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.
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.
Authors: Sarah Hohmann; Nicoletta Adamo; Benjamin B Lahey; Stephen V Faraone; Tobias Banaschewski Journal: Eur Child Adolesc Psychiatry Date: 2015-04-08 Impact factor: 4.785
Authors: Christoph Anacker; Annamaria Cattaneo; Ksenia Musaelyan; Patricia A Zunszain; Mark Horowitz; Raffaella Molteni; Alessia Luoni; Francesca Calabrese; Katherine Tansey; Massimo Gennarelli; Sandrine Thuret; Jack Price; Rudolf Uher; Marco A Riva; Carmine M Pariante Journal: Proc Natl Acad Sci U S A Date: 2013-05-06 Impact factor: 11.205
Authors: Karim Malki; Maria Grazia Tosto; Héctor Mouriño-Talín; Sabela Rodríguez-Lorenzo; Oliver Pain; Irfan Jumhaboy; Tina Liu; Panos Parpas; Stuart Newman; Artem Malykh; Lucia Carboni; Rudolf Uher; Peter McGuffin; Leonard C Schalkwyk; Kevin Bryson; Mark Herbster Journal: Am J Med Genet B Neuropsychiatr Genet Date: 2016-10-01 Impact factor: 3.568
Authors: Andrew F Leuchter; Ian A Cook; Steven P Hamilton; Katherine L Narr; Arthur Toga; Aimee M Hunter; Kym Faull; Julian Whitelegge; Anne M Andrews; Joseph Loo; Baldwin Way; Stanley F Nelson; Steven Horvath; Barry D Lebowitz Journal: Curr Psychiatry Rep Date: 2010-12 Impact factor: 5.285