Identification and replication of RNA-Seq gene network modules associated with depression severity

Area of Science:

• Genomics
• Molecular Psychiatry
• Bioinformatics

Background:

• Major depressive disorder (MDD) involves complex genetic factors and gene regulation.
• Gene co-expression network analysis offers a method to study these complex genetic interactions.
• Identifying gene modules associated with depression severity can reveal underlying biological pathways.

Purpose of the Study:

• To perform RNA-Seq gene co-expression network analysis on peripheral blood mononuclear cells from individuals with and without MDD.
• To identify gene modules associated with depression severity, as measured by the Montgomery-Åsberg Depression Scale (MADRS).
• To investigate the biological pathways and gene centrality within identified modules.

Main Methods:

• RNA-sequencing (RNA-Seq) was used to obtain mRNA expression data from 78 unmedicated MDD patients and 79 healthy controls.
• Hierarchical clustering and dynamic tree cut methods were employed to identify gene modules.
• Single-sample gene set enrichment scores were calculated for each module and tested for association with MADRS scores.

Main Results:

• Twenty-three gene modules were identified from the co-expression network, independent of MDD status.
• Two modules showed significant association with MADRS scores after multiple comparison correction (adjusted p < 0.05).
• One associated module replicated findings from a prior MDD RNA-Seq study; both modules were enriched for apoptosis and B cell receptor signaling pathways.

Conclusions:

• Gene co-expression network analysis successfully identified modules associated with depression severity.
• The identified modules implicate apoptosis and B cell receptor signaling in MDD pathophysiology.
• Intramodular hub genes within these modules may represent key players in MDD, correlating network centrality with depression association.