1. Academic Validation
  2. Identifying PTAFR as a hub gene in atherosclerosis: implications for NETosis and disease progression

Identifying PTAFR as a hub gene in atherosclerosis: implications for NETosis and disease progression

  • Hum Genomics. 2024 Dec 21;18(1):139. doi: 10.1186/s40246-024-00708-3.
Chaowen Ye # 1 Yunli Zhao # 1 2 Wei Yu 1 Rongzhong Huang 3 4 5 Tianyang Hu 6 7
Affiliations

Affiliations

  • 1 Precision Medicine Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • 2 Chongqing Municipality Clinical Research Center for Geriatrics and Gerontology, Chongqing, China.
  • 3 Precision Medicine Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China. rzhuang@hospital.cqmu.edu.cn.
  • 4 Chongqing Municipality Clinical Research Center for Geriatrics and Gerontology, Chongqing, China. rzhuang@hospital.cqmu.edu.cn.
  • 5 , 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China. rzhuang@hospital.cqmu.edu.cn.
  • 6 Precision Medicine Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China. hutianyang@stu.cqmu.edu.cn.
  • 7 , 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China. hutianyang@stu.cqmu.edu.cn.
  • # Contributed equally.
Abstract

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.

Keywords

Atherosclerosis; Cardiovascular diseases; NETosis; NETs; PTAFR.

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