Evidence map›Paper›PMID 39080630›Full record

ArticleCardiovascular diabetology2024

Identification of plasma miR-4505, miR-4743-5p and miR-4750-3p as novel diagnostic biomarkers for coronary artery disease in patients with type 2 diabetes mellitus: a case-control study.

Joanna Szydełko, Marcin Czop, Alicja Petniak, Monika Lenart-Lipińska, Janusz Kocki, Tomasz Zapolski, Beata Matyjaszek-Matuszek

Abstract read
In one paragraph

Article in Cardiovascular diabetology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

  1. Pooled it
  2. Article
  3. Observational
  4. Article
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  6. Review
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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.

Joanna SzydełkoDepartment of Endocrinology, Diabetology and Metabolic Diseases, Medical University of Lublin, Jaczewskiego 8, 20-090, Lublin, Poland. jszydelko@interia.pl.
Marcin CzopDepartment of Clinical Genetics, Medical University of Lublin, Radziwillowska 11, 20-080, Lublin, Poland.
Alicja PetniakDepartment of Clinical Genetics, Medical University of Lublin, Radziwillowska 11, 20-080, Lublin, Poland.
Monika Lenart-LipińskaDepartment of Endocrinology, Diabetology and Metabolic Diseases, Medical University of Lublin, Jaczewskiego 8, 20-090, Lublin, Poland.
Janusz KockiDepartment of Clinical Genetics, Medical University of Lublin, Radziwillowska 11, 20-080, Lublin, Poland.
Tomasz ZapolskiDepartment of Cardiology, Medical University of Lublin, Jaczewskiego 8, 20-090, Lublin, Poland.
Beata Matyjaszek-MatuszekDepartment of Endocrinology, Diabetology and Metabolic Diseases, Medical University of Lublin, Jaczewskiego 8, 20-090, Lublin, Poland.

Funding

Uniwersytet Medyczny w Lublinie DS 358/2020-2022Uniwersytet Medyczny w Lublinie PBsd 120/2021-2022
6 · The paper itself

Abstract

backgroundType 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) are commonly coexisting clinical entities with still growing incidence worldwide. Recently, circulating microRNAs (miRNAs) have emerged as novel molecular players in cardiometabolic diseases. This study aimed to identify a specific miRNA signature as a candidate biomarker for CAD in T2DM and to delineate potential miRNA-dependent mechanisms contributing to diabetic atherosclerosis.

methodsA total of 38 plasma samples from T2DM patients with and without CAD, CAD patients and healthy controls were collected for expression profiling of 2,578 miRNAs using microarrays. To investigate the regulatory role of differentially expressed (DE)-miRNA target genes, functional annotation and pathway enrichment analyses were performed utilizing multiple bioinformatics tools. Then, protein-protein interaction networks were established leveraging the STRING database in Cytoscape software, followed by cluster analysis and hub gene identification. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was carried out for microarray data validation in the larger replication cohort of 94 participants. Receiver operating characteristic analysis was applied to evaluate the diagnostic values of miRNAs. Multivariate logistic regression analysis was used to develop miRNA-based diagnostic models.

resultsIn the discovery stage, overexpression of hsa-miR-4505, hsa-miR-4743-5p, hsa-miR-6846-5p, and down-regulation of hsa-miR-3613-3p, hsa-miR-4668-5p, hsa-miR-4706, hsa-miR-6511b-5p, hsa-miR-6750-5p, hsa-miR-4750-3p, hsa-miR-320e, hsa-miR-4717-3p, hsa-miR-7850-5p were detected in T2DM-CAD patients. The DE-miRNA target genes were significantly enriched in calcium ion binding, regulation of actin cytoskeleton, and gene expression. hsa-miR-4505, hsa-miR-4743-5p, and hsa-miR-4750-3p were found to be involved in fatty acid metabolism, leukocyte transendothelial migration, and neurotrophin signaling pathway. Dysregulation of hsa-miR-4505, hsa-miR-4743-5p, and hsa-miR-4750-3p in T2DM-CAD patients compared with T2DM subjects and controls (all p < 0.001) was further confirmed by RT-qPCR. All validated miRNAs demonstrated good discriminatory values for T2DM-CAD (AUC = 0.833-0.876). The best performance in detecting CAD in T2DM was achieved for a combination of three miRNAs (AUC = 0.959, 100% sensitivity, 86.67% specificity).

conclusionsOur study revealed a unique profile of plasma-derived miRNAs in T2DM patients with CAD. Potential miRNA-regulated pathways were also identified, exploring the underlying pathogenesis of CAD in T2DM. We developed a specific three-miRNA panel of hsa-miR-4505, hsa-miR-4743-5p and hsa-miR-4750-3p, that could serve as a novel non-invasive biomarker for CAD in patients with T2DM.

Indexed as

Circulating MicroRNACoronary Artery DiseaseDiabetes Mellitus, Type 2Gene Expression ProfilingGene Regulatory NetworksMicroRNAsPredictive Value of TestsProtein Interaction MapsAgedBiomarkersCase-Control StudiesComputational BiologyFemaleGenetic MarkersHumansMaleBiomarkersCirculating MicroRNAGenetic MarkersMicroRNAsMIRN4505 microRNA, humanBiomarkerCoronary artery diseasemiRNAmiRNA expression profilingType 2 diabetes mellitus

Identifiers

PMID39080630
PMCPMC11287982

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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.