Genome-wide pharmacogenetics of antidepressant response in the GENDEP project by Uher Rudolf, Perroud Nader, Ng Mandy Y M, Hauser Joanna, Henigsberg Neven, Maier Wolfgang, Mors Ole, Placentino Anna, Rietschel Marcella, Souery Daniel, Zagar Tina, Czerski Piotr M, Jerman Borut, Larsen Erik Roj, Schulze Thomas G, Zobel Astrid, Cohen-Woods Sarah, Pirlo Katrina, Butler Amy W, Muglia Pierandrea, Barnes Michael R, Lathrop Mark, Farmer Anne, Breen Gerome, Aitchison Katherine J, Craig Ian, Lewis Cathryn M, McGuffin Peter in The American journal of psychiatry (2010). PubMed

Abstract

OBJECTIVE: The purpose of this study was to identify genetic variants underlying the considerable individual differences in response to antidepressant treatment. The authors performed a genome-wide association analysis of improvement of depression severity with two antidepressant drugs. METHOD: High-quality Illumina Human610-quad chip genotyping data were available for 706 unrelated participants of European ancestry treated for major depression with escitalopram (N=394) or nortriptyline (N=312) over a 12-week period in the Genome-Based Therapeutic Drugs for Depression (GENDEP) project, a partially randomized open-label pharmacogenetic trial. RESULTS: Single nucleotide polymorphisms in two intergenic regions containing copy number variants on chromosomes 1 and 10 were associated with the outcome of treatment with escitalopram or nortriptyline at suggestive levels of significance and with a high posterior likelihood of true association. Drug-specific analyses revealed a genome-wide significant association between marker rs2500535 in the uronyl 2-sulphotransferase gene and response to nortriptyline. Response to escitalopram was best predicted by a marker in the interleukin-11 (IL11) gene. A set of 72 a priori-selected candidate genes did not show pharmacogenetic associations above a chance level, but an association with response to escitalopram was detected in the interleukin-6 gene, which is a close homologue of IL11. CONCLUSIONS: While limited statistical power means that a number of true associations may have been missed, these results suggest that efficacy of antidepressants may be predicted by genetic markers other than traditional candidates. Genome-wide studies, if properly replicated, may thus be important steps in the elucidation of the genetic basis of pharmacological response.

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