Pharmacogenomic predictors of citalopram treatment outcome in major depressive disorder.

TitlePharmacogenomic predictors of citalopram treatment outcome in major depressive disorder.
Publication TypeJournal Article
Year of Publication2014
AuthorsMamdani F, Berlim M, Beaulieu M-M, Turecki G
JournalWorld J Biol Psychiatry
Volume15
Issue2
Pagination135-44
Date Published2014 Feb
ISSN1814-1412
KeywordsAdult, Biomarkers, Citalopram, Depressive Disorder, Major, Down-Regulation, Female, Gene Expression, Humans, Male, Pharmacogenetics, Remission Induction, Serotonin Uptake Inhibitors, Sialic Acid Binding Immunoglobulin-like Lectins, Smad7 Protein, Treatment Outcome
Abstract

OBJECTIVES: A significant proportion of patients with major depressive disorder (MDD) do not improve following treatment with first-line antidepressants and, currently, there are no objective indicators of predictors of antidepressant response. The aim of this study was to investigate pre-treatment peripheral gene expression differences between future remitters and non-responders to citalopram treatment and identify potential pharmacogenomic predictors of response.METHODS: We conducted a gene expression study using Affymetrix HG-U133 Plus2 microarrays in peripheral blood samples from untreated individuals with MDD (N = 77), ascertained at a community outpatient clinic, prior to an 8-week treatment with citalopram. Gene expression differences were assessed between remitters and non-responders to treatment. Technical validation of significant probesets was carried out by qRT-PCR.RESULTS: A total of 434 probesets displayed significant correlation to change in score and 33 probesests were differentially expressed between eventual remitters and non-responders. Probesets for SMAD 7 (SMA- and MAD-related protein 7) and SIGLECP3 (sialic acid-binding immunoglobulin-like lectin, pseudogene 3) were the most significant differentially expressed genes following FDR correction, and both were down-regulated in individuals who responded to treatment.CONCLUSIONS: These findings point to SMAD7 and SIGLECP3 as candidate predictive biomarkers of antidepressant response.

DOI10.3109/15622975.2013.766762
Alternate JournalWorld J. Biol. Psychiatry
PubMed ID23530732