Evidence map›Paper›PMID 27694855›Full record

ArticleScientific reports2016

Analysis of microRNA and Gene Expression Profiles in Multiple Sclerosis: Integrating Interaction Data to Uncover Regulatory Mechanisms.

Sherry Freiesleben, Michael Hecker, Uwe Klaus Zettl, Georg Fuellen, Leila Taher

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
4.2field-weighted citation impact, top 5% 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

36 citing papers in PubMed, 67 citations in OpenAlex.

  1. Review
  2. Review
  3. Iranian journal of medical sciences · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Gene network revealsFrontiers in neurology · 2023
    Article
  10. Article
  11. Article
  12. Multiple sclerosis is linked to MAPKJournal of molecular medicine (Berlin, Germany) · 2021
    Review
  13. MicroRNAs, Multiple Sclerosis, and Depression.International journal of molecular sciences · 2021
    Review
  14. Article
  15. Observational
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

5 authors at 2 institutions in 1 country.

Sherry FreieslebenDepartment of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany.
Michael HeckerDepartment of Neurology, Division of Neuroimmunology, University of Rostock, Rostock, Germany.
Uwe Klaus ZettlDepartment of Neurology, Division of Neuroimmunology, University of Rostock, Rostock, Germany.
Georg FuellenInstitute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany.
Leila TaherInstitute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany.
University of Rostock · DEFriedrich-Alexander-Universität Erlangen-Nürnberg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) have been reported to contribute to the pathophysiology of multiple sclerosis (MS), an inflammatory disorder of the central nervous system. Here, we propose a new consensus-based strategy to analyse and integrate miRNA and gene expression data in MS as well as other publically available data to gain a deeper understanding of the role of miRNAs in MS and to overcome the challenges posed by studies with limited patient sample sizes. We processed and analysed microarray datasets, and compared the expression of genes and miRNAs in the blood of MS patients and controls. We then used our consensus and integration approach to construct two molecular networks dysregulated in MS: a miRNA- and a gene-based network. We identified 18 differentially expressed (DE) miRNAs and 128 DE genes that may contribute to the regulatory alterations behind MS. The miRNAs were linked to immunological and neurological pathways, and we exposed let-7b-5p and miR-345-5p as promising blood-derived disease biomarkers in MS. The results suggest that DE miRNAs are more informative than DE genes in uncovering pathways potentially involved in MS. Our findings provide novel insights into the regulatory mechanisms and networks underlying MS.

Indexed as

Databases, Nucleic AcidGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksBiomarkersFemaleHumansMaleMicroRNAsMultiple SclerosisBiomarkersMicroRNAsMIRN345 microRNA, humanmirnlet7 microRNA, human

Identifiers

PMID27694855
PMCPMC5046091
OpenAlexW2528944866

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.