Precision psychiatry in depression via mechanism based stratification and therapy

Abstract

Major depressive disorder (MDD) exhibits such pronounced heterogeneity that conventional symptom-based diagnoses and monoamine-focused treatments have proven largely inadequate, pushing the field toward what we now call precision psychiatry. In this review, we map out stratification approaches rooted in mechanisms spanning neural circuits, immune function, metabolic regulation, and the gut-brain axis. We also discuss how multi-omics, neuroimaging, and digital phenotyping can be integrated to construct continuous, biological grounded disease subtypes. Building from this groundwork, precision drug development has increasingly turned its attention to targets with genetic validation, therapeutics tailored to specific biological profiles, and adaptive trial designs that leverage biomarker-guided patient selection. Making this vision operational demands more than scientific insight as it requires weaving predictive algorithms into closed-loop care systems and everyday clinical practice, all while keeping health equity front and center so that technological progress does not end up widening gaps in access and outcomes. Real progress in MDD care will only emerge when we manage to blend deep mechanistic understanding with intelligent data analysis and genuinely inclusive implementation.

Ethical statements

Not applicable.

Author contributions

The authors confirm their contributions to the work as follows: draft manuscript preparation: Wang M, Jiang Y, Wu C; performing the graphmapping: Liao J; data collection and manuscript revision: Zhou B, Yuan Y, Sun J. All authors reviewed the results and approved the final version of the manuscript.

Data availability

Data sharing is not applicable to this review as no datasets were generated or analyzed.

Acknowledgements

We gratefully acknowledge grant support from the Double First-Rate construction plan of China Pharmaceutical University (CPU2025CXY03), and Natural Science Foundation of Jiangsu Province (BK20242072).

Conflict of interest

The authors declare no competing financial interest.

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