Altered Reward-Related Resting-State Network Properties in Adolescent Cannabis Use and Depression

ObjectiveCannabis use among adolescents with depression is prevalent. Reward dysfunction has been documented in each condition separately, yet rarely examined in their co-occurrence. Here, we investigated cannabis use and depression comorbidity in relation to resting-state properties of reward networks in a trans-diagnostic adolescent sample. MethodClinicians interviewed adolescents and assessed depression with the Childrens Depression Rating Scale. Cannabis use was characterized by self-report and toxicology screens. Neuroimaging scans were acquired and processed using the Human Connectome Project pipelines. Participant-level resting state data were parcellated, and Reward Expectancy and Reward Attainment network masks derived from a reward task were applied. Graph theoretical metrics, including Strength Centrality (CStr), Eigenvector Centrality (CEig), and Local Efficiency (ELoc), were estimated within each network. Group-level clinical correlates of network properties were assessed with non-parametric analyses (10,000 permutations), adjusted for age, sex, and family-wise error (FWE) rates (pFWE < 0.05). ResultsIn the full sample (N = 131; 15.3 {+/-} 2.2 years; 65.2% female), depression severity was associated with stronger ELoc of the ventral striatum within the Reward Attainment network. Among those who used cannabis (n = 38), heavier cannabis use was linked to weaker CStr of the anterior cingulate cortex and ELoc of the postcentral somatosensory area within the Reward Expectancy network. Exploratory analyses further revealed cannabis-related dorsolateral prefrontal and cerebellar dysconnectivity across the whole brain, as well as sex differences. ConclusionsOur findings suggest that adolescent cannabis use and depression differentially influence resting-state reward network properties in co-occurring context. Additional research with larger cohort sizes is needed to corroborate findings.