Evidence map›Paper›PMID 36182975›Full record

ArticleGenes and immunity2022

Identification of an 11 immune-related gene signature as the novel biomarker for acute myocardial infarction diagnosis.

Nan Zhang, Bingquan Zhou, Su Tu

Abstract read
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In one paragraph

Article in Genes and immunity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

3 authors.

Nan ZhangDepartment of Emergency, The Affiliated WuXi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu, 214000, China.
Bingquan ZhouDepartment of Emergency, The Affiliated WuXi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu, 214000, China.
Su TuDepartment of Emergency, The Affiliated WuXi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu, 214000, China. tssujfylvcan3@163.com.ORCID 0000-0002-0971-7927

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explored the valuable immune gene signature for diagnosis of acute myocardial infarction (AMI). Three training gene expression datasets (GSE48060, GSE34198, and GSE97320) and one validation dataset (GSE109048) were downloaded from GEO database. The differentially infiltrated immune cells were analyzed by CIBERSORT. The immune genes were screened by WGCNA with differential immune cells as phenotype. Differentially expressed genes were analyzed in training datasets, followed by differential immune gene identification. The immune genes with diagnostic value were filtered by univariate regression analysis and LASSO model construction. ROC curve evaluated the diagnostic value of this model. A total of 304 differential immune genes were obtained, which were closely related to immune response-related pathways. An 11-gene signature (ADAMTS1, CNN2, DHRS13, DUSP1, FASLG, GNPTAB, NARF, PHC2, RAB7A, VNN3, and YIPF3) was filtered to be diagnostic biomarker for AMI (AUC = 0.805) and validated in GSE109048 dataset (AUC = 0.608). Based on the diagnostic model, high- and low-risk groups showed ten differential immune cells (such as T cells gamma delta, Macrophages M0, and Neutrophils) and differentially activated immune pathways (such as Antigen_Processing_and_Presentation and Cytokine_Receptors). PHC2 showed the highest positive correlation with Neutrophils and Cytokine_Receptors. The 11-gene signature could be served as a novel biomarker for the presence of AMI.

Indexed as

Gene Expression ProfilingMyocardial InfarctionBiomarkersCytokinesHumansBiomarkersCytokines

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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.