ArticleTranslational psychiatry2022
A game changer for bipolar disorder diagnosis using RNA editing-based biomarkers.
Article in Translational psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05603819 (Clinical Validation Study for EDIT-B Test), which is not on this map. Cited by 18 papers.
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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.
Clinical Validation Study for EDIT-B Test: an Aid for Differential Diagnosis of Bipolar Disorder, Based on RNA Editing Blood Biomarkers
Who cites it
18 citing papers in PubMed.
- EDIT-B consortium: an external pan-European validation of an innovative machine learning-based test for bipolar disorder diagnosis.BMJ mental health · 2026Article
- Special Issue "Translating Molecular Psychiatry: From Biomarkers to Personalized Therapies".International journal of molecular sciences · 2025Article
- Biomarkers of bipolar disorder in omics and neuroimaging.Journal of pharmaceutical analysis · 2025Review
- Comprehensive characterization of the RNA editing landscape in the human aging brains with Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- RNA editing-based biomarker blood test for the diagnosis of bipolar disorder: protocol of the EDIT-B study.Annals of general psychiatry · 2025Article
- Differentiation between bipolar disorder and major depressive disorder based on AMPA receptor distribution.Frontiers in neural circuits · 2025Article
- A Wonderful Journey: The Diverse Roles of Adenosine Deaminase Action on RNA 1 (ADAR1) in Central Nervous System Diseases.CNS neuroscience & therapeutics · 2025Review
- Bipolar disorders: an update on critical aspects.The Lancet regional health. Europe · 2025Review
- RNA Editing Signatures Powered by Artificial Intelligence: A New Frontier in Differentiating Schizophrenia, Bipolar, and Schizoaffective Disorders.International journal of molecular sciences · 2024Article
- RNA modifications: emerging players in the regulation of reproduction and development.Acta biochimica et biophysica Sinica · 2024Review
- Article
- Review
- Mental Health in Healthcare Workers Post-COVID-19: A Latin American Review and Insights into Personalized Management Strategies.Journal of personalized medicine · 2024Review
- Recommendations for detection, validation, and evaluation of RNA editing events in cardiovascular and neurological/neurodegenerative diseases.Molecular therapy. Nucleic acids · 2024Review
- RNA modifications in physiology and disease: towards clinical applications.Nature reviews. Genetics · 2024Review
- Advances in brain epitranscriptomics research and translational opportunities.Molecular psychiatry · 2024Review
- Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review.Briefings in bioinformatics · 2024Review
- RNA modifications in cardiovascular health and disease.Nature reviews. Cardiology · 2023Review
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In clinical practice, differentiating Bipolar Disorder (BD) from unipolar depression is a challenge due to the depressive symptoms, which are the core presentations of both disorders. This misdiagnosis during depressive episodes results in a delay in proper treatment and a poor management of their condition. In a first step, using A-to-I RNA editome analysis, we discovered 646 variants (366 genes) differentially edited between depressed patients and healthy volunteers in a discovery cohort of 57 participants. After using stringent criteria and biological pathway analysis, candidate biomarkers from 8 genes were singled out and tested in a validation cohort of 410 participants. Combining the selected biomarkers with a machine learning approach achieved to discriminate depressed patients (n = 267) versus controls (n = 143) with an AUC of 0.930 (CI 95% [0.879-0.982]), a sensitivity of 84.0% and a specificity of 87.1%. In a second step by selecting among the depressed patients those with unipolar depression (n = 160) or BD (n = 95), we identified a combination of 6 biomarkers which allowed a differential diagnosis of bipolar disorder with an AUC of 0.935 and high specificity (Sp = 84.6%) and sensitivity (Se = 90.9%). The association of RNA editing variants modifications with depression subtypes and the use of artificial intelligence allowed developing a new tool to identify, among depressed patients, those suffering from BD. This test will help to reduce the misdiagnosis delay of bipolar patients, leading to an earlier implementation of a proper treatment.
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