Literature DB >> 25649181

Identifying genetic loci associated with antidepressant drug response with drug-gene interaction models in a population-based study.

Raymond Noordam1, Nese Direk2, Colleen M Sitlani3, Nikkie Aarts4, Henning Tiemeier5, Albert Hofman6, André G Uitterlinden7, Bruce M Psaty8, Bruno H Stricker9, Loes E Visser10.   

Abstract

It has been difficult to identify genes affecting drug response to Selective Serotonin Reuptake Inhibitors (SSRIs). We used multiple cross-sectional assessments of depressive symptoms in a population-based study to identify potential genetic interactions with SSRIs as a model to study genetic variants associated with SSRI response. This study, embedded in the prospective Rotterdam Study, included all successfully genotyped participants with data on depressive symptoms (CES-D scores). We used repeated measurement models to test multiplicative interaction between genetic variants and use of SSRIs on repeated CESD scores. Besides a genome-wide analysis, we also performed an analysis which was restricted to genes related to the serotonergic signaling pathway. A total of 273 out of 14,937 assessments of depressive symptoms in 6443 participants, use of an SSRI was recorded. After correction for multiple testing, no plausible loci were identified in the genome-wide analysis. However, among the top 10 independent loci with the lowest p-values, findings within two genes (FSHR and HMGB4) might be of interest. Among 26 genes related to the serotonergic signaling pathway, the rs6108160 polymorphism in the PLCB1 gene reached statistical significance after Bonferroni correction (p-value = 8.1e-5). Also, the widely replicated 102C > T polymorphism in the HTR2A gene showed a statistically significant drug-gene interaction with SSRI use. Therefore, the present study suggests that drug-gene interaction models on (repeated) cross-sectional assessments of depressive symptoms in a population-based study can identify potential loci that may influence SSRI response.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Drug response biomarkers; Gene–environment interaction; Genome-wide association study; Pharmacogenetics; Serotonin uptake inhibitors

Mesh:

Substances:

Year:  2015        PMID: 25649181     DOI: 10.1016/j.jpsychires.2015.01.005

Source DB:  PubMed          Journal:  J Psychiatr Res        ISSN: 0022-3956            Impact factor:   4.791


  8 in total

1.  The Rotterdam Study: 2016 objectives and design update.

Authors:  Albert Hofman; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; M Arfan Ikram; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Ch Stricker; Henning W Tiemeier; André G Uitterlinden; Meike W Vernooij
Journal:  Eur J Epidemiol       Date:  2015-09-19       Impact factor: 8.082

Review 2.  Pharmacogenetics of major depressive disorder: top genes and pathways toward clinical applications.

Authors:  Chiara Fabbri; Alessandro Serretti
Journal:  Curr Psychiatry Rep       Date:  2015-07       Impact factor: 5.285

Review 3.  Pharmacogenetics and Imaging-Pharmacogenetics of Antidepressant Response: Towards Translational Strategies.

Authors:  Tristram A Lett; Henrik Walter; Eva J Brandl
Journal:  CNS Drugs       Date:  2016-12       Impact factor: 5.749

Review 4.  Identifying genetic loci affecting antidepressant drug response in depression using drug-gene interaction models.

Authors:  Raymond Noordam; Christy L Avery; Loes E Visser; Bruno H Stricker
Journal:  Pharmacogenomics       Date:  2016-06-01       Impact factor: 2.533

5.  The Rotterdam Study: 2018 update on objectives, design and main results.

Authors:  M Arfan Ikram; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Stricker; Henning Tiemeier; André G Uitterlinden; Meike W Vernooij; Albert Hofman
Journal:  Eur J Epidemiol       Date:  2017-10-24       Impact factor: 8.082

6.  HMGB4 is expressed by neuronal cells and affects the expression of genes involved in neural differentiation.

Authors:  Ari Rouhiainen; Xiang Zhao; Päivi Vanttola; Kui Qian; Evgeny Kulesskiy; Juha Kuja-Panula; Kathleen Gransalke; Mikaela Grönholm; Emmanual Unni; Marvin Meistrich; Li Tian; Petri Auvinen; Heikki Rauvala
Journal:  Sci Rep       Date:  2016-09-09       Impact factor: 4.379

7.  A pharmacogenetic risk score for the evaluation of major depression severity under treatment with antidepressants.

Authors:  Sofia H Kanders; Claudia Pisanu; Marcus Bandstein; Jörgen Jonsson; Enrique Castelao; Giorgio Pistis; Mehdi Gholam-Rezaee; Chin B Eap; Martin Preisig; Helgi B Schiöth; Jessica Mwinyi
Journal:  Drug Dev Res       Date:  2019-10-16       Impact factor: 4.360

Review 8.  Pharmacogenomic Characterization in Bipolar Spectrum Disorders.

Authors:  Stefano Fortinguerra; Vincenzo Sorrenti; Pietro Giusti; Morena Zusso; Alessandro Buriani
Journal:  Pharmaceutics       Date:  2019-12-21       Impact factor: 6.321

  8 in total

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