Weifeng Jin, Shuzi Chen, Dan Li, Qing Chen, Mengyuan Zhu, Mengxia Wang, Xiaomei Fu, Ping Lin

Department of Medical Laboratory, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China

Correspondence: Ping Lin, Email Linpingsun20000@aliyun.com

Abstract: Depressive disorders diagnosis relies on subjective clinical assessment due to the lack of validated biomarkers. This review synthesizes recent advances in depression biomarkers across genetic, epigenetic, neuroendocrine, neuroimaging, immune/inflammatory, and gut microbiota domains. Literature was systematically searched via PubMed/Web of Science.We analyze mechanisms, highlight challenges (eg, clinical heterogeneity, inadequate animal models), and propose future directions: multidimensional bioinformatics, AI-driven models, RDoC framework implementation, and interdisciplinary collaboration. Critically, our analysis reveals that multimodal integration of biomarkers—rather than single-domain approaches—holds the greatest promise for overcoming diagnostic heterogeneity and guiding personalized interventions. These strategies may revolutionize MDD management through early detection and tailored therapeutics.

Keywords: depressive disorders, biomarkers