Evidence map›Paper›PMID 36352383›Full record

Trial reportBMC medicine2022

Clinical improvement of DM1 patients reflected by reversal of disease-induced gene expression in blood.

Remco T P van Cruchten, Daniël van As, Jeffrey C Glennon, Baziel G M van Engelen, Peter A C 't Hoen, OPTIMISTIC consortium, ReCognitION consortium

Open access · goldAbstract readClinical Trial
In one paragraph

Trial report in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 42% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Myotonic dystrophy family registry. The patient experience.Journal of neuromuscular diseases · 2026
    Article
  2. Review
  3. Observational
  4. 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

7 authors at 7 institutions in 5 countries.

Remco T P van Cruchten *Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Daniël van As *Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Jeffrey C GlennonConway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Dublin, Ireland.
Baziel G M van Engelen *Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.
Peter A C 't Hoen *Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands. Peter-Bram.tHoen@radboudumc.nl.ORCID 0000-0003-4450-3112
OPTIMISTIC consortium
ReCognitION consortium
Radboud University Nijmegen · NLUniversity College Dublin · IEInserm · FRInstitut des Cellules Souches pour le Traitement et l'Étude des Maladies Monogéniques · FRNewcastle University · GBUniversity of Glasgow · GBVlaams Instituut voor Biotechnologie · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMyotonic dystrophy type 1 (DM1) is an incurable multisystem disease caused by a CTG-repeat expansion in the DM1 protein kinase (DMPK) gene. The OPTIMISTIC clinical trial demonstrated positive and heterogenous effects of cognitive behavioral therapy (CBT) on the capacity for activity and social participations in DM1 patients. Through a process of reverse engineering, this study aims to identify druggable molecular biomarkers associated with the clinical improvement in the OPTIMISTIC cohort.

methodsBased on full blood samples collected during OPTIMISTIC, we performed paired mRNA sequencing for 27 patients before and after the CBT intervention. Linear mixed effect models were used to identify biomarkers associated with the disease-causing CTG expansion and the mean clinical improvement across all clinical outcome measures.

resultsWe identified 608 genes for which their expression was significantly associated with the CTG-repeat expansion, as well as 1176 genes significantly associated with the average clinical response towards the intervention. Remarkably, all 97 genes associated with both returned to more normal levels in patients who benefited the most from CBT. This main finding has been replicated based on an external dataset of mRNA data of DM1 patients and controls, singling these genes out as candidate biomarkers for therapy response. Among these candidate genes were DNAJB12, HDAC5, and TRIM8, each belonging to a protein family that is being studied in the context of neurological disorders or muscular dystrophies. Across the different gene sets, gene pathway enrichment analysis revealed disease-relevant impaired signaling in, among others, insulin-, metabolism-, and immune-related pathways. Furthermore, evidence for shared dysregulations with another neuromuscular disease, Duchenne muscular dystrophy, was found, suggesting a partial overlap in blood-based gene dysregulation.

conclusionsDM1-relevant disease signatures can be identified on a molecular level in peripheral blood, opening new avenues for drug discovery and therapy efficacy assessments.

Indexed as

Myotonic DystrophyCarrier ProteinsGene ExpressionHSP40 Heat-Shock ProteinsHumansNerve Tissue ProteinsRNA, MessengerTrinucleotide Repeat ExpansionCarrier ProteinsDNAJB12 protein, humanHSP40 Heat-Shock ProteinsNerve Tissue ProteinsRNA, MessengerTRIM8 protein, humanBiomarkerLifestyle interventionMyotonic dystrophy type 1Peripheral bloodRNA-seqTherapeutic Response

Identifiers

PMID36352383
PMCPMC9646470
OpenAlexW4308730842

What OpenQuestion holds

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LicenceCC BY
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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.