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Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis.
- Source :
- PLoS Medicine, Vol 9, Iss 10, p e1001326 (2012)
- Publication Year :
- 2012
- Publisher :
- Public Library of Science (PLoS), 2012.
-
Abstract
- BackgroundIt has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way.Methods and findingsThe NEWMEDS consortium, an academia-industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance pConclusionsNo single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study. Please see later in the article for the Editors' Summary.
- Subjects :
- Medicine
Subjects
Details
- Language :
- English
- ISSN :
- 15491277 and 15491676
- Volume :
- 9
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- PLoS Medicine
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.911f831d0aa40feaf9412285f688221
- Document Type :
- article
- Full Text :
- https://doi.org/10.1371/journal.pmed.1001326