Genomewide interaction and enrichment analysis on antidepressant response

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Genomewide interaction and enrichment analysis on antidepressant response. / Antypa, N; Drago, A; Serretti, A.

I: Psychological Medicine, Bind 44, Nr. 4, 03.2014, s. 753-65.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

Harvard

Antypa, N, Drago, A & Serretti, A 2014, 'Genomewide interaction and enrichment analysis on antidepressant response', Psychological Medicine, bind 44, nr. 4, s. 753-65. https://doi.org/10.1017/S0033291713001554

APA

Antypa, N., Drago, A., & Serretti, A. (2014). Genomewide interaction and enrichment analysis on antidepressant response. Psychological Medicine, 44(4), 753-65. https://doi.org/10.1017/S0033291713001554

CBE

Antypa N, Drago A, Serretti A. 2014. Genomewide interaction and enrichment analysis on antidepressant response. Psychological Medicine. 44(4):753-65. https://doi.org/10.1017/S0033291713001554

MLA

Antypa, N, A Drago og A Serretti. "Genomewide interaction and enrichment analysis on antidepressant response". Psychological Medicine. 2014, 44(4). 753-65. https://doi.org/10.1017/S0033291713001554

Vancouver

Antypa N, Drago A, Serretti A. Genomewide interaction and enrichment analysis on antidepressant response. Psychological Medicine. 2014 mar.;44(4):753-65. https://doi.org/10.1017/S0033291713001554

Author

Antypa, N ; Drago, A ; Serretti, A. / Genomewide interaction and enrichment analysis on antidepressant response. I: Psychological Medicine. 2014 ; Bind 44, Nr. 4. s. 753-65.

Bibtex

@article{ebd0f6de1234441987e11e69050f2ab3,
title = "Genomewide interaction and enrichment analysis on antidepressant response",
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 = "Adult, Antidepressive Agents, Clinical Trials as Topic, Depression, Endosomal Sorting Complexes Required for Transport, Female, Gene-Environment Interaction, Genome-Wide Association Study, Humans, Male, Middle Aged, Pharmacogenetics, Polymorphism, Single Nucleotide, Predictive Value of Tests, Quality of Life, Ubiquitin-Protein Ligases",
author = "N Antypa and A Drago and A Serretti",
year = "2014",
month = mar,
doi = "10.1017/S0033291713001554",
language = "English",
volume = "44",
pages = "753--65",
journal = "Psychological Medicine",
issn = "0033-2917",
publisher = "Cambridge University Press",
number = "4",

}

RIS

TY - JOUR

T1 - Genomewide interaction and enrichment analysis on antidepressant response

AU - Antypa, N

AU - Drago, A

AU - Serretti, A

PY - 2014/3

Y1 - 2014/3

N2 - 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.

AB - 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.

KW - Adult

KW - Antidepressive Agents

KW - Clinical Trials as Topic

KW - Depression

KW - Endosomal Sorting Complexes Required for Transport

KW - Female

KW - Gene-Environment Interaction

KW - Genome-Wide Association Study

KW - Humans

KW - Male

KW - Middle Aged

KW - Pharmacogenetics

KW - Polymorphism, Single Nucleotide

KW - Predictive Value of Tests

KW - Quality of Life

KW - Ubiquitin-Protein Ligases

U2 - 10.1017/S0033291713001554

DO - 10.1017/S0033291713001554

M3 - Journal article

C2 - 23809733

VL - 44

SP - 753

EP - 765

JO - Psychological Medicine

JF - Psychological Medicine

SN - 0033-2917

IS - 4

ER -