Evidence map›Paper›PMID 40593091›Full record

ArticleScientific reports2025

Integrative in Silico and in vitro validation suggest LINC00963 and SNHG15 as candidate biomarkers for coronary artery disease.

Mohammadreza Saberiyan, Parisa Noorabadi, Ozra Kahourian, Ahmad Golestanifar, Negar Jafari, Venus Shahabi Rabori, Pegah Mousavi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

7 authors.

Mohammadreza Saberiyan *Department of Medical Genetics, Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.ORCID https://orcid.org/0000-0001-6343-8518
Parisa Noorabadi *Department of Internal Medicine, School of Medicine, Urmia University of Medical sciences, Urmia, Iran.ORCID https://orcid.org/0000-0002-3688-6443
Ozra KahourianDepartment of Cardiology, School of Medicine, Urmia University of Medical sciences, Urmia, Iran.ORCID https://orcid.org/0009-0009-4072-1543
Ahmad GolestanifarDepartment of Medical Genetics, Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.ORCID https://orcid.org/0000-0001-5150-6018
Negar JafariDepartment of Cardiology, School of Medicine, Urmia University of Medical sciences, Urmia, Iran. jnegar94@gmail.com.ORCID https://orcid.org/0000-0002-6249-2587
Venus Shahabi RaboriDepartment of Cardiology, School of Medicine, Urmia University of Medical sciences, Urmia, Iran. jasmin_vsh@yahoo.com.ORCID https://orcid.org/0009-0000-8929-8381
Pegah MousaviMolecular Medicine Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran. pegahmousavi2017@gmail.com.ORCID https://orcid.org/0000-0002-5654-7561

Funding

Molecular Medicine Research Center, Hormozgan University of Medical Sciences 4030313
6 · The paper itself

Abstract

Despite notable advancements in prevention, medication, and treatment approaches, coronary artery disease (CAD) remains a significant challenge for healthcare systems and the economy. In relation to CAD, long non-coding RNAs (lncRNAs) can impact its development by influencing immune responses, affecting the functions of endothelial and vascular smooth muscle cells, and modifying lipid metabolism. Through the analysis of the GEO dataset (GSE42148), we identified differentially expressed genes (DEGs) and lncRNAs (DELs) in CAD patients. We performed functional enrichment and pathway analyses to clarify the roles of these DEGs. To investigate the interactions between DEGs and DELs, we created the lncRNA-mRNA interaction network. To investigate the interactions between DEGs and DELs, we constructed an lncRNA-mRNA interaction network. Candidate lncRNAs were validated by real-time PCR using peripheral blood from CAD patients. Our in vitro study confirmed that LINC00963 and SNHG15 were upregulated in CAD patients compared to the control group. Notably, LINC00963 levels were significantly elevated in patients with a positive family history, hyperlipidemia, hypertension, and diabetes, while SNHG15 expression was higher in smokers. Additionally, a significant negative correlation was found between the expressions of LINC00963 and SNHG15 and the age of the individuals. ROC curve analysis indicated that both lncRNAs have high sensitivity and specificity as biomarkers. Furthermore, this study suggests that LINC00963 and SNHG15 could serve as valuable markers for the early detection of CAD, particularly in younger individuals. It is proposed that these lncRNAs are associated with inflammatory conditions in CAD. Overall, LINC00963 and SNHG15 may act as promising early detection markers for CAD based on bioinformatics and peripheral blood-based validation.

Indexed as

Coronary Artery DiseaseRNA, Long NoncodingBiomarkersComputational BiologyComputer SimulationFemaleGene Expression ProfilingGene Regulatory NetworksHumansMaleMiddle AgedRNA, MessengerROC CurveBiomarkersRNA, Long NoncodingRNA, MessengerBioinformatics analysisCADLINC00963LncRNA-mRNAMicroarraySNHG15

Identifiers

PMID40593091
PMCPMC12215653

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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.