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dc.contributor.authorTansey, KE
dc.contributor.authorGuipponi, M
dc.contributor.authorPerroud, N
dc.contributor.authorBondolfi, G
dc.contributor.authorDomenici, E
dc.contributor.authorEvans, D
dc.contributor.authorHall, SK
dc.contributor.authorHauser, J
dc.contributor.authorHenigsberg, N
dc.contributor.authorHu, X
dc.contributor.authorJerman, B
dc.contributor.authorMaier, W
dc.contributor.authorMors, O
dc.contributor.authorO'Donovan, M
dc.contributor.authorPeters, TJ
dc.contributor.authorPlacentino, A
dc.contributor.authorRietschel, M
dc.contributor.authorSouery, D
dc.contributor.authorAitchison, KJ
dc.contributor.authorCraig, I
dc.contributor.authorFarmer, A
dc.contributor.authorWendland, JR
dc.contributor.authorMalafosse, A
dc.contributor.authorHolmans, P
dc.contributor.authorLewis, G
dc.contributor.authorLewis, CM
dc.contributor.authorStensbøl, TB
dc.contributor.authorKapur, S
dc.contributor.authorMcGuffin, P
dc.contributor.authorUher, R
dc.date.accessioned2020-12-21T02:13:30Z
dc.date.available2020-12-21T02:13:30Z
dc.date.issued2012
dc.identifierpii: PMEDICINE-D-12-00808
dc.identifier.citationTansey, K. E., Guipponi, M., Perroud, N., Bondolfi, G., Domenici, E., Evans, D., Hall, S. K., Hauser, J., Henigsberg, N., Hu, X., Jerman, B., Maier, W., Mors, O., O'Donovan, M., Peters, T. J., Placentino, A., Rietschel, M., Souery, D., Aitchison, K. J. ,... Uher, R. (2012). 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.. PLoS Med, 9 (10), pp.e1001326-. https://doi.org/10.1371/journal.pmed.1001326.
dc.identifier.issn1549-1277
dc.identifier.urihttp://hdl.handle.net/11343/256834
dc.description.abstractBACKGROUND: 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.
dc.languageeng
dc.publisherPublic Library of Science (PLoS)
dc.titleGenetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis.
dc.typeJournal Article
dc.identifier.doi10.1371/journal.pmed.1001326
melbourne.affiliation.departmentMedicine Dentistry & Health Sciences
melbourne.source.titlePLoS Medicine
melbourne.source.volume9
melbourne.source.issue10
melbourne.source.pagese1001326-
dc.rights.licenseCC BY
melbourne.elementsid1232658
melbourne.openaccess.pmchttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3472989
melbourne.contributor.authorKapur, Shitij
dc.identifier.eissn1549-1676
melbourne.accessrightsOpen Access


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