A Review on Using the GEO Database for the Differentially Expressed Genes and Pathway Enrichment in Depression

Depression is a major cause of global disability, but the underlying biological processes for MDD are not fully elucidated. This study aimed to review the use of the Gene Expression Omnibus (GEO) database for the differentially expressed genes and pathway enrichment in depression. The study followed a systematic review to collect ten studies based on stringent inclusion and exclusion criteria following PRISMA. Subsequently, content analysis was performed to draw understanding on themes of dataset and sample Usage, methodological frameworks, differentially expressed genes (DEGs), enriched pathways, and emergent themes in depression. Following this, transcriptomics identified systematic transcriptomic changes including immune activation, endoplasmic reticulum stress, synaptic transmission, and apoptosis. Interestingly, genes like ERLIN1, GRB10, YAP1, and BCL7A were repeatedly found in both blood and brain-based studies that connect peripheral and central processes of depression pathophysiology. It was found that GEO's open-access platform allowed reproducibility and cross-study comparative analysis across a wide range of studies, albeit issues like sample heterogeneity and methodological variation remain. Relative to neuroimaging and proteomics, transcriptomics provides an adaptive and high-throughput platform for biomarker discovery. The results demonstrate the potential of GEO-based studies to enhance molecular psychiatry. However, this study was limited by publication bias and sample size. Ongoing studies should be directed toward multi-omics integration, longitudinal sampling, and functional validation to achieve the clinical potential of transcriptomic biomarkers. Thus, this study highlights the significance of strategically exploiting publicly available genomic data for the quest towards personalized medicine for depression.