Evidence map›Paper›PMID 27357636›Full record

SynthesisCardiovascular research2016

Identifying circulating microRNAs as biomarkers of cardiovascular disease: a systematic review.

Rokas Navickas, Diane Gal, Aleksandras Laucevičius, Agnė Taparauskaitė, Monika Zdanytė, Paul Holvoet

2 registry-linked trialsOpen access · hybridAbstract readSystematic Review
In one paragraph

Synthesis in Cardiovascular research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 180 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
180citing papers in PubMed, 5 pooled it
15.7field-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.

NCT03832153 withdrawnnot on this mapstarted 2019, after this paper: background citation

Pan-Cardio-Genetics Clot Assessment in Acute Coronary Syndromes

TypeobservationalSponsorAristotle University Of ThessalonikiRan2019 to 2022Enrolled0ConditionsSTEMI - ST Elevation Myocardial Infarction, Thrombi, MicroRNAArmsthrombus aspiration
NCT05726695 unknown statusnot on this mapstarted 2018, after this paper: background citation

The Use of miRNA Detection for Diagnostics of Cardiovascular Diseases

TypeobservationalSponsorUniversity Hospital OstravaRan2018 to 2023Enrolled200ConditionsHeart Failure, Heart Dilation, Left Ventricular HypertrophyArmsmicroRNA test, Heart ultrasound examination
3 · Its place in the literature

Who cites it

180 citing papers in PubMed, 5 syntheses or guidelines pooled it, 332 citations in OpenAlex.

  1. Pooled it
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  20. Evaluating Genetic Regulators of MicroRNAs Using Machine Learning Models.International journal of molecular sciences · 2025
    Article

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 3 countries.

Rokas NavickasFaculty of Medicine, Vilnius University, Vilnius, Lithuania Vilnius University Hospital Santariškių Klinikos, Vilnius, Lithuania.
Diane GalDepartment of Cardiovascular Sciences, Atherosclerosis and Metabolism Unit, KU Leuven, Leuven, Belgium.
Aleksandras LaucevičiusFaculty of Medicine, Vilnius University, Vilnius, Lithuania Vilnius University Hospital Santariškių Klinikos, Vilnius, Lithuania.
Agnė TaparauskaitėFaculty of Medicine, Vilnius University, Vilnius, Lithuania.
Monika ZdanytėUniversitäts Klinikum Tübingen, Tübingen, Germany.
Paul HolvoetDepartment of Cardiovascular Sciences, Atherosclerosis and Metabolism Unit, KU Leuven, Leuven, Belgium paul.holvoet@med.kuleuven.be.
Vilnius University · LTKU Leuven · BEUniversitätsklinikum Tübingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the present study is to identify microRNAs (miRs) with high potential to be used as biomarkers in plasma and/or serum to clinically diagnose, or provide accurate prognosis for survival in, patients with atherosclerosis, coronary artery disease, and acute coronary syndrome (ACS). A systematic search of published original research yielded a total of 72 studies. After review of the risk of bias of the published studies, according to Cochrane Collaboration and the QUADUAS Group standards, 19 studies were selected. Overall 52 different miRs were reported. In particular, miR-133a/b (5 studies), miR-208a/b (6 studies), and miR-499 (7 studies) were well studied and found to be significant diagnostic and/or prognostic markers across different cardiovascular disease progression stages. miR-1 and miR-145b are potential biomarkers of ACS; miR-1 with higher sensitivity for all acute myocardial infarction (AMI), and miR-145 for STEMI and worse outcome of AMI. But when miRs were studied across different ACS study populations, patients had varying degrees of coronary stenosis, which was identified as an important confounder that limited the ability to quantitatively pool the study results. The identified miRs were found to regulate endothelial function and angiogenesis (miR-1, miR-133), vascular smooth muscle cell differentiation (miR-133, miR-145), communication between vascular smooth muscle and endothelial cell to stabilize plaques (miR-145), apoptosis (miR-1, miR-133, miR-499), cardiac myocyte differentiation (miR-1, miR-133, miR-145, miR-208, miR-499), and to repress cardiac hypertrophy (miR-133). Their role in these processes may be explained by regulation of shared RNA targets such as cyclin-dependent kinase inhibitor 1A (or p21), ETS proto-oncogene 1, fascin actin-bundling protein 1, hyperpolarization-activated cyclic nucleotide-gated potassium channel 4, insulin-like growth factor 1 receptor LIM and SH3 protein 1, purine nucleoside phosphorylase, and transgelin 2. These mechanistic data further support the clinical relevance of the identified miRs. miR-1, miR-133a/b, miR-145, miR-208a/b, and miR-499(a) in plasma and/or serum show some potential for diagnosis of cardiovascular disease. However, biased selection of miRs in most studies and unexplained contrasting results are major limitations of current miR research. Inconsistencies need to be addressed in order to definitively identify clinically useful miRs. Therefore, this paper presents important aspects to improve future miR research, including unbiased selection of miRs, standardization/normalization of reference miRs, adjustment for patient comorbidities and medication, and robust protocols of data-sharing plans that could prevent selective publication and selective reporting of miR research outcomes.

Indexed as

Genetic Predisposition to DiseaseAnimalsBiomarkersCardiovascular DiseasesCyclin-Dependent KinasesHumansMicroRNAsProto-Oncogene MasRiskBiomarkersCyclin-Dependent KinasesMAS1 protein, humanMicroRNAsProto-Oncogene MasAcute coronary syndromeBiomarkersCirculating microRNACoronary artery disease(Disease) Progression

Identifiers

PMID27357636
PMCPMC4996262
OpenAlexW2463628819

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.