Evidence map›Paper›PMID 41257806›Full record

ArticleTranslational psychiatry2025

Metabolomic biomarkers of psychotic conversion in ultra-high-risk subjects: a pilot study.

Maria Teresa Avella, Gildas Bertho, Nicolas Giraud, Oussama Kébir, Cédric Caradeuc, Javier Labad, Sergi Papiol, Thomas G Schulze, Marie-Odile Krebs, Boris Chaumette and 1 more

Abstract read
In one paragraph

Article in Translational psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

11 authors.

Maria Teresa AvellaInstitute of Psychiatry and Neurosciences of Paris, INSERM UMR 1266, Pathophysiology of Psychiatric Diseases, Université Paris Cité, Paris, France.
Gildas BerthoLaboratoire de Chimie et Biochimie Pharmacologiques et Toxicologiques, UMR 8601 CNRS, Université Paris Cité, Paris, France. gildas.bertho@u-paris.fr.
Nicolas GiraudLaboratoire de Chimie et Biochimie Pharmacologiques et Toxicologiques, UMR 8601 CNRS, Université Paris Cité, Paris, France.ORCID http://orcid.org/0000-0003-2322-339X
Oussama KébirInstitute of Psychiatry and Neurosciences of Paris, INSERM UMR 1266, Pathophysiology of Psychiatric Diseases, Université Paris Cité, Paris, France.
Cédric CaradeucLaboratoire de Chimie et Biochimie Pharmacologiques et Toxicologiques, UMR 8601 CNRS, Université Paris Cité, Paris, France.
Javier LabadDepartment of Mental Health and Addictions, Consorci Sanitari del Maresme, Mataro, Spain.ORCID http://orcid.org/0000-0003-2214-1886
Sergi PapiolInstitute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, BY, Germany.ORCID http://orcid.org/0000-0001-9366-8728
Thomas G SchulzeInstitute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, BY, Germany.ORCID http://orcid.org/0000-0001-6624-2975
Marie-Odile Krebs *Institute of Psychiatry and Neurosciences of Paris, INSERM UMR 1266, Pathophysiology of Psychiatric Diseases, Université Paris Cité, Paris, France. marie-odile.krebs@inserm.fr.ORCID http://orcid.org/0000-0002-4715-9890
Boris Chaumette *Institute of Psychiatry and Neurosciences of Paris, INSERM UMR 1266, Pathophysiology of Psychiatric Diseases, Université Paris Cité, Paris, France.ORCID http://orcid.org/0000-0002-1313-2788
Ariel FrajermanInstitute of Psychiatry and Neurosciences of Paris, INSERM UMR 1266, Pathophysiology of Psychiatric Diseases, Université Paris Cité, Paris, France. ariel.frajerman@inserm.fr.ORCID http://orcid.org/0000-0002-4441-3873

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-17-CE37-003-01EPI youngAgence Nationale de la Recherche (French National Research Agency) ANR-18-RHUS-0014Fondation Bettencourt Schueller (Bettencourt Schueller Foundation) CCA Inserm
6 · The paper itself

Abstract

Psychosis is a psychiatric condition that can become a chronic and severe psychiatric disorder affecting more than 1% of the population. The ultra-high risk (UHR) patients have a transition rate to psychosis of 25% after three years. We aimed to identify circulating metabolomic biomarkers for psychotic conversion in UHR patients using nuclear magnetic resonance (NMR) spectroscopy. We used samples from 35 UHR patients: 14 converters (UHR-C) and 21 non-converters (UHR-NC) at inclusion from the ICAAR cohort. Serum samples were analysed using the high-throughput screening IVDr NMR method. R and SIMCA were used for statistical analysis. Several lipoprotein parameters related to HDL and LDL metabolism were downregulated in UHR-C compared to UHR-NC at the time of inclusion. The 3 best lipoproteins to predict psychotic conversion at baseline were H4A1, H4FC, and L4FC (Area under the Curve (AUC) values were 0.81, 0.81, and 0.78, respectively). These lipoproteins were also negatively correlated with PANSS scores. Our study is the first to use NMR technology to identify biomarkers to predict the risk of psychotic transition in UHR subjects. This pilot study found lipoprotein parameters related to ApoA-1 and HDL-cholesterol (subclass 4) as potential biomarkers. These results need to be replicated on a larger sample. This study highlights the importance of the detailed analysis of circulant lipoproteins related to the brain using NMR technology in early psychosis to identify biomarkers of psychotic transitions and perhaps to better understand the physiopathology of psychosis.

Indexed as

LipoproteinsMetabolomicsPsychotic DisordersAdolescentAdultBiomarkersFemaleHigh-Throughput Screening AssaysHumansMagnetic Resonance ImagingMalePilot ProjectsRiskYoung AdultBiomarkersLipoproteins

Identifiers

PMID41257806
PMCPMC12644573

What OpenQuestion holds

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Registered trials

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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.