4.6 Article

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

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PLOS MEDICINE
卷 9, 期 10, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pmed.1001326

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资金

  1. Innovative Medicine Initiative Joint Undertaking (IMI-JU) [115008]
  2. European Union's Seventh Framework Programme
  3. European Commission
  4. EC [LSHB-CT-2003-503428]
  5. GlaxoSmithKline [G0701420]
  6. UK National Institute for Health Research of the Department of Health
  7. UK Medical Research Council
  8. Mental Health Research Network
  9. Wyeth-Lederle
  10. Bristol-Myers Squibb
  11. Sanofi Aventis
  12. Canada Research Chair program
  13. NIMH [N01MH90003, MH072802]
  14. Bristol-Myers-Squibb
  15. Lundbeck
  16. Lilly
  17. Medical Research Council (UK)
  18. Wellcome Trust
  19. National Institutes of Medicine (USA)
  20. European Union
  21. Roche Molecular Systems
  22. Roche Diagnostics
  23. Johnson Johnson
  24. Otsuka Pharmaceuticals Limited
  25. Johnson AMP
  26. Johnson Pharmaceutical Research and Development
  27. AstraZeneca
  28. MRC [G0200243, G0701420] Funding Source: UKRI
  29. Medical Research Council [G0701420, G0200243, G9817803B, G0801418B] Funding Source: researchfish

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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<5x10(-8)). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p, 5610 28) 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.

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