Evidence map›Paper›PMID 23091423›Full record

SynthesisPLoS medicine2012

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.

Katherine E Tansey, Michel Guipponi, Nader Perroud, Guido Bondolfi, Enrico Domenici, David Evans, Stephanie K Hall, Joanna Hauser, Neven Henigsberg, Xiaolan Hu and 20 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in PLoS medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

66 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

30 authors.

Katherine E TanseyInstitute of Psychiatry, King's College London, London, UK.
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 Stensbøl
Shitij Kapur
Peter McGuffin
Rudolf Uher

Funding

Pharmacogenomics of Antidepressant ResponseR01MH072802 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HAMILTON, STEVEN P. · 2005 to 2008
$4.6M
TREATMENT RESISTANT DEPRESSION-278990003N01MH090003 · NIMH · UNIVERSITY OF TEXAS SW MED CTR/DALLAS · 1999 to 2003
–
Department of HealthMedical Research Council G0200243Medical Research Council G0701420NIMH NIH HHS MH072802NIMH NIH HHS N01 MH090003NIMH NIH HHS R01 MH072802
6 · The paper itself

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 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.

conclusionsNo 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.

Indexed as

Antidepressive AgentsFemaleGenome-Wide Association StudyGenotypeHumansLinear ModelsMajor Depressive DisorderMalePolymorphism, GeneticSelective Serotonin Reuptake InhibitorsTreatment OutcomeAntidepressive AgentsSelective Serotonin Reuptake Inhibitors

Identifiers

PMID23091423
PMCPMC3472989

What OpenQuestion holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.