"Identification and replication of RNA-Seq gene network modules associ" by Trang T. Le, Jonathan Savitz et al.

Department of Educational Psychology

 

ORCID IDs

Bill C. White

Document Type

Article

Date of this Version

2018

Citation

Translational Psychiatry (2018) 8:180

Comments

© The Author(s) 2018

Open access

DOI: 10.1038/s41398-018-0234-3

Abstract

Genomic variation underlying major depressive disorder (MDD) likely involves the interaction and regulation of multiple genes in a network. Data-driven co-expression network module inference has the potential to account for variation within regulatory networks, reduce the dimensionality of RNA-Seq data, and detect significant geneexpression modules associated with depression severity. We performed an RNA-Seq gene co-expression network analysis of mRNA data obtained from the peripheral blood mononuclear cells of unmedicated MDD (n = 78) and healthy control (n = 79) subjects. Across the combined MDD and HC groups, we assigned genes into modules using hierarchical clustering with a dynamic tree cut method and projected the expression data onto a lower-dimensional module space by computing the single-sample gene set enrichment score of each module. We tested the singlesample scores of each module for association with levels of depression severity measured by the Montgomery-Åsberg Depression Scale (MADRS). Independent of MDD status, we identified 23 gene modules from the co-expression network. Two modules were significantly associated with the MADRS score after multiple comparison adjustment (adjusted p = 0.009, 0.028 at 0.05 FDR threshold), and one of these modules replicated in a previous RNA-Seq study of MDD (p = 0.03). The two MADRS-associated modules contain genes previously implicated in mood disorders and show enrichment of apoptosis and B cell receptor signaling. The genes in these modules show a correlation between network centrality and univariate association with depression, suggesting that intramodular hub genes are more likely to be related to MDD compared to other genes in a module.

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