Evidence map›Paper›PMID 22549745›Full record

ArticleMolecular neurobiology2012

Integration of MicroRNA databases to study MicroRNAs associated with multiple sclerosis.

Charlotte Angerstein, Michael Hecker, Brigitte Katrin Paap, Dirk Koczan, Madhan Thamilarasan, Hans-Jürgen Thiesen, Uwe Klaus Zettl

Abstract read
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In one paragraph

Article in Molecular neurobiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

31 citing papers in PubMed, 54 citations in OpenAlex.

  1. Review
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  7. Observational
  8. Review
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  12. miR-142-3p Is a Key Regulator of IL-1β-Dependent Synaptopathy in Neuroinflammation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2017
    Article
  13. Biomarkers of multiple sclerosis: current findings.Degenerative neurological and neuromuscular disease · 2017
    Review
  14. Article
  15. Comprehensive evaluation of serum microRNAs as biomarkers in multiple sclerosis.Neurology(R) neuroimmunology & neuroinflammation · 2016
    Article
  16. Article
  17. Article
  18. Article
  19. MicroRNAs in neuronal communication.Molecular neurobiology · 2014
    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

7 authors at 1 institution in 1 country.

Charlotte AngersteinDepartment of Neurology, Division of Neuroimmunology, University of Rostock, Gehlsheimer Str. 20, 18147, Rostock, Germany.
Michael Hecker
Brigitte Katrin Paap
Dirk Koczan
Madhan Thamilarasan
Hans-Jürgen Thiesen
Uwe Klaus Zettl
University of Rostock · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs which regulate many genes post-transcriptionally. In various contexts of medical science, miRNAs gained increasing attention over the last few years. Analyzing the functions, interactions and cellular effects of miRNAs is a very complex and challenging task. Many miRNA databases with diverse data contents have been developed. Here, we demonstrate how to integrate their information in a reasonable way on a set of miRNAs that were found to be dysregulated in the blood of patients with multiple sclerosis (MS). Using the miR2Disease database, we retrieved 16 miRNAs associated with MS according to four different studies. We studied the predicted and experimentally validated target genes of these miRNAs, their expression profiles in different blood cell types and brain tissues, the pathways and biological processes affected by these miRNAs as well as their regulation by transcription factors. Only miRNA-mRNA interactions that were predicted by at least seven different prediction algorithms were considered. This resulted in a network of 1,498 target genes. In this network, the MS-associated miRNAs hsa-miR-20a-5p and hsa-miR-20b-5p occurred as central hubs regulating about 500 genes each. Strikingly, many of the putative target genes play a role in T cell activation and signaling, and many have transcription factor activity. The latter suggests that miRNAs often act as regulators of regulators with many secondary effects on gene expression. Our present work provides a guideline on how information of different databases can be integrated in the analysis of miRNAs. Future investigations of miRNAs shall help to better understand the mechanisms underlying different diseases and their treatments.

Indexed as

Databases, GeneticBase SequenceGene Expression RegulationGene Regulatory NetworksHumansMicroRNAsMolecular Sequence DataMultiple SclerosisReproducibility of ResultsMicroRNAs

Identifiers

PMID22549745
OpenAlexW1968791377

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.