Identification and analysis of diagnostic senescence-related gene signatures for acute myocardial infarction based on multi-omics data and machine learning - Summary - MDSpire
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Identification and analysis of diagnostic senescence-related gene signatures for acute myocardial infarction based on multi-omics data and machine learning
To identify AMI-associated senescence-related genes (SRGs) and develop multi-dimensional models for diagnostic evaluation and patient stratification.
Key Findings:
Thirteen AMI-associated SRGs were identified.
Four genes (FOS, SOD2, MXD1, GRN) showed consistent diagnostic relevance.
The four-gene diagnostic model achieved an AUC of 0.808.
Patient stratification revealed a low-senescence group with anti-inflammatory cells and a high-senescence group with pro-inflammatory neutrophil infiltration.
The senescence score correlated moderately with neutrophil infiltration.
Interpretation:
The study identifies candidate AMI-associated senescence-related biomarkers and establishes preliminary models for AMI diagnosis and stratification, highlighting the role of neutrophil-enriched inflammatory responses in AMI.
Limitations:
The study primarily focuses on transcriptomic data, which may not fully capture the complexity of cellular senescence.
Further validation in larger cohorts is needed to confirm the findings.
Conclusion:
The findings provide a framework for future studies on senescence-related pathways in personalized AMI management.
