Evidence map›Paper›PMID 37607340›Full record

ArticleSchizophrenia bulletin2024

Longitudinal MicroRNA Signature of Conversion to Psychosis.

Anton Iftimovici, Qin He, Chuan Jiao, Edouard Duchesnay, Marie-Odile Krebs, Oussama Kebir, Boris Chaumette

Open access · greenAbstract read
In one paragraph

Article in Schizophrenia bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
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

7 authors at 2 institutions in 2 countries.

Anton IftimoviciInstitute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Université de Paris, Paris, France.ORCID 0000-0003-4927-2798
Qin HeInstitute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Université de Paris, Paris, France.
Chuan JiaoInstitute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Université de Paris, Paris, France.
Edouard DuchesnayCEA Paris-Saclay, Joliot Institute, NeuroSpin, BAOBAB, Centre d'études de Saclay, Gif-sur-Yvette, France.
Marie-Odile KrebsInstitute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Université de Paris, Paris, France.
Oussama KebirInstitute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Université de Paris, Paris, France.
Boris ChaumetteInstitute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Université de Paris, Paris, France.ORCID 0000-0002-1313-2788
Inserm · FRCommissariat à l'Énergie Atomique et aux Énergies Alternatives · FR

Funding

ANR Epi-Young ANR-17-CE37-0003-01Fondation Bettencourt SchuellerFondation pour la Recherche Médicale FRM-FDM201806006059French Ministry PHRC AOM07-118
6 · The paper itself

Abstract

background and hypothesisThe emergence of psychosis in ultra-high-risk subjects (UHR) is influenced by gene-environment interactions that rely on epigenetic mechanisms such as microRNAs. However, whether they can be relevant pathophysiological biomarkers of psychosis' onset remains unknown. STUDY

designWe present a longitudinal study of microRNA expression, measured in plasma by high-throughput sequencing at baseline and follow-up, in a prospective cohort of 81 UHR, 35 of whom developed psychosis at follow-up (converters). We combined supervised machine learning and differential graph analysis to assess the relative weighted contribution of each microRNA variation to the difference in outcome and identify outcome-specific networks. We then applied univariate models to the resulting microRNA variations common to both strategies, to interpret them as a function of demographic and clinical covariates. STUDY

resultsWe identified 207 microRNA variations that significantly contributed to the classification. The differential network analysis found 276 network-specific correlations of microRNA variations. The combination of both strategies identified 25 microRNAs, whose gene targets were overrepresented in cognition and schizophrenia genome-wide association studies findings. Interpretable univariate models further supported the relevance of miR-150-5p and miR-3191-5p variations in psychosis onset, independent of age, sex, cannabis use, and medication.

conclusionsIn this first longitudinal study of microRNA variation during conversion to psychosis, we combined 2 methodologically independent data-driven strategies to identify a dynamic epigenetic signature of the emergence of psychosis that is pathophysiologically relevant.

Indexed as

MicroRNAsPsychotic DisordersGenome-Wide Association StudyHumansLongitudinal StudiesProspective StudiesMicroRNAs

Identifiers

PMID37607340
PMCPMC10919777
OpenAlexW4386055436

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.