March 3, 2026Open Access

Integrated transcriptomic and machine learning analysis reveals novel diagnostic biomarkers for adolescent major depressive disorder

Key Points

A three-gene biosignature was identified as a novel diagnostic tool for adolescent major depressive disorder.
The biosignature consists of SLC4A1, IGF1, and MMP9, indicating immune-metabolic involvement.
Observational analysis identified these molecular changes within adolescents experiencing depression.
This work highlights potential pathways for precision medicine in treating adolescent mental health issues.

Abstract

This study delineates a systemic molecular landscape of adolescent MDD defined by the coexistence of hypoxic compensation and neurotrophic/remodeling failure. The identified three-gene biosignature (SLC4A1, IGF1, MMP9) offers a promising, objective tool for the early diagnosis of adolescent depression, highlighting the immune-metabolic interface as a critical avenue for future precision medicine.

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Discussion

Authors

Runxu Yang

Linling Jiang

Junxi Pan

Journals

SHILAP Revista de lepidopterología

Frontiers in Psychiatry

Actions

Institutions

Centre for Mental Health

Kunming Medical University

First Affiliated Hospital of Kunming Medical University

References and Citations

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Integrated transcriptomic and machine learning analysis reveals novel diagnostic biomarkers for adolescent major depressive disorder

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

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