Background: Atherosclerosis (AS) is a major cause of cardiovascular diseases and neutrophil extracellular traps (NETs) may be actively involved in the development of atherosclerosis. Identifying key biomarkers in this process is essential for developing targeted treatments for AS.

Methods: We performed bioinformatics analysis using a NETosis-related gene (NRGs) set and three AS datasets (GSE100927, GSE21545, and GSE159677). Differential expression analysis and machine learning techniques (random forest and SVM-RFE) were used to screen for key NRGs. Functional enrichment analysis was conducted using GO and KEGG pathways. The expression and role of PTAFR and NETs in the mouse AS model were validated through histology, immunofluorescence, flow cytometry, and Western blot analysis. The regulatory relationship between PTAFR and NETs was confirmed by siRNA and antagonist intervention targeting PTAFR.

Results: We identified 24 differentially expressed NRGs in AS. Random Forest and SVM-RFE analyses highlighted PTAFR as a key gene. Prognostic analysis revealed PTAFR significantly impacts ischemic events in AS patients. WB and immunofluorescence confirmed increased levels of NETs and PTAFR in the mouse AS model. Single-cell analysis, flow cytometry, and immunofluorescence revealed that PTAFR is primarily distributed in macrophages and neutrophils. Cellular experiments further confirmed that PTAFR regulates NETs formation.

Conclusion: PTAFR is an important regulatory factor for NET formation in AS, influencing the progression and prognosis of atherosclerosis. Targeting PTAFR may provide new therapeutic strategies for AS.

Download full-text PDF

Source
http://dx.doi.org/10.1186/s40246-024-00708-3DOI Listing

Publication Analysis

Top Keywords

ptafr
9
random forest
8
forest svm-rfe
8
ptafr nets
8
mouse model
8
flow cytometry
8
revealed ptafr
8
analysis
6
nets
5
identifying ptafr
4

Similar Publications

Background: Atherosclerosis (AS) is a major cause of cardiovascular diseases and neutrophil extracellular traps (NETs) may be actively involved in the development of atherosclerosis. Identifying key biomarkers in this process is essential for developing targeted treatments for AS.

Methods: We performed bioinformatics analysis using a NETosis-related gene (NRGs) set and three AS datasets (GSE100927, GSE21545, and GSE159677).

View Article and Find Full Text PDF
Article Synopsis
  • SARS-CoV-2 infection severity may be influenced by genetic factors, particularly through the role of platelets and coagulation markers in severe COVID-19 cases.
  • A study of 43 unvaccinated hospitalized COVID-19 patients found significantly higher expression of the platelet-activating factor receptor (PTAFR) and platelet factor 4 (PF4) compared to healthy individuals.
  • The findings suggest that hyperexpression of these genes could serve as important biomarkers for assessing the risk of complications in COVID-19 patients, aiding in personalized treatment approaches.
View Article and Find Full Text PDF

Background: Pro-inflammatory processes triggered by the accumulation of extracellular amyloid beta (Aβ) peptides are a well-described pathology in Alzheimer's disease (AD). Activated astrocytes surrounding Aβ plaques contribute to inflammation by secreting proinflammatory factors. While astrocytes may phagocytize Aβ and contribute to Aβ clearance, reactive astrocytes may also increase Aβ production.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!