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Genomewide interaction and enrichment analysis on antidepressant response

Published online by Cambridge University Press:  01 July 2013

N. Antypa ,
A. Drago  and
A. Serretti
N. Antypa
Affiliation:
Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
A. Drago
Affiliation:
IRCCS Centro S. Giovanni di Dio, Fatebenefratelli, Brescia, Italy
A. Serretti*
Affiliation:
Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
*
*Address for correspondence: A. Serretti, M.D., Ph.D., Department of Biomedical and NeuroMotor Sciences, University of Bologna, Viale Carlo Pepoli 5, 40123 Bologna, Italy. (Email: alessandro.serretti@unibo.it)
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Abstract

Background

Genomewide association studies (GWASs) on antidepressant efficacy have yielded modest results. A possible reason is that response is influenced by other factors, which possibly interact with genetic variation. We used a GWAS model to predict antidepressant response, by including predictors previously known to affect response, such as quality of life (QoL). We also evaluated the association between genes, previously implicated in gene–environment (G × E) interactions, and response using an enrichment analysis.

Method

We examined a sample of 1426 depressed patients from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial: 774 responders, 652 non-responders and 418 865 single nucleotide polymorphisms (SNPs) were analysed. First, in a GWAS model, we investigated whether genetic variations interact with patients' levels of QoL to predict response, after controlling for demographic characteristics, severity and population stratification. Second, we conducted an enrichment analysis exploring whether candidate genes that have emerged from prior G × E interaction studies on depression are associated with treatment response.

Results

The GWAS model, with QoL as a moderator, yielded one SNP (rs520210) associated with response in the NEDD4L gene (p = 3.64 × 10−8). In the Caucasian sample only, we observed a drop in significance for this SNP. The enrichment analysis showed that SNPs within serotonergic genes contained more significant markers that predicted response, compared with a random set of genes in the genome.

Conclusions

Our findings point to possible target genes, which are proposed for further independent replication. Our enrichment analysis provides further support, in a genomewide context, of the role of serotonergic genes in influencing antidepressant response.

Keywords

Antidepressant responseenrichment analysisgenomewide interactionquality of life
Type
Original Articles
Information
Psychological Medicine , Volume 44 , Issue 4 , March 2014 , pp. 753 - 765
Copyright
Copyright © Cambridge University Press 2013 

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