Evidence map›Paper›PMID 39308815›Full record

ArticlePeerJ2024

Comprehensive analysis of macrophage-associated inflammatory genes in AMI based on bulk combined with single-cell sequencing data.

Xugang Kong, Guangjun Jin

Abstract read
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Xugang KongDepartment of Cardiology, Xiasha Campus, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Guangjun JinMedical Department, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Previous studies have highlighted the crucial role of macrophages in the post-acute myocardial infarction (AMI) inflammatory response. This study specifically focused on investigating macrophage-related targets involved in the inflammatory response after AMI. Methods: Bioinformatics methods were applied for identifying differentially expressed genes (DEGs) in datasets GSE163465, GSE236374, and GSE183272 obtained from the Gene Expression Omnibus (GEO) database. Communication analysis was conducted to analyze macrophages in AMI. Subsequent analyses encompassed functional enrichment analysis of Co-DEGs using Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG). Gene set variation analysis (GSVA) and immune infiltration analysis were carried out for screening key genes. Validation of the bioinformatics analysis results involved original and GSE114695 datasets, supported by quantitative real time polymerase chain reaction (qRT-PCR). Animal experiments confirmed the upregulation of Saa3, Acp5, and Fcgr4 genes in AMI mouse myocardial tissues. Results: A total of 80 and 1,907 DEGs were respectively identified by analyzing scRNA-seq and bulk RNA-seq data. The overlapping Co-DEGs were found to be closely associated with inflammation-associated pathways, specifically the PI3K-Akt-mTOR pathway. Screening based on GSVA scores and macrophage-associated scores highlighted four key genes (Saa3, Ms4a4c, Acp5, and Fcgr4). Immunoinfiltration analysis revealed their close association with macrophages. Dataset validation corroborated these findings. Experimental validation focused on Saa3, Ms4a4c, Acp5, and Fcgr4, demonstrating the upregulation of their expression in cardiac macrophages in the AMI group, consistent with previous reports. Conclusion: This study provides new perspectives on AMI treatment. In addition, Saa3, Acp5, and Fcgr4 exhibit potential as biomarkers for improving cardiac repair and slowing down the development of heart failure after AMI.

Indexed as

MacrophagesMyocardial InfarctionSingle-Cell AnalysisAnimalsComputational BiologyGene Expression ProfilingGene OntologyInflammationMaleMiceAcute myocardial infarctionBioinformatics analysisInflammationMacrophageSingle-cell sequencing

Identifiers

PMID39308815
PMCPMC11416078

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.