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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
Authors:Katherine E Tansey  Michel Guipponi  Nader Perroud  Guido Bondolfi  Enrico Domenici  David Evans  Stephanie K Hall  Joanna Hauser  Neven Henigsberg  Xiaolan Hu  Borut Jerman  Wolfgang Maier  Ole Mors  Michael O'Donovan  Tim J Peters  Anna Placentino  Marcella Rietschel  Daniel Souery  Katherine J Aitchison  Ian Craig  Anne Farmer  Jens R Wendland  Alain Malafosse  Peter Holmans  Glyn Lewis  Cathryn M Lewis  Tine Bryan Stensb?l  Shitij Kapur  Peter McGuffin  Rudolf Uher
Abstract:

Background

It 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 Findings

The 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 p<5×10−8). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10−8) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D.

Conclusions

No 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
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