Journal article

Pharmacogenetics of antidepressant response: A polygenic approach

Judit Garcia-Gonzalez, Katherine E Tansey, Joanna Hauser, Neven Henigsberg, Wolfgang Maier, Ole Mors, Anna Placentino, Marcella Rietschel, Daniel Souery, Tina Zagar, Piotr M Czerski, Borut Jerman, Henriette N Buttenschon, Thomas G Schulze, Astrid Zobel, Anne Farmer, Katherine J Aitchison, Ian Craig, Peter McGuffin, Michel Giupponi Show all

PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY | PERGAMON-ELSEVIER SCIENCE LTD | Published : 2017

Abstract

BACKGROUND: Major depressive disorder (MDD) has a high personal and socio-economic burden and >60% of patients fail to achieve remission with the first antidepressant. The biological mechanisms behind antidepressant response are only partially known but genetic factors play a relevant role. A combined predictor across genetic variants may be useful to investigate this complex trait. METHODS: Polygenic risk scores (PRS) were used to estimate multi-allelic contribution to: 1) antidepressant efficacy; 2) its overlap with MDD and schizophrenia. We constructed PRS and tested whether these predicted symptom improvement or remission from the GENDEP study (n=736) to the STAR*D study (n=1409) and vic..

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University of Melbourne Researchers

Grants

Awarded by NIMH


Awarded by Lundbeck Foundation


Awarded by Medical Research Council


Awarded by NATIONAL INSTITUTE OF MENTAL HEALTH


Funding Acknowledgements

We thank the NIMH for access to data on the STAR*D study. We also thank the authors of previous publicatiOns in this dataset, and foremost, we thank the patients and their families who accepted to be enrolled in the study. Data and biomaterials were Obtained from the limited access datasets distributed from the NIH-supported "Sequenced Treatment Alternatives to Relieve Depression" (STAR*D). The study was supported by NIMH Contract No. NO1MH90003 to the University of Texas Southwestern Medical Center. The ClinicalTrials.gov identifier is NCT00021528.