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J Psychiatr Res. 2016 Oct;81:119-26. doi: 10.1016/j.jpsychires.2016.07.009. Epub 2016 Jul 9.

Predisposition to treatment response in major depressive episode: A peripheral blood gene coexpression network analysis.

Author information

1
McGill Group for Suicide Studies, Department of Psychiatry, McGill University, Douglas Mental Health University Institute, Montreal, QC, Canada; Fondation FondaMental, Créteil, France; CRN2M-UMR7286, Aix-Marseille Université, CNRS, Marseille, France. Electronic address: raoul.belzeaux@mail.mcgill.ca.
2
Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.
3
TAGC, INSERM, Marseille, France.
4
Fondation FondaMental, Créteil, France; CRN2M-UMR7286, Aix-Marseille Université, CNRS, Marseille, France.
5
McGill Group for Suicide Studies, Department of Psychiatry, McGill University, Douglas Mental Health University Institute, Montreal, QC, Canada.
6
Campbell Family Mental Health Research Institute of CAMH, Departments of Psychiatry and of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada.

Abstract

Antidepressant efficacy is insufficient, unpredictable and poorly understood in major depressive episode (MDE). Gene expression studies allow for the identification of significantly dysregulated genes but can limit the exploration of biological pathways. In the present study, we proposed a gene coexpression analysis to investigate biological pathways associated with treatment response predisposition and their regulation by microRNAs (miRNAs) in peripheral blood samples of MDE and healthy control subjects. We used a discovery cohort that included 34 MDE patients that were given 12-week treatment with citalopram and 33 healthy controls. Two replication cohorts with similar design were also analyzed. Expression-based gene network was built to define clusters of highly correlated sets of genes, called modules. Association between each module's first principal component of the expression data and clinical improvement was tested in the three cohorts. We conducted gene ontology analysis and miRNA prediction based on the module gene list. Nine of the 59 modules from the gene coexpression network were associated with clinical improvement. The association was partially replicated in other cohorts. Gene ontology analysis demonstrated that 4 modules were associated with cytokine production, acute inflammatory response or IL-8 functions. Finally, we found 414 miRNAs that may regulate one or several modules associated with clinical improvement. By contrast, only 12 miRNAs were predicted to specifically regulate modules unrelated to clinical improvement. Our gene coexpression analysis underlines the importance of inflammation-related pathways and the involvement of a large miRNA program as biological processes predisposing associated with antidepressant response.

KEYWORDS:

Antidepressant; Gene network; Inflammation; MicroRNA; Mood disorder

[Indexed for MEDLINE]

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