Evidence map›Paper›PMID 42833865›Full record

ArticleBMJ mental health2026

EDIT-B consortium: an external pan-European validation of an innovative machine learning-based test for bipolar disorder diagnosis.

Dinah Weissmann, Nicolas Salvetat, Christopher Cayzac, Francisco Checa-Robles, Diana Vetter, Francisco Santos Schneider, Lara Walczer-Baldinazzo, Giovanna Ruggeri, Maurizio Ferrari, Andrea Miranda-Mendizabal and 10 more

Registry-linked trialAbstract readMulticenter StudyValidation Study
In one paragraph

Article in BMJ mental health, 2026. 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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

NCT05603819 completednot on this map

Clinical Validation Study for EDIT-B Test: an Aid for Differential Diagnosis of Bipolar Disorder, Based on RNA Editing Blood Biomarkers

TypeobservationalSponsorAlcediagRan2022 to 2024Enrolled418ConditionsBipolar Disorder, Major Depressive DisorderArmsEDIT-B
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Dinah WeissmannAlcediag/Sys2Diag UMR9005 (CNRS/Alcen), Montpellier, France.
Nicolas SalvetatAlcediag/Sys2Diag UMR9005 (CNRS/Alcen), Montpellier, France nicolas.salvetat@alcediag-alcen.com.ORCID http://orcid.org/0000-0002-0759-5129
Christopher CayzacAlcediag/Sys2Diag UMR9005 (CNRS/Alcen), Montpellier, France.
Francisco Checa-RoblesAlcediag/Sys2Diag UMR9005 (CNRS/Alcen), Montpellier, France.
Diana VetterAlcediag/Sys2Diag UMR9005 (CNRS/Alcen), Montpellier, France.
Francisco Santos SchneiderAlcediag/Sys2Diag UMR9005 (CNRS/Alcen), Montpellier, France.
Lara Walczer-BaldinazzoGenetic Unit, SYNLAB Italia Srl, Castenedolo, Italy.
Giovanna RuggeriGenetic Unit, SYNLAB Italia Srl, Castenedolo, Italy.
Maurizio FerrariIRCCS, SYNLAB SDN, Naples, Italy.
Andrea Miranda-MendizabalInstitut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.ORCID http://orcid.org/0000-0003-3649-7509
Victor ChavarriaParc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.
Oscar Soto-AngonaInstitut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.
Juan ZambranoUniversité Paris Cité, Paris, France.
Jeff ZarpCopenhagen Affective Disorder Research Center, Copenhagen, Denmark.ORCID http://orcid.org/0000-0002-3415-8098
Anna Gimenez-PalomoMental Health Networking Biomedical Research Centre (CIBERSAM), Madrid, Spain.
Marc ValentiMental Health Networking Biomedical Research Centre (CIBERSAM), Madrid, Spain.
Josep Maria HaroMental Health Networking Biomedical Research Centre (CIBERSAM), Madrid, Spain.ORCID http://orcid.org/0000-0002-3984-277X
Lars Vedel KessingCopenhagen Affective Disorder Research Center, Copenhagen, Denmark.
Chantal HenryUniversité Paris Cité, Paris, France.
Eduard VietaBipolar and Depressive Disorders Unit (IDIBAPS), Hospital Clinic de Barcelona, Barcelona, Spain.ORCID http://orcid.org/0000-0002-0548-0053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDifferentiating bipolar disorder (BD) from major depressive disorder (MDD) during major depressive episodes remains a significant challenge. EDIT-B is an in vitro diagnostic test based on machine learning (ML) method integrating clinical metadata with adenosine-to-inosine (A-to-I) RNA editing signatures in eight genes (

objectiveThe objective of this study is to assess and confirm the diagnostic performance of EDIT-B in a new, independent, double-blind, external, multicentre European cohort.

methodsWe evaluated EDIT-B results across four European centres (Spain, France, Denmark) compared with physician diagnoses. Explainability and sensitivity analyses were performed to identify the primary drivers of the model.

findingsIn 393 patients with current major depressive episode (238 MDD; 155 BD), EDIT-B demonstrated robust performance: area under the curve-receiver operating characteristic of 0.873 (95% CI 0.837 to 0.909), sensitivity of 82.6% (95% CI 75.7% to 88.2%) and specificity of 80.3% (95% CI 74.6% to 85.1%). Performances were consistent across sites and all stratified patient subgroups, corroborating previous results. Explainability analysis pointed to RNA editing biomarkers as the most important variables for EDIT-B diagnosis.

conclusionThis study confirms the diagnostic performances of EDIT-B showing that A-to-I RNA editing coupled with ML methods is a reliable approach to distinguish BD from MDD. CLINICAL IMPLICATIONS: EDIT-B represents an innovative, reliable and complementary diagnostic tool supporting psychiatric practice and enhancing clinical outcomes with potential impact in reducing diagnostic delays, tailoring the therapeutic strategy and improving therapeutic alliances. These findings may represent a significant advance towards precision psychiatry, with potential to reduce misdiagnosis and inappropriate treatment. TRIAL REGISTRATION NUMBER: NCT05603819.

Indexed as

Bipolar DisorderMachine LearningMajor Depressive DisorderAdultDenmarkDiagnosis, DifferentialDouble-Blind MethodEuropeFemaleHumansMaleMiddle AgedRNA EditingSensitivity and SpecificitySpainBipolar and Related DisordersDepressive DisorderMachine LearningMood DisordersPsychiatry

Identifiers

PMID42833865
PMCPMC13646935

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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.