Silent Myocardial Infarction is a biologically biased phenotype shaped by immune-metabolic and neurogenic modulation, for which a tiered biomarker and imaging approach supports risk stratification.
A tiered approach of biomarker screening followed by imaging is proposed for the early diagnosis and risk stratification of silent myocardial infarction.
Silent Myocardial Infarction (SMI) is a clinically underrecognized phenotype along the myocardial infarction continuum that progresses without anginal symptoms. Its prevalence in diabetes, chronic kidney disease, and the elderly reflects contributions from neuropathy, autonomic dysfunction, and neurogenic silencing. Emerging evidence indicates that SMI reflects a biologically biased phenotype within the myocardial infarction continuum shaped by immune-metabolic and neurogenic modulation rather than representing a distinct entity. Biomarkers such as sCD36, galectin-3, sST2, and GDF-15 capture fibrotic and inflammatory remodeling, while NETosis-linked markers (CitH3, MPO-DNA) highlight thrombo-inflammation. Lipidomic stressors, including ceramides and β-hydroxybutyrate, further define ischemic burden. Spatial omics and single-cell analyses identify enrichment of immune-regulatory macrophage programs associated with restrained inflammation without establishing the causality for symptom absence. A tiered approach-biomarker screening followed by imaging-supports risk stratification. This review integrates mechanistic and translational insights, proposing a pragmatic framework for early diagnosis and biologically aligned treatment of SMI.
Pethani et al. (Thu,) conducted a review in Silent Myocardial Infarction. Silent Myocardial Infarction is a biologically biased phenotype shaped by immune-metabolic and neurogenic modulation, for which a tiered biomarker and imaging approach supports risk stratification.