Pharmacogenetics of antidepressant response: a polygenic approach
By
Judit García-González,
Katherine E. Tansey,
Joanna Hauser,
Neven Henigsberg,
Wolfgang Maier,
Ole Mors,
Anna Placentino,
Marcella Rietschel,
Daniel Souery,
Tina Žagar,
Piotr M. Czerski,
Borut Jerman,
Henriette N. Buttenschøn,
Thomas G. Schulze,
Astrid Zobel,
Anne Farmer,
Katherine J. Aitchison,
Ian Craig,
Peter McGuffin,
Michel Giupponi,
Nader Perroud,
Guido Bondolfi,
David Evans,
Michael O’Donovan,
Tim J. Peters,
Jens R. Wendland,
Glyn Lewis,
Shitij Kapur,
Roy Perlis,
Volker Arolt,
Katharina Domschke,
Major Depressive Disorder Working Group of the Psychiatric Genomic Consortium,
Gerome Breen,
Charles Curtis,
Lee Sang-Hyuk,
Carol Kan,
Stephen J Newhouse,
Hamel Patel,
Bernhard T. Baune,
Rudolf Uher,
Cathryn M. Lewis,
Chiara Fabbri
Posted 14 Dec 2016
bioRxiv DOI: 10.1101/093799
(published DOI: 10.1016/j.pnpbp.2017.01.011)
Background: Major depressive disorder (MDD) has a high personal and socio-economic burden and more than 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 vice-versa, including the whole sample or only patients treated with escitalopram or citalopram. Using summary statistics from Psychiatric Genomics Consortium for MDD and schizophrenia, we tested whether PRS from these disorders predicted symptom improvement in GENDEP, STAR*D, and five further studies (n=3756). Results: No significant prediction of antidepressant efficacy was obtained from PRS in GENDEP/STAR*D but this analysis might have been underpowered. There was no evidence of overlap in the genetics of antidepressant response with either MDD or schizophrenia, either in individual studies or a meta-analysis. Stratifying by antidepressant did not alter the results. Discussion: We identified no significant predictive effect using PRS between pharmacogenetic studies. The genetic liability to MDD or schizophrenia did not predict response to antidepressants, suggesting differences between the genetic component of depression and treatment response. Larger or more homogeneous studies will be necessary to obtain a polygenic predictor of antidepressant response.
Download data
- Downloaded 798 times
- Download rankings, all-time:
- Site-wide: 17,477 out of 94,912
- In genetics: 1,110 out of 4,824
- Year to date:
- Site-wide: 49,356 out of 94,912
- Since beginning of last month:
- Site-wide: 48,363 out of 94,912
Altmetric data
Downloads over time
Distribution of downloads per paper, site-wide
PanLingua
News
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!