Literature DB >> 28159590

Pharmacogenetics of antidepressant response: A polygenic approach.

Judit García-González1, Katherine E Tansey2, Joanna Hauser3, Neven Henigsberg4, Wolfgang Maier5, Ole Mors6, Anna Placentino7, Marcella Rietschel8, Daniel Souery9, Tina Žagar10, Piotr M Czerski11, Borut Jerman12, Henriette N Buttenschøn13, Thomas G Schulze8, Astrid Zobel5, Anne Farmer1, Katherine J Aitchison14, Ian Craig1, Peter McGuffin1, Michel Giupponi15, Nader Perroud16, Guido Bondolfi17, David Evans18, Michael O'Donovan19, Tim J Peters20, Jens R Wendland21, Glyn Lewis22, Shitij Kapur1, Roy Perlis23, Volker Arolt24, Katharina Domschke25, Gerome Breen1, Charles Curtis1, Lee Sang-Hyuk1, Carol Kan1, Stephen Newhouse1, Hamel Patel1, Bernhard T Baune26, Rudolf Uher27, Cathryn M Lewis28, Chiara Fabbri29.   

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.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

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

Mesh:

Substances:

Year:  2017        PMID: 28159590     DOI: 10.1016/j.pnpbp.2017.01.011

Source DB:  PubMed          Journal:  Prog Neuropsychopharmacol Biol Psychiatry        ISSN: 0278-5846            Impact factor:   5.067


  27 in total

Review 1.  Pharmacogenomics in the treatment of mood disorders: Strategies and Opportunities for personalized psychiatry.

Authors:  Azmeraw T Amare; Klaus Oliver Schubert; Bernhard T Baune
Journal:  EPMA J       Date:  2017-09-05       Impact factor: 6.543

Review 2.  Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences.

Authors:  Ryan Bogdan; David A A Baranger; Arpana Agrawal
Journal:  Annu Rev Clin Psychol       Date:  2018-05-07       Impact factor: 18.561

3.  Genome-wide association studies of placebo and duloxetine response in major depressive disorder.

Authors:  M Maciukiewicz; V S Marshe; A K Tiwari; T M Fonseka; N Freeman; J L Kennedy; S Rotzinger; J A Foster; S H Kennedy; D J Müller
Journal:  Pharmacogenomics J       Date:  2017-07-11       Impact factor: 3.550

Review 4.  Ten challenges for clinical translation in psychiatric genetics.

Authors:  Eske M Derks; Jackson G Thorp; Zachary F Gerring
Journal:  Nat Genet       Date:  2022-09-22       Impact factor: 41.307

5.  Systematic review and meta-analysis of the moderating effect of rs1799971 in OPRM1, the mu-opioid receptor gene, on response to naltrexone treatment of alcohol use disorder.

Authors:  Emily E Hartwell; Richard Feinn; Paige E Morris; Joel Gelernter; John Krystal; Albert J Arias; Michaela Hoffman; Ismene Petrakis; Ralitza Gueorguieva; Joseph P Schacht; David Oslin; Raymond F Anton; Henry R Kranzler
Journal:  Addiction       Date:  2020-02-11       Impact factor: 6.526

6.  Polygenic Score for β-Blocker Survival Benefit in European Ancestry Patients With Reduced Ejection Fraction Heart Failure.

Authors:  David E Lanfear; Jasmine A Luzum; Ruicong She; Hongsheng Gui; Mark P Donahue; Christopher M O'Connor; Kirkwood F Adams; Sandra Sanders-van Wijk; Nicole Zeld; Micha T Maeder; Hani N Sabbah; William E Kraus; Hans-Peter Brunner-LaRocca; Jia Li; L Keoki Williams
Journal:  Circ Heart Fail       Date:  2020-10-04       Impact factor: 8.790

Review 7.  Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions.

Authors:  Ramón Cacabelos; Vinogran Naidoo; Lola Corzo; Natalia Cacabelos; Juan C Carril
Journal:  Int J Mol Sci       Date:  2021-12-10       Impact factor: 5.923

8.  Rare Functional Variants Associated with Antidepressant Remission in Mexican-Americans: Short title: Antidepressant remission and pharmacogenetics in Mexican-Americans.

Authors:  Ma-Li Wong; Mauricio Arcos-Burgos; Sha Liu; Alice W Licinio; Chenglong Yu; Eunice W M Chin; Wei-Dong Yao; Xin-Yun Lu; Stefan R Bornstein; Julio Licinio
Journal:  J Affect Disord       Date:  2020-10-17       Impact factor: 6.533

Review 9.  Polygenic risk scores: from research tools to clinical instruments.

Authors:  Cathryn M Lewis; Evangelos Vassos
Journal:  Genome Med       Date:  2020-05-18       Impact factor: 11.117

10.  The MAKE Biomarker Discovery for Enhancing anTidepressant Treatment Effect and Response (MAKE BETTER) Study: Design and Methodology

Authors:  Hee-Ju Kang; Ju-Wan Kim; Seon-Young Kim; Sung-Wan Kim; Hee-Young Shin; Myung-Geun Shin; Jae-Min Kim
Journal:  Psychiatry Investig       Date:  2018-04-05       Impact factor: 2.505

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