Trial reportNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2015
Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression.
Trial report in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 7 of them syntheses that pooled it.
What it found
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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
36 citing papers in PubMed, 7 syntheses or guidelines pooled it, 69 citations in OpenAlex.
- Gene expression signatures of response to fluoxetine treatment: systematic review and meta-analyses.Molecular psychiatry · 2025Pooled it
- Machine learning in the prediction of treatment response for emotional disorders: A systematic review and meta-analysis.Clinical psychology review · 2025Pooled it
- Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications.Psychological medicine · 2025Pooled it
- Transcriptomic Studies of Antidepressant Action in Rodent Models of Depression: A First Meta-Analysis.International journal of molecular sciences · 2022Pooled it
- Changes in RNA expression levels during antidepressant treatment: a systematic review.Journal of neural transmission (Vienna, Austria : 1996) · 2021Pooled it
- Pooled it
- Genetic Contributions of Inflammation to Depression.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2017Pooled it
- Machine learning for immune biomarkers in severe mental illness: a systematic review.Neuroscience applied · 2026Review
- Transcriptomics and psychotherapy: An integrative review.Brain, behavior, & immunity - health · 2024Review
- Investigation of Association Between Expression of DYX1C1, KIAA0319, and ROBO1 Genes and Specific Learning Disorder in Children and Adolescents.Journal of molecular neuroscience : MN · 2024Article
- The emergence, implementation, and future growth of pharmacogenomics in psychiatry: a narrative review.Psychological medicine · 2023Review
- Interferon signaling and hypercytokinemia-related gene expression in the blood of antidepressant non-responders.Heliyon · 2023Article
- An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response.Frontiers in psychiatry · 2023Article
- Genomic-Analysis-Oriented Drug Repurposing in the Search for Novel Antidepressants.Biomedicines · 2022Article
- Cellular and immunometabolic mechanisms of inflammation in depression: Preliminary findings from single cell RNA sequencing and a tribute to Bruce McEwen.Neurobiology of stress · 2022Article
- Whole blood transcriptional signatures associated with rapid antidepressant response to ketamine in patients with treatment resistant depression.Translational psychiatry · 2022Article
- Peripheral proteomic changes after electroconvulsive seizures in a rodent model of non-response to chronic fluoxetine.Frontiers in pharmacology · 2022Article
- Large-Scale Transcriptomics Studies Provide Insight Into Sex Differences in Depression.Biological psychiatry · 2022Review
- Transcriptomic signatures of psychomotor slowing in peripheral blood of depressed patients: evidence for immunometabolic reprogramming.Molecular psychiatry · 2021Article
- Genome wide analysis implicates upregulation of proteasome pathway in major depressive disorder.Translational psychiatry · 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 3 countries.
Funding
Abstract
Major depressive disorder (MDD) in general, and anxious-depression in particular, are characterized by poor rates of remission with first-line treatments, contributing to the chronic illness burden suffered by many patients. Prospective research is needed to identify the biomarkers predicting nonremission prior to treatment initiation. We collected blood samples from a discovery cohort of 34 adult MDD patients with co-occurring anxiety and 33 matched, nondepressed controls at baseline and after 12 weeks (of citalopram plus psychotherapy treatment for the depressed cohort). Samples were processed on gene arrays and group differences in gene expression were investigated. Exploratory analyses suggest that at pretreatment baseline, nonremitting patients differ from controls with gene function and transcription factor analyses potentially related to elevated inflammation and immune activation. In a second phase, we applied an unbiased machine learning prediction model and corrected for model-selection bias. Results show that baseline gene expression predicted nonremission with 79.4% corrected accuracy with a 13-gene model. The same gene-only model predicted nonremission after 8 weeks of citalopram treatment with 76% corrected accuracy in an independent validation cohort of 63 MDD patients treated with citalopram at another institution. Together, these results demonstrate the potential, but also the limitations, of baseline peripheral blood-based gene expression to predict nonremission after citalopram treatment. These results not only support their use in future prediction tools but also suggest that increased accuracy may be obtained with the inclusion of additional predictors (eg, genetics and clinical scales).
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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.