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Journal of Psychiatric Research
Article . 2015 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Identifying genetic loci associated with antidepressant drug response with drug–gene interaction models in a population-based study

Authors: Noordam, R.; Direk, N.; Sitlani, C.M.; Aarts, N.; Tiemeier, H.; Hofman, A.; Uitterlinden, A.G.; +3 Authors

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

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.

Countries
Turkey, Netherlands
Keywords

EMC NIHES-01-64-03, Male, Genome-wide association study, Genotype, Polymorphism, Single Nucleotide, EMC NIHES-04-55-01, Community Health Planning, Cohort Studies, Meta-Analysis as Topic, Humans, Drug response biomarkers, Serotonin uptake inhibitors, Aged, Aged, 80 and over, Psychiatric Status Rating Scales, EMC ONWAR-01-58-02, Depression, Middle Aged, Gene-environment interaction, Antidepressive Agents, Cross-Sectional Studies, Pharmacogenetics, EMC MM-01-39-09-A, Female, Genome-Wide Association Study

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Average
Top 10%
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