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. The gene discussed is ENO2; the disease is depressive symptom measurement.