Identification of biomarkers associated with M1 macrophages in the ST-segment elevation myocardial infarction through bioinformatics and machine learning approaches DOI Creative Commons
Huiying Li,

Qiwei Zhu,

Weimin Wang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 1, 2025

ST-segment elevation myocardial infarction (STEMI) is considered a critical cardiac condition with poor prognosis. Shortly after STEMI occurs, the increased number of circulating leukocytes including macrophages can lead to accumulation more cells in myocardium, affecting immune microenvironment. Identifying serum biomarkers associated infiltration important for diagnosing and treating STEMI. In this work, we aimed use integrated bioinformatics machine learning methods identify new biomarkers. First, candidate genes closely M1 macrophage were obtained using limma package, CIBERSORTx weighted gene coexpression network analysis (WGCNA), protein‒protein interaction (PPI) networks from GSE59867 dataset, which comprises peripheral blood mononuclear cell (PBMC) samples. The patients subsequently stratified into subtypes ConsensusClusterPlus package. Furthermore, methods, identified AKT3, GJC2, HMGCL RBM17 as greatest potential be during acute phase Finally, expression profile diagnostic value four feature validated GSE62646 datasets 24 real-time PCR. This study revealed logically comprehensively that RBM17, are derived PBMCs, could enhance accuracy diagnosis might provide effective treatment options patients.

Language: Английский

Cardiac Macrophages Promote Polarization of Macrophages toward M2 Phenotype to Improve Myocardial Remodeling via NGAL after Myocardial Infarction DOI
Donghui Shen,

Jiabing Chen

Cell Biochemistry and Biophysics, Journal Year: 2025, Volume and Issue: unknown

Published: March 26, 2025

Language: Английский

Citations

0
Identification of biomarkers associated with M1 macrophages in the ST-segment elevation myocardial infarction through bioinformatics and machine learning approaches DOI Creative Commons
Huiying Li,

Qiwei Zhu,

Weimin Wang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 1, 2025

ST-segment elevation myocardial infarction (STEMI) is considered a critical cardiac condition with poor prognosis. Shortly after STEMI occurs, the increased number of circulating leukocytes including macrophages can lead to accumulation more cells in myocardium, affecting immune microenvironment. Identifying serum biomarkers associated infiltration important for diagnosing and treating STEMI. In this work, we aimed use integrated bioinformatics machine learning methods identify new biomarkers. First, candidate genes closely M1 macrophage were obtained using limma package, CIBERSORTx weighted gene coexpression network analysis (WGCNA), protein‒protein interaction (PPI) networks from GSE59867 dataset, which comprises peripheral blood mononuclear cell (PBMC) samples. The patients subsequently stratified into subtypes ConsensusClusterPlus package. Furthermore, methods, identified AKT3, GJC2, HMGCL RBM17 as greatest potential be during acute phase Finally, expression profile diagnostic value four feature validated GSE62646 datasets 24 real-time PCR. This study revealed logically comprehensively that RBM17, are derived PBMCs, could enhance accuracy diagnosis might provide effective treatment options patients.

Language: Английский

Citations

0