Evidence map›Paper›PMID 31089747›Full record

ReviewCellular and molecular life sciences : CMLS2019

MicroRNA expression studies: challenge of selecting reliable reference controls for data normalization.

Soheil Madadi, Heidi Schwarzenbach, Johan Lorenzen, Meysam Soleimani

Open access · greenAbstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.5field-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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Urinary miRNA Analysis for Clear Cell Renal Cell Carcinoma:International journal of molecular sciences · 2026
    Article
  6. Evaluating Genetic Regulators of MicroRNAs Using Machine Learning Models.International journal of molecular sciences · 2025
    Article
  7. Article
  8. Article
  9. Serum MicroRNAs Predict Isolated Rapid Eye Movement Sleep Behavior Disorder and Lewy Body Diseases.Movement disorders : official journal of the Movement Disorder Society · 2022
    Article
  10. Review
  11. Article
  12. Review
  13. Review
  14. Targets and regulation of microRNA-652-3p in homoeostasis and disease.Journal of molecular medicine (Berlin, Germany) · 2021
    Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

4 authors at 3 institutions in 3 countries.

Soheil MadadiDepartment of Pharmaceutical Biotechnology, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan, Iran.
Heidi SchwarzenbachDepartment of Tumor Biology, University Medical Center Hamburg-Eppendorf, 20246, Hamburg, Germany.
Johan LorenzenDepartment of Nephrology, University Hospital Zürich, Zurich, Switzerland.
Meysam SoleimaniDepartment of Pharmaceutical Biotechnology, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan, Iran. m.soleymani@umsha.ac.ir.
Hamedan University of Medical Sciences · IRUniversität Hamburg · DEUniversity Hospital of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate determination of microRNA expression levels is a prerequisite in using these small non-coding RNA molecules as novel biomarkers in disease diagnosis and prognosis. Quantitative PCR is the method of choice for measuring the expression levels of microRNAs. However, a major obstacle that affects the reliability of results is the lack of validated reference controls for data normalization. Various non-coding RNAs have previously been used as reference controls, but their use may lead to variations and lack of comparability of microRNA data among the studies. Despite the growing number of studies investigating microRNA profiles to discriminate between healthy and disease stages, robust reference controls for data normalization have so far not been established. In the present article, we provide an overview of different reference controls used in various diseases, and highlight the urgent need for the identification of suitable reference controls to produce reliable data. Our analysis shows, among others, that RNU6 is not an ideal normalizer in studies using patient material from different diseases. Finally, our article tries to disclose the challenges to find a reference control which is uniformly and stably expressed across all body tissues, fluids, and diseases.

Indexed as

BiomarkersCardiovascular DiseasesCentral Nervous System DiseasesHepatitis BHumansMicroRNAsNeoplasmsPrognosisRNA, Small NuclearTuberculosisBiomarkersMicroRNAsRNA, Small NuclearBenign and malignant diseasesMicroRNA normalizationPlasmaReference controlsSerumTissue

Identifiers

PMID31089747
PMCPMC11105490
OpenAlexW2945561923

What OpenQuestion holds

Textmetadata
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.