Evidence map›Paper›PMID 40069305›Full record

ArticleScientific reports2025

An exploratory study of high-throughput transcriptomic analysis reveals novel mRNA biomarkers for acute myocardial infarction using integrated methods.

Fei Huang, Zongning Chen, Binjie Tan, Rong He, Xiaoyu Zhang, Yali Chen, Jinsong Gao, Bo Sun

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

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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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Fei HuangMedical School, People's Hospital of Lijiang, Kunming University of Science and Technology, Kunming, China.
Zongning ChenMedical School, People's Hospital of Lijiang, Kunming University of Science and Technology, Kunming, China.
Binjie TanMedical School, Kunming University of Science and Technology, Kunming, China.
Rong HeMedical School, Kunming University of Science and Technology, Kunming, China.
Xiaoyu ZhangMedical School, Kunming University of Science and Technology, Kunming, China.
Yali ChenMedical School, Kunming University of Science and Technology, Kunming, China.
Jinsong GaoMedical School, Kunming University of Science and Technology, Kunming, China.
Bo SunMedical School, Kunming University of Science and Technology, Kunming, China. 20130136@kust.edu.cn.

Funding

Kunming University of Science and Technology & People's Hospital of Lijiang Joint Special Project on Medical research KUST-LJ2022002ZNational Natural Science Foundation of China 81903611Project for Leading Academics and Technologists among Youth and Middle-aged in Lijiang LJ20220203Xingli Talented Youth Program LJ20220204
6 · The paper itself

Abstract

Acute myocardial infarction (AMI) is a major contributor to cardiovascular-related mortality, and early diagnosis is crucial for effective treatment and better outcomes. While several biomarkers have been explored for AMI, there remains a need for reliable, non-invasive biomarkers that can accurately differentiate AMI patients from healthy individuals. This study aims to identify potential mRNA biomarkers in peripheral blood that could aid in the diagnosis and monitoring of AMI. We performed transcriptomic analysis of blood samples from 81 individuals, including 16 healthy controls, 58 AMI patients, and 7 post-treated AMI individuals. Through a combination of Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA), random forest (RF), Weighted Gene Co-expression Network Analysis (WGCNA), and LASSO regression, we identified mRNA markers that are significantly correlated with AMI. Specifically, the mRNA expressions of ANKRD52, ART1, NRP2, and PPP1R15A were elevated in AMI patients, whereas BAIAP2L1 and CCNE1 were downregulated. However, while these mRNA biomarkers show potential for distinguishing AMI patients from healthy individuals, further studies are needed to confirm their clinical applicability.

Indexed as

BiomarkersGene Expression ProfilingMyocardial InfarctionRNA, MessengerTranscriptomeAgedCase-Control StudiesFemaleGene Regulatory NetworksHumansMaleMiddle AgedBiomarkersRNA, MessengerAcute myocardial infarction (AMI)Diagnostic screeningMachine learningmRNA biomarkers

Identifiers

PMID40069305
PMCPMC11897311

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.