Evidence map›Paper›PMID 30223713›Full record

ArticleRNA biology2018

Evaluation of methodologies for microRNA biomarker detection by next generation sequencing.

Anna M L Coenen-Stass, Iddo Magen, Tony Brooks, Iddo Z Ben-Dov, Linda Greensmith, Eran Hornstein, Pietro Fratta

Abstract readEvaluation Study
In one paragraph

Article in RNA biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 1 pooled it
–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

64 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. IsomiR Utility in Amyotrophic Lateral Sclerosis Prognostication.medRxiv : the preprint server for health sciences · 2025
    Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Identification of Oncogene-Induced Senescence-Associated MicroRNAs.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

4 more citing papers are in PubMed but not listed here.

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.

Anna M L Coenen-Stassa Sobell Department of Neuromuscular Diseases , UCL Institute of Neurology , London , UK.ORCID 0000-0001-6949-0747
Iddo Magenb Department of Molecular Genetics , Weizmann Institute of Science , Rehovot , Israel.ORCID 0000-0002-9180-3604
Tony Brooksc UCL Genomics , Institute of Child Health , London , UK.
Iddo Z Ben-Dovd Laboratory of Medical Transcriptomics, Department of Nephrology , Hadassah - Hebrew University Medical Center , Jerusalem , Israel.ORCID 0000-0002-9180-3604
Linda Greensmitha Sobell Department of Neuromuscular Diseases , UCL Institute of Neurology , London , UK.
Eran Hornsteinb Department of Molecular Genetics , Weizmann Institute of Science , Rehovot , Israel.
Pietro Frattaa Sobell Department of Neuromuscular Diseases , UCL Institute of Neurology , London , UK.

Funding

Medical Research Council MR/M008606/1Motor Neurone Disease Association FRATTA/JAN15/946-795Motor Neurone Disease Association GREENSMITH/APR15/839-791
6 · The paper itself

Abstract

In recent years, microRNAs (miRNAs) in tissues and biofluids have emerged as a new class of promising biomarkers for numerous diseases. Blood-based biomarkers are particularly desirable since serum or plasma is easily accessible and can be sampled repeatedly. To comprehensively explore the biomarker potential of miRNAs, sensitive, accurate and cost-efficient miRNA profiling techniques are required. Next generation sequencing (NGS) is emerging as the preferred method for miRNA profiling; offering high sensitivity, single-nucleotide resolution and the possibility to profile a considerable number of samples in parallel. Despite the excitement about miRNA biomarkers, challenges associated with insufficient characterization of the sequencing library preparation efficacy, precision and method-related quantification bias have not been addressed in detail and are generally underappreciated in the wider research community. Here, we have tested in parallel four commercially available small RNA sequencing kits against a cohort of samples comprised of human plasma, human serum, murine brain tissue and a reference library containing ~ 950 synthetic miRNAs. We discuss the advantages and limits of these methodologies for massive parallel microRNAs profiling. This work can serve as guideline for choosing an adequate library preparation method, based on sensitivity, specificity and accuracy of miRNA quantification, workflow convenience and potential for automation.

Indexed as

Gene Expression ProfilingGenomeAnimalsBiomarkersBrainGene LibraryHealthy VolunteersHigh-Throughput Nucleotide SequencingHumansMiceMicroRNAsBiomarkersMicroRNAsbiomarkermicroRNAnext-generation-sequencingsequencing library preparationsmall RNA sequencing

Identifiers

PMID30223713
PMCPMC6161688

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.