Major depressive disorder in children and adolescents is associated with reduced hair cortisol and anandamide (AEA): cross-sectional and longitudinal evidence from a large randomized clinical trial.

Pediatric major depressive disorder (MDD) represents a leading cause of disability worldwide in children and adolescents, while its underlying pathophysiology remains largely elusive. The endocannabinoid system (ECS) and the hypothalamus-pituitary-adrenal (HPA) axis are considered intertwined regulatory systems crucially implicated in the pathophysiology of depressive disorders. This study explores the cross-sectional and longitudinal association between the ECS, specifically anandamide (AEA), and the HPA axis with its main effector cortisol and MDD status and severity in children and adolescents. Utilizing data from the omega-3-pMDD trial, a phase III Randomized Clinical Trial assessing the efficacy and safety of omega-3 fatty acid supplementation in pediatric MDD, we examined hair AEA and cortisol concentrations in 110 children and adolescents aged 8-17 years, with MDD. Associations between MDD, symptom severity and hair AEA and cortisol concentrations were explored across four measurement time points (baseline, week 6, 24 and 36). Additionally, 127 healthy children and adolescents were examined once to enable cross-sectional comparisons between MDD cases and healthy controls. Baseline comparisons for the 237 children and adolescents showed lower cortisol and AEA levels in hair of children and adolescents with MDD compared to healthy controls. Longitudinal multi-level analysis over all time-points further corroborated negative longitudinal associations between hair cortisol and depressive symptoms in children and adolescents with MDD. Taken together, reduced baseline AEA and cortisol levels emerge as robust biomarker in depressed youth, while the negative longitudinal association between hair cortisol and depression symptoms might provide useful for therapy monitoring purposes. These results hold implications for early detection, diagnosis, and therapeutic response prediction in pediatric MDD.