Reanalysis of Public Transcriptomes Reveals Shared Immune Signatures Between Major Depressive Disorder And...

Area of Science:

• Genomics
• Immunology
• Bioinformatics

Background:

• Major depressive disorder (MDD) and dermatomyositis (DM) are distinct conditions with complex etiologies.
• Shared biological pathways, particularly immune-related ones, may underlie comorbid presentations or influence disease pathogenesis.
• Transcriptomic analysis offers a powerful approach to uncover molecular links between seemingly unrelated diseases.

Purpose of the Study:

• To identify candidate shared transcriptomic signals between MDD and DM.
• To characterize the immune-related cellular context of these shared signals.
• To prioritize potential diagnostic biomarkers using machine learning.

Main Methods:

• Integrative bioinformatic reanalysis of public Gene Expression Omnibus (GEO) datasets.
• Weighted Gene Co-expression Network Analysis (WGCNA) for module identification.
• Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), GeneMANIA, and network analysis for functional and pathway characterization.
• Machine learning models with SHapley Additive exPlanations (SHAP) for feature selection.
• Gene Set Enrichment Analysis (GSEA), immune infiltration analysis, and single-cell RNA-seq contextualization.

Main Results:

• Identified 570 differentially expressed genes in DM datasets, yielding 33 candidate shared genes via WGCNA.
• Functional analyses highlighted immune defense, cytotoxicity, and pathways including PPAR, IL-17, and antigen processing.
• Machine learning prioritized 8 candidate genes (KIF4A, OLR1, KIR2DL4, KRT23, KIR3DS1, AZU1, SCG5, LRRC37E).
• Shared genes were associated with regulatory T cells (Tregs), mast cells, dendritic cells, and M1/M2 macrophages.
• Single-cell analysis suggested distinct intercellular communication patterns in CD8+ T-cell subsets and highlighted the MIF-(CD74+CD44) axis.

Conclusions:

• This study identified potential shared transcriptomic signatures between MDD and DM.
• Immune-related cellular contexts, including T-cell interactions and macrophage polarization, are implicated.
• The findings provide candidate biomarkers and biological insights warranting further validation in comorbid patient cohorts.