Recent insights into depression from transcriptomic analysis

Depression is a widespread mood disorder with a high rate of relapse and chronicity that can be affected by gender, and caused by traumatic or stressful events. Transcriptome analysis measures gene expression heterogeneity in cells, tissues, organs, and the whole body. The purpose of the study was to investigate both gender-specific and tissue-specific variations in gene expression regarding depression based on transcriptomic analysis using RNA-Seq data.

The depression datasets GSE190518 and GSE214921 were downloaded from the Gene Expression Omnibus database provided by the NCBI. The GSE190518 datasets include peripheral blood samples (4 patients, 4 healthy controls), and the GSE214921 datasets contain human postmortem orbitofrontal cortex bulk tissue (20 patients, 19 healthy controls). All datasets were analyzed separately with the DESeq2 package in R. Later, GO and KEGG enrichment analyses of differentially expressed genes were performed using the clusterProfiler package in R.

Our results reveal that depression stimulates genes linked to the immune system, which is a common denominator in both brain tissue and blood samples. Overall, tissue-specific factors contribute to the association between depression and the immune system via distinct genes. Furthermore, gene ontology analyses revealed that HSPA6, HSPA7, HSPA1L, HSPA1A, and HSPA1B genes are co-represented in different pathways involved in molecular function, biological processes, and cellular components.

Comparative transcriptomic evidence supports the immune hypothesis of depression in different tissue samples. Gender-specific depression may be triggered by protein misfolding.