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DNA methylation in interleukin-11 predicts clinical response to antidepressants in GENDEP.

Powell, TR and Smith, RG and Hackinger, S and Schalkwyk, LC and Uher, R and McGuffin, P and Mill, J and Tansey, KE (2013) 'DNA methylation in interleukin-11 predicts clinical response to antidepressants in GENDEP.' Translational psychiatry, 3. ISSN 2158-3188

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Abstract

Transcriptional differences in interleukin-11 (IL11) after antidepressant treatment have been found to correspond to clinical response in major depressive disorder (MDD) patients. Expression differences were partly mediated by a single-nucleotide polymorphism (rs1126757), identified as a predictor of antidepressant response as part of a genome-wide association study. Here we attempt to identify whether DNA methylation, another baseline factor known to affect transcription factor binding, might also predict antidepressant response, using samples collected from the Genome-based Therapeutic Drugs for Depression project (GENDEP). DNA samples from 113 MDD individuals from the GENDEP project, who were treated with either escitalopram (n=80) or nortriptyline (n=33) for 12 weeks, were randomly selected. Percentage change in Montgomery-Åsberg Depression Rating Scale scores between baseline and week 12 were utilized as our measure of antidepressant response. The Sequenom EpiTYPER platform was used to assess DNA methylation across the only CpG island located in the IL11 gene. Regression analyses were then used to explore the relationship between CpG unit methylation and antidepressant response. We identified a CpG unit predictor of general antidepressant response, a drug by CpG unit interaction predictor of response, and a CpG unit by rs1126757 interaction predictor of antidepressant response. The current study is the first to investigate the potential utility of pharmaco-epigenetic biomarkers for the prediction of antidepressant response. Our results suggest that DNA methylation in IL11 might be useful in identifying those patients likely to respond to antidepressants, and if so, the best drug suited to each individual.

Item Type: Article
Subjects: Q Science > QH Natural history > QH426 Genetics
Divisions: Faculty of Science and Health > Biological Sciences, School of
Depositing User: Jim Jamieson
Date Deposited: 10 Nov 2014 14:32
Last Modified: 17 Aug 2017 17:46
URI: http://repository.essex.ac.uk/id/eprint/11092

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