Evidence map›Paper›PMID 38880872›Full record

ArticleBMC cardiovascular disorders2024

Identification and verification of circRNA biomarkers for coronary artery disease based on WGCNA and the LASSO algorithm.

Qilong Zhong, Shaoyue Jin, Zebo Zhang, Haiyan Qian, Yanqing Xie, Peiling Yan, Wenming He, Lina Zhang

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC cardiovascular disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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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

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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

3 citing papers in PubMed.

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4 · The record

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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

8 authors.

Qilong ZhongGeneral Practice Department, The Seventh Hospital of Ningbo, Ningbo, Zhejiang, China.
Shaoyue JinSchool of Public Health, Health Science Center, Ningbo University, Ningbo, Zhejiang, China.
Zebo ZhangSchool of Public Health, Health Science Center, Ningbo University, Ningbo, Zhejiang, China.
Haiyan QianSchool of Public Health, Health Science Center, Ningbo University, Ningbo, Zhejiang, China.
Yanqing XieInstitute of Geriatrics, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Peiling YanGeneral Practice Department, The Seventh Hospital of Ningbo, Ningbo, Zhejiang, China.
Wenming HeInstitute of Geriatrics, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China. fyhewenming@nbu.edu.cn.
Lina ZhangZhejiang Key Laboratory of Pathophysiology, Health Science Center, Ningbo University, Ningbo, Zhejiang, China. zhanglina@nbu.edu.cn.

Funding

Key R & D Program of Zhejiang 2023C04017Natural Science Foundation of Ningbo Municipality 2023-144Science and technology cooperation project of "Vanguard" "Leading goose" of Zhejiang Province ZX2023000225Zhejiang Key Laboratory of Pathophysiology 202303
6 · The paper itself

Abstract

backgroundThe role of circular RNAs (circRNAs) as biomarkers of coronary artery disease (CAD) remains poorly explored. This study aimed to identify and validate potential circulating circRNAs as biomarkers for the diagnosis of CAD.

methodsThe expression profile of circRNAs associated with CAD was obtained from Gene Expression Omnibus (GEO) database. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operation (LASSO) were employed to identify CAD-related hub circRNAs. The expression levels of these hub circRNAs were validated using qRT-PCR in blood samples from 100 CAD patients and 100 controls. The diagnostic performance of these circRNAs was evaluated through logistic regression analysis, receiver operator characteristic (ROC) analysis, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Functional enrichment analyses were performed to predict the possible mechanisms of circRNAs in CAD.

resultsA total of ten CAD-related hub circRNAs were identified through WGCNA and LASSO analysis. Among them, hsa_circ_0069972 and hsa_circ_0021509 were highly expressed in blood samples of CAD patients, and they were identified as independent predictors after adjustment for relevant confounders. The area under the ROC curve for hsa_circ_0069972 and hsa_circ_0021509 was 0.760 and 0.717, respectively. The classification of patients was improved with the incorporation of circRNAs into the clinical model composed of conventional cardiovascular risk factors, showing an IDI of 0.131 and NRI of 0.170 for hsa_circ_0069972, and an IDI of 0.111 and NRI of 0.150 for hsa_circ_0021509. Functional enrichment analyses revealed that the hsa_circ_0069972-miRNA-mRNA network was enriched in TGF-β、FoxO and Hippo signaling pathways, while the hsa_circ_0021509-miRNA-mRNA network was enriched in PI3K/Akt and MAPK signaling pathways.

conclusionHsa_circ_0069972 and hsa_circ_0021509 were identified by integrated analysis, and they are highly expressed in CAD patients. They may serve as novel biomarkers for CAD.

Indexed as

AlgorithmsCoronary Artery DiseaseDatabases, GeneticGene Expression ProfilingGene Regulatory NetworksPredictive Value of TestsRNA, CircularAgedBiomarkersCase-Control StudiesFemaleGenetic MarkersHumansMaleMiddle AgedReproducibility of ResultsBiomarkersGenetic MarkersRNA, CircularBiomarkerCircular RNACoronary artery diseaseLASSOWGCNA

Identifiers

PMID38880872
PMCPMC11181640

What Socratic holds

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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 Socratic graph.