Evidence map›Paper›PMID 29179461›Full record

ArticleOncotarget2017

Differential expression profiles of long non-coding RNAs as potential biomarkers for the early diagnosis of acute myocardial infarction.

Ling Li, Yingying Cong, Xueqin Gao, Yini Wang, Ping Lin

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.0field-weighted citation impact, top 28% 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

19 citing papers in PubMed, 26 citations in OpenAlex.

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  10. Long Noncoding RNAs in Myocardial Ischemia-Reperfusion Injury.Oxidative medicine and cellular longevity · 2021
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  17. Circulating Long Noncoding RNA LIPCAR Acts as a Novel Biomarker in Patients with ST-Segment Elevation Myocardial Infarction.Medical science monitor : international medical journal of experimental and clinical research · 2018
    Article
  18. 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

5 authors at 2 institutions in 2 countries.

Ling LiDepartment of Cardiology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Yingying CongDepartment of Biological Sciences and Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada.
Xueqin GaoDepartment of Cardiology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Yini WangDepartment of Cardiology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Ping LinSchool of Nursing, Harbin Medical University, Harbin, China.
Harbin Medical University · CNSecond Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myocardial infarction (AMI) is a major cause of morbidity and mortality worldwide. The early diagnosis of AMI is crucial for deciding the course of treatment and saving lives. Long non-coding RNAs (lncRNAs) are recently discovered ncRNA class and their dysregulated expression has been implicated in cardiovascular diseases. In this study, we analyzed lncRNA expression pattern by using two microarray datasets of AMI and healthy samples from the Gene Expression Omnibus (GEO) database and tried to identify novel AMI-related lncRNAs and investigate the predictive roles of lncRNAs in the early diagnosis of AMI. From the discovery cohort, 11 differentially expressed lncRNAs were identified as candidate biomarkers that were validated in the discovery cohort, internal cohort and an independent cohort, respectively. Hierarchical clustering analysis suggested that the expression pattern of these 11 candidate lncRNA biomarkers was closely associated with disease status of samples. Then a lncRNA risk classifier was developed by integrating expression value of 11 differentially expressed lncRNAs using support vector machine (SVM) algorithm. The results of leaving one out cross-validation (LOOCV) suggested that the lncRNA risk classifier has a good discrimination between AMI patients and healthy samples with the area under ROC curve (AUC) of 0.955, 0.92 and 0.701 in three cohorts, respectively. Functional enrichment analysis suggested that these 11 candidate lncRNA biomarkers might be involved in inflammation- and immune-related biological processes. Our study indicates the potential roles in the early diagnosis of AMI and will improve our understanding of the molecular mechanism of the occurrence and recurrence of AMI.

Indexed as

acute myocardial infarctionbiomarkersearly diagnosisexpression profileslong non-coding RNAs

Identifiers

PMID29179461
PMCPMC5687631
OpenAlexW2743458198

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.