Untargeted plasma proteomics and clinical phenotypes in adolescent depression

Background Depressive disorders are among the most common mental disorders, often emerging in adolescence. Despite advances in biological psychiatry, research on early psychopathology remains scarce. Given the heterogeneity and comorbidity of depressive disorders, identifying biologically informed phenotypes could enhance diagnostic accuracy and personalized treatment approaches. Methods This study utilized baseline and 6-month follow-up plasma samples (n=47) and clinical data (n=103) of adolescent outpatients with depression (DD, aged 14-19) from the Finnish SMART study and healthy control samples (HC, n=53, aged 15-16) from the Finnish PANIC study. Fasting plasma samples were analyzed using untargeted liquid chromatography-tandem mass spectrometry for proteomics. Data analyses included dimensionality reduction, regression models, correlation analysis, functional enrichment, and factor analysis of mixed data with k-means clustering, including 72 symptom-related items, lifestyle, and socioeconomic scales. Results Among 756 proteins detected in DD and HC, 308 proteins showed notable, significant (adjusted p<0.01 and Log2FC [&ge;]|1|) alterations in depression. These proteins were enriched in stress-response pathways, including complement and coagulation cascades, energy metabolism, the proteasome complex, and growth factor signaling. Additionally, extracellular matrix proteins were altered. Clinical phenotypes were mostly distinguished by symptom severity, bullying victimization and other trauma-related experiences, social relationships, and medication. Improvement in mood over the 6-month follow-up was associated with shifts in proteins involved in extracellular matrix, cytoplasmic vesicles, and complement and coagulation cascades. Conclusions Together, adolescent depression displays shared plasma proteomic signatures across its clinical phenotypes, and systemic immune dysfunction, oxidative stress, and extracellular matrix are potential targets for biologically informed interventions in depression.