A genomewide association study points to multiple loci that predict antidepressant drug treatment outcome in depression
Date
2009
Authors
Ising, M.
Lucae, S.
Binder, E.
Bettecken, T.
Uhr, M.
Ripke, S.
Kohli, M.
Hennings, J.
Horstmann, S.
Menke, A.
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Journal article
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Archives of General Psychiatry, 2009; 66(9):966-975
Statement of Responsibility
Marcus Ising, Susanne Lucae, Elisabeth B. Binder, Thomas Bettecken, Manfred Uhr, Stephan Ripke, Martin A. Kohli, Johannes M. Hennings, Sonja Horstmann, Stefan Kloiber, Andreas Menke, Brigitta Bondy, Rainer Rupprecht, Katharina Domschke, Bernhard T. Baune, Volker Arolt, A. John Rush, Florian Holsboer, Bertram Müller-Myhsok
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Abstract
<h4>Context</h4>The efficacy of antidepressant drug treatment in depression is unsatisfactory; 1 in 3 patients does not fully recover even after several treatment trials. Genetic factors and clinical characteristics contribute to the failure of a favorable treatment outcome.<h4>Objective</h4>To identify genetic and clinical determinants of antidepressant drug treatment outcome in depression.<h4>Design</h4>Genomewide pharmacogenetic association study with 2 independent replication samples.<h4>Setting</h4>We performed a genomewide association study in patients from the Munich Antidepressant Response Signature (MARS) project and in pooled DNA from an independent German replication sample. A set of 328 single-nucleotide polymorphisms highly related to outcome in both genomewide association studies was genotyped in a sample of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study.<h4>Participants</h4>A total of 339 inpatients with a depressive episode (MARS sample), a further 361 inpatients with depression (German replication sample), and 832 outpatients with major depression (STAR*D sample).<h4>Main outcome measures</h4>We generated a multilocus genetic variable that described the individual number of alleles of the selected single nucleotide polymorphisms associated with beneficial treatment outcome in the MARS sample ("response" alleles) to evaluate additive genetic effects on antidepressant drug treatment outcome.<h4>Results</h4>Multilocus analysis revealed a significant contribution of a binary variable that categorized patients as carriers of a high vs low number of response alleles in the prediction of antidepressant drug treatment outcome in both samples (MARS and STAR*D). In addition, we observed that patients with a comorbid anxiety disorder combined with a low number of response alleles showed the least favorable outcome.<h4>Conclusion</h4>These results demonstrate the importance of multiple genetic factors combined with clinical features in the prediction of antidepressant drug treatment outcome, which underscores the multifactorial nature of this trait.
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©2009 American Medical Association. All rights reserved.