Evidence map›Paper›PMID 24586876›Full record

ArticlePloS one2014

A critical evaluation of microRNA biomarkers in non-neoplastic disease.

Baqer A Haider, Alexander S Baras, Matthew N McCall, Joshua A Hertel, Toby C Cornish, Marc K Halushka

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing papers in PubMed
8.9field-weighted citation impact, top 1% 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

86 citing papers in PubMed, 153 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

26 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

6 authors at 3 institutions in 1 country.

Baqer A HaiderDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore Maryland, United States of America.
Alexander S BarasDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore Maryland, United States of America.
Matthew N McCallDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, New York, United States of America.
Joshua A HertelDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore Maryland, United States of America.
Toby C CornishDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore Maryland, United States of America.
Marc K HalushkaDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore Maryland, United States of America.
Johns Hopkins University · USJohns Hopkins Medicine · USUniversity of Rochester · US

Funding

CANCER RESEARCH TRAINING-EXPERIMENTAL THERAPY MODELST32CA009363 · NCI · UNIVERSITY OF ROCHESTER · PI LAND, HARTMUT · 1985 to 2013
$2.9M
NCI NIH HHS T32 CA009363
6 · The paper itself

Abstract

backgroundMicroRNAs (miRNAs) are small (∼22-nt), stable RNAs that critically modulate post-transcriptional gene regulation. MicroRNAs can be found in the blood as components of serum, plasma and peripheral blood mononuclear cells (PBMCs). Many microRNAs have been reported to be specific biomarkers in a variety of non-neoplastic diseases. To date, no one has globally evaluated these proposed clinical biomarkers for general quality or disease specificity. We hypothesized that the cellular source of circulating microRNAs should correlate with cells involved in specific non-neoplastic disease processes. Appropriate cell expression data would inform on the quality and usefulness of each microRNA as a biomarker for specific diseases. We further hypothesized a useful clinical microRNA biomarker would have specificity to a single disease. METHODS AND

findingsWe identified 416 microRNA biomarkers, of which 192 were unique, in 104 publications covering 57 diseases. One hundred and thirty-nine microRNAs (33%) represented biologically plausible biomarkers, corresponding to non-ubiquitous microRNAs expressed in disease-appropriate cell types. However, at a global level, many of these microRNAs were reported as "specific" biomarkers for two or more unrelated diseases with 6 microRNAs (miR-21, miR-16, miR-146a, miR-155, miR-126 and miR-223) being reported as biomarkers for 9 or more distinct diseases. Other biomarkers corresponded to common patterns of cellular injury, such as the liver-specific microRNA, miR-122, which was elevated in a disparate set of diseases that injure the liver primarily or secondarily including hepatitis B, hepatitis C, sepsis, and myocardial infarction.

conclusionsOnly a subset of reported blood-based microRNA biomarkers have specificity for a particular disease. The remainder of the reported non-neoplastic biomarkers are either biologically implausible, non-specific, or uninterpretable due to limitations of our current understanding of microRNA expression.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticAutoimmune DiseasesBiomarkersCardiovascular DiseasesHumansLeukocytes, MononuclearLiver DiseasesLung DiseasesMicroRNAsPrognosisBiomarkersMicroRNAs

Identifiers

PMID24586876
PMCPMC3935874
OpenAlexW1983085353

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.