents with depression

Abstract Adolescent depression differs from adult depression in neurobiology and treatment response. Although resting-state functional connectivity (rsFC) of the default mode network (DMN) has been linked to treatment response in adults, its value as a biomarker in adolescents remains unclear. This study investigated whether baseline DMN rsFC predicts response to selective serotonin reuptake inhibitor (SSRI) treatment in adolescents with major depressive disorder (MDD). Seventy medication-naïve adolescents with MDD (ages 12-17 years) underwent baseline resting-state functional magnetic resonance imaging and an 8-week open-label escitalopram trial. Depressive symptoms were measured using the Children’s Depression Rating Scale-Revised (CDRS-R). Seed-based DMN rsFC analyses used the ventromedial prefrontal cortex (vMPFC), dorsomedial prefrontal cortex (dMPFC), and posterior cingulate cortex (PCC) as seeds. Voxel-wise regressions assessed associations between baseline rsFC and treatment response, defined as the change in CDRS-R score from baseline to week 8. Our results showed that greater baseline DMN rsFC consistently predicted SSRI treatment response in adolescents with MDD. Stronger vMPFC-postcentral gyrus, vMPFC-insula, dMPFC-supramarginal, and PCC-supramarginal gyrus rsFCs at baseline were significantly associated with greater treatment response, as reflected by greater reductions in CDRS-R score following escitalopram treatment ( r = -0.498 to -0.603, all p s < 0.001). However, rsFCs within the DMN did not predict SSRI treatment response (all p s > 0.05). These findings suggest that baseline rsFC between DMN hubs and regions in the sensorimotor and frontoparietal networks may serve as a biomarker of SSRI treatment response in adolescents with depression. This could support individualized treatment strategies within precision psychiatry for youth with MDD.