Trial reportTranslational psychiatry2013
DNA methylation in interleukin-11 predicts clinical response to antidepressants in GENDEP.
Trial report in Translational psychiatry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed, 4 syntheses or guidelines pooled it, 93 citations in OpenAlex.
- Pooled it
- The Relationship between DNA Methylation and Antidepressant Medications: A Systematic Review.International journal of molecular sciences · 2020Pooled it
- DNA Methylation as a Biomarker of Treatment Response Variability in Serious Mental Illnesses: A Systematic Review Focused on Bipolar Disorder, Schizophrenia, and Major Depressive Disorder.International journal of molecular sciences · 2018Pooled it
- Pooled it
- DNA methylation is associated with inhaled corticosteroid response in persistent childhood asthmatics.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2019Trial
- Association of DNA methylation in BDNF with escitalopram treatment response in depressed Chinese Han patients.European journal of clinical pharmacology · 2018Trial
- Mechanism of N6-Methyladenosine Modification in the Pathogenesis of Depression.Molecular neurobiology · 2025Review
- Optimizing and Predicting Antidepressant Efficacy in Patients with Major Depressive Disorder Using Multi-Omics Analysis and the Opade AI Prediction Tools.Brain sciences · 2024Article
- Pharmacogenetics in IBS: update and impact of GWAS studies in drug targets and metabolism.Expert opinion on drug metabolism & toxicology · 2024Review
- Biomarker-Guided Tailored Therapy in Major Depression.Advances in experimental medicine and biology · 2024Review
- Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential.Signal transduction and targeted therapy · 2023Review
- The Role of Pharmacogenetics in Personalizing the Antidepressant and Anxiolytic Therapy.Genes · 2023Review
- Review
- An optimized procedure for preparation of conditioned medium from Wharton's jelly mesenchymal stromal cells isolated from umbilical cord.Frontiers in molecular biosciences · 2023Article
- Promises and challenges in pharmacoepigenetics.Cambridge prisms. Precision medicine · 2023Review
- DNA Methylation in Depression and Depressive-Like Phenotype: Biomarker or Target of Pharmacological Intervention?Current neuropharmacology · 2022Review
- Gut Hormones as Potential Therapeutic Targets or Biomarkers of Response in Depression: The Case of Motilin.Life (Basel, Switzerland) · 2021Review
- The Importance of Epigenetics in Diagnostics and Treatment of Major Depressive Disorder.Journal of personalized medicine · 2021Review
- Drug Response-Related DNA Methylation Changes in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder.Frontiers in neuroscience · 2021Review
- DNA Methylation of Fluoxetine Response in Child and Adolescence: Preliminary Results.Pharmacogenomics and personalized medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.