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Prog Neuropsychopharmacol Biol Psychiatry. 2017 Apr 3;75:128-134. doi: 10.1016/j.pnpbp.2017.01.011. Epub 2017 Jan 31.

Pharmacogenetics of antidepressant response: A polygenic approach.

Author information

1
Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
2
College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom.
3
Laboratory of Psychiatric Genetics, Department of Psychiatry, Poznan University of Medical Sciences, Poznan, Poland.
4
Croatian Institute for Brain Research, Medical School, University of Zagreb, Zagreb, Croatia.
5
Department of Psychiatry, University of Bonn, Bonn, Germany.
6
Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark.
7
Biological Psychiatry Unit and Dual Diagnosis Ward, Istituto Di Ricovero e Cura a Carattere Scientifico, Centro San Giovanni di Dio, Fatebenefratelli, Brescia, Italy.
8
Division of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim, Germany.
9
Laboratoire de Psychologie Médicale, Université Libre de Bruxelles and Psy Pluriel-Centre Européen de Psychologie Médicale, Brussels, Belgium.
10
Institute of Public Health of the Republic of Slovenia, Ljubljana, Slovenia.
11
Laboratory of Psychiatric Genetics, Poznan University of Medical Sciences, Poland.
12
Institute of Public Health of the Republic of Slovenia, Ljubljana, Slovenia; Department of Molecular and Biomedical Sciences, Jozef Stefan Institute, Ljubljana, Slovenia.
13
Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Risskov, Denmark.
14
Department of Psychiatry, University of Alberta, Edmonton, AB, Canada.
15
Department of Genetic Medicine and Laboratories, University Hospitals of Geneva, Geneva, Switzerland.
16
Department of Psychiatry, University of Geneva, Geneva, Switzerland.
17
Center of Excellence for Drug Discovery in Psychiatry, GlaxoSmithKline Medicines Research Centre, Verona, Italy.
18
Medical Research Council CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
19
Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Department of Psychological Medicine and Neurology, School of Medicine, Cardiff University, Cardiff, United Kingdom.
20
School of Clinical Sciences, University of Bristol, Bristol, United Kingdom.
21
Pharma Research and Early Development, F. Hoffmann-La Roche, Basel, Switzerland.
22
Division of Psychiatry, University College London, London, UK.
23
Department of Psychiatry, Center for Experimental Drugs and Diagnostics, Massachusetts General Hospital, Boston, USA.
24
Department of Psychiatry, University of Münster, Münster, Germany.
25
Department of Psychiatry Psychosomatics and Psychotherapy, University of Wuerzburg, Wuerzburg, Germany.
26
Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, Australia.
27
Department of Psychiatry, Dalhousie University, Halifax, Canada.
28
Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom. Electronic address: Cathryn.lewis@kcl.ac.uk.
29
Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.

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 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.

TRIAL REGISTRATION:

ClinicalTrials.gov NCT00021528.

KEYWORDS:

Antidepressant; Major depressive disorder; Pharmacogenomics; Polygenic risk scores; Schizophrenia

PMID:
28159590
DOI:
10.1016/j.pnpbp.2017.01.011
[Indexed for MEDLINE]

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