Evidence map›Paper›PMID 39815348›Full record

ArticleOrphanet journal of rare diseases2025

Multi-omics analysis in inclusion body myositis identifies mir-16 responsible for HLA overexpression.

Daphne Wijnbergen, Mridul Johari, Ozan Ozisik, Peter A C 't Hoen, Friederike Ehrhart, Anaïs Baudot, Chris T Evelo, Bjarne Udd, Marco Roos, Eleni Mina

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In one paragraph

Article in Orphanet journal of rare diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

10 authors.

Daphne Wijnbergen *Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands. D.Wijnbergen@lumc.nl.ORCID http://orcid.org/0000-0002-7449-6657
Mridul Johari *Harry Perkins Institute of Medical Research, Centre for Medical Research, University of Western Australia, Nedlands, WA, Australia.
Ozan OzisikUniversité Paris Cité, INSERM U976, Paris, France.
Peter A C 't HoenDepartment of Medical BioSciences, Radboud university medical center, Nijmegen, The Netherlands.
Friederike EhrhartDepartment of Bioinformatics - BiGCaT, NUTRIM/MHeNs, Maastricht University, Maastricht, The Netherlands.
Anaïs BaudotAix Marseille University, INSERM, MMG, Marseille, France.
Chris T EveloDepartment of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands.
Bjarne UddFolkhälsen Research Center, Helsinki, Finland.
Marco RoosDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Eleni MinaDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.

Funding

AFM-Téléthon 24438Biomedicum Helsinki-säätiö Biomedicum Helsinki-säätiöH2020 Health 825575Helsingin Yliopiston Tiedesäätiö Helsingin Yliopiston TiedesäätiöPäivikki ja Sakari Sohlbergin Säätiö Päivikki ja Sakari Sohlbergin Säätiö
6 · The paper itself

Abstract

backgroundInclusion Body Myositis is an acquired muscle disease. Its pathogenesis is unclear due to the co-existence of inflammation, muscle degeneration and mitochondrial dysfunction. We aimed to provide a more advanced understanding of the disease by combining multi-omics analysis with prior knowledge. We applied molecular subnetwork identification to find highly interconnected subnetworks with a high degree of change in Inclusion Body Myositis. These could be used as hypotheses for potential pathomechanisms and biomarkers that are implicated in this disease.

resultsOur multi-omics analysis resulted in five subnetworks that exhibit changes in multiple omics layers. These subnetworks are related to antigen processing and presentation, chemokine-mediated signaling, immune response-signal transduction, rRNA processing, and mRNA splicing. An interesting finding is that the antigen processing and presentation subnetwork links the underexpressed miR-16-5p to overexpressed HLA genes by negative expression correlation. In addition, the rRNA processing subnetwork contains the RPS18 gene, which is not differentially expressed, but has significant variant association. The RPS18 gene could potentially play a role in the underexpression of the genes involved in 18 S ribosomal RNA processing, which it is highly connected to.

conclusionsOur analysis highlights the importance of interrogating multiple omics to enhance knowledge discovery in rare diseases. We report five subnetworks that can provide additional insights into the molecular pathogenesis of Inclusion Body Myositis. Our analytical workflow can be reused as a method to study disease mechanisms involved in other diseases when multiple omics datasets are available.

Indexed as

HLA AntigensMicroRNAsMyositis, Inclusion BodyHumansMultiomicsHLA AntigensMicroRNAsMIRN16 microRNA, humanActive subnetwork identificationData integrationGenomicsInclusion body myositisMulti-omicsMultiplex networkNetwork analysisRare diseasesTranscriptomics

Identifiers

PMID39815348
PMCPMC11737257

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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.