Immune-related biomarkers for major depressive disorder identified via integrated bioinformatics and machine learning - PubMed
3 months ago
- #Biomarkers
- #Major depressive disorder
- #Machine learning
- Major depressive disorder (MDD) lacks reliable biomarkers for early diagnosis.
- Integrated bioinformatics and machine learning identified 122 differentially expressed genes (DEGs) in MDD, enriched in immune and inflammatory pathways.
- Four hub genes (DDIT4, DHRS9, FKBP5, GPER) were consistently selected by machine learning, showing high diagnostic accuracy (AUC 0.82-0.91).
- These genes are predominantly expressed in immune cells and validated in a chronic unpredictable mild stress (CUMS) rat model.
- Single-cell RNA sequencing (scRNA-seq) confirmed upregulation of these genes in specific immune cell subtypes.
- The study provides insights into immune mechanisms underlying MDD and a framework for precision diagnosis and personalized intervention.