Major depressive disorder (MDD) is a common mental health condition characterized by substantial clinical heterogeneity and variability in treatment response. Current diagnosis and treatment selection for MDD mainly rely on clinical assessments, and reliable biological markers that can support diagnosis, predict antidepressant treatment response, guide personalized treatment, and improve understanding of disease mechanisms remain limited.

The goal of this prospective observational cohort study is to develop and optimize multi-omics-based models for MDD diagnosis and antidepressant treatment response prediction using longitudinal clinical characteristics and biological data collected from an independent prospective cohort. The study also aims to evaluate the generalizability and predictive performance of existing multi-omics-based models in this independent cohort of participants aged 14-45 years.

The main questions it aims to answer are:

Can integrated clinical and multi-omics features identify biomarkers and develop predictive models for MDD diagnosis and antidepressant treatment response? Can existing multi-omics-based models for MDD diagnosis and treatment response prediction be replicated and validated in an independent prospective cohort?

Participants with MDD and healthy controls will undergo standardized clinical assessments, longitudinal follow-up, and biological sample collection for multi-omics profiling. Clinical and multi-omics data will be integrated to identify biomarkers, develop and validate predictive models for MDD diagnosis, antidepressant treatment response, and long-term outcomes, and explore biological pathways and potential therapeutic targets associated with MDD.

The study is expected to improve understanding of the biological heterogeneity of MDD and contribute to the development of objective approaches for diagnosis, treatment response prediction, personalized care, and future therapeutic discovery.