Overall, this study reveals the increasing trend in the incidence and DALYs of depression among individuals aged 10–24 globally, and through machine learning methods, we identified key risk factors for depression, such as S100β, NSE, and PLT, providing simple and effective auxiliary tools for the early detection of depression. This evidence concerns the gene ENO2 and depressive disorder.